An Assessment of the Ecological Quality of the Tidal Freshwater sections of Transitional Waters (TFTW) in the Republic of Ireland By Noelle Dunne Student number: 13314616 Supervisors: Professor James Wilson and Dr. Michelle Giltrap M.Sc. Biodiversity and Conservation Word Count: 13,775
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An Assessment of the Ecological Quality of the Tidal
Freshwater sections of Transitional Waters (TFTW)
in the Republic of Ireland
By Noelle Dunne
Student number: 13314616
Supervisors: Professor James Wilson and Dr. Michelle Giltrap
M.Sc. Biodiversity and Conservation
Word Count: 13,775
Declaration
I hereby acknowledge that this dissertation is entirely my own work. It has not been
submitted as an exercise for a degree at this or any other University. I authorise the Library
at Trinity College Dublin to lend or copy the dissertation upon request to other institutes or
individuals for the purpose of scholarly research. I further authorise that Trinity College
Dublin to reproduce this thesis by photocopying or other means for study purposes subject
to the normal conditions of acknowledgement.
Signature:
i
Acknowledgements
I would sincerely like to thank Professor James Wilson and Dr. Michelle Giltrap for all their
dedicated guidance and assistance throughout this entire project. I would also like to thank
Trinity College Dublin for the brilliant facilities provided by the Library, Post Graduate
Research Room and the excellent laboratory facilities in the Zoology department, all of which
were essential for the fulfilment of my dissertation. Regarding lab equipment I would like to
thank Peter Stafford and Allison Boyce for all of their assistance. Furthermore I owe a great
deal of gratitude to my mother, Josephine Dunne, for all of her advice and support
throughout the entire academic year. I truly would not have been able to complete my MSc
in Biodiversity and Conservation without her.
ii
Abstract
The Water Framework Directive (WFD) is currently the primary legislation for monitoring
water quality throughout Europe with the goal for all water bodies to achieve at least good
ecological status by 2015.The tidal freshwater section of transitional waters (TFTW) and
transitional waters in general are seldom studied in Ireland The EPA has ranked them
amongst Europe’s top five water quality conditions. The term is used to describe the areas of
water between fresh and coastal waters. In accordance with the WFD, the status of
European surface waters is to be assessed using aquatic organism groups such as
macroinvertebrates. Biotic indices are used globally for determining the quality of an
ecosystem by examining the types of organisms present within the area.
This study aimed to assess various transitional water bodies in the Republic of Ireland in
order to gain an understanding of the macroinvertebrate community structure within the
ecosystems. A variety of rivers ranging from polluted to pristine water quality conditions were
assessed including the rivers Tolka, Barrow, Slaney, Lee, Bandon, Gweebarra, Munster
Blackwater and Suir. The rivers were sampled via kick, cores and grabs to demonstrate the
fauna present throughout different zones within the rivers. Widely used biotic indices
(Shannon-Wiener, BMWP, ASPT, EPT taxa richness, Q-values, AMBI and M-AMBI) were
used to establish which ones (if any) best describe the macrobenthic fauna and water quality
status in transitional waters. Considering salinity levels are known to significantly impact the
composition of invertebrate fauna, analysis was carried out to determine if high, medium and
low salinity levels impact macrobenthic community structure.
A wide range of invertebrate taxa were found within the TFTWs primarily consisting of
freshwater species, although marine species were also well represented. The biotic indices
varied greatly in their classifications of water qualities and rarely agreed with one another.
The indices assessed only represented fractions of the invertebrate species encountered
demonstrating the need for an index which comprises both marine and freshwater benthic
fauna such as the Infaunal Quality Index (IQI) which was developed specifically to assess
the transitional waters in the UK and Ireland. Salinity levels were shown to greatly impact the
macrobenthic community structure with diversity tending to decrease with increasing
salinities. The results for this study show that a multivariate index incorporating a wide
variety of metrics would be best to assess the transitional water ways for both pollution and
salinity fluctuations.
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Table of Contents
Acknowledgements …………………………………………………………………………….. i
Figure 9. AMBI results for the 8 sites assessed via grab samples showing pollution status and biotic index values.
Undisturbed
Slightly disturbed
Moderately disturbed
Heavily disturbed
Extremely disturbed
40
Figure 10. M-AMBI results showing the biotic indices and WFD interpreted water qualities for the 8 sites
assessed via grab samples.
41
3.2.6 Summary of Biotic Indices
Over all the biotic indices rarely agreed with each other throughout the assessment. The
Shannon-Wiener Diversity indices indicated the lowest water quality for all of the sites
assessed. The BMWP and associated ASPT mostly showed different water quality statuses
along with the AMBI and M-AMBI; however less of a difference was observed with the latter
indices. The kick samples taken for the rivers Lee, Slaney and Barrow show the highest
classifications for all of the indices used. Both the sample size and diversity for the core and
grabs was much lower than the kick samples which resulted in lower classifications by the
biotic indices. The calculation, taxa scoring mechanisms and inclusion/exclusion of taxa for
these indices likely reflect the observed disagreements.
Site Slaney Barrow Gweebarra Tolka Blackwater Bandon Lee Suir
Method K C G K C G K C G K C G K C G K C G K C G K C G
H' BMWP ASPT EPT Q-Values AMBI M-AMBI
Table 13. Summary of biotic indices showing average scores for all rivers with kicks (K), cores (C), and grabs
(G). The colours indicate the ecological quality of each site with blue representing bad, green poor, red
moderate, purple good and yellow high.
42
3.3 Statistical Analysis
3.3.1 Cluster Analysis for Similarities
In order to determine similarities among samples within estuaries a cluster analysis was
carried out including the salinity ranges as factors. For this the Bray-Curtis similarity
coefficient was calculated on the square root transformed data for the kick, core and grab
samples. These values were then used to form a dendogram which illustrates clusters based
upon group averages.
For the kick samples the dendogram produced five main clusters grouping the sites based
on their similarities (Figure 11).
Figure 11. Dendogram illustrating the similarities between the 11 sites assessed via kick samples using the Bray-
Curtis similarity coefficient on square root transformed data with the salinity groups as factors with Low <1,
Medium 3-5 and High 27.
For the kick samples the salinity ranges were quite similar with only one site (GWEE-A) in
the high group of 27, two sites in the medium group 3-5 and the remaining nine sites in the
low group of less than 1. Working up the dendogram the two Gweebarra sites (GWEE-A &
B) form the first cluster showing a low similarity of 15% relating to the low species richness.
The second cluster includes four sites in which the two Barrow sites (BAR-H & E) are
together with a similarity of 70% along with two Slaney sites (SLA-D & C) at 77%. These
sites were clustered together because of the presence of Oligochaetes, Chironomids and the
mayfly Ephemerella ignita. Cluster three incorporates the rivers Tolka (TO-A) and Munster
Blackwater (BWA-I) with a high similarity of 70% which is due to the large abundances of
Oligochaetes found at these sites. These two sites represent 50% of the total Oligochaete
Kick SamplesGroup average
SLA-A
LEE-B
BAN-A
TO-A
BWA-I
SLA-C
SLA-D
BAR-H
BAR-E
GWEE-A
GWEE-B
Sa
mp
les
100 80 60 40 20 0
Similarity
Transform: Square root
Resemblance: S17 Bray Curtis similarity
SalinityMedium
Low
High
43
abundances found at all sites for the kick samples. Cluster four joined the rivers Lee (LEE-B)
and Bandon (BAN-A) at 50% which is related to similar species diversity. The final Slaney
site (SLA-A) was shown to have a low similarity to SLA-C (39%) and SLA-D (44%) mostly
relating to the low abundances found here.
