Extant benthic Foraminifera from two bays along the SW coast of South Africa, with a
comment about their use as indicators of pollution.
By
Rashieda Toefy
Submitted in fulfillment of the requirements for the degree
In the Faculty of Science
At the University of the Western Cape
October 2010
Supervisor: Professor Mark J. Gibbons
This thesis is dedicated to my family.
Seraj and children Rafeeq, Muneeb and Imra and
my mother Gafsa and late father, Achmat Rashied Domingo
ii
Acknowledgements
There are many people I need to thank in my quest to complete this degree. First and
foremost is my supervisor Prof. Mark Gibbons. I am extremely grateful that I have been guided
by such a brilliant scientist who knows so much about everything. I could not have asked for a
better supervisor especially since he was prepared to spend so much time commenting on the
thesis. His belief in me has also led me to complete this thesis.
I would like to thank my friend and colleague, Martin Hendricks, for assisting with
sampling and giving up lab space for me. On a more personal note, I want to thank him for
listening to all my moans and groans over coffee. Thank you to Dr Wayne Florence, Dr Gordon
Harkins, Mr Dylan Clarke and Mr Goosain Isaacs for diving and sampling for me. Thanks to the
workshop at UWC for coping with my persistent demand for slides and stubs, it is much
appreciated. Thank you to Basil Julies at UWC’s Electron Microscope Unit for his assistance and
making sure that the SEM was fixed and in working order. Thank you to Mr Lilburne Cyster, for
assisting me with the AA Spectrophotometer and my metal analysis. Funding for the project was
provided by the National Research Foundation. Thanks to Rene Frans for technical assistance.
Most importantly, I would like to thank the people closest to me, my family, who have
stood by me throughout my studies. They have all encouraged me when I was ready to give this
up. My sisters, Adela and Badehria, thank you for all the encouragement to complete and my
brothers, Dawood and Rashaad, for their quiet pride in me. My mother, most importantly, for
being a woman that I could grow up admiring; I can only aspire to her strength and
determination. Although, my father is not there anymore, I would like to thank him for his belief
in me.
I would like to thank my husband, Seraj, for his encouragement when I was too tired to
carry on and for his very vocal pride in me. To my kids, Rafeeq, Muneeb and Imra, you’re the
reason I did this.
iii
Table of Contents
Legends to Figures
v
Legends to tables
viii
Abstract
1
Chapter 1:
General Introduction
Chapter 2:
An examination of the structure and chemistry of sediments in two
study sites along the south west coast of South Africa
Chapter 3:
Chapter 5:
23
The assemblage structure of foraminifera in two study sites along
the south west coast of South Africa
Chapter 4:
4
61
A study linking foraminiferal communities to their environment at
two study sites on the south west coast of South Africa
124
General Conclusions
158
References
165
Appendix:
Appendix 1.1: Species of foraminifera identified by previous studies in South Africa
183
Appendix 2.1: Environmental variables measured in St Helena Bay and Robben Island
sediment samples
208
Appendix 3.1: Abundance of live foraminifera identified in samples collected from
around Robben Island and St Helena Bay
213
Appendix 3.2: Abundance of dead foraminifera identified in Robben Island and
St Helena Bay samples
223
Appendix 3.3: Species richness in some other studies on foraminifera
238
Appendix 3.4: Generic data for all samples from Robben Island and St Helena Bay
240
Appendix 3.5: Total abundance of live foraminifera in the different size classes for all
samples of Robben Island and St Helena Bay
245
Appendix 3.6: The abundance of dead foraminifera in the different size classes for all
samples of Robben Island and St Helena Bay
248
Appendix 4.1: Plates of foraminifera identified in both study sites
252
Appendix 4.2: Elemental Analysis of shells
268
Appendix 4.3: ANOVA of shells of all stations, sites and locations of both Robben Island
and St Helena Bay
274
iv
Legends to Figures
Chapter 1
Figure 1.1:
Map illustrating the position of St Helena Bay and the sampling area. The
direction of the Benguela current relative to the bay and the anticylonic gyre are
also illustrated (adapted from Touratier
Figure 1.2:
., 2003).
Map of Table Bay showing the position of Robben Island and the currents in the
bay (adapted from Van Ieperen, 1971).
Chapter 2
Figure 2.1:
Map of St Helena Bay illustrating the position of the sampling sites (a) as well as
those around the pipeline (b). (SHA to SHI are the pipeline sites and the control
sites are SPA to SPC) (http://maps.google.com).
Figure 2.2:
Map of Robben Island illustrating the position of sampling sites around the
pipeline (RIA to RIE) and the control sites (RIF to RIH)(http://maps.google.com).
Figure 2.3 (a) to (c): Correlations of the percentage total carbon, percentage organic carbon and
percentage total nitrogen using data collected from St Helena Bay by Monteiro &
Roychoudhury (2005). Correlation coDefficients are (a) R = 0.675 (b) R = 0.747
(c) R = 0.919.
Figure 2.4:
The mean grain size (Phi) and the standard error (n = 6) for each of the sampling
stations at Robben Island, RIA to RIE are pipeline stations and RIF to RIH are
control stations, and St Helena Bay, SPA to SPC are control stations and SHA to
SHI are pipeline stations. Refer to Fig. 2.1 and Fig. 2.2 for the location of each
station.
Figure 2.5:
Graph depicting the mean percentage contribution of each sediment size class of
the total sediment weight for each of the stations sampled in Robben Island and St
Helena Bay.
Figure 2.6:
Dendogram representing the cluster analysis of the sediment structure of each
sample in Robben Island and St Helena Bay. These data were log x + 1
transformed and Euclidean distance was used in the analysis. (PRI is the pipeline
stations at Robben Island, CRI is the control stations at Robben Island, CSH is
the control stations of St Helena Bay and PSH refers to the pipeline stations of St
v
Helena Bay. Each of the samples are labelled according to the station and the core
number. Refer to Figs. 2.1 and 2.2 for the location of each station.
Figure 2.7:
Graphs illustrating the means and standard errors of the trace metal concentration
in the sediments at the Robben Island stations as well as the mean for the control
(C) and pipeline (P) sites.
Figure 2.8:
Graphs illustrating the means and standard errors of the trace metal concentration
in the sediments at the sites sampled St Helena Bay as well as the mean for the
control (C) and pipeline (P) sites.
Figure 2.9:
Graphs illustrating the means and standard errors of the trace metal concentration
in the sediments at Robben Island (PRI and CRI) and St Helena Bay (CSH and
PSH), P = pipeline sites and C = control sites.
Figure 2.10:
MDS ordination of the two study areas sampled using all environmental data. The
data were log x+1 transformed and
normalised. Euclidean distance was used to
plot the samples. RI refers to Robben Island and SH to St Helena Bay.
Chapter 3
Figure 3.1:
Species accumulation curves of live foraminifera for St Helena Bay (a), Robben
Island (b) and all samples (c). The MMF Model y = (a*b+c*x^d)/(b+x^d) using
Curve Expert is indicated by the dashed line, dots represent the observed data.
Figure 3.2:
Dendrogram showing the similarity between samples, in terms of the structure of
live foraminiferal assemblages across all study sites and samples (BrayDCurtis
Index). Species data were rootD root transformed and the dendrogram was
produced using GroupDAverage Linkage. (PRI –Pipeline sites Robben Island, CRI
– Control sites Robben Island, CSH – Control sites St Helena Bay and PSH –
Pipeline sites St Helena Bay).
Figure 3.3:
MDS Ordination of all live foraminiferal species. Species data were fourth root
transformed and the MDS was produced using the Bray Curtis similarity index.
(PRI –Pipeline sites Robben Island, CRI – Control sites Robben Island, CSH –
Control sites St Helena Bay and PSH – Pipeline sites St Helena Bay).
vi
Figure 3.4:
The mean and standard error for each of the five dominant genera for each station
in St Helena Bay as well as the pooled results for the control (C) and pipeline (P)
sites.
Figure 3.5:
The mean and standard errors for each of the five dominant genera for Robben
Island as well as the pooled results for the control (C) and pipeline (P) sites.
Figure 3.6:
Graph depicting the percentage contribution of the abundance of each live
foraminiferal size class for each of the stations in St Helena Bay and Robben
Island. The mean data of the foraminiferal size classes for each of the six cores
per station were used.
Figure 3.7:
Dendrogram of the BrayDCurtis similarity index between all sites using the
abundance of live foraminifera divided into the size classes. Data were rootDroot
transformed and the cluster analysis used GroupDAverage linkage. PRI –Pipeline
sites Robben Island, CRI – Control sites Robben Island, CSH – Control sites St
Helena Bay and PSH – Pipeline sites St Helena Bay.
Figure 3.8:
MDS Ordination of the total abundance of live foraminifera of polluted and
control sites in Robben Island and St Helena Bay using Bray Curtis similarity and
fourth root transformation. (PRI –Pipeline sites Robben Island, CRI – Control
sites Robben Island, CSH – Control sites St Helena Bay and PSH – Pipeline sites
St Helena Bay).
Figure 3.9:
Dendrogram of the dead foraminiferal assemblages of each sample from each site
in St Helena Bay and Robben Island. Species data were fourth root transformed
and the dendrogram was produced using the BrayDCurtis Similarity Index with
GroupDAverage Linkage. (PRI –Pipeline sites Robben Island, CRI – Control sites
Robben Island, CSH – Control sites St Helena Bay and PSH – Pipeline sites St
Helena Bay).
Figure 3.10:
MDS Ordination of all dead foraminiferal species. Species data were fourth root
transformed and the MDS was produced using the Bray Curtis similarity index.
PRI –Pipeline sites Robben Island, CRI – Control sites Robben Island, CSH –
Control sites St Helena Bay and PSH – Pipeline sites St Helena Bay.
vii
Figure 3.11:
The percentage contribution of the total of each size class of foraminifera in the
dead assemblages for each station in St Helena Bay and Robben Island. The mean
of each foraminiferal size classmfor each of the samples per station was used.
Figure 3.12:
Dendrogram of the BrayDCurtis similarity index between all sites using the
abundance of dead foraminifera per size classes. Data were rootDroot transformed
and the cluster analysis used GroupDAverage linkage. PRI –Pipeline sites Robben
Island, CRI – Control sites Robben Island, CSH – Control sites St Helena Bay
and PSH – Pipeline sites St Helena Bay.
Figure 3.13:
MDS Ordination of the total abundance of dead foraminifera of polluted and
control sites in Robben Island and St Helena Bay using BrayDCurtis similarity and
fourth root transformation. PRI –Pipeline sites Robben Island, CRI – Control sites
Robben Island, CSH – Control sites St Helena Bay and PSH – Pipeline sites St
Helena Bay.
Chapter 4
Figure 4.1:
MDS Ordination of all measured elements in the analysis of foraminiferal tests.
Data were square root transformed and Euclidean distance was used to produce a
resemblance matrix. CSH – Control sites St Helena Bay; PSH – Pipeline Sites St
Helena Bay. CRI D Control sites Robben Island; PRI – Pipeline Sites Robben
Island.
Figure 4.2:
Results of the NonDparametric, Spearman Rank Order Correlation between the
trace metal concentrations in the sediments and the trace metal concentration in
the tests. Spearman RD values are represented. The red symbols represent Robben
Island samples while the green symbols represent St Helena Bay samples.
Legends to Tables
Chapter 2
Table 2.1:
The following are the results of a oneDWay ANOVA performed on the mean
sediment grain size (Phi) of all cores for each site in Robben Island. For a postD
hoc comparison of means, the Tukey Honest Significant Difference (HSD) Test
was performed to obtain a statistical significance. F (7, 39) = 7.16. Significance at
p < 0.05* after the Bonferroni adjustment.
viii
Table 2.2:
Results of the oneDway ANOVA performed on the mean sediment grain size (Phi)
of all cores of St Helen Bay. Levene’s test for homogeneity of variances did not
show a significant result (p = 0.11). For a postD hoc comparison of means, the
Tukey Honest Significant Difference (HSD) Test was performed to obtain a
statistical significance. F(11, 58) = 8.92. Significance at p < 0.05 *.
Table 2.3:
Results of the oneDway ANOVA performed on the mean sediment grain size (Phi)
of all cores for each of the sampling sites. The Tukey Honest Significant
Difference (HSD) Test postDhoc comparison was performed to obtain a statistical
significance. F(1, 111) = 31.89. Significant at p < 0.05 * after the Bonferroni
adjustment. Pipeline Robben Island (PRI), Control Robben Island (CRI), Control
St Helena Bay (CSH) and Pipeline St Helena Bay (PSH).
Table 2.4:
Results of the percentage total Carbon and the percentage total Nitrogen
measured samples collected from around Robben Island (RIA to RIH) and St
Helena Bay (SPA to SHI), as well as that for the various sites and a mean for the
two study areas.
Table 2.5:
The following represents the oneDway ANOVA performed on the total %
Nitrogen and % Carbon between the study areas (a) and the sites (b). RI refers to
Robben Island and SHB to St Helena Bay; PRI is the pipeline stations at Robben
Island, CRI is the control stations at Robben Island, CSH is the control stations of
St Helena Bay and PSH refers to the pipeline stations of St Helena Bay. The
Tukey Honest Significant Difference postDhoc comparison of means was
performed to obtain a significant value (p < 0.05) * after the Bonferroni
adjustment. F (1, 111).
Table 2.6:
The following tables represent the ANOVA performed on the trace metal
concentrations in the sediments between the sites (a) and the study areas (b). The
Tukey Honest Significant Difference postDhoc comparison of means was
performed to obtain a significant value (p < 0.05) in bold type*. F (1, 111).
Table 2.7:
Results of the NonDparametric, Spearman Rank Order Correlations between all
environmental variables measured showing R Values. Significant RDvalues are at
p < 0.05 after the. Bonferroni adjustment.
ix
Table 2.8:
SIMPER (Similarity Percentage) of the two study areas using all environmental
variables. A resemblance matrix using Euclidean distance was used in the
analysis. Table (a) represents the average similarity between the four groups. The
values in bold represent the environmental variables which contribute most to the
similarity within each group. Table (b) represents the average dissimilarity
between the two study areas and the environmental factors most responsible for
the dissimilarity between the two study areas.
Table 2.9:
SIMPER (Similarity Percentage) of the control and pipeline sites of both sites
using all environmental variables. A resemblance matrix using Euclidean
distance was used in the analysis. The following table represents the average
similarity between the four groups. The values in bold represent the
environmental variables which contribute most to the similarity within each
group.
Chapter 3
Table 3.1:
The dominant species of foraminifera and their percentage of the total numbers, in
samples collected from Robben Island.
Table 3.2:
The dominant species of foraminifera in St Helena Bay samples, as a percentage
of the total abundance.
Table 3.3:
Diversity indices of living foraminifera in samples from Robben Island and St
Helena Bay and the means of the control and pipeline sites. SD total species, J’ –
Pielou’s evenness, H’ – ShannonDWeiner Index of diversity and the abundance/g
sediment.
Table 3.4:
Estimations of the species richness of the live foraminifera using an extrapolation
of an MMF Model: y = (a*b+c*x^d)/(b+x^d) of a plot of species accumulation
per sample.
Table 3.4:
Estimations of the species richness of the live foraminifera using an extrapolation
of an MMF Model: y = (a*b+c*x^d)/(b+x^d) of a plot of species accumulation
per sample.
x
Table 3.5:
NonDparametric statistical estimators of species richness of the live assemblages
from Colwell’s EstimateS program compared with actual species richness and
estimated species richness from the Curve Expert program.
Table 3.6:
The SIMPER procedure in PRIMER between all species of the live assemblages
in all samples of St Helena Bay performed on fourth root transformed data using
the BrayD Curtis similarity matrix. The average similarity percentage of each of
the two groups is in brackets and the species most responsible for determining
community structure within each group is in bold (a). The average dissimilarity
between the two groups is in brackets and the species most responsible for the
dissimilarity is represented in (b).
Table 3.7:
The SIMPER between all live species in all Robben Island samples. The data
were rootDroot transformed and the BrayD Curtis similarity matrix was used to
produce the SIMPER. The average similarity percentage of each of the two
groups is in brackets and the species most responsible for determining community
structure within each group is in bold (a). The average dissimilarity between the
two groups is in brackets and the species most responsible for the dissimilarity is
represented in (b).
Table 3.8:
The SIMPER between all live species in the two study areas, performed on fourth
root transformed data using the BrayD Curtis similarity matrix. The average
similarity percentage of each of the two groups is in brackets and the species most
responsible for determining community structure within each group is in bold (a).
The average dissimilarity between the two groups is in brackets and the species
most responsible for the dissimilarity is represented in (b).
Table 3.9:
Results of the PERMANOVA based on BrayDCurtis similarity of the live species
data for St Helena Bay. Data were fourth root transformed. Each test was
conducted using 998 random permutations.
Table 3.10:
The PERMANOVA based on BrayDCurtis similarity of the live foraminiferal
species from Robben Island samples. Data were fourth root transformed. Each test
was conducted using 998 random permutations.
xi
Table 3.11:
The PERMANOVA based on BrayDCurtis similarity of the live foraminiferal
species data from all samples from Robben Island and St Helena Bay. Data were
fourth root transformed. Each test was conducted using 998 random permutations.
Table 3.12:
The oneDway ANOVA, of the abundance of the dominant genera at the control
and pipeline sites of St Helena Bay, as well as the p values and the result of the
postD hoc comparison of means using the Tukey Honest Significant Difference
(HSD) Test. Significant pDvalues < 0.05 after the Bonferroni adjustment.
Table 3.13:
The oneDway ANOVA, of the abundance of the dominant genera in St Helena
Bay, the result of the postD hoc comparison of means using the Tukey Honest
Significant Difference (HSD) Test. Significant differences were only found
between SPA, SPA & SPC (control sites) and all other sites, no significant
differences were found between pipeline sites and were therefore not represented.
showed no significant differences and therefore the results were not
represented. Significant pD values are < 0.05 after the Bonferroni adjustment.
Table 3.14:
The results of a oneDway ANOVA, of the abundance of the dominant genera at
the control and pipeline sites of Robben Island, as well as the p values and the
result of the postD hoc comparison of means using the Tukey Honest Significant
Difference (HSD) Test. No Significant pDvalues < 0.05 were found after the
Bonferroni adjustment
Table 3.15:
The oneDway ANOVA, of the abundance of the dominant genera from Robben
Island samples, only significant results from the postD hoc comparison of means
using the Tukey Honest Significant Difference (HSD) Test were represented;
significant pDvalues < 0.05* after the Bonferroni adjustment.
Table 3.16:
The following are results of a oneDway ANOVA between the control and pipeline
sites of both study areas on the abundance of live foraminifera per size class. The
postDhoc comparison of means using the Tukey Honest Significant Difference
(HSD) Test is also represented. Significant pDvalues < 0.05 after the Bonferroni
adjustment.
Table 3.17:
The dominant species of foraminifera in the dead assemblages and their
percentage of the total numbers, in samples collected from Robben Island.
xii
Table 3.18:
The dominant species of foraminifera from the dead assemblages and their
percentage of the total numbers, in samples collected from St Helena Bay.
Table 3.19:
The following are the results of a RELATE statistic in PRIMER which attempts
to correlate the dead and live assemblages of all samples together (ALL) and St
Helena Bay (SHB) and Robben Island (RI) separately. All pDvalues were
statistically significant.
Table 3.20:
Tables illustrating the results of the SIMPER procedure in PRIMER between all
species of the dead assemblages in all samples of St Helena Bay. The data were
fourth root transformed and the BrayD Curtis similarity matrix was used to
produce the SIMPER. The average similarity percentage of each of the two
groups is in brackets and the species most responsible for determining
community structure within each group is in bold (a). The average dissimilarity
between the two groups is in brackets and the species most responsible for the
dissimilarity is represented in (b).
Table 3.21:
Tables illustrating the results of the SIMPER procedure in PRIMER between all
species of the dead assemblages in all samples of Robben Island. The data were
fourth root transformed and the BrayD Curtis similarity matrix was used to
produce the SIMPER. The average similarity percentage of each of the two
groups is in brackets and the species most responsible for determining community
structure within each group is in bold (a). The average dissimilarity between the
two groups is in brackets and the species most responsible for the dissimilarity is
represented in (b).
Table 3.22:
Tables illustrating the results of the SIMPER procedure in PRIMER between all
species of the dead assemblages in the two study areas. The data were fourth
root transformed and the BrayD Curtis similarity matrix was used to produce the
SIMPER. The average similarity percentage of each of the two groups is in
brackets and the species most responsible for determining community structure
within each group is in bold (a). The average dissimilarity between the two groups
is in brackets and the species most responsible for the dissimilarity is represented
in (b).
xiii
Table 3.23:
The following represents the results of a oneDway ANOVA between the control
and pipeline sites of both Robben Island and St Helena Bay in terms of the
abundance of dead foraminifera per size class. The Tukey Honest Significant
Difference Tests provided significant values at p < 0.05* after the Bonferroni
adjustment.
Table 3.24:
The following are the results of a RELATE statistic in PRIMER which attempts
to correlate the dead and live foraminiferal abundance of all samples together
(ALL) and St Helena Bay (SHB) and Robben Island (RI) separately. All pDvalues
were statistically significant.
Table 3.25:
NonDparametric spearman rank order correlations between the live and dead mean
foraminiferal size. All correlations were significant at p < 0.05 after a Bonferroni
adjustment.
Table 3.26:
OneDway ANOVA of the mean size of live and dead foraminifera between St
Helena Bay (SHB) and Robben Island (RI). Significant differences are at p <
0.05 after the Bonferroni adjustment.
Chapter 4
Table 4.1:
The following are the results of the nonDparametric Spearman Rank Order
correlations between Species Richness, Species Diversity and the abundance of
live foraminifera in all samples and all environmental variables in St Helena Bay.
Significant RD values are at p < 0.05*.
Table 4.2:
The results of the NonDparametric Spearman Rank Order correlations between
Species Richness, Species Diversity and the abundance of live foraminifera and
all environmental variables for the Robben Island samples are represented.
Significant RD values are at p < 0.05*.
Table 4.3:
The results of the Pearson Product Moment correlations between Species
Richness, Species Diversity and the abundance of
live
foraminifera
and
all
environmental variables using pooled data from both study areas. Significant RD
values are at p < 0.05 *.
Table 4.4:
The BIOENV BEST procedure in PRIMER for St Helena Bay samples which
attempted to explain the environmental variables most responsible for assemblage
xiv
structure. Data was log x+1 transformed. Spearman rank correlation was
performed using Euclidean distance.
Table 4.5:
Results of the BIOENV BEST procedure in PRIMER for Robben Island samples,
which attempted to explain the environmental variables most responsible for
assemblage structure. Data was log x+1 transformed. Spearman rank correlation
was performed using Euclidean distance.
Table 4.6:
BIOENV BEST was used to explain the environmental variables most responsible
for the assemblage structure of both Robben Island and St Helena Bay samples.
Data were log x+1 transformed and Euclidean distance and Spearman rank
correlation was performed.
Table 4.7:
Results of the NonDparametric, Spearman Rank Order Correlation between all
environmental variables and the abundance of
the dominant genera for St
Helena Bay. Significant RDvalues are at p < 0.05*
Table 4.8:
Results of the NonDparametric Spearman Rank Order Correlation between all
environmental variables and the dominant genera of Robben Island. Significant
RDvalues are at p < 0.05*.
Table 4.9:
The following represents the dominant size classes of foraminiferal specimens in
the live assemblages and the dominant sediment size class. The percentages are of
the total found at each of the St Helena Bay stations.
Table 4.10:
The following represents the dominant size classes of foraminiferal specimens in
the live assemblages and the dominant sediment size class in each of the Robben
Island stations. The percentage represents that of the total.
Table 4.11:
Represents the % tests that displayed abnormalities (chamber regrowth or
deformation) and the percentage of broken or abraded tests for each site. Only
live foraminifera were examined. (Appendix – plates of normal, abraded and
broken foraminifera).
xv
Table 4.12:
Results of the NonDparametric, Spearman Rank Order Correlation between the
trace metal concentrations in the sediments and the trace metal concentration in
the tests. Spearman RD values are represented, significant at p < 0.05.
SH – St Helena Bay; CSH – Control sites St Helena Bay; PSH – Pipeline Sites St
Helena Bay
RI – Robben Islands; CRI D Control sites Robben Island; PRI – Pipeline Sites
Robben Island
xvi
Extant benthic Foraminifera from two bays along the South West coast of South Africa,
with a comment about their use as indicators of pollution.
Abstract
Studies of foraminifera in South Africa have largely focused on their use in geology, and
work on extant taxa is missing. This project goes some way to redressing the imbalance in
emphasis and it is aimed at describing the benthic foraminifera from two bays along the SW
coast of South Africa and determining the environmental factors that might be associated with
structuring communities: an attempt is made to assess whether foraminifera can be used as
indicators in the environmental assessment in the region.
Six sediment cores were collected from a number of control and polluted sites around
Robben Island (Table Bay) and in St Helena Bay, and all living foraminifera in the upper 5 cm
were identified and counted. Information on the size structure, carbon and nitrogen content and
trace metal concentrations of the sediments were also collected, as was information on the size
structure of the communities, and the traceDmetal content of, and abnormalities to, tests.
Relationships between variables were investigated using a suite of univariate and multivariate,
parametric and nonDparametric statistical methods.
Sediments were coarser around Robben Island than in St Helena Bay, which reflects the
more sheltered aspect of the latter as well as the greater input of organic contaminants, and is
supported by the higher levels of nitrogen and greater concentrations of trace metals in the latter
than former. The sediment environment at control and pipeline sites around Robben Island did
not differ significantly from each other, but in St Helena Bay, the control sites had a significantly
smaller mean grain than the pipeline sites. The percentage nitrogen in St Helena Bay samples
was higher than that of Robben Island, which may be a reflection of higher production and
increased eutrophication within the area. The two locations showed obvious differences in the
condition of the sediments: those at Robben Island did not display signs of sediment pollution,
whereas in St Helena Bay, most trace metals were high and some higher than SA SQG’s and
ERL levels.
1
A total of 38 morphoDspecies of foraminifera were identified from 120 samples and 20
stations at both sites. The number of species is much the same as identified in other studies of
nearshore and marginal marine environments, though studies in the deepDsea have yielded a
higher species richness. Communities around St Helena Bay were of a lower diversity but a
higher abundance than Robben Island, previously identified as an indication of a polluted
environment. Assemblages of Robben Island were dominated by
(not
): larger numbers of miliolids and fewer bolivinids were observed by
comparison with St Helena Bay. The absence of miliolids is often used as an indication that an
environment may be polluted as they generally do not display a wide tolerance range. A
dominance of bolivinids, and opportunistic taxa (like
and
is more
indicative of a polluted environment.
The live and dead assemblages were characterized by the same species, an indication that
these areas are not depositional environments. The abundance of specimens in each species
accounted for the low correlations between dead and live assemblages, indicating an
accumulation of dead tests on the seafloor. The differences were more marked in St Helena Bay
than Robben Island, reflecting the differences in the currents and residence time of the two bays.
There was a high abundance of small foraminifera in both locations despite the generally
large grain size. The small foraminifera may be indicative of pollution, but may also reflect the
cold temperate waters present yearDround, which generally support smaller foraminifera.
The results of the multivariate analyses suggest that most of the variation in the
composition of the samples was of an intraDsample nature, illustrating large scale patchiness in
foraminiferal distribution. There were, however, definite differences between communities
around Robben Island and in St Helena Bay, and least variation was found between the control
and pipeline sites, and between the stations of each site. When the trace metal concentrations and
the percentage nitrogen increased, the richness, diversity and abundance of foraminifera tended
to decrease. Sediment grain size positively affected abundance but negatively affected diversity
and richness. In both areas mean grain size did not, however, appear to play a very large role in
influencing diversity. Cadmium, copper, chromium, the percentage nitrogen and the mean grain
size were identified as the most important variables influencing the community structure by the
BIOENV BEST routine in PRIMER. The trace metals and percentage nitrogen only had negative
2
effects on the diversity and abundance as well as on the abundance of the dominant genera,
whereas the mean grain size had variable effects.
Few foraminifera displayed morphological abnormalities and there was no clear
correlation between the trace metal concentrations of the sediments and tests. Because
foraminifera in a nearshore environment are exposed to wave action and stronger tides than those
in deeper environments, it would be difficult in this case to use morphological abnormalities as
indicative of pollution. The trace metal content of the tests of foraminifera is difficult to interpret
as no baseline has been established against which the present values could be compared.
Although foraminifera have been used elsewhere to identify polluted environments, they
display a few drawbacks as a monitoring tool. Examination of field collected samples is timeD
consuming, given that one needs a large number of replicates to ensure statistical rigour. These
replicates are essential because foraminifera display largeDscale variability and patchiness even
between cores at the same station, so differences may merely be a result of microDscale
variability within the benthos and not as a result of pollutants. Identification of foraminifera is
often difficult using light microscopy because of their size. However, once an assemblage is
identified as a possible bio – indicator, these organisms could be a useful adjunct to other
analyses.
The use of foraminifera as bioDindicators is still being explored to a large degree globally
and is totally new in South Africa. Many of the findings of this study were similar to those of
other studies but differed in that morphological abnormalities did not appear to be a reliable
method of identifying polluted environments and the foraminifera did not appear to take up the
trace metals from the sediments in as high concentrations as expected. This study would,
therefore, contribute largely towards a better understanding of the ecology of foraminifera and
how they react towards environmental conditions which would not only be useful in a South
African setting but also globally.
Key Words: Foraminifera, trace metals, sediment grain size, percentage nitrogen, percentage
carbon, taphonomy, morphological abnormalities, elemental analysis, South Africa, St Helena
Bay, Robben Island.
3
Chapter 1
General Introduction
1.1
The South African Marine Environment
South Africa is bathed by a cold, northDflowing current (the Benguela Current) on the west
coast and a warmer, southward flowing current on the east and south coasts (the Agulhas
Current), these currents provide very different conditions and therefore support different marine
organisms (Branch & Branch, 1995).
The surface waters of the Agulhas Current are nutrient poor, and most east coast areas are
considered less productive than west coast areas at the same latitude (Bailey & Rogers, 1997).
The origin of water in the Benguela Current is from South Atlantic Central Water, with a small
contribution from the Agulhas Current (Nelson & Hutchings, 1983). Surface currents in the
Benguela are primarily windDdriven, and although the net movement of water is equatorward
there is evidence that subsurface waters move southward over the shelf and poleward west of the
shelf break (Shannon, 1986). The coldest waters in the Benguela are found close inshore due to
upwelling (Van Ieperen, 1971).
On the west coast, the outerDshelf sediments are dominated by Holocene planktonic
foraminiferal ooze, the middle shelf sediments consist of glauconitic sands, and the inner shelf
comprises of terrigenous muds and sands, which are organicDrich (Bailey & Rogers, 1997). The
Benguela ecosystem has been exploited for many centuries with little understanding of the
oceanographic processes, however when the South African demersal fishing industry developed
at the beginning of the twentieth century, studies of the system were started by Dr J. D. F.
Gilchrist (1895/1896) (Shannon & Pillar, 1986).
The west coast of South Africa is characterised by being an upwelling area, from Cape
Point (34° 21' 24" S; 18° 29' 51" E) in South Africa to Cape Frio (18° 26' 60" S; 12° 1' 0" E) in
the north of Namibia (Nelson & Hutchings, 1983). Two outcrops on the west coast at Cape
Peninsula and Cape Columbine have canyons, which alter the velocity of the Benguela flow as
well as enhancing upwelling (Nelson & Hutchings, 1983). These are areas of intense upwelling,
high nutrient recycling and high primary production (Nelson & Hutchings, 1983). The water off
Cape Town may be influenced by tongues of the Agulhas Current, but is mainly influenced by
the Benguela Current (Van Ieperen, 1971). Two shallow regions near St Helena Bay and Walvis
4
Bay (Namibia), have less equatorward windstress and have been reported as being ecologically
important within the system (Shannon, 1986).
Upwelling is caused by the prevailing southDeasterly winds (mainly in summer) that blow
parallel to the coast and the Coriolis Effect, which effectively pushes surface water offDshore and
causes subsurface waters to well up (Hart & Currie, 1960). These nutrient rich bottom waters are
what sustain high phytoplankton biomass and support an abundance of marine life, including a
largeDscale commercial fisheries (Van Ieperen, 1971). One of the consequences of the nutrientD
rich water is phytoplankton blooms, which may on occasion be toxic and lead to large scale
mortalities within the system (Hart & Currie, 1960).
Mixing and advection in the top 20 m of the water column assist in preventing upwelled
water from sinking, and keeps nutrientDrich upwelled water in the euphotic zone for prolonged
periods of time (Brink, 1987). Although the upwelling season is mostly in summer in South
Africa, in winter, when westerly winds tend to dominate, winter storms and reduced insolation
can result in a deep, wellDmixed surface layer (Shannon & Pillar, 1986). The phytoplankton
biomass and hence primary production is found to be higher but more variable in summer than in
winter, as a result of upwelling and the response of phytoplankton to the increase in nutrients in
surface layers (Shannon & Pillar, 1986).
Coastal waters in eastern boundary currents, such as the Benguela, are also thought to
support high productivity due to the settling of particulate carbon and nutrients in the sediment,
which is generally higher on the leeward side of upwelling centres (Bailey, 1987). The nutrient
content of the St Helena Bay region was found to exceed that of other upwelling source water by
100 percent (Bailey, 1987). It was found that there is a northward reduction in the seasonality of
upwelling, which was reflected in an increase in the reducing nature of the organicDrich
sediments found between St Helena Bay and Walvis Bay (Bailey & Rogers, 1997).
Net plankton productivity in the Benguela Current appears to be controlled by nitrate
concentration and regenerated nitrogen (Shannon & Pillar, 1986). Although nutrient cyling can
be important in the system, it appears to be of more importance in the northern Benguela and off
the shelf at St Helena Bay than off the Cape Peninsula (Shannon, 1986). Following a bloom,
productivity drops due to nutrientDdepletion and selfDshading in surface waters as well as losses
as a result of zooplankton grazing, death and sinking (Branch
1987). Mass mortality of
5
phytoplankton after a bloom and sinking provides detritus and increased food availability to
benthic organisms causing them to increase in abundance.
In a review on the impacts of human activities in the Benguela region, Griffiths
(2004) have described the present as postDindustrial and have found that although there is
improved resource management and stabilisation of catches, there appears to be an increasing
impact on the system which is nonDfishery related.
1.2
Marine pollution and sediment chemistry
The coastal marine environment is constantly subjected to disturbance and changes as a
result of storms and strong winds, as well as the structure of the coastline. Disturbance in a
coastal environment is an important factor contributing to community structure and spatial
heterogeneity (Guichard & Steenweg, 2008). However, an increase in anthropogenic disturbance
is placing largeDscale stress on near shore environments. More than half of the world’s
population now lives within 200 km of the coast and that number is still increasing (De Souza
., 2003 in Gao
., 2008). With increasing urbanisation and settlement on the coast, more
domestic waste is being generated and as a result more outfalls have been built. In South Africa,
two coastal cities, Cape Town and Port Elizabeth grew by 22 % and 24 % respectively in the
1990s (UNEP, 2003). Increased urbanisation has led to increased industrial effluent, stormwater
runDoff, sewerage, windDblown litter, suspended sediments and agroDchemicals entering the sea
(UNEP, 2003).
The ocean has for centuries been regarded as vast enough to accommodate waste without
major changes and to have the ability to dilute toxic waste or carry it away from the coastline
with its currents (O’ Neill, 1993). However, it is becoming increasingly apparent that the
increase in the rate of pollutant input is having an effect on coastal areas. Pollutants may be
regarded as any introduced substance which may harm a resource, and includes substances that
are usually present in the environment but have exceeded natural levels due to anthropogenic
input (O’Neill, 1993).
Excessive nutrient loading can accelerate the eutrophication process and cause an
imbalance in the products of this process. Eutrophication is the production of organic matter that
forms the basis of the food web and is a natural process in many aquatic systems (Livingston,
2001). Nitrogen and phosphorous are regarded as limiting elements in biological production;
6
human activity has increased global nitrogen fluxes and has been found to cause a significant rise
in the primary productivity of the coastal zone (Libes, 1992). An increase in the concentration of
these otherwise limiting nutrients causes an increase in the growth of coastal phytoplankton,
which causes an increase in the levels of organic carbon that in turn can be deposited on the sea
floor (Mojtahid
., 2009). This increase in the supply of organic material to sediments leads to
an increase in the abundance of detritusDdependent benthic organisms, which rapidly remove
oxygen and eventually produce hypoxic/anoxic sediments. This anoxia usually results in the
decrease in the diversity of benthic organisms (Mojtahid
2009), as well as mortality of
benthic organisms.
Increased anthropogenic inputs have been found to affect the trace metal content of the
marine environment. Trace metals are present in marine sediments in the form of biogenic
detritus (concentrated in the marine organism), clay minerals (in crystal lattice) and hydrogenous
precipitates (polymetallic oxyhydroxides) (Libes, 1992). Essential trace elements are necessary
for the growth of phytoplankton and for the catalysis of biological reactions (Libes, 1992). In an
environment where organic carbon loading is very high, trace metals bind with sulphides and
will only remobilize when resuspended during storms or dredging (Monteiro
, 1999).
Disturbance remobilizes the contaminants and can cause localized effects and eventually form
precipitates of hydroxides which return the metals to the sediments (Henry
., 1989).
Organic materials form organometal complexes when binding to trace metals and these
are regarded as hazardous to aquatic life when they occur in very high concentrations (Abel,
1996). Organisms tend to accumulate these metals within their body tissues which could be a
toxic hazard to the organism itself and to organisms higher up in the food web due to
bioaccumulation (Abel, 1996). Toxic heavy metals that appear to be most affected by human
activity are As, Cd, Cu, Cr, Hg, Pb, Ni, Sb, Se, V and Zn, which have high enrichment factors
(degree to which a metal is concentrated in the organism) and slow clearance rates (rate of
degradation or excretion by the organism) (Libes, 1992).
It is apparent that anthropogenic inputs in the marine environment affect production by
disturbing the balance of carbon, nitrogen, oxygen and trace metals which in turn determines the
types of organisms present. It is therefore necessary to monitor the concentrations of these
substances, in any area which could possibly be affected, on a regular basis in order to determine
their possible effects.
7
1.3
Marine pollution in South Africa
About 67 ocean outfalls are located along the South African coast and these discharge
approximately 1.3 million m3/ day of sewage and industrial effluent into the sea (National State
of the Environment Report – South Africa, 2008). Most of these discharge into deeper waters,
but 27 of the older pipelines discharge above the high water mark, 23 of these being in the
Western Cape (National State of the Environment Report – South Africa, 2008). All municipal
waste water discharges to the offshore marine environment receive preliminary treatment with
coarse and fine screens (Taljaard
2006). However, wastewater outlets from industries are
solely controlled by the industry and there is no means of controlling the quality of the
wastewater during the discharge process (Taljaard
2006). In an attempt to control the
discharge process to the marine environment, the Department of Water Affairs and Forestry drew
up an operational policy for the disposal of landDderived water containing waste with guidelines
for both industries and municipalities (Taljaard
2006).
The Council for Scientific and Industrial Research (CSIR) as well as the Department of
Environmental Affairs (Oceans and Coasts) (formerly Sea Fisheries Research Institute and
Marine and Coastal Management), have been responsible for many marineDmonitoring programs
in South Africa. In South Africa, offshore marine outfalls are monitored at their point of
discharge and in the environment they impact, whereas wastewater discharges into the surf zone
and estuaries are only monitored at their source, and environmental monitoring is normally nonD
existent (Taljaard
2006). The CSIR in Durban has been conducting annual surveys on
both domestic and industrial outfalls along the east coast of South Africa, and the surveys
include chemical analysis of water and sediments, physical factors and biological studies of both
meiofauna and macrofauna providing a complete study of the effects of the outfalls on the
concentration of chemicals in sediments as well as the effects on marine organisms.
Most surveys on the west coast of South Africa have not included the shallow areas
where outfalls occur. The CSIR in Stellenbosch has however conducted research on the Hout
Bay, Camps Bay and Green Point sewage outfalls in 1999 and again in 2003. These surveys
examined a variety of physical and chemical factors but excluded a biological component. The
outfalls from the fish factories in St Helena Bay and Saldanha Bay have been monitored from
time to time by the CSIR, however, these assessments and reports are not available for public
perusal.
8
Few published biological assessments have been done in polluted environments in South
Africa. Biological assessments that have been conducted mostly examine macrofauna. Globally,
macrobenthic invertebrates are better understood and documented than those of smaller
invertebrates and protozoans in terms of their life histories, responses to natural and
anthropogenic conditions and changes, and trophic strategies (Burd
., 2008). In addition,
many commercially important invertebrate species live within the sediments (e.g., clams) or on
the surface of the sediments or hard substrata (e.g., crabs) (Burd
., 2008). The benthic
environment, where most pollutants settle is inhabited by a vast number and variety of
meiofauna, and these meiofauna react quickly to changes in their environment and can provide a
good indication of the conditions therein. Examination of these sediments for meiofauna is
labour intensive and time consuming and the need for easy biological assessment of these
sediments is required.
1.4
Foraminifera
Foraminifera belong to the Kingdom Protista and are currently recognised as their own
phylum Foraminifera, though they were previously classified as order Foraminiferida Eichwald,
1830 within the phylum Protozoa (Loeblich & Tappan, 1987). These unicellular organisms are
characterised by the presence of a test, which surrounds the cytoplasm (Loeblich & Tappan,
1987). Their tests can be composed of chitin, silica or calcium carbonate, or they may be
agglutinated, using detrital material to form a test (Cushman, 1959). The walls of some
calcareous types are perforated for the extension of pseudopodia while others are smooth and
imperforate (Albani
., 2001). The nature of the test is often indicative of the environment in
which the organism is found. For example, agglutinated species sometimes indicate an area
where little or no carbonate is available, where salinities are low, or where the water is very cold
(Scott
., 2001). The formation of foraminiferal tests differ from that of other testate protists,
like the phylum Rhizopoda or Pyrrophyta, in that it is constructed by incremental additions of the
chambers, each new chamber covers the old external aperture, ensuring the continuity of the
cytoplasm and contact with the external environment (Loeblich & Tappan, 1987).
Foraminifera are also characterized by an alternation of generations, that is, an alternation
of an asexual and sexual reproductive mode, although it appears that the asexual mode normally
outnumbers the sexual mode (Boltovskoy & Wright, 1976; Gooday, 1992). The morphology of
9
the different generations differ in that those produced sexually have a small first chamber and a
large test (microspheric form) and the asexual form is characterised by a large first chamber and
a small test (megalospheric form) (Scott
, 2001). When there is a dominance of sexual
forms in some environments it is thought to be a response to harsher conditions (Boltovskoy &
Wright, 1976).
In addition to being planktonic, foraminifera can form part of the meiofauna (63 Rm –
100 Rm) and are generally small in size, although large Tertiary (up to 5 cm) and Cretaceous (up
to 10 cm) species have been reported (Boltovskoy & Wright, 1976). In temperate areas, such as
the west coast of South Africa, a high abundance of small foraminifera are encountered (< 250
Rm), with very few foraminifera being larger than 500 Rm (Personal Observation).
Foraminifera are primarily marine and hypersaline organisms, although some freshwater
forms have been reported (Phleger, 1973). Species in hypersaline environments exhibit less
morphological variety than those encountered in a normal marine (35 ‰) environment (Murray,
1991). Foraminifera are ubiquitous in their distribution and will be found in all marine habitats
from the plankton (Cifelli & Smith, 1970; Bé
., 1971; Cifelli, 1982; Morard,
the benthos where they may be living attached to hard substrates or algae (Hedley
Atkinson, 1969, Boltovskoy & Wright, 1976; Toefy
., 2009) to
., 1967;
l, 2005) as well as in soft sediments
(Murray, 1991).
Most foraminifera are fairly specific in their depth ranges, being either neritic or oceanic
(Murray, 1991). They also occupy specific temperature ranges, generally being cold, temperate
or tropical in habitat (Halfar & Ingle, 2003). Foraminiferal distribution has been found to be
influenced by a number of abiotic factors, such as salinity and pH, as well as varying with the
organic matter content and grain size of the sediment (Duleba & Debenay, 2003). Some authors
have found that fine, silty sand yields a high abundance of species and individuals while coarse
sand or clay supports lower numbers, and this is thought to be a result of the higher organic
matter and therefore more food in finer sediments (Samir & ElD Din, 2001). However, other
authors have found that coarse sediments provide more favourable habitats for benthic
foraminifera, especially those which attach to the substrate (du Châtelet
., 2009). Benthic
species composition has been linked to sediment grain size in many studies, however, this factor
has been found to be of variable importance in determining individual species abundance
patterns and hence in determining the distribution of benthic assemblages (Bremner
2006).
10
1.5
Foraminiferal pollution studies
Their characteristic test generally preserves well in sediments and this has made
foraminifera useful for mapping paleontological records and environmental changes.
Foraminifera are useful because they provide an extensive geological record which dates from
the Cambrian to the Recent (Buzas & Culver, 1991). The fact that extinct foraminifera have
specific geological distribution ranges makes them suitable for aging sediments and therefore
they can be of use to mining and geological explorations (Cushman, 1959). When foraminifera
die, their tests accumulate on the sea floor and can provide a record of environmental conditions
in both the ocean and the sediment at the time of their death (Phleger, 1973). This characteristic
can provide “
” information of assemblages, in environmental studies where no baseline
data are available (Yanko
, 1994).
Globally, foraminiferal studies have concentrated on fossilized material (Boltovskoy &
Wright, 1976), although ecological studies have increased since the 1950s (Murray, 1991). With
an increase in the number of ecological studies, authors have also realised their potential use in
determining anthropogenic effects on the environment. Studies related to their use as indicators
of anthropogenic effects were started in the late 1950s and early 1960s by Zalesny (1959), Resig
(1960) and Watkins (1961).
Benthic foraminifera are useful as indicators of pollution because they live in, and on,
sediments; they can be abundant even in small sample volumes and many species have very
specific ecological requirements (Yanko
, 1994). Foraminifera generally have short lifeD
cycles (one month to a year) and therefore they respond quickly to their environment, which
makes them useful as bioDindicators of shortDterm and longDterm changes in the marine
environment on both local and global scales (Frontalini
., 2009). Yanko
(1994) used
foraminifers to study the effects of various pollution sources in the Mediterranean Sea along the
coast of Israel. These included domestic sewerage, a coalDfired power station and heavy metal
contamination. The results of their study showed that foraminifera were sensitive
monitors
of coastal pollution. Sites with domestic sewage displayed high population densities and
diversity of large foraminifera which were mostly agglutinated, while those exposed to coal
pollution had the lowest population densities and diversity, and the sites where heavy metal
contamination took place had foraminifera with smaller tests and these tests displayed abnormal
11
morphology (Yanko
., 1994). Culver & Buzas (1995) studied the anthropogenic effects as
well as the effects of global warming on shallow marine benthic foraminifera in geological
history around North and Central America. The authors concluded that while foraminifera are
widespread and exhibit rapid dispersal, rare and geographically restricted foraminifera are most
at risk due to coastal development. The loss of habitat during geological time was attributed by
these authors as the major cause of foraminiferal extinction.
Foraminifera have been found to be sensitive to a variety of chemicals being pumped into
the sea. Lead has been found to affect shell composition in foraminifera as well as molluscs and
other shelled invertebrates; shells were found to contain higher lead concentrations but lower
calcium concentrations (Almeida
1998). TriD DButyltin (TBT) mesocosm experiments
showed that foraminifera display greater tolerance to low levels of TBT than other taxa
(nematodes, ostracods and small molluscs), but at high levels (2.00 nmol) they decreased in
abundance but did not show any significant decrease in diversity (Gustafsson
2000). In
sites with methane coldDseeps, the species composition of foraminifera were very similar to those
of organic rich environments, and they appeared to be attracted to the extra food and had a high
range of oxygen and carbon values in their shells (Rathburn
, 2000).
Very high trace metal concentrations have only negative impacts, unlike the varying impacts
of high organic carbon. It has been observed that as the trace metal concentration of sediments
increases and other chemicals are discharged, populations of foraminifera may decrease to such
an extent that some areas may become completely devoid of living specimens (Scott
Ferraro
., 2006; Frontalini
., 2001;
., 2009).
Foraminifera are also sensitive to oxygen concentrations as well as to the levels of
dissolved organic matter. Moodley
(1998) found fewer softDshelled and more hardDshelled
foraminifera in anoxic environments, and these authors concluded that some foraminifera can be
facultative anaerobes. In dysoxic and anoxic environments, some foraminifera have been found
to sequester chloroplasts from algae, which is thought to allow the host to be provided with
oxygen (Bernhard & Bowser, 1999). Other studies of anoxic and hypoxic environments,
generally found lower diversity and abundance and the strong dominance of certain species
many of them deep infaunal species (Gustaffson & Nordberg, 2000; den Dulk
2000;
FernandezDLeborans & Herrero, 2000; Alve, 2003).
12
Typical anaerobic environments exhibit low foraminiferal species diversity, high
dominance and large standing stocks of those taxa tolerant to this stress (Frontalini
., 2009).
The effect of organic matter on the diversity of foraminifera appears to be complex, as some
authors report a decrease in abundance and diversity with increasing organic matter (Schafer
1995), while others report an increase in abundance and diversity (du Châtelet
., 2009):
some authors have reported no correlation (Alve, 1991). Anthropogenically sourced organic
matter appears from most studies to produce aboveDbackground foraminiferal population
densities (Bernhard, 1986; Yanko
1994; Scott
, 2001). Mojtahid
. (2009) are of
the opinion that when organic matter is high and oxygen levels are still tolerable, a number of
opportunistic species will dominate, these being both epifaunal and mobile infaunal species.
Many authors have shown that foraminifera exposed to environmental stress may display
largeDscale malformations of the test (Toler & Hallock, 1998; Stouff
Geslin
1999). However,
(2002) found a higher percentage of abnormal tests in nonDpolluted than polluted
environments and cautioned against the use of using abnormal morphology as a pollution
indicator. Test deformations and stunted growth have been primarily reported in areas
contaminated by high trace metal concentrations, domestic sewage and various chemicals
including liquid hydrocarbons (Culver & Buzas, 1995; Frontalini
., 2009).
Test
deformations can range from changes in chamber shape or growth patterns; double apertures,
wrong coiling, Siamese twins, high spires or poor development (Yanko
1994; Frontalini
., 2009). Siamese twins are thought to arise from early fusion of juveniles or attachment of
juveniles to the parental test after schizogony (Stouff
1999). Samir & ElDDin (2001)
suggest that trace metals affect the calcium uptake of foraminifera which weakens tests leading
to test deformation. More recently the possibility of using the trace element content of
foraminiferal tests as tracers of environmental quality has also been explored (Samir & ElDDin,
2001; Frontalini
., 2009).
When environmental conditions are measured and species are identified as being
commonly found in those conditions, it can be concluded that the presence of these species or
groups of species are indicative of certain environmental conditions. These species are often then
used to identify biofacies, that is, species which commonly occur together in certain
environmental conditions (Pielou, 1979). By identifying, describing and documenting these
biofacies, one can immediately tell if an environment is polluted by the presence of that
13
assemblage or species. Opportunists are species that are most resistant to pollutants, and tend to
dominate assemblages in polluted environments (Culver & Buzas, 1995). Foraminiferal species
which tend to dominate stressed environments are often elongated, flattened and small. This may
be due to sexual maturity being reached earlier, or due to dwarfism in adverse conditions
(Bernhard, 1986).
and species of
have been widely reported as
indicative of environmental stress and have been found to have a wide tolerance range of
chemical, thermal and oxygen conditions (Frontalini
., 2009). Agglutinated foraminifera
have also been cited as an important indicator of pollution in cold water sites, as it is thought that
the ability of foraminifera to take up calcium for test formation is affected by pollutants, leading
to fewer calcareous forms (Yanko
., 1994). Although differences in foraminiferal
assemblages in polluted environments have been widely reported, Gooday & Lambshead (1989)
cautioned against the use of foraminifera without taking patchiness into account, as spatial
heterogeneity may be due to patchiness in foraminiferal distribution and not to differences in
environmental conditions. Patchiness occurs as a result of clumping and biological interactions
like competition and reproduction which would affect the distribution of foraminifera in the
microDenvironment (Murray
., 1991). Scott
(2001), however, are of the opinion that the
more polluted an environment, the less the spatial variability as opportunists would tend to take
over and the less complex and patchy the assemblage would become.
1.6
Foraminiferal studies in South Africa
Studies of foraminifera in South Africa have been mostly of a palaeontological nature,
and have been conducted as a result of geological surveys and mineralogical exploration
(Appendix 1.1). The earliest of these studies were undertaken by Chapman (1904, 1907, 1916,
1923, 1924, and 1930) who provided lists and some illustrations of species found. After this
period studies on foraminifera stopped until the 1950s (Biesiot, 1957; Parr, 1958; Albani, 1965;
Lambert & Scheibnerova, 1974). The Joint Geological Survey and the University of Cape Town
Marine Geoscience Unit conducted a number of geological surveys on the RV
in the 1970s and 1980s, which reported some foraminifera on the west coast of South
Africa(Martin, 1974; Salmon, 1979a, 1979b, 1981). During mineralogical studies conducted by
the then De Beers Marine (PTY) Ltd, a number of papers on foraminfera were published
14
(McMillan, 1987, 1990, 1993; Dale & McMillan, 1998). More recently a study on extant
foraminifera was conducted by Toefy
(2003).
Many of the above studies provided only lists of foraminifera and information on their
distribution but did not attempt to relate distribution to any environmental factors. McMillan
(1990) and Toefy
. (2005) provided taxonomic descriptions of some foraminifera sampled
around South Africa. Toefy
(2003) have conducted the only ecological study on extant
foraminifera around South Africa which related the community structure to the level of exposure
in an intertidal environment and to their algal habitat. Foraminifera were found to be more
abundant on exposed than on sheltered rocky shores. Foraminifera studied have been mostly offD
shore and from deep sea environments. Studies of foraminifera in coastal environments and as
potential environmental indicators have been neglected.
1.7
Study Site 9 St Helena Bay
St Helena Bay is situated on the west coast of South Africa (32º 40' S; 17º 58' E)
approximately 160 km north of the Cape Peninsula (Fig. 1.1). Just south of St Helena Bay is a
major upwelling centre at Cape Columbine, and nutrients are transported offDshore near St
Helena Bay via a cyclonic gyre (Walker & Pitcher, 1991). The southern Benguela upwelling
system appears to exert considerable control on the biogeochemical characteristics of St Helena
Bay (Monteiro & Roychoudhury, 2005). The nutrientDrich waters off Cape Columbine support a
large pelagic fishery, and the close proximity of St Helena Bay to both the fishing grounds and
the city of Cape Town led to the establishment of fish processing plants in the 1940s (Shannon,
1983). St Helena Bay is a semiDclosed system, an antiDcyclonic gyre within the bay (Fig.
1.1) has been found to trap water for up to 25 days compared to a retention time of 3 – 5 days
outside the bay (Walker & Pitcher, 1991). Particulate matter deposited in St Helena Bay,
therefore, tends to settle in the area. Sediments in the bay are primarily brought in either as
atmospheric input or carried by the Berg River or even from the Orange River (Monteiro &
Roychoudhury, 2005). The Berg River and its tributaries flow through areas dominated by
agriculture, wineries, canneries and textile mills (Monteiro & Roychoudhury, 2005).
Historically, two types of effluent were released by the fish processing plants. The first
type was produced during offDloading, where the hold of the ship was flooded with sea water to
float off the cargo and the water was then pumped directly into the sea. This is known as the wet
15
system of offDloading (Newman & Pollock, 1973). Secondly “blood water” from factory effluent
was pumped into the sea and this contained all the biological material from processing, including
guts, scales and bones (Newman & Pollock, 1973). Large amounts of organic matter were
released into the bay, especially when offDloading large amounts of catch after long periods at
sea (Newman & Pollock, 1973).
An accumulation of organic matter in St Helena Bay was thought to result in the high
mortality of rock lobster (
and other inshore animals in 1972 (Newman & Pollock,
1973). As a result, the system of wet offDloading was replaced by dry offDloading (vacuum
removal of fish from boats) in 1974/75. A small amount of water is still used in this method
(Shannon
., 1983).
In the 1950s, the Sea Fisheries Research Institute (SFRI) started a programme of research
called the Pilchard Research Programme in St Helena Bay and this focussed on the physical and
chemical properties of water, seasonal trends and annual anomalies of water in the upper 50 m
(Clowes, 1954; Buys, 1957). These data were used to establish an environmental baseline for
management purposes. Unfortunately, the research did not include the region in the bay where
the fish factories and harbour are found. Studies in this region have continued, and are still being
done at present (Bailey, 1983; Shannon
., 1983; Bailey & Chapman, 1985; Walker &
Pitcher, 1991; Guastella, 1992), although they are still only conducted in deeper coastal waters
(≥ 30 m depth), which are accessible to shipDbased research. Moldan (1983) examined the effects
of a fish factory on benthic macrofauna in St Helena Bay but this study was presented in the
form of a short note and no details of organisms were given. No study has examined the benthic
meiofauna and more particularly foraminifera, in conjunction with chemical properties of the
sediment.
The factory where the outfall was studied processes pilchard, anchovy and lobster into
canned fish, fishmeal, fish oil, and processed and live lobster. It processes approximately 150
000 tons of fish per year and processing takes place for most of the year, when fish is available:
usually no production takes place for about 3 weeks in January, and during winter the processing
is slow as fish is scarce (Fish factory manager, pers. comm.). The factory pumps seaDwater in, for
the processing of fish and waste water is pumped out into the surf zone approximately 30 m off
shore (Fish factory manager, pers. comm.). The estimated flow from the fish factory is 18 000 m3
/ day (DWAF, 2004).
16
1.8
Study Site 9 Robben Island
Robben Island (33º 48' S, 18º 22' E) is situated about 12 km from Cape Town in Table
Bay (Fig. 1.2). The deepest point of the bay is 27 m and the substrate is comprised mostly of
sand with a few rocky patches (Van Ieperen, 1971). The bay is open to the sea from the S.E. to
the N.W. and tidal currents are weak (average of 20 cm/ sec), and are weakest in winter (Van
Ieperen, 1971). Because of the high wind velocities and the shallowness of the bay, surface
currents are thought to be windDdriven (Van Ieperen, 1971). Winds are S.S.E. for most of the
year and in winter mostly northerly, however wind direction can vary greatly (Jury & Bain,
1989). Water enters the bay between Robben Island and Green Point, while in the bay water
movement is mostly northward. The bathymetry around Robben Island is shallow and shows a
high percentage of negligible current velocities, varying with wind speeds (Van Ieperen, 1971).
