My Thesis PFD

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:

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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.

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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
Abstract ………………………………………………………………………………………….. ii
1. Introduction …………………………………………………………………………………. 1
2. Materials and Methods: …………………………………………………………………… 8
2.1 Site Descriptions ……………………………………………………………………….. 8
2.2 Field Sampling Methods ……………………………………………………………..... 10
2.3 Laboratory Methods ……………………………………………………………………. 11
2.4 Biotic Indices ……………………………………………………………………………. 12
3. Results: ……………………………………………………………………………………….17
3.1 Community Structure in TFTWs ………………………………………………………. 17
3.2 Biotic Indices ……………………………………………………………………………. 19
3.2.1 Shannon-Wiener Index …………………………………………………………. 19
3.2.2 BMWP and ASPT ……………………………………………………………….. 22
3.2.3 EPT Taxa Richness …………………………………………………………….. 25
3.2.4 EPA Q-values …………………………………………………………………….26
3.2.5 AMBI/M-AMBI …………………………………………………………………….28
3.2.6 Summary of Biotic Indices ………………………………………………………41
3.3 Statistical Analysis ………………………………………………………………………42
3.3.1 Cluster Analysis for Similarities ……………………………………………….. 42
3.3.2 MDS Analysis for Similarities ………………………………………………….. 45
3.3.3 ANOSIM for Salinity Groups …………………………………………………… 48
3.3.4 SIMPER Analysis for Salinity Groups ………………………………………… 50
4. Discussion …………………………………………………………………………………...62
5. Conclusion ………………………………………………………………………………….. 70
References ……………………………………………………………………………………... 71
Appendix 1. List of sample sites assessed for this study. 80
Appendix 2. Invertebrate species found for the kick samples. 81
Appendix 3. Invertebrate species found for the core samples. 83
Appendix 4. Invertebrate species found for the grab samples. 84

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List of Tables
Table 1. Interpretation of BMWP and ASPT scores including the WFD water quality status
(Seaby and Henderson, 2006, Wenn, 2008)…………………………………………………...13
Table 2. The EPA’s Q-values, associated Ecological Quality Ratios (EQRs) and WFD
interpretation as described by (EPA, 2007, Williams, 2009)………………………………….14
Table 3. AMBI and M-AMBI scores along with their associated water quality status (Borja et
al., 2012)……………………………………………………………………………………………15
Table 4. Kick samples showing number of species (S), number of individuals (#), Shannon
Diversity Index (H) and Evenness (E). For a guide to sites refer to Appendix 2…………. 19
Table 5. Core samples showing number of species (S), number of individuals (#), Shannon
Table 6. Grab samples showing number of species (S), number of individuals (#), Shannon
Table 7. EPT taxa richness numbers found at the 11 sites assessed via kick samples…. 25
Table 8. EPT taxa richness numbers found at the 22 sites assessed via core samples… 25
Table 9. EPT taxa richness numbers found at the 8 sites assessed via grab samples….. 26
Table 10. EPA Q-values, EQRs and WFD water quality status for the 11 sites assessed via
kick sampling……………………………………………………………………………………… 26
core sampling………………………………………………………………………………………27
grab sampling………………………………………………………………………………………27
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…………….. 41
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……………………………………………………………………….. 48
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……………………………………………………………………. 49
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…………………………………………………………………….. 50

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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………………………………………………………………… 50
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………………………………………………………………… 51
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………………………………………………………………...54
Table 20. SIMPER analysis displaying the Low (<1) and High (13-27) salinity groups with an
assessed via core samples……………………………………………………………………… 54
Table 21. SIMPER analysis displaying the Low (<1) and High (13-27) salinity groups with an
assessed via core samples……………………………………………………………………… 55
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…………………………………………………… 59

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List of Figures
Figure 1. Map of Ireland showing the rivers sampled during this study……………………. 8
Figure 2. Bar chart displaying the BMWP values with the ASPT values above each bar for
the kick samples…………………………………………………………………………………. 22
the core samples………………………………………………………………………………… 23
the grab samples………………………………………………………………………….......... 24
Figure 5. AMBI results for the 11 sites assessed via kick samples showing pollution status
and biotic index values…………………………………………………………………………. 30
Figure 6. M-AMBI results showing the biotic indices and WFD interpreted water qualities for
the 11 sites assessed via kick samples……………………………………………………….. 31
Figure 7. AMBI results for the 22 sites assessed via core samples showing pollution status
and biotic index values………………………………………………………………………….. 32
Figure 8. M-AMBI results showing the biotic indices and WFD interpreted water qualities for
the 22 sites assessed via core samples………………………………………………………. 33
Figure 9. AMBI results for the 8 sites assessed via grab samples showing pollution status
and biotic index values…………………………………………………………………………. 34
Figure 10. M-AMBI results showing the biotic indices and WFD interpreted water qualities
for the 8 sites assessed via grab samples……………………………………………………. 40
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…………………………... 42
Figure 12. Dendogram illustrating the similarities between the 22 sites assessed via core
salinity groups as factors with Low <1, Medium 2-6 and High 13-27……………………… 43
Figure 13. Dendogram illustrating the similarities between the 8 sites assessed via grab
salinity groups as factors with Low <1 and Medium 5……………………………………….. 44
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…………………………………………………… 45
transformed abundance data for the 22 sites assessed via core samples across three salinity
groups, Low <1, Medium 2-6, and High 13-27……………………………………………….. 46