The following dendogram illustrates the similarities found among the core samples with
salinity groups of Low <1, Medium 2-6 and High 13-27 across the 22 sites sampled (Figure
12).
Figure 12. Dendogram illustrating the similarities between the 22 sites assessed via core samples using the
Bray-Curtis similarity coefficient on square root transformed data with the salinity groups as factors with Low <1,
Medium 2-6 and High 13-27.
The dendogram identifies six main clusters with the core samples. Working up the
dendogram the first main cluster groups five sites at 50% similarity. These were all grouped
together because the subclass Oligochaeta dominates each site within the cluster at low
abundances ranging from 10-60 individuals. The second cluster includes a further five sites
which were also grouped together based on the larger Oligochaete abundances ranging
from 220-1000 individuals at a similarity of 40%. Cluster three includes the only Gweebarra
site (GWEE-A) showing no similarity to other groups. This is the only site which was largely
dominated by the crustacean Corophium multisetosum. Cluster four includes the three
remaining Slaney sites which are grouped together at 25% based on their high abundances
of the mayfly Ephemerella ignita (which were only found at the Slaney sites) and
Core Samples
Group average
BAN-D
BAN-B
BAN-E
SUIR-B
BAN-C
SUIR-G
SUIR-E
BAR-B
SLA-B
SLA-C
SLA-D
GWEE-A
SUIR-C
BAR-D
TO-A
BAR-A
BAR-C
SUIR-D
BAR-F
SLA-A
SUIR-A
BAR-E
Sam
ple
s
100 80 60 40 20 0
Similarity
Transform: Square root
Resemblance: S17 Bray Curtis similarity
SalinityLow
Medium
High
44
Oligochaetes. Cluster five forms at 20% including SUIR-B, C and D as well as BAN-C and
BAR-B which all had the lowest abundances and diversity of species primarily comprising of
Oligochaetes. The final cluster grouped the remaining river Bandon sites together at a lower
similarity level of approximately 15% based on the presence of polychaetes from the family
Nereidae which only occurred at BAN-B,D &E as well as GWEE-A in the core samples.
The grab samples had much lower species richness and abundance in comparison to the
kick and core samples. The dendogram for the grab samples highlights two main clusters
with one large cluster linking them together (Figure 13).
Figure 13. Dendogram illustrating the similarities between the 8 sites assessed via grab samples using the Bray-
Curtis similarity coefficient on square root transformed data with the salinity groups as factors with Low <1 and
Medium 5.
For the grab samples two main clusters are identified. Cluster one has grouped BWA-E,
BWA-G, SLA-A, and BAR-E together at a similarity level of 20%. Within this cluster the two
Munster Blackwater sites are clustered together with a similarity of 32% which is based on
extremely low species diversity and abundances. The BAR-E and SLA-A are grouped at
40% primarily due to the high number of Oligochaetes. Cluster two encompasses the
remaining Blackwater sites at 37% with A & B showing 48% similarity and C & D with 55%
similarity. These four sites are clustered together because of the presence of the gastropod
Potamopyrgus jenkinsi which occurs in high numbers at sites A & B (88) and low numbers at
sites C & D (17).
Grab SamplesGroup average
BWA-C
BWA-D
BWA-A
BWA-B
BAR-E
SLA-A
BWA-E
BWA-G
Sam
ple
s
100 80 60 40 20 0
Similarity
Transform: Square root
Resemblance: S17 Bray Curtis similarity
SalinityLow
Medium
45
3.3.2 MDS Analysis for Similarities
A non-parametric multidimensional scaling (MDS) analysis was carried out for the kick, core
and grab samples to graphically demonstrate the relationships between the sites and
demonstrate the inclusion of the >1 salinity factor in linking sites. For this analysis, the
similarities between sites, community structure and salinity groups were computed using the
Bray-Curtis similarity coefficient on the fourth root transformed abundance data, displaying
the data in 2-dimensional plots.
For the kick samples the MDS ordination plot groups the sites together at similarity levels of
20, 40 and 60 percent (Figure 14).
Figure 14. 2-dimensional MDS plot using Bray-Curtis similarity coefficient on fourth root transformed abundance
data for the 11 sites assessed via kick samples across three salinity groups, Low <1, Medium 3-5, and High 27.
As with the dendogram, both Gweebarra sites are grouped alone, as these showed the least
similarity to the other sites. The remaining sites formed one large group at a similarity of
20%, followed by four groups at 40%. SLA-A was grouped alone here because it had much
lower species abundances then the other two Slaney sites. The 60% similarity formed three
main groups which grouped the two Barrow sites together, the two remaining Slaney sites
and the rivers Tolka and Munster Blackwater which is similar to the dendogram. The Lee
and Bandon were grouped together at 40% as they had a similarity of 50%.
Kick SamplesTransform: Fourth root
Resemblance: S17 Bray Curtis similarity
SalinityMedium
Low
High
Similarity20
40
60
TO-A
LEE-B
GWEE-A
GWEE-B
BAN-A
BWA-I
BAR-HBAR-E
SLA-ASLA-CSLA-D
2D Stress: 0.07
46
Considering the similarity levels were much lower among the core samples the similarity was
fixed at 10, 30 and 50 percent as these best described the data graphically (Figure 15).
Figure 15. 2-dimensional MDS plot using Bray-Curtis similarity coefficient on fourth root transformed abundance
data for the 22 sites assessed via core samples across three salinity groups, Low <1, Medium 2-6, and High 13-
27.
As with the dendogram one major group was formed at a similarity level of 10%, followed by
four groups at 30% and six main groups at 50% which are illustrated with more clarity via the
2-dimensional plot.
Core SamplesTransform: Fourth root
Resemblance: S17 Bray Curtis similarity
SalinityLow
Medium
High
Similarity10
30
50
TO-A
SUIR-A
SUIR-B
SUIR-C
SUIR-D
SUIR-E
SUIR-G
SLA-A
SLA-B
SLA-C
SLA-D
BAR-A
BAR-B
BAR-C
BAR-D
BAR-E
BAR-F
GWEE-A
BAN-B
BAN-C
BAN-D
BAN-E
2D Stress: 0.14
47
For the grab samples the 2-dimensional MDS plot showed that similarities of 30, 40 and 50
percent best fit the data (Figure 16).
Figure 16. 2-dimensional MDS plot using Bray-Curtis similarity coefficient on fourth root transformed abundance
data for the 8 sites assessed via kick samples across two salinity groups, Low <1 and Medium 5.