There is some evidence of localised upwelling within Table Bay during summer, which is caused
by the prevailing winds and this causes sea temperatures to be highly variable (Jury & Bain,
1989). The movement of upwelled water appears to be concentrated in a cool band 3 km
offshore, related to the southerly wind wake of Table Mountain, which suppresses offshore
transport and upwelling along a NDS line across Robben Island (Jury & Bain, 1989). The
residence time of water varies from 15 to 190 hours, therefore, the flushing potential is variable
(Van Ieperen, 1971). The path of pollutants will be a function of local wind direction and
strength and when upwelling ceases in winter, water may become stagnant (< 5 cm/sec) (Van
Ieperen, 1971). The area has some of the highest wave energy along the South African coastline,
driven by the southDwesterly swells. Wind and waves appear to be the most important agents in
moving substances, while the tidal currents, which are highly variable and sometimes even
negligible, are of lesser importance (Jury & Bain, 1989).
Robben Island has been historically isolated for over 400 yrs, being the site of a hospital
for lepers and the mentally ill in the 1800s, a defence training camp in the Second World War,
and a maximum security prison (for political prisoners) and is famous as it held former president
Nelson Mandela for eighteen years (www.RobbenIsland.org.). The island was opened as a
museum in 1997, after South Africa was established as a democracy in 1994, and as a result of
its significant history it has become a major tourist attraction. Thousands of tourists visit the
island each year which has placed increased pressure on its sewerage system.
17
A marine outfall to the sea was built in an attempt to alleviate this problem in 2002. The
pipeline is approximately 400 m long and is situated on the eastern side of the island. The
Robben Island pipeline discharges 550 m3 / day at a depth of 8 m (DWAF, 2004).
The pipeline was designed to yield a 50 x dilution in accordance with the beneficial use
and health requirements for this area (WAMTechnology & Rossouw, 1999). The design was
based on standard jet dilution principles using historical environmental data (WAMTechnology
& Rossouw, 1999). Two dye tests were conducted on the Robben Island pipeline in 2001 to test
the dilution effects of the pipeline (Ove Arup Consulting Engineers, 2001). The results of both
studies indicated that the direction of the plume differed according to the wind direction. The
plume moved north easterly when the wind was southDwesterly, and northwards along the coast
with a slight onshore component when the wind was southDeasterly (Ove Arup Consulting
Engineers, 2001). In the first experiment a dilution of 50 x was achieved at 1200 m and in the
second at 375 m from the diffuser (Ove Arup Consulting Engineers, 2001).
The building of the Robben Island marine outfall was completed in 2002 and began
discharging in April of the same year. IOIDSA conducted a baseline study in 2001 and a
subsequent study in 2002/2003 – after the pipeline had become operational (Prochazka, 2001;
Prochazka, 2003). However, there is still some concern by the management of the island about
the current sewerage system and the need for an upgrade (Cape Argus, Nov. 13 2004).
1.9
Aim of the study
The aim of this study was to
a. Examine environmental conditions in sediments, including sediment grain size
analysis, trace metals and nitrogen and carbon concentrations.
b. Determine the foraminiferal assemblages present in these sediments and the factors
that influence their distribution.
To this end two marine outfalls were studied, a fish factory outfall at St Helena Bay and a
sewage outfall at Robben Island off Cape Town both situated on the west coast of South Africa.
Samples collected were examined for the following:
1.
Sediment grain size structure
2.
Chemical analysis of the sediments for Carbon and Nitrogen content
18
3.
Trace metal content of the sediments
4.
Community structure of foraminiferal assemblages
5.
Size structure and abundance of foraminifera
6.
Trace metal content of the shells of some randomly selected foraminifera
7.
Morphological abnormalities of foraminifera
The thesis has been divided into the following chapters:
Chapter 1:
General Introduction (this chapter)
Chapter 2:
An examination of the sediment structure and chemistry in two
embayments along the south west coast of South Africa.
This chapter examines the sediments around the Robben Island outfall and the fish
factory outfall of St Helena Bay. To this end, sediment grain size analysis was
conducted, percentage carbon and percentage nitrogen and trace metal concentrations
within the sediments were measured. Results of these measurements were reported
and analysed and any correlations between the factors were discussed.
Chapter 3:
The assemblage structure of foraminifera in two
embayments along the south west coast of South Africa.
Chapter 4 examines the foraminiferal assemblage structure around the Robben Island
pipeline and the fish factory outfall in St Helena Bay. Species richness, diversity and abundance
of live foraminifera are examined per core, station, site and locality to determine patterns in
distribution. Species and genera most important in determining this assemblage structure are also
examined.
Chapter 4:
A study linking foraminiferal communities to their environment in two
embayments along the south west coast of South Africa.
Chapter 5 examines the influence of grain size, percentage carbon, percentage nitrogen
and trace metals of the sediments on the foraminiferal assemblages of the two study sites. This
chapter also attempts to identify foraminiferal taxa which could be used as proxies.
19
Chapter 5:
General Conclusions
This chapter summarises the findings of the study, examines the use of foraminifera as
proxies and examines the state of pollution studies in South Africa.
20
Figure 1.1:
Map illustrating the position of St Helena Bay and the sampling area. The
direction of the Benguela current relative to the bay and the anticylonic gyre are
also illustrated (adapted from Touratier
., 2003).
21
Figure 1.2:
Map of Table Bay showing the position of Robben Island and the currents in the
bay (adapted from Van Ieperen, 1971).
22
Chapter 2
An examination of the structure and chemistry of sediments in two
study areas along the south west coast of South Africa
Abstract
The sediments around the Robben Island sewage pipeline and a fish
factory pipeline in St Helena Bay were examined for sediment size structure,
percentage total carbon and nitrogen and the trace metals Cd, Cu, Cr, Pb, Fe and
Zn. Twelve stations were examined in St Helena Bay and eight at Robben
Island: six cores per station were collected where possible. The mean sediment
grain size from samples in both study areas was > 125 Rm and little mud was
present. The percentage total carbon was significantly higher at the Robben
Island (7.17 %) stations compared to those of St Helena Bay (3.78 %) and
samples from the control sites were significantly higher than those from the
pipeline sites in both study areas in terms of the percentage total carbon,
although some pipeline stations showed higher percentages (station SHD in St
Helena Bay). The percentage nitrogen in the sediments was significantly higher
at St Helena Bay (0.168 %) than Robben Island (0.1 %), especially at the
pipeline sites, which could be a result of the loading from the fish factory. The
percentage nitrogen was used as a proxy for the percentage organic carbon
using data from a previous study in St Helena Bay. Except for the Pb
concentrations in the sediments, all other measured trace metal concentrations
were significantly higher in the St Helena Bay samples than the Robben Island
samples. The trace metal concentrations were lower than accepted ERL (Effects
Range Low) levels in both study areas. In St Helena Bay, Station SHD (pipeline
site) had a concentration higher than ERL for Cd and Cu. No guidelines for
acceptable Fe concentrations in sediments exist, however, the concentrations in
the sample sediments from St Helena Bay (maximum 6000 Rg / g) were more
than double those from Robben Island (maximum 2800 Rg / g). The samples
from the pipeline sites in St Helena Bay had significantly higher trace metal
concentrations than those of the control sites (except for Cr concentration), but
no significant difference was found between the control and pipeline samples at
23
Robben Island. Most environmental variables were correlated with each other.
Positive correlations occurred between all the trace metal concentrations and
each other and the percentage nitrogen. The mean grain size had both positive
(Cd, Cr, Cu, Fe, Zn & % N) and negative correlations (Pb) with the trace metal
concentrations, but only the correlations with Cd, Cr, Zn and % N were
significant. Samples from both sites displayed little evidence of organic or trace
metal enrichment, although, St Helena Bay had higher trace metal and
percentage nitrogen concentrations in the sediments than those from Robben
Island. The reasons may be the length of time which the area has being exposed
to pollutants, as well as the hydrodynamics of the bay which favour the
retention of water along with any substances introduced into the bay.
24
2.1
Introduction
The sedimentary benthic marine habitat is shaped by a large number of environmental
factors, the characteristics of the sediment itself being one of the most important factors. The
shape and compositions of sediment grains provides the microDhabitat for small infaunal
organisms (Fricke & Flemming, 1983). Coarse sediments are found in areas where currents are
strong, whereas fine sediments are found in slowDmoving currents which allow the settlement of
fine particles (Castro & Huber, 2008). Coarse sediments generally have larger interstitial spaces,
are more oxygenated and provide more microDhabitats for infaunal benthic organisms whereas
muddy sediments have fewer interstitial spaces and are less oxygenated, but normally have a
higher organic matter content (Fricke & Flemming, 1983). The ability of the sediment to trap
organic matter is an important factor determining the ability of the environment to sustain
organisms (Fricke & Flemming, 1983). The permeability of sediments also plays a large role in
the adsorption or precipitation of trace metals out of porewater as sulphides, carbonates,
phosphate phases or solid hydroxides, as more permeable sandy sediments allow transport
through the interstitial space (Huettel
., 1998). Sediments act as sinks and accumulate
contaminants that are introduced into an aquatic system as a result of effluents or runoff from a
variety of natural and anthropogenic activities (Mucha
., 2003). Many contaminants are
rapidly adsorbed to suspended sediments and organic matter and in this way are scavenged from
the water column through flocculation, coagulation and sedimentation (Newman & Watling,
2007).
Organic matter in the oceans is produced as a result of primary production and
additionally, the benthic environment receives input from sinking detritus (Fricke & Flemming,
1983). Bacteria are largely responsible for the breakdown of energy– rich organic compounds to
carbon dioxide, water and ammonia (Clark, 1993). If the addition of organic material is greater
than the rate at which bacteria can break down the material, accumulation may result and can
lead to deoxygenation of environments (Clark, 1993). Nitrogen and phosphorous are regarded as
limiting elements for biological production in aquatic systems (Smith
., 2006). When organic
matter input increases, the amount of nitrogen recycled by benthic organisms increases, which
results in higher phytoplankton production when it is returned to the surface waters, and this in
turn leads to an increase in organic carbon (Mojtahid
2009). Nutrient enrichment, besides
25
causing an increase in biological activity, has also been found to change the biotic community
structure in marine ecosystems (Smith
2006). While eutrophication is a natural process in
many aquatic systems, an unnatural increase in limiting nutrients like nitrogen and phosphorous
can cause a significant increase in organic carbon deposited on the seafloor (Mojtahid
.,
2009). Humans using water to dispose of waste have been found to increase the load of nitrogen
and phosphorous in the world’s rivers, lakes and oceans (Smith
., 2006). Nitrogen pollution
is regarded as one of the greatest consequences of anthropogenic global change on the coastal
oceans, and has been found to be highest near areas of intense agricultural activity and urban
development, and is the leading cause of the increase in eutrophication observed in coastal
systems (Howarth & Marino, 2006).
Trace metals are normally present in marine sediments and are necessary for the growth
of phytoplankton and the catalysis of biological reactions (Libes, 1992). The natural occurrence
of trace metals sometimes complicates assessments as a high trace metal concentration may not
necessarily be as a result of anthropogenic enrichment (Mucha
., 2003). Trace metals,
halogenated hydrocarbons, DDT and PCB’s are not bioDdegradable and can become a permanent
addition to the environment and may accumulate in body tissues and bioDmagnify up the food
web (Abel, 1996). The toxicity of trace metals depends on the form in which they are present in
the environment. Metals can form complexes with organic compounds or inorganic molecules;
complexes with organic compounds tend to be more toxic to organisms than those with inorganic
molecules (Clark, 1993). Toxic heavy metals that are most affected by human activity are those
with high enrichment factors and slow clearance rates such as Cd, Cu, Cr, Pb, Zn and Hg (Libes,
1992). Abnormally high trace metal concentrations in sediments have been found to have
negative effects on the diversity of organisms and some areas have even been reported that are
devoid of any benthic organisms (Scott
., 2001; Ferraro
., 2006).
While trace metals are important in the normal functioning of the marine benthos, excess
amounts of any of these substances can lead to a highly polluted environment. Pollution is
defined here as occuring when a substance or material is added to an environment above the
natural level and causes harm to the system (O’ Neill, 1993). Pollutants reach the sea via various
sources, for example, point sources, river runDoff, shipping, offshore dumping and atmospheric
inputs. Globally, the greatest volume of discharge is composed of organic material (Clark, 1993).
26
The aim of this chapter is to examine the structure and chemistry of the sediments at two
study areas on the west coast of South Africa, namely, St Helena Bay and Robben Island in order
to understand the abiotic environment of the foraminifera studied in chapters 3 and 4. These sites
were identified as being potentially polluted as they are both exposed to discharge from
pipelines.
2.2
Materials and Methods
2.2.1
Field Sampling
Sampling in St Helena Bay took place during September 2003. Nine sites were randomly
selected around the pipeline within a 150 m radius of the outfall (Fig. 2.1). Three control sites
were selected ((SPA) 3.6 km, (SPB) 1.5 km and (SPC) 0.9 km away from the pipeline with
similar depths to stations around the pipeline (Fig. 2.1). The approximate depth of all sampling
sites was 4 m. Sites were chosen of similar depth in order to eliminate depth as a potential
variable as depth has been shown to determine differences in abundance, diversity and
community structure within the marine environment (Sajan
., 2010).
Sampling at Robben Island took place during February 2004. Eight sites were randomly
selected, five within a 225 m radius around the opening of the outfall and three control sites (Fig.
2.2). Two of the control sites were on the western side of the harbour 190 m and 300 m from the
pipeline and one on the same side as the pipeline but 190 m away. These sites were chosen as
they are situated away from the direction of the outfall plume (Fig. 2.2). Again, an attempt was
made to choose sites of similar depth in order to eliminate depth as a potential variable, although
this was not always possible as depth varies greatly within the area.
In both areas, sampling was conducted by SCUBA using modified
(Fleeger
., 1988). Each corer was 30 cm in length and 3.57 cm in internal diameter (10 cm2 area). Six
cores were obtained at each site, because foraminifera (like most meiofauna) are known to be
patchily distributed and many replicates are required to provide an overall picture of distribution in
the area (Harrad
., 2008). Samples were kept on ice on the boat and transferred to the freezer
on return to the laboratory.
27
2.2.2
Laboratory Analysis
Only the top 5 cm of each sediment core was examined. SubDsamples of the core were
used for the determination sediment grain size structure, percentage carbon and nitrogen and
trace metal concentration.
2.2.2.1 Sediment Size Structure
Sediments were dried at 60 º C in an oven for 24 hours and each sample was sizeD
fractionated using sieves with mesh sizes of 500 Rm, 250 Rm, 125 Rm and 63 Rm. In order to
determine the sediment size structure, the dry sediment weight in each grain size class was
determined using an analytical balance.
The sediment grain size was converted from Rm to phi units using the formula:
Phi units (ø) = Dlog 2 D, where D = grain diameter in mm (Pfannkuch & Paulson, 2010)
Therefore, < 63 Rm = 5 Phi, 63 Rm = 4 Phi, 125 Rm = 3 Phi, 250 Rm = 2 Phi and 500 Rm = 1
Phi. The mean grain size was calculated using the following formula:
Mean sediment grain size = (ø16 + ø50 + ø84)/ 3 (Pfannkuch & Paulson, 2010).
2.2.2.2 Percentage Total Carbon and Percentage Total Nitrogen
Approximately 5 g of sediment from each station was kept frozen to determine the
percentage of total carbon and the percentage of total nitrogen. Subsamples from each station
were combined, dried and homogenised to produce one sample for each station. The percentage
total carbon and the percentage nitrogen of the 12 stations were determined using a Eurovector
EA CHN Analyser. Combustion of samples in the presence of oxygen was used to determine the
Wt % of total carbon and nitrogen. Detection limits for the Analyzer were 0.1 Wt %. Calibration
was performed using certified Eurovector standards, accepting a margin of error of 0.05 % for
the percentage total carbon and 0.02 % for the percentage nitrogen. Samples were not acidD
digested, therefore, the percentage organic carbon concentrations were not determined.
Because the percentage organic carbon measurements were not measured, data on the
percentage total carbon, total nitrogen and percentage organic carbon concentrations from
Monteiro & Roychoudhury (2005) were analysed for correlations between the percentage
nitrogen and the percentage organic carbon (Fig. 2.3 (a) to (c)). This was conducted to determine
28
whether the percentage nitrogen concentrations could be used as a proxy for the percentage
organic carbon concentrations in St Helena Bay. The correlation between the percentage nitrogen
and the percentage organic carbon using data from Monteiro & Rochoudhury (2005) had a
highly significant rDvalue of 0.918 and pDvalue of < 0.0001. From this, one could conclude that
the percentage nitrogen concentration could be used as a proxy for percentage organic carbon
concentration in the sediments. The percentage total carbon was also significantly correlated
with the percentage organic carbon (R = 0.675) and the percentage nitrogen (R = 0.747).
Unfortunately, no data for the percentage nitrogen and percentage organic carbon could
be found for Robben Island, but it is assumed that relationships established in the one site would
hold good, in this regard, for the other.
While the correlation between the two elements is significant, Kähler and Koeve (2001)
caution against using particular ratios for organic carbon and nitrogen. This is because,
especially during phytoplankton blooms, these elements may be decoupled due to
overconsumption of either one at different stages of the bloom. Ratios may also vary as a result
of depth, biogeography and latitudes, therefore it would be preferable to have both
measurements. However, as a result of an error in the analysis of samples for this study, it is
assumed that there would be a strong relationship between the two elements as previously
reported.
2.2.2.3 Trace Metals
Subsamples of sediments from each core were dried and ground to homogeneity.
Approximately 2 g of sediments were digested using an acid mixture of 4 HCl:1 HNO3 following
Morton & Roberts (1999). A 4:1 ratio was used as it was regarded as a better method for the
digestion of sludges and sediments that are thought to contain high trace metal concentrations.
Sediments were digested at temperatures of 110 ºC on a Gerhardt digestion block for three hours
(Morton & Roberts, 1999). The supernatant was then filtered off and diluted to 100 ml with
distilled water. A UNICAM SOLAAR MDSERIES Atomic Absorption Spectrometer was used to
determine trace metal concentrations of the sediments. Readings were then taken of Cu, Zn, Pb,
Fe, Cd and Cr.
29
2.2.3
Statistical Analyses
2.2.3.1 Sediment grain size structure
In order to determine whether there were any significant differences within each study
area as well as between the control and pipeline sites in terms of their mean grain size,
STATISTICA v. 9 (Statsoft) was used to conduct a oneDway ANOVA. OneDway ANOVA was
used in this study as there were unequal sample numbers within each group. STATISTICA was
used for the statistical analyses, data management and graphics throughout the study. The Tukey
Honest Significant Difference Test was used as a postDhoc comparison of means (or multiple
comparison test) to determine the significant differences between the means of multiple groups
(Zar, 1999). The Tukey HSD is generally regarded as more conservative than the Fisher LSD test
but less conservative than Scheffe’s Test (Zar, 1999).
In all statistical analyses, a confidence limit of 95 % or p = 0.05 was used; this was
adjusted for multiple testing using the Bonferroni correction (a posteriori) (Hochberg, 1988).
This decreases the risk of making TypeDI statistical errors and pDvalues lower than the Bonferroni
value were then accepted as being significant. The bonferroni adjusted pDvalue was calculated as
the number of variables divided by the significant p – value of 0.05 (Hochberg, 1988).
In order to examine the similarity in the sediment structure of the different stations, a
dendogram representing the cluster analysis of the sediment structure of all samples was
produced using PRIMER (Plymouth Routines in Multivariate Ecological Research) version 6.
PRIMER is a software package that consists of a wide range of univariate, graphical and
multivariate routines for analysing community ecology (Clarke & Gorley, 2006).
Dendograms representing the cluster analysis of samples were produced to visualise
groupings of samples which were most similar to each other, samples within a group are
generally regarded as more similar than those from different groups (Clarke & Warwick, 2001).
Groupings were often determined arbitrarily as no particular cutDoff for a ‘good’ similarity or
distance linkage is provided. Data were log x + 1 transformed and normalised and Euclidean
distance was used to produce a similarity matrix. Transformation of environmental data is used
to justify using Euclidean distance as a dissimilarity measure on normalised data (Clarke &
Gorley, 2006). Euclidean distance is regarded as an appropriate measure for environmental data
(Clarke & Gorley, 2006).
30
2.2.3.2 Percentage Total Carbon and Percentage Nitrogen
To determine whether there were any significant differences between the pipeline and the
control sites and between the two study areas, occurred in the percentage total carbon and the
percentage Nitrogen, a oneDway ANOVA was used. The Tukey Honest Significant Difference
postDhoc comparison of means was used to obtain a significant value.
2.2.3.3 Trace Metal Content of Sediments
In order to determine whether there were significant differences between the control sites
and the pipeline sites of each study area as well as for differences between the two study areas, a
oneDway ANOVA was conducted. The Tukey HSD postDhoc comparison of means was
performed, and a Bonferroni adjusted pDvalue was used to determine significant values.
2.2.3.4 Summary of environmental variables
In order to determine the relationship between the measured environmental variables,
nonDparametric Spearman Rank Order correlations were performed in STATISTICA. NonD
parametric correlations were used as the data set was not normally distributed (Zar, 1999) and a
Bonferroni pDvalue was calculated.
An MDS (multiDdimensional scaling) ordination of all environmental variables of the
each study area as well as the control and pipeline sites was produced in PRIMER. MDS
ordinations were used to plot samples so that their relative distances are in the same rank order as
their relative dissimilarities, this allows for visualisation of the samples (Clarke & Gorley, 2006).
Samples that are similar to each other are close together whilst dissimilar samples are further
apart. The stress level indicates how well the relationships are represented in twoDdimension: the
lower the stress level the better the relationship, little confidence can be placed on ordination
plots where the stress level is > 0.2 (Clarke & Gorley, 2006).The data were first log x + 1
transformed and normalised and Euclidean distance was used (Clarke & Gorley, 2006).
In order to determine whether there were significant differences in the multivariate state
of control and pipeline sites at both study areas, an ANOSIM (Analysis of Similarity) was used.
ANOSIM is used to test the null hypothesis that there were no significant differences between
the two sets of samples which were set
(Clarke & Gorley, 2006). In order to determine
31
the percentage similarity within the control and pipeline sites, as well as the environmental
variables most responsible for determining the average percentage dissimilarity between the sites
and study areas, a SIMPER (Similarity Percentage) was conducted. This provides an indication
of which environmental factors would be most important in structuring the general environment
in the study area.
2.3 Results
2.3.1
Sediment Size Structure
The mean sediment grain size varied across the stations (Fig. 2.4; Appendix 2.1), and
most samples from the sites in St Helena Bay had a smaller mean grain size (1 – 3 Phi; 125 Rm –
500 Rm) than those from Robben Island (all less than 2 Phi; > 250 Rm). The results of a one–way
ANOVA between the mean grain sizes of all stations from Robben Island showed no significant
differences between the control sites (RIF, RIG and RIH) (Table 2.1). RIA and RIC had the
largest mean grain sizes, with RIA being significantly larger than most other sites; RIC was only
significantly larger than RID and RIH.
In St Helena Bay the mean grain sizes of all the sampled stations showed no significant
differences within the control sites (Table 2.2). However there were some significant differences
between SHD and some of the other pipeline sites, and SHF with the control stations and SHA.
The samples from the control sites (2.44 ± 0.35 Phi) in St Helena Bay had a lower mean grain
size (overall) than those from the pipeline sites (1.84 ± 0.7 Phi), and these differences were
significant (F (1, 68) = 11.93; p <0.001) (Table 2.3). Samples from the control sites (0.84 ± 0.18
Phi) of Robben Island had a larger mean grain size than the pipeline sites (1.17 ± 0.48 Phi)
although these differences were not significant (Table 2.3). The mean grain size of the samples
from the control and pipeline sites of Robben Island was significantly larger than those in St
Helena Bay.
The sediment size structure and the percentage contribution of each sediment size class
varied greatly between the St Helena Bay stations (Fig 2.5). Stations SPA, SPB and SPC (the
control sites), as well as SHA and SHI were dominated by a grain size of 3 Phi. Most other
stations were otherwise dominated by the 1 phi grain size. Mud (5 Phi) formed less than 2 % of
the total sediments at most stations except for SHC and SPA which had > 15 % mud. All
32
stations in Robben Island were dominated by the 1 Phi mean grain size and mud formed less than
2 % of the total sediments at each station.
In a cluster analysis of the sediment size structure of all samples, Robben Island samples
grouped separately from those of St Helena Bay although some overlap between the sites did
occur (Fig 2.6). In the St Helena Bay samples, the control and pipeline sites grouped separately,
and although some grouping was evident in Robben Island samples, the distance between
groupings was very small. Samples from all the stations in Robben Island were found to group
together, although there was no apparent structure within groups, suggesting large scale variation
of sediment size at a micro level.
2.3.2
Percentage total carbon and Percentage Nitrogen
The percentage total carbon at each of the stations varied between 1 % and 10 % (Table 2.4).
The percentage total carbon in the samples from Robben Island was higher than observed in St
Helena Bay (Table 2. 4). For St Helena Bay the percentage carbon at site SHD was the highest (7
%), while RIH was highest (10.3 %) around Robben Island. The mean percentage carbon from
the St Helena Bay samples (3.78 %) was significantly lower than that from Robben Island (7.17
%) (F (1, 111) = 125; p = 0.000 1) (Table 2.5(a)). The control sites at both study areas had
significantly higher percentage carbon than those of their corresponding pipeline sites (Table 2.5
(b)) (F (1, 111 = 84.94; p < 0.05).
The percentage nitrogen varied from 0.02 % to 0.8 % in all samples (Table 2. 4). Station
SHD from St Helena Bay was much higher in this regard than the rest of the stations. The mean
percentage nitrogen of Robben Island samples (0.1 %) was significantly lower than the mean
percentage nitrogen of the St Helena Bay samples (0.17 %) (F (1, 111) = 5.69; p = 0.000 1)
(Table 2.5 (a)). The percentage nitrogen in the samples from the pipeline sites of St Helena Bay
(0.2 % ± 0.23%) was significantly higher than from the control sites around Robben Island (0.05
± 0.02 %) (p = 0.02) and St Helena Bay (0.09 ± 0.015 %) (p = 0.05), but not from the pipeline
sites at Robben Island (F (1, 111) = 5.39) (Table 2.5 (b)).
2.3.3. Trace Metals
33
The trace metal content of the sediments in the Robben Island samples were lower than both
the maximum allowable ERL at all sites as well as the South African sediment quality guidelines
(SA SQG) (Fig. 2.7). The mean metal concentration of samples from the control sites were lower
than those from the pipeline sites (Table 2.6).
In the St Helena Bay samples, station SHD was higher than both the ERL and SA SQG for
Cr and Cu concentrations, and station SHG was higher than both the ERL and SA SQG for Cu
(Fig. 2.8). All other trace metal concentrations were lower than the ERL value.
Samples from the pipeline sites had higher trace metal concentrations in the sediments than
the control sites, for both areas, with those from the pipeline sites in St Helena Bay being the
highest (Fig. 2.9). Samples from the control and pipeline sites in St Helena Bay had
concentrations higher than the SA SQG for Cd. Except for the Pb concentrations, samples from
the Robben Island sites were significantly lower than those of St Helena Bay for all the other
trace metals (Table 2.6 (b)). Table 2.6 (a) shows that the pipeline sites in St Helena Bay (PSH)
were significantly higher than all other sites in all trace metals except Pb, where they were only
significantly higher than the control sites in St Helena Bay (CSH) (p < 0.05). CSH was also
significantly higher than all sites for Cd concentration and higher than CRI for Cr concentration.
Although the pipeline sites of Robben Island (PRI) were generally higher than the control sites
(CRI), these differences were not significant.
3.3.4
Summary of environmental variables
NonDparametric Spearman Rank Order correlations of all environmental variables revealed
significant relationships between most of the measured environmental variables (Table 2. 7). The
mean sediment grain size, however, appeared to have the fewest significant correlations with the
other environmental variables, and it only correlated significantly with Cd and Cr .
An MDS of all environmental data for Robben Island and St Helena Bay (stress = 0.08)
showed the Robben Island samples grouped separately from the St Helena Bay samples although
some overlap did occur (Fig 2.10). An ANOSIM between control and pipeline sites of Robben
Island showed a significant difference in environmental variables (Global R = 0.518, p = 0.001).
Although an ANOSIM between the control and pipeline sites of St Helena Bay showed a
significant difference in environmental variables, the rDvalue was low (Global R = 0.167, p =
0.05) which indicated that these differences were not very strong.
34
The MDS which separated the control and pipeline sites of the two study areas, revealed a
large amount of overlap in these samples for both study areas (Fig 2.10). An ANOSIM between
the environmental variables of Robben Island and St Helena Bay showed that these differences
were significant (Global R = 0.404, p = 0.001).
The results of the SIMPER analysis (Table 2. 8) showed that the factors that were most
responsible for the similarity within the Robben Island samples were the trace metals (except Cd)
and the mean sediment grain size. By contrast, the percentage nitrogen and only some of the
trace metals (Zn, Fe, Cu and Pb) were important in the samples from St Helena Bay. The trace
metals and the mean sediment grain size were most responsible for the differences between the
two study areas.
The trace metals and the mean grain size were most responsible for the similarity with the
control sites of Robben Island, whereas the only the trace metals were most responsible for the
similarity within the pipeline sites (Table 2.9). In the pipeline sites of St Helena Bay on the other
hand, the percentage nitrogen was the largest contributor along with the mean grain size and a
few of the trace metals (Cr, Fe and Cu). In the control site, the percentage nitrogen and the mean
sediment grain size contributed very little and the most important contributor to the similarity
within the group was the trace metals.
2.4
Discussion
2.4.1. Sediment Grain Size Structure
Although both study areas were dominated by sediments having a large mean grain size,
those around Robben Island were of a significantly larger mean grain size than those of St
Helena Bay. In both sites, mud was largely absent. Strong water movement tends to wash away
fine material to leave coarse particles in sediments (Castro & Huber, 2008).
Physical
resuspension by heavy wave action can also maintain fine sediments in the water column
resulting in coarser sediments dominating the top 2 cm vertically into the benthos (Wheatcroft &
Butman, 1997). While both study sites were located near the surf zone (which could explain the
dominance of large grains), the presence of coarser sediments in St Helena Bay may also be due
to the presence of calcareous reefs in the vicinity (Monteiro & Roychoudhury, 2005). The
dominance of Robben Island sediments by coarse grains and the absence of mud and fine sand is
more an indication of a highly exposed area with strong wave action (Jury & Bain, 1989). Coarse
35
grains are normally well oxygenated and ideal for infauna but have been found to have less
organic matter as a source of food than fine sand as a result of lower settlement rates in these
environments (Samir & ElD Din., 2001). Therefore, while having the potential microhabitats to
support infauna, food supply may be a limiting factor. In areas with sandy grains, transport of
interstitial water is influenced mainly by bottom currentDsediment interactions, advection and
dispersion (Jahnke
., 2005). Sediment permeability, especially in sandy sediments, plays a
large role in advective transport of metals and remineralization of NH4+ (Huettel
2.4.2
., 1998).
Percentage total carbon and Percentage Nitrogen
Nitorgen in the marine environment stimulates phytoplankton production, which
increases the amount of organic carbon in the system; when phytoplankton die, this organic
carbon reaches the benthos as phytodetritus, which is broken down by the microDoragnisms and
bacteria in the benthos releasing nitrogen into the water column again (Cloern, 2001). Carbon
and nitrogen cycling in the marine environment are thus closely linked.
The percentage total carbon in the samples from St Helena Bay was generally high;
Monteiro & Roychoudhury (2005) observed much the same in their study from St Helena Bay
and also found the concentrations to be higher than most other harbours globally. Bailey (1987)
reported a percentage total carbon of 4 % and percentage nitrogen of 0.5 % in the top 5 cm of the
sediment in St Helena Bay. This high percentage carbon may merely be a result of the
hydrodynamics of the bay, i.e. sluggish flowing, semiDclosed bay with a retention time of
approximately 25 days as opposed to 2 D3 days outside the bay (Walker & Pitcher, 1991) rather
than from high carbon loading from the fish factories. St Helena Bay is also downstream of an
upwelling area and has enhanced primary productivity and high deposition of particulate organic
matter which results in highly organic sediments (Bailey, 1987). In other areas with upwelling,
such as in the Arabian Sea, marine sediment accumulates very rapidly, this material is rich in
organic matter which is derived from pelagic primary production and also tends to be anaerobic
(Murray
., 2002). Carbon reaching the sediments can also be from a number of other sources
like detritus, faecal matter and large zooplankton, in fact, Touratier
. (2003) considered that
only 8.4 % of carbon that reached sediments were found to be a result of primary production in
St Helena Bay.
36
In St Helena Bay, the percentage total carbon from the control sites was significantly
higher than the sites around the pipeline but station SHD was much higher than all other stations.
Site SHD was the station with a high amount of biological material (fish scales and bones) in the
top layer which may account for the presence of the high percentage carbon in the sediments. It
has been suggested by Monteiro & Roychoudhury (2005) that organic carbon loading in St
Helena Bay is of planktonic origin, and alternating upwelling and relaxation events that transport
external blooms from poleward nearshore flow into the retention area. The data presented here
tends to support this as no significant difference was found between the control and pipelines
sites.
In a study of Table Bay, Monteiro (1997) concluded that the organic matter loading was
of natural marine origin linked to the Benguela upwelling system, as well as input from the Salt
and Diep Rivers driven by winter rains, and that land derived organic matter was a samller
contribution. In addition to upwelling it is also thought that organic matter of marine origin is
also advected into the bay during poleward movement of water between upwelling events
(Monteiro, 1997).
The percentage nitrogen in the sediments of St Helena Bay was significantly higher than
those around Robben Island, and the pipeline sites in both study areas were richer in nitrogen
than those of the control sites. Station SHD once again displayed levels higher than all other
stations in both study areas. An increase in the percentage nitrogen input into a system is said to
increase eutrophication of a system by increasing the primary production (Cloern, 2001;
Howarth & Marino, 2006). In a study in St Helena Bay, Touratier
(2003) found that
regeneration of nutrients from the sediments was important in the pelagic productivity of the area
and that nitrogen recycling did not only come from nitrates but also from ammonia, urea and
other forms so that the area is not nitrogen limited as in most marine environments. Verardo &
McIntyre (1994 in Twichell
., 2002) found that areas with high carbon but low nitrogen
result from more rapid loss of nitrogen than carbon because nitrogenDrich proteinaceous matter is
more readily utilized by microbes than carbohydrate components. It does appear that the effluent
from the fish factory has a localized effect displayed by the higher percentage nitrogen closest to
the outlet.
37
2.4.3. Trace Metals
Trace metals occur naturally in the marine environment, and in order to assess whether
trace metals have natural or enriched levels it is necessary to normalize the concentration against
the regional background values (Herut & Sandler, 2006). Normalisation of trace metals against
iron or aluminium in marine sediments is important as it effectively takes granulometry and
organic matter content into account (Newman & Watling, 2007). Different trace metals have
different affinities to sediments and their organic matter content. For example, anthropogenic Cd
and Hg have a stronger affinity to organic matter than to clays (Herut & Sandler, 2006). No
baseline data was available for the study areas and therefore, no normalisation of the trace metal
data could be performed. As a consequence, it was not possible to determine if any of the sites
were enriched (above background) and hence polluted.
With the exception of Pb, all other measured trace metals occurred at significantly higher
concentrations in samples from St Helena Bay than Robben Island. No significant difference was
found between the metal concentrations of the control and pipeline sites around Robben Island,
but all the measured trace metals (except Cr) were significantly higher in the samples from the
pipeline sites in St Helena Bay. Station SHD was higher than all the other stations and appears to
be the point of deposition and accumulation in St Helena Bay because it was found to be higher
in organic carbon, nitrogen and trace metals than all other sites. A high organic carbon input is
thought to lead to the accumulation of trace metals, due to changes in the redox potential and
accompanying eutrophication when sediments become anoxic (Monteiro
., 1999). In
retention zones associated with upwelling, as in St Helena Bay and Robben Island, complex
biological, chemical and physical processes also control the trace metal variability and it has
been suggested that the dominant source of trace metals in the benthos is from phytoplankton
and newly upwelled water from the South Atlantic (Monteiro & Roychoudhury, 2005). Trace
metal concentrations in sediments and suspended matter are also found to be several orders of
magnitude higher than those in the dissolved phase and are likely to be found in areas where
finer sediments (< 200 Rm) accumulate (Monteiro, 1997). This may explain the higher trace
metal concentrations of St Helena Bay (mean grain size < 250 Rm) as opposed to Robben Island
(> 250 Rm). In this study there was a definite correlation between the sediment grain size and
some of the trace metal concentrations (Cd, Cr and Zn).
38
Trace metals that are at levels higher than permissible ERL levels (below this level adverse
biological effects are rarely observed) and ERM levels (levels between ERL and ERM or higher
than ERM are where adverse biological effects are observed) are a cause for concern
(Bjørgesæter & Gray, 2008). The metals considered toxic to most marine life are, in descending
order of toxicity, mercury, cadmium, silver, nickel, selenium, lead, copper, chromium, arsenic
and zinc (Islam and Tanaka, 2004). The levels of Cd, Cr, Cu and Zn were significantly higher in
St Helena Bay samples than in Robben Island, suggesting potentially toxic trace metals. This is
also supported by the fact that the higher trace metal concentrations were at the pipeline sites in
St Helena Bay and that the area is impacted by the fish factory and possibly the other activities
within the bay.
Monteiro & Roychoudhury (2005) reported values lower than the world average for trace
metal concentrations with the lowest trace metal concentrations near the shore and the highest
near the middle of the bay; sites corresponding with those of this study share similar
concentrations of trace metals in the sediments. These concentrations of trace metals were much
higher than those of Robben Island (this study), Table Bay (Cu), Saldanha Bay (Cu, Cd, Pb), but
lower than the highest concentrations in Sidney, Kenya, Hong Kong, Dutch Wadden Sea, NW
Mediterranean and Gulf of Thermaikos, Greece which were used in the comparison of Monteiro
(1997).
Trace metal concentrations from samples around Robben Island were lower than those
reported from Prochazka (2003). However, it has since been established that incorrect
calculations were used by Prochazka (pers. comm.).
The biological uptake and the toxicity of trace metals depends on which free ions they
combine with; for example with, chloride, carbonate, hydroxide or sulphide (Cherchi
.,
2009). When trace metals bind with sulphides, they form an insoluble species that concentrates
the metals in the sediments (Monteiro & Scott, 2001). In an environment where the organic
carbon loading is very high, trace metals remain within the system by binding with sulphides and
will only remobilize when resuspended during storms or dredging (Monteiro
, 1999). The
trace metal concentrations, in this study, were positively related with the percentage nitrogen.
Most studies that have reported a high anthropogenic input of organic matter have noted a
high concentration of trace metals. However, trace metals may be partitioned between residual
organic matter, terrigenous clays and sulphide complexes in St Helena Bay and Robben Island
39
(Monteiro & Roychoudhury, 2005). A large percentage of marine trace elements are also
scavenged onto FeDoxyhydroxides (especially Ni, Cd, As, Pb and Cu) or complexed with large
aggregates or colloids, which is not necessarily organic carbon (Powell
., 1996). Iron may,
therefore, control the concentrations of other trace metals in the seawater and may exhibit nonD
conservative removal of FeDoxyhydroxides and nonDlabile organic complexes (Powell
.,
1996). The concentration of Fe in St Helena Bay was almost double that of Robben Island and it
is possible that Fe is controlling the concentrations of trace metals more so than the
concentration of organic compounds.
Therefore a semiDclosed sheltered bay, not easily affected by storms, like St Helena Bay, will
tend to trap and accumulate these trace metals as resuspension would not take place on a regular
basis. The observed strong correlation between the trace metals suggests that their input is from a
common source (Monteiro & Roychoudhury, 2005).
2.5
Conclusions
Spatial variability within the sediments of the benthos was extremely marked. Variability
often occurs as a result of the fluctuations of food supply as a result of different settlement rates
of phytodetritus, in addition, faunal tubes and burrows can influence spatial distribution of
organic matter which is being transported by currents (Lavigne
., 1997). There is also
considerable variability in the supply of organic matter to the sediment as a result of spatial and
temporal differences in the rates of primary production and zooplankton grazing, chemical and
hydrographic regimes in the water column and environmental conditions (Gee
., 1985).
The two study areas had obvious environmental differences. St Helena Bay has been
exposed to effluent since 1945 with the opening of the fish factories whereas the sewage plant of
Robben Island has only been discharging since 2002. The very obvious differences are in both
the nitrogen and trace metals concentrations which were much higher in St Helena Bay samples
than Robben Island. St Helena Bay thus should be constantly monitored. Besides the length of
time that St Helena Bay has been exposed and the level of exposure, the two bays have very
different hydrodynamics. Robben Island will experience fewer effects from anthropogenic
inputs, as the strong winds and the turbulence within Table Bay allows very little settling. The
wind direction is also highly variable and the plume from the sewage plant will change
accordingly, therefore settlement of substances does not consistently occur in one particular area.
40
St Helena Bay appears to be more at risk than Robben Island because the bay is not as turbulent
and is not exposed to high winds and therefore pollutants will more easily settle. The sewage
pipeline of Robben Island does not appear to pose any risks to the area directly and provided that
the input does not increase dramatically does not appear to be causing any changes in the levels
of naturally occurring elements.
41
(a)
Figure 2.1:
(b)
Map of St Helena Bay illustrating the position of the sampling sites (a) as well as those around the pipeline (b).
(SHA to SHI are the pipeline sites and the control sites are SPA to SPC) (http://maps.google.com).
42
Figure 2.2:
Map of Robben Island illustrating the position of sampling sites around the pipeline (RIA to RIE) and the control sites
(RIF to RIH) (http://maps.google.com).
43
8
2.6
7
2.4
2.2
6
1.8
% Total Nitrogen
% Organic Carbon
2.0
5
4
3
2
1.6
1.4
1.2
1.0
0.8
0.6
1
0.4
0
D1
D1
0.2
0.0
0
1
2
3
4
5
6
7
8
9
D0.2
D2
% Total Carbon
0
2
4
6
8
10
12
14
16
% Total Carbon
(a)
8
(b)
7
% Organic Carbon
6
5
4
3
2
1
0
D1
D0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
% Total Nitrogen
(c)
Figure 2.3 (a) to (c): Correlations of the percentage total carbon, percentage organic carbon and percentage total nitrogen
using data collected from St Helena Bay by Monteiro & Roychoudhury (2005). Correlation coDefficients are
(a) R = 0.675 (b) R = 0.747 (c) R = 0.919.
44
Mean grain size (Phi)
RIA
RIB
RIC
RID
RIE
RIF
RIG
RIH
SPA SPB SPC SHA SHB SHC SHD SHE SHF SHG SHH
SHI
Station
Figure 2.4:
The mean grain size (Phi) and the standard error (n = 6) for each of the sampling stations at Robben Island, RIA to RIE
are pipeline stations and RIF to RIH are control stations, and St Helena Bay, SPA to SPC are control stations and SHA
to SHI are pipeline stations. Refer to Fig. 2.1 and Fig. 2.2 for the location of each station.
45
Table 2.1:
The following are the results of a oneDWay ANOVA performed on the mean sediment grain size (Phi) of all cores for
each site in Robben Island. For a postDhoc comparison of means, the Tukey Honest Significant Difference (HSD) Test
was performed to obtain a statistical significance. F (7, 39) = 7.16. Significance at p < 0.05* after the Bonferroni
adjustment.
RIA
RIB
RIC
RID
RIE
RIF
RIG
RIH
Mean Grain Size 1.73
1.06
1.30
0.70
1.09
0.85
0.96
0.72
RIA
RIB
0.01
RIC
0.27
0.87
RID
0.00*
0.49
0.03
RIE
0.02
1.00
0.93
0.38
RIF
0.00*
0.94
0.26
0.99
0.89
RIG
0.00*
1.00
0.55
0.83
1.00
1.00
RIH
0.00*
0.55
0.04
1.00
0.44
1.00
0.88
46
Table 2.2:
Results of the oneDway ANOVA performed on the mean sediment grain size (Phi) of all cores of St Helen Bay.
Levene’s test for homogeneity of variances did not show a significant result (p = 0.11). For a postD hoc comparison of
means, the Tukey Honest Significant Difference (HSD) Test was performed to obtain a statistical significance. F (11,
58) = 8.92. Significance at p < 0.05 * and in bold type.
SPA
SPB
SPC
SHA
SHB
SHC
SHD
SHE
SHF
SHG
SHH
SHI
2.44
2.44
2.45
2.38
1.93
2.16
3.22
1.38
1.12
1.48
1.55
1.81
MEAN
GRAIN
SIZE
SPA
SPB
1.00
SPC
1.00
1.00
SHA
1.00
1.00
1.00
SHB
0.80
0.80
0.79
0.92
SHC
1.00
1.00
1.00
1.00
1.00
SHD
0.35
0.35
0.36
0.23
0.00
0.04
SHE
0.01
0.01
0.01
0.02
0.70
0.19
0.00*
SHF
0.00*
0.00*
0.00*
0.00*
0.14
0.01
0.00*
1.00
SHG
0.03
0.03
0.03
0.07
0.90
0.39
0.00*
1.00
0.98
SHH
0.07
0.07
0.06
0.12
0.97
0.56
0.00*
1.00
0.93
1.00
SHI
0.50
0.50
0.49
0.68
1.00
0.99
0.00*
0.93
0.34
0.99
1.00
47
Table 2.3:
Results of the oneDway ANOVA performed on the mean sediment grain size (Phi) of all cores for each of the sampling
sites. The Tukey Honest Significant Difference (HSD) Test postDhoc comparison was performed to obtain a statistical
significance. F (1, 111) = 31.89. Significant at p < 0.05 * after the Bonferroni adjustment. Pipeline Robben Island
(PRI), Control Robben Island (CRI), Control St Helena Bay (CSH) and Pipeline St Helena Bay (PSH).
PRI
CRI
CSH
PSH
1.17
0.84
2.44
1.86
CRI
0.22
CSH
0.000 1*
0.000 1*
PSH
0.000 1*
0.000 1*
0.002*
48
120
100
n
o
it
u
b
ir
t
n
o
C
eg
a
t
n
ec
re
P
5 Phi
80
4 Phi
60
3 Phi
40
2 Phi
1 Phi
20
0
A
I
R
B
I
R
C
I
R
D
I
R
E
I
R
F
I
R
G
I
R
H
I
R
A
P
S
B
P
S
C
P
S
A
H
S
B
H
S
C
H
S
D
H
S
E
H
S
F
H
S
G
H
S
H
H
S
I
H
S
Stations
Figure 2.5:
The mean percentage contribution of each sediment size class of the total sediment weight for each of the stations
sampled in Robben Island and St Helena Bay.
49
6
site
PRI
CRI
CSH
PSH
Distance
4
2
RIG1
RIG5
RIF1
RIH6
RIH4
RIF5
RIH1
RIH5
RIF2
RIH2
RIC6
RIF4
RIG2
RIG6
RIG3
RIG4
RIE4
RIE1
RIE2
RIE3
RIE5
RIE6
SHI5
SHF5
SHF4
RID2
RID5
RIC3
SHF6
RIF3
SHB5
RIB3
RIB6
RIA1
RIB1
SHI2
RIA6
RIC2
SHE6
RIC1
RID6
SHG1
RIB2
RIB5
RID4
SHG6
SHE2
SHG3
RIA4
RIC5
SHG4
SHI1
RID1
RID3
SHE4
RIC4
SHE3
RIA3
RIB4
RIH3
SHF3
SHE5
SHF2
SHA4
SHC5
SHD2
SHD5
SHC6
SHD3
SHD4
SHA6
SHB1
SHG5
SHC1
SHC2
SHH2
SHC4
SHH5
RIA2
RIA5
SHC3
SHF1
SPA6
SPA3
SHG2
SHA3
SPB3
SHB6
SHH3
SHE1
SHI3
SPB2
SPB5
SPA4
SPA5
SPC5
SHA1
SPC6
SPB4
SHA2
SPC1
SPC2
SPC3
SPB6
SPC4
SHA5
SHB2
SHB3
SHH1
SPB1
SPA1
SHI4
SHI6
SHH4
SPA2
0
Samples
Figure 2.6:
Dendogram representing the cluster analysis of the sediment structure of each sample in Robben Island and St Helena
Bay. These data were log x + 1 transformed and Euclidean distance was used in the analysis. (PRI is the pipeline
stations at Robben Island, CRI is the control stations at Robben Island, CSH is the control stations of St Helena Bay
and PSH refers to the pipeline stations of St Helena Bay. Each of the samples is labelled according to the station and
the core number. Refer to Figs. 2.1 and 2.2 for the location of each station.
50
Table 2.4:
Results of the percentage total Carbon and the percentage total Nitrogen measured samples collected from around
Robben Island (RIA to RIH) and St Helena Bay (SPA to SHI), as well as that for the various sites and a mean for the
two study areas.
Station
RIA
RIB
RIC
RID
RIE
RIF
RIG
RIH
SPA
SPB
SPC
SHA
SHB
SHC
SHD
SHE
SHF
SHG
SHH
SHI
Mean RI
Mean SH
Control RI
Pipeline RI
Control SH
Pipeline SH
Site
Pipeline
Pipeline
Pipeline
Pipeline
Pipeline
Control
Control
Control
Control
Control
Control
Pipeline
Pipeline
Pipeline
Pipeline
Pipeline
Pipeline
Pipeline
Pipeline
Pipeline
% total N
0.16
0.14
0.22
0.09
0.04
0.08
0.02
0.05
0.08
0.09
0.11
0.07
0.17
0.14
0.80
0.1
0.13
0.24
0.08
0.08
0.1
0.17
0.05
0.13
0.09
0.2
% total C
4.97
5.89
6.75
7.78
5.22
9.48
7.34
10.30
4.77
4.44
4.33
3.71
4.29
3.02
7.52
2.92
2.67
4.15
1.51
2.00
7.17
3.78
9.01
6.12
4.51
3.51
51
Table 2.5:
The following represents the oneDway ANOVA performed on the total % Nitrogen and % Carbon between the study
areass (a) and the sites (b). RI refers to Robben Island and SHB to St Helena Bay; PRI is the pipeline stations at
Robben Island, CRI is the control stations at Robben Island, CSH is the control stations of St Helena Bay and PSH
refers to the pipeline stations of St Helena Bay. The Tukey Honest Significant Difference postDhoc comparison of
means was performed to obtain a significant value (p < 0.05) * after the Bonferroni adjustment. F (1, 111).
(a)
study area % N
F
5.69
Mean
RI
0.100
SHB
0.168
RI
p
0.000*
%C
125
Mean
7.168
3.782
RI
P
0.000*
(b)
Site
%N
Mean
F
PRI
CRI
CSH
PSH
5.39
0.130
0.048
0.093
0.195
PRI
p
0.25
0.83
0.22
CRI
p
CSH
p
%C
Mean
PRI
p
CRI
p
CSH
p
0.79
0.002* 0.05
84.99
6.122
9.014
4.513
3.518
0.000*
0.000* 0.000*
0.000* 0.000* 0.029
52
0.14
6000
Cd ERL = 1.2 ug/g
ERM = 9.6 ug/g
SA SQG = 0.3 ug/g
0.12
0.10
Fe ERL = ?
ERM = ?
5000
Iron ug/g
Cadmium
4000
0.08
0.06
3000
2000
0.04
1000
0.02
0.00
0
RIA
RIB
RIC
RID
RIE
RIF
RIG
RIH
C
P
RIA
RIB
RIC
RID
RIE
RIF
RIH
C
P
30
12
28
Cr ERL = 81 ug/g
ERM = 370 ug/g
SA SQG = 50 ug/g
10
Pb ERL = 46.7 ug/g
ERM = 218 ug/g
SA SQG = 100 ug/g
26
24
22
20
8
18
Lead ug/g
Chromium ug/g
RIG
6
16
14
12
10
4
8
6
2
4
2
0
0
RIA
RIB
RIC
RID
RIE
RIF
RIG
RIH
C
RIA
P
RIB
RIC
RID
RIE
RIF
RIG
RIH
C
P
20
14
10
16
14
8
Zinc ug/g
Copper ug/g
Zn ERL = 150 ug/g
ERM = 410 ug/g
SA SQG = 150 ug/g
18
Cu ERL = 34 ug/g
ERM = 270 ug/g
SA SQG = 50 ug/g
12
6
12
10
8
4
6
2
4
0
2
0
D2
RIA
RIB
RIC
RID
RIE
RIF
RIG
RIH
C
P
RIA
Station
Figure 2.7:
RIB
RIC
RID
RIE
RIF
RIG
RIH
C
P
Stations
Graphs illustrating the means and standard errors of the trace metal concentration in the sediments at the Robben Island
stations as well as the mean for the control (C) and pipeline (P) sites.
53
1.6
8000
Cd ERL = 1.2 ug/g
ERM = 9.6 ug/g
SA SQG = 0.3 ug/g
1.4
6000
1.0
5000
Iron ug/g
Cadmium ug/g
1.2
0.8
4000
0.6
3000
0.4
2000
0.2
1000
0.0
0
SPA SPB SPC SHA SHB SHC SHD SHE SHF SHG SHH SHI
C
P
SPA SPB SPC SHA SHB SHC SHD SHE SHF SHG SHH SHI
C
P
SPA SPB SPC SHA SHB SHC SHD SHE SHF SHG SHH SHI
C
P
35
35
Cr ERL = 81 ug/g
ERM = 370 ug/g
SA SQG = 50 ug/g
30
30
25
25
20
20
Lead ug/g
Chromium ug/g
Fe ERL = ?
ERM = ?
7000
15
15
10
10
5
5
0
0
D5
SPA SPB SPC SHA SHB SHC SHD SHE SHF SHG SHH SHI
C
P
160
120
Cu ERL = 34 ug/g
ERM = 270 ug/g
SA SQG = 50 ug/g
100
140
120
100
Zinc ug/g
Copper ug/g
80
60
80
60
40
40
20
20
0
0
D20
D20
SPA SPB SPC SHA SHB SHC SHD SHE SHF SHG SHH SHI
C
P
SPA SPB SPC SHA SHB SHC SHD SHE SHF SHG SHH SHI
Station
Figure 2.8:
C
P
Station
Graphs illustrating the means and standard errors of the trace metal concentration in the sediments at the sites sampled
St Helena Bay as well as the mean for the control (C) and pipeline (P) sites.
54
4500
0.9
0.8
0.7
Cd ERL = 1.2 ug/g
ERM = 9.6 ug/g
SA SQG = 0.3 ug/g
4000
Fe ERL = ?
ERM = ?
3500
3000
0.5
Iron ug/g
Cadmium ug/g
0.6
0.4
0.3
2500
2000
0.2
1500
0.1
1000
0.0
D0.1
500
PRI
CRI
CSH
PSH
PRI
14
13
12
11
CSH
PSH
Pb ERL = 46.7 ug/g
ERM = 218 ug/g
SA SQG = 100 ug/g
9
Cr ERL = 81 ug/g
ERM = 370 ug/g
SA SQG = 50 ug/g
8
7
9
6
Lead ug/g
Chromium ug/g
10
CRI
10
8
7
5
6
4
5
3
4
2
3
1
2
1
PRI
CRI
CSH
0
PSH
PRI
30
25
20
CRI
CSH
PSH
CSH
PSH
80
70
Cu ERL = 34 ug/g
ERM = 270 ug/g
SA SQG = 50 ug/g
60
Zn ERL = 150 ug/g
ERM = 410 ug/g
SA SQG = 150 ug/g
Zinc ug/g
Copper ug/g
50
15
10
40
30
20
5
10
0
0
D10
D5
PRI
CRI
CSH
Site
Figure 2.9:
PSH
PRI
CRI
Site
Graphs illustrating the means and standard errors of the trace metal concentration in the sediments at Robben Island
(PRI and CRI) and St Helena Bay (CSH and PSH), P = pipeline sites and C = control sites.
55
Table 2.6:
The following tables represent the ANOVA performed on the trace metal concentrations in the sediments between the
sites (a) and the study areas (b). The Tukey Honest Significant Difference postDhoc comparison of means was
performed to obtain a significant value (p < 0.05) *, F (1, 111).
(a)
Site
F
PRI
CRI
CSH
PSH
Site
F
PRI
CRI
CSH
PSH
(b)
study
F
RI
SHB
Cd
7.47
Means
0.085
0.031
0.440
0.743
Fe
11.43
Means
1819.7
847.0
1470.2
3586.5
Cd
75.38
Means
0.0656
0.66247
PRI
CRI
CSH
p
p
p
0.955
0.005*
0.000*
0.004*
0.000*
0.011*
PRI
CRI
CSH
p
p
p
0.382
0.936
0.001*
RI
p
0.000*
0.793
0.000*
Cr
36.248
Means
4.251
11.362
0.0018
RI
p
0.000*
Cr
13.7
Means
5.157
2.651
9.438
12.054
Pb
4.52
Means
7.015
3.658
1.607
8.053
Cu
8.065
Means
3.042
17.297
PRI
CRI
CSH
p
p
p
0.541
0.098
0.000*
0.008*
0.000*
0.415
PRI
CRI
CSH
p
p
p
0.405
0.056
0.921
RI
p
0.005*
0.827
0.127
Fe
14.854
Means
1467.9
3026.3
0.007*
RI
p
0.000*
Cu
5.66
Means
4.059
1.248
2.296
22.698
Zn
22.44
Means
10.895
4.446
7.405
63.910
Pb
0.005
Means
5.8
6.346
PRI
CRI
CSH
p
p
p
0.984
0.996
0.012*
0.999
0.019*
0.024*
PRI
CRI
CSH
p
p
p
0.936
0.988
0.000*
0.995
0.000*
0.000*
RI
p
0.699
Zn
27.266
Means
8.563
48.953
RI
p
0.000*
56
Table 2.7:
Results of the NonDparametric, Spearman Rank Order Correlations between all environmental variables measured
showing R Values. Significant RDvalues are at p < 0.05 after the Bonferroni adjustment.
Cd
Cr
Cu
Fe
Pb
Zn
%N
Cd
Cr
0.740*
Cu
0.625*
0.677*
Fe
0.595*
0.749*
0.896*
Pb
0.332
0.509*
0.717*
0.716*
Zn
0.730*
0.702*
0.881*
0.848*
0.679*
%N
0.414*
0.554*
0.653*
0.663*
0.434*
0.592*
Mean grain size
0.552*
0.470*
0.115
0.156
D0.209
0.259
0.240
57
2D Stress: 0.08
Study Area
RI
SH
Figure 2.10:
MDS ordination of the two study areas sampled using all environmental data. The data were log x+1 transformed and
normalised. Euclidean distance was used to plot the samples. RI refers to Robben Island and SH to St Helena Bay.
58
Table 2.8:
SIMPER (Similarity Percentage) of the two study areas using all environmental variables. A resemblance matrix using
Euclidean distance was used in the analysis. Table (a) represents the average similarity between the four groups. The
values in bold represent the environmental variables which contribute most to the similarity within each group. Table
(b) represents the average dissimilarity between the two study areas and the environmental factors most responsible for
the dissimilarity between the two study areas.