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transformed abundance data for the 8 sites assessed via kick samples across two salinity
groups, Low <1 and Medium 5…………………………………………………………………. 47
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…………………………………………………………………………………………… 52
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…………………………………………………………………………………………… 53
(High-13-27, Medium- 2-6 and Low- <1) using Bray-Curtis similarity coefficient for the core
samples…………………………………………………………………………………………… 56
Figure 20. MDS plot showing the square root transformed abundances of the family
Nereidae which contributed most to the dissimilarities over the salinity groups
samples…………………………………………………………………………………………… 57
Chironomidae which contributed most to the dissimilarities over the salinity groups
samples…………………………………………………………………………………………… 58
(Medium-5 and Low- <1) using Bray-Curtis similarity coefficient for the grab samples…... 60
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……………... 61

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1. Introduction
The EU Water Framework Directive (WFD) 2000/60/EC (EC, 2000) was adopted in 2000 as
a result of persistent demands for cleaner water bodies by both the public and environmental
organisations. The WFD is currently the primary legislation for monitoring water quality
throughout Europe. The Directive has established a framework for the protection and
improvement of all European surface and ground waters. Under the Directive it was
essential to categorize all water bodies into appropriate groups which included rivers, lakes,
groundwater and transitional (estuarine) and coastal waters because of the varying
ecosystem responses within each environment. The main objective is achieving at least
‘good’ ecological statuses for all water bodies by 2015 whilst also ensuring that water quality
does not deteriorate in any water bodies. Under the WFD an integrated management and
planning system for the specified water bodies is also required. As a result of this River
Basin Districts (RBDs) were established to promote an integrated management system. On
the island of Ireland a total of eight RBDs have been designated for the implementation of
the WFD. In Ireland the Environmental Protection Agency (EPA) are responsible for
developing and publishing River Basin Management Plans for each RBD. These plans
account for six years with the current plans covering the period from 2009-2014.
A recent publication by the European Commission (EC, 2007) reported that a substantial
percent of European water bodies are at risk of failing to reach ‘good ecological status’ by
2015. The main drivers behind this were stated to be eutrophication as a result of
anthropogenic activities. In relation to other EU member states, Ireland’s water quality is
generally good, however the monitoring of some water bodies has been neglected. The tidal
freshwater section of transitional waters (TFTW) and transitional waters in general are
seldom studied in Ireland (Hering et al., 2013). The EPA (2012b) carried out an assessment
of Ireland’s transitional water quality and found they are ranked amongst the top five in
Europe, even with a majority of the population residing on or near the coast.

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The term ‘transitional waters’ first came into context in 2000 during the publication of the
WFD and was used to describe the areas of water between fresh and coastal waters
(McLusky and Elliott, 2007). These waters include estuaries, fjords, lagoons, rias and deltas.
Transitional waters are defined as, “bodies of surface water in the vicinity of river mouths
which are partially saline in character as a result of their proximity to coastal waters but
which are substantially influenced by freshwater flows” (EC, 2000). Transitional waters are
characterized by fast biogeochemical cycles, variation of chemical and physical
characteristics and high trophic flux (Ponti et al., 2012). These characteristics lead to both
rapid and generally unpredictable changes in community structure and function. Salinity
levels are known to play a major role in the composition of invertebrate fauna in many water
bodies (Pinder et al., 2005). Research has evinced that a decrease in species richness is
observed at the freshwater-estuarine transition zones because they become intolerant of the
increased salinities, the species richness then increases again further within the estuary and
is dominated by marine species (Rundle et al., 1998). The salinity levels in the TFTW are
generally low; however they are also succumbing to great variability. Biota of the TFTW may
be considered resilient because of their ability to survive within transitional ecosystems
(Elliott and Quintino, 2007). The characteristics of transitional waters inevitably allow for a
unique flora and fauna which have adapted to this ever changing environment. In
compliance with the WFD, the UK Technical Advisory Group (UKTAG) has identified six
types of transitional waters in the UK and Republic of Ireland which are based on various
factors including salinity, wave exposure, substratum, depth, mean tidal range and mixing
characteristics (WFD, 2014). Transitional water types one to four include those water bodies
defined by the combination of salinity, depth, tidal range and mixing characteristics whereas
type five represents transitional sea lochs and type six transitional lagoons (UKTAG, 2004).
In the Republic of Ireland only two types of the transitional waters occur of which 110 water
bodies were identified as type two and 86 as type six (WFD, 2005).
Globally, transitional waters are the sites of major ports and cities which has led to severe
degradation as a result of various human induced impacts including development, dredging
and pollution from urban, industrial and agricultural areas. It has been evinced that
transitional waters are particularly vulnerable to eutrophication, chemical and microbial
pollution because of their shallow depth, confinement and reduced water exchange (Barnes,
1999). On a global scale, transitional waters are facing an increase in degradation due to
population density increases in coastal areas. In Ireland, the EPA report (2012b) revealed
that the greatest threat for transitional waters results from municipal waste water treatment
plants followed by agricultural practices such as silage effluent and the spreading of animal
manure during unsuitable conditions. The EPA report suggests that a reduction of nutrient