The three main groups found on the dendogram are show to group together at 30%. The
Munster Blackwater sites C and D show the greatest similarity here at 50%, followed by
BWA-A and BWA-B at 40%. The remaining sites are grouped together 30% similarity. There
is much less similarity observed between the grab samples.
Grab SamplesTransform: Fourth root
Resemblance: S17 Bray Curtis similarity
SalinityLow
Medium
Similarity30
40
50BAR-E
BWA-A
BWA-B
BWA-C
BWA-D
BWA-E
BWA-G
SLA-A
2D Stress: 0.07
48
3.3.3 ANOSIM for Salinity Groups
In order to determine statistically significant similarities between the community structures
and salinity groups an analysis of similarities (ANOSIM) was carried out for all sampling
methods. The maximum permutations were set at 999 for all the sampling methods. The
ANOSIM test showed that there were strong positive linear relationships between the
community structure and differing salinity groups for the kick samples. The overall global R
value was 0.846 with a significance level of p<0.2%. A total of 495 permutations were
carried out (Table 14).
Groups
R-Significance
Statistic Significance
Level % Actual
Permutations Number
Observed
Low ,High 1 11.1 9 1
Low, Medium 0.75 2.2 45 1
High, Medium 1 33.3 3 1
Table 14. Pairwise tests calculated by ANOSIM with a maximum of 999 permutations for the kick samples via
one-way ANOVA for the 11 sites across three salinity ranges Low <1, Medium 3-5 and High 27.
For all salinity groups the R-statistic value is closer to one than zero, therefore the null
hypothesis that there is no difference in community structure among the salinity groups must
be rejected. The greatest differences are seen when comparing the high salinity groups with
the medium and low groups. This can best be explained by the lack of species found in the
only high salinity site, Gweebarra-A, which only had two species present. These both show
an optimum R value of 1 which indicates a complete difference in community structure
between the two salinity groups. In terms of p-values a significant difference is only found
between the Low, Medium groups with a significance level of 2.2% which is less than 0.05.
As outlined by Clarke and Gorley (2006) low significance levels must be interpreted carefully
because they are very dependent on the number of replicates carried out which are quite low
for the Low, High (9) and High, Medium (3) groups. A low number of replicates may result in
a large R-value and thus a large p-value which indicates that it is more useful to interpret the
R-values in this case (Clarke and Gorley, 2006). Therefore, for the kick samples there is a
significant difference between the community structure and salinity levels.
49
The ANOSIM results for the core samples showed a global R value of 0.078 with a
significance level of 22.8% (Table 15).
Groups
R-Significance
Statistic Significance
Level % Actual
Permutations Number
Observed
Low, Medium 0.075 26.9 999 268
Low, High 0.086 28.8 153 44
Medium, High -0.214 73.3 15 11
Table 15. Pairwise tests calculated by ANOSIM with a maximum of 999 permutations for the core samples via
one-way ANOVA for the 22 sites across three salinity ranges Low <1, Medium 2-6 and High 13-27.
Looking at the R-statistic the group Medium, High shows a very strong negative linear
relationship between community structure and salinity groups. The sites with Low, Medium
and Low, High salinities show almost no linear relationship between the variables as the R-
statistic is close to zero. The R values for all sites are closer to zero than one therefore the
null hypothesis must be accepted indicating that there is no difference between the variables
being tested. The significance levels for all sights did not exhibit any differences either as all
p-values were greater than 0.05. In accordance with the advice described by Clarke and
Gorley (2006) the pairwise comparisons are not significant and should not be interpreted
because the null hypothesis was not rejected.
Considering the salinity groups for the grab samples were not differing with only one site
(SLA-A) representing the medium group and the rest low the ANOSIM test could not be
carried out effectively. This is also related to the lack of species richness and abundances
found with the grab samples. The test results showed a global R value of 0.109 suggesting
there were little differences in community structure between the two salinity groups. The
significance level of the sample was at 50% which is far greater than the acceptable p-
values of less than 0.05.
50
3.3.4 SIMPER Analysis between Salinity Groups
Kick Samples
A Similarity Percentage analysis (SIMPER) was carried out to identify the species which
contributed the most to the differences found between the sample groups. For the kick
samples the groups with salinities of Low and High showed the greatest dissimilarity with a
complete average dissimilarity of 100% (Table 16). The subclass Oligochaeta contributed to
the highest average dissimilarity of 20.5% followed by Mysis relicta 13.1%, the family
Chironomidae at 10.1% and Gammarus duebeni accounting for 51% of the overall
dissimilarity. A further 22 species made up the rest of the dissimilarity seen between the
groups.
Species
Group Low Avg.
Abundance
Group High Avg.
Abundance Contribution
% Cumulative
%
Subclass Oligochaeta 19.2 0.0 20.5 20.5
Mysis relicta 0.0 11.3 13.1 33.6
Chironomidae 8.9 0.0 10.1 43.7
Gammarus duebeni 7.7 0.0 6.9 50.6
Table 16. SIMPER analysis displaying the Low (<1) and High (27) salinity groups with an average dissimilarity of
100% highlighting the primary contributing species for the 11 sites assessed via kick samples.
For the samples grouped High and Medium an average dissimilarity of 86.5% (Table 17)
was computed by the SIMPER analysis with Mysis relicta, subclass Oligochaeta, Gammarus
duebeni and Gammarus pulex accounting for the highest dissimilarities with a cumulative
percent of 61%. The remaining 9 species described the rest of the dissimilarities.
Species
Group High Avg.
Abundance
Group Medium
Avg. Abundance
Contribution %
Cumulative %
Mysis relicta 11.3 1.3 35.6 35.6
Subclass Oligochaeta 0.0 4.2 12.8 48.4
Gammarus duebeni 0.0 2.4 6.5 54.9
Gammarus pulex 2.0 1.9 6.4 61.3
Table 17. SIMPER analysis displaying the High (27) and Medium (3-5) salinity groups with an average
dissimilarity of 86.5% highlighting the primary contributing species for the 11 sites assessed via kick samples.
51
The samples grouped Low and Medium showed the lowest average dissimilarity of the
groups at 81.3% (Table 18). The species which contributed the most to this dissimilarity
were the subclass Oligochaeta, Chironomidae, Gammarus duebeni and Ephemerella ignita
which gave a cumulative percent of 42%. A remaining 29 species accounted for the rest of
the dissimilarities.
Species
Group Low Avg.
Abundance
Group Medium
Avg. Abundance
Contribution %
Cumulative %
Subclass Oligochaeta 19.2 4.2 19.3 19.3
Chironomidae 8.9 1.4 9.7 29.0
Gammarus duebeni 7.7 2.4 7.5 36.5
Ephemerella ignita 4.9 0.9 5.49 42.0
Table 18. SIMPER analysis displaying the Low (<1) and Medium (3-5) salinity groups with an average
dissimilarity of 81.3% highlighting the primary contributing species for the 11 sites assessed via kick samples.
52
MDS plots were established to demonstrate the distribution of the species which contributed
most to the noted dissimilarities between sites described by the SIMPER analysis (Figures
17-18).
Figure 17. MDS plot showing the square root transformed abundances of the subclass Oligochaeta which
contributed most to the dissimilarities over the salinity groups (High-27, Medium- 3-5 and Low- <1) using Bray-
Curtis similarity coefficient for the kick samples.