(a)
(b)
Site
RI
SH
Average squared distance
3.91
7.47
Environmental factor
% contribution
% contribution
Cd
4.83
%N
Groups RI & SH
Average squared distance
19.52
Environmental Variable
% Contribution
5.51
Cd
17.35
7.1
19.03
Mean Grain size
14.22
Mean Grain size
10.56
9.83
Cr
14.22
Zn
13.13
12.36
Zn
12.49
Fe
14.03
15.22
Cu
11.56
Cr
15.42
8.63
Fe
10.81
Cu
16.99
13.1
Pb
9.68
Pb
17.93
16.33
59
Table 2.9:
SIMPER (Similarity Percentage) of the control and pipeline sites of both sites using all environmental variables. A
resemblance matrix using Euclidean distance was used in the analysis. The following table represents the average
similarity between the four groups. The values in bold represent the environmental variables which contribute most to
the similarity within each group.
Site
PRI
CRI
PSH
CSH
3.2
2.59
6.98
3.01
Environmental factor
% contribution
% contribution
% contribution % contribution
Cd
1.84
4.8
4.22
19.52
Zn
5.61
19.96
8.84
10.35
%N
7.81
1.76
25.96
0.37
Cr
13.7
17.61
11.13
9.3
Fe
13.71
11.46
17.03
15.4
Mean Grain Size
15.31
4.64
11.74
4.16
Cu
18.35
18.89
12.19
11.14
Pb
23.67
20.88
8.89
29.76
Average
squared distance
60
Chapter 3
The assemblage structure of foraminifera in two study areas along the SW coast of
South Africa
Abstract
Sediment samples from around the Robben Island sewage pipeline and
a fish factory pipeline in St Helena Bay were examined for foraminifera.
Twelve stations were sampled in St Helena Bay and eight in Robben Island,
six cores per station were examined. The top 5 cm of sediments within each
core were examined. Foraminifera were sizeDfractioned (63 Rm, 125 Rm, 250
Rm and 500 Rm) and counted. A total of 300 foraminifera per samples were
picked, separated into live or dead and identified to species level.
A total of 38 morpho species in the live assemblages were identified
from both study areas. Samples from Robben Island had a significantly higher
species richness (34) than those from St Helena Bay (28). The mean species
diversity of the samples from St Helena Bay (1.69 ± 0.06) was significantly
lower than that of samples from around Robben Island (2.17 ± 0.04), although
the abundance of foraminifera in samples from St Helena Bay (537 ± 109)
was higher than that from Robben Island (236.3 ± 23.6). The species diversity
was lowest at the pipeline stations in St Helena Bay and highest at the Robben
Island control sites. Species accumulation curves reached an asymptote,
indicating that the sampling effort was sufficient.
Samples from St Helena Bay were dominated by
and bolivinids, while those from
Robben Island contained lower numbers of
and a
dominance of
and miliolids. The dominance of
bolivinids and
and the rarity of miliolids in St Helena Bay samples
may be a result of organic matter accumulation and sedimentation due to the
high retention time within the bay.
The structure of assemblages from St Helena Bay was different to that
of Robben Island, although variability within the cores of each station was
61
very high, attesting to small scale variability/patchiness within the benthic
environment. Samples from both study areas had a dominance of small
foraminifera which may be a result of the cold temperate waters.
A significant relationship was found between the generic data and the
species data of the live assemblages.
This was conducted to determine
whether generic data could be used as a proxy for species, in a study of this
type, and whether they would provide sufficient information for interpretation,
a relate statistic was performed.
The dead assemblages were examined separately to give an indication
of the effect of taphonomic processes (such as transport and test dissolution).
Although significant correlations were found between the dead and live
assemblages were found, the correlation coDefficients were all low. The
correlation between the live and dead assemblages in St Helena Bay samples
(0.388) were lower than those in samples from around Robben Island (0.551)
which indicates greater accumulation of dead tests, which could be an
indication of a depositional environment. The rate of deposition within St
Helena Bay could increase the risk of accumulation of pollutants.
62
3.1
Introduction
Communities in the marine benthic environment often show a humpDshaped
relationship between diversity and depth. Shallow areas are typically less diverse due to
the dominance of opportunistic species which are adapted to the fluctuating environment,
while midDdepth waters are often more diverse due to greater stability, and very deep
water shows another decrease due to less habitat variability (Flint & Holland, 1980). The
factors that appear to govern the depth distribution of taxa in the marine environment are
light transparency, a decrease in temperature and hydrodynamic energy (Cleary
2005 in Samaai
.,
., 2010). The soft sediments of shallow water environments have
been found to be dominated by polychaetes, while deposit feeding mollusks and
crustaceans dominate the midDdepths and no particular dominance is found in the deep
waters (Flint & Holland, 1980). Sponges off the east coast of South Africa appear to
follow this trend of decreasing diversity with depth (Samaai
., 2010).
Latitudinal gradients of species richness in the marine environment appear to follow
the same pattern as those of the terrestrial environment, that is, a decrease in species
richness with an increase in latitude (Hillebrand, 2004). These gradients are thought to be
a result of seasonal variability and the greater range of environmental conditions
experienced at higher latitudes (Samaai
., 2010). Weak gradients have been found in
aquatic macrophytes, sediment infauna and unicellular eukaryotes; the weak gradient in
unicellular eukaryotes like diatoms and other protists have been thought to be a result of
their low body mass (Hillebrand, 2004). In a comparative study of benthic nematodes,
polychaetes and molluscs across latitudinal gradients, no clear trends or changes in the
species diversity were identified with latitude (Gobin & Warwick, 2006). Benthic
diversity has also been found to be negatively affected by the increase in the input of
phytodetritus, although, these effects have been found to vary with habitat, depth and
study area and often shortDterm due to the rapid utilization by benthic organism (Quijón
., 2008).
To date, approximately ~2140 extant benthic foraminiferal species have been
formally described, 701 from marginal marine environments, 989 from the shelf and 831
from the deep sea (Murray, 2007). Only 33 % of these have been found to be in large
abundance (> 10 %) while 67 % are of minor abundance, most being rare and endemic
63
and few being cosmopolitan (Murray, 2007). Studies in most areas have reported a low
species richness of between 20 and 80 species, with the greatest numbers being identified
in lagoon areas (180 – 340) and on the European coast, although these numbers may be a
reflection of the number of studies conducted there rather than an indication of a species
rich environment (Murray, 2007).
In the deepDsea, comparisons between foraminifera and metazoan meiofauna
(nematodes and harpaticoid copepods) have shown that foraminifera did not exceed these
taxa in abundance but sometimes did exceed them in biomass (Bernhard
., 2008).
The density and biomass of foraminifera also did not consistently vary with depth
(Bernhard
., 2008).
Foraminiferal tests remain in the sediments after death, and can provide an idea of
environmental conditions (Yanko
., 1999; Scott
., 2001; du Châtelet
., 2004).
In ecological studies, live foraminifera are examined as they can provide an indication of
the present environmental conditions, and dead assemblages are studied to provide an
indication of postDmortem processes (Murray, 1991). The study of dead assemblages in
ecological studies can assist in the interpretation of taphonomic changes like the transport
of tests and test dissolution (Murray & Pudsey, 2004). Differences between live and dead
assemblages in an area could be indicative of depositional sinks (Alve & Murray, 1997).
Foraminifera have short lifeDcycles and respond quickly to changes in the
environment, both positively and negatively, and they are therefore useful bioDindicators.
Most environmental studies involving taxa have concentrated on identifying biofacies or
proxies, that is, species or assemblages that can be used to identify a particular set of
environmental conditions (Pielou, 1979; Murray, 2001). Opportunistic taxa could be
identified as proxies as these species would tend to dominate environments which have
become harmful to those with a limited tolerance range (Culver & Buzas, 1995). Taxa
that have typically been reported in these studies have been species of the genera
(which are small foraminifera) and
, as both taxa appear to have a wide
tolerance to a range of environmental factors (Frontalini
2009). Although genera
and species have been identified as bioDindicators in previous studies, Murray (2001) is of
the opinion that studies should identify assemblages rather than species as proxies.
64
In any study of foraminiferal assemblages, it is important to take patchiness of
distribution into account (Gooday & Lambshead, 1989), as foraminifera are meiofauna
and respond to changes in the microDenvironment as found in other benthic fauna (Flint &
Holland, 1980; Murray, 1991). Clumping of foraminifera often occurs when
opportunistic species reproduce quickly in response to an increase in the food source and
increase their numbers (Murray, 2001).
The aim of this chapter is to describe foraminiferal communities (live and dead)
and their size structure at two study areas on the west coast of South Africa, namely, St
Helena Bay and Robben Island. These assemblages will be compared to those of other
studies glaobally. The assemblages were also examined at generic level, to determine
whether genera could be used as proxies for species. The influence of taphonomic
processes on the communities will also be examined.
3.2
Materials and Methods
3.2.1
Field Sampling
Please refer to Chapter 2 for a full description of the field methods employed (Fig.
2.3 and 2.4). Essentially, twelve stations were sampled in St Helena Bay, nine of these
stations were randomly selected within a 150 m radius of the fish factory outfall (pipeline
sites) and three stations were selected as the control site (3.6 km, 1.5 km and 0.9 km from
the pipeline). Around Robben Island, a total of eight stations were selected, five of them
within a 225 m radius of the outfall (pipeline sites) and three between 190 m and 300 m
from the pipeline (control sites). SCUBA divers used handDheld
(Fleeger
., 1988) to obtain sediment samples. Each core was 30 cm long and had a diameter of
3.57 cm. Where possible, 6 cores per station were collected. Samples were kept on ice in
the field and frozen on return to the laboratory.
3.2.2
Laboratory Analyses
3.2.2.1 Foraminiferal assemblages
Subsamples from the top 5cm of the sediment core were preserved in 70 %
ethanol with Rose Bengal stain. Rose Bengal was used to stain foraminifera because this
stain gives an indication of which foraminifera were alive at the time of collection as it
65
stains protoplasm pink (Murray, 1991). Sediments from each core were size fractioned
using mesh sizes 63 Rm, 125 Rm, 250 Rm and 500 Rm. Carbon Tetrachloride was used
to separate foraminifera from the sediments (Murray, 1991). Each size fraction was
examined for foraminifera using a stereoscopic dissecting microscope at 80 x
magnification. Specimens were placed in water for examination as this assists in the
recognition of stained tests (Berkeley
., 2008). Live and dead foraminifera per size
fraction were counted separately.
Where possible, 300 foraminifera per sample were picked and mounted onto a
slide for the identification of species; these were also separated into live and dead
specimens. It was difficult to determine the exact numbers of species in all instances, as
bolivinids, for example, are difficult to consistently identify under normal light
microscopy. The bolivinids were therefore grouped into elongated bolivinids and
perforated bolivinids. That said, some species of bolivinids could be consistently
identified, for example,
,
and
3.2.3
Statistical Analyses
3.2.3.1 Live Foraminiferal Community Structure
ThirtyDeight species were used in the analyses. The bolivinid species and specimens
of foraminifera from the genera
, !
and "
were similarly hard to
separate and were grouped as genera rather than identified into species.
Dominant species were determined for each station as well as for the control and
pipeline sites. The diversity indices, namely, species richness (S), evenness (J’) and
species diversity (H’) were determined using PRIMER software. These diversity indices
have commonly been used to assess the impact of disturbance on the marine
environment. Other estimators of species richness were also considered using the
# 8.2.0 program (Colwell, 2009). These were only conducted on the live
assemblages as the nature of this study is ecological. The estimators ICE (incidenceD
based coverage estimator), Chao 2 and Jackknife 2 were chosen as they are regarded as
more robust when assemblages are prone to patchy spatial distributions and additionally
they are relatively insensitive to sample size (Lambshead
., 2003). Chao 2 is nonD
66
parametric and based on the number of species with one and two individuals per species,
this estimator was found to overestimate species and a very large sample size is required
before it was found to be a reliable estimator (Gray, 2000).
In order to determine whether the sampling effort was sufficient to determine
diversity, species accumulation curves were plotted of the observed species richness
against the sample number for each study area and for the pooled data using Colwell’s
# 8.2.0 program. The program calculates species accumulation curves for
randomized samples without replacement (Colwell, 2009). Models were fitted to the
observed data using nonDlinear regression in the program CurveExpert 1.4 which
provided the best fit to the data as the sigmoidal MMF Model with the equation
y=(a*b+c*x^d)/(b+x^d). The shape of the rarefraction curve depends on the relative
abundance of sampled species and the fitted model provides a prediction of the increase
in richness with additional sampling effort (Colwell & Coddington, 1994).
In order to visualize the similarity of the assemblages between all samples, a
similarity matrix of all samples was constructed using the BrayDCurtis Similarity Index
on fourth root transformed data with group average linkage, and a cluster analysis was
performed on this to construct a dendrogram. FourthDroot transformation reduces the
distortion of similarities calculated between samples by rare or dominant species (Clarke
& Gorley, 2006). The BrayDCurtis Similarity Index was used for biological data as it
appears to follow natural biological axioms not found in other coDefficients (Clarke &
Gorley, 2006). To plot the relationships between all stations of the control and pipeline
sites, an MDS (MultiDdimensional Scaling) Ordination was performed on same similarity
matrix.
To determine which species were most responsible for the similarity within and the
dissimilarity between, each site, a SIMPER (Similarity Percentage) was performed on the
assemblages of each study area separately and together. This SIMPER provided an idea
of the species that may have been different between the two study areas. To determine the
partition variation within the live species data between sites, stations and cores of each
study area and for the pooled data, PERMANOVA was conducted on the fourth root
transformed species data, it provided an indication of which of these groupings displayed
67
the most variation. This provided tool for the evaluation of microD or macroDscale
variation of the foraminifera from the samples.
In order to determine whether genera rather than species, would be sufficient to use in
the evaluation of communities, species data were reduced to generic data. These data
were fourth –root transformed and a similarity matrix was produced using the BrayD
Curtis similarity index, group average linkage and cluster analysis provided a
dendrogram. To determine the correlation between the generic and species data, their
similarity matrices of the species data and the generic data were then subjected to a
Relate statistic using PRIMER software. The nonDparametric correlation coefficient
(Rho) indicated whether these two matrices were significantly correlated.
To determine whether any significant differences in the abundance of specimens per
genus occurred between the control and pipeline sites and each station of both St Helena
Bay and Robben Island, oneDway ANOVA’s were used with a Bonferroni adjustment.
Foraminifera separated into size classes were used for these analyses, no separation
into species was done. OneDway ANOVA was used to determine any differences between
the abundance of foraminifera per size class between the control and the pipeline sites of
both study areas. A postDhoc comparison of means was performed using the Tukey
Honest Significant Difference Test.
A similarity matrix was constructed using fourthDroot transformed data, the BrayD
Curtis Similarity Index with group average linkage and a cluster analysis was performed
to construct a dendrogram (Clarke & Gorley, 2006). An MDS Ordination was performed
in on the similarity matrix of the live foraminifera in order to visualise the relationship
between all stations of the control and pipeline sites.
3.2.3.3 Dead Foraminiferal Assemblages
Dominant species were determined for each station as well as for the control and
pipeline sites. To illustrate the similarity between the dead assemblages of all samples, a
similarity matrix was constructed using the BrayDCurtis Similarity Index on fourth root
transformed data with group average linkage. A cluster analysis was performed on this to
68
construct a dendrogram. In order to plot the relationships between all stations of the
control and pipeline sites, an MDS Ordination was performed on the assemblages from
each sample. To determine which species were most responsible for the similarity within
and the dissimilarity between each site, a SIMPER (Similarity Percentage) was
performed on the assemblages of each study area separately and together. To provide an
indication of whether there were similarities between live and dead assemblages of all
samples, a RELATE statistic was conducted. Similarities or differences between the
assemblages could give an indication of taphonomic processes.
ANOVA was used to determine any significant differences between the abundance of
foraminifera between the control and the pipeline sites of both study areas. A postDhoc
comparison of means was performed using the Tukey Honest Significant Difference Test.
A similarity matrix was constructed using fourthDroot transformed data. The BrayD
Curtis Similarity Index with group average linkage was utilized and a cluster analysis
was performed to construct a dendrogram (Clarke & Gorley, 2006). An MDS Ordination
was performed on the same data in order to visualise the relationship between all stations
of the control and pipeline sites. A RELATE statistic was conducted between the
abundance of live and dead foraminifera to establish the correlation between them.
3.3
Results
3.3.1
Live Foraminiferal Community Structure
Twenty eight morphospecies of foraminifera were identified from the samples
collected from St Helena Bay and 34 from around Robben Island; 38 morphospecies
were collected in total from the two study areas (Appendix 3.1; 3.2)). Most species were
present in all samples and in all size classes.
was the most
common species in Robben Island samples (Table 3.1) while
was most abundant in the live assemblages of St Helena Bay samples (Table 3.2).
Robben Island samples were also characterized by a high abundance of $ %
%
of $
&
%
'
and ( %
With the exception
the other species did not form a major component of the assemblages in
St Helena Bay. The bolivinids, which were also important in the assemblages of St
Helena Bay, did not form a major component in Robben Island samples.
69
The species richness (S) of the live community was lowest at the pipeline sites in St
Helena Bay, particularly at stations SHD, SHE and SHF (Table 3.3). The samples from
the stations around Robben Island displayed a higher species richness than those of St
Helena Bay samples, particularly the control site RIH. The species diversity (H’) was
highest in the Robben Island samples and in the control sites from St Helena Bay (Table
3.3). The species diversity was lowest at the St Helena Bay pipeline sites SHC and SHD,
while it was highest at the Robben Island control sites (RIH). Evenness (J’) did not differ
much between sites and values were approaching unity, an indication that the numbers of
individuals were almost evenly spread across the species (Table 3.3). The abundance of
live foraminifera was highest around the control sites in St Helena Bay while all other
sites were generally low with the lowest abundance at the pipeline sites of St Helena Bay
(Table 3.3).
Species richness in the samples from the Robben Island sites (14 ± 0.5) was
significantly higher than those of St Helena Bay (9 ± 0.5) (p < 0.000 1; F (1, 113) =
33.87). Similar differences were observed in the diversity (St Helena Bay – 1.69 ± 0.06;
Robben Island – 2.17 ± 0.04; p < 0.000 1; F (1, 113) = 36.92). The abundance of
foraminifera was significantly lower (St Helena Bay – 537 ± 109 / 10 cm3; Robben Island
– 236.3 ± 23.7/ 10 cm3 ; p = 0.02; F (1, 113) = 5.066). When examining the control and
pipeline sites of both study areas, the pipeline sites of St Helena Bay had a significantly
lower species richness (p = 0.0001; F (1, 66) = 46.53) and diversity (p = 0.001; F (1, 66)
= 15.85) than the control sites of St Helena Bay as well as all sites of Robben Island.
However, the control sites of St Helena Bay had a significantly higher abundance (p =
0.0001; F (3, 111) = 34.065) of foraminifera than all other sites.
The species accumulation curves of St Helena Bay samples (Fig. 3.1 (a)), Robben
Island samples (Fig. 3.1 (b)) and the pooled data (Fig. 3.1 (c)) reached an asymptote after
15 to 20 samples indicating that the sampling effort was sufficient to determine the
richness of the sites. The fitted extrapolation curve, the sigmoidal MMF curve, provided
an indication of the estimated richness in the sites and all three graphs fitted the model
with a correlation coDefficient of 0.999 (Table 3.4). Table 3.5 compares the observed
species richness with that estimated by the MMF model, which was slightly higher than
the observed richness, except for the St Helena Bay samples where the estimate was
70
lower than the true species richness. The ICE and Chao 2 were the same as the observed
total species richness for the St Helena Bay samples but not for the Robben Island
samples. The Jackknife 2 calculation underestimated richness for the pooled data and the
St Helena Bay samples but overestimated richness for the Robben Island samples.
The cluster analysis (Fig. 3.2) of the live assemblage per sample, for both study areas,
showed high variability between the cores from the same station. Robben Island and St
Helena Bay samples nevertheless grouped separately from each other with a similarity
percentage below 40 %, indicating that there are differences in assemblage structure
between the two study areas. In St Helena Bay, the pipeline sites and the control sites
mostly grouped separately, although cores from SHA and SHB also grouped with those
of the control sites. Robben Island samples however overlapped and there was no clear
grouping of the control and pipeline sites. An MDS ordination of the two study areas
(stress 0.17) showed much the same as the dendrogram (Fig. 3.3): there was a definite
difference between the Robben Island and St Helena Bay assemblages. A large amount of
overlap occurred between the control and pipeline sites of Robben Island but some
separation was evident in St Helena Bay.
The results of the SIMPER analysis of the live assemblages of St Helena Bay samples
revealed that
$
)
%
and
were most responsible for the similarity within the control sites
(69.84 %), all with similar percentage contributions of under 15 % (Table 3.6). In the
pipeline sites,
%
elongated bolivinids
and
'
were the main species contributing to the
similarity within the group (44.09 %).
dominated this assemblage with
a percentage contribution of 34 %. The dissimilarity between the two groups (55.56 %)
was mainly as a result of the differences in the contribution of
)
and $
%
* all with just under 5 % contribution to the dissimilarity.
The similarity within the control sites (62.44 %) and the pipeline sites (60.14 %) of
the live assemblages of Robben Island were a result of the contributions by
%
$
%
+
%
and +
(Table 3.7). The average dissimilarity between the two groups was only
71
40.34 % caused by the differences in the contribution of ( %
Bolivinitidae and &
'
%
)
Upon examination of the two
study areas, St Helena Bay samples showed a similarity of 45 % as a result of
longated bolivinids,
(Table 3.8).
%
and
Robben Island (60.61 % similarity) samples were characterised by
$
%
%
+
%
and &
'
The average dissimilarity between the two study areas was 68.7 % which was
mainly a result of the differences in the average abundance of
%
&
+
and
The nested PERMANOVA using site, stations and cores of St Helena Bay showed
that 33.1 % of the variation within the data was due to the differences between the
composition of the fauna of the control and pipeline sites, and the least variation occurred
between stations within the two sites (16.85 %) (Table 3.9). The largest percentage of the
variation occurred between the cores within the stations themselves (50 %). The nested
PERMANOVA using site, stations and cores of Robben Island showed that only 8.9 % of
the variation within the data was due to the differences between the composition of the
fauna of the control and pipeline sites, and most variation occurred between all the
stations within the two sites (31.03 %) and between samples within each station (60.05
%) (Table 3.10).
The nested PERMANOVA using all samples of the two study areas, sites, stations
and samples showed that 33.1 % of the variation within the data was due to the
differences between the two study areas, while the most variation was still between
samples (35.41 %) (Table 3.11). In other words, there is a high degree of mesoscale
variability in foraminiferal assemblage structure.
In summary, the SIMPER analyses showed clear differences in terms of the species of
the live assemblages and their related contribution between the two study areas, while the
dissimilarity between the control and pipeline sites of St Helena Bay was also more
marked than that of Samples from around Robben Island, further evident in the cluster
analysis and the MDS ordination. The PERMANOVA conducted showed large scale
within station variation of foraminiferal community structure for both study areas while
St Helena Bay samples shows clear differences between the control and pipeline sites
72
which were not evident in the community structure of Samples from around Robben
Island. The two study areas were therefore obviously different in terms of community
structure, which was also further supported by the ANOSIM, cluster analysis and MDS
ordination.
The generic data was very similar to that of the species data, with the control and
pipeline sites of Robben Island overlapping, but the St Helena Bay control sites grouped
separately from the pipeline sites (Appendix 3.4). The Relate statistic between the species
resemblance matrix and that of the generic data had a Rho value of 0.645 and a p – value
of 0.001 which shows that the two data sets are significantly correlated and that generic
data could possibly be used as a proxy for species.
The genera (of the live assemblages), that were most abundant in all the assemblages
of St Helena Bay, were
$%
(Fig.
3.4). All these genera were significantly more abundant at control sites than at pipeline
sites, with the exception of
which was not significantly different (Table 3.12).
An ANOVA of the five genera in each station revealed that generally SPA, SPB and SPC
(control sites) had higher mean abundances of these genera than sites nearer the pipeline,
no significant differences could be found with the genus
and $ %
(Table 3.13)
appeared to have the most significant differences between the
stations of the control site and those of the pipeline sites. The genera with the most
abundance of specimens in samples from around Robben Island were
$%
&
'
&
and
'
and
(Fig.
3.5).
were significantly more abundant at control sites than at
pipeline sites (Table 3.14). An ANOVA of the five genera in each station revealed that
generally
&
'
were not significantly different between
stations, however, RIE (pipeline station) consistently showed significant differences in
terms of
3.3.2
$%
and
(Table 3.15)
Size Structure of Foraminiferal Communities
Foraminiferal specimens in the 63 Rm and 125 Rm size classes dominated the live
assemblages in both St Helena Bay and Robben Island samples (Table 3.16, Fig. 3.6,
Appendix 3.5; Appendix 3.6). A larger percentage of small foraminifera dominated at the
73
pipeline sites than the control sites in both study areas. The abundance of live
foraminifera at the pipeline sites were significantly lower than that of the control sites in
the 63 Rm, 125 Rm and 250 Rm size classes in the St Helena Bay samples. In the Robben
Island samples, the abundance of the small foraminifera (63 Rm and 125 Rm size classes)
was higher at the pipeline site but foraminifera lower in the 250 Rm and 500 Rm size
classes; there was only a significant difference in the 500 Rm size class.
A cluster analysis of the abundance of live foraminifera separated into their size
classes revealed a high similarity between samples from around Robben Island and St
Helena Bay samples, although the control sites of St Helena Bay did mostly group
teogether (Fig. 3.7). The grouping or separation between sites or study areas was not
clearly defined in the size structure of live foraminifera, revealing no particular patterns
in study area, sites or stations. An MDS of the live assemblages showed that all samples
from both study areas displayed a large degree of overlap (Fig. 3.8).
3.3.1 Dead Foraminiferal Community Structure
was the most common species in the Robben Island (Table
3.17) and St Helena Bay samples (Table 3.18) in the dead assemblages. As for the cluster
analysis and the MDS Ordination of the live assemblages, the dead assemblages also
showed a separation between the St Helena Bay and Robben Island samples with a
similarity of about 50 % (Fig. 3.9 and Fig. 3.10). The samples of the control and pipeline
sites of both study areas did not separate from each other.
The Relate statistic for live and dead assemblages for all samples, St Helena Bay and
Robben Island samples separately, show a significant relationship (Table 3.19). The
correlation coDefficients (Rho) for all three tests were relatively low, an indication that
there is a difference between the live and dead assemblages. The correlation coDefficient
between the St Helena Bay live and dead assemblages are even lower than that of
samples from around Robben Island, showing an even greater difference live and dead
assemblages.
The SIMPER of both study areas (Table 3.20 and Table 3.21) also showed that the
average dissimilarity between the control and pipeline sites was low (38.91 % and 37.17
%, respectively). The SIMPER between the two study areas showed an average
74
dissimilarity of 54.72 % (Table 3.22). The species most responsible for the differences in
the community structure in both study areas reflect those of the live assemblages, namely
the bolivinids,
+
%
+
and &
%
The dead assemblages were dominated by foraminifera in the 63 Rm and 125 Rm size
classes, with the 250 Rm and 500 Rm contributing small amounts (Fig. 3.11). The size
structure of the dead assemblages of the St Helena Bay samples only have significant
differences between the control and pipeline sites in the 250 Rm size class, while the
Robben Island samples have significant differences in the 250 Rm and 500 Rm size
classes (Table 3.23).
A cluster analysis of the abundance of dead foraminifera separated into their size
classes revealed a high similarity between samples from around Robben Island and St
Helena Bay samples (Fig. 3.12). No real grouping of or separation between sites or study
areas occured, revealing overlap in the study areas, sites and stations. The MDS of the
dead assemblages further displayed the levels of overlap (Fig. 3.13). This pattern follows
that of the size structure of the live foraminifera. A RELATE statistic between the
abundance of live and dead foraminifera of all samples, St Helena Bay and Robben
Island samples, was significant, however, the correlation coefficients were very low
(Table 3.24). These low coDefficients may reveal that some differences between the
abundance of live and dead assemblages does occur.
NonDparametric Spearman rank order correlations between the mean size of
foraminifera in the live and dead assemblages of St Helena Bay, Robben Island and all
samples together were significant (Table 3.25). No significant differences were found in
the mean size of live foraminifera between Robben Island and St Helena Bay (Table
3.26). However, there was a significant difference in the mean size of dead foraminifera,
with Robben Island having a larger mean size of dead foraminifera.
3.4
Discussion
3.4.1
Community Structure
ThirtyDeight species of foraminifera were identified. This species number may be
higher but many species could not be consistently identified, especially those that were of
small size. Previous studies have shown that using morphotypes, or even just separating
75
foraminifera based on their test shape, can be useful for ecological studies, as the shape
of the foraminifers often determine where they would live (Bernhard, 1986). According
to Debenay
(2001), commonly occurring species can explain the characteristics of
an area just as well as using all species. Morphotypes are often considered to be
equivalent to species for the purpose of biodiversity studies (Lambshead
2003).
was present in the largest abundance throughout the St
Helena Bay samples in the live assemblages, but was absent or rare in Robben Island
samples. The genus
has been reported as opportunistic and found in most types
of environments, even those experiencing chemical stress (Seiglie, 1971; Alve, 1987;
Yanko
1994; Scott
., 2001; Ferraro
and
Bay and Robben Island samples.
, 2006; Bergin
., 2006).
were also present in large numbers in both St Helena
,
has the ability to change from an
epifaunal to an infaunal habitat and appears to be highly adaptable to food and
environmental changes (Debenay
., 2001).
feed mainly on diatoms; in an
area with increased productivity, diatom abundance increases with an incremental
increase in
(Thomas
., 2004). When diatoms are not in large abundance,
tends to be present in higher abundance than
$
%
(Thomas
., 2004).
were also present in large numbers at the stations around the pipeline in
St Helena Bay. This species is associated with hard surfaces and coarse sediments and
does not live in sandy sediments (Murray, 2001). The area surrounding the study site at
St Helena Bay is typically rocky with a large mean sediment size and represents an ideal
habitat for this species.
Bolivinids were dominant in the samples around the pipeline in St Helena Bay.
Bolivinids have an elongated, tapering shape: this genus is known to be infaunal, capable
of living 6 – 8 cm below the surface, because of lower oxygen levels deeper in the
sediments, and they are thought to be able to survive anoxic conditions better than other
groups (Stott
, 1996). The miliolids which were rare or absent in St Helena Bay
samples were very common in most samples around Robben Island. The miliolids are
generally warmer water species which could explain their higher dominance in Robben
Island samples (Murray, 1991), as some injection of warmer waters from the Agulhas
Current does occur in the area.
76
Agglutinated foraminifera were absent in samples, this was also the case in Israel
(Yanko
., 1994) and was attributed to the warm water in the bays that were studied.
The absence of live or dead agglutinated tests in samples could also be a result of the fact
that these tests are very weakly held together by organic material and do not often last for
very long after death (Murray, 1991), therefore, they deteriorate very quickly, unless
examined immediately after careful collection, fixation and preservation. Calcareous
species dominated assemblages, while hyalinated species were less abundant; this was
also the case in a study in France (Debenay
., 2001).
The speciesDaccumulation curves for both sampling study areas reached asymptote
and estimates of species richness were close to the observed species richness within the
areas. This implies that the sampling effort was sufficient (Colwell & Coddington, 1994).
The fact that asymptotes were reached and the curves did not differ appreciably from the
fitted models indicates that all samples came from a relatively homogenous spatial habitat
(Colwell & Coddington, 1994). Habitat variation or heterogeneity is regarded as a driver
of functional composition and diversity and coastal areas which are nonDdegraded are
known for a higher diversity as a result of this high habitat variation (Hewitt
., 2008).
Homogenous coastal areas which have lost previous habitat diversity due to development
or dredging activities, display decreased diversity or a change in the taxa to more
colonizing species (Airoldi
., 2008). Variability within aquatic systems is thought to
be a result of this heterogeneity and the tendency of patchiness within benthic organisms
(Flint & Holland, 1980).
Some of the nonDparametric estimators, particularly the Jackknife 2, underDestimated
species richness and this is thought to be a result of smallDscale patchiness in species
composition which is evident in the samples of this study (Butler & Chazdon, 1998).
Gray (2000) is of the opinion that one measurement of diversity is not sufficient or robust
enough for different environments or taxa and that a suite of measurements should be
used. However, the differences between the various estimators and the observed species
richness were not very large, an indication that in this study, the use of the observed
species richness would be sufficient.
Evenness in both study areas was high, therefore there was a lack of dominance by
any particular species. This suggests that species have been environmentally filtered and
77
would share many traits (Hewitt
., 2008). It also reflects the potential for the
maintenance of ecosystem function even with the loss of individual species (Hewitt
.,
2008). Foraminiferal assemblages in both study areas were largely homogeneous at the
mesoscale, and most species were present in all samples. The high evenness may also
reflect the homogeneity of the habitat; high variation in habitat normally leads to higher
diversity and lower evenness as more species are able to inhabit the area.
The species found were much less than the cumulative number reported from other
studies around South Africa (Appendix 1.1). The studies which were reported on were
from a wide variety of study sites from deep sea to coastal, most were geological studies
and from different geological eras and some were on different coasts (east, south and
west coasts which support different assemblages of most organisms). This species
richness was also compared to some previous studies in coastal areas (Appendix 3.3 (a)
and (b)). Most authors reported between 20 and 100 species of foraminifera, but the
species richness varied between samples depending on the location of the sampling site.
Authors also reported a high dominance of only three or four species with most species
being rare in samples.
Murray (2007) reported that studies on the shelf areas of Africa reported only 28
benthic species, much lower than other shelf areas. He was of the opinion that this has
something to do with the lack of studies in the area. Other authors investigating
foraminiferal assemblages in shallow water environments have reported a varying
number of species, depending on the location of samples; these varied from no live
species in areas of strong contamination to about 100 species in nonDpolluted areas. In a
study in Havstens Fjord, Sweden, the pattern in species richness appeared to be related to
depth, where the shallowest areas had the lowest species richness due to a larger
influence by seasonal fluctuations (Gustaffson & Nordberg, 2000). Buzas
(2007)
reviewed the community structure of benthic foraminifera in the Gulf of Mexico, finding
that shallow (S = 22) and deep environments (S = 12) were less species rich, whereas the
midDdepths were the most species rich (S = 44D86). DeepDsea benthic foraminifera appear
to display a decreasing diversity with increasing latitude in the North and South Atlantic
and greater diversity in the South than the North (Culver & Buzas, 2000). These
differences appear to be a result of differing phytodetritus supply and originated more
78
than 36 million years ago (Culver & Buzas, 2000). Latitudinal gradients have been found
in shallow water foraminifera which have been attributed to its dispersal capabilities;
other meiofauna, like nematodes, have not displayed these gradients and this is thought to
be due to the group’s lack of dispersal abilities (Culver & Buzas, 2000).
Patterns of distribution of foraminifera are dependent on a broad range of factors
including depth, oxygen levels and organic matter flux (Murray, 2001). Ecological
factors would determine the range of species, and the number of species could vary both
spatially and temporally even in the same area. The number of species found in this study
is not much different from what could be encountered in shallow water environments that
are highly variable. Many authors reporting on the richness and diversity of foraminifera
report a large percentage of rare species with only 4 or 5 species making up the largest
abundance (refer to authors in Appendix 3.3 a). Authors that reported high species
richness had conducted sampling of the same area over a period of time (eg. Gustfsson &
Nordberg, 2000; Bernhard
(eg Yanko
., 2001), sampled at a greater depth than that of this study
1994; Romano
cores (Tsujimoto
., 2008) and/ or had conducted research on deep
., 2006) which were more than just the top few centimeters of
sediments, these studies sometimes did not distinguish between live and dead.
Foraminiferal assemblages reported in most studies do not appear to be very diverse, with
few species being common, this despite their potential to be transported easily in the
marine environment.
The number of species reported in an area also appears to be dependent on the
conditions that the area was subjected to at the time of sampling, for example, an increase
in organic matter causes an increase in the type of species that could inhabit the area.
Foraminifera, as in other meiofauna, respond to changes in the microDenvironment
spatially and temporally, therefore repeated sampling of the same area could yield
different numbers and proportions of species.
In a study of marine nematodes in Saldanha Bay on the west coast of South Africa,
Hendricks (unpublished) found between 5 and 36 species per sample but cumulatively
there were 136 species; these nematodes varied with season as well as the level of
disturbance within the bay. The degree of patchiness and variability in these nematodes
appear to be of a larger scale than observed in foraminifera in this study. A temporal
79
study of foraminifera on the west coast might yield similar results for foraminifera as the
area experiences seasonal variation in organic matter and phytodetritus input.
While some foraminiferal studies have used morphotypes and test shape in
biodiversity studies Bernhard (1986), the use of genera, which are more easily identified
than species in foraminifera, has been relatively unexplored. With the growing evidence
that biological assessments at species level is very expensive as it requires large numbers
of manpower, authors like Williams & Gaston (1994) proposed the use of higher taxon
richness as surrogates for species richness. Balmford
(1996) examined higher taxon
richness (genus and family) in woody plants as measures of species diversity. They
concluded that in their study, information from higher taxon richness was comparable to
that of species richness. Their concerns were the reduction of information on inDsite
variation and whether the tradeDoff between cost savings and the loss of specific
information was worth it. Andersen (1995) tested this theory using Australian ant fauna,
these ants are used extensively as bioDindicators in environmental assessment in
Australia, their species taxonomy is poorly known but their genera are clearly defined.
Andersen (1995) found that the species: genus relationship was only good when there
were few habitat and biogeographic differences in an area and when a genus was
represented by few species. He concluded that although, the relationship can work well
on organisms which are difficult to identify (invertebrates and insects) there is some
masking of detailed information.
While most authors conclude that the use of genera is sufficient, they also advise that
caution should be used and each taxon and area should be assessed individually; Grelle
(2002) in assessing mammal diversity in the Amazon and Central America, Prinzing
(2003) in the assessment of woddy plants in Kenya, Cardoso
spiders in Portugal and Mazaris
., (2004) assessing
. (2008) in the assessment of birds, mammals,
amphibian and reptiles in Greece. The species and generic data for all sites in this study
were significantly related and it was evident that in this study, the use of generic data
would be sufficient for use in an ecological or diversity study on foraminifera and
identification of species would only really be necessary for pure taxonomic studies.
Foraminifera are particularly difficult to identify at species level but the genera have been
80
clearly defined by Loeblich & Tappan (1987) and are widely use. The labour intensive
factor could also be reduced in future studies on environmental assessment.
The variability in foraminiferal assemblages both between cores, stations and sites
was found to be extremely high and it is very difficult to pinpoint clear patterns in the
data. The large amount of variability occurs as a result of patchiness of distribution
especially of meiofauna which occurs within the benthos. One of the reasons for
patchiness is the variability in food source and organic matter input at the sedimentDwater
interface (Lavigne
., 1997). Some opportunistic foraminferal species can exist in very
small numbers when unfavourable conditions occur but as soon as conditions improve,
especially an increase in organic matter input, they reproduce rapidly in those microD
environments (Murray, 2001). Some species respond to changes in food levels faster than
others and assemblage structure can change at a microDlevel, a quick response may be
favoured by the short life cycle, of small paralic species, that may be as short as one
month (Morvan
., 2006). Species were counted based on their size and whether they
were live or dead at the time of sampling. Planktonic species found in the samples were
excluded from the statistical analyses of community structure, as planktonic species are
assumed to have no function within the benthic environment. More species were
identified in the samples from Robben Island than in those from St Helena Bay samples,
and there may be a variety of reasons for this. Robben Island is in the transitional zone
for two biogeographic provinces on the west coast of South Africa, the Namaqua
Province and the Agulhas Province (Bustamante & Branch, 1996). Transitional zones
often have species which would be common to both regions, therefore Robben Island
would have both warm and cold water species. St Helena Bay, on the other hand, is in the
cold temperate province and would therefore not have species found in warmer temperate
provinces (Bustamante & Branch, 1996).
3.4.2
Size Structure of Foraminiferal Communities
Live foraminifera were much more abundant around the control than the pipeline sites
of both study areas and highest at St Helena Bay. In a previous study in Saldanha Bay on
macrofauna around a fish factory it was also found that abundances tended to increase
away from the pipeline as the toxic effects of the effluent are diluted and the increased
81
organic carbon loading can be taken advantage of by increasing reproduction of the
organisms (Christie & Moldan, 1977). The ratio of live:dead foraminifera was much
lower at the pipeline sites i.e. more dead than live tests, the small number of live tests
attests to foraminiferal response to conditions when sampling took place.
The dominance of smaller foraminifera in samples within communities has been
regarded as an indication of pollution (Yanko
, 1994; Samir
., 2001) and anoxic
environments (Bernhard, 1986). However, the area in which sampling took place is cold,
temperate which is generally characterized by smaller organisms than warmer waters.
3.4.3
Dead Foraminiferal Assemblages
The separation of live and dead tests of foraminifera may lead to some errors even
when using Rose Bengal stain. There is some evidence that preserved protoplasm can
stain for at least three months after death especially in anoxic environments (Gustafsson
& Nordberg, 2000). Despite this flaw, Rose Bengal is still the only practical way to
distinguish between live and dead tests, and is said to lead to 96 % correct identification
(Frontalini & Coccioni, 2008). No separation or grouping of the dead assemblages of
samples from the same sites occurred, in contrast to the live assemblages where the two
study areas and the control and pipeline sites separated. This attests to the fact that the
live assemblages were responding to conditions within the area; this response was absent
in the dead assemblages. The differences in the structure of the two assemblages allows
for the conclusion that although some error in the separation of live and dead tests may
have occurred, the margin of error is small and still reflects the differences between live
and dead assemblages.
Although, the live and dead assemblages in both study areas were characterized by
the same species, there were low correlations between the live and dead assemblages; this
may be attributed to different numbers of individuals represented within each species.
Dead assemblages provide a timeDaveraged faunal record of between 12 and 50 years
depending on the rate of bioturbation in an area (Murray & Pudsey, 2004). Therefore the
fact that dead and live assemblages are characterised by the same species only attests to
changes in relative or absolute abundance of the species already present. Although, it is
also known that taphonomic processes like calcareous test dissolution may affect the
82
number of species present in dead assemblages (Murray & Pudsey, 2004). Carbonate
dissolution is complex and may be caused by corrosive bottom or sediment pore waters
usually a result of metabolization of organic matter or bacterial decomposition (Murray &
Alve, 1999).
The fact that no other species were found in the dead assemblages than those present
in live assemblages shows that in both areas dead tests are not transported into the area
from elsewhere and deposited there (Alve & Murray, 1997). The differences in the
abundance of live and dead assemblages can therefore be attributed to deposition of dead
tests over time. The abundance of foraminifera within each species of the dead
assemblages was larger than the abundance in live assemblages and this was more
marked in St Helena Bay samples than those from around Robben Island, providing some
idea of the amount of accumulation that occurs there. The relationship between the
overall abundance of live and dead foraminifera in both study areas were very low.
The mean size of foraminifera of the live and dead assemblages correlated for both
study areas, possibly an indication there has been no significant changes over time that
have affected the size and possibly rate of growth of the foraminifera present. Robben
Island had a larger mean size of dead foraminifera than St Helena Bay, this may indicate
suspension and transport of smaller foraminifera away from the area, leaving only the
larger foraminifera in the sediment: similar to processes which determine mean sediment
grain size.
3.5
Conclusion
The samples from Robben Island and St Helena Bay displayed different
foraminiferal communities. The dominance of
and
, as well as
in the assemblages of St Helena Bay samples could point to an environment that
is dominated by opportunistic species. Samples from around Robben Island does not have
the same assemblage structure with
low abundance of the
and +
dominating and a very
. Live and dead assemblages were dominated by the same
species, but had a low correlation, showing no deposition from other environments. A
higher abundance of dead tests in St Helena Bay samples is an indication of accumulation
of dead tests, possibly a result of the long retention time of water within the bay. The
83
higher diversity and richness of the live assemblages in Robben Island than St Helena
Bay samples may be a result of its more dynamic environment. Species accumulation
curves reached asymptote and the estimated species richness from the extrapolated data
did not differ much from the observed data, therefore, the sampling effort was sufficient
and the diversity points to a relatively homogenous species richness at the mesoscale.
However, there is large scale patchiness and variability at the microscale. The higher
abundance of live foraminifera in St Helena Bay samples appears to be a result of higher
settlement and accumulation rates as a result of its low energy environment; bedDload
transport of Robben Island would carry fine sediments as well as foraminifera with it.
84
Table 3.1:
The dominant species of foraminifera and their percentage of the total numbers, in samples collected from Robben
Island.
Site
Live
Percentage of the Total
RIA
37 %
RIB
36 %
RIC
21 %
$
%
RID
20 %
23 %
RIE
&
RIF
$
RIG
(
20 %
%
27 %
15 %
RIH
19 %
CONTROL
16 %
$
%
PIPELINE
17 %
25 %
$
%
14 %
85
Table 3.2:
Site
The dominant species of foraminifera in St Helena Bay samples, as a percentage of the total abundance.
Live
Percentage of the Total
SPA
21 %
SPB
36 %
SPC
25 %
SHA
20 %
SHB
36 %
SHC
20 %
SHD
$
$
%
%
SHE
20 %
%
40
29 %
SHF
$
%
20 %
33
SHG
$
%
30 %
%
46
SHH
40 %
SHI
33 %
CONTROL
20 %
%
29
PIPELINE
38 %
86
Table 3.3:
Diversity indices of living foraminifera from Robben Island and St Helena Bay and the means of the control and
pipeline sites. SD total species, J’ – Pielou’s evenness, H’ – ShannonDWeiner Index of diversity and the abundance/10
cm3 sediment.
STATION
SPA
SPB
SPC
SHA
SHB
SHC
SHD
SHE
SHF
SHG
SHH
SHI
RIA
RIB
RIC
RID
RIE
RIF
RIG
RIH
Mean control RI
Mean pipeline RI
Mean control SH
Mean pipeline SH
SITE
Control
Control
Control
Pipeline
Pipeline
Pipeline
Pipeline
Pipeline
Pipeline
Pipeline
Pipeline
Pipeline
Pipeline
Pipeline
Pipeline
Pipeline
Pipeline
Control
Control
Control
STUDY
St Helena Bay
St Helena Bay
St Helena Bay
St Helena Bay
St Helena Bay
St Helena Bay
St Helena Bay
St Helena Bay
St Helena Bay
St Helena Bay
St Helena Bay
St Helena Bay
Robben Island
Robben Island
Robben Island
Robben Island
Robben Island
Robben Island
Robben Island
Robben Island
S
15
15
15
11
10
9
7
4
8
10
9
7
27
26
29
25
19
27
28
33
16
14
15
8
J'
0.78
0.69
0.79
0.85
0.72
0.84
0.80
0.86
0.83
0.68
0.77
0.87
0.695
0.687
0.778
0.757
0.804
0.753
0.749
0.77
0.84
0.80
0.76
0.80
H’
1.86
2.17
1.92
1.66
1.78
1.28
1.23
1.58
1.55
1.66
1.55
1.70
2.294
2.241
2.622
2.439
2.368
2.485
2.498
2.721
2.31
2.08
2.05
1.58
Abundance / 10
1662
1902
1117
61
131
663
34
17
107
155
94
203
465
361
282
164
49
190
129
240
186
264
1560
167
87
40
35
35
Cumulative number of observed species
Cumulative number of observed species
40
30
25
20
15
10
5
0
30
25
20
15
10
5
0
0
10
20
30
40
50
60
70
80
0
10
Number of samples
20
30
40
50
Number of samples
(a)
(b)
40
Cumulative number of observed species
35
30
25
20
15
10
5
0
0
10
20
30
40
50
60
70
80
90
100
110
120
130
Number of samples
Figure 3.1:
Species accumulation curves of live foraminifera for St Helena Bay (a), Robben Island (b) and all samples (c). The
MMF Model y = (a*b+c*x^d)/(b+x^d) using Curve Expert is indicated by the dashed line, dots represent the observed
data.
88
Table 3.4:
Estimations of the species richness of the live foraminifera using an extrapolation of an MMF Model:
y = (a*b+c*x^d)/(b+x^d) of a plot of species accumulation per sample.
Sigmoidal
Data
Growth Model
r
Parameters
Standard
Estimated
Observed
Species
species
Richness
richness
Error
a = 0.213
All Samples
b = 3.843
0.999
0.106
39
38
0.999
0.065
27
28
0.999
0.165
36
34
c = 39.359
d = 1.014
a = 1.129
St Helena Bay
b = 2.904
c = 27.074
d = 1.047
a = 0.116
Robben Island
b = 2.507
c = 36.198
d = 0.941
89
Table 3.5:
NonDparametric statistical estimators of species richness of the live assemblages from Colwell’s EstimateS
program
compared with actual species richness and estimated species richness from the Curve Expert program.
Observed species
MMF Model
richness
ICE
Chao 2
Jackknife 2
All
38
39
38
38
37
St Helena Bay
28
27
28
28
26
Robben Island
34
36
36
36
37
90
Figure 3.2:
Similarity %
0
20
40
60
80
100
Dendrogram showing the similarity between samples, in terms of the structure of live foraminiferal assemblages across
all study sites and samples (BrayDCurtis Index). Species data were rootD root transformed and the dendrogram was
produced using GroupDAverage Linkage. (PRI –Pipeline sites Robben Island, CRI – Control sites Robben Island,
CSH – Control sites St Helena Bay and PSH – Pipeline sites St Helena Bay).
91
R ID1
R IE5
R IC 3
R IG3
R ID3
R IE4
R IG1
R IG2
R IG5
R IH4
R IC 4
R IF3
R IH2
R IG4
R IH5
R IA1
R IF1
RIB 3
R IB4
R IA2
R IA3
R IA4
R IH1
R IA5
R IB 1
R ID5
R IA6
R IF5
R IC 6
R ID6
R IB 6
R IC 5
R IB 2
R IH3
R ID2
R IB 5
R IC 2
R ID4
R IH6
R IF2
R IC 1
R IF4
R IE1
R IE2
R IE3
R IE6
R IG6
SHA2
SHA3
SPA3
SPC 3
SPC 2
SPB 1
SPB 3
SPA1
SPC 1
SPA2
SPB 2
SPC 5
SPA5
SPA6
SPB 5
SPC 6
SPB 6
SHB 5
SHA4
SPA4
SPB 4
SHG5
SPC 4
SHI5
SHI1
SHG6
SHF6
SHG4
SHB 1
SHH5
SHC 5
SHC 4
SHF5
SHD5
SHA6
SHB 3
SHC 2
SHI3
SHI2
SHG1
SHH1
SHG3
SHH4
SHD4
SHC 6
SHH2
SHD2
SHB 6
SHC 3
SHB 2
SHC 1
SHE6
SHG2
SHI6
SHE4
SHF1
SHA5
SHF4
SHH3
SHI4
SHD3
SHE5
SHF3
SHE1
SHF2
SHA1
SHE3
SHE2
site
PRI
CRI
CSH
PSH
2D Stress: 0.17
site
PRI
CRI
CSH
PSH
Figure 3.3:
MDS Ordination of all live foraminiferal species. Species data were fourth root transformed and the MDS was
produced using the Bray Curtis similarity index. (PRI –Pipeline sites Robben Island, CRI – Control sites Robben
Island, CSH – Control sites St Helena Bay and PSH – Pipeline sites St Helena Bay).
92
Table 3.6:
The SIMPER procedure in PRIMER between all species of the live assemblages in all samples of St Helena Bay
performed on fourth root transformed data using the BrayDCurtis similarity matrix. The average similarity percentage of
each of the two groups is in brackets and the species most responsible for determining community structure within each
group is in bold (a). The average dissimilarity between the two groups is in brackets and the species most responsible
for the dissimilarity is represented in (b).
(a)
(b)
Species
$
%
)
Elongated bolivinids
%
'
% Contribution
%
Contribution
Control (69.84 %)
Pipeline (44.09 %)
14.91
33.99
10.24
4.74
)
10
4.24
$
9.37
3.12
8.01
<1
6.23
13.76
6.67
10.72
6.85
10.05
<1
6.77
Species
Average dissimilarity
%
(55.56 %)
Contribution
4.51
8.12
4.44
7.98
4.11
7.41
3.94
7.1
3.73
6.72
2.58
4.65
Perforated bolivinids
2.54
4.58
Elongated bolivinids
2.49
4.49
%
+
93
Table 3.7:
The SIMPER between all live species in all Robben Island samples. The data were rootDroot transformed and
the BrayDCurtis similarity matrix was used to produce the SIMPER. The average similarity percentage of each
of the two groups is in brackets and the species most responsible for determining community structure within
each group is in bold (a). The average dissimilarity between the two groups is in brackets and the species most
responsible for the dissimilarity is represented in (b).
(a)
(b)
% Contribution
Species
Control
(62.44 %)
$
+
&
%
Average
Contribution
Species
Pipeline
3.05
%
6.47
2.2
%
5.96
5.33
%
2.44
2.05
2.43
2.33
% Contribution
(40.34 %)
(60.14 %)
8.9
dissimilarity
(
2.76
6.85
)
1.99
4.93
Bolivinitidae
1.9
4.71
1.83
4.53
1.72
4.27
1.69
4.20
1.65
4.10
1.65
4.08
1.6
3.96
1.57
3.90
&
%
'
&
'
94
Table 3.8:
The SIMPER between all live species in the two study areas, performed on fourth root transformed data using
the BrayDCurtis similarity matrix. The average similarity percentage of each of the two groups is in brackets and
the species most responsible for determining community structure within each group is in bold (a). The average
dissimilarity between the two groups is in brackets and the species most responsible for the dissimilarity is
represented in (b).
(a)
SITE
Species
$
+
&
%
%
%
RI (60.61 %)
% Contribution
14.67
13.66
11.31
10.61
10.16
Species
Elongated Bolivinids
%
SH (45.04 %)
% Contribution
27.75
12.11
10.14
10.02
6.8
(b)
Species
+
&
%
$
%
%
Bolivinitidae
& %
'
RI
Average
0.2
1.54
1.47
2.01
1.85
0.36
1.57
0.85
0.79
0.97
SH
Average
1.93
0.03
0.09
1.01
0.81
1.16
1
0
0
0.5
Ave. diss. (68.7
% Contribution
7.8
7.03
6.45
5.96
5.71
4.36
3.87
3.67
3.58
3.55
95
Table 3.9:
Results of the PERMANOVA based on BrayDCurtis similarity of the live species data for St Helena Bay. Data were
fourth root transformed. Each test was conducted using 998 random permutations.
Site (Control vs Pipeline)
NESTED
(Stations)
Residual
(cores)
df
SS
MS
% variation
1
16821
16821
7.85
0.001
33.1
10
20 868
2086.8
1.65
0.003
16.85
57
72085
1264.6
50
96
Table 3.10:
The PERMANOVA based on BrayDCurtis similarity of the live foraminiferal species from Robben Island samples.
Data were fourth root transformed. Each test was conducted using 998 random permutations.
df
SS
MS
F
p
% Variation
Site (Control vs Pipeline)
1
2007.8
2007.8
1.1869
0.266
8.9
Nested (Stations)
6
10 281
1713.5
2.5717
0.003
31.03
Residual (cores)
39
25 985
666.28
60.05
97
Table 3.11:
The PERMANOVA based on BrayDCurtis similarity of the live foraminiferal species data from all samples from
Robben Island
and St Helena Bay. Data were fourth root transformed. Each test was conducted using 998 random permutations.
Source
df
study area (SH & RI)
Nested (sites within study areas)
Nested (stations within the sites within
study area)
Residual (samples)
SS
MS
PseudoDF
P (perm)
% Variation
1
53566
53566
6.0269
0.023
33.19
2
17915
8957.7
4.7194
0.002
18.58
16
30008
1875.5
1.7504
0.001
12.82
95
101790
1071.5
35.41
98
70
35
60
30
50
25
40
20
30
15
20
10
10
5
0
SPA
SPB
SPC
SHA SHB
SHC
SHD
SHE
SHF
SHG SHH
SHI
C
0
P
90
SPB
SPC
SHA SHB
SHC
SHD
SHE
SHF
SHG SHH
SHI
C
P
SPA
SPB
SPC
SHA
SHC
SHD
SHE
SHF
SHG
SHI
C
P
C
P
18
80
16
70
14
60
12
50
10
$%
40
30
8
6
20
4
10
0
SPA
2
SPA
SPB
SPC
SHA SHB
SHC
SHD
SHE
SHF
SHG SHH
SHI
C
P
SHA
SHB
0
SHB
SHH
12
10
8
6
4
2
0
Figure 3.4:
SPA
SPB
SPC
SHC
SHD
SHE
SHF
SHG
SHH
SHI
The mean and standard error for each of the five dominant genera for each station in St Helena Bay as well as the
pooled results for the control (C) and pipeline (P) sites.
99
Table 3.12:
The oneDway ANOVA, of the abundance of the dominant genera at the control and pipeline sites of St Helena Bay, as
well as the p values and the result of the postD hoc comparison of means using the Tukey Honest Significant
Difference (HSD) Test. Significant pDvalues < 0.05* after the Bonferroni adjustment.
Genus
control
pipeline
mean
38.94
15.5
F(df1,2)=1,68
27.09
p9level
0.000 1*
mean
18.38
F(df1,2)=1,68
9.18
p9level
0.003*
mean
49.16
F(df1,2)=1,68
91.5
p9level
0.000 1*
mean
11.28
F(df1,2)=1,68
100.6
p9level
0.000 1*
mean
5.72
F(df1,2)=1,68
3.63
p9level
0.06
9.73
5.09
1.13
3.038
100
Table 3.13:
The oneDway ANOVA, of the abundance of the dominant genera in St Helena Bay, the result of the postD hoc
comparison of means using the Tukey Honest Significant Difference (HSD) Test. Significant differences were only
found between SPA, SPA & SPC (control sites) and all other sites, no significant differences were found between
pipeline sites an were therefore not represented.
showed no significant differences and therefore the results
were not represented. Significant pD values are < 0.05* after the Bonferroni adjustment.