The plot clearly illustrates that the Oligochaetes were in highest numbers for the low
salinities and completely absent from the high salinity site GWEE-A. The two groups outlined
by the red circle show the sites with the greatest numbers of Oligochaetes which are the
rivers Tolka (TO-A) and Munster Blackwater (BWA-I).
Kick SamplesTransform: Square root
Resemblance: S17 Bray Curtis similarity
Subclass Oligochaeta
5
20
35
50
Low
Low
High
Medium
Low
Low
LowLow
Medium
LowLow
2D Stress: 0.03
53
Figure 18. MDS plot showing the square root transformed abundances of the Gammarus duebeni which
contributed most to the dissimilarities over the salinity groups (High-27, Medium- 3-5 and Low- <1) using Bray-
Curtis similarity coefficient for the kick samples.
Figure 18 shows that the abundances for Gammarus duebeni were also highest in the low
salinity groups and they were also completely absent from the high salinity group (GWEE-A)
along with one medium group GWEE-B and two low groups LEE-B, BWA-I and BAN-A. The
abundances were highest at TO-A and BAR-H showing a maximum of 212.
Kick SamplesTransform: Square root
Resemblance: S17 Bray Curtis similarity
Gammarus duebeni
3
12
21
30
Low
Low
High
Medium
Low
Low
LowLow
Medium
LowLow
2D Stress: 0.03
54
Core Samples
Although there were no statistically significant differences found in relation to community
structure and salinity groups for the core samples, SIMPER analysis was carried out to
demonstrate the species that contributed most to the dissimilarities between the groups. The
highest dissimilarity was seen for the salinity groups Medium and High with 69% (Table 19).
Here the species which contributed mostly to the differences were Corophium multisetosum
(23.5%), subclass Oligochaeta (22%), the families Nereidae (19.4%) and Chironomidae
(17.6%) adding up to a cumulative of 82.5%.
Species
Group Medium
Avg. Abundance
Group High Avg.
Abundance Contribution
% Cumulative
%
Corophium multisetosum 0 1.9 23.5 23.5
Subclass Oligochaeta 1.3 1.9 22.1 45.5
Nereidae 0.6 1.1 19.4 64.9
Chrionomidae 0.0 0.5 17.6 82.5
Table 19. SIMPER analysis displaying the Medium (2-6) and High (13-27) salinity groups with an average
dissimilarity of 69% highlighting the primary contributing species for the 22 sites assessed via core samples.
The Low and High salinity groups showed an average dissimilarity of 63% with the subclass
Oligochaeta (26.4%), Corophium multisetosum (23.2%), the families Nereidae (16.2%) and
Chironomidae (15.1%) contributing a cumulative 80.9% of the dissimilarities (Table 20).
Species
Group Low Avg.
Abundance
Group High Avg.
Abundance Contribution
% Cumulative
%
Corophium multisetosum 2.5 1.9 26.4 26.4
Subclass Oligochaeta 0.2 1.9 23.2 49.6
Nereidae 0.3 1.1 16.2 65.8
Chrionomidae 0.5 0.5 15.1 80.9
Table 20. SIMPER analysis displaying the Low (<1) and High (13-27) salinity groups with an average dissimilarity
of 63% highlighting the primary contributing species for the 22 sites assessed via core samples.
55
The Low and Medium groups showed an average dissimilarity of 68.1% with the subclass
Oligochaeta (36.5%), Nereidae (14.3%), Chironomidae (8.4%) and Ephemerella ignita(7.3%)
contributing to 66.5% of the overall differences between the groups (Table 21).
Species
Group Low Avg.
Abundance
Group Medium
Avg. Abundance
Contribution %
Cumulative %
Subclass Oligochaeta 2.5 1.3 36.5 36.5
Chrionomidae 0.3 0.6 14.3 50.8
Nereidae 0.5 0.0 8.4 59.2
Ephemerella ignita 0.4 0.3 7.3 66.5
Table 21. SIMPER analysis displaying the Low (<1) and High (13-27) salinity groups with an average dissimilarity
of 63% highlighting the primary contributing species for the 22 sites assessed via core samples.
For the core samples the SIMPER analysis shows that the three main species that
contribute greatly to the differences among all of salinity groups are the subclass
Oligochaeta and the families Nereidae and Chironomidae. These three taxa are
superimposed on MDS plots in Figures 19-21 to clearly show their distribution along the
salinity groups and sites.
56
Figure 19. MDS plot showing the square root transformed abundances of the subclass Oligochaeta which
contributed most to the dissimilarities over the salinity groups (High-13-27, Medium- 2-6 and Low- <1) using
Bray-Curtis similarity coefficient for the core samples.
As the plot demonstrates (Figure 19), Oligochaetes are seen in highest abundances for the
lower salinity groups. The largest bubble represents the largest proportion of species at 312
which is from SUIR-C located just above the red circle. The remaining high abundances are
found in TO-A, BAR-A, C and D which are shown in the red circle. The two sites with no
Oligochaetes present are the BAN-E (Low) and BAN-B (Medium).
Core SamplesTransform: Square root
Resemblance: S17 Bray Curtis similarity
Oligochaeta
4
16
28
40
Low
Low
Low
Low
Low
Medium High
Medium
Low
Low
Low
Low
Low
Low
Low
Low
Medium
High
Medium
Low
Low
Low
2D Stress: 0.11
57
Figure 20. MDS plot showing the square root transformed abundances of the family Nereidae which contributed
most to the dissimilarities over the salinity groups (High-13-27, Medium- 2-6 and Low- <1) using Bray-Curtis
similarity coefficient for the core samples.
Although polychaetes from the family Nereidae were found to contribute greatly to the
dissimilarity between groups they are present in low numbers. The polychaetes are absent
from most of the sites only being present in 6 of the 22 sites including SLA-A, BAN-B, D and
E which all have differing salinities. The sites with the highest abundances of polychaetes
are the GWEE-A (High) and BAR-D (Low) which are shown in the red circle. They appear in
all three salinity groups indicating that they may have high tolerances to changing salinities.
Core SamplesTransform: Square root
Resemblance: S17 Bray Curtis similarity
Nereidae
0.6
2.4
4.2
6
Low
Low
Low
Low
Low
MediumHigh
Medium
Low
Low
Low
Low
Low
Low
Low
Low
Medium
High
Medium
Low
Low
Low
2D Stress: 0.11
58
Figure 21. MDS plot showing the square root transformed abundances of the family Chironomidae which
contributed most to the dissimilarities over the salinity groups (High-13-27, Medium- 2-6 and Low- <1) using
Bray-Curtis similarity coefficient for the core samples.
The Chironomids are also only present in 6 of the 22 sites assessed and are found in the low
and high salinities but absent from the medium groups. The lack of Chironomids found in the
other sites may be a result of sampling methods or their habitat preferences. They are
present in highest abundances in the SLA-D which had a low salinity, followed by TO-A,
SLA-C and SUIR-B which all had low salinities. A low abundance of the diptera larvae is also
found at the high salinity site, SUIR-G and remaining low salinity site BAR-C.
Core SamplesTransform: Square root
Resemblance: S17 Bray Curtis similarity
Chironomidae
0.5
2
3.5
5
Low
Low
Low
Low
Low
MediumHigh
Medium
Low
Low
Low
Low
Low
Low
Low
Low
Medium
High
Medium
Low
Low
Low
2D Stress: 0.11
59
Grab Samples
SIMPER was carried out to determine the key species contributing to the dissimilarities
between the two groups Low and Medium showing an average dissimilarity of 71% (Table
21). The species that contributed the most to the dissimilarities include the subclass
Oligochaeta (16.7%), the families Chironomidae (15.2%) and Nereidae (13.6%) followed by
the mayfly Ephemerella ignita (12.3%).
Species
Group Low Avg.
Abundance
Group Medium
Avg. Abundance
Contribution %
Cumulative %
Subclass Oligochaeta 1.5 2.5 16.7 16.7
Chrionomidae 0.4 1.8 15.2 31.9
Nereidae 0.0 1.3 13.6 45.5
Ephemerella ignita 0.0 1.2 12.3 57.8
Table 22. SIMPER analysis displaying the Low (<1) and Medium (5) salinity groups with an average dissimilarity
of 71% highlighting the species primarily contributing to the differences for the 22 sites assessed via grab
samples.
The species that contributed most to the differences seen between the Low and Medium
salinities for the grab samples were the subclass Oligochaeta and Chrionomidae; therefore
they were superimposed on the MDS bubble plots (Figures 22 & 23).
60
Figure 22. MDS plot showing the square root transformed abundances of the subclass Oligochaeta which
contributed most to the dissimilarities over the salinity groups (Medium-5 and Low- <1) using Bray-Curtis
similarity coefficient for the grab samples.
The Oligochaetes were present in relatively low abundances throughout the sites. The two
sites with the highest numbers were the BAR-E (Low) and the SLA-A (Medium). The worms
were completely absent from the BWA-C site shown furthest to the right of the graph.
Grab SamplesTransform: Square root
Resemblance: S17 Bray Curtis similarity
Oligochaeta
3
12
21
30
Low
Low
Low
Low
Low
Low
Low
Medium
2D Stress: 0.06
61
Figure 23. MDS plot showing the square root transformed abundances of the family Chironomidae which
contributed most to the dissimilarities over the salinity groups (Medium- 5 and Low- <1) using Bray-Curtis
similarity coefficient for the grab samples.
The Chironomids contributed significantly to the dissimilarity between the sites; however
they are only present at 3 of the 8 sights. The largest abundances are seen within the
medium group which is the SLA-A, followed by the low group, BWA-A and at the top of the
graph BWA-G.
Grab SamplesTransform: Square root
Resemblance: S17 Bray Curtis similarity
Chironomidae
0.4
1.6
2.8
4
Low
Low
Low
Low
Low
Low
Low
Medium
2D Stress: 0.06
62
4. Discussion
In terms of total abundance within the rivers, individuals from the subclass Oligochaeta were
the most dominant species of the total invertebrates encountered. The kick samples were
largely characterised by oligochaetes and crustaceans from the families Gammaridae and
Mysidae. A variety of insect larvae were also abundant in many of the sites including caddis
flies, may flies and beetles. Out of a total of 68 species found with the kicks, 17 were classed
as marine with freshwater species dominating the samples. The invasive Asian Clam,
Corbicula fluminea, was found in the River Barrow and represented 74% of the total bivalves
found in this site. They were first recorded in the tidal freshwater section of the River Barrow
in County Carlow in April of 2010 in relatively well established abundances (Sweeney, 2009).
The Asian Clams are known to compete largely with native species (Thorp and Covich,
2009), including Ireland’s protected freshwater pearl mussel Margaritifera margaritifera and
other species from the families Sphaeridae and Unionidae (Sousa et al., 2008). The
freshwater pearl mussel was not recorded from any sites during this study; however several
pea mussels from the family Sphaeridae were well represented and few from the family
Unionidae. Research carried out by Caffrey et al. (2011) found the Asian Clam to be well
established in the River Barrow from St. Mullins to New Ross reaching maximum densities of
9,636 individuals per metre squared. Caffrey et al. (2011) also found that the clam was
restricted to the tidal freshwater sections of the Barrow with low densities also present in the
lower reaches of the River Nore. The rivers Nore, Barrow and Suir are all connected
providing possible routes of transport for the invasive species. Research carried out by Lucy
et al. (2012) found that only 2.1% of Irish lakes and 0.9% of Irish rivers have a low probability
of being colonized by Corbicula fluminea due to low average pH levels. During this study the
Asian Clam was only recorded from the River Barrow at the St. Mullins and New Ross
sampling sites; however its presence could lead to the ecological demise of many lakes and
rivers if the invasive species colonized new areas.
The core samples were primarily dominated by oligochaetes and the crustacean Corophium
multisetosum. Polychaetes from the family Nereidae were also found in reasonable numbers
with the core samples. For the cores 8 of the 21 species identified were considered to be
marine with the remaining to be of a freshwater nature. Grab samples were also largely
dominated by oligochaetes and gastropods from the family Hydrobiidae (Potamorpyrgus
jenkinsi). For the grab samples 5 out of the 15 species were considered to be marine. Both
the core and grab samples showed a significant reduction for both macroinvertebrate
diversity and abundances.
63
A wide range of taxa were presented throughout this study all with varying tolerances to
organic pollution. Stoneflies are considered to be the least tolerant to organic pollution;
therefore the highest representatives of good water quality (Mason, 2002). For this study,
stonefly larvae were found in very few numbers; however this does not indicate poor water
quality. The stoneflies typically emerge as adults during the summer months (Sterry and
Mooney, 2010) when these samples were taken which explains their absence from samples.
The mayflies and caddis flies are considered to be relatively sensitive to environmental
stresses (Hall Jr et al., 2006, Wenn, 2008) and were found in great abundances throughout
this study. Crustaceans from the family Gammaridae are thought to be relatively sensitive to
organic pollution with its competitors from the family Asellidae being relatively tolerant to
organic pollution (Bloor and Banks, 2006). In polluted waters Asellidae tend to dominate
Gammarus species. In this study Gammarus were the most abundant crustaceans found
although Asellus aquaticus was well represented throughout the sites. Finally oligochaetes,
chironomids and leeches are thought to be the most tolerant of organic pollution (Mason,
2002) of which all were well represented for this study.