Site
SPA
SPB
SPC
SPA
SPB
SPC
SPA
SPB
SPC
$%
Mean
Mean
Mean
Mean
SPA
28.83
14.33
62.33
9.33
SPB
52.33
0.17
SPC
35.67
1.00
0.66
SHA
5.67
0.19
0.00*
SHB
27.33
1.00
SHC
12.67
SHD
14.17
1.00
51.33
0.99
26.67
0.54
0.52
33.83
0.16
0.81
0.02
4.67
0.84
0.86
0.01
9.00
0.00*
0.00*
0.12
1.00
15.00
1.00
1.00
0.63
8.00
0.00*
0.70
0.00*
0.20
17.67
1.00
1.00
0.89
6.00
1.25
0.13
0.00*
0.02
4.25
0.89
0.90
0.03
SHE
3.67
0.11
0.00*
0.01
0.83
0.40
0.42
SHF
19.67
0.99
0.01
0.71
8.83
1.00
SHG
31.17
1.00
0.30
1.00
10.33
SHH
22.67
1.00
0.03
0.90
SHI
10.67
0.54
0.00*
0.12
SPA
SPB
SPC
10.33
1.00
14.17
0.49
0.80
0.33
3.00
0.13
0.04
0.00*
0.00*
0.27
3.67
0.26
0.09
0.00*
0.00*
0.00*
0.18
0.50
0.01
0.00*
0.00*
0.75
0.00*
0.00*
0.12
0.75
0.03*
0.01
0.00*
0.00*
0.67
0.00*
0.00*
0.05
0.17
0.00*
0.00*
0.00*
1.00
0.08
4.83
0.00*
0.00*
0.14
0.33
0.00*
0.00*
0.00*
1.00
1.00
0.15
6.00
0.00*
0.00*
0.18
0.33
0.00*
0.00*
0.00*
14.33
1.00
1.00
0.54
4.17
0.00*
0.00*
0.12
0.67
0.01
0.00*
0.00*
9.83
1.00
1.00
0.13
5.00
0.00*
0.00*
0.15
0.67
0.01
0.00*
0.00*
101
100
220
90
200
180
80
160
70
140
60
120
50
+
100
40
80
30
60
20
40
20
10
0
0
RIA
RIB
RIC
RID
RIE
RIF
RIG
RIH
C
P
200
24
180
22
RIB
RIC
RID
RIE
RIF
RIG
RIH
C
P
RIA
RIB
RIC
RID
RIE
RIF
RIG
RIH
C
P
20
160
18
140
16
120
14
100
12
80
10
8
60
6
40
4
20
2
0
RIA
RIB
RIC
RID
RIE
RIF
RIG
RIH
C
P
$%
0
RIA
Figure 3.5:
The mean and standard errors for each of the five dominant genera for Robben Island as well as the pooled results for
the control (C) and pipeline (P) sites.
102
Table 3.14:
The results of a oneDway ANOVA, of the abundance of the dominant genera at the control and pipeline sites of Robben
Island, as well as the p values and the result of the postD hoc comparison of means using the Tukey Honest Significant
Difference (HSD) Test. No Significant pDvalues < 0.05 were found after the Bonferroni adjustment.
Genus
!
"
control
pipeline
mean
25
17.3
F(df1,45)
4.187
p9level
0.04
mean
48.8
F(df1,45)
4.57
p9level
0.03
mean
24.56
F(df1,45)
1.868
p9level
0.17
mean
13.13
F(df1,45)
1.63
p9level
0.202
mean
7.06
F(df1,45)
4.16
p9level
0.04
34.7
18.88
17.4
10.82
103
Table 3.15:
The oneDway ANOVA, of the abundance of the dominant genera from Robben Island samples, only significant results
from the postD hoc comparison of means using the Tukey Honest Significant Difference (HSD) Test were represented;
significant pDvalues < 0.05 after the Bonferroni adjustment are highlighted*.
$%
RIE
RIH
RIE
RIC
0.03
RIC
0.02
RIH
0.0006*
RIF
0.01
RIG
0.016
RIE
RIA
0.02
RIB
0.0005*
RIC
0.03
RIG
RIB
0.02
104
Table 3.16:
The following are results of a oneDway ANOVA between the control and pipeline sites of both study areas on the
abundance of live foraminifera per size class. The postDhoc comparison of means using the Tukey Honest Significant
Difference (HSD) Test is also represented. Significant pDvalues < 0.05 after the Bonferroni adjustment.
St Helena Bay
Robben Island
LIVE
LIVE
Size class
Control
Pipeline
p9value
F(df1,2)1,68
> 63 um
616.28
95.23
0.000 1*
17.6
>125 um
800.50
58.87
0.000 1*
41.37
>250 um
141.67
11.63
0.000 1*
41.06
>500 um
1.50
0.81
0.049
4.01
> 63 um
48.7
96.33
0.1
2.85
>125 um
98.43
151.6
0.26
1.27
>250 um
27.14
16.43
0.04
4.16
>500 um
1
0.13
0.0003*
15.76
105
120
Percentage Contribution
100
80
500 um
250 um
60
125 um
63 um
40
20
SHI
SHH
SHG
SHF
SHE
SHD
SHC
SHB
SHA
SPC
SPB
SPA
RIH
RIG
RIF
RIE
RID
RIC
RIB
RIA
0
Stations
Figure 3.6:
Graph depicting the percentage contribution of the abundance of each live foraminiferal size class for each of the
stations in St Helena Bay and Robben Island. The mean data of the foraminiferal size classes for each of the samples
per station were used.
106
20
40
60
80
100
Figure 3.7:
Similarity %
site
PRI
CRI
CSH
PSH
Dendrogram of the BrayDCurtis similarity index between all sites using the abundance of live foraminifera divided into
the size classes. Data were rootDroot transformed and the cluster analysis used GroupDAverage linkage. PRI –Pipeline
107
sites Robben Island, CRI – Control sites Robben Island, CSH – Control sites St Helena Bay and PSH – Pipeline sites St
Helena Bay.
SPA3
SPB3
SPA1
SPB1
SPC2
SPA2
SPA6
SPB5
SPB6
SPC6
SPA5
SPC1
SPB2
SPB4
SHC3
SHC4
SHC5
RIH1
SHG3
RIG4
RIG2
SHG4
RIH5
SHF3
SHG6
SHG2
RIC3
RIF3
RIG3
RIH2
RIH4
SPC4
SHC2
RIF1
RIH6
RIB5
SHC6
SHD3
SHE 3
SHF5
SHI3
RIF5
SHB2
SHB5
RIE 2
RIG1
RIE 6
SHA2
SHH1
SHH4
RIG6
SHE 2
SHG5
SHG1
SHH3
SHI4
SPA4
SHA4
SPC3
SHH2
SHC1
RID1
RID2
RIC4
RID5
SHI1
RIC5
RIC6
RIB6
RIH3
RIF4
RID3
RID6
SHI2
RID4
SHI6
RIB3
SHI5
RIA5
RIB4
RIA3
RIA4
RIA2
SPC5
RIA1
RIA6
RIB1
SHB1
SHF2
RIF2
RIC2
RIB2
RIC1
SHE 6
SHE 5
SHA3
SHA5
SHD5
SHB3
SHD4
SHF4
SHF6
SHF1
RIE 4
SHH5
RIG5
SHA6
SHA1
RIE 3
RIE 5
RIE 1
SHB6
SHD2
SHE 4
SHE 1
2D Stress: 0.11
site
PRI
CRI
CSH
PSH
Figure 3.8:
MDS Ordination of the total abundance of live foraminifera of polluted and control sites in Robben Island and St
Helena Bay using Bray Curtis similarity and fourth root transformation. (PRI –Pipeline sites Robben Island, CRI –
Control sites Robben Island, CSH – Control sites St Helena Bay and PSH – Pipeline sites St Helena Bay).
108
Table 3.17:
The dominant species of foraminifera in the dead assemblages and their percentage of the total numbers, in samples
collected from Robben Island.
Site
Dead
Percentage of the total
RIA
27 %
RIB
27 %
RIC
22 %
RID
34 %
RIE
+
RIF
RIG
%
26 %
17 %
(
20 %
RIH
18 %
CONTROL
17 %
PIPELINE
25 %
109
Table 3.18:
The dominant species of foraminifera from the dead assemblages and their percentage of the total numbers, in samples
collected from St Helena Bay.
Site
Dead
Percentage of the total
SPA
36 %
SPB
40 %
SPC
21 %
SHA
31 %
SHB
20 %
SHC
Elongated bolivinids
26 %
21 %
SHD
Elongated bolivinids
SHE
SHF
19 %
32 %
Elongated Bolivinids
25 %
SHG
28 %
SHH
18 %
SHI
30 %
CONTROL
32 %
PIPELINE
21 %
110
PRI
CRI
CSH
PSH
Dendrogram of the dead foraminiferal assemblages of each sample from each site in St Helena Bay and Robben Island.
Species data were fourth root transformed and the dendrogram was produced using the BrayDCurtis Similarity Index
111
with GroupDAverage Linkage. (PRI –Pipeline sites Robben Island, CRI – Control sites Robben Island, CSH – Control
sites St Helena Bay and PSH – Pipeline sites St Helena Bay).
R IE5
R IG6
R IG1
R IG2
R IG3
R IC4
R IG5
R IE2
R IE4
R IF5
R IA1
R IH2
R IC2
R ID1
R IB4
R ID2
R ID3
R ID5
R ID6
R IB1
R IF2
R IH5
R IH6
R IA6
R IB6
R ID4
R IA3
R IA4
R IB5
R IA2
R IB3
R IC3
R IF1
R IF3
R IH1
R IC1
R IC5
R IF4
R IC6
R IA5
R IB2
R IG4
R IH3
R IH4
R IE3
R IE1
R IE6
SHE4
SHH1
SHI1
SHB6
SHE5
SHB2
SHD6
SHE6
SHA6
SPB5
SHB4
SPC2
SHA1
SHH5
SPA4
SPA3
SHG3
SHA2
SHB1
SPB3
SHA4
SPB6
SHC2
SHG2
SHH4
SHF4
SHG4
SPC6
SPB2
SHG5
SHF2
SHI2
SHI6
SHI4
SHI5
SHC4
SHI3
SHB5
SHG1
SHF6
SHG6
SHC5
SHC6
SHD5
SPB4
SPC4
SPC1
SHD3
SHD2
SHD4
SHC1
SHC3
SHH3
SHF3
SHH2
SPC3
SHF1
SPC5
SHB3
SHF5
SHA5
SHA3
SPA6
SPA2
SPA5
SPA1
SPB1
SHE2
SHE3
SHE1
0
20
40
60
80
100
Figure 3.9:
Similarity %
2D Stress: 0.17
Site
PRI
CRI
CSH
PSH
Figure 3.10:
MDS Ordination of all dead foraminiferal species. Species data were fourth root transformed and the MDS was
produced using the Bray Curtis similarity index. PRI –Pipeline sites Robben Island, CRI – Control sites Robben Island,
CSH – Control sites St Helena Bay and PSH – Pipeline sites St Helena Bay.
112
Table 3.19:
The following are the results of a RELATE statistic in PRIMER which attempts to correlate the dead and live
assemblages of all samples together (ALL) and St Helena Bay (SHB) and Robben Island (RI) separately. All pDvalues
were statistically significant.
ALL
SHB
RI
Rho
0.563
0.388
0.511
P
0.01*
0.01*
0.01*
113
Table 3.20:
The following are the results of the SIMPER procedure in PRIMER between all species of the dead assemblages in all
samples of St Helena Bay. The data were fourth root transformed and the BrayDCurtis similarity matrix was used to
produce the SIMPER. The average similarity percentage of each of the two groups is in brackets and the species most
responsible for determining community structure within each group is in bold (a). The average dissimilarity between
the two groups is in brackets and the species most responsible for the dissimilarity is represented in (b).
(a)
Species
Elongated Bolivinids
perforated bolivinids
% Contribution
12.48
11.25
10.88
10.62
9.36
% Contribution
9.6
9.97
12.19
8.45
10.52
Average dissimilarity
2.52
2.18
2.07
2.07
1.82
1.81
% Contribution
6.48
5.61
5.31
5.31
4.69
4.66
1.78
4.58
1.63
1.61
1.55
1.53
1.39
4.19
4.13
3.99
3.92
3.57
(b)
Species
)
$
%
%
Elongated Bolivinids
114
Table 3.21:
The results of the SIMPER procedure in PRIMER between all species of the dead assemblages in all samples of
Robben Island are represented. The data were fourth root transformed and the BrayDCurtis similarity matrix was used to
produce the SIMPER. The average similarity percentage of each of the two groups is in brackets and the species most
responsible for determining community structure within each group is in bold (a). The average dissimilarity between
the two groups is in brackets and the species most responsible for the dissimilarity is represented in (b).
(a)
Species
Elongated Bolivinids
+ %
+
$
%
% Contribution
% Contribution
Pipeline (63 %)
Control (66.59 %)
11.48
9.84
9.02
8.62
7.82
6.34
10.78
9.12
9.69
6.51
8.09
3.81
(b)
Species
(
Bolivinitidae
'
)
Average
2.25
1.62
1.58
1.49
1.45
1.44
1.34
1.28
1.28
1.27
1.26
% Contribution
6.06
4.37
4.26
4.01
3.89
3.87
3.61
3.46
3.45
3.42
3.38
115
Table 3.22:
The following are the results of the SIMPER procedure in PRIMER between all species of the dead assemblages in the
two study areas. The data were fourth root transformed and the BrayDCurtis similarity matrix was used to produce the
SIMPER. The average similarity percentage of each of the two groups is in brackets and the species most responsible
for determining community structure within each group is in bold (a). The average dissimilarity between the two
groups is in brackets and the species most responsible for the dissimilarity is represented in (b).
(a)
SITE
Species
Elongated Bolivinids
+ %
$ %
+
(b)
Species
Perforated Bolivinids
+ %
+
&
%
(
$
%
%
RI (63.61 %)
% Contribution
11.32
9.75
9.43
8.05
7.92
RI
Average Abundance
0
0.18
1.73
1.59
1.06
0.94
1.01
2.22
1.65
0.3
1.07
1.1
Species
Elongated Bolivinids
Perforated Bolivinids
SHB
Average Abundance
1.68
1.83
0.19
0.31
0
0
0.95
2.08
1.33
0.9
0.85
0.98
SHB (60.95 %)
% Contribution
11.8
11.41
11.01
10.07
9.78
Average dissimilarity
% Contribution
6.38
6.36
6.05
5.01
4
3.59
3.39
3.29
3.08
3.03
2.98
2.9
116
100
90
80
70
60
500 um
50
250 um
125 um
40
63 um
30
20
10
Figure 3.11:
SHI
SHH
SHG
SHF
SHE
SHD
SHC
SHB
SHA
SPC
SPB
SPA
RIH
RIG
RIF
RIE
RID
RIC
RIB
RIA
0
The percentage contribution of the total of each size class of foraminifera in the dead assemblages for each station in St
Helena Bay and Robben Island. The mean of each foraminiferal size class for each of the samples per station was used.
117
Table 3.23:
The following represents the results of a oneDway ANOVA between the control and pipeline sites of both Robben
Island and St Helena Bay in terms of the abundance of dead foraminifera per size class. The Tukey Honest Significant
Difference Tests provided significant values at p < 0.05 after the Bonferroni adjustment.
St Helena Bay
Robben Island
DEAD
DEAD
Size class
Control
Pipeline
p9value
F(df1,2)1,68
> 63 um
295.72
220.63
0.48
0.49
>125 um
367.72
151.62
0.04
4.5
>250 um
130.22
18.90
0.000 1*
18.4
>500 um
1.44
1.15
0.67
0.17
> 63 um
123.1
132.6
0.85
0.03
>125 um
129.1
172.3
0.49
0.49
>250 um
64.85
21.4
0.005*
8.97
>500 um
2.57
0.2
0.000005*
29.01
118
50
60
70
80
90
100
Figure 3.12:
Similarity %
site
PRI
CRI
CSH
PSH
Dendrogram of the BrayDCurtis similarity index between all sites using the abundance of dead foraminifera per size
classes. Data were rootDroot transformed and the cluster analysis used GroupDAverage linkage. PRI –Pipeline sites
119
Robben Island, CRI – Control sites Robben Island, CSH – Control sites St Helena Bay and PSH – Pipeline sites St
Helena Bay.
SHD3
RIG6
SHE4
SPC2
SPC3
SHH1
RID1
SHD5
RID5
SHD6
SHE5
RIG5
SHB6
SHE6
RIE1
RIE2
RIE6
SHE1
SHE3
SHB3
SHH2
SHF1
SPC1
SHF6
SHA3
RIE4
RIE3
RIE5
RIF5
RIG1
SHE2
SPA3
SHC4
SHC3
SHC5
SPB1
SPB3
RIG4
RIG3
RIH5
RIG2
RIH2
SHB5
RID4
RIH6
SHB4
SHF5
RIF1
SHH4
RIC3
RIH3
RIH4
RIF4
SPA5
SHF4
SHG1
RIH1
SHF2
SHG3
SHG2
SHI4
RIF2
RIC2
SPA1
SPA4
SPA6
SPB4
SPA2
SPB6
RIB5
SPC5
RIC6
RIC1
SPB2
RIA2
RIA5
RIB2
SHA4
RIA1
RIB6
RIA6
SPB5
RIC5
SHH3
SHC1
SHB1
SHC2
RIA4
SHC6
SHA2
SPC6
RIB3
SHI5
SHI2
SHI6
SHD2
RIB4
RIA3
SHI3
RIF3
SPC4
SHG4
SHG6
SHG5
SHI1
RIB1
SHD4
RID6
SHB2
SHF3
SHH5
RID2
SHA5
SHA1
SHA6
RIC4
RID3
2D Stress: 0.13
site
PRI
CRI
CSH
PSH
Figure 3.13:
MDS Ordination of the total abundance of dead foraminifera of polluted and control sites in Robben Island and St
Helena Bay using BrayDCurtis similarity and fourth root transformation. PRI –Pipeline sites Robben Island, CRI –
Control sites Robben Island, CSH – Control sites St Helena Bay and PSH – Pipeline sites St Helena Bay.
120
Table 3.24:
The following are the results of a RELATE statistic in PRIMER which attempts to correlate the dead and live
foraminiferal abundance of all samples together (ALL) and St Helena Bay (SHB) and Robben Island (RI) separately.
All pDvalues were statistically significant.
ALL
SHB
RI
Rho
0.473
0.458
0.426
p
0.01*
0.01*
0.01*
121
Table 3.25:
NonDparametric spearman rank order correlations between the live and dead mean foraminiferal size. All correlations
were significant at p < 0.05.
R
ALL
0.66*
Robben Island
0.68*
St Helena Bay
0.69*
122
Table 3.26:
OneDway ANOVA of the mean size of live and dead foraminifera between St Helena Bay (SHB) and Robben Island
(RI). Significant differences are at p < 0.05.
Mean
size live
SHB
118.49
RI
122.08
p
0.43
Mean
Size Dead
111.74
p
0.001*
128.85
123
Chapter 4
A study linking foraminiferal communities to their environment at two study sites of
the west coast of South Africa
Abstract
Sediment samples from around the Robben Island sewage pipeline and
a fish factory pipeline in St Helena Bay were examined for foraminifera, as
well as for a suite of environmental factors. The top 5 cm of each core was
examined from a total of twenty cores. In St Helena Bay samples, species
diversity, richness and abundance were negatively correlated with trace
metals. The percentage nitrogen and all trace metals were negatively
correlated with diversity, richness and diversity while the mean grain size was
positively correlated. However, few of these relationships were significant
(Fe, Pb, Zn and mean grain size), and those that were had very low
correlations.
There were no significant correlations between the environmental
conditions and richness and diversity in the samples from Robben Island. The
abundance of foraminifera was positively significantly correlated with Cd, Cr,
Zn, percentage nitrogen and the mean grain size. In the St Helena Bay and
Robben Island samples, the factors which together most influenced
community structure were the percentage nitrogen, the mean grain size and
Cd, Cr and Cu concentrations.
The dominant genera in St Helena Bay
and $ %
were negatively correlated with trace metals and percentage
nitrogen, although $ %
grain size.
had a positive correlation the mean sediment
was positively correlated with all environmental
variables, however, these correlations were not significant. The dominant
$%
genera from around Robben Island were
&
'
and
few correlations were found and were mostly
with Cd, Cr, Fe and % N and
and &
'
and &
'
may be regarded as good bioD
124
indicators.
although
dominant
was
less
correlated
with
environmental factors and because it is considered an opportunist, it has a
wide tolerance range and would not be indicative of environmental changes.
Both study areas were dominated by small foraminifera and there was no
correlation between the size of the foraminifera and the mean grain size of the
sediments, though the small foraminifera could be indicative of a polluted
environment or the cold temperate waters of both study areas. Robben Island
showed very different environmental conditions to St Helena Bay and did not
show signs of a polluted environment.
Morphological abnormalities in both study areas were low and were
not found to be a reliable method of identifying a polluted environment. The
trace metal content of the shells did not display a significant difference
between the two study areas and did not appear to correspond with the trace
metal concentrations of the sediments. The foraminiferal assemblage structure
of Robben Island was also not indicative of pollution, unlike that of St Helena
Bay.
125
4.1
Introduction
Benthic infaunal organisms, because of their habitation of the sediment water
interface, often reflect local sedimentary conditions in their abundance and diversity
(Mucha
., 2003). Benthic foraminifera have been used as bioDindicators for chemical
and biological environmental factors because of the incorporation of chemicals into their
shells and their changes in abundance or composition in the presence of certain
environmental conditions (Murray, 2001). The factors that control foraminiferal
distribution are still poorly understood and the critical response threshold for
environmental factors may differ between species (Murray, 2001). Foraminiferal
abundance and diversity may be influenced by a number of factors such as depth, water
temperature, salinity, pH, organic matter content or sediment grain size (Duleba &
Debenay, 2003).
Foraminiferal abundance appears to vary with sediment grain size structure, and
increases with a higher percentage of finer sediments, as fine sediments and organic
matter tend to accumulate in the same area (Frontalini & Coccioni, 2008). On the other
hand, coarse sediments have been found to provide more substrata for foraminifera,
particularly those that are attached (du Châtelet
, 2009). Although, benthic species
composition has been linked to sediment grain size its effect in influencing abundance
and diversity has been found to vary from study to study (Bremner
., 2006).
Many studies have shown that a decrease in the abundance and density of
foraminifera can be used as a measure of environmental stress (Frontalini & Coccioni,
2008). Pollution studies using these organisms have been conducted in bays, harbours
, 2006). Foraminifera have been found to be
and coastal margins worldwide (Burone
affected by anthropogenic contaminators like organic enrichment, heavy metals and
petroleum hydrocarbons (Burone
, 2006). Some studies on the effect of sewage
discharge on foraminifera have reported an increase and others a decrease in abundance
and diversity of foraminifera (Topping
., 2006). Topping
(2006) have
hypothesized that in some studies other factors like localized oxygen depletion or
changes in salinity or grain size as a result of sewage pollution may have masked the
effects of an increase in organic matter.
126
Unlike the variable effects of sewage pollution, only negative impacts have been
observed from heavy metal contamination (Scott
Ferraro
., 2001; Frontalini
., 2009).
. (2006) have found a correlation between the level of chemical pollutants
and foraminifera, with a totally barren assemblage in a highly polluted harbour. Similar
effects were observed by Yanko
. (1994) in sites exposed to heavy metal and coal
pollution; in addition, these authors also observed that assemblages were dominated by
species with smaller tests. The environmental factor or factors which are close to the
threshold of tolerance for any species will therefore limit its distribution (Murray, 2001).
While many authors have reported test abnormalities as an indication of a polluted
environment (Yanko
, 1994; Alve, 1991 and Sharifi
., 1991), test abnormalities
are found in all foraminiferal species under normal environmental conditions (Burobe
, 2006). These may be due to environmental stresses (including temperature, pH,
salinity, food availability, high wave action etc.), which may slow down or change the
rate of growth of chambers (Alve, 1991). Test abnormalities may also merely be
intraspecific variation, as in )
forms in South African samples (Toefy
which presents itself in many different
, 2005). Marginal and shallow marine
environments have variable environmental conditions and have been found to possess
species with much ecophenotypic variation (Murray, 1991). Therefore, it may be difficult
to pinpoint the reason(s) for morphological abnormalies when observed, and specifically
regard the anthropogenic pollutant as the cause for the defect. Only controlled laboratory
experiments can conclusively eliminate certain factors. Samir & ElDDin (2001,) in XDRay
analysis of deformed and normal tests of the same species showed that species that were
deformed showed a higher concentration of trace metals within their shells than
specimens that were normal, implying that trace metals might have been responsible for
the deformities present.
This chapter examines the influence of environmental factors (mean grain size,
percentage nitrogen and trace metals) measured within the sediments on the foraminiferal
assemblages at two study areas on the west coast of South Africa, St Helena Bay and
Robben Island. Morphological abnormalities and trace metal concentrations, found in the
foraminiferal tests are presented. The aim of the chapter is to determine whether
foraminiferal assemblages can be used as proxies for environmental conditions.
127
4.2
Materials & Methods
4.2.1
Laboratory Analyses
All laboratory analyses have been explained in detail in the previous chapters.
4.2.1.1 Shell Morphology
Any morphological abnormalities in live foraminifera were noted and counted
from the 300 specimens that were picked per core. Morphological abnormalities were
regarded as any change in structure i.e. regrowth of chambers in an abnormal way
(protuberances, distortion of chambers, difference in size or shape of one or more
chambers), double apertures, wrong coiling direction or Siamese twins (Samir
.,
2001) . Broken or abraded tests which did not display any reDgrowth were not counted as
abnormal. Representatives of these abnormal tests were photographed using Scanning
Electron Microscopy.
4.2.1.2 Scanning Electron Microscopy and Elemental Analysis
Representative examples of foraminifera were scanned to examine any
morphological abnormalities as well as to perform elemental analysis on the shells.
Scanning was performed using a Hitachi X650 SEM in conjunction with the XDanalysis
EDAX utilizing the computer program Genesis 2000. Samples were carbon coated rather
than gold coated using the EMITECH K950X. For elemental analysis, 1 cm2 of scan area
and 100 s live time analysis was used to collect and identify the elements present. The
atomic % of each element measured was recorded. At least 10 live specimens of
were examined per site. This species alone was chosen as it
appeared most frequently in all samples and the use of more species introduces other
variables (e.g. shape, chamber size or number, etc) that would make the interpretation of
results difficult.
4.2.2
Statistical Analyses
In order to determine whether the species richness, diversity and abundance of live
foraminifera and all measured environmental variables were correlated, the nonD
128
parametric Spearman correlation was used. Significant values of less than 0.05 were used
after calculating a Bonferroni pD value.
The BIOENV BEST procedure was conducted to explain the environmental variables
which were most responsible for the assemblage structure (Clarke & Gorley, 2006). NonD
parametric Spearman Rank Order correlations between the dominant genera of both study
areas and the environmental variables were performed. Genera and not individual species
were used as the relate function in PRIMER revealed a significant correlation (see
Chapter 3).
An MDS Ordination of the concentration of the measured elements in the
foraminiferal tests of control and pipeline sites of both study areas was produced. Data
were fourth root transformed and Euclidean distance was used to produce the
resemblance matrix. NonDparametric Spearman Correlations of trace metals in sediment
samples and trace metals of shells per site were determined. ANOVA was used to
determine any differences in the trace metal concentrations of the shells between stations
as well as between sites and the two different study areas.
4.3 Results
Summary of results from Chapter 2
Environmental variables
The mean sediment grain size of both St Helena Bay and Robben Island samples
was large (> 1 Phi), but the sediment samples from Robben Island were larger.
Trace metal concentrations of the sediments from St Helena Bay samples were higher
than those of Robben Island but concentrations were not higher than those of the
USEPA sediment quality guidelines for ERM where toxicity would affect biota. The
percentage carbon from Robben Island samples were higher than those from St Helena
Bay, but the percentage nitrogen was higher in St Helena Bay than Robben Island
samples.
129
Summary of results from Chapter 3
Foraminiferal assemblages
The diversity and species richness of the live foraminiferal assemblages was higher
in the samples from around Robben Island but the abundance of foraminifera from St
Helena Bay samples was higher than from the sediments of Robben Island samples. The
dominant genera in St Helena Bay samples were
$%
. In the Robben Island samples
&
'
4.3.1
and
$%
were dominant genera.
Community Structure
Significant negative correlations were found between the species richness, species
diversity and the abundance of live foraminifera and most sediment trace metals except
Cd, Cr and Cu in the St Helena Bay samples (Table 4.1). The percentage nitrogen was
significantly negatively correlated with the species diversity and species richness, but not
with the abundance of the live foraminifera. The mean grain size was not significantly
correlated with species richness, diversity or the abundance of the live foraminifera.
Significant correlations were fewer in Robben Island samples and no significant
correlations were found between richness and diversity and the measured environmental
variables. (Table 4.2). The abundance of live foraminifera was significantly correlated
with Cd, Cr, Zn and the mean sediment grain size.
When pooling samples from both study areas, significant negative correlations
were found between the species richness and diversity and Fe, Pb, Zn and the percentage
nitrogen (Table 4.3). Although the abundance of foraminifera followed more or less the
same pattern, it was not significantly correlated with the percentage nitrogen. All
correlations were low and were greater than the Bonferroni pDvalue of 0.001.
The BIOENV BEST procedure revealed that the environmental variables that
appeared to most influence community structure in the St Helena Bay samples were the
percentage nitrogen, the mean grain size and Cd, Cu and Pb concentrations in the
sediments (Table 4.4). The results of the BIOENV BEST on Robben Island samples
revealed much the same, except Pb did not feature as an important environmental factor
(Table 4.5). The BIOENV of the pooled samples placed the percentage nitrogen and Cd
130
as being very large contributors (42 %) to the assemblage structure, additionally, the
mean sediment grain size, Cr and Cu concentrations play a smaller role (Table 4.6). This
contrasts with the results from St Helena samples in that Pb is also listed as an important
factor.
4.3.2
Genera
The dominant genera in the assemblages of St Helena Bay samples were
$%
and
NonDparametric Spearman rank order
correlations between the measured environmental variables and the abundance for each of
the dominant genera showed mostly negative correlations with the trace metals and the
percentage nitrogen (Table 4.7). The relationship with the mean grain size was variable.
Most correlations were not significant or had very low correlation coefficients. The
and $ %
abundance of
followed the same pattern with negative
significant correlations with Fe, Pb and Zn and positive significant correlations with the
mean sediment grain size The abundance of
was negatively significantly
correlated with Cd, Zn and the mean sediment grain size. The abundance of
showed no significant correlations and
was only significantly correlated with
the mean sediment grain size.
The dominant genera in the Robben Island samples were
$%
&
'
and
NonDparametric Spearman rank order
and &
correlations revealed
'
as being negatively
significantly correlated with Cd, Cr, Fe concentrations in the sediments, while
additionally the abundance of
and
were negatively significantly
was only
correlated with the percentage nitrogen (Table 4.8). The abundance of
negatively significantly correlated with the mean grain size. The abundance of $ %
did not correlate with the environmental variables. The effect of the environmental
variables appeared to be most prevalent in
&
'
and
,
while the mean grain size appeared to be the least important factor influencing the
abundance of the dominant genera in Robben Island.
131
4.3.3
Foraminiferal size structure
Foraminifera were most abundant in the 63 Rm and 125 Rm size classes in the St
Helena Bay samples, these size classes did not correspond with the dominant sediment
size class (Table 4.9). The dominant size class of foraminiferal tests in the Robben Island
stations was 125 Rm, though the dominant sediment size class which was 500 Rm (Table
4.10). A Spearman Rank Correlation which related the abundance of foraminifera per
size class to the sediment structure yielded a Rho value of D0.002 and a pDvalue of 0.51
(St Helena Bay) and Rho value of D0.003 and a pDvalue of 0.58 (Robben Island) showing
no significant correlation between size structure of the sediments and that of the live
foraminifera.
4.3.4
Morphological Abnormalities
Test abnormalities were not found in large numbers and varied from 0.6 % to 4%
in all stations (Table 4.11). The main abnormalities observed were broken chambers with
some regrowth, Siamese twins and abnormal chamber growth. These abnormalities were
mainly observed in the family Cibicididae and a few in the Elphididae (Appendix 4.1).
Large numbers of broken or abraded tests were found.
4.3.5
Elemental Analysis of Shells
An MDS Ordination of all the measured elements of the foraminiferal tests
showed a large amount of overlap between the control and pipeline sites of both Robben
Island and St Helena Bay (Fig 4.1; Appendix 4.2). No clear structure or differences
between the elemental composition of the shells of the two study sites was evident. The
concentrations of the trace metals within the foraminiferal tests of the pipeline sites of St
Helena Bay appeared to display a larger degree of variation than those of the other sites.
Comparisons of all Robben Island stations showed no significant differences in
the elemental composition of the shells, except in station RIE where shells had a
significantly higher concentration of Cr than those from all other stations (Appendix 4.3.1
– 4.3.8) no significant differences were found between the control and pipeline sites.
Comparisons of all control and all pipeline sites of Robben Island showed no significant
132
difference between the analyzed shell elements (Appendix 4.3.9). In St Helena Bay, a
comparison of elements within the shells revealed that shells within station SHH had a
significantly lower concentration of calcium with a significantly higher concentration of
Zn and Fe than the other sites (Appendix 4.3.10 – 4.3.17).
Significantly higher
concentrations of Mg and Fe were found when the control and pipeline sites were
analyzed in St Helena Bay (Appendix 4.3.19).
When the concentrations of elements of the shells were compared between the
two sites, Mg concentrations were significantly higher and Ca significantly lower in St
Helena Bay than in Robben Island specimens. No significant differences were apparent
in the trace metal concentrations but an expected higher concentration due to higher
sediment trace metal concentration did not occur in St Helena Bay except for Fe and Pb
(Appendix 4.3.19).
NonDparametric Spearman correlations performed to relate the trace metal
contents of the shells with that of the sediments between all samples revealed a no
significant correlation with all the trace metals (Fig. 4.2). The St Helena Bay samples did
not have any significant correlations between the trace metals of the sediments and the
concentrations of trace metals in the tests, while those of the Robben Island samples
showed significant negative correlations between Cd, Cr, Cu and Zn concentrations of the
tests and the sediments (Table 4.12). The control sites showed no significant correlation
while the pipeline sites only had a significant negative correlation with Cr concentration
in the sediments. These significant correlations were quite low.
4.4
Discussion
4.4.1
Community Structure
The abundance, species richness and diversity of foraminifera increased with an
increase in the mean grain size of the sediments, although these correlations were not
significant. A high abundance of species and individuals have been found in fine, silty
sands as opposed to coarse sand or clay and this is thought to be a result of higher organic
enrichment in fine sediments and therefore greater food availability (Samir & ElD Din,
2001). That said, Frontalini & Coccioni (2008) have found that this is not always true
when examining individual species like
The relationship
133
between foraminifera and grain size appears to change depending on the individual
species present and the species dominating in these study areas appear to be able to take
advantage of the greater habitats offered by coarser grain sizes.
The percentage nitrogen in sediments is often an indication of organic matter input,
however, the percentage nitrogen was negatively correlations with richness, diversity and
the abundance of foraminifera in St Helena Bay samples, but positively correlated in
Robben Island samples. These differing results may be a result of the higher percentage
nitrogen concentrations found in St Helena Bay as opposed to Robben Island and may be
a result of increased eutrophication as a result of increased organic carbon loading.
Bacteria break down organic compounds to carbon dioxide, water and ammonia, when
organic matter input increases, the amount of nitrogen produced by benthic organisms
also increases (Mojtahid
2009). While this increase in nitrogen leads to more
phytoplankton production, too much organic matter can lead to an increase in
eutrophication. Nitrogen pollution has been found to be highest near agricultural activity
and urban development, and is the leading cause of the increase in eutrophication
observed in coastal systems (Howarth & Marino, 2006). An increase in eutrophication
can lead to changes in the biotic community structure in marine ecosystems (Smith
2006).
The BIOENV BEST procedure in PRIMER revealed a high contribution of the
percentage nitrogen in the sediments in determining community structure. Besides the
input of organic matter into the system from the processing of the fish, St Helena Bay is
sheltered and has a long retention time of water, which traps and accumulates organic
matter that has been deposited there (Walker & Pitcher, 1991). Anthropogenically
sourced organic matter has been found to produce aboveDbackground foraminiferal
population densities, evident in the large abundance of foraminifera in St Helena Bay as
opposed to Robben Island (Bernhard, 1986; Yanko
1994; Scott
, 2001). In St
Helena Bay, the effect of the increased organic matter may not be found near the source
of pollution because oxidation of organic matter near the source may be high enough to
cause local anoxia and therefore a decrease in population density but populations further
from the point may have larger population sizes (Scott
, 2001).
134
Both study areas normally have high levels of organic carbon as a result of upwelling
events, they may have large phytoplankton blooms and eventually high levels of
phytodetritus these effects, however, are seasonal (more so in St Helena Bay than Table
.,
Bay) and may not have a permanent effect on the community structure (Scott
2001). Opportunistic benthic foraminiferal species take advantage of high levels of
phytodetritus and increase in abundance (Scott
., 2001). Upwelled areas that
experience seasonal increases in organic matter input (phytodetitritus) to the sediments,
may experience variable increases in the abundance of foraminifera, this results in spatial
variability and a patchy distribution of foraminiferal species (Diz
., 2006).
In a study of an upwelling region in NW Spain, it was found that seasonal variability
of organic carbon flux to the seafloor (especially during upwelling and downwelling
events) made assessing the correlation between foraminiferal abundance, biomass and
assemblage composition difficult, as foraminifera respond quickly to even small changes
in organic matter over short time periods (Diz
., 2006). Most foraminifera that
increased in abundance during upwelling events were considered to be rDstrategists that
reproduced quickly in response to phytoplankton blooms, a change in the abundance of kD
strategists was found to be a longDterm response to low oxygen concentrations or
reducing microenvironmental conditions (Diz
., 2006). Because sampling took place
in spring and summer when upwelling occurs in the study area, the correlations with
foraminiferal abundance and diversity with organic carbon were significant, an
assessment after upwelling events may be different as organic carbon could be depleted.
Iron, Pb and Zn concentrations in the sediment appeared to negatively impact the
diversity and richness and abundance of foraminifera in St Helena Bay samples. All other
trace metals also showed a negative impact. In studies of foraminifera, the trace metal
concentrations have only been found to negatively impact communities (Scott
.,
2001) No significant correlations were found between the richness and diversity of
Robben Island samples and the trace metals in the sediments. The concentrations of trace
metals in Robben Island samples were much lower than those of St Helena Bay which
may account for the fact that foraminifera did not appear to be impacted. Other pollution
studies have also reported lower foraminiferal diversity in response to high trace metal
concentrations (Ferraro
., 2006). Cadmium, Cu and Cr were the trace metals most
135
responsible for the community structure of both study areas although none of the trace
metals displayed any significant correlations with species diversity or species richness of
foraminifera. The effects of trace metals on the community structure appears to be more
marked when there is a concurrent input of organic matter, but on their own appear to
have minor effects on foraminiferal diversity (Scott
., 2001). Ferraro
. (2006)
reported an area completely devoid of foraminifera in Diaz dock, Naples where the
concentrations of trace metals were higher than USEPA ERM levels. In both study areas,
there was not a complete absence of foraminiferal specimens, although, some stations
especially in St Helena Bay had extremely low numbers. While this suggests that the
levels of trace metals in this area are generally tolerable for foraminifera, some localized
effects particularly in the St Helena Bay stations may be occurring.
4.4.2
Genera
The correlations between the abundance of all the dominant genera varied in the
samples from St Helen Bay and Robben Island and correlations were not very high. The
grain size does not appear to be an important factor influencing these organisms, as it
appears that different types of foraminifera could inhabit different sediment
microhabitats. Grain size influences the depth to which foraminifera are able to live, fine
sand and mud are often anoxic deeper than 1 cm and coarser sediments are less anoxic
allowing deeper penetration of foraminifera (Murray, 1991).
The percentage nitrogen, however, had significant negative correlations with
and
(Robben Island) and
(St Helena Bay). These species may not be
as tolerant to the increased nitrogen input into the system.
has been found to
dominate shallow water assemblages irrespective of substrate type or percentage carbon
input (Frontalini & Coccioni, 2007) and is therefore a species with wide tolerance ranges
and could be regarded as opportunistic.
All the dominant genera from St Helena Bay had a negative relationship with trace
metal concentration of the sediments, but only
significantly correlated with Fe, Pb and Zn and
and &
'
and $ %
were
with Zn and Cd.
while
in Robben Island had significantly negative
correlations with Cd, Cr and Fe. In an attempt to identify proxies for the two study areas
136
for trace metals concentrations in sediments, it appears that different species should be
does not appear to be a good indicator of environmental conditions as it
used.
does not appear to respond to changes in environmental conditions. $ %
and
appear to have different responses in the two study areas and may be responding
to conditions other than those which have been measured. Specimens of bolivinids in the
sites of St Helena Bay were also glassy or transparent (personal observation) which has
been commonly found in foraminifera in low oxygen environments. High acidicity in
normally leads to reduced carbonate uptake and therefore glassy or transparent tests
(Bernhard, 1986). Acidity was not measured in this study; but could possibly be implied
by the presence of these test types.
has the same reponse in both study areas and appears to be the only species
which can be used as an indicator, although, &
'
(Robben Island) and
(St Helena Bay) also appear affected by environmental conditions.
,
have been found to be facultative anaerobes and able to develop even under
stressed conditions (Burone
., 2006). In some temperate regions it has been found
that species of Elphidium flourish in nearDshore polluted environments (Samir
2000; Scott
2001).
and more specifically
identified in this study has
been found to be sensitive to heavy metal pollution even at low concentrations (Frontalini
& Coccioni, 2008).
%
forma
has been found to dominate areas
close to sewage, fertilizer and industrial outfalls (Seiglie, 1971; Alve, 1987; Yanko
1994; Scott
., 2001).
.,
has been globally used as an indicator of high trace
metal concentrations and appears to be an important indicator of chemical stress (Bergin
., 2006; Ferraro
., 2006). The genus
therefore appears to be able to
respond to many different stressors and therefore could be used as an indicator as
identified in the St Helena Bay samples.
and
are both adapted to
marginal and shallow marine environments and are able to survive in highly polluted
waters, and easily survive low oxygen conditions (Thomas
., 2004). &
'
are unable to tolerate high levels of toxic trace metals therefore their absence in an area
may be indicative of a polluted environment, as in St Helena Bay.
137
4.4.3
Foraminiferal Size Structure
The dominant size class of the foraminiferal assemblages of both study areas did not
appear to be influenced by the dominant sediment grain size. Foraminiferal assemblages
in St Helena Bay and Robben Island were dominated by the size classes 63 m 125 m.
The smaller of the size classes dominated in both live and dead specimens around the
pipeline despite the fact that sediment size was dominated by a larger size class, implying
that sediment size had very little to do with the size of foraminifera that are being
supported in this environment. Sediment grain size has been shown to influence the size
of organisms found in the sediment (McLachlan, 1978), however, in a system not
strongly influenced by factors like increased organic carbon, nitrogen and trace metals
this would probably be the case.
The sediments at both study areas were coarse, indicative of a wellDaerated
environment; this may explain why all the foraminiferal size classes were not correlated
with the corresponding sediment size class in terms of abundance. All size classes of
foraminifera were able to penetrate through the loosely packed coarse sand grains.
Sediment size therefore appears to have very little impact on overall foraminiferal size
structure. Benthic foraminifera can be epifaunal or infaunal and their shape and size and
orientation are often linked to the nature of their substrate within their environment,
because the size of the grains will influence their ability to move and their ability to feed
(Murray, 1991). The coarse grain size may also provide more habitats for even small
foraminifera particularly those that attach to substrates (du Châtelet
., 2009).
The presence of heavy metals is thought to stunt growth and cause a physiological
disturbance in the growth of foraminifera (Samir
2001). All trace metals, except Cd
and Cr, in the sediments were found to be negatively significantly correlated with the
abundance of foraminifera of St Helena Bay samples but played a more positive role in
Robben Island samples. Bernhard (1986) also suggests that smaller lighter foraminifera
stand less of a chance of sinking deeper into anoxic sediments than foraminifera that are
larger and heavier and that smaller tests have a larger surface area: volume ratio
enhancing uptake of oxygen. Therefore the dominance of the smaller size class of
foraminifera found in both study areas may be due to the high trace metal content of the
sediments or even an oxygen poor environment. Bernhard (1986) has further suggested
138
that smaller foraminifera would be more successful in an oxygen deficient environment
than larger foraminifera as sufficient oxygen would be available for their metabolic
activities.
4.4.4. Shell Morphology
Test deformities in St. Helena Bay and Robben Island samples were not high,
ranging from 0.6 % – 4 % of the total 300 picked foraminifera per sample. It has been
.,
found in previous studies that test deformities were usually less than 10 % (Scott
2001). It therefore appears as if the level of pollutants is not high enough to have caused
this phenomenon. Alve and Olsgard (1999) also reported no increased abundance of
deformed tests in experiments where foraminifera were exposed to high concentrations of
copper.
These abnormalities (abnormal chamber growth and Siamese twins) although
observed in different families were mainly observed in the family Cibicidae and a few in
the Elphididae.
The Cibicidae, however, have been known to have varying test
morphology determined by their environment and the substrate to which they attach
themselves, these perceived abnormalities may therefore merely be this variation. Samir
& ElDDin (2001) observed most abnormalities in the Miliolids; suggesting that Miliolids
were most sensitive to pollutants. Miliolids were absent in St. Helena Bay samples which
may be a direct result of pollution or may be that Miliolids are most abundant in shallow
warmDwater and coral reef regions (Cushman, 1959). In an unpublished thesis (Toefy
, 2002) found that Miliolids increased in abundance on the south coast of South Africa
which is characterized by warmer more stable water temperatures than the west coast
which is subject to cold temperatures and many temperature fluctuations during
upwelling.
Studies by Yanko
(1994), Alve (1991) and Sharifi
. (1991) have
correlated morphological abnormalities with trace metal concentrations. Sharifi
.,
1991 has also concluded in laboratory experiments using Cu that certain concentrations
of copper cause morphological abnormalities.
Foraminiferal tests can be used as indicators of wave turbulence and bottom
currents, as high velocities often cause broken or abraded tests (Scott
., 2001). The
139
foraminifera in the St Helena Bay samples had a large number of broken or abraded tests
which attests to their position in wave turbulent area; this is not an indication of a high
velocity current as it has already been established that currents in St Helena Bay and
resident time of water is very slow (Walker & Pitcher, 1991). Toler & Hallock (1998)
suggest that large numbers of broken specimens are a result of stress which compromises
biomineralization in shells of foraminifera.
It is extremely difficult when doing a onceDoff study and only studying the top
few centimetres of a core to conclusively say whether morphological abnormalities are a
result of chemical factors within the sediments. Morphological abnormalities could also
be caused by a range of factors both natural and anthropogenic and it would be difficult
to isolate any specific cause. In a study conducted by Elberling
. (2003), a core was
examined where preD, during and postDpollution foraminiferal tests were examined. This
study could then examine natural background abnormalities comparing it to occurrences
of abnormalities during pollution events, and could therefore conclude that higher trace
metals contributed to an increase in morphological abnormalities.
4.4.5
Elemental Analysis
From the analysis of the trace metals concentration in the shells of
foraminifera, it appeared as if there was no correlation between the concentration of the
metals in the sediment and the concentration of the metals in the foraminiferal tests. The
trace metal concentration of the sediments does play some role in determining the trace
metal content of the foraminiferal tests, however, the conflicting results from the two
sites and the low correlations may mean that some other factor is controlling the trace
metal uptake. Marsden & Rainbow (2004) found that in crustaceans, the bioavailability of
trace metals did not necessarily follow the absolute concentrations of trace metals in the
sediments in the same order of magnitude.
Metals entering organisms are either excreted or detoxified, detoxification occurs
when metals are bound so that they are unavailable to metabolites within the organism,
however, when excretion and detoxification is less than uptake, the trace metal becomes
toxic to the organism (Marsden & Rainbow, 2004). Metals are concentrated into protein –
rich tissues such as the liver and muscle in organisms as they tend to bind with sulphydryl
140
groups of proteins (Islam & Tanaka, 2004). This could possibly explain why the
concentration of metals is not high in the shells which consist mainly of calcium
carbonate, a hard substance. The fact that foraminifera have such a small mass of
cytoplasm might also be a contributing factor for it being less able to take up trace metals.
The other important factor may be that some metals have an inhibitory effect on toxic
metal uptake by aquatic organisms, for example, Zinc has been found to inhibit the
uptake of lead and some other metals (Elberling,
2003; Marsden & Rainbow 2004).
That is, one has to determine the bioDavailability of these trace metals which depends on a
number of factors. These factors may be the chemical speciation of metals, the control of
metal concentration by FeDoxides and organic compounds which scavenge metals,
competition between trace metals, bioturbation by benthic fauna, changes in pH or redox
reactions (Bryan & Langston, 1992).
Another factor which could be playing a role in the lack of strong correlations
between the sediments and the tests could also be that foraminifera may be able to
regulate the concentrations of the trace metals within their shells, that is, trace metals will
not be absorbed exponentially but will level off at a certain point. This was evident in
correlations where the concentrations in the tests remained low despite an increase in the
trace metal concentrations of the sediments. This has been found to occur in some
mussels which have been found to be partial regulators of copper and / or zinc (Rainbow
& Phillips, 1993), and decapods which tend to regulate all trace metals in their tissues in
varying trace metal concentrations (Marsden & Rainbow, 2004). In a study on polychaets
in S.W. England, there was no clear relationship with Fe, Mn and Zn concentrations in
the sediments and the tissues, but Cu concentrations reflected more bioDavailability
(Bryan & Langston, 1992). Trace metals also display competition for attachment sites in
organisms, for example, Cu with Ag, and Zn with Cd, and Pb was found to bind strongly
with FeDoxyhydroxides which may regulate their bioDavailability and uptake (Bryan &
Langston, 1992).
The foraminiferal shells of SHH showed a significantly higher concentration of
trace metals than other sites but a lower concentration of Calcium. Yanko & Kronfeld
(1992) in Samir & ElDDin (2001) suggested that high trace metal concentration weakens
biological barriers that distinguish between the uptake of Mg and Ca, therefore shells
141
formed in highly polluted areas often have a lower Calcium and higher Magnesium
concentration in their shells and are weaker. This was apparent in the shells from the St
Helena Bay samples which displayed a significantly higher concentration of Mg and
significantly lower concentration of Ca than those from Robben Island. Magnesium
modifies the morphology of calcite crystals, forming triangular crystals as well as
affecting the organic matrix of glycosaminoglycans which weaken the test structure
(Toler et al., 2001). A similarity was found to be the case in an experiment on oyster
shells where Calcium: magnesium ratios were affected by pollutants (Almeida
.,
1998).
The foraminiferal shells of RIE had a higher chromium concentration. Chromium,
along with copper and zinc has been found to be more easily absorbed than lead (Samir &
ElD Din, 2001). Elberling
(2003) reports that Zinc is one of the essential metals
which inhibits the toxicity of lead and other metals, and may have an inhibitory effect on
toxic metal uptake by aquatic organism. Zinc and Lead were two trace metals important
in the grouping of sites according to trace metal content in Robben Island samples.
Biomonitors of trace metals cannot be regulators but have to be net accumulators
of trace metals in order to make a proper assessment of the environment.
4.4 Conclusions
The trace metal concentrations of St Helena Bay samples were much higher than
those of Robben Island. Therefore, the probability that some of these sediments could be
toxic to living organisms has to be considered. This is evident in the decrease in the
abundance, species richness and diversity of foraminifera with increasing trace metal
concentrations in St Helena Bay, while Robben Island showed mostly positive
correlations, which were significant for abundance. The percentage nitrogen had negative
correlations with abundance, diversity and richness in St Helena Bay but positive
correlations in Robben Island. As the grain size increased in both study areas diversity,
richness and abundance decreased except for the abundance of foraminfera in Robben
Island which actually increased with increasing grain size. The two study areas had
obvious differences with regards to their diversity, richness and abundance which appear
to be influenced by their differences in trace metal concentrations of the sediments as
142
well as the percentage nitrogen. The mean grain size does not appear to have a very
strong influence over the diversity, abundance and richness.
When examining the community structure it became clear that the most important
factors determining this structure were the percentage nitrogen and Cd, while the Cr and
Cu concentrations and the mean grain size played a smaller role. The presence of the
mean grain size in this structure may appear contradictory to previous statements
regarding diversity, richness and abundance but community structure refers more to the
abundance of foraminiferal specimens within each species and is thus a different
parameter which is being examined.
Genera which appear to be related to the environmental conditions within the
sediments were
&
'
and
, as well as the presence/absence of
These genera appear could possibly be used as proxies for the
environmental factors, as bioDindicators are normally the ones which are most affected by
the changes in environmental factors.
Both assemblages were dominated by small foraminifera despite being found in
an environment dominated by a large mean grain size. This may be a result of the high
trace metal content or low oxygen environments known to limit growth of foraminifera or
the temperate waters which support smaller foraminifera than warmer waters.
Morphological abnormalities in both study areas were negligible and below 5 %,
the foraminifera in both study areas do not appear to be affected although it is difficult to
conclusively comment as no baseline studies of the area exists. The trace metal content of
the shells seem largely unrelated to that of the sediments and as trace metals have been
known to cause morphological abnormalities, this may be the reason for the low
percentage of abnormality. Foraminifera may be affected by trace metals but it appears
that foraminifera are able to regulate trace metals within their tissues or that the
bioavailability of trace metals within this system is low.
143
Table 4.1:
The following are the results of the nonDparametric Spearman Rank Order correlations between Species Richness, Species
Diversity and the abundance of live foraminifera in all samples and all environmental variables in St Helena Bay. Significant RD
values are at p < 0.05*.
Species Richness
Species Diversity
Abundance
Cd
D0.218
D0.218
D0.180
Cr
D.0773
D0.112
D0.099
Cu
D0.178
D0.189
D0.203
Fe
D0.282*
D0.310*
D0.269*
Pb
D0.260*
D0.286*
D0.332*
Zn
D0.298*
D0.324*
D0.323*
%N
D0.243*
D0.296*
D0.205
Mean Grain Size
0.219
0.146
0.166
144
Table 4.2:
The results of the NonDparametric Spearman Rank Order correlations between Species Richness, Species Diversity and the
abundance of live foraminifera and all environmental variables for the Robben Island samples are represented. Significant RD
values are at p < 0.05*.
Species Richness
Species Diversity
Abundance
Cd
D0.123
D0.182
0.299
Cr
0.086
0.053
0.296
Cu
D0.054
0.033
0.137
Fe
0.089
0.125
0.243
Pb
0.140
0.151
D0.093
Zn
0.117
0.083
0.425*
Mean Grain Size
D0.086
D0.098
0.416*
% N
0.168
0.031
0.561*
145
Table 4.3:
The results of the Pearson Product Moment correlations between Species Richness, Species Diversity and the abundance of live
foraminifera and all environmental variables using pooled data from both study areas. Significant RD values are at p < 0.05 *.
Species Richness
Species Diversity
Abundance
Cd
D0.22
D0.22
D0.18
Cr
D0.08
D0.11
D0.10
Cu
D0.18
D0.19
D0.20
Fe
D0.28*
D0.31*
D0.27*
Pb
D0.26*
D0.29*
D0.33*
Zn
D0.30*
D0.32*
D0.32*
%N
D0.24*
D0.30*
D0.20
Mean Grain Size
0.22
0.15
0.17
146
Table 4.4:
The BIOENV BEST procedure in PRIMER for St Helena Bay samples which attempted to explain the environmental variables
most responsible for assemblage structure. Data was log x+1 transformed. Spearman rank correlation was performed using
Euclidean distance.
Percentage Contribution
Variable (s)
23.1
Cd, Cu, % N
23.1
Cd, Cu
23.1
Cd, Cu, % N, Mean Grain Size
23.1
Cd, Cu, Mean Grain Size
22.9
Cu, % N
22.9
Cu, % N, Mean Grain Size
22.9
Cu, Mean Grain Size
22.9
Cu
22.2
Cd, Cu, Pb, % N, Mean Grain Size
22.2
Cd, Cu, Pb, Mean Grain Size
147
Table 4.5:
Results of the BIOENV BEST procedure in PRIMER for Robben Island samples, which attempted to explain the environmental
variables most responsible for assemblage structure. Data was log x+1 transformed. Spearman rank correlation was performed
using Euclidean distance.
Percentage Contribution
Variable (s)
16.4
Cd, % N
11.9
%N
11.4
Cd, Cu
11.4
Cd, Cu, % N
11.3
Cu
11.3
Cu, % N
10.5
Cd, Cu, % N, Mean Grain Size
10.5
Cd, Cu, Mean Grain Size
10.4
Cu, % N, Mean Grain Size
10.4
Cu, Mean Grain Size
148
Table 4.6:
BIOENV BEST was used to explain the environmental variables most responsible for the assemblage structure of both Robben
Island and St Helena Bay samples. Data were log x+1 transformed and Euclidean distance and Spearman rank correlation was
performed.
Percentage Contribution
Variable (s)
42.7
Cd
42
Cd, % N
29.3
Cd, Mean Grain Size
29.3
Cd, % N, Mean Grain Size
29.2
Cd, Cr, Cu, % N, Mean Grain Size
29.1
Cd, Cr, Cu, Mean Grain Size
29
Cr, Cu, % N, Mean Grain Size
29
Cr, Cu, Mean Grain Size
29
Cd, Cr, Cu, % N
29
Cd, Cr, Cu
149
Table 4.7:
Results of the NonDparametric, Spearman Rank Order Correlation between all environmental variables and the abundance of the
dominant genera for St Helena Bay. Significant RDvalues are at p < 0.05*
Cd
D0.358*
D0.165
D0.210
D0.210
0.006
Cr
D0.123
D0.097
D0.064
D0.059
0.083
Cu
D0.146
D0.053
D0.173
D0.225
0.153
Fe
D0.194
D0.166
D0.273*
D0.282*
0.015
Pb
D0.225
D0.120
D0.319*
D0.368*
0.019
Zn
D0.290*
D0.226
D0.373*
D0.403*
0.057
% N
D0.246*
D0.102
D0.199
D0.207
0.051
Mean Grain Size
D0.008
0.054
0.262*
0.265*
0.351*
150
Table 4.8:
Results of the NonDparametric Spearman Rank Order Correlation between all environmental variables and the dominant genera of
Robben Island. Significant RDvalues are at p < 0.05*.
!
"
Cd
D0.338
D0.356*
D0.108
D0.347*
D0.252
Cr
D0.391*
D0.417*
0.042
D0.366*
D0.145
Cu
D0.222
D0.236
D0.028
D0.219
0.062
Fe
D0.333
D0.356*
D0.011
D0.324
D0.234
Pb
D0.037
D0.039
0.021
D0.030
D0.059
Zn
D0.230
D0.240
0.018
D0.212
0.017
%N
D0.313
D0.342*
0.227
D0.254
D0.255
Mean Grain Size
D0.195
D0.218
D0.103
D0.222
D0.376*
.
151
Table 4.9:
The following represents the dominant size classes of foraminiferal specimens in the live assemblages and the dominant sediment
size class. The percentages are of the total found at each of the St Helena Bay stations.
SITE
LIVE
SEDIMENT
SPA
>125 m
64%
>125 m
45%
SPB
>125 m
40%
>125 m
42%
SPC
>125 m
52%
>125 m
40%
SHA
>125 m
38%
>125 m
49%
SHB
>125 m
49%
>500 m
35%
SHC
>63 m
76%
>63 m
50%
SHD
>63 m
61%
>500 m
62%
SHE
>63 m
44%
>500 m
70%
SHF
>125 m
46%
>500 m
50%
SHG
>63 m
52%
>500 m
42%
SHH
>63 m
65%
>500 m
22%
SHI
>125 m
72%
>125 m
50%
152
Table 4.10:
The following represents the dominant size classes of foraminiferal specimens in the live assemblages and the dominant sediment
size class in each of the Robben Island stations. The percentage represents that of the total.