The noted decline of species was likely related to the actual sampling methods applied
throughout the study. Various studies have demonstrated the impacts particular sampling
methods have on abundances and diversity of species. During this study, the diversity of
macroinvertebrates were greater for the kick samples with a total of 68 species found in
comparison to the 21 species for cores and 15 for the grabs. In general, kick sampling often
results in a higher richness of species in comparison to corers (Mackey et al., 1984). The
littoral zone of rivers usually supports a greater number of species relating to habitat
preferences in comparison the sub-littoral and pro-fundal zones which are often sampled via
corers (Mandaville, 2002). Corers often result in less invertebrate taxa richness than kicks
as they do not tend to capture mobile species (Hyvonen and Nummi, 2000). Core samples
are found to be most appropriate when the aim is to assess benthic invertebrates such as
oligochaetes, molluscs and chironomids (Hershey et al., 1998). Grab samplers tend to
capture everything from the water column down to the sediment and essentially provide a
good representation of the benthic community structure (Helgen, 2002). However; there are
negative associations with the grab samplers. Relating to the design of the grab samplers,
they can often over penetrate soft sediment and a cause a shock wave which impacts the
sediment and displaces invertebrates away from the sampler thus reducing the accuracy
(Fleming et al., 1994).
64
During this study the biotic indices used rarely agreed with each other in their classification
of water quality for the sites. None of the indices applied represented all of the species
present in the samples indicating that an index composed of both freshwater and marine
species would be most appropriate for the assessment of transitional water ways. The EPA
classed the River Tolka as being of a moderate status in 2008, primarily relating to the
various pollution sources entering the river from Dublin City (CRFB, 2008b). For this study,
depending on the sampling methods, the River Tolka was classed as moderate status only
for the kick samples under the ASPT, Q-values, AMBI and M-AMBI. The H’, BMWP and EPT
all ranged between poor and bad ecological status. With the core samples all indices
indicated either poor or bad ecological status. Similarly the Munster Blackwater River was
classed as moderate only by the BMWP and ASPT for the kicks and for the grabs AMBI
indicated moderate water quality with M-ABMI indicating good ecological status. The
remaining indices represented poor and bad ecological status. This river was determined to
be of good ecological status by the EPA in 2011 (EPA, 2011a). Both of these rivers were
largely dominated by oligochaete worms which reflected their quality status defined by the
biotic indices.
For the River Bandon, the sampling method had a significant effect on the BI outputs. With
the kick samples the BMWP, ASPT, EPT and AMBI all indicated good or high ecological
status. The remaining indices, H’, M-AMBI and Q-values indicated a moderate status.
However for the cores the highest classification was moderate from AMBI and M-AMBI with
the remaining indices showing poor or bad ecological status. The EPA classified this river as
of moderate ecological status in 2008 primarily relating to diffuse pressures and structural
changes within the water column (CRFB, 2008a, EPA, 2008). The River Lee was only
assessed via kick samples, in which all indices indicated good or high status except for the
H’ index which indicated moderate status and a Q-value rating of poor. The River Lee also
received a Q-value classification of moderate by the EPA in 2008 (CRFB, 2008a, EPA,
2008).
The River Suir was only sampled via core samples where all of the indices indicated either
poor or bad ecological status. The diversity was very low for the Suir ranging from 1-3
species found at each site. The indices may not accurately represent the River Suir due to
the low sample size. The river is also affected by agricultural and sewage diffuse (EPA,
2012a) receiving a Q-value of 3 (poor) in 2008 and improving to Q3-4 (moderate to high) in
2011 (EPA, 2011b).
The Rivers Slaney and Barrow showed the greatest diversity of all the sites assessed,
receiving the highest Shannon-Wiener diversity values of 1.9 and 2.22. The River Slaney
65
received good ecological status from AMBI, M-AMBI and BMWP; moderate for the H’ and
ASPT; and poor for EPT and Q-values for the kick samples. The core samples resulted in
lower classifications receiving a moderate classification for H, ASPT and M-AMBI; and poor
ecological status for the EPT and Q-values. The M-AMBI indicated a good ecological status
for the grab samples with AMBI and ASPT showing moderate status and the rest of the
indices indicated poor and bad ecological status. The EPA classed the River Slaney with a
Q-value of 3-4 (moderate to good) in 2010 (McGarrigle et al., 2010, Ecofact, 2010). The
River Barrow received all high or good ecological status for the kick samples with the
exception of the Q-values which indicated moderate to good ecological status (Q3-4). These
results coincide with the EPAs classification of Q3-4 in 2012 which was related to municipal
and agricultural diffuse (EPA, 2012c). The River Barrow also represented the greatest
number of pollution sensitive families via the EPT index further emphasizing its good water
quality.
Finally the Gweebarra River, which was not assessed via grab samples, received good
ecological status from AMBI, moderate for M-AMBI and ASPT and poor status for the
remaining indices for the kick samples. The core samples differed here where they were
classed as good for M-AMBI, moderate for AMBI, poor for Shannon-Wiener Index and ASPT
and bad ecological status for BMWP and Q-values. The river Gweebarra was classed of a
good ecological status in 2009 (CRFB, 2009a) where it decreased to moderate ecological
status in 2012 (Kelly et al., 2012).
The general findings for this study show a great variation with the ecological water
classifications between each biotic index which also differs greatly depending on sampling
method, sample size and diversity. It has been evinced that the values of diversity indices
are highly sensitive to macroinvertebrate sample size (Clarke and Warwick, 2001) whilst also
being sensitive to changes in sample processing (Kennedy et al., 2011).
A great deal of research has criticized the accuracy and relationships between the BMWP
and ASPT scores which rarely agreed in this study. Mandaville (2002) carried out research
on several biotic indices including four of those used in this study (Shannon-Wiener, BMWP,
ASPT and EPT). Previous research by Kirsch and Mandaville (1999) revealed significant
differences between all of biotic indices; and found that BMWP and EPT were the most
strongly correlated; where as ASPT showed no strong correlations with any of the indices,
not even its associated BMWP. This study found that BMWP was more appropriate for
assessing water quality than ASPT because it accounts more for the individual pollution
tolerances of organisms (Mandaville, 2002). A study carried out by Hasan and Melek (2011)
applied a series of biotic indices in two Mediterranean rivers in Turkey including BMWP,
66
ASPT, Shannon-Wiener and EPT reporting that the Shannon-Wiener Index and EPT were
the most reliable methods for determining water quality. In contrast to this study, findings by
Wenn (2008) find BMWP, ASPT and EPT to be more reliable then Shannon-Wiener’s Index
because the species are described based on their sensitivities to pollution rather than just
richness and diversity in general. Abel (1996) states that the Shannon-Wiener Index may be
a better indicator of environmental stresses rather than the pollution levels within an aquatic
ecosystem. Many authors also question the use of species level biotic indices versus family
levels ones. Solimini et al. (2000) found that BMWP and ASPT worked better than the
species level Trent Biotic Index. Another negative aspect of ASPT is that it does not account
for the site type effects as well as BMWP as it often underestimates high scoring families
because it works as an average (Paisley et al., 2007). Although many authors criticize the
efficiency of the ASPT, some authors find ASPT to be more reliable than BMWP because it
is less affected by sampling efforts (Abel, 1996). Research has also shown that sampling
methods greatly influence the values obtained for the BMWP and ASPT (Solimini et al.,
2000).