STATION
LIVE Foraminifera
SEDIMENT
RIA
>125 m
56 %
>500 m
44 %
RIB
>125 m
68 %
>500 m
74 %
RIC
>125 m
51 %
>500 m
51 %
RID
>125 m
56 %
>500 m
85 %
RIE
>63 m
46 %
>500 m
50 %
>125 m
54 %
>500 m
72 %
RIG
>125 m
43 %
>500 m
57 %
RIH
>63 m
48 %
>500 m
80 %
153
Table 4.11:
Represents the % tests that displayed abnormalities (chamber regrowth or deformation) and the percentage of broken or abraded
tests for each site. Only live foraminifera were examined. (Appendix – plates of normal, abraded and broken foraminifera).
STUDY AREA
STATION
% abnormalities tests
% broken/ abraded tests
Robben Island
RIA
RIB
0.64
0.98
3
2
RIC
1
3.5
RID
1.8
6
RIE
0.97
4
RIF
1.86
4
RIG
2
6
RIH
0.89
3
SPA
1
10
SPB
3
18
SPC
2
20
SHA
1
25
SHB
1
23
SHC
2
18
SHD
3
16
SHE
4
18
SHF
3
18
SHG
2
15
SHH
1
20
SHI
1
22
St Helena Bay
154
2D Stress: 0.08
SITE
PSH
CSH
PRI
CRI
Figure 4.1:
MDS Ordination of all measured elements in the analysis of foraminiferal tests. Data were square root transformed and Euclidean
distance was used to produce a resemblance matrix. CSH – Control sites St Helena Bay; PSH – Pipeline Sites St Helena Bay. CRI
D Control sites Robben Island; PRI – Pipeline Sites Robben Island.
155
60
0.5
50
0.4
40
Fe in tests (Wt %)
Cd in tests (Wt %)
0.6
0.3
0.2
0.1
30
20
10
0.0
D0.1
D1
0
0
1
2
3
4
5
D10
D2000
6
Cd in Sediments (ug/g)
r = 0.128, p = 0.078
0
2000
4000
6000
8000
10000
12000
Fe in sediments (ug/g)
r = 0.106, p = 0.143
6
0.8
0.7
5
Pb in tests (Wt %)
Cr in tests (Wt %)
0.6
0.5
0.4
0.3
0.2
4
3
2
1
0.1
0
0.0
D0.1
D10
0
r = D0.1304, p = 0.0728
10
20
30
40
D1
D10
50
Cr in sediments (ug/g)
0
10
20
30
40
50
60
70
Pb in sediments (ug/g)
r = 0.002, p = 0.981
5
7
6
4
Zn in tests (Wt %)
Cu in tests (Wt %)
5
4
3
2
3
2
1
1
0
0
D1
D200
200
r = 0.0991, p = 0.1738
Figure 4.2:
600
1000
1400
1800
Cu in sediments (ug/g)
D1
D20
0
20
r = D0.008, p = 0.916
40
60
80
100
120
140
160
180
200
Zn in sediments (ug/g)
Results of the NonDparametric, Spearman Rank Order Correlation between the trace metal concentrations in the sediments and the
trace metal concentration in the tests. Spearman RD values are represented. The red symbols represent Robben Island samples
while the green symbols represent St Helena Bay samples
156
Table 4.12:
Results of the NonDparametric, Spearman Rank Order Correlation between the trace metal concentrations in the sediments and the
trace metal concentration in the tests. Spearman RD values are represented, significant at p < 0.05.
SH – St Helena Bay; CSH – Control sites St Helena Bay; PSH – Pipeline Sites St Helena Bay
RI – Robben Islands; CRI D Control sites Robben Island; PRI – Pipeline Sites Robben Island
Trace Metal
SH
CSH
PSH
RI
CRI
PRI
Cd
0.180
0.217
0.216
D0.405*
0.040
D0.040
Cr
D0.133
D0.226
D0.001
D0.455*
0.174
90.48*
Cu
0.070
0.295
D0.110
D0.27
D0.290
0.040
Fe
0.178
0.021
0.130
0.050
0.040
0.080
Pb
D0.070
0.362
D0.110
D0.234
D0.110
D0.120
Zn
0.080
0.241
D0.130
90.56*
0.140
D0.190
157
Chapter 5
General Conclusions
The aim of the study was to examine foraminiferal assemblages on the west coast of
South Africa and to investigate the environmental factors which may play a role in
determining the structure of these foraminiferal assemblages. The study also attempted to
evaluate their use as bioDindicators of trace metals, percentage nitrogen and sediment size
structure. In order to achieve these aims two study sites, the area around a sewage
pipeline off Robben Island and a fish factory pipeline in St Helena Bay were evaluated.
The mean sediment grain size of both areas was high, as little mud was present. The
St Helena Bay sites had higher concentrations of all trace metals than those of Robben
Island, with some stations showing concentrations higher than ERL and the SA SQG’s,
an indication of their accumulation within the sediments. The percentage nitrogen in
sediment samples from St Helena Bay was also higher than recorded around Robben
Island which could be indicative of an environment with increased eutrophication. One of
the major differences between the two study areas, that may be causing environmental
differences, is the length of time that each of the sites have been exposed to effluent. St
Helena Bay has had a long history of fish factory processing since 1945 (Shannon
.,
1983) while Robben Island has only had a sewage pipeline since 2002 (Prochazka, 2003).
The organic loading in St Helena Bay has thus been added and accumulated over a long
period of time. The hydrodynamics of St Helena Bay are also very different to those
around Robben Island. St Helena Bay is an enclosed embayment which has a long
residence time of water increased by an anticyclonic gyre and very little wind (Walker &
Pitcher, 1991). The area around Robben Island, on the other hand, is subjected to strong
winds of variable direction (Van Ieperen, 1971), which changes the direction of the
plume from the pipeline constantly. Very little settlement would occur in one particular
area, around Robben Island. Wave turbulence and currents around the island cause water
from the pipeline to join the general current out of Table Bay (Ove Arup Consulting
Engineers, 2001).
The measured environmental variables indicated that St Helena Bay may be polluted
and at risk of sediment toxicity. However, because no baseline for trace metal
158
concentrations has been done for the west coast of South Africa, it is not easy to assess
whether the area is enriched above the normal concentrations for the area. Monitoring of
the sediments within this area is essential and a lengthening of the pipeline should be
considered to outside the bay. The companies which rely on the bay as a source of water
for processing are polluting the immediate area with their byproducts. The environmental
variables around Robben Island indicated that the area is not polluted and that there was
no risk of sediment toxicity, however, monitoring of the area should continue as this
study was conducted when the pipeline had only been operating for a short time.
The species richness in both locations was low but consistent with other studies in
shallow, nearshore marine environments (Murray, 2007). Both locations had many of the
same species, which is to be expected as they are both within the cold temperate waters
of the Benguela province. The species diversity curves reached asymptote and the
estimated richness using various diversity indices were close to those observed, meaning
that sampling effort was sufficient to capture all species which would be present. The low
species richness was also indicative of a homogenous environment (on a mesoscale)
which often displays low diversity as a result of the dominance of more colonizing
species (Hewitt
., 2008; Airoldi
., 2008). Robben Island also showed higher
diversity and species richness than St Helena Bay but a lower abundance of foraminifera.
Low diversity and richness is indicative of pollution while the abundance of organisms
will vary according to the tolerance of certain species, that is, the richness was low but
the dominant species was abundant. The diversity indices of both sites therefore signaled
much the same as the environmental factors, that is that St Helena Bay is an area of
increased chemical contamination while Robben Island is not.
On examination of foraminiferal assemblages on a species versus genus level, it was
found that using genera as proxies for environmental studies was sufficient and yielded
much the same results and reacted in the same way as when using individual species.
Using foraminiferal genera would thus decrease the time required for evaluation of an
environment. The genus
which was dominant in St Helena Bay samples was
not present in large abundance in Robben Island samples.
was dominant in
both locations. Both these genera are regarded as opportunistic and can occupy a wide
range of environmental conditions (Nagy & Alve, 1987; Yanko
. 1994; Samir
.,
159
2000; Scott
2001). The bolivinids were found in large abundance in St Helena Bay
samples and were rare in those from around Robben Island, this taxa is often associated
with a polluted environment (Bernhard, 1986; Frontalini
., 2009). Robben Island had
a large abundance of miliolids which were absent in St Helena Bay, this taxon is known
for its sensitivity to pollutants and its absence in an assemblage could be a warning of an
environment that is polluted (Ferraro
&
'
., 2006).
and
were identified as good indicators of environmental conditions.
Although some errors may occur in distinguishing live from dead foraminifera, the
error appears small as differences between the two assemblages were evident. The live
assemblages showed differences between the Robben Island and St Helena Bay study
sites, and some separation between the control and pipeline sites. The dead assemblages,
on the other hand showed no structure and samples from both study areas grouped
together in no particular pattern. This shows that the dead assemblages were not
subjected to the same processes as the live assemblages. There was also an absence of
exotic species or species different from live assemblages in the dead assemblages, an
indication that both areas were not a depositional environment (Alve & Murray, 1997).
The number of test deformities in both sites was not high, this could indicate that the
areas are not polluted, as in previous studies test deformities were displayed in areas with
high trace metal concentrations (Yanko
., 1994). It could also be that the foraminifera
have developed a tolerance to the levels of pollutants and as such do not display
morphological abnormalities. The trace metal content of the shells did not correlate with
the trace metals concentrations of the sediments and may be the reason for the low
percentage of test abnormalities.
The response to the percentage nitrogen by foraminiferal abundance, diversity and
richness was negative in both locations, although previous studies of foraminifera predict
an increase in abundance when nitrogen is high due to an increase in phytodetritus (Scott
., 2001). The percentage nitrogen can be linked to the percentage of organic carbon
present; foraminifera display a variable response to organic carbon levels, if the amount
is too high or too low, the abundance of foraminifera is low but there appears to be a
level at which they can take advantage of the organic carbon and increase in numbers
(Scott
., 2001).
160
Dale & Beyeler (2001) provided a comprehensive checklist for evaluating the use of
ecological indicators in monitoring and providing early warning signals, the choice of
indicators needs to be carefully considered. As such this study will be evaluated against
this checklist, which appears in italics in subsequent paragraphs.
%
-
Although only the top 5 cm of sediments
were used in this study, the abundance of foraminifera in these samples was high enough
for statistical analysis. Six replicates were used for each core, making the study timeD
consuming. However, the six replicates were used because of the amount of variation
normally found in foraminiferal communities where cores from the same station could
have completely different community structures. The shape of a rarefraction curve
depends on the relative abundance of sampled species and the fitted model provides a
prediction of the increase in richness with additional sampling effort; the fact that the
plotted graph reached asymptote is indicative that sampling effort was sufficient (Colwell
& Coddington, 1994).
Foraminifera are microscopic and identification is often difficult (except when a
scanning electron microscope is used), mistakes can easily be made in determining
community structure. However, a simple abundance and presence/ absence study seems
enough to determine ecological conditions as they appear to consistently react to
environmental conditions in terms of their abundance and the presence of certain
indicator taxa. Morphotypes are often considered to be equivalent to species for the
purpose of biodiversity studies (Lambshead
2003). In this study the use of generic
data appears to be as robust as using species data.
%
%
.
-
/
In this study foraminifera consistently showed a negative response to
trace metal concentrations by decreasing in abundance, diversity and richness. This was
consistent with other studies conducted on foraminifera and therefore it appears that this
response does not change irrespective of other ecological parameters like global position,
water temperature or depth (Yanko
Frontalini
., 1994; Scott
., 2001; Ferraro
., 2006;
., 2009). The richness, diversity and abundance displayed a positive
response to organic matter input in both locations while the percentage nitrogen displayed
161
a negative response. The response of both these parameters has been found to be
consistent with other studies.
The genera that could possibly be used as indicators were
&
'
and
as they displayed the strongest relationship with the measured
environmental variables. The presence of an opportunistic species in large abundance can
be indicative of a stressed system but could also be indicative of a healthy system as this
species could proliferate in any conditions.
0
%
-
%
.
-
%-
-
Benthic foraminifera occupy the sediments and any substance present in the
water column settles in the sediments (Fricke & Flemming, 1983). Foraminifera have
been found to react to organic matter input, trace metals and sediment size. The presence
or absence of a high abundance of foraminifera or individual genera and sometimes even
species is a normal response to changes in these environmental conditions. Thus
investigation of the chemistry and physical structure of the sediments as well as the
foraminifera present can provide a management and monitoring tool for ecological
systems.
0
/
%
Numerous studies have been conducted and are
increasing with respect to foraminiferal response to ecological conditions (Yanko
1994; Samir
., 2000; Scott
.,
2001). Although there are still many unanswered
questions regarding the ecology of individual species of foraminifera, the surge in new
studies is providing new useful information which can be used for future monitoring.
0
/
%
-
Although the foraminifera have
been found to display predictable response to environmental conditions, foraminifera
themselves are known for their patchy distribution within their microhabitat. In this
study, high variability was found between cores of the same station. Studies would
therefore, require many replicates in order to make conclusive observations and studying
one core only per station as done by many previous studies is not sufficient. Other studies
conducted also reported high morphological abnormalities in test morphology which was
not observed in this study. The possible use of test morphology as indicative of
162
environmental stress should be used cautiously as morphological abnormalities have been
reported under natural conditions in unpolluted environments.
No relationship could be found between the trace metal content of the sediments and
the concentration found in the shells. There could have been for a number of reasons for
this, organisms normally take up trace metals into their tissues and foraminifera have a
limited amount of protoplasm, foraminifera have the ability to limit the uptake trace
metals into their shells or the type of trace metal complex present in these environments
limits its bioDavailability. Biomonitors, that is, species which accumulate trace metals in
their tissues, which have most successfully been used as monitors belonged to taxa which
are suspension feeders and detritivores (Rainbow & Phillips, 1993). Of these taxa,
+-
)
and $
appear to be the most reliable in reflecting environmental
conditions, many of the organisms like crustaceans (barnacles) and polychaetes appear to
regulate either their intake or the accumulation of trace metals in their tissues and have
been found to have variable responses even between species (Rainbow and Phillips,
1993). It appears that macrofauna because of their larger body size are measurably
affected by trace metals whereas the response of smaller organisms and particularly
meiofauna may experience variable or negligible effects.
Foraminifera can be successfully used as bioDindicators locally as they have displayed
much the same results as have been reported in other studies globally. However, shell
abnormalities and shell trace metal concentrations as indicators should be used cautiously
and would need to be backed up by environmental data and experimental studies. While
this study examined foraminifera on a microD, meso and macroscale (only a few 100 km),
a larger scale study examining the biogeographic provinces around South Africa would
be useful. This study also does not take temporal variability into account; conditions on
the south west coast of South Africa vary greatly between seasons and a very different
assemblage structure could be encountered during different seasons.
The number of marine pollution studies in South Africa has not historically been very
high and could possibly be due to the perception that the marine environment is able to
absorb much of the landDbased pollutants, as a result more impact studies have focused
on freshwater and terrestrial pollution. O’ Donoghue & Marshall (2003) reviewed marine
pollution research in South Africa and found that between 1960 and 2002; fewer than 100
163
pollution studies were conducted on marine pollution, which is fewer than three per year.
This has become a concern for the National Research Foundation (NRF) in South Africa,
which funds scientific research in South Africa; it has reported that only 4 % of research
applied for in their Sea and Coast Programme has been related to marine pollutionD
related projects (NRF & SANCOR, 2010). In 2010, the NRF and SANCOR held a joint
workshop with scientists and other stakeholders interested in marine pollution research.
The main outcomes from this workshop were that there was a lack of specific coordinated
research in South Africa and as such it was recommended that a National Marine
Pollution Forum be established to facilitate research (NRF & SANCOR, 2010). Most
importantly, the results of research and monitoring should be made accessible to the
public. In this study it was particularly difficult to access historical data on the two
locations as these were conducted for private companies, information/ data gathered by
private consultants is not open to public perusal and therefore scientific studies are often
conducted in isolation. ResearchDspecific gaps identified were the economic evaluations
of coastal resources, the identification of novel technologies for assessments (monitoring
devices, predictive modeling, remote sensing and biomarkers) and risk analysis of the
consumption of fish and shellfish and contact recreation as a result of marine pollution
(NRF & SANCOR, 2010)
This study could therefore contribute to these identified gaps and assist in increasing
our understanding of how environmental factors react in different environments, in this
particular case, in upwelled, cold temperate waters and the effects these environmental
factors have on specific taxa. Studies must however have both a biological and a
physical/ environmental component as it is very difficult to make comprehensive
conclusions from only one aspect. A study such as this one should also be repeated in the
same area to provide information on temporal variability and in other ‘normal’ areas
around the west coast to obtain baseline information.
164
References
Abel, P. D. 1996. 1
)
- Taylor and Francis, U. K. 286 pp.
Airoldi, L., Balata, D. and Beck, M. W. 2008. The Gray Zone: Relationships between
.
habitat loss and marine diversity and their applications in conservation.
,
+
-
-. 366: 8 – 15.
Albani, A. D. 1965. The foraminifera in a sample dredged from the vicinity of Salisbury
Island, Durban Bay, South Africa. $
.
.
%
.
$
16 (2): 60 – 67.
.
Albani, A. D., Hayward, B. W., Grenfell, H. R. and Lombardo, R. 2001.
.
#
1
)
.
Australian Biological resources Study. CDDROMD
ISBN 0 7334 1835 X.
Almeida, M. J., Moura, G., Pinheiro, T., Machado, J. and Coimbra, J. 1998.
Modifications in $
shell composition exposed to high
concentrations of lead. '
,
- 40: 323 – 334.
Alve, E. 1991. Benthc foraminifera in sediment cores reflecting heavyDmetal pollution in
.
Sorfjord, Western Norway.
.
21 (1): 1 D 19.
Alve, E. 2003. A common opportunistic foraminiferal species as an indicator of rapidly
$
changing conditions in a range of environments.
#
#
.
57: 501 – 514.
Alve, E. and Olsgard, F. 1999. Benthic foraminiferal colonization in experiments with
.
copperDcontaminated sediments.
.
29: 186 –
195.
Alve, E. & Murray, J. W. 1997. High benthic fertility and taphonomy of foraminifera: a
case study of the Skaggerak, North Sea. +
+
-. 31: 157 –
175.
Andersen, A. N. 1995. Measuring more of biodiversity: genus richness as a surrogate for
$
species richness in Australian ant faunas.
73: 39D43
Atkinson, K. 1969. The association of living foraminifera with algae from the littoral
zone, South Cradigan Bay, Wales.
.2
- 3: 517 – 542.
Bailey, G. W. 1983. Pilot study of the vertical flux of P. O. C. and P. O. N. in St Helena
Bay. #
.
.#
79: 145 – 146.
165
Bailey, G. W. 1987. The role of nutrient regeneration from the sediments in the supply of
nutrients to the euphotic zone in the southern Benguela system. In:
$
%
(eds). #
-
Payne. A. I. L., Gulland, J. A. and Brink, K. H.
.
.+
#
5: 3 D 9.
Bailey, G. W. and Chapman, P. 1985.The nutrient status of the St Helena Bay region in
February 1979. In: Shannon, L. V. (ed.). #
3 /
,
.
!
$
Sea Fisheries Research Institute. 125 – 145.
Bailey, G. W. and Rogers, J. 1997. Chemical oceanography and marine geoscience off
southern Africa. Past discoveries in the postDGilchrist era and future prospects.
.
-
#
- .#
.
52(1): 51 – 79.
Balmford, A., Jayasuriya, A. H. M. & Green, M. J. B. 1996. Use of higherDtaxon richness
as a surrogate for species richness: II. Local applications. )
#
- ."
.
-
. 263: 1571 – 1575.
Bé, A. W. H., Vilks, G. and Lott., L. 1971. Winter distribution of planktonic foraminifera
between the Grand banks and the Caribbean. +
- 17 (1): 31 – 42.
Bergin, F., Kucuksezgin, F., Uluturhan, E., Barut., I. F., Meric., E., Avsar, N. and Nazik,
A. 2006. The response of benthic foraminifera and ostracoda t heavy metal
pollution in Gulf of Izmir (Eastern Aegean Sea).
#
$
#
.
66: 368 D 386.
Berkeley, A., Perry, C. T., Smithers, S. G. and Horton, B. P. 2008. The spatial and
vertical distribution of living (stained) benthic foraminifera from a tropical,
intertidal environment, north Queensland, Australia. +
+
-.
69: 240 – 261.
Bernhard, J. M. 1986. Characteristic assemblages and morphologies of benthic
foraminifera from anoxic, organicDrich deposits: Jurassic through Holocene.
.
.
16 (3): 207 – 215.
Bernhard, J. M. and Bowser, S. S. 1999. Benthic foraminifera of dysoxic sediments:
chloroplast sequestration and functional morphology.
*#
/ 46:
149 – 165.
166
Bernhard, J. M., Buck, K. R. and Barry, J. P. 2001. Monterey Bay coldDseep biota:
Assemblages, abundance, and ultrastructure of living foraminifera. DeepDSea
Research I. 48: 2233 – 2249.
Bernhard, J. M., Sen Gupta, B. K. and Baguley, J. G. 2008. Benthic foraminifera living in
the Gulf of Mexicobathyal and abyssal sediments: community analysis and
*#
comparison to metazoan meiofaunal biomass and density.
00
55: 2617 – 2626.
Biesiot, P. G. 1957. Miocene foraminifera from the Uloa Sandstone, Zululand.
)
.
(
#
- .#
.
60: 61 –
80.
Bjørgesæter, A. and Gray, S. 2008. Setting sediment quality guidelines: A simple yet
effective method. +
)
57: 221 – 235.
.
Boltovskoy, E. and Wright, R. 1976.
The Hague: Dr. W. Junk.
.
Branch, G. M. and Branch, M. 1995.
.
. Struik
Publishers. Cape Town.
Branch, G. M., Barkai, A., Hockey, P. A. R. and Hutchings, L. 1987. Biological
Interactions: causes or effects of variability in the Benguela Ecosystem? In:
$
%
K. H. (eds). #
-
.
Payne. A. I. L., Gulland, J. A. and Brink,
.+
#
5: 425 – 445.
Bremner, J., Rogers, S. I. and Frid, C. L. J. 2006. Matching biological traits to
environmental conditions in marine benthic ecosystems.
#-
.+
60 (3 – 4): 302 – 316.
Brink, K. H. 1987. Upwelling fronts: implications and unknowns. In:
$
#
%
.
-
Payne. A. I. L., Gulland, J. A. and Brink, K. H. (eds)
.+
#
5: 3 D 9.
Bryan, G. W. and Langston, W. J. 1992. Bioavailability, accumulation and effects of
heavy metals in sediments with special reference to United Kingdom estuaries: a
review.
)
. 89 – 131.
Burd, B. J, Barnes, P. A. G., Wright, C. A. and Thomson, R. E. 2008. A review of
subtidal benthic habitats and invertebrate biota of the Strait of Georgia, British
Columbia. +
66 (1): S3 – S38.
167
Burone, L., Venturini, N., Sprechmann, P., Valente, P. and Muniz, P. 2006. Foraminiferal
responses to polluted sediments in the Montevideo coastal zone, Uruguay.
+
)
52: 61 – 73.
Butler, B. J. and Chazdon, R. L. 1998. Species richness, spatial variation, and abundance
30 (2): 214 –
of the soil seed bank of a secondary tropical rain forest.
222.
Buys, M. E. L. 1957. The South African Pilchard (#
. Temperature
variations in the upper 50 metres in the St Helena Bay area, September 1950 –
August 1954. 0
.
.
.#
.#
27: 114 pp.
Buzas, M. A and Culver, S. J. 1991. Species diversity and dispersal of benthic
foraminifera: Analysis of extant organisms and fossils of the waters around North
41 (7): 483 – 489.
America.
Buzas, M. A., Hayek, L. C. and Culver, S. J. 2007. Community structure of benthic
foraminifera in the Gulf of Mexico. +
+
-. 65: 43 – 53.
Cardoso, P., Silva, I., de Oliveira, N. G., Serrano, A. R. M. Higher taxa surrogates of
spider (Araneae) diversity and their efficiency in conservation.
$
117: 453–459.
Castro, P. and Huber, M. E. 2008. +
- Seventh Edition. McGrawDHill
International. New York.
Chapman, F. 1904. Foraminifera and ostracoda from the Cretaceous of East Pondoland,
South Africa.
.
#
.
+
4 (5): 221 – 237.
Chapman, F. 1907. Report on Pleistocene microzoa from a boring in the bed of the
Buffalo River, East London.
%
-+
2 (1): 6 – 17.
Chapman, F. 1916. Foraminifera and Ostracoda from the Upper Cretaceous of Needs
.
Camp, Buffalo River, Cape Province.
#
.
+
12
(4): 107 – 118.
Chapman, F. 1923. On some foraminifera and ostracoda from the Cretaceous of Uzamba
River, Pondoland.
.
(
#
- .#
.
26: 1–
6.
168
Chapman, F. 1924. A first report of foraminifera collected by the S. African Government
Fisheries and Marine Biological Survey. 3
+
#
.#
.
- Report 3, Special Report XI (for 1922): 1–19.
Chapman, F. 1930. On a foraminiferal limestone of the Upper Eocene Age from the
.
Alexandria formation, South Africa.
#
.
+
28 (2):
291 – 296.
Cherchi, A., Da Pelo, S. Ibba, A., Mana, D., Buosi, C. and Floris, N. 2009. Benthic
foraminifera response and geochemical characterization of the coastal
environment surrounding the polluted industrial area of Portovesme (South –
Western Sardinia, Italy). +
)
59: 281 – 296.
Cifelli, R. 1982. Textural observations on some living species of planktonic foraminifera.
#
$
%
)
%
-. 45: 1 – 16.
Cifelli, R. and Smith, R. K. 1970. Distribution of planktonic foraminifera in the vicinity
of the North Atlantic Current. #
$
%
)
%
-. 4: 1 –
51.
Clark, R. B. 1993. +
)
Oxford University Press. New York. 168 pp.
Clarke, K. R. and Gorley, R. N. 2006. )
4. Roborough, Plymouth, UK: Plymouth
Marine Laboratory. www.primerDe.com.
Clarke, K. R. and Warwick, R. M. 2001. $
-
5
. PRIMERDE. Plymouth, UK.
Cloern, J. E. 2001. Our evolving conceptual model of the coastal eutrophication problem.
+
-)
#
210: 223 – 253.
Clowes, A. J. 1954. The South African Pilchard (#
. The temperature,
salinity and inorganic phosphate content of the surface layer near St Helena Bay,
1950 –1952. 0
.
.
.#
.#
16: 47 pp.
Colwell, R. K. and Coddington, J. A. 1994. Estimating terrestrial biodiversity through
extrapolation. )
#
"
345: 101 – 118.
Colwell, R. K. 2009. EstimateS 8.2. www.viceroy.eeb.uconn.edu/estimates
169
Culver, S. J. and Buzas, M. A. 1995. The effects of anthropogenic habitat disturbance,
habitat destruction, and global warming on shallow marine benthic foraminifera.
.
.
25 (3): 204 – 211.
Culver, S. J. and Buzas, M. A. 2000. Global latitudinal species diversity gradient in deepD
*#
sea benthic foraminifera.
.
Cushman, J. A. 1959.
0 47: 259 D 275
5
.
Harvard
University Press, Cambridge.
Dale, V. H. & Beyeler, S. C. 2001. Challenges in the development and use of ecological
0
indicators.
. 1: 3 – 10.
Dale, D. C. & McMillan, I. K. 1998. Mud belt and middle shelf benthonic and planktonic
foraminiferal assemblages and sedimentation processes compared through the
Holocene successions at two tropical African (Sierra Leone) and two temperate
African (western offshore, South Africa) sites. #
.
.#
94: 319 – 340.
den Dulk, M., Reichart, G. J., van Heyst, S., Zachariasse, W. J. and Van der Zwaan, G. J.
2000. Benthic foraminifera as proxies of organic matter flux and bottom water
oxygenation? A case history from northen Arabian Sea. )
)
- )
-
- 161: 337 – 359.
Debenay, J.DP., Tsakiridis, E., Soulard, R. and Grossel, H., 2001. Factors determining the
distribution of foraminiferal assemblages in Port Joinville Harbor (Ile d'Yeu,
France): the influence of pollution. +
+
- 43: 75 D 118.
Diz, P., Francés, G. and Rosōn, G. 2006. Effects of contrasting upwellingDdownwelling
.
on benthic foraminifera distribution in the Ría de Vigo (NW Spain).
+
#-
60: 1 D18.
du Châtelet, É. A. , BoutDRoumazeilles, V., Riboulleau, A. and Trentesaux, A. 2009.
Sediment (grain size and mineralogy) and organic matter quality control on living
benthic foraminifera.
+
6
52: 75 – 84.
du Châtelet, É. A., Debenay, JDP. and Soulard, R. 2004. Foraminiferal proxies for
pollution monitoring in moderately polluted harbours.
)
127: 27 – 40.
170
Duleba, W. and Debenay, JDP. 2003. Hydrodynamic circulation in the estuaries of the
Estação Ecológica JuréiaDItatins, Brazil, inferred from foraminifera and
.
thecamoebian assemblages.
.
33 (1): 62 – 93.
Elberling, B., Knudsen, K. L., Kristensen, P. H. and Asmund, G. 2003. Applying
foraminiferal stratigraphy as a biomarker for heavy metal comtamination and
mining impact in a fiord in West Greenland. +
55:
235 – 256.
FernandezDLeborans, G. and Herrero, Y. O. 2000. Toxicity and Bioaccumulation of Lead
,
and Cadmium in Marine Protozoan Communities.
-
# . - 47 (3): 266D276.
Ferraro, L., Sprovieri, M., Alberico., I, Lirer, F., Prevedello, L and Marsella, E. 2006.
Benthic foraminifera and heavy metals distribution: A case study from the Naples
)
Harbour (Tyrrhenian Sea, Southern Italy).
142 (2):274D
87.
Fleeger, J. W., Thistle, D. and Thiel, H. 1988. Sampling equipment. In: Higgins RP,
Thiel, H. (eds) 0
- .
.
. Smithsonian Institution
Press, London. 115–125
Flint, R. W. and Holland, J. S. 1980. Benthic infaunal variability on a transect in the Gulf
$
of Mexico.
+
#
. 10: 1 – 14.
Fricke, A. H. and Flemming, B. W. 1983. Selective microhabitat colonization by
interstitial meiofauna as a function of grain size. In: #
-%
-
McLachlan, A. and Erasmus, T. (eds). Junk. The Hague. 421 – 431.
Frontalini, F. and Coccioni, R. 2008. Benthic foraminifera for heavy metal pollution
monitoring: A case study from the central Adriatic Sea coast of Italy.
$
#
.#
76 (2): 404 – 417.
Frontalini, F., Buosi, C., Da Pelo, S., Coccioni, R. Cherchi, A. and Bucci, C. 2009.
Benthic foraminifera as bioDindicators of trace metal pollution in the heavily
contaminated Santa Gilla lagoon (Cagliari, Italy). +
)
58
(6): 858 – 877.
Gao, X., Chen, S. and Long, A. 2008. Composition and sources of organic matter and its
solvent extractable components in surface sediments of a bay under serious
171
anthropogenic influences: Daya Bay, China. +
)
. 56 (6):
1066 – 1075.
Gee, J. M., Warwick, R. M., Schaaning, M., Berge, J. A. and Ambrose, W. G. 1985.
Effects of organic enrichment on meiofaunal abundance and community structure
. ,
in sublittoral soft sediments.
+
-
- 91: 247 – 262.
Geslin, E., Debenay, JDP.,Duleba, W. and Bonetti, C. 2002. Morphological abnormalities
of foraminiferla tests in Brazilian environments: comparison between polluted
and nonDpolluted areas. +
+
- 45: 151 – 168.
Gobin, J. F. and Warwick, R. M. 2006. Geographical variation in species diversity: A
. ,
comparison of marine polychaets and nematodes.
-
+
- 330: 234 – 244.
Gooday, A. J. and Lambshead, P. J. D. 1989. Influence of seasonally deposited
phytodetritus on benthic foraminiferal populations in the bathyal northeast
Atlantic: the species response. +
-)
#
Gooday, A. J. 1992. Sarcomastigophora. 0
58: 53 – 67.
- .
.
Higgins
R. P and Jalmar, T. H. (eds). Smithsonian Institution Press. Washington D. C.,
London. 243D 257.
Gray, J. S. 2000. The measurement of marine species diversity, with an application to
. ,
benthic fauna of the Norwegian continental shelf.
+
-
-. 250: 23 – 49.
Grelle, C. E. V. 2002. Is higherDtaxon analysis an useful surrogate of species richness in
$
studies of Neotropical mammal diversity?
. 108: 101–
106.
Griffiths, C. L and 17 authors. 2004. Impacts of human activities on marine animal life in
the Benguela: an historical overview. !
-
+
-5
/ 42: 303 – 392.
Guastella, L. ADM. 1992. Sea surface heat exchange at St Helena Bay and implications
for the southern Benguela upwelling system. In: Payne, A. I. L., Brink, K. H.,
Mann, K. H. and Hillborn, R. (eds).
.+
#
#
.
12: 61 – 70.
172
Guichard, F. and Steenweg, R. 2008. Intrinsic and extrinsic causes of spatial variability
.
across scales in a metacommunity.
- 250: 113 D124.
Gustafsson, M., Dahllöf, I., Blanck, H., Hall, P., Molander, S and Nordberg, K. 2000.
Benthic foraminiferal tolerance to TriD *Butylin (TBT) in an experimental
mesocosm. +
)
40 (12): 1072 – 1075.
Gustafsson, M. and Nordberg, K. 2000. Living (stained) benthic foraminifera and their
response to the seasonal hydrographic cycle, periodic hypoxia and to primary
$
production in Havstens Fjord on the Swedish west coast.
#
.#
51: 743 D 761.
Halfar, J. and Ingle, J. C. 2003. Modern warmDtemperate and subtropical shallowDwater
.
benthic foraminifera of the southern Gulf of California, Mexico.
.
33 (4): 309 – 329.
Harrad, S., Batty, L., Arhonditsis, G. and Diamond, M. 2008. #
#
) 7
John Wiley and Sons Ltd. England. pp 161.
Hart, T. J. and Currie, R. I. 1960. The Benguela Current.
-
31: 127 –
289.
Hendricks, M. J. G. (unpublished) Nematodes of Saldanha Bay. Cape Town. University
of the Western Cape. (Ph. D Thesis).
Henry, J. L., McGibbon, S., Davis, G. Mackay, R. M. and Moldan, A. G. S. 1989. Heavy
metals, carbon and hydrocarbons in the sediments of Table Bay harbour. #
0
#
8. Department of Environmental
Affairs, Republic of South Africa.
Herut, B & Sandler, A. 2006. Normalization methods for pollutants in marine sediments:
review and recommendations for the Mediterranean. IOLR Report H18/2006.
UNEP/MAP.
Heuttel, M., Ziebis, W., Forster, S. and Luther III, G. W. 1998. Advective transport
affecting metal and nutrient distributions and interfacial fluxes in permeable
sediments. (
$
. 62 (4): 613 – 631.
Hewitt, J. E., Thrush, S. F. and Dayton, P. D. 2008. Habitat variation, species diversity
and ecological functioning in a marine system.
-
. ,
+
-. 366: 116–122.
173
Hillebrand, H. 2004. Strength, slope and variability of marine latitudinal gradients.
+
-)
#
. 273: 251 – 267.
Howarth, R. W. and Marino, R. 2006. Nitrogen as the limiting nutrient for eutrophication
in coastal marine ecosystems: Evolving views over three decades. "
!
-
- 51 (1 part 2): 364 – 376.
Islam, M. S. and Tanaka, M. 2004. Impacts of of pollution on coastal and marine
ecosystems including coastal and marine fisheries and approach for management:
a review and synthesis. +
)
. 48: 624 – 649.
Jahnke, R., Richards, M., Nelson, J., Roberston, C., Rao, A. and Jahnke, D. 2005.
Organic matter remineralization and porewater exchange rates in permeable South
Atlantic Bight continental shelf sediments. $
#
.
. 25: 1433
– 1452.
Jury, M. R. and Bain, C. A. R. 1989. Observations of the oceanic environment and warmD
water outfall near the Koeberg Nuclear Power Station, South Africa. #
.
.+
#
8: 67 – 89.
Kähler, P. and Koeve, W. 2001. Marine dissolved organic matter: can C:N ratio explain
carbon overconsumption?
*#
0. 48: 49 D 62.
Lambert, G. and Scheibnerová, V. 1974. Albian foraminifer of Zululand (South Africa)
and Great Artesian Basin (Australia). +
- 20(1): 76 – 96.
Lambshead, P. J. D., Brown, C. J., Ferrero, T. J. Hawkins, L. E., Smith, C. R. and
Mitchell, N. J. 2003. Biodiversity of nematode assemblages from the region of
the ClarionDClipperton Fracture Zone, an area of commercial mining interest.
+$
- 3 (1).
Lavigne, C., Juniper, S. K. and Silverberg, N. 1997. SaptioDtemporal variability in
benthic microbial activity and particle flux in the Laurentian Trough.
*#
. 44: 1793 – 1813.
0
+
Livingston, R. J. 2001.
)
Libes, S. M. 1992.
- John Wiley and Sons,
U. S.A. 734pp
#
$
.)
$
..
##
!
-)
( .
CRC Press, Florida U. S. A. 327 pp.
174
.
Loeblich, A. R. and Tappan, H. 1987.
.
. Van
Rostrand Reinhold Company, New York.
Martin, R. A. 1974. Benthonic foraminifera from the western coast of southern Africa.
(
#
-#
.
9 3$ +
(
3
6 (14): 83 D 87.
Marsden, I. D. and Rainbow, P. S. 2004. Does accumulation of trace metals in
.
crustaceans affect their ecology – the amphipod example?
,
+
-
-. 300: 373 – 408.
Mazaris, A. D., Kallimanis, A. S. and Sgardelis, S. P. 2008. Does higher taxon diversity
reflect richness of conservation interest species? The case for birds, mammals,
0
amphibians, and reptiles in Greek protected areas.
. 8: 664 –
671.
Brünnich, 1771 (Foraminiferida) and its
McMillan, I. K. 1987.The genus
potential for elucidating the latest Cainozoic stratigraphy of South Africa. #
.
.#
83: 32 – 42.
McMillan, I. K. 1990. Foraminifera from the late Pleistocene (Latest Eemian to Earliest
.
Wechselian) shelly sands of Cape Town city centre, South Africa.
#
.
+
99 (5): 121 – 186.
McMillan, I. K. 1993.Foraminiferal biostratigraphy, sequence stratigraphy and
interpreted chronostratigraphy of marine Quaternary sedimentation on the South
African continental shelf. #
.
.#
89: 83 – 89.
Moldan, A. 1983. Effects of fish factory effluents on the benthic macrofauna in St Helena
Bay. #
.
.#
79: 163.
Mojtahid, M., Jorissen, F. Lansard, B., Fontanier, C. Bombled, B and Rabouille, C. 2009.
Spatial distribution of live benthic foraminifera in the Rhône prodelta: Faunal
response to a continentalDmarine organic matter gradient. +
+
- 70: 177 – 200.
Monteiro, P. M. S. 1997. Tabe Bay Sediment Study: Phase III. $#0
2:9#*$
;<=>? 62 pp.
Monteiro, P. M. S., Pascall, A. and Brown, S. 1999. The Biogeochemical Status of
Surface Sediments in Saldanha Bay in 1999. $#0
2:*#*$ ;;=;@
175
Monteiro, P. M. S. and Roychoudhury, A. N. 2005. Spatial characteristics of sediment
trace metals in an eastern boundary upwelling retention area (St. Helena Bay,
$
South Africa): A hydrodynamicDbiological pump hypothesis.
#
.#
65: 123 – 134.
Monteiro, P. M. S. and Scott, D. L. 2001. Sediment Assessment Programme for the Port
of Cape Town. $#0
2:* #* $A==B*=<;. 22 pp
Moodley, L., van der Zwaan,G. J., Rutten, G. M. W., Boom R. C. E. and Kempers, A. J.
1998.Subsurface activity of benthic foraminifera in relation to porewater oxygen
content: laboratory experiments. +
+
- 34 (192): 91D106.
Morard, R., Quillévéré, F., Gilles Escarguel, G., Ujiie. Y., de GaridelDThoron, T., Richard
D. Norris, R. D. and de Vargas C. 2009. Morphological recognition of cryptic
species in the planktonic foraminifer ! %
+
.+
- 71 (3): 148 D 165.
Morton, S. and Roberts, D. J. 1999. 320$ +
#
. UNICAM Ltd. UK.
2 (05/93)
Morvan, J., Debenay, JDP., Jorissen F., Redois, F., Beneteau, E., Delplancke, M. and
Amato, ADS. 2006. Patchiness and life cycle of intertidal foraminifera:
Implication for environmental and paleoenvironmental interpretation. +
+
- 61 (193): 131 – 154.
Mucha, A. P., Vasconcelos, M. T. S. D. and Bordalo, A. A. 2003. Macrobenthic
community in Douro estuary: relations with trace metals and natural sediment
)
characteristics.
-
Murray, J. W. 1991.
121: 169 – 180.
)
- .%
.
.
Longman
Group UK Limited, England. 397 pp.
Murray, J. W. 2001. The niche of benthic foraminifera, critical thresholds and proxies.
+
+
- 41: 1 – 7.
Murray, J. W. 2007. Biodiversity of living benthic foraminifera: How many species are
there? +
+
-
Murray, J. W. & Alve, E. 1999. Natural dissolution of modern shallow water benthic
foraminifera: taphonomic effects on the palaeoecological record.
)
- )
- )
-. 146: 195 – 209.
176
Murray, J. M. H., Meadows A. and Meadows, P. S. 2002. Biogeomorphological
implications of microscale interactions between sediment geotechnics and marine
benthos: a review. (
- 47 (1): 15 – 30.
Murray, J. W. & Pudsey, C. J. 2004. Living (stained) and dead foraminifera from the
newly iceDfree Larsen Ice Shelf, Weddell Sea, Antarctica: ecology and
taphonomy. +
+
-. 53: 67 – 81.
Nagy, J. and Alve, E., 1987. Temporal changes in foraminiferal faunas and impact of
pollution in Sandebukta, Oslo Fjord. +
+
. 12: 109D128.
National State of the Environment Report, South Africa. 2008. www.soer.deat.gov.za
National Research Foundation. 2010. Report on the Marine and coastal pollution research
workshop. 23 pp.
Nelson, G. and Hutchings, L. 1983. The Benguela Upwelling area. )
!
- 12: 333 – 356.
Newman, G. G. and Pollock, D. E. 1973. Organic pollution of the marine environment by
pelagic fish factories in the western Cape. #
.
.#
69:
27 – 29.
Newman, B. K. & Watling, R. J. 2007. Definition of baseline metal concentrations for
assessing metal enrichment of sediment from the southDeastern Cape coastline of
South Africa. 1
# . 33: 675 – 691.
O’ Donoghue, S. H. and Marshall, D. J. 2003. Marine pollution research in South Africa:
a status report. #
.
.#
$
O’Neill, P. 1993.
. 99: 349 – 356.
- Chapmann and Hall, London. 268pp.
Ove Arup Consulting Engineers. 2001. Dye and plume dispersion study of the Robben
Island marine sewer outfall. Draft Report No. 1.
Parr, W. J. 1958. The foraminifera of the Bluff Beds, Durban and some other South
African calcareous coastal rocks.
#
- .#
.
)
.
(
61: 103 – 109.
Perdue, E. M. and Koprivnjak, JDF. 2007. Using the C/N ratio to estimate terrigenous
inputs of organic matter to aquatic environments.
#
$
#
.
73: 65 – 72.
177
-
Phleger, F. B. 1973.
%
.
.
The Jon Hopkins
Press, Baltimore.
Pielou, E. C. 1979. Precedence Analysis: The identification and use of benthic
foraminiferal groups as environmental indicators.
.
.
9 (1): 14 – 28.
Powell, R. T., Landing, W. M. and Bauer, J. E. 1996. Colloidal trace metals, organic
carbon and nitrogen in a southeastern US estuary. +
$
-. 165 – 176.
Prinzing, A., Klotz, S., Stadler, J. & Brandl, R. 2003. Woody plants in Kenya: expanding
$
the HigherDTaxon Approach.
110: 307–314.
Prochazka, K. 2001. Marine Biological monitoring of the Robben Island marine sewage
outfall. Baseline Report. IOI – SA. 17 pp.
Prochazka, K. 2003. Marine Biological monitoring of the Robben Island marine sewage
outfall. Final Report. IOI – SA. 21 pp.
Quijón, P. A., Kelly, M. C. and Snelgrove, P. V. R. 2008. The role of sinking
phytodetritus in structuring shallowDwater benthic communities.
,
+
-
.
-. 366: 134 – 145.
Rainbow, P. S. and Phillips, D. J. H. 1993. Cosmopolitan biomonitors of trace metals.
+
)
. 26: 593 – 601.
Rathburn, A. E., Levin, L. A., Held, Z. and Lohmann, K. C. 2000. Benthic foraminifera
associated with cold methane seeps on the northern Californian margin: Ecology
and stable isotopic composition. +
+
- 38: 247 – 266.
Republic of South Africa, Department of Water Affairs and Forestry, 2004. Water
Quality management Series, SubDseries No. MS 13.4. Operational policy for the
disposal of landDderived water containing waste to the marine environment of
South Africa: Appendices. Edition 1. Pretoria.
Resig, J. M. 1960. Foraminiferal ecology around ocean outfalls off southern California.
1
+
Pergamon Press, London 104 – 121.
Romano, E., Bergamin, L., Finoia, M. G., Carboni, M. G., Ausili, A. and Gabellini, M.
2008. +
)
. 56(3): 439 – 457.
Ruiz, F., GonzálezDRegalado, M. L., Borrego, J., Abad, M. and Pendón, J. G. 2004.
Ostracoda and foraminifera as shortDterm tracers of environmental changes in
178
)
very polluted areas: the Odiel Estuary (SW Spain).
. 129:
49 – 61.
Sajan, S., Joydas, T.V. and Damoradan, R. Meiofauna of the western continental shelf of
$
India, Arabian Sea.
#
.#
86 (4): 665 – 674.
Salmon, D. A. 1979a. Quaternary foraminifers in piston cores from the S. W. Indian
(
Ocean.
#
-#
.
9 3$ +
(
3
11 (8): 72 – 79.
Salmon, D. A. 1979b. Quaternary foraminifers in piston cores from the S. W. Indian
(
Ocean.
#
-#
.
9 3$ +
(
3
11 (9): 80 D 88.
Salmon, D. A. 1980. Tertiary planktic foraminiferida and biostratigraphy of cores from
three deep sea areas in the SW Indian Ocean.
.
9 3$ +
(
(
3
#
-#
12 (1): 1 D17.
Samaai, T., Gibbons, M. J., Kerwath, S., Yemane, D. & Sink, K. 2010. Sponge richness
along a bathymetric gradient within the iSimangaliso Wetland Park, South Africa.
Marine Biodiversity. 40: 205 – 217.
Samir, A. M. and ElDDin, A. B. 2001. Benthic foraminiferal assemblages and
morphological abnormalities as pollution proxies in two Egyptian bays. +
+
- 41: 193 – 227.
Schafer, C. T., winters, G.V. Scott, D. B. Pocklington, P., Cole, F. E. and Honig, C. 1995.
Survey of living foraminifera and polychaete populations at some Canadian
.
aquaculture sites: potential for impact mapping and monitoring.
.
25: 236 – 259.
Scott, D. B., Medioli, F. S. and Schafer, C. T. 2001. +
.
%
0
$
Cambridge University Press,
U. K. 177 pp.
Shannon, L. V. 1986. Some distinguishing features of the Benguela system. $
.
0$#
.
13 (11): 225 – 228.
Shannon, L. V., Walters, N. M. and Moldan, A. G. S. 1983. Some features in two Cape
bays as deduced from satellite ocean colour. #
#
.
.+
1: 111 – 122.
179
Shannon, L. V. and Pillar, S. C. 1986. The Benguela Ecosystem. Part III. Plankton.
!
-
+
/ 24: 65 – 170.
Smith, V. H., Joye, S. B. and Howarth, R. W. 2006. Eutrophication of freshwater and
marine ecosystems. "
-
!
- 51 (1 part 2): 351 – 355.
StatSoft, Inc. 2010. Electronic Statistics Textbook. Tulsa, OK: StatSoft. WEB:
http://www.statsoft.com/textbook/. (Electronic version).
Stouff, V. Debenay, JDP. and Lesourd, M. 1999. Origin of double and multiple tests in
benthic foraminifera: observations in laboratory cultures. +
+
- 36: 189 D 204.
Taljaard, S., Botes W. A. M., Oelofse, S. H. H. and Viljoen, P. Operational policy for
disposal of landDderived wastewater to the marine environment of South Africa.
1
#
32 (4): 527 – 533.
Thomas, E. A., Varekamp, J. C. and Buchholtz ten Brink, M. R. 2004. Eutrophication of
Long Island Sound as traced by benthic foraminifera. )
"
0
+
4
87 – 91.
Toefy, R., McMillan, I. K. and Gibbons, M. J. 2003. The effect of wave exposure on the
foraminifera of (
.
+
3 C 83: 705 – 710.
Toefy, R. Gibbons, M. J. and McMillan, I. K. 2005. The foraminifera associated with the
alga (
South Africa. .
0
%
46: 1 – 26.
Toler, S. K. and Hallock, P. 1998. Shell malformation in stressed
populations: relation to biomineralization and paleoenvironmental potential.
+
+
- 34: 107 D 115.
Toler, S. K., Hallock, P. and Schijf, J. 2001. Mg/Ca ratios in stressed foraminifera,
%%
from the Florida Keys. +
+
- 43:
199 D 206.
Topping, J. N., Murray, J. W. & Pond, D. W. 2006. Sewage effects on the food sources
and diet of benthic foraminifera living in oxic sediment: A microcosm
experiment.
. ,
+
-
- 329 (2): 239D
250.
180
Touratier, F., Field, J. G. and Moloney, C. L. 2003. Simulated carbon and nitrogen flows
of the planktonic food web during an upwelling relaxation period in St Helena
Bay (southern Benguela ecosystem). )
!
-. 1 – 41.
Tsujimoto, A., Nomura, R., Yasuhara, M., Yamazaki, H. and Yoshikawa, S. 2006. Impact
of eutrophication on shallow marine benthic foraminifers over the last 150 years
in Oskaka Bay, Japan. +
+
-. 60: 258 – 268.
Twichell, S. C., Meyers, P. A. and DietserDHaass, L. 2002. Significance of C/N ratios in
organicDrich Neogene sediments under the Benguela Current upwelling system.
!
(
- 33: 715 – 722.
UNEP, 2003. Africa environment outlookD Southern Africa. www.grida.no/aeo/115.htm
Van Ieperen, M. P. 1971. -
- .
%
- Department of Oceanography,
University of Cape Town, Unpublished Report. 46 pp.
Walker, D. R. and Pitcher, G. C. 1991. The dynamics of phytoplankton populations,
including a redDtide bloom, during a quiescent period in St Helena Bay, South
Africa. #
.
.+
#
10: 61 – 70.
WAMTechnology cc and Rossouw, J. 1999. Wave climate study and plume dispersion
study for a marine sewer outfall off Robben Island. WAMTechnology,
Stellenbosch.
Watkins, J. G. 1961. Foraminiferal ecology around the Orange County, California, ocean
sewer outfall. +
- 7: 199 – 206.
Wheatcroft, R. A. and Butman, C. A. 1997. Spatial and temporal variability in aggregated
grainDsize distributions, with implications for sediment dynamics. $
#
.
17 (4): 367D390.
Williams, B. 1994.
5$
.
%
. Chapman and
Hall. London.
Williams, P. H. & Gaston, K. J. Measuring more of biodiversity: can higherDtaxon
richness predict wholesale species richness?
$
67: 211D
217.
Yanko, V., Kronfeld, J. and Flexer, A. 1994. Response of benthic foraminifera to various
pollution sources: Implcations for pollution monitoring.
.
.
24 (1): 1 – 17.
181
Zalesny, E. 1959. Foraminiferal Ecology of Santa Monica Bay, California.
+
Zar, J. H. 1999.
- 5: 101 – 126.
-
Prentice hall. New Jersey.
182
Appendix 1.1: Species of foraminifera identified by studies in South Africa
Species
%
sp
%
Brady
d'Orbigny
(Linne, 1767)
7
(Hada, 1931)
Dd'Orbigny, 1839)
Author
Siesser & Miles, 1979
Siesser & Miles, 1979
Siesser & Miles, 1979
Siesser & Miles, 1979
Siesser & Miles, 1979
Phleger, 1973
Chapman, 1924
Chapman, 1924
Chapman, 1907
Biesiot, 1957
Albani, 1965
Phleger, 1973
Martin, 1974
Salmon, 1979a
Salmon, 1981
McMillan, 1990
McMillan, 1998
Dale & McMillan, 1999
Dale & McMillan, 1999
Dale & McMillan, 1999
McMillan, 1990
Location
Birbury
Birbury
Birbury
Birbury
Birbury
St. Lucia Bay, Natal
S. A. Coast
S. A. Coast
Buffalo River, Cape Province
Umfolozi River, Natal
Durban Bay
St. Lucia Bay, Natal
W.coast SA
S. W. Indian Ocean
S. W. Indian Ocean
Cape Town
W.coast SA
Saldanha Region
Saldanha Region
Saldanha Region
Cape Town
Age
Lower Eocene
Lower Eocene
Lower Eocene
Lower Eocene
Lower Eocene
?unspecified
?unspecified
?unspecified
Pleistocene
Miocene
Recent
?unspecified
?unspecified
Quaternary
Quaternary
Late Pleistocene
Holocene
Late Pleistocene
Early Pleistocene
Holocene
Late Pleistocene
Dale & McMillan1999
Saldanha Region
Late Pleistocene
183
Species
Dd'Orbigny, 1839)
-
Batsch
d' Orbigny
(Fichtel & Moll, 1798)
Biesiot, 1957
Cushman & Edwards
Reuss, 1845
d'Orbigny
(Chapman & Parr)
%
sp.
cf.
Stache, 1865
,
.
(Millet, 1904)
Norman
Brady
Kennet, 1967
%
(Cushman, 1921)
-
. .
%
Schlumberger
Author
Dale & McMillan, 1999
Phleger, 1973
Martin, 1974
Biesiot, 1957
Parr, 1958
Biesiot, 1957
Biesiot, 1957
Chapman, 1916
Chapman, 1930
Chapman, 1924
Martin, 1974
Chapman, 1916
Salmon, 1979b
Phleger, 1973
Albani, 1965
Chapman, 1924
Chapman, 1924
Chapman, 1924
McMillan, 1990
Ehrenberg, 1863
Ehrenberg, 1863
Ehrenberg, 1863
Ehrenberg, 1863
Albani, 1965
Chapman, 1924
Location
Saldanha Region
St. Lucia Bay, Natal
W.coast SA
Umfolozi River, Natal
Durban
Umfolozi River, Natal
Umfolozi River, Natal
Buffalo River, Cape Province
Alexandria Formation
S. A. Coast
W.coast SA
Buffalo River, Cape Province
Agulhas Passage
St. Lucia Bay, Natal
Durban Bay
S. A. Coast
S. A. Coast
S. A. Coast
Cape Town
Agulhas Bank
Agulhas Bank
Agulhas Bank
Agulhas Bank
Durban Bay
S.A. Coast
Age
Holocene
?unspecified
?unspecified
Miocene
Pleistocene
Miocene
Miocene
Upper Cretaceous
Upper Eocene
?unspecified
?unspecified
Upper Cretaceous
Eocene
?unspecified
Recent
?unspecified
?unspecified
?unspecified
Late Pleistocene
?unspecified
?unspecified
?unspecified
?unspecified
Recent
?unspecified
Chapman, 1924
S.A. Coast
?unspecified
184
Species
d' Orbigny
Schlumberger
Brady
.
McMillan, 1987
%
Cushman
.
Seguenza
% %
Biesiot, 1957
HeronDAllen & Earland
d'Orbigny
'
Schwager
sp
Pearcey
.
(Hoglund)
McMillan, 1987
Williamson
d' Orbigny
Cushman
d' Orbigny
%%
Author
Chapman, 1925
Chapman, 1924
Chapman, 1924
Toefy
., 2003
Salmon, 1979a
Chapman, 1924
Biesiot, 1957
Toefy
., 2003
Chapman, 1924
Salmon, 1979a
Phleger, 1973
Chapman, 1924
Chapman, 1924
McMillan, 1998
Dale & McMillan, 1999
Toefy
., 2003
Martin, 1974
McMillan, 1990
Dale & McMillan, 1999
Martin, 1974
Salmon, 1979a
Martin, 1974
McMillan, 1998
Location
S.A. Coast
S.A. Coast
S.A. Coast
False Bay
S. W. Indian Ocean
S.A. Coast
Umfolozi River, Natal
False Bay
S.A. Coast
S. W. Indian Ocean
St. Lucia Bay, Natal
S. A. Coast
S. A. Coast
W.coast SA
Saldanha Region
False Bay
W.coast SA
Cape Town
Saldanha Region
W.coast SA
S. W. Indian Ocean
W.coast SA
W.coast SA
Age
?unspecified
?unspecified
?unspecified
Recent
Quaternary
?unspecified
Miocene
Recent
?unspecified
Quaternary
?unspecified
?unspecified
?unspecified
Holocene
Holocene
Recent
?unspecified
Late Pleistocene
Late Pleistocene
?unspecified
Quaternary
?unspecified
Holocene
Dale & McMillan, 1999
Saldanha Region
Early Pleistocene
185
Species
%%
.
Seguenza
d' Orbigny, 1826
d' Orbigny, 1826
Brady
.
Cushman, 1947
var. ,
(Cushman)
var.