During this study the M-AMBI did not always follow the same pattern as AMBI despite their
common derivation. The metrics used for M-AMBI (AMBI, S and Shannon-Wiener Index) all
have seemingly weak and equal effects on M-AMBI. Most of the variance in M-AMBI is
caused by the interaction between the indices relating to the factor rotation used in the
calculation of M-AMBI which further explains the differences among the indices (Kennedy et
al., 2011). For this study the AMBI did not efficiently represent all of the species present in
the transitional waters as they were dominated by freshwater species. Ponti and Abbiati
(2004) used AMBI to assess the environmental quality of transitional waters of the Pialassa
Baiona. They found that this approach was limiting because the classification of the species
sensitivity depended on the geographic location and the type and intensity of disturbance. It
is known that organisms are likely to respond to stresses differently based on both
geographic location and ecosystem type(Birk et al., 2012). Ponti and Abbiati (2004)
recommend that a specific sensitivity table be developed for the calculation of biotic indices
in different locations and ecosystem types. They also state that data on environmental
sensitivities are only available for a restricted number of species; therefore BI’s are often
calculated on a fraction of the whole species list as it is only possible to work with those for
which sensitivity data is available. Many researchers find that multivariate approaches for
assessing water quality are more powerful than those using single metrics as more aspects
of the samples can be examined to give a fuller picture of the ecosystems health (Muxika et
al., 2007, Irvine et al., 2010). The EPA Q-values were developed specifically to assess Irish
riverine systems and also rarely agreed with the other indices. Overall many of the indices
67
excluded a large proportion of the species found and an index that combines both freshwater
and marine species appears to be preferable for assessing transitional waters.
Throughout this study all sampling was carried out during the summer months from May to
July because many of the invertebrates were present as larvae during the summer season
with the exception of stoneflies. Research has evinced that seasons impact the community
structures within an ecosystem and the resulting biotic index classifications. Bispo et al.
(2006) found that BMWP values may decrease relating to season rather than an increase in
pollution. For the BMWP and ASPT, both abundances and diversity greatly impact the
scores. For this method to be carried out effectively, a season in which the species are
represented abundantly is favourable. Kennedy et al. (2010) points out that APST values are
more advantageous than BMWP values when comparing water quality with seasons as they
can distinguish between the natural seasonal differences in macroinvertebrate abundances
and pollution based on their use of average scores. Season seems to be significant with
AMBI equally as Muxika et al. (2007) describes sampling to be carried out in the winter
months for water quality in the Basque Country’s coastal and estuarine waters. Solimini et
al. (2000) also found season to play an important role in determining water quality for
BMWP. Zamora-Muñoz et al. (1995) reports that BMWP, more so than ASPT, was not
significantly correlated with season for unpolluted sites; however both indices show
significant correlation with season in polluted sites. Paisley et al. (2007) also finds that
pollution to play a major role with BMWP and ASPT with scores varying in polluted versus
non polluted. Although biotic indices tend to give similar results in polluted streams the
results have been noted to differ in unpolluted parts for many biotic indices (Hasan and
Melek, 2011).
For the statistical analysis the dendograms produced by the cluster analysis grouped sites
based on their similarities, with salinity groups introduced to infer if salinity factors cause
similarities amongst macroinvertebrate communities. For the kick samples the dendogram
appears to create clusters based on locations rather than salinities; however only 3 of the 11
sites assessed represented the medium and high groups, with these salinities being grouped
alone. The core sample formed six main clusters with many smaller groups linking the sites.
Salinity levels are better represented for the core samples with a wider range for low,
medium and high groups. However the linkages formed with the dendogram show no clear
relationship to salinity with many different groups being clustered together. The grab
samples mostly represented low salinities with only one site representing the medium group,
for this the dendogram primarily groups by site as there were only three sites sampled. The
Munster Blackwater site was sampled several times which offers a better picture of what was
present in this river. Both the grab and core samples were characterized by low species
68
diversity and abundances. The MDS plots further demonstrated how the >1 salinity levels
were involved in the grouping of sites and added further emphasis on the similarities noted
with the dendograms. The MDS plots were primarily used to give a graphical representation
of the data.
The ANOSIM results showed that salinity levels did impact the community structure for the
larger kick samples. These samples represented a greater diversity of species, larger
abundances and were sampled more accurately with greater replicates. The ANOSIM
results for the core and grab samples showed no significant differences relating to the
salinity levels. However these results were interpreted with care owing to the lack of diversity
and abundances relating to the sampling methods and procedures. Following the guidelines
by Clarke and Gorley (2006) results showing no relevant sample differences should not be
interpreted. The SIMPER analysis demonstrated with greater clarity, the difference in
community structures observed amongst the salinity gradients. All of the sample methods
tested showed significant dissimilarities between macroinvertebrate composition and the
salinity groups. For the kick samples the salinity groups of low and high showed a
dissimilarity level of 100% likely because only one site (GWEE-A) represented the high
salinity group. This site also only contained two species in comparison to the multitude of
species found in the lower salinities. The groups (high and medium) as well as (low and
medium) showed dissimilarity ratings of 86.5% and 81.3%. The species which were thought
to contribute most to the dissimilarities for the kick samples were oligochaete worms and
Gammarus duebeni which were superimposed onto MDS plots to demonstrate their
distributions throughout the salinity gradients. Both invertebrate taxa were found in highest
densities for the low salinity groups. The SIMPER results for the core samples indicated
dissimilarities ranging from 63%-69%, with the least variation found for the Low,High group.
Here three main species causing the dissimilarities including oligochaete worms,
polychaetes from the family Nereidae and diptera larvae from the family Chironomidae.
Similarly to the kick samples Oligochaete abundances were greater in the lower salinity
groups, with Nereidae and Chironomids occupying all salinity groups. For the grab samples
only one salinity group was represented relating to the lack of salinity levels of which
oligochaetes and chironomids caused the greatest dissimilarities. These results indicate that
crustaceans tend to dominate the higher salinities, with insect larvae and oligochaete worms
being more restricted to lower salinities.
69
A great deal of research has shown that salinity plays a major role in the structural design of
macroinvertebrates in rivers, lakes and estuaries, with richness and abundance tending to
decrease with increasing salinities (Brucet et al., 2012, Horrigan et al., 2005, Kefford et al.,
2013). Community structure can be altered based on an individual species ability to tolerate
varying salinity levels which are strongly based on their physiological, morphological and life
history traits (James et al., 2003). Overall salinity has been proven to have the most
significant effect on community structure in comparison to hydrologic changes such as flow
and water level reductions with highest abundances and diversities typically occurring at
salinities of less than 5ppt (Mattson et al., 2011). Salinity levels are demonstrated to greatly
influence the community structure found within TFTW.
For this study only a few of the wide range of biotic indices were used to assess the water
quality of the transitional waters. Many authors suggest different indices and approaches to
improve the assessment such as sensitivity based salinity indices (Dunlop et al., 2008a,
Dunlop et al., 2008b), trait based indices using bio-criteria (Mouillot et al., 2006) and single
species approaches (Maltby et al., 2002). Research carried out by Blanchet et al. (2008)
emphasises the limits of taxonomic based indices as they are greatly dependant on habitat
characteristics for the ecological quality classification. The future development and accuracy
of biotic indices requires a better understanding of indicator species and their responses to
different natural or anthropogenic disturbances (Blanchet et al., 2008). It is also of the utmost
importance to include invasive species in biotic indices as these are known to cause
significant changes amongst native invertebrate communities. Neither the Irish Q-value
system nor the BMWP included the invasive Asian Clam (Corbicula fluminea) on their
species lists even though these have become well established in both Britain and Ireland.