Chapman, 1904
$
$
$
Egger
(Williamson, 1858)
(Fichtel & Moll)
%
$
$
$
$
$
$
d' Orbigny, 1839
%
- (Norman)
d' Orbigny, 1839
% Seguenza
Silvestri
d' Orbigny
Author
Dale & McMillan, 1999
Martin, 1974
Salmon, 1979a
Chapman, 1924
Albani, 1965
Martin, 1974
McMillan, 1990
Chapman, 1930
Salmon, 1979a
Biesiot, 1957
Martin, 1974
Chapman, 1904
Dale & McMillan, 1999
Chapman, 1923
Albani, 1965
Biesiot, 1957
Martin, 1974
McMillan, 1998
Salmon, 1979a
Giraudeau, 1993
Martin, 1974
McMillan, 1990
Chapman, 1924
McMillan, 1998
Location
Saldanha Region
W.coast SA
S. W. Indian Ocean
S. A. Coast
Durban Bay
W.coast SA
Cape Town
Alexandria Formation
S. W. Indian Ocean
Umfolozi River, Natal
W.coast SA
E. Pondoland
Saldanha Region
Uzamba River, Natal
Durban Bay
Umfolozi River, Natal
W.coast SA
W.coast SA
S. W. Indian Ocean
Benguela
W.coast SA
Cape Town
S. A. Coast
W.coast SA
Age
Late Pleistocene
?unspecified
Quaternary
?unspecified
Recent
?unspecified
Late Pleistocene
Upper Eocene
Quaternary
Miocene
?unspecified
Cretaceous
Holocene
Cretaceous
Recent
Miocene
?unspecified
Holocene
Quaternary
Recent
?unspecified
Late Pleistocene
?unspecified
Holocene
Salmon, 1979a
S. W. Indian Ocean
Quaternary
186
Species
$
$
$
$
$
$%
$%
d' Orbigny
var.
%
.
%
$%
$%
$%
$%
$%
.
/
%
(Cushman)
Chapman & Parr
Smitter, 1956
Galloway & Wissler, 1927
(Walker & Jacob, 1784)
(Seguenza)
(Cushman)
Montfort, 1808
Biesiot, 1957
. (Schwager)
Author
McMillan, 1990
McMillan, 1998
Dale & McMillan, 1999
Dale & McMillan, 1999
Martin, 1974
Salmon, 1979a
Ehrenberg, 1863
Smitter, 1956
McMillan, 1990
Chapman, 1930
Biesiot, 1957
Albani, 1965
Martin, 1974
McMillan, 1990
McMillan, 1998
Toefy
., 2003
Biesiot, 1957
Martin, 1974
Parr, 1958
Albani, 1965
Martin, 1974
Salmon, 1981
Biesiot, 1957
Salmon, 1979a
Location
Cape Town
W.coast SA
Saldanha Region
Saldanha Region
W.coast SA
S. W. Indian Ocean
Agulhas Bank
St. Lucia Bay, Natal
Cape Town
Alexandria Formation
Umfolozi River, Natal
Durban Bay
Alexandria Formation
Cape Town
W.coast SA
False Bay
Umfolozi River, Natal
W.coast SA
Durban
Durban Bay
W.coast SA
S. W. Indian Ocean
Umfolozi River, Natal
S. W. Indian Ocean
Age
Late Pleistocene
Holocene
Late Pleistocene
Holocene
?unspecified
Quaternary
?
?Recent
Late Pleistocene
Upper Eocene
Miocene
Recent
?unspecified
Late Pleistocene
Holocene
Recent
Miocene
?unspecified
Pleistocene
Recent
?unspecified
Quaternary
Miocene
Quaternary
187
Species
$%
$%
$%
$%
$%
$
$
$
$ %
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
Biesiot, 1957
%
(d' Orbigny, 1826)
sp
d'Orbigny
Costa
Phillipi
%
(G. O Sars)
Fichtel & Moll
Montfort
Fichtel & Moll
Costa
Reuss, 1845
Defrance
Karrer
Reuss, 1862
.
%
/
Lamarck
%
Reuss
Reuss, 1860
Reuss, 1854
Reuss
Jones
Author
Biesiot, 1957
Salmon, 1981
Albani, 1965
McMillan, 1990
Dale & McMillan, 1999
Phleger, 1973
Chapman, 1924
Chapman, 1924
Chapman, 1924
Martin, 1974
Chapman, 1924
Chapman, 1924
Chapman, 1930
Chapman, 1924
Chapman, 1916
Chapman, 1924
Chapman, 1924
Chapman, 1916
Ehrenberg, 1863
Chapman, 1924
Chapman, 1923
Chapman, 1916
Chapman, 1904
Chapman, 1923
Chapman, 1924
Chapman, 1924
Location
Umfolozi River, Natal
S. W. Indian Ocean
Durban Bay
Cape Town
Saldanha Region
St. Lucia Bay, Natal
S. A. Coast
S. A. Coast
S. A. Coast
W.coast SA
S.A. Coast
S.A. Coast
Alexandria Formation
S.A. Coast
Buffalo River, Cape Province
S.A. Coast
S.A. Coast
Buffalo River, Cape Province
Agulhas Bank
S.A. Coast
Uzamba River, Natal
Buffalo River, Cape Province
E. Pondoland
Uzamba River, Natal
S.A. Coast
S.A. Coast
Age
Miocene
Quaternary
Recent
Late Pleistocene
Late Pleistocene
?unspecified
?unspecified
?unspecified
?unspecified
?unspecified
?unspecified
?unspecified
Upper Eocene
?unspecified
Upper Cretaceous
?unspecified
?unspecified
Upper Cretaceous
?unspecified
?unspecified
Cretaceous
Upper Cretaceous
Cretaceous
Cretaceous
?unspecified
?unspecified
188
Species
$- %
%
. .
(d' Orbigny)
(Mich.)
(Kaufmann)
%
d' Orbigny
%
d' Orbigny
d'Orbigny, 1839
d' Orbigny
' (Brady, 1884)
%
%
%
%
%
%
.
(Brady, 1884)
(d' Orbigny, 1826)
- (Cushman)
Eade
Cushman & Jarvis, 1936
(Cushman, 1922)
Author
Albani, 1965
Albani, 1965
Martin, 1974
Martin, 1974
Chapman, 1930
Chapman, 1930
Chapman, 1924
Chapman, 1924
Chapman, 1916
Chapman, 1923
Albani, 1965
Martin, 1974
Salmon, 1979a
Salmon, 1979a
Location
Durban Bay
Durban Bay
W.coast SA
W.coast SA
Alexandria Formation
Alexandria Formation
S.A. Coast
S.A. Coast
Buffalo River, Cape Province
Uzamba River, Natal
Durban Bay
W.coast SA
S. W. Indian Ocean
S. W. Indian Ocean
Age
Recent
Recent
?unspecified
?unspecified
Upper Eocene
Upper Eocene
?unspecified
?unspecified
Upper Cretaceous
Cretaceous
Recent
?unspecified
Quaternary
Quaternary
Salmon, 1979b
Agulhas Passage
Eocene
Albani, 1965
Martin, 1974
Salmon, 1979a
Salmon, 1981
McMillan, 1990
McMillan, 1998
Dale & McMillan, 1999
Dale & McMillan, 1999
Durban Bay
W.coast SA
S. W. Indian Ocean
S. W. Indian Ocean
Cape Town
W.coast SA
Saldanha Region
Saldanha Region
Recent
?unspecified
Quaternary
Quaternary
Late Pleistocene
Holocene
Late Pleistocene
Early Pleistocene
Dale & McMillan, 1999
Saldanha Region
Holocene
189
Species
(Cushman, 1922)
(d'Orbigny, 1839)
(Fictel & Moll, 1798)
Montfort, 1808
cf. .
%
(Cushman)
(Fichtel & Moll, 1798)
Author
Toefy
., 2003
Dale & McMillan, 1999
McMillan, 1990
Dale & McMillan, 1999
Chapman, 1930
Albani, 1965
Salmon, 1981
Chapman, 1907
Parr, 1958
Albani, 1965
Martin, 1974
Salmon, 1979a
Salmon, 1981
McMillan, 1990
Dale & McMillan, 1999,
Dale &
McMillan, 1999
Dale & McMillan, 1999
Biesiot, 1957
Chapman, 1907
Albani, 1965
McMillan, 1990
McMillan, 1998
Location
False Bay
Saldanha Region
Cape Town
Saldanha Region
Alexandria Formation
Durban Bay
S. W. Indian Ocean
Buffalo River, Cape Province
Durban
Durban Bay
W.coast SA
S. W. Indian Ocean
S. W. Indian Ocean
Cape Town
Age
Recent
Holocene
Late Pleistocene
Holocene
Upper Eocene
Recent
Quaternary
Pleistocene
Pleistocene
Recent
?unspecified
Quaternary
Quaternary
Late Pleistocene
Saldanha Region
Saldanha Region
Saldanha Region
Umfolozi River, Natal
Buffalo River, Cape Province
Durban Bay
Cape Town
W.coast SA
Late Pleistocene
Early Pleistocene
Holocene
Miocene
Pleistocene
Recent
Late Pleistocene
Holocene
Dale & McMillan, 1999
Saldanha Region
Late Pleistocene
190
Species
(Fichtel & Moll, 1798)
%% Hedberg, 1937
%
(Reuss)
Biesiot, 1957
%
(Reuss)
(Williamson, 1848)
(Walker & Boys, 1784)
(d' Orbigny)
Defrance
%
(Czjzek)
%
%'
(
-
.%
(
-
,
(Egger)
- Cushman
(
( %
(HeronDAllen & Earland, 1932)
( %
(
(HeronDAllen & Earland, 1932)
var.
(Cushman)
Author
Dale & McMillan, 1999
Toefy
., 2003
Salmon, 1981
Martin, 1974
Biesiot, 1957
Chapman, 1930
Martin, 1974
McMillan, 1990
Dale & McMillan, 1999
McMillan, 1990
Martin, 1974
Chapman, 1924
Martin, 1974
Location
Saldanha Region
False Bay
S. W. Indian Ocean
W.coast SA
Umfolozi River, Natal
Alexandria Formation
W.coast SA
Cape Town
Saldanha Region
Cape Town
W.coast SA
S.A. Coast
W.coast SA
Age
Holocene
Recent
Quaternary
?unspecified
Miocene
Upper Eocene
?unspecified
Late Pleistocene
Holocene
Late Pleistocene
?unspecified
?unspecified
?unspecified
Martin, 1974
W.coast SA
?unspecified
Chapman, 1930
Alexandria Formation
Upper Eocene
Phleger, 1973
St. Lucia Bay, Natal
?unspecified
Dale & McMillan, 1999
Saldanha Region
Late Pleistocene
McMillan, 1990
Dale & McMillan, 1999
Dale & McMillan, 1999
Toefy
., 2003
Martin, 1974
Cape Town
Saldanha Region
Saldanha Region
False Bay
W.coast SA
Late Pleistocene
Late Pleistocene
Early Pleistocene
Recent
?unspecified
191
Species
( %
( %
( %
( %
'
Brady
Cushman & Jarvis, 1936
var '
Le Roy, 1944
d' Orbigny, 1826
%
%
( %
( %
( %
Parker, 1962
Reuss, 1854
%
Brady
( %
(
(
(
(
(
(
(
(
(
(
%
%
%
%
%
%
%
%
%
%
Brady, 1879
Rhumbler, 1900
.
,
% '
d' Orbigny
Cushman, 1925
,
Bolli & Bermudez
cf.
' '
DEhrenberg, 1861)
Parker
%
Author
Siesser & Miles, 1979
Salmon, 1979b
Biesiot, 1957
Chapman, 1924
Chapman, 1907
Chapman, 1930
Albani, 1965
Salmon, 1979a
McMillan, 1990
Giraudeau, 1993
Salmon, 1979a
Chapman, 1904
Chapman, 1924
Siesser & Miles, 1979
Salmon, 1979a
Giraudeau, 1993
Albani, 1965
Giraudeau, 1993
Chapman, 1923
Salmon, 1979b
Siesser & Miles, 1979
Ehrenberg, 1863
Salmon, 1979a
Siesser & Miles, 1979
Ehrenberg, 1863
Giraudeau, 1993
Location
Zululand
Agulhas Passage
Umfolozi River, Natal
S.A. Coast
Buffalo River, Cape Province
Alexandria Formation
Durban Bay
S. W. Indian Ocean
Cape Town
Benguela
S. W. Indian Ocean
E. Pondoland
S.A. Coast
Zululand
S. W. Indian Ocean
Benguela
Durban Bay
Benguela
Uzamba River, Natal
Agulhas Passage
Zululand
Agulhas Bank
S. W. Indian Ocean
Zululand
Agulhas Bank
Benguela
Age
Upper Miocene
Miocene
Miocene
?unspecified
Pleistocene
Upper Eocene
Recent
Quaternary
Late Pleistocene
Recent
Quaternary
Cretaceous
?unspecified
Upper Miocene
Quaternary
Recent
Recent
Recent
Cretaceous
Eocene
Upper Miocene
?unspecified
Quaternary
Upper Miocene
?unspecified
Recent
192
Species
( %
( %
( %
( %
( %
(
(
(
(
(
%
%
%
%
%
( %
( %
(
(
(
(
%
%
%
%
( %
'
'
%
%
%
'
'
%
d' Orbigny, 1939
Chapman
(Reuss)
Hedberg, 1937
(Brady)
(Brady)
.
(d' Orbigny, 1839)
(Egger, 1893)
Bolli, Loeblich & Tappan, 1957
%
(Brady, 1879)
Blow, 1956Finlay, 1939
, Finlay, 1939
'
%
.
(Brady, 1877)
% (d' Orbigny, 1939)
.
(Brady, 1879)
Author
McMillan, 1998
Salmon, 1979b
Chapman, 1924
Giraudeau, 1993
Chapman, 1924
Siesser & Miles, 1979
Salmon, 1979b
Biesiot, 1957
Giraudeau, 1993
Salmon, 1979a
Salmon, 1979a
Giraudeau, 1993
Salmon, 1979b
Chapman, 1907
Chapman, 1930
Albani, 1965
Salmon, 1979a
Giraudeau, 1993
Salmon, 1979b
Salmon, 1979b
Albani, 1965
Salmon, 1979a
Giraudeau, 1993
Biesiot, 1957
Salmon, 1979a
Salmon, 1979b
Giraudeau, 1993
Location
W.coast SA
Agulhas Passage
S.A. Coast
Benguela
S.A. Coast
Zululand
Agulhas Passage
Umfolozi River, Natal
Benguela
S. W. Indian Ocean
S. W. Indian Ocean
Benguela
Agulhas Passage
Buffalo River, Cape Province
Alexandria Formation
Durban Bay
S. W. Indian Ocean
Benguela
Agulhas Passage
Agulhas Passage
Durban Bay
S. W. Indian Ocean
Benguela
Umfolozi River, Natal
S. W. Indian Ocean
Agulhas Passage
Benguela
Age
Holocene
Miocene
?unspecified
Recent
?unspecified
Upper Miocene
Eocene
Miocene
Recent
Quaternary
Quaternary
Recent
Eocene
Pleistocene
Upper Eocene
Recent
Quaternary
Recent
Miocene
Eocene
Recent
Quaternary
Recent
Miocene
Quaternary
Miocene
Recent
193
Species
(
(
(
(
(
(
(
(
(
(
(
(
(
%
%
%
%
%
%
%
%
%
%
%
%
%
(
(
(
(
(
%
%
%
%
%
(
(
(
(
%
%
%
%
%
'
'
'
Keijer, 1945
de Stefani, 1952
Blow, 1956
(d' Orbigny)
D
(Cushman & Jarvis)
%
Bolli
(d' Orbigny, 1839)
Bolli, 1957
-
%
%
.
Chapman, Parr & Collins, 1934
.
(d' Orbigny)
%
(d' Orbigny, 1939)
(d' Orbigny, 1939)
Bolli, 1957
Blow & Banner, 1966
Brady, 1882
Cushman, 1927
(Brady, 1877)
. ,
(Koch, 1923)
(d' Orbigny)
Author
Location
Age
Salmon, 1979b
Salmon, 1979b
Salmon, 1979b
Biesiot, 1957
Martin, 1974
Siesser & Miles, 1979
Siesser & Miles, 1979
Salmon, 1979a
Salmon, 1979b
Giraudeau, 1993
Salmon, 1979b
Giraudeau, 1993
Salmon, 1979a
McMillan, 1990
Giraudeau, 1993
Dale & McMillan, 1999
Salmon, 1979a
Giraudeau, 1993
Salmon, 1979b
Salmon, 1979b
Salmon, 1979b
Giraudeau, 1993
Salmon, 1979b
Salmon, 1979a
Salmon, 1979a
Salmon, 1979a
Agulhas Passage
Agulhas Passage
Agulhas Passage
Umfolozi River, Natal
W.coast SA
Zululand
Zululand
S. W. Indian Ocean
Agulhas Passage
Benguela
Agulhas Passage
Benguela
S. W. Indian Ocean
Cape Town
Benguela
Saldanha Region
S. W. Indian Ocean
Benguela
Agulhas Passage
Agulhas Passage
Agulhas Passage
Benguela
Agulhas Passage
S. W. Indian Ocean
S. W. Indian Ocean
S. W. Indian Ocean
Eocene
Miocene
Miocene
Miocene
?unspecified
Upper Miocene
Upper Miocene
Quaternary
Eocene
Recent
Miocene
Recent
Quaternary
Late Pleistocene
Recent
Late Pleistocene
Quaternary
Recent
Miocene
Miocene
Miocene
Recent
Eocene
Quaternary
Quaternary
Quaternary
194
Species
( %
( %
( %
(
(
(
(
(
(d' Orbigny)
%% d' Orbigny
'
Reuss
%
.
%
((-
%
(d' orbigny, 1826)
(d' Orbigny)
(d' Orbigny)
%
Finlay, 1939
Shokina, 1937
Cushman, 1952
.
d' Orbigny, 1839
Norman
%
.
Parker & Jones
Brady
Bornemann
Chapman, 1894
Chapman, 1904
%
-
%
(Schroeter, 1783)
Author
Giraudeau, 1993
Biesiot, 1957
Biesiot, 1957
Ehrenberg, 1863
Ehrenberg, 1863
Ehrenberg, 1863
Ehrenberg, 1863
Biesiot, 1957
Albani, 1965
Martin, 1974
Martin, 1974
Salmon, 1979a
Salmon, 1979b
Salmon, 1979b
Salmon, 1979b
Chapman, 1907
Chapman, 1924
Chapman, 1924
Chapman, 1924
Chapman, 1924
Chapman, 1904
Chapman, 1916
Chapman, 1904
Phleger, 1973
Giraudeau, 1993
Martin, 1974
Salmon, 1981
Location
Benguela
Umfolozi River, Natal
Umfolozi River, Natal
Agulhas Bank
Agulhas Bank
Agulhas Bank
Agulhas Bank
Umfolozi River, Natal
Durban Bay
W.coast SA
W.coast SA
S. W. Indian Ocean
Agulhas Passage
Agulhas Passage
Agulhas Passage
Buffalo River, Cape Province
S. A. Coast
S. A. Coast
S. A. Coast
S. A. Coast
E. Pondoland
Buffalo River, Cape Province
E. Pondoland
St. Lucia Bay, Natal
Benguela
W.coast SA
S. W. Indian Ocean
Age
Recent
Miocene
Miocene
?unspecified
?unspecified
?unspecified
?unspecified
Miocene
Recent
?unspecified
?unspecified
Quaternary
Eocene
Eocene
Eocene
Pleistocene
?unspecified
?unspecified
?unspecified
?unspecified
Cretaceous
Upper Cretaceous
Cretaceous
?unspecified
Recent
?unspecified
Quaternary
195
Species
-
%
%
C
"
"
"
"
"
"
"
"
%
'
(Schroeter, 1783)
(Schroeter, 1783)
Brady
Brady
Brady
- (Cushman)
(Williamson)
Williamson
(Seguenza)
(Williamson)
Walker & Boys
(Montagu)
(Williamson) var.
Wright, 1886
"
Williamson, 1858
"
"
"
(d' Orbigny, 1839)
(d' Orbigny, 1839) var
(Walker & Jacob)
"
"
"
(Walker & Jacob) var
(Parker & Jones)
E! %
(Bailey)
Author
Location
Age
cMillan, 1990
Dale & McMillan, 1999
Chapman, 1924
Chapman, 1924
Chapman, 1924
Martin, 1974
Salmon, 1979a
Biesiot, 1957
Salmon, 1979a
Martin, 1974
Martin, 1974
Chapman, 1924
Salmon, 1979a
Salmon, 1979a
McMillan, 1990
Toefy
., 2003
Albani, 1965
Martin, 1974
Albani, 1965
Salmon, 1979a
Martin, 1974
Chapman, 1924
Salmon, 1979a
Salmon, 1979a
Martin, 1974
Cape Town
Saldanha Region
S. A. Coast
S. A. Coast
S. A. Coast
W.coast SA
S. W. Indian Ocean
Umfolozi River, Natal
S. W. Indian Ocean
W.coast SA
W.coast SA
S.A. Coast
S. W. Indian Ocean
S. W. Indian Ocean
Cape Town
False Bay
Durban Bay
W.coast SA
Durban Bay
S. W. Indian Ocean
W.coast SA
S.A. Coast
S. W. Indian Ocean
S. W. Indian Ocean
W.coast SA
Late Pleistocene
Late Pleistocene
?unspecified
?unspecified
?unspecified
?unspecified
Quaternary
Miocene
Quaternary
?unspecified
?unspecified
?unspecified
Quaternary
Quaternary
Late Pleistocene
Recent
Recent
?unspecified
Recent
Quaternary
?unspecified
?unspecified
Quaternary
Quaternary
?unspecified
196
Species
"
" %
Location
W.coast SA
Saldanha Region
Saldanha Region
Saldanha Region
Durban Bay
S. A. Coast
S. A. Coast
W.coast SA
Age
?unspecified
Late Pleistocene
Early Pleistocene
Holocene
Recent
?unspecified
?unspecified
?unspecified
(Fichtel & Moll)
Salmon, 1979a
S. W. Indian Ocean
Quaternary
Phleger, 1973
St. Lucia Bay, Natal
?unspecified
Chapman, 1916
Buffalo River, Cape Province
Upper Cretaceous
Dale & McMillan, 1999
Chapman, 1924
Chapman, 1916
Chapman, 1907
Chapman, 1930
McMillan, 1990
Toefy
, 2003
Siesser & Miles, 1979
Siesser & Miles, 1979
McMillan, 1990
Giraudeau, 1993
Saldanha Region
S. A. Coast
Buffalo River, Cape Province
Buffalo River, Cape Province
Alexandria Formation
Cape Town
False Bay
Birbury
Zululand
Cape Town
Benguela
Late Pleistocene
?unspecified
Upper Cretaceous
Pleistocene
Upper Eocene
Late Pleistocene
Recent
Lower Eocene
Upper Miocene
Late Pleistocene
Recent
McMillan, 1998
W.coast SA
Holocene
(Cushman)
%
" ,
+
+
+
%
-
+
+
.
+
.
+
+
+
+
+
2
2
(Brady, 1879)
HeronDAllen & Earland
Brady
(d'Orbigny)
Author
Martin, 1974
Dale & McMillan, 1999
Dale & McMillan, 1999
Dale & McMillan, 1999
Albani, 1965
Chapman, 1924
Chapman, 1924
Martin, 1974
Bornemann
Bornemann
d' Orbigny
d' Orbigny
Montagu, 1803
. .
%
%%
% '
% '
-
(Takayangi & Saito)
(Ehrenberg, 1861)
197
Species
2
2
2
2
2
2
. .
% '
2
2
2
2
2
2
2
2
2
2
2
2
2
2
-
Cushman, 1923
D'Orbigny
D'Orbigny
Linne
D'Orbigny
Reuss, 1860
d'Orbigny
(Linne)
Batsch
%
*
Nilsson, 1825
Reuss, 1845
%
Cushman, 1917
(d' Orbigny, 1846)
%
(d' Orbigny)
Cole, 1927
DFichtel & Moll, 1798)
(Montagu)
%
(Williamson)
(Williamson)
(Dawson)
Author
Salmon, 1979b
Chapman, 1924
Chapman, 1924
Chapman, 1924
Chapman, 1924
Chapman, 1904
Chapman, 1923
Chapman, 1924
Martin, 1974
Chapman, 1924
Albani, 1965
Chapman, 1916
Chapman, 1904
Chapman, 1916
Biesiot, 1957
Albani, 1965
McMillan, 1998
Dale & McMillan, 1999
Biesiot, 1957
Salmon, 1979b
Salmon, 1981
Chapman, 1924
Martin, 1974
Martin, 1974
McMillan, 1998
Martin, 1974
Location
Agulhas Passage
S.A. Coast
S.A. Coast
S.A. Coast
S.A. Coast
E. Pondoland
Uzamba River, Natal
S.A. Coast
W.coast SA
S.A. Coast
Durban Bay
Buffalo River, Cape Province
E. Pondoland
Buffalo River, Cape Province
Umfolozi River, Natal
Durban Bay
W.coast SA
Saldanha Region
Umfolozi River, Natal
Agulhas Passage
S. W. Indian Ocean
S.A. Coast
W.coast SA
W.coast SA
W.coast SA
W.coast SA
Age
Eocene
?unspecified
?unspecified
?unspecified
?unspecified
Cretaceous
Cretaceous
?unspecified
?unspecified
?unspecified
Recent
Upper Cretaceous
Cretaceous
Upper Cretaceous
Miocene
Recent
Holocene
Early Pleistocene
Miocene
Eocene
Quaternary
?unspecified
?unspecified
?unspecified
Holocene
?unspecified
198
Species
2
!%
d' Orbigny
!%
d' Orbigny
!
!
!
!
!
)
)
(Batsch)
(Williamson)
d'Orbigny
sp A, McMillan, 1987
'
(HeronDAllen & Earland, 1922)
%
Bermudez, 1949
Williamson
,
)
)
)
)
)
(Terquem, 1882)
(Asano, 1936)
%
%
Brady
Brady
d' Orbigny, 1826
Author
Dale & McMillan, 1999
Chapman, 1924
Biesiot, 1957
Salmon, 1979a
Siesser & Miles, 1979
Giraudeau, 1993
McMillan, 1998
Salmon, 1979a
Salmon, 1979a
Toefy
., 2003
McMillan, 1990
McMillan, 1990
Biesiot, 1957
Dale & McMillan, 1999
Toefy
., 2003
Salmon, 1981
McMillan, 1990
Dale & McMillan, 1999
Dale & McMillan, 1999
Dale & McMillan, 1999
Chapman, 1924
Chapman, 1924
Parr, 1958
Location
Saldanha Region
S.A. Coast
Umfolozi River, Natal
S. W. Indian Ocean
Zululand
Benguela
W.coast SA
S. W. Indian Ocean
S. W. Indian Ocean
False Bay
Cape Town
Cape Town
Umfolozi River, Natal
Saldanha Region
False Bay
S. W. Indian Ocean
Cape Town
Saldanha Region
Saldanha Region
Saldanha Region
S. A. Coast
S. A. Coast
Durban
Age
Holocene
?unspecified
Miocene
Quaternary
Upper Miocene
Recent
Holocene
Quaternary
Quaternary
Recent
Late Pleistocene
Late Pleistocene
Miocene
Late Pleistocene
Recent
Quaternary
Late Pleistocene
Late Pleistocene
Early Pleistocene
Holocene
?unspecified
?unspecified
Pleistocene
199
Species
)
)
%
d' Orbigny, 1826
E! % -
)
)
)
/
%
%
)
) ) ) )
)
)
)
)
)
)
)
)
)
)
. (Schwager)
(Jones & Parker, 1862)
Palmer & Bemudez
%
Reuss, 1851
%% d' Orbigny, 1826
Walker & Jacobs
'
'
(Cole)
% /
Biesiot, 1957
Cushman & Todd, 1943
'
% Reuss
% '
(d'Orbigny)
% '
(Parker & Jones, 1865)
Fichtel & Moll
Reuss, 1862
Author
Location
Age
Toefy
., 2003
McMillan, 1998
Dale & McMillan, 1999
Martin, 1974
McMillan, 1990
Salmon, 1979a
Salmon, 1979b
Chapman, 1904
Ehrenberg, 1863
Chapman, 1904
Chapman, 1924
Chapman, 1930
Albani, 1965
Ehrenberg, 1863
Salmon, 1979b
Biesiot, 1957
Biesiot, 1957
Martin, 1974
Salmon, 1979a
Chapman, 1924
Giraudeau, 1993
Martin, 1974
Salmon, 1979a
Chapman, 1924
Chapman, 1904
Chapman, 1923
False Bay
W.coast SA
Saldanha Region
W.coast SA
Cape Town
S. W. Indian Ocean
Agulhas Passage
E. Pondoland
Agulhas Bank
E. Pondoland
S. A. Coast
Alexandria Formation
Durban Bay
Agulhas Bank
Agulhas Passage
Umfolozi River, Natal
Umfolozi River, Natal
W.coast SA
S. W. Indian Ocean
S. A. Coast
Benguela
W.coast SA
S. W. Indian Ocean
S.A. Coast
E. Pondoland
Uzamba River, Natal
Recent
Holocene
Late Pleistocene
?unspecified
Late Pleistocene
Quaternary
Eocene
Cretaceous
?unspecified
Cretaceous
?unspecified
Upper Eocene
Recent
?unspecified
Eocene
Miocene
Miocene
?unspecified
Quaternary
?unspecified
Recent
?unspecified
Quaternary
?unspecified
Cretaceous
Cretaceous
200
Species
)
)
Parker & Jones
d' Orbigny, 1826
)
Reuss, 1855
)
)
d'Orbigny
Chapman, 1904
)
Reuss, 1862
)
)
))-
d'Orbigny
sp.
%
))& '
& '
&
&
&
&
'
'
'
'
d' Orbigny
(Schwager)
aff.
%
d' Orbigny
d' Orbigny, 1839
d' Orbigny
d'Orbigny
d'Órbigny, 1846
'
HeronDAllen & Earland
Author
Chapman, 1924
Chapman, 1904
Chapman, 1907
Chapman, 1924
Chapman, 1907
Chapman, 1916
Chapman, 1924
Chapman, 1904
Chapman, 1923
Chapman, 1904
Chapman, 1923
Chapman, 1924
Chapman, 1916
Martin, 1974
Martin, 1974
Salmon, 1979a
Martin, 1974
Biesiot, 1957
Biesiot, 1957
Albani, 1965
Martin, 1974
Biesiot, 1957
Martin, 1974
McMillan, 1990
McMillan, 1990
Dale & McMillan, 1999
Location
S.A. Coast
E. Pondoland
Buffalo River, Cape Province
S.A. Coast
Buffalo River, Cape Province
Buffalo River, Cape Province
S.A. Coast
E. Pondoland
Uzamba River, Natal
E. Pondoland
Uzamba River, Natal
S.A. Coast
Buffalo River, Cape Province
W.coast SA
W.coast SA
S. W. Indian Ocean
W.coast SA
Umfolozi River, Natal
Umfolozi River, Natal
Durban Bay
W.coast SA
Umfolozi River, Natal
W.coast SA
Cape Town
Cape Town
Saldanha Region
Age
?unspecified
Cretaceous
Pleistocene
?unspecified
Pleistocene
Upper Cretaceous
?unspecified
Cretaceous
Cretaceous
Cretaceous
Cretaceous
?unspecified
Upper Cretaceous
?unspecified
?unspecified
Quaternary
?unspecified
Miocene
Miocene
Recent
?unspecified
Miocene
?unspecified
Late Pleistocene
Late Pleistocene
Late Pleistocene
201
Species
& '
'
%
Author
Dale & McMillan, 1999
Toefy et al, 2003
McMillan, 1990
Toefy et al, 2003
Albani, 1965
Biesiot, 1957
McMillan, 1990
Dale & McMillan, 1999
Location
Saldanha Region
False Bay
Cape Town
False Bay
Durban Bay
Umfolozi River, Natal
Cape Town
Saldanha Region
Age
Early Pleistocene
Recent
Late Pleistocene
Recent
Recent
Miocene
Late Pleistocene
Late Pleistocene
Chapman, 1907
Albani, 1965
Martin, 1974
McMillan, 1990
Dale & McMillan, 1999
Dale & McMillan, 1999
Toefy et al, 2003
Albani, 1965
Buffalo River, Cape Province
Durban Bay
W.coast SA
Cape Town
Saldanha Region
Saldanha Region
False Bay
Durban Bay
Pleistocene
Recent
?unspecified
Late Pleistocene
Late Pleistocene
Early Pleistocene
Recent
Recent
Albani, 1965
Durban Bay
Recent
d'Órbigny, 1846
McMillan, 1990
Cape Town
Late Pleistocene
d'Órbigny, 1852
McMillan, 1990
Toefy
2003
Ehrenberg, 1863
Parr, 1958
Cape Town
False Bay
Agulhas Bank
Durban
Late Pleistocene
Recent
?unspecified
Pleistocene
Toefy
False Bay
Recent
HeronDAllen & Earland
&
'
d'Órbigny, 1846
&
&
'
'
aff.
d' Orbigny, 1839
Terquem
&
'
aff.
Terquem
&
'
&
'
&
'
&
'
&
'
&
'
(Linne, 1767)
Cushman, 1932
d' Orbigny, 1826
cf.
d' Orbigny, 1826
2003
202
Species
%
,
,
,
,
Author
Chapman, 1924
Martin, 1974
McMillan, 1998
Chapman, 1924
Chapman, 1924
Phleger, 1973
Chapman, 1924
Chapman, 1924
Chapman, 1924
Chapman, 1924
Chapman, 1924
Biesiot, 1957
Biesiot, 1957
Location
S. A. Coast
W.coast SA
W.coast SA
S. A. Coast
S. A. Coast
St. Lucia Bay, Natal
S. A. Coast
S. A. Coast
S. A. Coast
S. A. Coast
S. A. Coast
Umfolozi River, Natal
Umfolozi River, Natal
Age
?unspecified
?unspecified
Holocene
?unspecified
?unspecified
?unspecified
?unspecified
?unspecified
?unspecified
?unspecified
?unspecified
Miocene
Miocene
(Reuss, 1863)
Albani, 1965
Durban Bay
Recent
Cushman & Renz
Biesiot, 1957
Umfolozi River, Natal
Miocene
Albani, 1965
McMillan, 1990
Dale & McMillan, 1999
Chapman, 1930
Dale & McMillan, 1999
Dale & McMillan, 1999
Toefy
2003
Salmon, 1981
Ehrenberg, 1863
Durban Bay
Cape Town
Saldanha Region
Alexandria Formation
Saldanha Region
Saldanha Region
False Bay
S. W. Indian Ocean
Agulhas Bank
Recent
Late Pleistocene
Early Pleistocene
Upper Eocene
Early Pleistocene
Holocene
Recent
Quaternary
?unspecified
.
Brady
(Mathews)
.
.
Brady
Brady
Montfort
Brady
Brady
%
%
,
Brady
(Bornemann)
Cushman, 1947
%
%
%
%
%
%
%
F
d Orbigny, 1839
- Cushman, 1915
F
%
d' Orbigny
d'Orbigny, 1850
203
Species
d' Orbigny
Parker & Jones, 1865
%
%
d' Orbginy, 1826
'
Reuss, 1844
var.
Reuss, 1844
#
#
%.
cf.
#
#
#
#
#
#
#
#
#
Brady
Defrance
%
E
-
Silvestri
%
(Silvestri)
(Schwager, 1866)
Cushman, 1913
E McMillan
%
%
(Reuss, 1848)
d' Orbigny
%
(Parker & Jones, 1865)
Author
Chapman, 1930
Chapman, 1907
Ehrenberg, 1863
Ehrenberg, 1863
Chapman, 1907
Ehrenberg, 1863
Ehrenberg, 1863
Chapman, 1924
Chapman, 1904
Chapman, 1923
Parr, 1958
Chapman, 1924
Biesiot, 1957
Martin, 1974
Salmon, 1979a
Martin, 1974
Albani, 1965
Albani, 1965
McMillan, 1998
Dale & McMillan, 1999
McMillan, 1990
Martin, 1974
Ehrenberg, 1863
Chapman, 1924
Salmon, 1979a
Giraudeau, 1993
Location
Alexandria Formation
Buffalo River, Cape Province
Agulhas Bank
Agulhas Bank
Buffalo River, Cape Province
Agulhas Bank
Agulhas Bank
S.A. Coast
E. Pondoland
Uzamba River, Natal
Durban
S.A. Coast
Umfolozi River, Natal
W.coast SA
S. W. Indian Ocean
W.coast SA
Durban Bay
Durban Bay
W.coast SA
Saldanha Region
Cape Town
W.coast SA
Agulhas Bank
S.A. Coast
S. W. Indian Ocean
Benguela
Age
Upper Eocene
Pleistocene
?unspecified
?unspecified
Pleistocene
?unspecified
?unspecified
?unspecified
Cretaceous
Cretaceous
Pleistocene
?unspecified
Miocene
?unspecified
Quaternary
?unspecified
Recent
Recent
Holocene
Late Pleistocene
Late Pleistocene
?unspecified
?unspecified
?unspecified
Quaternary
Recent
204
Species
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
# %%
#
,
,
,
,
,
,
.
Cushman & Todd, 1944
d' Orbigny, 1839
Cushman & Todd, 1944
d' Orbigny
Reuss
d' Orbigny, 1846
Cushman & Todd, 1944
Brady
,
%
Lamarck, 1805
(Czjzek)
Reuss, 1845
.
Chapman, 1916
%
sp.
(Schwager)
d' Orbigny
Brady, 1884
d'Orbigny
.
%
d'Orbigny, 1846
Defrance
(Williamson, 1858)
Author
Biesiot, 1957
Albani, 1965
Albani, 1965
Biesiot, 1957
Chapman, 1924
Chapman, 1907
Albani, 1965
Chapman, 1930
Martin, 1974
Chapman, 1907
Martin, 1974
Chapman, 1916
Ehrenberg, 1863
Chapman, 1916
Chapman, 1924
Salmon, 1979b
McMillan, 1990
Siesser & Miles, 1979
Salmon, 1979a
Chapman, 1930
Albani, 1965
Chapman, 1916
Chapman, 1930
Ehrenberg, 1863
Albani, 1965
Martin, 1974
McMillan, 1990
Location
Umfolozi River, Natal
Durban Bay
Durban Bay
Umfolozi River, Natal
S. A. Coast
Buffalo River, Cape Province
Durban Bay
Alexandria Formation
W.coast SA
Buffalo River, Cape Province
W.coast SA
Buffalo River, Cape Province
Agulhas Bank
Buffalo River, Cape Province
S. A. Coast
Agulhas Passage
Cape Town
Birbury
S. W. Indian Ocean
Alexandria Formation
Durban Bay
Buffalo River, Cape Province
Alexandria Formation
Agulhas Bank
Durban Bay
W.coast SA
Cape Town
Age
Miocene
Recent
Recent
Miocene
?unspecified
Pleistocene
Recent
Upper Eocene
?unspecified
Pleistocene
?unspecified
Upper Cretaceous
?unspecified
Upper Cretaceous
?unspecified
Eocene
Late Pleistocene
Lower Eocene
Quaternary
Upper Eocene
Recent
Upper Cretaceous
Upper Eocene
?unspecified
Recent
?unspecified
Late Pleistocene
205
Species
.
%
- Cushman
d' Orbigny, 1826
d' Orbigny, 1826
d' Orbigny, 1826
Parker & Jones
d' Orbigny
Brady
.
d' Orbigny, 1846
%
.
Walker & Jacob, 1798
Hautken, 1875
Montfort, 1808
%
Reuss, 1862
d' Orbigny, 1846
Author
Location
Age
Salmon, 1979a
Biesiot, 1957
Albani, 1965
Salmon, 1979a
Chapman, 1907
Chapman, 1930
Parr, 1958
Albani, 1965
Dale & McMillan, 1999
Biesiot, 1957
Chapman, 1924
Chapman, 1924
Phleger, 1973
Dale & McMillan, 1999
Phleger, 1973
Chapman, 1907
S. W. Indian Ocean
Umfolozi River, Natal
Durban Bay
S. W. Indian Ocean
Buffalo River, Cape Province
Alexandria Formation
Durban
Durban Bay
Saldanha Region
Umfolozi River, Natal
S. A. Coast
S. A. Coast
St. Lucia Bay, Natal
Saldanha Region
St. Lucia Bay, Natal
Buffalo River, Cape Province
Quaternary
Miocene
Recent
Quaternary
Pleistocene
Upper Eocene
Pleistocene
Recent
Early Pleistocene
Miocene
?unspecified
?unspecified
?unspecified
Holocene
?unspecified
Pleistocene
Chapman, 1907
Chapman, 1924
Chapman, 1907
Chapman, 1907
Chapman, 1904
Chapman, 1916
Chapman, 1923
Chapman, 1907
Chapman, 1916
Buffalo River, Cape Province
S. A. Coast
Buffalo River, Cape Province
Buffalo River, Cape Province
E. Pondoland
Buffalo River, Cape Province
Uzamba River, Natal
Buffalo River, Cape Province
Buffalo River, Cape Province
Pleistocene
?unspecified
Pleistocene
Pleistocene
Cretaceous
Upper Cretaceous
Cretaceous
Pleistocene
Upper Cretaceous
206
Species
/
3
3
3
3
3
3
3
3
:
:
:
:
:
:
:
:
:
:
G .
. Schwager
Bronniman & Bermudez, 1953
.
(d'Orbigny)
(d'Orbigny)
d' Orbigny
(Czjzek)
d' Orbigny
aff.
Morozova, 1939
Gumbel, 1968
(Cushman)
var. . %
Brady
%
Schwager
Reuss, 1862
Reuss, 1862
Linne, 1758
Montagu
Brady
%
DGalloway & Wissler), 1927
Biesiot, 1957
Biesiot, 1957
Reuss
Author
Chapman, 1924
Salmon, 1979b
McMillan, 1998
McMillan, 1998
Salmon, 1979a
Martin, 1974
Martin, 1974
Biesiot, 1957
Salmon, 1979b
Martin, 1974
Salmon, 1979a
Salmon, 1979a
Chapman, 1904
Chapman, 1904
Chapman, 1904
Chapman, 1923
Chapman, 1924
Martin, 1974
Albani, 1965
Biesiot, 1957
Biesiot, 1957
Chapman, 1924
Phleger, 1973
Dale & McMillan, 1999
Location
S.A. Coast
Agulhas Passage
W.coast SA
W.coast SA
S. W. Indian Ocean
W.coast SA
W.coast SA
Umfolozi River, Natal
Agulhas Passage
W.coast SA
S. W. Indian Ocean
S. W. Indian Ocean
E. Pondoland
E. Pondoland
E. Pondoland
Uzamba River, Natal
S.A. Coast
W.coast SA
Durban Bay
Umfolozi River, Natal
Umfolozi River, Natal
S. A. Coast
St. Lucia Bay, Natal
Saldanha Region
Age
?unspecified
Eocene
Holocene
Holocene
Quaternary
?unspecified
?unspecified
Miocene
Eocene
?unspecified
Quaternary
Quaternary
Cretaceous
Cretaceous
Cretaceous
Cretaceous
?unspecified
?unspecified
Recent
Miocene
Miocene
?unspecified
?unspecified
Holocene
207
Appendix 2.1: Environmental variables measured from the sediments of St Helena Bay and Robben Island.
Sample
Phi 5
Phi 4
Phi 3
Phi 2
Phi 1
RIA1
RIA2
RIA3
RIA4
RIA5
RIA6
RIB1
RIB2
RIB3
RIB4
RIB5
RIB6
RIC1
RIC2
RIC3
RIC4
RIC5
RIC6
RID1
RID2
RID3
RID4
RID5
RID6
RIE1
0.90
2.74
2.09
1.39
3.14
1.00
0.61
2.74
1.84
0.50
0.60
1.03
0.83
1.14
0.27
2.85
0.70
0.47
0.10
0.32
0.20
0.39
1.26
0.09
0.05
14.24
28.18
5.57
55.37
18.43
12.68
5.17
6.85
7.28
8.18
5.53
10.08
6.93
7.59
1.35
10.35
37.29
2.31
0.28
1.50
0.87
3.19
2.67
4.23
0.16
11.63
23.14
14.25
19.67
31.98
11.05
8.30
14.23
11.37
12.82
9.89
13.84
17.44
19.85
8.15
2.00
24.50
15.32
0.64
4.27
2.40
14.61
6.34
13.32
12.36
6.20
16.11
4.95
5.83
13.06
20.90
5.56
12.25
2.93
5.32
8.29
3.73
11.13
14.59
23.53
11.70
17.16
36.64
0.74
3.91
2.78
7.12
5.10
9.35
39.42
67.02
29.83
73.14
17.74
33.39
54.37
80.36
63.93
76.59
73.18
75.69
71.32
63.67
56.82
66.70
73.10
20.34
45.26
98.24
90.01
93.75
74.69
84.63
73.02
48.01
Mean
Grain
Size
1.30
2.08
1.11
2.59
1.96
1.33
0.83
1.19
1.09
1.11
0.96
1.19
1.19
1.27
0.91
0.94
2.30
1.21
0.51
0.56
0.53
1.01
0.59
1.01
1.10
Cd
(Kg/g)
Cr
(Kg/g)
Cu
(Kg/g)
Fe (Kg/g)
Pb
(Kg/g)
Zn
(Kg/g)
0.09
0.11
0.10
0.09
0.10
0.10
0.07
0.14
0.09
0.03
0.07
0.09
0.11
0.10
0.09
0.12
0.12
0.09
0.12
0.05
0.05
0.05
0.06
0.05
0.14
5.08
4.63
5.76
6.37
4.67
5.49
11.73
4.80
6.68
2.55
6.56
9.51
4.32
7.45
4.57
7.55
5.08
4.07
4.29
4.79
6.15
4.49
10.73
3.90
2.56
4.74
2.80
2.59
4.74
3.18
5.64
3.91
4.67
4.05
1.90
3.32
4.97
4.51
2.96
2.22
8.29
2.56
2.67
7.01
6.73
14.48
2.79
13.25
3.70
1.08
1956.08
2288.38
1942.11
2418.54
1953.61
1665.30
1989.20
2209.22
2626.14
924.74
2098.69
2510.36
1384.65
1814.97
1205.48
2370.64
1592.70
1195.03
1714.69
1752.67
1787.73
1689.47
7385.28
1747.25
633.82
1.79
2.62
3.96
2.85
2.80
1.93
7.74
5.99
6.27
2.56
5.85
6.78
8.17
6.56
3.99
8.69
3.23
5.50
9.60
5.06
5.19
3.90
26.18
59.15
3.04
12.28
12.69
10.31
20.96
14.69
8.79
11.59
12.66
10.26
2.23
8.98
15.11
15.73
10.33
7.31
18.58
8.93
29.71
11.50
10.55
14.23
5.15
15.13
6.42
7.83
208
Appendix 2.1: Environmental variables measured from the sediments of St Helena Bay and Robben Island.
Sample
Phi 5
Phi 4
Phi 3
Phi 2
Phi 1
RIE2
RIE3
RIE4
RIE5
RIE6
RIF1
RIF2
RIF3
RIF4
RIF5
RIG1
RIG2
RIG3
RIG4
RIG5
RIG6
RIH1
RIH2
RIH3
RIH4
RIH5
RIH6
SPA1
SPA2
SPA3
0.05
0.11
0.06
0.09
0.03
0.08
0.65
0.40
0.51
0.17
0.05
0.05
0.11
0.13
0.05
0.03
0.28
0.65
0.77
0.15
0.12
0.13
15.07
91.29
0.76
0.25
0.29
0.14
0.30
0.11
0.42
2.97
1.79
3.88
0.29
0.14
0.48
0.59
0.84
0.17
0.21
0.67
2.97
2.23
0.55
0.73
1.00
34.02
103.53
10.77
13.80
11.75
10.00
11.70
19.34
3.43
12.69
4.96
13.72
2.54
1.89
6.15
4.91
6.33
2.95
5.14
1.80
12.69
3.34
1.39
2.05
1.69
85.99
140.24
36.52
36.21
37.89
33.66
36.34
35.27
18.32
15.74
9.87
33.45
17.55
26.19
47.38
36.84
39.91
35.19
43.46
18.01
15.74
16.63
12.03
17.55
11.36
21.35
11.60
21.99
49.68
49.96
56.13
51.57
45.25
77.75
67.95
82.98
48.43
79.46
71.72
45.94
57.54
52.80
61.65
51.16
79.24
67.94
77.02
85.87
79.56
85.82
16.13
4.14
29.77
Mean
Grain
Size
1.09
1.07
1.00
1.06
1.22
0.73
1.00
0.63
1.18
0.70
0.80
1.08
0.96
1.01
0.90
1.02
0.70
1.00
0.76
0.58
0.69
0.58
2.58
3.29
1.78
Cd
(Kg/g)
Cr
(Kg/g)
Cu
(Kg/g)
Fe (Kg/g)
Pb
(Kg/g)
Zn
(Kg/g)
0.07
0.06
0.07
0.07
0.05
0.06
0.03
0.06
0.13
0.02
0.02
0.01
0.02
0.01
0.01
0.02
0.03
0.01
0.03
0.03
0.02
0.02
0.42
0.35
0.29
2.44
2.78
2.21
2.54
0.98
5.11
1.38
3.73
3.51
4.96
2.48
0.65
2.59
1.05
1.84
2.18
3.29
1.79
3.22
2.78
2.00
2.50
9.61
10.02
5.56
0.81
0.49
0.70
1.00
0.01
1.94
0.01
1.64
1.11
3.20
1.19
0.21
0.73
0.68
1.45
1.16
2.95
0.59
1.46
0.95
0.92
1.01
1.80
1.68
1.69
793.58
1085.42
728.42
716.90
410.07
986.15
305.95
1148.38
969.22
482.13
751.18
312.26
996.10
620.17
973.27
1126.16
1811.27
872.62
845.06
714.59
664.45
820.05
1180.80
1393.37
1206.38
3.11
3.40
1.13
3.09
0.32
7.97
0.55
6.94
4.05
3.46
2.27
0.68
9.39
1.11
3.37
2.44
4.01
3.02
4.79
3.22
2.45
2.47
1.29
1.41
0.54
10.58
4.22
3.30
3.93
2.90
3.38
1.34
3.56
12.67
0.75
0.60
1.80
4.79
1.14
1.68
2.66
30.55
0.80
2.92
1.42
1.15
4.36
6.15
3.62
4.84
209
Appendix 2.1: Environmental variables measured from the sediments of St Helena Bay and Robben Island.
Sample
Phi 5
Phi 4
Phi 3
Phi 2
Phi 1
SPA4
SPA5
SPA6
SPB1
SPB2
SPB3
SPB4
SPB5
SPB6
SPC1
SPC2
SPC3
SPC4
SPC5
SPC6
SHA1
SHA2
SHA3
SHA4
SHA5
SHA6
SHB1
SHB2
SHB3
SHB5
1.67
1.60
0.15
1.45
1.00
0.39
2.91
0.80
0.91
1.24
1.48
1.27
1.43
2.95
1.77
3.80
2.12
0.12
7.04
0.03
0.12
0.05
0.05
1.24
0.17
12.48
12.07
8.60
43.20
18.30
20.65
18.37
20.43
22.76
23.95
34.90
34.78
35.90
12.23
12.80
15.57
24.36
15.99
15.70
7.06
19.33
14.88
6.89
13.31
1.21
32.76
40.91
30.21
56.38
30.24
41.18
34.43
29.65
47.09
39.83
38.07
40.25
37.30
21.14
25.56
25.29
31.27
42.22
42.79
44.12
35.99
43.31
32.13
40.09
1.82
7.90
11.91
7.06
57.98
5.10
9.97
8.77
4.43
8.46
15.78
9.69
14.67
7.56
6.85
12.13
6.81
9.62
17.82
27.06
41.20
9.13
12.76
25.51
22.25
4.81
2.10
3.40
15.58
35.68
4.87
27.56
9.80
3.63
6.67
14.70
14.68
8.03
7.96
9.14
9.25
5.81
9.14
23.61
1.50
7.58
0.52
0.54
2.84
6.10
26.46
Mean
Grain
Size
2.62
2.45
1.96
2.08
2.70
2.04
2.43
2.78
2.62
2.29
2.45
2.59
2.76
2.32
2.26
2.59
2.51
1.96
2.47
2.01
2.71
2.54
2.12
2.25
0.79
Cd
(Kg/g)
Cr
(Kg/g)
Cu
(Kg/g)
Fe (Kg/g)
Pb
(Kg/g)
Zn
(Kg/g)
0.30
1.04
0.32
0.39
0.02
0.02
0.58
0.49
0.58
0.84
0.77
0.28
0.23
0.72
0.29
0.28
0.31
0.26
0.27
0.28
0.30
0.69
1.46
1.15
0.49
8.01
21.72
5.61
8.25
9.31
5.08
13.66
10.47
10.44
11.32
10.78
5.72
4.23
13.50
6.59
9.08
9.64
5.89
7.05
8.20
8.01
30.49
46.93
29.85
7.46
1.27
8.78
1.82
1.43
2.44
0.21
2.23
1.70
1.60
3.76
3.70
0.59
0.32
4.45
1.87
0.62
1.78
0.89
0.44
1.33
0.67
24.50
23.47
24.37
1.90
969.35
4532.30
1199.05
1222.43
1107.50
603.20
1812.39
1450.39
1084.70
1427.74
2060.97
534.90
474.04
3282.86
921.86
307.29
1337.49
668.75
334.37
1003.12
501.56
7412.97
7265.86
9120.51
1115.11
0.76
4.39
0.14
1.12
2.12
0.43
2.29
1.42
1.57
2.76
1.86
0.17
0.52
5.71
0.43
1.39
0.53
5.63
3.83
2.51
3.62
12.03
13.78
14.96
2.14
2.64
23.45
3.30
5.33
6.94
1.65
8.06
5.11
7.27
14.68
16.06
2.17
1.67
16.87
3.47
1.16
23.55
11.77
5.89
17.66
8.83
79.67
168.98
145.54
7.24
210
Appendix 2.1: Environmental variables measured from the sediments of St Helena Bay and Robben Island.
Sample
Phi 5
Phi 4
Phi 3
Phi 2
Phi 1
SHB6
SHC1
SHC2
SHC3
SHC4
SHC5
SHC6
SHD2
SHD3
SHD4
SHD5
SHE1
SHE2
SHE3
SHE4
SHE5
SHE6
SHF1
SHF2
SHF3
SHF4
SHF5
SHF6
SHG1
SHG2
0.53
1.53
1.90
1.33
1.09
15.36
6.58
7.44
15.04
11.84
16.37
12.11
0.22
0.12
0.12
0.22
0.33
0.20
2.62
0.43
0.37
1.20
0.13
0.96
0.95
16.49
6.74
8.87
10.96
8.85
96.44
17.68
44.41
27.32
23.52
14.92
37.38
16.29
5.71
0.81
0.57
0.82
4.84
17.40
0.60
1.28
1.09
4.47
1.62
4.41
39.66
8.42
9.68
10.19
13.96
29.22
10.54
22.14
8.72
10.59
12.69
15.65
16.05
7.70
0.69
7.74
1.16
6.67
11.00
1.03
1.03
1.86
1.20
2.02
3.02
13.40
10.02
9.41
12.76
10.08
10.61
6.22
10.84
3.62
4.46
5.78
6.92
16.28
7.74
0.70
1.07
1.92
5.54
12.26
2.41
2.37
3.70
3.38
4.64
4.79
28.67
28.89
21.24
15.28
24.11
3.91
2.49
4.60
1.22
1.20
5.23
3.11
46.72
76.76
1.81
7.27
5.15
27.54
17.16
6.07
4.70
70.00
50.50
29.91
29.72
Mean
Grain
Size
1.94
1.40
1.71
1.90
1.79
3.20
2.95
2.97
3.47
3.32
3.11
3.15
1.49
0.85
1.68
1.71
1.30
1.25
2.08
1.17
1.49
0.56
0.59
0.84
1.15
Cd
(Kg/g)
Cr
(Kg/g)
Cu
(Kg/g)
Fe (Kg/g)
Pb
(Kg/g)
Zn
(Kg/g)
0.70
1.57
0.83
1.27
1.20
0.79
0.97
1.34
1.41
1.58
0.72
0.88
0.47
0.50
0.71
0.61
1.26
1.27
2.32
2.11
0.14
0.51
0.53
0.64
0.27
9.91
24.29
14.30
14.29
21.26
9.93
11.07
7.39
19.16
17.09
6.14
23.30
8.33
12.10
21.03
17.88
10.70
13.71
17.13
16.63
2.26
5.42
9.04
8.69
7.13
23.96
31.68
8.94
10.04
20.65
8.38
11.51
188.91
32.07
33.94
5.96
55.63
30.28
29.82
26.00
33.54
23.05
11.66
23.72
17.12
11.36
4.24
13.45
28.36
4.33
6433.32
3309.33
1940.32
2546.59
4186.89
1667.48
2124.21
1975.73
4849.83
6306.29
2441.97
8211.21
2486.53
2501.07
6958.63
8373.69
7956.32
5573.26
5397.32
3246.94
829.81
1930.85
4353.67
5301.85
2071.69
6.57
9.16
5.59
6.17
10.18
4.00
4.47
27.17
8.32
6.90
1.96
12.09
9.11
7.92
10.47
12.13
15.83
11.59
10.91
11.55
1.85
5.59
10.46
14.02
3.37
78.96
84.29
39.18
66.16
82.45
37.93
51.74
143.70
153.59
128.26
59.86
160.96
56.94
62.32
85.13
110.01
54.45
69.48
93.60
87.51
16.43
20.88
75.94
93.68
16.50
211
Appendix 2.1: Environmental variables measured from the sediments of St Helena Bay and Robben Island.
Sample
Phi 5
Phi 4
Phi 3
Phi 2
Phi 1
SHG3
SHG4
SHG5
SHG6
SHH1
SHH2
SHH3
SHH4
SHH5
SHI1
SHI2
SHI3
SHI4
SHI5
SHI6
1.09
1.17
4.48
4.74
0.39
0.56
2.07
1.24
0.70
0.31
3.18
0.65
1.22
3.83
0.86
10.83
9.47
5.06
10.81
2.66
9.66
8.08
8.65
97.96
3.22
1.35
5.28
23.29
17.84
0.98
33.06
7.97
5.12
11.29
11.77
15.37
14.10
30.33
7.74
4.19
1.96
5.89
10.02
31.57
17.33
24.44
7.34
6.14
10.04
4.20
16.05
11.37
28.52
99.93
3.89
2.38
5.85
28.11
29.24
32.72
18.71
71.58
6.80
43.27
68.22
8.40
36.16
84.07
106.94
20.52
4.03
13.64
45.84
17.21
38.73
Mean
Grain
Size
1.91
1.09
2.28
1.49
0.97
2.07
1.41
1.24
1.82
1.22
2.29
1.63
1.65
2.12
1.28
Cd
(Kg/g)
Cr
(Kg/g)
Cu
(Kg/g)
Fe (Kg/g)
Pb
(Kg/g)
Zn
(Kg/g)
0.32
0.27
0.39
0.16
0.45
0.68
1.06
0.60
0.45
0.40
0.55
0.50
0.35
0.46
0.40
25.44
15.00
13.56
6.01
6.04
8.12
2.96
2.83
4.99
2.90
5.02
5.14
5.79
5.21
2.93
43.99
44.88
205.90
3.94
2.48
31.10
4.61
4.98
2.60
2.54
4.13
3.27
3.86
3.96
4.07
8758.59
5439.46
10439.42
2417.33
1617.50
6282.53
733.97
1272.07
1742.24
1081.12
1811.33
1441.35
1393.05
1375.63
1475.36
19.81
23.31
27.10
3.48
3.40
10.70
3.84
4.95
2.86
2.32
2.69
2.97
2.59
2.92
1.90
164.61
157.47
189.14
18.33
14.44
112.49
16.05
14.18
12.68
9.74
21.12
14.38
20.36
15.83
14.44
212
Appendix 3.1: Abundance of live foraminifera per species in both Robben Island and St
Helena Bay
SPECIES
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
%
'
)
% &
'
elongated
& '
&
%
&
&
#
(
(
RIA1
RIA2
RIA3
RIA4
RIA5
RIA6
RIB1
RIB2
RIB3
RIB4
RIB5
0
2
0
0
0
0
1
1
0
0
2
40
1
0
0
0
10
3
0
0
0
0
0
0
9
1
1
0
0
0
0
3
3
0
2
3
2
1
0
0
3
37
0
0
0
0
17
10
4
0
1
0
0
0
2
0
0
2
0
0
0
5
1
0
4
2
0
1
0
0
0
40
0
0
0
0
7
10
10
0
2
1
0
0
3
1
0
0
0
0
0
20
0
0
0
3
3
1
0
0
1
24
0
1
2
2
6
8
4
1
0
0
0
0
5
0
0
0
0
0
0
1
0
0
0
2
0
0
0
0
2
11
0
0
0
0
10
2
2
0
0
0
0
0
2
0
0
0
0
0
0
4
1
0
0
0
1
0
0
0
2
7
0
0
0
0
7
4
3
0
0
0
0
0
7
1
0
0
0
0
0
6
0
0
0
1
1
0
0
0
4
35
0
0
0
0
10
1
1
0
0
0
0
0
11
0
0
0
0
0
0
11
0
0
3
0
1
4
0
0
2
13
0
0
0
0
13
5
4
0
0
0
0
1
9
8
1
0
0
0
0
5
0
0
2
1
1
0
0
0
0
31
1
0
0
0
22
10
1
0
0
0
0
1
3
3
0
0
0
0
0
5
1
0
0
4
0
3
0
0
5
56
0
0
0
0
20
0
2
0
0
0
0
0
3
1
0
0
0
0
0
22
3
0
1
5
0
6
0
0
5
34
0
0
0
0
12
6
3
0
0
0
0
1
4
2
0
0
0
2
0
7
0
0
0
2
8
0
0
0
4
35
0
0
0
0
18
7
1
0
0
0
0
0
9
7
0
1
0
2
5
1
0
0
0
1
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
2
0
0
0
0
0
0
0
2
0
0
0
0
1
0
0
1
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
1
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
1
2
1
1
0
3
0
0
0
3
0
0
213
RIB6
Appendix 3.1: Abundance of live foraminifera per species in both Robben Island and St
Helena Bay
SPECIES
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
%
'
)
% &
'
elongated
& '
&
%
&
&
#
(
(
RIC1
RIC2
RIC3
RIC4
RIC5
RIC6
RID1
RID2
RID3
RID4
RID5
RID6
0
3
1
0
0
0
2
4
0
0
0
16
1
2
0
0
11
2
6
0
0
0
0
0
2
2
0
0
0
0
0
7
2
0
2
7
0
8
0
0
5
34
0
0
2
0
22
16
13
0
0
1
0
1
11
1
0
3
0
0
0
14
0
0
0
0
0
2
0
0
0
28
3
0
0
1
21
8
11
0
0
4
0
4
4
2
0
1
0
0
0
10
5
0
0
6
3
13
0
0
13
24
3
0
0
0
21
17
14
0
0
0
0
5
6
2
0
0
0
0
0
5
0
0
0
1
3
0
0
0
3
7
0
0
0
0
19
4
3
0
0
0
0
0
4
1
0
0
0
4
0
3
0
0
0
3
4
5
0
0
1
28
0
1
1
0
39
8
6
0
0
0
0
0
14
1
0
0
0
5
0
0
0
0
0
0
0
21
0
0
0
14
0
0
0
0
3
0
0
0
0
0
0
0
25
2
0
1
0
0
0
4
0
0
0
0
0
10
0
0
1
34
0
0
1
0
11
6
9
0
0
0
0
0
13
12
0
2
0
0
0
9
0
0
0
0
0
0
0
0
1
28
0
0
0
0
18
10
9
1
0
0
0
5
19
0
0
1
0
0
2
7
1
0
0
0
0
5
0
0
3
19
0
0
3
0
37
17
8
0
0
1
0
1
11
6
0
0
0
3
0
8
0
0
0
1
0
3
0
0
2
10
0
0
0
0
12
5
3
0
0
1
0
0
0
6
0
0
0
2
0
11
1
0
0
3
1
3
0
0
2
27
0
0
1
0
12
8
12
0
0
0
0
0
6
3
0
1
0
2
0
1
1
1
0
0
0
0
1
0
3
0
2
2
0
0
2
0
0
0
0
1
4
0
0
9
0
0
0
1
9
0
0
2
0
0
0
0
1
0
0
9
0
0
0
0
0
0
0
0
0
0
1
2
0
0
3
0
0
0
1
2
0
0
0
0
0
0
0
0
1
0
0
3
0
0
0
0
0
0
1
3
0
0
0
1
0
0
0
2
0
0
0
0
0
0
214
Appendix 3.1: Abundance of live foraminifera per species in both Robben Island and St
Helena Bay
SPECIES
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
%
'
)
% &
'
elongated
& '
&
%
&
&
#
(
(
RIE1
RIE2
RIE3
RIE4
RIE5
RIE6
RIF1
RIF2
RIF3
RIF4
RIF5
0
0
0
0
0
0
0
0
0
0
1
4
0
0
0
0
1
3
21
0
0
0
0
0
6
0
0
1
0
0
1
0
0
0
0
0
1
0
0
0
0
12
0
0
0
0
2
5
9
0
0
1
0
1
14
0
0
5
0
0
1
4
0
0
0
0
0
0
0
0
0
4
0
0
0
0
5
1
9
0
0
0
0
0
0
4
0
2
0
0
0
1
0
0
0
0
0
0
0
0
1
6
0
0
0
1
2
9
11
0
0
0
0
4
6
0
0
1
0
1
0
1
0
0
0
0
0
0
0
0
5
0
0
0
0
0
1
2
10
0
0
0
0
5
2
1
0
0
0
1
1
2
0
0
0
0
0
0
0
0
0
2
0
1
0
0
5
33
6
0
0
0
0
0
2
0
0
0
0
8
0
2
0
0
0
4
0
14
0
0
1
11
2
0
0
0
14
9
0
0
0
0
0
1
8
1
2
0
0
0
0
1
0
0
0
0
0
3
0
0
0
14
0
0
2
0
38
6
27
1
0
0
0
0
3
5
0
1
0
0
0
9
0
0
0
3
8
3
0
0
3
35
0
0
0
0
48
9
13
0
0
0
0
0
7
5
0
0
0
0
0
0
1
0
0
0
1
5
0
0
0
9
1
0
0
0
10
2
4
0
0
0
0
0
8
1
0
0
0
2
0
2
0
0
0
0
1
2
0
0
2
9
0
0
0
0
11
2
5
0
0
0
0
1
6
1
0
0
0
6
0
4
0
0
0
0
0
0
1
0
1
6
0
0
0
0
2
2
8
0
0
0
0
1
5
10
0
1
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
3
0
0
1
0
0
0
0
0
0
0
1
0
0
0
2
2
0
0
0
0
0
0
0
0
0
0
13
0
0
0
3
0
0
0
2
0
0
0
0
0
0
0
0
0
2
0
0
1
1
0
7
1
0
0
2
5
1
0
1
0
2
2
2
2
0
0
7
0
0
0
0
0
0
0
1
0
0
0
0
10
0
215
RIG1
Appendix 3.1: Abundance of live foraminifera per species in both Robben Island and St
Helena Bay
SPECIES
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
%
'
)
%
-
&
'
elongated
& '
&
%
&
&
#
(
(
RIG2
RIG3
RIG4
RIG5
RIG6
RIH1
RIH2
RIH3
RIH4
RIH5
RIH6
3
2
0
0
0
0
0
0
0
0
0
8
0
1
0
0
7
13
25
0
0
0
0
3
18
3
0
0
0
0
0
2
1
0
0
0
0
0
0
0
2
32
2
0
0
0
34
8
29
0
0
0
0
13
21
2
0
3
0
0
0
5
0
0
0
1
2
1
0
0
0
22
0
0
0
0
15
6
24
0
0
0
0
5
16
0
0
0
0
5
0
0
1
0
0
0
0
0
0
0
0
8
0
0
0
0
13
12
10
0
0
0
0
1
4
2
0
0
0
6
0
1
0
0
0
0
0
0
0
0
0
5
0
1
0
0
5
1
2
0
0
0
0
0
3
0
0
3
0
3
0
8
5
0
0
2
3
2
1
0
1
20
0
0
1
0
10
4
11
1
0
0
0
2
11
9
0
0
0
0
1
2
0
0
0
1
0
1
0
0
0
15
1
0
0
0
15
8
18
0
0
0
0
13
11
0
0
0
0
0
0
24
0
0
3
0
8
3
0
0
1
32
0
0
0
0
7
18
6
0
0
1
0
4
18
16
0
0
0
0
1
27
0
0
0
3
4
6
0
0
1
29
0
1
0
0
37
6
10
0
1
6
6
8
6
8
0
0
0
5
1
4
1
0
0
2
0
4
0
0
0
21
0
1
0
0
19
7
13
0
0
0
0
2
16
1
0
0
0
4
1
14
0
0
0
4
0
1
0
0
0
25
0
1
1
0
11
0
5
0
0
1
0
1
23
3
0
1
0
0
25
0
0
0
2
4
0
0
2
1
111
10
8
2
1
0
16
0
0
0
0
0
0
10
11
1
2
0
6
0
0
2
0
4
0
8
14
0
1
1
0
0
0
4
38
1
0
5
5
0
1
4
13
0
0
4
0
0
0
1
8
0
0
0
0
0
1
0
6
0
2
0
0
0
0
0
4
0
0
5
0
0
0
0
15
2
6
0
0
0
1
1
2
0
1
5
0
1
1
7
7
1
0
2
0
0
0
5
5
0
0
4
0
0
0
0
0
0
0
0
0
0
0
0
0
0
216
SPA1
Appendix 3.1: Abundance of live foraminifera per species in both Robben Island and St
Helena Bay
SPECIES
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
%
'
)
%
-
&
'
elongated
& '
&
%
&
&
#
(
(
SPA2
SPA3
SPA4
SPA5
SPA6
SPB1
SPB2
SPB3
SPB4
SPB5
SPB6
41
1
16
1
0
0
0
0
9
0
0
12
10
0
0
0
2
2
0
0
0
1
0
4
7
1
0
0
0
0
35
4
2
0
3
4
0
0
2
0
0
1
21
3
0
0
10
0
1
0
0
4
0
10
3
0
1
0
0
0
28
6
8
0
0
3
2
0
1
0
1
7
8
0
3
1
12
2
0
1
1
4
0
7
6
0
0
0
0
0
22
6
0
8
0
0
1
0
3
0
16
59
7
2
0
0
8
1
0
0
0
0
0
21
1
0
0
0
0
0
22
6
0
8
0
0
1
0
3
0
16
59
7
2
0
0
8
1
0
0
0
0
0
21
1
0
0
0
0
0
28
1
6
1
1
2
0
0
1
0
9
11
10
0
0
0
9
0
0
0
0
0
0
3
9
0
2
0
0
0
50
1
1
0
0
0
0
0
2
0
8
3
8
0
0
0
2
0
0
0
0
1
0
3
1
0
0
0
0
0
48
4
5
2
1
2
1
0
6
1
11
4
16
0
0
0
15
0
0
1
0
0
0
4
15
0
2
0
0
0
66
8
9
0
1
3
3
0
2
0
7
56
6
3
2
1
21
0
0
1
0
3
0
3
1
0
3
0
0
0
60
8
5
2
0
0
0
0
2
0
18
50
11
1
0
0
15
0
0
0
0
3
0
4
2
0
1
0
0
0
62
9
3
0
3
3
0
0
2
0
7
46
11
0
0
0
0
0
0
1
1
1
0
7
0
0
0
0
0
0
44
0
8
1
3
3
1
0
0
4
16
1
5
0
8
0
22
0
1
0
0
4
1
8
20
0
0
0
4
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
217
SPC1
Appendix 3.1: Abundance of live foraminifera per species in both Robben Island and St
Helena Bay
SPECIES
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
%
'
)
%
-
&
'
elongated
& '
&
%
&
&
#
(
(
SPC2
SPC3
SPC4
SPC5
SPC6
SHA1
SHA2
SHA3
SHA4
SHA5
SHA6
38
10
5
1
1
4
0
0
0
0
4
2
5
10
0
0
20
0
0
0
0
1
0
1
6
0
2
0
0
0
10
1
10
1
1
4
0
0
0
1
6
5
3
0
2
0
6
0
0
0
0
0
0
4
3
0
0
0
0
0
32
6
6
0
5
0
0
0
2
0
2
33
3
0
0
1
12
0
0
1
0
1
1
0
4
3
0
0
0
0
26
21
5
21
0
2
0
0
1
1
15
42
3
5
2
0
15
0
0
0
0
0
1
3
2
0
0
0
0
0
64
15
7
15
0
0
3
0
0
0
18
22
9
1
0
0
10
0
0
0
0
2
0
8
1
0
0
0
0
0
2
1
0
0
0
0
0
0
0
1
0
0
0
0
0
0
1
0
0
0
0
0
0
0
2
0
0
0
0
0
5
0
3
0
1
1
0
0
0
2
2
3
3
0
0
0
2
0
0
0
0
1
0
1
5
0
2
0
0
0
6
1
1
0
1
0
0
0
1
3
2
0
1
0
0
0
5
0
0
0
0
0
0
1
1
0
1
0
0
0
10
1
9
0
2
1
1
0
3
0
4
12
1
0
1
1
5
0
0
1
1
2
0
0
3
0
1
0
0
0
9
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
2
0
2
0
0
1
0
0
2
5
5
3
1
0
1
5
0
0
0
0
0
1
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
218
Appendix 3.1: Abundance of live foraminifera per species in both Robben Island and St
Helena Bay
SPECIES
Elongated
Bolivinids
perforated
bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
%
'
)
% &
'
elongated
& '
&
%
&
&
#
(
(
SHB1
SHB2
SHB3
SHB4
SHB5
SHB6
SHC1
SHC2
SHC3
SHC4
SHC5
SHC6
24
18
17
57
28
20
20
5
14
15
15
7
0
12
0
2
3
9
14
19
4
0
0
3
4
8
2
0
2
15
14
2
2
2
11
8
0
4
5
1
0
4
1
3
0
0
0
0
0
9
0
0
0
0
0
0
0
14
2
1
0
0
0
0
0
0
0
0
0
0
1
12
1
0
0
0
1
1
0
0
0
0
0
0
0
0
0
0
0
0
2
0
8
3
0
0
1
0
0
0
0
0
0
2
0
0
0
0
0
0
0
4
2
0
0
0
0
0
0
1
0
0
2
0
0
15
0
2
3
0
9
0
0
1
0
4
0
0
8
0
1
0
0
0
0
0
0
0
0
0
0
1
2
1
0
0
0
0
0
0
0
0
0
1
0
2
4
0
0
0
0
0
0
0
0
0
0
0
1
2
1
1
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
2
0
0
0
0
1
0
0
0
1
0
0
0
0
0
0
0
0
0
6
0
0
0
0
0
0
0
0
0
0
0
0
2
2
0
0
0
0
0
0
0
0
0
0
0
0
10
2
0
0
0
0
0
1
9
2
0
1
0
2
2
3
0
1
0
3
0
0
0
0
0
0
0
5
3
0
0
0
0
0
12
4
2
0
2
0
0
3
0
0
0
0
0
0
0
0
0
0
0
0
22
2
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
7
1
0
0
0
0
0
3
0
0
0
0
0
3
15
0
0
0
0
0
0
0
0
0
0
0
0
5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
219
Appendix 3.1: Abundance of live foraminifera per species in both Robben Island and St
Helena Bay
SPECIES
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
%
'
)
% &
'
elongated
& '
&
%
&
&
#
(
(
SHD2
SHD3
SHD4
SHD5
SHD6
SHE1
SHE2
SHE3
SHE4
SHE5
SHE6
0
1
1
0
0
0
0
0
0
0
0
0
0
1
2
0
0
0
0
0
0
0
0
0
13
1
0
0
0
0
3
3
2
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
1
1
0
0
0
0
1
5
3
0
0
0
2
0
1
0
0
1
1
0
1
0
1
0
0
1
0
1
0
1
0
2
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
1
0
0
0
0
0
14
0
1
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
7
2
0
0
0
3
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
3
2
0
0
0
0
0
0
0
0
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
7
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0
0
0
0
6
0
2
3
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
220
SHF1
Appendix 3.1: Abundance of live foraminifera per species in both Robben Island and St
Helena Bay
SPECIES
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
%
'
)
% &
'
elongated
& '
&
%
&
&
#
(
(
SHF2
SHF3
SHF4
SHF5
SHF6
SHG1
SHG2
SHG3
SHG4
SHG5
SHG6
28
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
23
5
8
2
3
4
4
0
1
0
1
5
1
0
0
0
1
0
0
0
0
0
0
0
0
0
1
0
0
0
44
6
9
0
1
0
0
0
8
0
3
4
2
0
0
0
1
0
0
0
0
0
0
0
0
7
0
0
0
0
10
2
4
0
0
0
0
0
1
0
2
1
0
1
0
0
0
0
0
0
0
1
0
0
4
1
0
0
0
0
1
3
4
0
0
0
0
0
0
0
0
4
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
29
3
11
0
3
0
0
0
0
0
0
0
2
1
1
0
0
0
0
0
0
0
0
0
6
1
0
0
0
0
42
5
5
0
0
0
0
0
2
0
0
7
1
0
0
0
0
0
0
0
0
0
0
0
0
3
0
0
0
0
29
3
8
0
0
0
1
0
0
1
2
3
1
0
0
0
2
1
0
0
1
3
0
0
14
1
1
0
0
0
73
5
4
0
3
0
0
0
1
0
0
3
4
0
0
2
0
0
0
0
0
0
0
0
1
2
0
0
0
0
13
3
1
0
0
0
0
0
1
0
0
3
1
1
0
0
0
0
0
1
0
0
0
0
3
1
0
0
0
0
19
2
9
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
6
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
221
Appendix 3.1: Abundance of live foraminifera per species in both Robben Island and St
Helena Bay
SPECIES
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
%
'
)
% &
'
elongated
& '
&
%
&
&
#
(
(
SHH1
SHH2
SHH3
SHH4
SHH5
SHI1
SHI2
SHI3
SHI4
SHI5
SHI6
4
0
1
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
28
4
12
0
0
1
0
0
2
0
0
0
2
1
0
0
0
0
0
0
0
0
0
0
3
2
2
0
0
0
65
6
10
0
2
2
0
0
3
1
2
0
0
0
0
0
3
0
0
0
0
0
0
0
0
4
1
0
0
0
11
9
15
9
0
1
0
0
2
0
0
6
1
0
0
0
1
0
0
0
0
0
0
0
0
3
0
0
0
0
9
1
1
1
0
0
0
0
1
0
1
0
2
0
0
0
0
0
0
0
0
1
0
0
1
1
0
0
0
0
27
4
20
2
0
3
0
0
0
1
3
0
3
0
0
0
0
0
0
0
0
4
0
0
1
0
0
0
0
0
8
0
0
0
0
0
0
0
0
1
0
0
7
0
0
0
0
0
0
0
0
0
0
4
0
0
0
0
0
0
7
3
9
0
0
1
0
0
0
0
2
4
0
0
0
1
1
0
0
0
0
1
3
0
3
1
1
0
0
0
15
3
11
0
0
0
0
0
0
0
1
1
0
0
0
0
0
0
0
0
1
0
0
0
0
0
1
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
6
1
1
0
1
0
0
0
0
0
4
0
3
0
0
0
3
0
0
4
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
222
Appendix 3.2: The abundance of each species in the dead assemblages
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
sp A
%
'
)
%
&
&
&
&
#
'
%
SPA1
SPA2
SPA3
SPA4
SPA5
SPA6
SPB1
SPB2
11
10
18
11
7
2
9
14
1
1
10
2
6
12
6
34
2
3
0
1
6
0
1
0
1
2
1
8
1
8
11
13
4
0
0
0
0
0
0
2
0
0
17
4
0
0
3
0
0
0
4
0
0
2
0
0
0
0
0
0
0
0
0
0
1
5
0
0
4
2
1
3
1
0
0
2
0
0
1
0
15
15
10
11
13
10
14
14
18
142
40
7
47
61
17
132
5
7
6
0
4
1
5
11
1
0
1
6
0
0
0
1
3
2
5
14
0
0
6
1
0
0
3
0
0
0
0
0
9
13
26
21
11
14
29
10
2
0
2
8
0
2
1
0
2
0
1
2
2
6
0
1
0
0
0
1
0
2
0
2
1
1
0
0
1
0
0
0
3
0
2
1
1
1
0
0
1
0
2
1
0
0
0
0
5
9
8
13
10
14
4
6
8
3
9
9
5
1
8
4
0
0
1
0
0
0
0
2
1
0
1
0
0
0
0
0
1
0
0
0
1
0
1
0
9
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
(
0
0
0
0
0
0
0
0
(
0
0
0
0
0
0
0
0
223
SPB3
SPB4
SPB5
SPB6
SPC1
SPC2
SPC3
SPC4
18
1
7
8
3
4
20
4
5
6
26
9
16
15
5
14
0
0
0
0
1
1
2
0
2
2
2
6
2
6
8
11
1
2
0
0
0
0
0
0
3
5
0
0
11
9
5
2
3
3
0
1
0
1
3
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
2
0
0
0
0
0
0
0
10
3
10
11
7
13
2
4
17
16
51
91
1
4
2
14
3
3
5
1
0
4
0
0
3
2
3
0
1
0
3
2
9
4
7
6
3
6
5
2
0
1
0
4
2
0
0
1
27
1
10
0
6
16
6
4
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
4
0
2
0
1
0
0
3
1
0
0
3
1
0
0
0
0
0
1
0
0
2
0
0
2
0
0
1
0
0
0
0
8
1
1
3
2
0
1
2
13
0
2
0
1
2
6
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
(
0
0
0
0
0
0
0
0
0
(
0
0
0
0
0
0
0
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
sp A
%
'
)
%
&
&
&
&
#
'
%
224
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
sp A
%
'
)
%
&
&
&
&
#
(
(
'
%
SPC5
SPC6
SHA1
SHA2
SHA3
SHA4
SHA5
SHA6
6
4
40
30
2
19
25
9
22
24
4
3
0
2
0
11
22
24
4
0
0
0
0
11
11
8
2
5
1
4
3
3
3
3
0
1
0
2
0
0
1
0
0
4
0
1
1
0
3
3
1
0
0
1
0
0
0
0
0
0
0
0
0
0
0
2
0
0
1
4
3
0
0
0
3
0
2
0
0
0
5
8
8
44
18
25
19
26
22
69
11
19
15
61
86
84
0
2
3
3
4
6
6
4
1
1
7
0
0
3
0
1
9
7
9
4
0
5
2
1
0
0
0
0
0
0
0
0
16
4
19
49
19
17
12
28
1
0
0
0
0
0
0
0
0
1
1
0
1
0
0
0
0
0
0
2
0
1
3
0
0
1
0
0
0
3
0
0
0
0
2
6
0
0
3
1
0
0
0
2
0
0
1
0
0
2
0
1
1
2
0
1
1
0
11
16
4
10
0
0
0
0
0
0
1
0
0
0
0
0
0
0
1
0
2
0
1
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
225
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
sp A
%
'
)
%
&
&
&
&
#
(
(
'
%
SHB1
SHB2
SHB3
SHB4
SHB5
SHB6
SHC1
SHC2
36
10
12
13
58
5
20
11
3
18
6
20
25
13
27
54
2
0
0
0
0
0
2
0
20
4
11
15
17
6
11
15
4
0
3
0
4
0
1
3
19
0
10
4
4
0
32
0
2
0
7
0
0
0
6
3
0
0
0
0
0
0
0
0
4
0
0
0
3
0
0
0
1
0
0
0
0
0
0
0
18
4
4
15
12
4
4
10
28
46
4
28
42
9
3
67
1
2
1
1
1
2
2
1
0
0
1
7
6
0
7
3
2
0
7
11
22
0
9
5
1
1
0
0
2
0
1
1
21
0
1
31
8
7
6
0
0
1
0
0
0
0
1
0
0
0
0
0
0
0
0
0
1
1
0
1
2
0
0
3
1
0
0
1
1
0
0
1
0
0
0
1
1
0
0
2
0
0
0
0
1
0
0
1
0
0
0
0
1
0
0
1
10
1
3
5
3
0
10
9
0
0
0
0
0
0
0
0
2
0
0
0
0
0
2
0
2
0
1
0
1
0
2
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
226
Elongated Bolivinids
perforated bolivinids
SHC3
SHC4
SHC5
SHC6
SHD2
SHD3
SHD4
SHD5
16
6
10
8
1
3
2
2
19
30
60
78
18
4
26
18
1
0
0
0
0
0
0
0
12
9
29
10
1
8
19
7
3
12
2
3
8
0
4
0
23
7
1
0
12
14
14
2
4
5
5
1
10
0
4
1
0
0
0
0
0
0
0
0
0
1
1
1
1
0
1
0
1
0
1
0
0
0
0
1
6
5
20
16
4
4
12
9
7
26
51
58
6
6
7
7
0
0
3
4
0
0
0
3
4
6
7
3
4
1
0
0
12
12
15
7
12
5
10
4
1
2
1
1
1
0
0
1
10
10
7
2
6
3
11
0
1
2
1
1
0
0
0
0
1
0
0
0
1
0
0
0
1
1
0
0
0
1
0
0
0
0
0
0
1
0
0
0
0
0
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
11
8
8
3
13
6
0
0
3
1
0
1
2
0
7
0
0
0
0
1
0
0
0
0
2
1
1
3
0
1
0
0
0
0
0
0
3
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
&
0
0
0
0
0
0
0
0
&
#
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
(
0
0
0
0
0
0
0
0
(
0
0
0
0
0
0
0
0
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
sp A
%
'
)
%
&
&
'
%
227
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
sp A
%
'
)
%
&
&
&
&
#
(
(
'
%
SHD6
SHE1
SHE2
SHE3
SHE4
SHE5
SHE6
SHF1
3
2
16
8
2
6
6
4
5
0
1
1
4
1
2
6
0
0
1
0
0
1
2
1
1
0
0
2
1
2
2
7
0
0
3
0
0
0
1
7
0
0
1
0
0
0
0
5
0
1
0
0
1
0
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
1
0
0
0
0
1
1
0
0
1
3
0
3
28
0
0
0
1
2
10
1
0
0
0
0
0
3
1
0
0
0
1
0
2
0
4
4
6
0
5
0
2
0
6
8
1
0
0
0
0
1
0
0
0
0
4
0
0
1
0
3
1
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
1
0
0
0
0
1
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
3
0
0
1
0
0
0
1
0
0
3
0
2
0
0
0
0
0
0
0
0
0
1
0
1
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
228
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
sp A
%
'
)
%
&
&
&
&
#
(
(
'
%
SHF2
SHF3
SHF4
SHF5
SHF6
SHG1
SHG2
SHG3
12
17
27
16
20
38
54
17
52
28
60
22
48
16
47
18
6
4
0
0
3
3
0
0
40
19
23
15
20
16
45
12
2
3
4
6
5
4
0
3
0
26
3
2
0
20
0
20
1
5
1
3
0
9
2
4
0
0
0
0
0
0
0
0
1
0
1
0
1
1
0
0
0
2
1
0
0
0
0
0
18
2
33
10
4
15
7
5
54
9
32
20
40
21
96
16
1
2
3
0
3
3
3
0
3
10
1
2
6
4
3
1
5
18
3
6
16
10
5
9
0
0
0
0
0
2
0
0
1
4
0
0
1
19
0
25
0
0
1
0
0
1
0
0
0
0
0
0
0
0
0
1
2
0
0
0
0
2
0
1
0
0
0
0
1
1
2
0
0
0
0
1
1
1
1
1
0
0
1
0
0
0
0
1
0
0
0
0
0
0
0
1
6
0
0
3
3
6
3
9
0
1
4
0
0
0
0
1
0
1
0
0
0
0
0
2
0
0
0
1
1
1
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
229
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
sp A
%
'
)
%
&
&
&
&
#
(
(
'
%
SHG4
SHG5
SHG6
SHH1
SHH2
SHH3
SHH4
SHH5
11
23
39
6
6
11
40
19
28
27
55
5
16
20
36
32
0
0
0
0
4
1
36
32
11
10
21
9
42
12
43
23
3
1
1
1
3
1
5
0
1
0
0
2
28
22
4
4
5
1
1
6
9
8
6
5
0
0
0
0
0
0
0
0
3
1
3
0
0
0
5
0
0
1
0
3
2
1
0
2
27
13
20
1
6
3
9
11
44
81
79
0
7
13
38
23
1
2
2
0
2
0
3
5
2
3
4
0
1
0
4
7
6
5
8
10
7
4
12
13
0
0
4
0
0
0
0
1
0
5
6
0
10
8
0
3
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
32
1
0
2
1
0
0
0
0
1
1
0
0
0
0
0
0
2
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
6
0
7
2
2
8
8
0
0
0
5
7
3
0
0
0
0
0
1
2
0
0
0
1
0
2
0
1
1
0
0
0
1
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
230
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
sp A
%
'
)
%
&
&
&
&
#
(
(
'
%
SHI1
SHI2
SHI3
SHI4
SHI5
SHI6
RIA1
RIA2
11
32
5
30
26
39
0
0
26
47
23
23
44
23
33
10
6
6
0
0
0
0
4
2
41
32
39
19
23
24
0
0
13
3
7
4
10
9
0
2
28
0
12
4
0
2
14
11
1
0
1
4
2
5
5
14
0
0
0
0
0
0
5
3
1
0
1
4
4
0
0
0
2
0
0
3
3
0
0
0
0
18
8
32
27
12
11
9
0
100
17
107
78
98
96
62
2
0
0
7
20
10
0
0
0
2
4
5
11
1
0
3
0
8
22
11
25
3
0
6
0
0
2
2
2
2
0
3
0
4
15
3
6
12
7
6
0
0
1
0
1
0
12
45
0
0
0
0
0
0
3
5
0
2
2
4
0
2
0
2
0
0
1
2
1
4
0
1
0
0
0
0
1
1
0
2
0
0
1
0
1
0
0
0
0
4
0
0
0
1
2
0
0
0
9
0
0
0
4
1
0
0
1
1
0
0
0
0
0
0
0
2
1
0
1
1
0
0
0
0
0
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
2
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
231
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
sp A
%
'
)
%
&
&
&
&
#
(
(
'
%
RIA3
RIA4
RIA5
RIA6
RIB1
RIB2
RIB3
RIB4
3
1
1
1
0
0
0
0
33
48
21
43
43
25
24
29
4
8
6
1
4
0
2
5
0
0
0
0
0
0
0
0
1
2
1
3
1
3
6
0
0
0
6
5
13
6
13
2
9
11
7
9
13
8
23
0
0
1
1
0
1
0
0
7
0
0
0
0
6
0
0
0
0
0
0
0
0
0
0
0
1
4
12
4
10
8
4
10
65
36
37
52
61
59
59
57
0
0
0
0
2
0
0
3
3
7
3
3
3
4
5
4
1
5
3
7
7
2
2
4
1
5
1
0
1
0
2
0
9
17
11
29
11
19
16
16
13
20
18
25
13
16
15
5
13
8
16
15
1
13
8
7
0
1
2
0
0
2
1
0
0
0
4
0
0
5
0
0
1
0
3
4
0
0
0
2
0
0
0
0
0
0
0
0
4
1
1
0
1
2
0
1
2
5
1
5
0
4
1
2
0
0
2
0
0
9
4
1
0
0
5
0
0
1
3
1
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
1
0
1
0
0
0
0
0
1
2
2
1
4
2
3
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
4
0
3
1
1
0
1
1
0
1
0
2
0
0
0
0
0
0
0
0
232
RIB5
RIB6
RIC1
RIC2
RIC3
RIC4
RIC5
RIC6
0
2
0
0
0
0
0
0
21
21
23
7
20
5
28
14
3
4
3
0
1
3
2
3
0
0
0
0
0
0
0
0
3
5
4
8
1
0
6
2
7
6
11
7
5
1
14
7
7
6
5
2
4
2
2
4
2
3
4
8
8
0
11
2
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
5
4
8
11
6
10
5
10
26
36
74
23
44
18
31
41
0
0
0
0
2
0
0
2
7
4
2
0
2
2
2
3
0
6
7
5
2
0
9
4
0
4
5
2
1
0
0
8
9
8
21
11
18
12
32
26
10
9
13
15
5
3
13
14
4
9
4
22
20
3
16
14
3
1
1
1
1
5
0
0
0
0
1
1
0
0
0
3
0
1
1
0
1
0
3
1
0
0
1
0
0
0
0
0
1
1
1
0
0
2
1
1
3
2
9
0
0
0
6
4
3
0
1
0
2
0
1
1
2
0
1
2
1
0
1
2
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
3
1
0
0
0
1
4
0
3
1
16
0
2
1
3
0
0
0
5
0
0
0
1
0
&
0
1
0
0
0
0
0
0
#
0
2
1
0
1
0
0
4
4
0
1
8
3
1
4
0
0
0
4
7
2
5
4
1
2
0
0
2
0
0
0
0
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
sp A
%
'
)
%
&
&
&
(
(
'
%
233
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
sp A
%
'
)
%
&
&
&
&
#
(
(
'
%
RID1
RID2
RID3
RID4
RID5
RID6
RIE1
RIE2
0
0
0
1
0
0
0
0
9
1
20
17
6
18
3
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
2
2
0
1
2
6
1
0
0
0
3
6
7
4
0
4
5
4
2
0
2
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
6
2
4
3
3
3
0
1
36
39
47
44
20
42
13
7
0
1
1
0
0
1
0
2
0
3
0
3
3
2
0
1
3
4
1
6
6
2
0
0
0
0
0
2
0
0
0
0
2
5
17
14
8
9
0
1
3
2
6
18
10
7
1
6
0
4
11
16
5
10
8
14
0
1
1
2
0
0
1
1
0
0
0
0
0
0
0
0
1
3
1
3
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
2
7
4
6
3
1
3
3
14
2
2
1
0
3
1
0
0
4
0
0
0
0
1
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
2
0
0
0
1
2
1
2
3
1
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
2
0
0
0
1
0
1
2
0
0
0
1
2
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
234
RIE3
RIE4
RIE5
RIE6
RIF1
RIF2
RIF3
RIF4
0
0
0
0
0
0
1
0
5
4
2
1
12
49
19
11
0
1
1
0
1
0
3
3
0
0
0
0
0
0
0
0
0
0
0
0
1
4
0
2
0
1
0
0
3
0
4
0
1
2
0
0
2
0
7
1
0
0
0
0
14
2
3
7
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
4
0
4
0
9
3
2
7
0
1
39
23
20
33
0
1
1
0
0
0
0
0
0
0
0
1
0
3
4
4
4
0
1
0
1
12
2
3
0
0
0
0
2
2
2
1
2
1
0
4
17
17
19
35
6
5
0
4
12
10
6
4
11
12
7
8
3
19
11
25
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
2
1
0
0
0
0
1
3
3
0
0
0
0
0
0
0
0
0
4
2
0
2
2
2
3
0
1
0
1
7
5
1
15
3
0
1
0
5
0
5
3
1
0
0
0
2
1
4
2
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
2
3
0
0
0
3
0
0
1
4
4
6
2
3
0
0
0
0
0
1
0
2
&
0
0
0
0
0
0
0
0
#
0
0
0
0
2
4
2
3
0
2
0
0
0
3
0
2
0
0
0
1
5
3
4
7
0
0
0
0
0
0
0
0
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
sp A
%
'
)
%
&
&
&
(
(
'
%
235
RIF5
RIG1
RIG2
RIG3
RIG4
RIG5
RIG6
RIH1
0
0
1
0
0
0
0
0
2
6
4
6
21
3
3
16
0
0
0
0
1
0
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
1
2
0
2
3
0
0
0
3
1
0
4
6
0
1
0
0
0
0
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
6
1
0
2
3
1
0
3
17
5
15
21
30
8
2
27
1
0
1
0
0
0
0
0
0
0
0
2
6
3
0
1
1
1
0
1
2
1
0
4
0
0
1
1
2
0
0
0
6
7
6
3
11
5
1
5
1
8
4
1
4
3
0
15
13
14
20
23
24
4
4
18
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
4
2
0
0
0
0
0
0
0
0
0
0
0
0
2
6
6
9
10
2
1
4
2
0
3
7
4
1
0
4
0
9
0
0
1
0
0
5
0
0
0
0
1
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
1
0
0
0
3
2
1
1
2
2
0
3
0
0
0
0
0
0
0
0
3
0
4
1
0
0
0
0
0
0
2
0
2
0
0
0
2
0
0
2
0
1
1
1
(
2
10
35
29
19
2
7
11
(
0
1
1
0
2
0
0
0
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
sp A
%
'
)
%
&
&
&
&
#
'
%
236
Elongated Bolivinids
perforated bolivinids
Bolivinitidae
"
$
+
+
!
!
!
!
)
%
%
,
sp A
%
'
)
%
&
&
&
&
#
(
(
'
%
RIH2
RIH3
RIH4
RIH5
RIH6
0
0
0
0
0
8
12
39
17
31
0
0
0
0
0
0
0
0
0
0
0
3
2
0
0
3
1
9
3
7
0
5
9
0
5
1
3
3
0
0
0
0
0
0
0
0
0
0
0
0
6
3
3
0
5
30
17
23
27
27
0
0
0
0
1
1
4
4
2
4
1
2
5
3
8
0
1
1
1
1
7
1
4
3
13
9
4
5
7
3
8
6
15
9
9
0
0
0
0
0
0
0
0
0
0
0
4
3
2
0
0
0
3
0
0
2
3
1
0
0
1
1
3
1
5
0
0
1
4
9
0
1
0
3
0
1
0
0
0
0
0
0
0
0
0
0
0
0
2
8
8
2
1
2
14
0
0
0
0
0
0
0
0
0
0
0
1
2
2
0
5
2
0
1
6
19
3
3
4
3
1
1
0
0
0
237
Appendix 3.3 (a): Species Richness of foraminifera found in some studies similar to the present study with the location and a short description of
environmental conditions, the number and type of samples, depth where provided (N/A where no depth profiles were given).
Location of Study
Israel D Hadera (effluent from coal power station)
Israel D Haifa Bay (heavy metal contamination)
Israel D Plamahim (sewage)
Israel D Nitzanim (unpolluted)
Californian Margin (methane cold seeps)
Havstens Fjord, Sweden (Hypoxic)
Monterey Bay (methane seeps)
Vendeé, France (harbours)
Odiel estuary, Spain (polluted)
Gulf of Izmir, Aegean Sea
Naples Harbour, Italy
Osaka Bay, Japan (industrial, agricultural and domestic
waste)
Adriatic Sea, Italy (low pollutant and nutrient budget)
Bagnoli, Italy (industrial pollution)
Firth of Clyde, Scotland (organic pollution)
No. of Samples
Depth
17.5 – 24
m
2
6 – 12 m
7
20 – 50 m
4
20 – 50 m
450 – 600
2
m
19 samples over 3 months 12 – 40 m
906 –
15 over 3 years
1003 m
18 from 5 harbours
N/A
17
7 – 25 m
8
16
90 – top 20 cm of
sediment
1 x 84 cm core (does not
distinguish between live
& dead assemblages
42 – over summer for 3
years
27 (2 sampling trips)
11
15 – 70 m
Species
Richness
Author (s)
0 D 42
Yanko
., 1994
55
0 D 61
71
Yanko
Yanko
Yanko
., 1994
., 1994
., 1994
28 D 43
Rathburne
9 D 27
39
4 D 34
19
67 (2 – 20 sp
per sample)
., 2000
Gustafsson & Nordberg, 2000
Bernhard
., 2001
du Châtelet
., 2004
Ruiz
., 2004
Bergin
., 2006
., 2006
6 – 56 m
39
Ferraro
N/A
76
Tsujimoto
11.5 m
40
1.2 – 25.5
m
113
Romano
., 2008
58 – 178 m
2 D 26
Mojtahid
., 2008
., 2006
Frontalini & Coccioni, 2008
238
Appendix 3.3 (b): Number of species in shelf seas around the Atlantic (from shoreline to shelf break)
(Murray 2007).
Location
Dominant
Subsidiary
Minor
Sum = species
pool
% Minor species
Eastern Seaboard
Europe
72
39
195
Africa
28
8
81
305
64
117
69
Western Seaboard
Gulf of
N. America
Mexico
35
21
17
22
186
124
238
78
167
74
S. America
7
14
104
125
83
239
Appendix 3.4: Abundance of specimen within each genus within the live assemblages
Genus
( %
(
"
$%
!
)
)
%
)
#
+
)
Genus
( %
(
"
$%
!
)
)
%
)
#
+
)
RIA1
0
4
43
0
0
0
0
10
0
0
1
0
9
0
1
10
0
0
RIA2
0
14
40
0
0
0
0
17
1
2
0
0
2
0
0
15
0
0
RIA3
0
13
40
0
0
0
0
7
3
0
0
0
3
0
1
20
0
0
RIA4
0
27
25
3
0
0
2
6
1
0
0
0
5
0
0
16
0
0
RIA5
0
3
13
0
1
0
0
10
0
0
0
0
2
0
0
6
0
0
RIA6
0
6
9
0
0
0
0
7
0
0
0
0
7
0
1
8
0
0
RIB1
0
8
39
0
0
0
0
10
0
0
0
0
11
0
0
4
0
0
RIB2
0
19
15
0
0
0
0
13
0
0
1
1
9
0
8
12
0
0
RIC1
0
10
17
2
0
0
0
11
0
0
0
0
2
0
2
11
0
0
RIC2
0
26
39
2
0
0
0
22
1
3
0
1
11
2
1
35
0
0
RIC3
0
16
31
0
4
0
1
21
4
1
0
4
4
0
2
22
0
0
RIC4
0
37
40
0
9
0
0
21
0
0
0
5
6
0
2
41
0
0
RIC5
0
9
10
0
1
0
0
19
0
0
0
0
4
0
1
13
0
0
RIC6
0
15
29
2
0
0
0
39
0
0
0
0
14
0
1
28
0
0
RID1
0
21
14
0
0
0
0
3
0
1
0
0
25
1
2
2
0
0
RID2
0
14
35
1
0
0
0
11
0
2
0
0
13
1
12
20
0
0
RIB3
0
9
32
0
0
0
0
22
0
0
0
1
3
0
3
11
0
0
RID3
0
9
29
0
1
0
0
18
1
1
0
5
19
0
0
19
0
0
RIB4
0
13
61
0
0
0
0
20
0
0
0
0
3
0
1
2
0
0
RID4
2
13
22
3
0
0
0
37
1
0
0
1
11
0
6
31
0
0
RIB5
0
37
39
0
1
1
0
12
0
0
0
1
4
1
2
14
0
0
RID5
0
12
12
0
0
0
0
12
1
0
0
0
0
0
6
15
0
0
RIB6
0
17
39
0
0
0
0
18
0
1
0
0
9
0
7
16
0
0
RID6
0
19
29
1
0
0
0
12
0
1
0
0
6
0
3
24
0
0
240
Appendix 3.4: Abundance of specimen within each genus within the live assemblages
Genus
RIE1 RIE2 RIE3 RIE4 RIE5 RIE6 RIF1 RIF2 RIF3 RIF4 RIF5 RIG1
0
1
1
0
0
1
0
0
0
0
0
0
0
1
4
1
1
2
20
4
23
7
5
4
5
12
4
7
5
2
14
14
38
10
11
8
0
0
0
0
0
1
0
2
0
0
0
0
( %
0
3
0
2
0
0
0
1
5
2
0
10
(
0
0
0
0
0
0
0
1
1
0
0
0
"
0
0
0
1
0
0
0
0
0
0
0
0
$%
1
2
5
2
1
5
14
38
48
10
11
2
!
0
1
0
0
0
0
0
1
0
0
0
0
)
1
5
2
1
0
0
0
1
0
0
0
1
)
%
0
0
0
0
0
0
2
0
0
0
0
0
)
0
1
0
4
5
0
1
0
0
0
1
1
6
14
0
6
2
2
8
3
7
8
6
5
#
0
0
0
0
0
0
0
0
0
2
0
0
0
0
4
0
1
0
1
5
5
1
1
10
+
25
14
11
24
13
63
11
35
32
13
20
11
0
0
0
0
0
0
0
0
0
0
0
0
)
0
0
0
0
0
0
0
0
0
0
0
0
Genus
( %
(
"
$%
!
)
)
%
)
#
+
)
RIG2
3
2
8
1
14
0
0
7
0
0
0
3
18
0
3
52
0
0
RIG3
0
3
36
0
38
1
0
34
0
3
0
13
21
0
2
43
0
0
RIG4
0
9
22
0
13
0
0
15
0
0
0
5
16
1
0
49
0
0
RIG5
0
1
8
0
8
0
0
13
0
0
0
1
4
0
2
33
0
0
RIG6
0
1
5
1
6
0
0
5
0
3
0
0
3
1
0
6
0
0
RIH1
0
20
22
1
4
0
0
10
1
0
0
2
11
0
9
17
0
0
RIH2
1
4
16
0
15
2
0
15
0
0
0
13
11
0
0
31
0
0
RIH3
0
38
33
0
2
0
0
7
1
0
0
4
18
1
16
31
0
0
RIH4
1
40
30
1
7
1
0
37
13
0
0
8
6
1
8
35
0
0
RIH5
1
11
21
1
5
0
0
19
0
0
0
2
16
0
1
31
0
0
RIH6
1
19
25
2
0
0
0
11
1
1
0
1
23
0
3
9
0
0
SPA1
25
6
132
3
0
0
0
16
0
0
0
0
17
0
1
0
2
10
241
Appendix 3.4: Abundance of specimen within each genus within the live assemblages
Genus
( %
(
"
$%
!
)
)
%
)
#
+
)
Genus
( %
(
"
$%
!
)
)
%
)
#
+
)
SPA2
41
18
31
0
0
0
0
2
1
0
0
0
7
0
1
2
0
4
SPC2
38
21
11
10
0
0
0
20
1
0
0
0
6
0
0
0
2
1
SPA3
35
13
24
3
0
0
0
10
4
0
0
0
3
0
0
1
1
10
SPC3
10
17
15
2
0
0
0
6
0
0
0
0
3
0
0
0
0
4
SPA4
28
19
17
3
0
0
1
12
6
0
0
0
6
0
0
2
0
7
SPC4
32
17
40
0
0
0
1
12
3
0
0
0
4
0
3
0
0
0
SPA5
22
15
85
2
0
0
0
8
0
0
0
0
1
0
0
1
0
21
SPC5
26
49
62
7
0
0
0
15
1
0
0
0
2
0
0
0
0
3
SPA6
22
15
85
2
0
0
0
8
0
0
0
0
1
0
0
1
0
21
SPC6
64
40
49
1
0
0
0
10
2
0
0
0
1
0
0
0
0
8
SPB1
28
11
31
0
0
0
0
9
0
0
0
0
9
0
0
0
2
3
SHA1
2
1
1
0
0
0
0
1
0
0
0
0
2
0
0
0
0
0
SPB2
50
2
21
0
0
0
0
2
1
0
0
0
1
0
0
0
0
3
SPB3
48
15
38
0
0
0
0
15
1
0
0
0
15
0
0
0
2
4
SPB4
66
24
71
5
0
0
1
21
4
0
0
0
1
0
0
0
3
3
SPB5
60
15
81
1
0
0
0
15
3
0
0
0
2
0
0
0
1
4
SHA2
5
5
10
0
0
0
0
2
1
0
0
0
5
0
0
0
2
1
SHA3
6
3
7
0
0
0
0
5
0
0
0
0
1
0
0
0
1
1
SHA4
10
14
20
1
0
0
1
5
4
0
0
0
3
0
0
0
1
0
SHA5
9
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
SPB6
62
18
66
0
0
0
0
0
3
0
0
0
0
0
0
0
0
7
SHA6
2
5
15
1
0
0
1
5
1
0
0
0
1
0
0
0
0
0
SPC1
44
16
26
8
0
0
0
22
5
0
0
0
24
0
0
1
0
8
SHB1
24
22
8
0
0
0
0
9
0
0
0
0
14
0
2
0
1
0
242
Appendix 3.4: Abundance of specimen within each genus within the live assemblages
Genus
( %
(
"
$%
!
)
)
%
)
#
+
)
Genus
( %
(
"
$%
!
)
)
%
)
#
+
)
SHB2
18
2
14
0
0
0
0
1
0
0
0
0
0
0
0
1
0
0
SHB3
17
25
1
0
0
0
0
2
0
0
0
0
4
0
2
0
0
0
SHD3
3
5
0
0
0
0
0
2
0
0
0
0
1
0
1
0
0
0
SHB4
57
34
17
5
0
0
0
9
5
0
0
0
8
0
0
0
1
0
SHD4
1
10
3
1
0
0
0
1
2
0
0
0
0
0
2
0
0
1
SHB5
28
4
4
0
0
0
0
0
1
0
0
0
2
0
4
0
0
0
SHD5
1
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
SHB6
20
3
4
1
0
0
0
1
0
0
0
0
0
0
0
0
0
0
SHD6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
SHC1
20
15
1
1
0
0
0
0
0
0
0
0
6
0
0
0
0
0
SHE1
0
0
0
0
0
0
0
1
0
0
0
0
1
0
0
0
0
0
SHC2
5
2
4
0
0
0
0
0
0
0
0
0
10
0
2
0
0
0
SHE2
14
1
1
0
0
0
0
0
0
0
0
0
0
0
7
0
2
0
SHC3
14
29
8
1
0
0
0
3
0
0
0
0
5
0
3
0
0
0
SHE3
3
2
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
SHC4
15
34
5
0
0
0
0
0
0
0
0
0
22
0
2
0
2
0
SHE4
3
2
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
SHC5
15
4
0
0
0
0
0
0
0
0
0
0
7
0
1
0
0
0
SHE5
2
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
SHE6
7
0
0
0
0
0
0
0
0
0
0
0
1
0
1
0
0
0
SHC6
7
22
18
0
0
0
0
0
0
0
0
0
5
0
0
0
0
0
SHD2
0
2
0
3
0
0
0
0
0
0
0
0
13
0
1
0
0
0
SHF1
6
5
0
1
0
0
0
0
0
0
0
0
2
0
0
0
0
0
SHF2
28
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
243
Appendix 3.4: Abundance of specimen within each genus within the live assemblages
Genus
( %
(
"
$%
!
)
)
%
)
#
+
)
Genus
( %
(
"
$%
!
)
)
%
)
#
+
)
SHF3
23
26
8
0
0
0
0
1
0
0
0
0
0
0
0
0
1
0
SHF4
44
16
17
0
0
0
0
1
0
0
0
0
0
0
7
0
0
0
SHH1
4
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
SHH2
28
17
4
1
0
0
0
0
0
0
0
0
3
0
2
0
2
0
SHF5
10
6
4
1
0
0
0
0
1
0
0
0
4
0
1
0
0
0
SHH3
65
20
6
0
0
0
0
3
0
0
0
0
0
0
4
0
1
0
SHF6
1
7
4
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
SHH4
11
34
9
0
0
0
0
1
0
0
0
0
0
0
3
0
0
0
SHG1
29
17
2
2
0
0
0
0
0
0
0
0
6
0
1
0
0
0
SHH5
9
3
4
0
0
0
0
0
1
0
0
0
1
0
1
0
0
0
SHG2
42
10
10
0
0
0
0
0
0
0
0
0
0
0
3
0
0
0
SHI1
27
29
7
0
0
0
0
0
4
0
0
0
1
0
0
0
0
0
SHG3
29
12
7
0
0
0
0
2
4
0
0
0
14
0
1
1
1
0
SHG4
73
12
8
0
0
0
2
0
0
0
0
0
1
0
2
0
0
0
SHI2
8
0
8
0
0
0
0
0
0
0
0
0
0
0
0
0
0
4
SHI3
7
13
6
0
0
0
1
1
4
0
0
0
3
0
1
0
1
0
SHG5
13
4
5
1
0
0
0
0
1
0
0
0
3
0
1
0
0
0
SHI4
15
14
2
0
0
0
0
0
1
0
0
0
0
0
0
0
1
0
SHG6
19
11
1
0
0
0
0
0
0
0
0
0
6
0
1
0
1
0
SHI5
1
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
SHI6
6
3
7
0
0
0
0
3
4
0
0
0
0
0
2
0
0
0
244
Appendix 3.5: Total abundance of live foraminifera in the different size classes for all samples of Robben Island and
St Helena Bay
Sample
RIA1
RIA2
RIA3
RIA4
RIA5
RIA6
RIB1
RIB2
RIB3
RIB4
RIB5
RIB6
RIC1
RIC2
RIC3
RIC4
RIC5
RIC6
RID1
RID2
RID3
RID4
RID5
RID6
RIE1
RIE2
RIE3
RIE4
RIE5
RIE6
RIF1
RIF2
RIF3
RIF4
RIF5
RIG1
> 63 Km
240
178
160
211
116
249
115
180
118
80
47
91
158
220
56
29
58
124
81
75
51
46
18
54
34
39
20
8
18
16
80
96
44
50
15
31
> 125 Km
318
284
157
235
328
248
185
206
502
334
136
101
209
212
71
138
116
113
72
99
55
165
82
79
6
27
8
23
8
31
136
228
77
42
32
32
> 250 Km
19
18
5
7
7
13
9
22
18
6
4
14
36
46
31
10
33
33
3
6
14
51
14
19
16
8
9
10
5
7
18
45
34
27
21
10
> 500 Km
0
0
0
0
0
0
0
0
0
0
1
0
0
0
1
0
0
0
0
0
0
0
0
0
0
1
0
0
0
1
3
0
1
0
1
1
TOTAL
577
480
322
453
451
510
309
408
638
420
188
206
403
478
159
177
207
270
156
180
120
262
114
152
56
75
37
41
31
55
237
369
156
119
69
74
245
Appendix 3.5: Total abundance of live foraminifera in the different size classes for all samples of Robben Island and
St Helena Bay
Sample
RIG2
RIG3
RIG4
RIG5
RIG6
RIH1
RIH2
RIH3
RIH4
RIH5
RIH6
SPA1
SPA2
SPA3
SPA4
SPA5
SPA6
SPB1
SPB2
SPB3
SPB4
SPB5
SPB6
SPC1
SPC2
SPC3
SPC4
SPC5
SPC6
SHA1
SHA2
SHA3
SHA4
SHA5
SHA6
SHB1
SHB2
SHB3
SHB5
SHB6
SHC1
SHC2
SHC3
SHC4
SHC5
> 63 Km
25
44
66
16
8
358
75
84
87
32
58
713
244
100
303
513
271
1016
385
3443
327
435
355
673
1703
168
49
167
227
14
16
6
126
3
15
112
22
52
22
18
64
144
1072
1401
286
> 125 Km
142
72
49
27
14
107
103
62
64
52
160
1397
623
3655
38
377
256
1489
551
953
667
453
479
531
1390
66
312
346
826
6
42
16
33
16
25
211
26
3
36
12
124
199
96
306
43
> 250 Km
35
40
128
13
5
33
56
17
46
19
18
209
544
69
173
84
384
79
64
117
125
91
376
68
68
10
26
15
48
4
5
7
15
7
11
22
17
10
27
18
2
11
12
16
8
> 500 Km
1
9
6
0
5
1
2
0
4
2
1
7
1
3
0
3
2
0
2
1
2
0
0
3
1
0
1
0
1
0
1
0
0
0
0
0
3
0
3
0
0
1
1
1
1
TOTAL
203
165
249
56
32
499
236
163
201
105
237
2326
1412
3827
514
977
913
2584
1002
4514
1121
979
1210
1275
3162
244
388
528
1102
24
64
29
174
26
51
345
68
65
88
48
190
355
1181
1724
338
246
Sample
SHC6
SHD2
SHD3
SHD4
SHD5
SHE1
SHE2
SHE3
SHE4
SHE5
SHE6
SHF1
SHF2
SHF3
SHF4
SHF5
SHF6
SHG1
SHG2
SHG3
SHG4
SHG5
SHG6
SHH1
SHH2
SHH3
SHH4
SHH5
SHI1
SHI2
SHI3
SHI4
SHI5
SHI6
> 63 Km
72
49
23
20
13
16
19
12
4
2
3
12
106
57
46
7
35
120
71
224
15
16
45
30
134
94
32
16
28
23
8
101
61
22
> 125 Km
89
19
10
16
3
0
16
9
1
6
1
20
162
48
23
26
22
44
45
75
70
16
43
10
60
12
14
20
70
254
79
25
287
165
> 250 Km
7
0
1
1
2
0
6
2
2
6
6
4
23
24
13
2
8
15
33
21
35
10
20
6
5
8
13
12
14
18
2
5
12
42
> 500 Km
2
0
1
0
0
0
4
1
1
0
0
0
0
2
0
1
0
4
1
2
2
2
1
1
0
1
2
0
0
0
1
1
0
0
TOTAL
170
68
35
37
18
16
45
24
8
14
10
36
291
131
82
36
65
183
150
322
122
44
109
47
199
115
61
48
112
295
90
132
360
229
247
Appendix 3.6: The abundance of live and dead foraminifera within each size class in samples from
Robben Island and St Helena Bay
sample
SPA1
SPA2
SPA3
SPA4
SPA5
SPA6
SPB1
SPB2
SPB3
SPB4
SPB5
SPB6
SPC1
SPC2
SPC3
SPC4
SPC5
SPC6
SHA1
SHA2
SHA3
SHA4
SHA5
SHA6
SHB1
SHB2
SHB3
SHB4
SHB5
SHB6
SHC1
SHC2
SHC3
SHC4
SHC5
SHC6
63 Km
live (l)
713
244
100
303
513
271
1016
385
3443
327
435
355
673
1703
168
49
167
227
14
16
6
126
3
15
112
22
52
42
22
18
64
144
1072
1401
286
72
dead (d)
176
169
170
239
427
175
546
252
1009
163
370
173
97
981
31
96
136
113
34
26
9
277
21
44
610
40
83
104
72
17
357
598
1452
2609
781
472
125 Km
l
1397
623
3655
38
377
256
1489
551
953
667
453
479
531
1390
66
312
346
826
6
42
16
33
16
25
211
26
3
97
36
12
124
199
96
306
43
89
d
191
318
3016
62
399
155
74
274
118
239
372
367
29
65
13
179
243
505
118
338
84
201
105
126
613
26
2
182
85
12
465
440
149
380
113
194
250 Km
l
209
544
69
173
84
384
79
64
117
125
91
376
68
68
10
26
15
48
4
5
7
15
7
11
22
17
10
33
27
18
2
11
12
16
8
7
d
48
206
130
133
138
272
5
37
14
145
58
290
4
785
3
34
13
29
5
22
11
19
25
6
16
17
17
36
63
7
1
8
5
5
11
6
500 Km
l
7
1
3
0
3
2
0
2
1
2
0
0
3
1
0
1
0
1
0
1
0
0
0
0
0
3
0
1
3
0
0
1
1
1
1
2
TOTAL
d
2
0
2
0
2
0
0
0
0
0
0
0
3
17
0
0
0
0
0
0
2
0
0
0
0
0
2
1
5
0
0
0
1
0
2
0
Live
2326
1412
3827
514
977
913
2584
1002
4514
1121
979
1210
1275
3162
244
388
528
1102
24
64
29
174
26
51
345
68
65
173
88
48
190
355
1181
1724
338
170
Dead
417
693
3318
434
966
602
625
563
1141
547
800
830
133
1848
47
309
392
647
157
386
106
497
151
176
1239
83
104
323
225
36
823
1046
1607
2994
907
672
248
sample
SHD2
SHD3
SHD4
SHD5
SHD6
SHE1
SHE2
SHE3
SHE4
SHE5
SHE6
SHF1
SHF2
SHF3
SHF4
SHF5
SHF6
SHG1
SHG2
SHG3
SHG4
SHG5
SHG6
SHH1
SHH2
SHH3
SHH4
SHH5
SHI1
SHI2
SHI3
SHI4
SHI5
SHI6
RIA1
RIA2
RIA3
RIA4
63 Km
live (l)
49
23
20
13
1
16
19
12
4
2
3
12
106
57
46
7
35
120
71
224
15
16
45
30
134
94
32
16
28
23
8
101
61
22
240
178
160
211
dead (d)
154
46
97
40
12
15
25
9
17
7
13
105
220
106
396
57
101
344
218
265
91
66
82
35
106
316
86
64
89
131
64
277
136
77
217
254
126
384
125 Km
l
19
10
16
3
10
0
16
9
1
6
1
20
162
48
23
26
22
44
45
75
70
16
43
10
60
12
14
20
70
254
79
25
287
165
318
284
157
235
d
41
15
71
27
23
2
16
4
3
2
9
9
299
44
105
109
43
107
148
158
114
92
77
7
18
109
111
59
119
656
224
125
663
642
210
346
171
358
250 Km
l
0
1
1
2
2
0
6
2
2
6
6
4
23
24
13
2
8
15
33
21
35
10
20
6
5
8
13
12
14
18
2
5
12
42
19
18
5
7
d
1
0
3
1
2
1
19
5
0
14
8
3
20
22
73
19
7
34
52
23
45
13
40
3
35
56
45
23
12
38
7
43
27
9
16
19
6
7
500 Km
l
0
1
0
0
0
0
4
1
1
0
0
0
0
2
0
1
0
4
1
2
2
2
1
1
0
1
2
0
0
0
1
1
0
0
0
0
0
0
TOTAL
d
0
0
0
0
0
1
4
1
1
0
0
1
4
0
8
3
2
6
3
3
0
0
0
0
2
0
2
0
0
2
0
3
0
1
0
0
0
0
Live
68
35
37
18
13
16
45
24
8
14
10
36
291
131
82
36
65
183
150
322
122
44
109
47
199
115
61
48
112
295
90
132
360
229
577
480
322
453
Dead
196
61
171
68
37
19
64
19
21
23
30
118
543
172
582
188
153
491
421
449
250
171
199
45
161
481
244
146
220
827
295
448
826
729
443
619
303
749
249
sample
RIA5
RIA6
RIB1
RIB2
RIB3
RIB4
RIB5
RIB6
RIC1
RIC2
RIC3
RIC4
RIC5
RIC6
RID1
RID2
RID3
RID4
RID5
RID6
RIE1
RIE2
RIE3
RIE4
RIE5
RIE6
RIF1
RIF2
RIF3
RIF4
RIF5
RIG1
RIG2
RIG3
RIG4
RIG5
RIG6
63 Km
live (l)
116
249
115
180
118
80
47
91
158
220
56
29
58
124
81
75
51
46
18
54
34
39
20
8
18
16
80
96
44
50
15
31
25
44
66
16
8
dead (d)
244
367
83
360
125
88
132
189
256
207
69
26
362
191
28
19
30
102
15
47
5
14
13
10
6
10
127
324
92
259
19
13
28
25
85
6
5
125 Km
l
328
248
185
206
502
334
136
101
209
212
71
138
116
113
72
99
55
165
82
79
6
27
8
23
8
31
136
228
77
42
32
32
142
72
49
27
14
d
328
408
95
204
698
259
323
189
166
198
59
81
200
287
28
106
41
242
43
39
13
22
11
18
12
15
99
208
153
206
41
17
180
59
66
29
8
250 Km
l
7
13
9
22
18
6
4
14
36
46
31
10
33
33
3
6
14
51
14
19
16
8
9
10
5
7
18
45
34
27
21
10
35
40
128
13
5
d
18
34
4
19
22
1
25
10
37
55
16
9
64
52
2
19
8
83
2
18
12
16
14
25
13
16
43
46
28
225
25
26
61
33
184
30
0
500 Km
l
0
0
0
0
0
0
1
0
0
0
1
0
0
0
0
0
0
0
0
0
0
1
0
0
0
1
3
0
1
0
1
1
1
9
6
0
5
TOTAL
d
0
0
0
0
0
0
0
0
0
1
1
0
0
0
0
0
0
1
0
0
0
0
1
1
1
0
1
1
0
3
2
7
4
14
13
0
3
Live
451
510
309
408
638
420
188
206
403
478
159
177
207
270
156
180
120
262
114
152
56
75
37
41
31
55
237
369
156
119
69
74
203
165
249
56
32
Dead
590
809
182
583
845
348
480
388
459
461
145
116
626
530
58
144
79
428
60
104
30
52
39
54
32
41
270
579
273
693
87
63
273
131
348
65
16
250
sample
RIH1
RIH2
RIH3
RIH4
RIH5
RIH6
RIH1
RIH2
RIH3
63 Km
live (l)
358
75
84
87
32
58
358
75
84
dead(d)
236
51
92
91
43
97
236
51
92
125 Km
l
107
103
62
64
52
160
107
103
62
d
99
115
70
60
68
278
99
115
70
250 Km
l
33
56
17
46
19
18
33
56
17
d
14
62
23
32
33
28
14
62
23
500 Km
l
1
2
0
4
2
1
1
2
0
d
1
6
1
2
4
1
1
6
1
TOTAL
Live
499
236
163
201
105
237
499
236
163
Dead
350
234
186
185
148
404
350
234
186
251
Appendix 4.1: Foraminifera identified in samples from Robben Island and St Helena Bay
a
b
c
d
e
Plate 4.1.1 :
a.
c,d.
f
ventral view
b.
ventral view
e
f
252
Appendix 4.1: Foraminifera identified in samples from Robben Island and St Helena Bay
a
b
c
d
e
Plate 4.1.2:
f
b Bolivinitidae
c,d,e,f. examples of
grouped together as elongated
253
Appendix 4.1: Foraminifera identified in samples from Robben Island and St Helena Bay
a
b
c
d
e
Plate 4.1.3:
a, b, c. examples of
d
f
grouped together as perforated
e.
f.