The AMBI did however include these species in their species list and described them in
ecological group three (EGIII) which comprises the species tolerant to disturbance. The
ecological status of transitional water bodies would be described more accurately by the
integration of multiple metrics including the AMBI; such as the Infaunal Quality Index which
was developed specifically for TFTW in Ireland and Britain. The IQI uses Simpson’s
Evenness, AMBI and the number of taxa; covering a wider range of species including those
considered to be both freshwater and marine.
70
5. Conclusion
The Water Framework Directive establishes the need to assess the water quality for all
water bodies in Europe defining a goal to reach at least good ecological status for all water
bodies by 2015 (EC, 2000). This study assessed the water quality of eight tidal-freshwater
transitional water bodies in the Republic of Ireland including the rivers Barrow, Slaney,
Tolka, Suir, Munster Blackwater, Gweebarra, Bandon and Lee. The macroinvertebrate
community structure was determined for these waterways and comprised of a wide range of
taxa including molluscs, oligochaete worms and the larval stages of a diverse range of
insects. Overall most of the species encountered were considered to be of a freshwater
nature whilst a reasonable abundance of marine organisms were also well represented. The
water quality status’ derived from the study varied greatly depending on the biotic indices
used. On a whole note none of the indices represented the total invertebrates found as they
were either strictly riverine (BMWP, ASPT, Q-values) or marine indices (AMBI, M-AMBI).
Sample size was evinced to greatly affect the output for the indices with less diverse
samples typically indicating poorer water qualities. The riverine indices failed to address the
invasive Asian Clam, Corbicula fluminea, which has become well established in Ireland. This
was however included in the marine indices. The UK-Ireland Benthic Invertebrate Sub-group
have developed and index to specifically assess transitional waters in the UK and Ireland
named the Infaunal Quality Index (IQI). The IQI represents both marine and freshwater
species including alien invasives in both countries. This method could not be applied for this
study relating to information gaps. The rivers ranged from bad ecological status to high
ecological status, with many representatives of the moderate, good and high water qualities.
These results indicate that some waterways are at risk of failing to meet the goals set out by
the WFD. Salinity was found to have significant impacts on the community structure within
the TFTWs with species richness typically decreasing with increasing salinities. On a global
scale the salinization of freshwater ecosystems has greatly increased relating to both global
warming and the direct introduction of salt into waterways via anthropogenic activities
(Dunlop et al., 2008a, Dunlop et al., 2008b). With the current global warming crisis there are
greater chances for shallow waterways becoming both warmer and more saline which will
inevitably result in a severe decrease and changes within macroinvertebrate communities
(Brucet et al., 2012). It is on utmost importance to use appropriate biotic indices for
assessing water quality to determine both pollution status as well as salinity increases.
Macrobenthic fauna are suitable indicators for both salinity and pollution levels relating to
their individual sensitivities to both of these factors.
71
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Appendix 1. List of sample sites assessed for this study.
Estuary Station I.D. Description Northing Easting
Tolka TO-A 53° 21' 43.56" N 6° 14' 33.46" W
Slaney SLA-A Est: Deeps bridge, killurin 52° 23' 4.269" N 6° 34' 7.591" W
Slaney SLA-B TFW: Macmine 52° 25' 23.160" N 6° 33' 55.080" W
Slaney SLA-C TFW: Edermine bridge 52° 27' 15.480" N 6° 33' 42.840" W
Slaney SLA-D Killagoley (1 km d/s Enniscorthy Br) 52° 29' 33.720" N 6° 34' 9.840" W
Barrow BAR-A Pollmunty 52° 25' 14.880" N 6° 56' 11.760" W
Barrow BAR-B Mountgarret bridge 52° 25' 14.880" N 6° 56' 11.760" W
Barrow BAR-C Nore Estuary at Ballyneale 52° 25' 36.480" N 7° 0' 30.240" W
Barrow BAR-D 52° 25' 36.480" N 7° 0' 30.240" W
Barrow BAR-E Upstream New Ross bridge 52° 23' 47.760" N 6° 57' 6.480" W
Barrow BAR-F Barrow Nore Est at Stokestown House 52° 22' 2.640" N 6° 58' 19.200" W
Barrow BAR-H St. Mullins 52° 29.229 N 6° 55.616 W
Suir Suir-A Suir Estuary at Fiddown Br. 52° 19' 38.640" N 7° 19' 1.920" W
Suir Suir-B Suir Estuary at Carrick-on-Suir 52° 20' 48.480" N 7° 25' 10.560" W
Suir Suir-C Suir Estuary at Pollrone Quay 52° 17' 23.640" N 7° 17' 8.160" W
Suir Suir-D Suir Estuary at Suir Lodge 52° 15' 43.920" N 7° 14' 31.560" W
Suir Suir-E Suir Estuary at Granny Pier 52° 16' 37.200" N 7° 9' 51.120" W
Suir Suir-F Suir Estuary at Waterford Br. 52° 15' 50.760" N 7° 7' 8.400" W
Suir Suir-G Suir Estuary at Smelting House 52° 15' 5.760" N 7° 5' 16.080" W
Blackwater BWA-A Tourin Castle 52° 7' 11.587" N 7° 51' 17.663" W
Blackwater BWA-B Dromana House 52° 6' 34.367" N 7° 52' 0.871" W
Blackwater BWA-C Dromana Quay, Villierstown 52° 5' 14.599" N 7° 51' 44.669" W
Blackwater BWA-D Kilmanicholas / Strancally Castle 52° 3' 54.372" N 7° 52' 20.664" W
Blackwater BWA-E Glenassy Quay 52° 2' 56.038" N 7° 50' 56.871" W
Blackwater BWA-F Strancally House 52° 1' 50.604" N 7° 51' 9.890" W
Blackwater BWA-G Lickey River Mouth 52° 0' 48.821" N 7° 51' 18.901" W
Blackwater BWA-H Molana Abbey 51° 59' 45.291" N 7° 52' 56.645" W
Blackwater BWA-I Cappoquin (kick sample) 51° 59' 45.291" N 7° 52' 56.645" W
Lee Lee-B Upper estuary (kick sample) 51° 53.714 N 8° 30.233 W
Bandon BAN-A Upper estuary (kick sample) 51° 45.799 N 8° 42.074 W
Bandon BAN-B Ballydawley 51° 43' 22.664" N 8° 36' 46.252" W
Bandon BAN-C Kilmacsimon (d/s Quay) 51° 43' 44.183" N 8° 37' 46.983" W
Bandon BAN-D Rockhouse 51° 44' 14.019" N 8° 38' 4.073" W
Bandon BAN-E Knockroe 51° 44' 44.805" N 8° 37' 55.122" W
Gweebarra GWEE-A Lower estuary 54° 51.703 N 8° 16.712 W
Gweebarra GWEE-B Upper estuary 54° 54.246 N 8° 12.312 W
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Appendix 2. Invertebrate species found for the kick samples.