254
Appendix 4.1: Foraminifera identified in samples from Robben Island and St Helena Bay
a
b
c
d
e
Plate 4.1.4 :
f
a.
c
e.
b.
sp A
d.
f.
sp A
255
Appendix 4.1: Foraminifera identified in samples from Robben Island and St Helena Bay
a
b
c
d
e
Plate 4.1.5:
f
a, b. !
d. !
,
c !
sp A
e. !
t
f. (
256
Appendix 4.1: Foraminifera identified in samples from Robben Island and St Helena Bay
a
b
c
d
e
Plate 4.1.6:
f
a. "
c "
e ( %
b. "
sp A
d. )
dorsal view
f ( %
view
ventral
257
Appendix 4.1: Foraminifera identified in samples from Robben Island and St Helena Bay
a
b
c
d
e
Plate 4.1.7:
Variation in $ %
f
%
258
Appendix 4.1: Foraminifera identified in samples from Robben Island and St Helena Bay
a
b
c
d
e
Plate 4.1.8:
f
a.
%
c.
sp A
e.
dorsal view
b.
d.
'
f #
%
%
ventral view
-
sp A
259
Appendix 4.1: Foraminifera identified in samples from Robben Island and St Helena Bay
a
b
c
d
e
Plate 4.1.9:
a. )
f
b. )
c &
'
d &
e &
'
f. +
sp A
'
%
260
Appendix 4.1: Foraminifera identified in samples from Robben Island and St Helena Bay
a
b
c
d
e
Plate 4.1.10: a. &
'
'
b.c,d Miliolids
e. Unknown species
261
Appendix 4.1: Foraminifera identified in samples from Robben Island and St Helena Bay
a
b
c
d
e
f
Plate 4.1.11: Some abnormal specimens of
262
Appendix 4.1: Foraminifera identified in samples from Robben Island and St Helena Bay
a
b
c
d
e
Plate 4.1.12: Abnormal tests
b.
d. "
H
broken neck
a.
c
e. "
abraded
263
Appendix 4.1: Foraminifera identified in samples from Robben Island and St Helena Bay
a
b
c
d
e
Plate 4.1.13: aDe. Abnormal
264
Appendix 4.1: Foraminifera identified in samples from Robben Island and St Helena Bay
a
b
c
d
e
f
Plate 4.1.14: Abnormal tests of
265
Appendix 4.1: Foraminifera identified in samples from Robben Island and St Helena Bay
a
b
c
d
e
Plate 4.1.15: a D f. Abnormal and broken $ %
f
?
266
Appendix 4.1: Foraminifera identified in samples from Robben Island and St Helena Bay
a
b
c
d
Plate 4.1.16: a. Abnormal )
b. ( %
twins
d. +
c.
siamese
siamese twins
abnormal?
267
Appendix 4.2: Elemental analysis of foraminiferal tests in wt %
C
O
Mg
Al
Si
S
Cl
Cd
K
Ca
Cr
Fe
Cu
Zn
Pb
SHA201
8.99
5.57
0.48
0.45
14.25
2.59
0.72
0.00
0.09
61.81
0.12
2.55
0.65
0.57
1.74
SHA202
8.42
2.64
0.58
0.13
2.91
1.06
0.59
0.00
0.00
79.46
0.00
2.67
0.29
0.26
1.24
SHA203
5.09
2.27
0.32
0.00
1.05
1.20
2.40
0.00
0.00
86.52
0.00
0.65
0.49
0.42
0.00
SHA204
4.00
5.28
0.00
0.00
0.57
0.29
0.10
0.00
0.00
89.36
0.00
0.16
0.24
0.19
0.00
SHA205
11.71
6.03
0.24
0.00
0.53
1.02
0.89
0.00
0.00
78.73
0.00
0.34
0.51
0.45
0.00
SHA206
8.67
0.00
0.32
0.25
5.45
1.29
0.36
0.00
0.11
80.51
0.00
2.77
0.26
0.23
0.00
SHA207
11.07
3.19
0.79
0.30
4.14
1.82
0.96
0.00
0.21
71.87
0.18
2.96
1.00
0.65
1.49
SHA208
5.39
2.94
0.18
0.00
0.48
1.00
1.37
0.00
0.00
85.50
0.00
0.56
1.02
0.86
1.55
SHA209
4.61
6.52
0.31
0.00
0.89
0.69
0.27
0.00
0.00
85.66
0.00
0.46
0.59
0.23
0.00
SHA210
4.52
5.66
0.52
0.22
3.40
1.50
0.26
0.00
0.00
80.10
0.00
2.02
0.74
0.63
1.06
SHB201
2.81
2.87
0.21
0.00
0.63
0.53
0.13
0.41
0.00
89.38
0.15
0.74
0.89
0.77
1.24
SHB202
3.19
6.67
0.18
0.00
1.00
0.51
0.05
0.00
0.00
87.24
0.15
0.31
0.70
0.65
0.00
SHB203
2.84
8.70
0.00
0.12
1.07
0.84
0.19
0.00
0.06
85.39
0.00
0.38
0.39
0.28
0.00
SHB204
3.56
8.77
0.00
0.00
0.56
0.54
0.21
0.00
0.00
85.68
0.00
0.24
0.45
0.42
0.00
SHB205
3.05
3.79
0.28
0.09
1.89
1.28
0.24
0.00
0.00
87.36
0.00
0.69
0.67
0.59
0.67
SHB206
3.85
6.45
0.00
0.00
0.53
0.68
0.37
0.00
0.00
85.99
0.00
0.57
0.79
0.76
0.77
SHB207
4.21
6.99
0.29
0.27
3.90
1.42
0.39
0.00
0.00
74.62
0.00
6.71
0.66
0.54
0.54
SHB208
3.98
6.95
0.09
0.12
1.00
1.32
0.00
0.00
0.00
85.56
0.00
0.59
0.39
0.34
0.00
SHB209
3.98
6.98
0.25
0.00
0.47
0.46
0.45
0.00
0.00
86.63
0.00
0.45
0.31
0.22
0.00
SHB210
3.96
4.26
0.15
0.00
0.32
0.58
0.08
0.28
0.00
90.01
0.00
0.13
0.24
0.18
0.00
SHC201
7.36
8.85
0.99
0.40
13.59
1.27
0.50
0.00
0.23
57.52
0.12
8.87
0.31
0.27
0.00
SHC202
9.14
5.57
0.41
0.00
1.08
1.30
2.21
0.00
0.00
78.70
0.00
0.94
0.66
0.64
0.00
SHC203
32.04
8.31
0.99
0.93
18.19
5.31
2.04
0.00
0.41
24.80
0.00
6.43
0.56
0.51
0.00
SHC204
8.56
0.00
0.19
0.13
2.21
1.18
1.03
0.00
0.10
79.36
0.00
2.96
2.09
1.89
2.19
SHC205
3.58
10.87
0.19
0.12
1.77
0.44
0.28
0.00
0.00
82.05
0.00
0.40
0.31
0.22
0.00
SHC206
5.17
5.45
0.80
0.50
3.89
1.53
0.30
0.00
0.18
80.63
0.00
0.93
0.60
0.62
0.00
SHC207
9.55
3.01
0.39
0.12
2.46
1.97
0.80
0.00
0.07
79.24
0.00
1.80
0.60
0.59
0.00
SHC208
3.42
7.61
0.27
0.15
1.64
1.34
0.59
0.00
0.00
83.31
0.00
0.77
0.91
0.86
0.00
SHC209
3.77
7.30
0.13
0.10
2.66
0.88
0.54
0.00
0.12
82.99
0.14
0.73
0.64
0.62
0.00
SHC210
5.75
7.06
1.90
0.09
6.38
1.77
0.92
0.00
0.00
74.48
0.00
0.87
0.78
0.71
0.00
SHD201
4.80
6.29
0.24
0.00
1.30
1.03
0.39
0.29
0.00
83.28
0.19
0.74
0.87
0.85
0.57
SHD202
3.30
2.57
0.56
0.14
3.44
1.12
0.39
0.00
0.00
85.46
0.00
2.44
0.59
0.62
0.00
SHD203
4.63
8.93
0.25
0.10
2.05
0.54
0.29
0.00
0.00
80.76
0.07
0.68
0.79
0.73
0.93
268
C
O
Mg
Al
Si
S
Cl
Cd
K
Ca
Cr
Fe
Cu
Zn
Pb
SHD204
7.58
8.53
0.35
0.27
4.06
1.08
1.07
0.14
0.00
73.22
0.00
3.29
0.41
0.38
0.00
SHD205
11.18
10.19
0.53
1.15
51.90
3.76
1.16
0.00
0.54
13.05
0.19
5.23
1.12
0.92
0.00
SHD206
5.89
8.06
1.19
0.43
21.53
1.94
0.73
0.00
0.33
49.89
0.09
9.63
0.30
0.26
0.00
SHD207
4.75
3.52
0.25
0.54
8.14
1.37
1.06
0.00
0.12
72.46
0.00
5.49
1.15
0.85
1.16
SHD208
8.10
9.11
0.15
0.00
1.90
0.88
0.24
0.15
0.07
78.34
0.00
0.35
0.70
0.66
0.00
SHD209
4.33
5.25
0.32
0.27
3.80
1.01
0.83
0.00
0.07
81.46
0.17
1.52
0.98
0.92
0.00
SHD210
5.11
10.87
0.63
0.94
10.63
0.98
0.57
0.00
0.09
67.21
0.00
2.32
0.66
0.63
0.00
SHE201
4.06
7.14
0.68
0.16
6.22
1.25
0.15
0.00
0.00
76.24
0.09
2.59
0.58
0.62
0.84
SHE202
4.56
4.19
0.59
0.30
5.79
1.58
0.27
0.00
0.06
78.36
0.20
3.77
0.32
0.27
0.00
SHE203
5.45
7.38
0.66
0.16
3.93
1.27
0.51
0.00
0.00
78.49
0.00
1.95
0.21
0.19
0.00
SHE204
17.97
8.46
0.73
0.52
11.46
1.51
1.32
0.00
0.37
48.55
0.00
7.34
0.95
0.88
0.83
SHE205
5.64
6.28
0.10
0.16
3.35
0.29
0.58
0.00
0.06
80.45
0.00
1.07
0.73
0.64
1.28
SHE206
7.20
6.57
0.67
0.67
16.76
2.28
0.79
0.00
0.38
53.02
0.12
10.96
0.57
0.59
0.00
SHE207
11.91
8.71
0.61
1.07
27.64
3.83
1.80
0.00
0.45
34.80
0.09
8.64
0.44
0.43
0.00
SHE208
9.41
9.81
0.50
0.75
20.01
1.92
0.44
0.00
0.28
51.25
0.14
4.95
0.55
0.59
0.00
SHE209
3.93
4.91
0.15
0.00
1.02
1.01
0.18
0.00
0.00
87.58
0.19
0.78
0.25
0.26
0.00
SHE210
3.29
5.78
0.40
0.15
6.68
0.67
0.16
0.00
0.08
77.07
0.00
4.38
0.32
0.34
1.00
SHF201
0.95
11.72
0.00
0.00
81.95
4.27
0.17
0.00
0.00
0.07
0.00
0.11
0.76
0.77
0.00
SHF202
2.89
7.42
0.25
0.00
1.08
0.82
0.26
0.19
0.00
84.22
0.00
0.16
1.14
0.98
1.57
SHF203
4.85
13.86
0.40
0.67
8.36
0.95
0.59
0.00
0.00
66.63
0.00
2.36
0.78
0.88
0.55
SHF204
4.59
11.91
0.46
0.21
3.00
0.84
0.24
0.00
0.00
75.79
0.12
0.96
0.92
0.87
0.96
SHF205
14.57
5.21
0.45
0.27
4.67
1.38
1.07
0.00
0.07
70.06
0.00
1.67
0.57
0.63
0.00
SHF206
5.41
5.96
0.88
0.48
12.76
1.43
0.39
0.00
0.20
65.60
0.28
5.97
0.66
0.57
0.00
SHF207
13.09
10.34
0.40
0.43
8.75
1.11
0.51
0.00
0.23
61.64
0.00
2.94
0.56
0.39
0.00
SHF208
7.49
6.61
0.40
0.30
5.01
1.07
0.80
0.00
0.06
75.29
0.14
1.48
0.72
0.61
0.61
SHF209
6.27
7.99
0.62
0.77
9.78
1.55
0.48
0.00
0.12
66.95
0.00
4.87
0.60
0.63
0.00
SHF210
10.91
10.09
0.62
0.95
48.48
7.46
1.06
0.00
0.92
10.98
0.00
7.52
1.01
0.97
0.00
SHG201
4.52
6.79
0.00
0.17
1.43
0.66
0.06
0.00
0.07
82.69
0.00
2.35
0.66
0.62
0.59
SHG202
2.85
7.47
0.80
0.26
9.66
0.72
0.17
0.00
0.11
72.39
0.12
5.23
0.23
0.18
0.00
SHG203
5.06
6.24
0.22
0.25
3.88
1.23
0.24
0.00
0.00
75.75
0.00
6.64
0.48
0.48
0.00
SHG204
5.51
8.25
0.21
0.14
1.29
0.60
0.44
0.13
0.00
81.23
0.09
0.70
0.64
0.54
0.77
SHG205
4.29
2.95
0.50
0.22
5.55
1.33
0.22
0.00
0.14
78.12
0.00
3.89
0.83
0.67
1.96
SHG206
3.46
6.02
0.44
0.08
6.61
0.84
0.46
0.00
0.10
76.04
0.00
5.56
0.40
0.33
0.00
SHG207
13.09
10.34
0.40
0.43
8.75
1.11
0.51
0.00
0.23
61.64
0.00
2.94
0.56
0.64
0.00
269
C
O
Mg
Al
Si
S
Cl
Cd
K
Ca
Cr
Fe
Cu
Zn
Pb
SHG210
6.01
6.48
0.75
0.16
6.10
0.70
0.37
0.00
0.15
75.65
0.11
3.12
0.41
0.43
0.00
SHH201
10.16
3.73
0.46
0.56
10.00
3.40
0.55
0.00
0.31
63.22
0.12
6.55
0.93
0.86
0.00
SHH202
12.66
8.42
1.20
1.78
27.77
0.95
0.28
0.00
0.76
34.53
0.00
10.81
0.85
0.83
0.00
SHH203
9.07
9.10
1.35
2.18
35.12
2.42
0.00
0.00
0.99
22.45
0.33
14.48
1.74
1.33
0.78
SHH204
8.19
7.59
0.16
0.18
78.79
1.41
0.17
0.00
0.11
0.74
0.00
1.39
1.27
0.95
0.00
SHH205
37.48
0.00
1.05
0.67
9.07
12.93
2.38
0.00
1.04
26.75
0.26
5.55
2.81
1.75
0.00
SHH206
30.14
2.11
2.03
1.26
21.10
8.64
0.36
0.00
0.37
14.18
0.37
18.52
0.95
0.88
0.00
SHH207
63.47
0.00
0.35
0.46
22.08
1.66
0.17
0.00
0.14
0.81
0.16
5.02
2.34
1.92
3.35
SHH208
4.46
8.51
0.23
0.17
1.22
0.70
0.00
0.00
0.00
81.96
0.00
0.65
1.19
1.02
0.90
SHH209
2.77
8.71
0.13
0.19
0.00
0.08
0.00
0.00
0.00
85.91
0.00
0.25
1.14
1.05
0.81
SHH210
5.00
9.24
0.50
1.10
16.29
0.98
0.00
0.00
0.37
58.76
0.00
6.57
1.20
1.13
0.00
SPA201
2.85
2.17
0.11
0.22
3.57
0.90
0.10
0.00
0.12
86.31
0.00
2.44
1.22
1.09
0.00
SPA202
3.89
8.08
0.12
0.16
1.66
0.83
0.31
0.00
0.00
80.47
0.16
1.09
0.87
0.74
2.36
SPA203
4.96
9.14
0.27
0.00
0.49
0.83
0.07
0.00
0.00
83.55
0.00
0.38
0.33
0.28
0.00
SPA204
3.70
7.56
0.28
0.29
3.56
0.70
0.15
0.00
0.00
81.19
0.11
1.71
0.75
0.63
0.00
SPA205
2.96
8.72
0.21
0.11
1.60
0.52
0.18
0.18
0.00
83.43
0.00
0.37
0.60
0.58
1.12
SPA206
4.40
9.85
0.44
0.42
6.54
0.62
0.15
0.00
0.00
73.86
0.24
1.94
0.66
0.62
0.89
SPA207
11.04
3.83
0.56
0.19
3.03
1.08
0.88
0.00
0.00
76.34
0.13
1.07
1.01
0.97
0.83
SPA208
26.69
3.73
0.73
0.41
6.87
1.01
1.55
0.00
0.14
55.24
0.00
2.94
0.69
0.63
0.00
SPA209
4.68
13.44
0.15
0.24
3.02
0.66
0.19
0.00
0.00
76.21
0.14
0.80
0.47
0.31
0.00
SPA210
3.94
9.56
0.25
0.14
1.56
0.61
0.20
0.00
0.00
83.35
0.00
0.39
0.00
0.06
0.00
SPB401
38.34
0.00
0.64
0.28
5.63
2.16
3.06
0.00
0.10
47.79
0.00
1.99
0.00
0.02
0.00
SPB402
14.40
7.02
0.57
0.26
6.02
1.56
2.04
0.00
0.00
65.66
0.16
1.69
0.63
0.52
0.00
SPB403
7.00
9.71
0.21
0.20
3.88
1.21
0.56
0.00
0.07
75.36
0.11
1.25
0.46
0.43
0.00
SPB404
4.08
6.31
0.00
0.00
1.20
0.58
0.08
0.00
0.00
86.23
0.00
0.38
0.53
0.56
0.62
SPB405
3.87
6.99
0.20
0.13
2.80
1.00
0.00
0.00
0.00
83.30
0.19
1.00
0.53
0.48
0.00
SPB406
13.43
5.46
0.34
0.12
2.40
1.18
0.73
0.00
0.00
75.03
0.00
0.85
0.47
0.39
0.00
SPB407
8.76
11.51
0.59
0.61
11.79
1.57
0.32
0.00
0.22
58.89
0.17
3.98
0.72
0.67
0.90
SPB408
4.83
11.76
0.55
0.51
8.20
0.77
0.13
0.00
0.13
69.98
0.00
2.82
0.33
0.31
0.00
SPB409
13.50
8.77
0.53
0.55
13.79
1.07
0.96
0.00
0.29
55.46
0.00
4.49
0.58
0.52
0.00
SPB410
3.51
8.34
0.13
0.23
4.26
0.12
0.26
0.00
0.00
81.10
0.00
1.86
0.19
0.08
0.00
SPC401
3.51
0.00
0.09
0.27
4.69
0.51
0.00
0.00
0.00
86.89
0.00
1.92
0.68
0.56
1.44
270
C
O
Mg
Al
Si
S
Cl
Cd
K
Ca
Cr
Fe
Cu
Zn
Pb
SPC402
2.90
3.13
0.14
0.19
2.50
0.74
0.07
0.00
0.00
87.73
0.00
1.04
0.68
0.61
0.87
SPC403
9.73
6.34
0.42
0.68
14.47
2.16
0.36
0.00
0.25
59.74
0.13
4.92
0.80
0.74
0.00
SPC405
3.60
6.38
0.30
0.36
5.84
0.85
0.12
0.00
0.09
78.71
0.00
1.75
0.86
0.91
1.14
SPC406
6.28
3.04
0.10
0.16
3.30
0.44
0.57
0.00
0.00
82.91
0.00
2.91
0.29
0.23
0.00
SPC407
13.63
6.51
0.44
0.27
6.05
1.08
0.96
0.00
0.13
68.44
0.10
2.08
0.29
0.25
0.00
SPC408
3.04
3.06
0.19
0.26
2.65
0.60
0.17
0.00
0.00
87.23
0.00
0.86
0.90
0.81
1.03
SPC409
3.05
1.39
0.07
0.11
1.13
0.71
0.00
0.16
0.00
90.53
0.00
0.54
0.91
0.86
1.39
SPC410
4.05
8.72
0.61
0.61
9.14
1.00
0.41
0.00
0.17
70.48
0.00
4.03
0.34
0.23
0.44
RIA101
5.99
4.75
0.10
0.00
1.00
0.57
0.20
0.00
0.00
86.15
0.19
0.17
0.88
0.73
0.00
RIA102
4.45
5.91
0.15
0.00
0.35
0.78
0.22
0.00
0.00
87.65
0.08
0.16
0.26
0.25
0.00
RIA103
3.07
4.27
0.18
0.00
0.31
1.03
0.33
0.00
0.00
89.51
0.00
0.34
0.97
0.88
0.00
RIA104
4.72
3.61
0.00
0.00
1.34
0.46
0.44
0.00
0.00
88.58
0.00
0.18
0.67
0.63
0.00
RIA105
6.73
10.50
0.20
0.08
0.35
0.63
0.13
0.00
0.00
79.83
0.00
0.16
0.51
0.49
0.89
RIA106
4.86
5.52
0.37
0.21
3.79
0.38
0.17
0.00
0.09
83.55
0.00
0.81
0.24
0.21
0.00
RIA107
4.33
4.47
0.14
0.00
0.55
0.72
0.18
0.00
0.00
89.20
0.00
0.12
0.30
0.26
0.00
RIA108
3.29
0.00
0.00
0.00
0.50
0.80
0.07
0.14
0.00
93.88
0.11
0.42
0.79
0.76
0.00
RIA109
4.76
6.74
0.32
0.10
1.05
0.68
0.35
0.00
0.00
83.64
0.00
1.01
0.72
0.71
0.65
RIA110
4.89
0.00
0.18
0.00
0.40
0.75
0.17
0.49
0.00
92.04
0.00
0.31
0.76
0.69
0.00
RIB101
4.79
5.90
0.30
0.28
4.75
1.34
0.53
0.00
0.00
80.48
0.00
1.05
0.58
0.52
0.00
RIB102
5.85
3.65
0.15
0.00
2.23
1.06
0.68
0.00
0.00
85.15
0.00
0.75
0.49
0.46
0.00
RIB103
22.35
0.00
0.12
0.00
0.69
0.00
0.00
0.00
0.00
71.93
0.17
0.87
3.67
1.62
0.00
RIB104
9.33
6.75
0.20
0.32
23.08
0.94
0.72
0.00
0.11
51.13
0.10
7.14
0.20
0.19
0.00
RIB105
5.69
5.00
0.21
0.15
2.01
1.07
0.41
0.28
0.00
83.72
0.00
0.92
0.55
0.62
0.00
RIB106
6.34
3.45
0.13
0.12
3.10
1.06
1.00
0.00
0.00
82.66
0.00
0.70
0.69
0.63
0.75
RIB107
5.12
3.43
0.28
0.00
1.01
1.05
0.19
0.00
0.00
87.33
0.12
0.65
0.83
0.79
0.00
RIB108
4.91
4.70
0.31
0.23
3.86
0.97
0.41
0.00
0.00
82.37
0.00
1.46
0.78
0.82
0.00
RIB109
5.39
7.10
0.27
0.12
1.99
0.76
0.46
0.00
0.00
82.52
0.00
0.75
0.64
0.64
0.00
RIB110
3.37
0.00
0.00
0.00
0.51
0.67
0.17
0.00
0.00
94.56
0.00
0.00
0.72
0.69
0.00
RIC101
48.33
0.00
0.00
0.30
2.71
0.33
0.11
0.00
0.00
40.27
0.00
0.92
4.91
3.25
2.12
RIC102
7.30
5.45
0.42
0.10
3.32
1.16
0.54
0.00
0.00
79.31
0.00
0.68
0.55
0.61
1.16
RIC103
9.30
3.06
0.62
0.27
5.37
1.14
1.10
0.00
0.10
75.67
0.00
2.96
0.41
0.37
0.00
RIC104
10.37
0.00
0.20
0.17
3.15
0.99
0.24
0.00
0.00
82.46
0.00
1.51
0.92
0.85
0.00
RIC105
14.18
0.00
0.00
0.15
3.40
1.33
0.29
0.00
0.00
78.67
0.00
1.62
0.36
0.23
0.00
RIC106
6.43
5.58
0.27
0.29
7.31
1.10
0.40
0.00
0.07
76.57
0.29
1.17
0.53
0.47
0.00
271
C
O
Mg
Al
Si
S
Cl
Cd
K
Ca
Cr
Fe
Cu
Zn
Pb
RIC107
5.26
6.95
0.32
0.18
2.15
0.95
0.53
0.00
0.00
81.48
0.26
0.71
0.74
0.68
0.47
RIC108
4.71
9.31
0.24
0.10
1.58
0.68
0.09
0.00
0.00
81.48
0.10
0.62
0.61
0.69
0.47
RIC110
3.86
3.48
0.25
0.14
4.51
1.55
0.62
0.00
0.09
79.48
0.00
2.77
1.09
0.95
2.15
RID101
2.52
0.00
0.11
0.10
0.95
0.57
0.16
0.00
0.00
93.09
0.00
0.75
0.91
0.98
0.83
RID102
12.93
0.00
0.33
0.22
4.43
2.18
3.76
0.00
0.10
72.40
0.17
1.56
0.93
1.05
0.99
RID103
3.66
5.66
0.19
0.00
0.82
0.71
0.24
0.00
0.00
87.72
0.00
0.40
0.58
0.63
0.00
RID104
8.75
10.34
0.54
0.35
6.06
1.71
0.28
0.00
0.00
68.84
0.14
1.49
0.60
0.59
0.91
RID105
16.60
0.00
0.41
0.14
2.10
1.92
6.64
0.00
0.11
68.99
0.00
1.69
0.79
0.63
0.62
RID106
10.06
0.00
0.22
0.00
0.86
1.05
0.18
0.00
0.00
86.32
0.00
0.34
0.42
0.39
0.54
RID107
5.14
5.11
0.22
0.00
0.51
0.78
0.21
0.00
0.00
87.27
0.19
0.17
0.40
0.45
0.00
RID108
14.16
4.93
0.38
0.11
7.30
1.55
1.94
0.00
0.00
66.75
0.26
1.97
0.65
0.59
0.00
RID109
5.76
5.51
0.26
0.11
2.05
0.97
0.91
0.24
0.00
83.05
0.10
0.48
0.57
0.63
0.00
RID110
4.13
4.54
0.00
0.00
1.73
1.21
0.15
0.00
0.00
87.37
0.00
0.27
0.60
0.54
0.00
RIE101
4.82
2.95
0.31
0.00
1.21
0.96
0.19
0.00
0.00
86.35
0.36
1.26
0.97
0.65
0.00
RIE102
5.33
3.40
0.24
0.00
0.82
0.92
0.12
0.00
0.00
87.58
0.07
0.91
0.60
0.06
0.00
RIE103
37.44
0.00
0.22
0.89
18.41
0.56
0.73
0.00
1.50
10.65
0.68
16.92
6.32
4.68
5.67
RIE104
4.52
4.91
0.56
0.00
0.80
1.85
0.13
0.00
0.00
85.23
0.12
0.22
0.99
0.75
0.66
RIE105
8.00
2.50
0.78
0.86
13.26
1.13
1.01
0.00
0.24
15.03
0.24
52.17
3.55
2.89
1.23
RIE106
10.76
2.70
0.51
0.10
1.41
1.99
3.63
0.00
0.00
77.44
0.20
0.63
0.63
0.51
0.00
RIE107
7.03
0.00
0.27
0.13
3.06
1.20
1.43
0.00
0.00
83.85
0.25
1.78
1.00
0.86
0.00
RIE108
5.47
6.11
0.55
0.00
0.36
0.88
0.10
0.00
0.00
85.41
0.10
0.21
0.82
0.81
0.00
RIE109
13.12
0.00
0.29
0.24
5.15
1.41
3.68
0.00
0.13
72.95
0.00
1.20
1.02
0.98
0.81
RIE110
6.26
0.00
0.14
0.00
2.32
0.33
1.18
0.00
0.00
87.42
0.17
1.24
0.94
0.91
0.00
RIF101
7.75
4.20
0.31
0.09
1.05
0.47
0.30
0.15
0.00
84.89
0.00
0.38
0.42
0.38
0.00
RIF102
5.77
6.24
0.15
0.00
4.82
0.89
0.10
0.00
0.00
81.08
0.12
0.33
0.49
0.35
0.00
RIF103
4.35
3.22
0.24
0.00
0.95
0.68
0.25
0.00
0.00
88.42
0.00
0.33
1.02
0.96
0.55
RIF104
4.33
4.77
0.18
0.00
0.46
0.72
0.30
0.17
0.00
88.52
0.00
0.10
0.46
0.41
0.00
RIF105
3.71
4.59
0.07
0.00
0.28
1.03
0.18
0.00
0.00
89.71
0.00
0.00
0.44
0.43
0.00
RIF106
7.11
4.42
0.59
0.00
0.33
0.78
0.07
0.13
0.00
85.90
0.00
0.13
0.55
0.52
0.00
RIF107
6.21
2.87
0.28
0.00
0.72
0.82
0.19
0.00
0.00
88.60
0.00
0.00
0.30
0.33
0.00
RIF108
6.61
5.27
0.30
0.09
1.29
1.27
0.52
0.13
0.00
84.15
0.00
0.37
0.00
0.00
0.00
RIF109
4.98
4.75
0.24
0.00
1.03
1.07
0.87
0.00
0.00
85.68
0.18
0.45
0.74
0.68
0.00
272
C
O
Mg
Al
Si
S
Cl
Cd
K
Ca
Cr
Fe
Cu
Zn
Pb
RIF110
5.58
5.25
0.15
0.11
1.98
1.06
0.59
0.00
0.00
83.68
0.16
0.74
0.71
0.65
0.00
RIG101
6.10
7.70
0.38
0.07
2.17
0.72
0.32
0.15
0.00
81.24
0.00
0.59
0.54
0.59
0.00
RIG102
6.30
0.00
0.30
0.00
1.88
1.54
0.20
0.00
0.00
88.12
0.00
0.12
0.57
0.51
0.98
RIG103
5.34
5.73
0.45
0.16
3.14
1.60
1.03
0.00
0.00
81.32
0.00
0.94
0.30
0.28
0.00
RIG104
5.84
9.73
0.14
0.00
0.41
1.02
0.24
0.25
0.00
82.16
0.00
0.00
0.21
0.15
0.00
RIG105
7.81
4.71
0.58
0.00
1.06
0.60
0.48
0.00
0.00
83.21
0.25
0.73
0.57
0.46
0.00
RIG106
5.55
2.55
0.27
0.00
0.25
0.88
0.15
0.00
0.00
88.92
0.00
0.25
0.44
0.39
0.75
RIG107
5.13
4.37
1.62
0.00
0.35
1.63
0.33
0.00
0.00
84.65
0.00
0.32
0.96
0.86
0.64
RIG108
5.97
3.83
0.09
0.00
3.81
0.88
0.28
0.00
0.00
84.41
0.00
0.10
0.64
0.71
0.00
RIG109
7.85
10.17
0.00
0.00
0.30
0.45
0.08
0.00
0.00
80.39
0.00
0.24
0.53
0.47
0.00
RIG110
8.45
12.66
0.39
0.00
0.13
1.02
0.12
0.25
0.00
75.62
0.00
0.00
0.54
0.53
0.81
RIH101
15.78
2.33
0.36
0.48
44.37
0.79
0.07
0.00
0.12
23.45
0.00
6.06
6.19
1.19
0.00
RIH102
3.44
1.96
0.00
0.00
0.16
0.79
0.25
0.00
0.00
92.28
0.14
0.32
0.66
0.56
0.00
RIH103
3.95
5.56
0.23
0.00
0.86
0.36
0.22
0.00
0.00
88.05
0.00
0.17
0.60
0.52
0.00
RIH104
4.78
0.00
0.05
0.00
0.21
1.24
0.39
0.00
0.00
92.06
0.00
0.18
1.09
1.20
0.00
RIH105
3.98
0.00
0.00
0.00
0.51
0.40
0.16
0.49
0.00
93.78
0.15
0.22
0.32
0.24
0.00
RIH106
3.60
3.26
0.12
0.08
3.99
0.52
0.44
0.00
0.00
86.37
0.09
0.82
0.70
0.63
0.00
RIH107
5.67
5.11
0.33
0.17
4.35
0.96
0.46
0.00
0.10
80.08
0.11
2.06
0.60
0.52
0.00
RIH108
3.40
2.68
0.33
0.00
0.24
0.56
0.07
0.00
0.00
92.24
0.00
0.00
0.48
0.36
0.00
RIH109
7.29
0.00
0.08
0.15
0.90
1.17
0.41
0.00
0.00
87.08
0.00
1.22
0.91
0.83
0.81
RIH110
5.28
7.28
0.33
0.19
2.50
1.66
0.82
0.00
0.11
77.84
0.16
2.42
0.83
0.65
0.59
273
Appendix 4.3: Results for the oneDWay ANOVA performed on all trace metals measured in the tests of samples from Robben Island
and St Helena Bay.
Appendix 4. 3.1:Results for the oneDWay ANOVA performed on the Magnesium concentration of the tests of each station in
Robben Island. The Tukey Honest Significant Difference (HSD) Test was performed to obtain a statistical significance,
df = 72, MS error = 0.047. Significant differences at p < 0.05 are in bold*
RIA
RIB
RIC
RID
RIE
RIF
RIG
RIH
Mean (wt %) 0.16
0.20
0.23
0.27
0.39
0.25
0.42
0.18
RIA
RIB
1.00
RIC
1.00
1.00
RID
0.96
1.00
1.00
RIE
0.31
0.52
0.75
0.92
RIF
0.99
1.00
1.00
1.00
0.85
RIG
0.15
0.30
0.52
0.75
1.00
0.65
RIH
1.00
1.00
1.00
0.99
0.43
1.00
0.23
274
Appendix 4.3.2: Results for the oneDWay ANOVA performed on the Cadmium concentration of the tests of each station in Robben
Island. The Tukey Honest Significant Difference (HSD) Test was performed to obtain a statistical significance, df = 72,
MS error = 0.0099. Significant differences at p < 0.05 *.
RIA
RIB
RIC
RID
RIE
RIF
RIG
RIH
Mean (wt %) 0.06
0.03
0.00
0.02
0.00
0.06
0.07
0.05
RIA
RIB
0.99
RIC
0.85
1.00
RID
0.99
1.00
1.00
RIE
0.85
1.00
1.00
1.00
RIF
1.00
1.00
0.90
0.99
0.90
RIG
1.00
0.99
0.83
0.98
0.83
1.00
RIH
1.00
1.00
0.96
1.00
0.96
1.00
1.00
275
Appendix 4.3.3: Results for the oneDWay ANOVA performed on the Calcium concentration of the tests of each station in Robben
Island. The Tukey Honest Significant Difference (HSD) Test was performed to obtain a statistical significance, df = 72,
MS error = 224.09. Significant differences at p < 0.05 *.
RIA
Mean (Wt %) 87.40
RIB
RIC
RID
RIE
RIF
RIG
RIH
80.19
76.39
80.18
69.19
86.06
83.00
81.32
RIA
RIB
0.96
RIC
0.72
1.00
RID
0.96
1.00
1.00
RIE
0.13
0.72
0.96
0.72
RIF
1.00
0.99
0.83
0.99
0.20
RIG
1.00
1.00
0.97
1.00
0.45
1.00
RIH
0.98
1.00
1.00
1.00
0.61
1.00
1.00
276
Appendix 4.3.4: Results for the oneDWay ANOVA performed on the Chromium concentration of the tests of each station in Robben
Island. The Tukey Honest Significant Difference (HSD) Test was performed to obtain a statistical significance, df = 72,
MS error = 0.01069. Significant differences at p < 0.05 *
Mean (Wt %)
RIA
RIB
RIC
RID
RIE
RIF
RIG
RIH
0.04
0.04
0.07
0.09
0.22
0.05
0.03
0.07
RIA
RIB
1.00
RIC
1.00
1.00
RID
0.97
0.97
1.00
RIE
0.00*
0.01*
0.03*
0.09
RIF
1.00
1.00
1.00
0.99
0.01*
RIG
1.00
1.00
0.99
0.89
0.00*
1.00
RIH
1.00
1.00
1.00
1.00
0.03*
1.00
0.99
277
Appendix 4.3.5: Results for the oneDWay ANOVA performed on the Iron concentration of the tests of each station in Robben Island.
The Tukey Honest Significant Difference (HSD) Test was performed to obtain a statistical significance, df = 72, MS
error = 34.9. Significant differences at p < 0.05 *.
Mean (Wt %)
RIA
RIB
RIC
RID
RIE
RIF
RIG
RIH
0.37
1.43
1.37
0.91
7.65
0.28
0.33
1.35
RIA
RIB
1.00
RIC
1.00
1.00
RID
1.00
1.00
1.00
RIE
0.12
0.28
0.27
0.19
RIF
1.00
1.00
1.00
1.00
0.11
RIG
1.00
1.00
1.00
1.00
0.12
1.00
RIH
1.00
1.00
1.00
1.00
0.26
1.00
1.00
278
Appendix 4.3.6: Results for the oneDWay ANOVA performed on the Copper concentration of the tests of each station in Robben
Island. The Tukey Honest Significant Difference (HSD) Test was performed to obtain a statistical significance, df = 72,
MS error = 1.189. Significant differences at p < 0.05 *.
Mean (Wt %)
RIA
RIB
RIC
RID
RIE
RIF
RIG
RIH
0.61
0.92
1.08
0.65
1.68
0.51
0.53
1.24
RIA
RIB
1.00
RIC
0.98
1.00
RID
1.00
1.00
0.99
RIE
0.36
0.76
0.91
0.41
RIF
1.00
0.99
0.94
1.00
0.26
RIG
1.00
0.99
0.95
1.00
0.27
1.00
RIH
0.90
1.00
1.00
0.92
0.98
0.81
0.83
279
Appendix 4.3.7: Results for the oneDWay ANOVA performed on the Copper concentration of the tests of each station in Robben
Island. The Tukey Honest Significant Difference (HSD) Test was performed to obtain a statistical significance, df = 72,
MS error = 0.392. Significant differences at p < 0.05 *.
RIA
RIB
RIC
RID
RIE
RIF
RIG
RIH
Mean (Wt %) 0.56
0.70
0.87
0.65
1.31
0.47
0.50
0.67
RIA
RIB
1.00
RIC
0.95
1.00
RID
1.00
1.00
0.99
RIE
0.15
0.37
0.77
0.28
RIF
1.00
0.99
0.84
1.00
0.07
RIG
1.00
1.00
0.88
1.00
0.09
1.00
RIH
1.00
1.00
1.00
1.00
0.32
1.00
1.00
280
Appendix 4.3.8: Results for the oneDWay ANOVA performed on the Lead concentration of the tests of each station in Robben Island.
The Tukey Honest Significant Difference (HSD) Test was performed to obtain a statistical significance, df = 72, MS
error = 0.561. Significant differences at p < 0.05 *.
SITE
RIA
RIB
RIC
RID
RIE
RIF
RIG
RIH
0.15
0.08
0.64
0.39
0.84
0.06
0.32
0.14
RIA
RIB
1.00
RIC
0.83
0.70
RID
1.00
0.98
1.00
RIE
0.46
0.32
1.00
0.88
RIF
1.00
1.00
0.66
0.97
0.29
RIG
1.00
1.00
0.98
1.00
0.78
0.99
RIH
1.00
1.00
0.81
1.00
0.44
1.00
1.00
281
Appendix 4.3.9: Results for the oneDWay ANOVA performed on the trace metals and Ca and Mg concentration of the tests of the
control (CRI) and pipeline (PRI) sites in Robben Island. The Tukey Honest Significant Difference (HSD) Test was
performed to obtain a statistical significance, df = 72, MS error = 0.561. Significant differences at p < 0.05*.
Mg
Cd
Ca
Cr
Site
Mean
p
MS Error Mean
p
MS Error Mean
p
MS Error Mean
p
MS Error
CRI
0.285
0.49
0.051
0.131
0.009
0.17
230.88
0.09
0.013
PRI
0.249
0.023
78.67
0.089
Fe
Cu
Zn
Pb
0.057
83.46
0.045
Site
Mean
p
MS Error Mean
p
MS Error Mean
p
MS Error Mean
p
MS Error
CRI
0.653
0.23
36.92
0.383
1.238
0.06
0.41
0.161
0.575
PRI
2.234
0.76
0.985
0.54
0.817
0.171
0.418
282
Appendix 4.3.10: Results for the oneDWay ANOVA performed on the Magnesium concentration of the tests of each station in St
Helena Bay. The Tukey Honest Significant Difference (HSD) Test was performed to obtain a statistical significance, df
= 99, MS error = 0.106. Significant differences at p < 0.05*
Mean (Wt %)
SHA
SHB
SHC
SHD
SHE
SHF
SHG
SHH
SPA
SPB
SPC
0.374
0.145
0.626
0.447
0.509
0.448
0.434
0.746
0.312
0.376
0.244
SHA
SHB
0.889
SHC
0.814
0.048*
SHD
1.000
0.596
0.977
SHE
0.997
0.315
0.999
1.000
SHF
1.000
0.591
0.978
1.000
1.000
SHG
1.000
0.657
0.963
1.000
1.000
1.000
SHH
0.284
0.004*
0.999
0.610
0.865
0.615
0.548
SPA
1.000
0.986
0.538
0.997
0.956
0.997
0.999
0.113
SPB
1.000
0.883
0.822
1.000
0.998
1.000
1.000
0.292
1.000
SPC
0.998
1.000
0.249
0.947
0.764
0.945
0.966
0.032
1.000
0.998
283
Appendix 4.3.11: Results for the oneDWay ANOVA performed on the cadmium concentration of the tests of each station in St Helena
Bay. The Tukey Honest Significant Difference (HSD) Test was performed to obtain a statistical significance, df = 99,
MS error = 0.004. Significant differences at p < 0.05 *.
SHA
Mean (Wt %) 0.000
SHB
SHC
SHD
SHE
SHF
SHG
SHH
SPA
SPB
SPC
0.069
0.000
0.058
0.000
0.019
0.013
0.000
0.018
0.000
0.035
SHA
SHB
0.393
SHC
1.000
0.393
SHD
0.652
1.000
0.652
SHE
1.000
0.393
1.000
0.652
SHF
1.000
0.821
1.000
0.959
1.000
SHG
1.000
0.698
1.000
0.899
1.000
1.000
SHH
1.000
0.393
1.000
0.652
1.000
1.000
1.000
SPA
1.000
0.803
1.000
0.951
1.000
1.000
1.000
1.000
SPB
1.000
0.393
1.000
0.652
1.000
1.000
1.000
1.000
1.000
SPC
0.981
0.984
0.981
0.999
0.981
1.000
1.000
0.981
1.000
0.981
284
Appendix 4.3.12: Results for the oneDWay ANOVA performed on the calcium concentration of the tests of each station in St Helena
Bay. The Tukey Honest Significant Difference (HSD) Test was performed to obtain a statistical significance, df = 99,
MS error = 310.85. Significant differences at p < 0.05 *.
Mean (Wt %)
SHA
SHB
SHC
SHD
SHE
SHF
SHG
SHH
SPA
SPB
SPC
79.952
85.786 72.308 68.513 66.581 57.723 74.575 38.931 77.995 69.880 79.983
SHA
SHB
1.000
SHC
0.996
0.827
SHD
0.932
0.517
1.000
SHE
0.834
0.355
1.000
1.000
SHF
0.166
0.023* 0.747
0.953
0.988
SHG
1.000
0.940
1.000
0.995
SHH
0.000*
0.000* 0.003* 0.013* 0.027* 0.388
0.001*
SPA
1.000
0.996
1.000
0.981
0.933
0.278
1.000
0.000*
SPB
0.971
0.638
1.000
1.000
1.000
0.902
1.000
0.007* 0.994
SPC
1.000
1.000
0.996
0.931
0.832
0.165
1.000
0.000* 1.000
1.000
0.554
0.970
285
Appendix 4.3.13: Results for the oneDWay ANOVA performed on the chromium concentration of the tests of each station in St Helena
Bay. The Tukey Honest Significant Difference (HSD) Test was performed to obtain a statistical significance, df = 99,
MS error = 0.0070. Significant differences at p < 0.05 *.
SHA
SHB
SHC
SHD
SHE
SHF
SHG
SHH
SPA
SPB
SPC
Mean (Wt %) 0.03
0.03
0.026
0.71
0.83
0.054
0.046
0.124
0.078
0.063
0.023
SHA
SHB
1.00
SHC
1.00
1.00
SHD
0.99
0.99
0.98
SHE
0.94
0.94
0.91
1.00
SHF
1.00
1.00
1.00
1.00
1.00
SHG
1.00
1.00
1.00
1.00
1.00
1.00
SHH
0.31
0.31
0.25
0.94
0.99
0.73
0.59
SPA
0.97
0.97
0.95
1.00
1.00
1.00
1.00
0.98
SPB
1.00
1.00
1.00
1.00
1.00
1.00
1.00
0.87
1.00
SPC
1.00
1.00
1.00
0.97
0.88
1.00
1.00
0.22
0.93
0.99
286
Appendix 4.3.14: Results for the oneDWay ANOVA performed on the iron concentration of the tests of each station in St Helena Bay.
The Tukey Honest Significant Difference (HSD) Test was performed to obtain a statistical significance, df = 99, MS
error = 7.69. Significant differences at p < 0.05 are in bold*
SHA
Mean (Wt %)
SHB
SHC
1.514 1.081 2.47
SHD
SHE
SHF
SHG
SHH
SPA
SPB
SPC
3.169 4.643 2.804 3.678 6.979 1.313 2.031 2.086
SHA
SHB
1.000
SHC
1.000 0.989
SHD
0.960 0.840 1.000
SHE
0.304 0.147 0.804 0.982
SHF
0.994 0.948 1.000 1.000 0.922
SHG
0.808 0.584 0.996 1.000 0.999 1.000
SHH
0.001* 0.000* 0.018* 0.091 0.726 0.041* 0.233
SPA
1.000 1.000 0.997 0.918 0.222 0.981 0.711 0.001*
SPB
1.000 1.000 1.000 0.998 0.576 1.000 0.962 0.006* 1.000
SPC
1.000 0.999 1.000 0.999 0.607 1.000 0.970 0.007* 1.000 1.000
287
Appendix 4.3.15: Results for the oneDWay ANOVA performed on the copper concentration of the tests of each station in St Helena
Bay. The Tukey Honest Significant Difference (HSD) Test was performed to obtain a statistical significance, df = 99,
MS error = 0.113. Significant differences at p < 0.05 are in bold*
Mean (Wt %)
SHA
SHB
SHC
SHD
SHE
SHF
SHG
SHH
SPA
SPB
SPC
0.579
0.549
0.746
0.757
0.492
0.772
0.553
1.442
0.662
0.444
0.628
SHA
SHB
1.000
SHC
0.989
0.965
SHD
0.983
0.950
1.000
SHE
1.000
1.000
0.838
0.800
SHF
0.970
0.922
1.000
1.000
0.741
SHG
1.000
1.000
0.970
0.956
1.000
0.931
SHH
0.000
0.000
0.001
0.001
0.000
0.001
0.000
SPA
1.000
1.000
1.000
1.000
0.989
1.000
1.000
0.000
SPB
0.998
1.000
0.645
0.594
1.000
0.525
1.000
0.000
0.936
SPC
1.000
1.000
0.999
0.999
0.998
0.997
1.000
0.000
1.000
0.978
288
Appendix 4.3.16: Results for the oneDWay ANOVA performed on the zinc concentration of the tests of each station in St Helena Bay.
The Tukey Honest Significant Difference (HSD) Test was performed to obtain a statistical significance, df = 99, MS
error = 0.0754. Significant differences at p < 0.05 *.
Mean
SHA
SHB
SHC
SHD
SHE
SHF
SHG
SHH
SPA
SPB
SPC
0.449
0.475
0.693
0.682
0.481
0.73
0.51
1.172
0.591
0.398
0.562
SHA
SHB
1.000
SHC
0.658
0.791
SHD
0.717
0.839
1.000
SHE
1.000
1.000
0.818
0.862
SHF
0.450
0.596
1.000
1.000
0.630
SHG
1.000
1.000
0.920
0.945
1.000
SHH
0.000* 0.000* 0.008* 0.006* 0.000* 0.020* 0.000*
SPA
0.986
0.997
0.999
1.000
0.998
0.988
1.000
0.001*
SPB
1.000
1.000
0.376
0.433
1.000
0.213
0.998
0.000* 0.890
SPC
0.998
1.000
0.992
0.996
1.000
0.953
1.000
0.000* 1.000
0.782
0.960
289
Appendix 4.3.17: Results for the oneDWay ANOVA performed on the lead concentration of the tests of each station in St Helena Bay.
The Tukey Honest Significant Difference (HSD) Test was performed to obtain a statistical significance, df = 99, MS
error = 0.422. Significant differences at p < 0.05 *.
Mean (Wt %)
SHA
SHB
SHC
SHD
SHE
SHF
SHG
SHH
SPA
SPB
SPC
0.708
0.322
0.219
0.266
0.395
0.369
0.393
0.584
0.52
0.152
0.631
SHA
SHB
0.962
SHC
0.841
1.000
SHD
0.910
1.000
1.000
SHE
0.992
1.000
1.000
1.000
SHF
0.985
1.000
1.000
1.000
1.000
SHG
0.991
1.000
1.000
1.000
1.000
1.000
SHH
1.000
0.998
0.974
0.991
1.000
1.000
1.000
SPA
1.000
1.000
0.994
0.999
1.000
1.000
1.000
1.000
SPB
0.708
1.000
1.000
1.000
0.999
1.000
0.999
0.921
0.972
SPC
1.000
0.992
0.941
0.974
0.999
0.998
0.999
1.000
1.000
0.858
290
Appendix 4.3.18: Results for the oneDWay ANOVA performed on the trace metals and Ca and Mg concentration of the tests of the
control (CSH) and pipeline (PSH) sites in St Helena Bay. The Tukey Honest Significant Difference (HSD) Test was
performed to obtain a statistical significance, df =99. Significant differences at p < 0.05 *.
Mg
Cd
Ca
Cr
Site
Mean
p
MS
Mean
p
MS
Mean
p
MS
Mean
p
MS
CSH
0.31
0.036*
0.117
0.017
0.877
0.0044
75.95
0.07
426.72
0.054
0.855
0.007
PSH
0.466
0.019
68.04
0.058
Fe
Cu
Zn
Pb
Site
Mean
p
MS
Mean
p
MS
Mean
p
MS
Mean
p
MS
CSH
1.81
0.025*
9.356
0.577
0.07
0.166
0.517
0.064
0.108
0.434
0.843
0.416
PSH
3.29
0.736
0.649
0.407
291
Appendix 4.3.19: Results for the oneDWay ANOVA performed on the trace metals and Ca and Mg concentration of the tests of the St
Helena Bay (SH) and Robben Island (RI). The Tukey Honest Significant Difference (HSD) Test was performed to
obtain a statistical significance, df =188. Significant differences at p < 0.05*.
Mg
Cd
Ca
Cr
Site
Mean
p
MS Error Mean
p
MS Error Mean
p
MS Error Mean
p
MS Error
SH
0.424
0.0003
0.092
0.164
0.0066
0.0001
350.47
0.276
0.009
RI
0.263
0.035
80.467
0.072
Fe
Cu
Zn
Pb
0.019
70.202
0.058
Site
Mean
p
MS Error Mean
p
MS Error Mean
p
MS Error Mean
p
MS Error
SH
2.888
0.082
21.232
0.071
0.617
0.155
0.241
0.384
0.484
RI
1.712
0.693
0.901
0.613
0.715
0.414
0.326
292
rashieda Toefy