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input is a key measure for improving the status of Ireland’s transitional and coastal waters. In
order to manage eutrophication it is first necessary to identify the role of nutrients as limiting
factors such as nitrogen and phosphorus (Domingues et al., 2011). Once this is established,
managers can make effective decisions for improving water quality.
During the period of 2007-2009 the EPA assessed the quality of 121 transitional and coastal
water systems in Ireland, of which 46% were classified as either high or good status, 51% as
moderate, 3% as poor and none were of bad status (EPA, 2012b). Due to the varying
characteristics of transitional waters, evaluating the ecological quality becomes a challenge.
Transitional waters are often classified as naturally stressed environments because of their
varying physico-chemical characteristics such as salinity, temperature and oxygen levels
(McLusky and Elliott, 2007). Estuaries are also adversely impacted by anthropogenic
stresses which often resemble natural stresses; the difficulty to differentiate between the two
has been defined as the Estuarine Quality Paradox (Elliott and Quintino, 2007) or the
Transitional Estuarine Quality Paradox (Zaldívar et al., 2008). In conjunction with the WFD
many methods for assessing water quality have been established following the criteria
specified by the Directive.
Under the WFD, all member states are required to assess the ecological status (ES) or
ecological quality status (EcoQS) of their water bodies. The WFD established two different
quality statuses; the chemical status which is based upon concentrations of organic
compounds and metals and the ecological status which incorporates physico-chemical,
chemical and biological indicators. Based on the review carried out by Birk et al. (2012), it
was evinced that Europe decided to use ecological status as the primary determinant of
management needs for surface waters.
In accordance with the WFD, the status of European surface waters is to be assessed using
aquatic organism groups such as macroinvertebrates. Worldwide, aquatic
macroinvertebrates are used as bioindicators of an ecosystems health. Biological monitoring
is defined as “surveillance using the responses of living organisms to determine whether the
environment is favourable to living material” (Cairns Jr and Pratt, 1993). Benthic
macroinvertebrates can generally be defined as organisms that can be retained by a 0.5 mm
sieve size (Ponti et al., 2012). They are bottom dwelling organisms often found in rivers,
lakes and streams. Benthic invertebrate communities are valuable indicators of organic
pollution and are also sensitive to toxic pollutants. Benthic invertebrates have been used to
assess water quality in Europe since the early 20th
century (Maltby et al., 2002). Globally,
soft bottom benthic macrofauna are one of the most frequently used elements for
determining habitat quality in transitional waters (Kennedy et al., 2011). Aquatic insects are

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often the favoured group of organisms for biological monitoring because they are; relatively
long lived and therefore reflect the water quality changes over time; because they are
benthic organisms they cannot avoid deteriorating water/sediment conditions and they
represent a wide range of taxonomic, trophic and functional groups representing different
tolerances to different sources of disturbance (Dauer, 1993). Soft bottom communities also
play important roles in overall ecosystem functioning by providing nutrient cycling between
the sediment and water column (Borja et al., 2000). Macroinvertebrates also tend to be
immobile in nature; therefore the source of pollution can be pin-pointed by comparing
communities of these organisms. The pollution levels can be indicated by shifts in
macroinvertebrate abundance and composition at the community level. In a study carried out
by Azrina et al. (2006), it was noted that organic pollution had negative impacts on both the
distribution and species diversity of macrobenthic invertebrates in the Langat River,
Peninsular Malaysia.
Freshwater systems can be defined as areas in which the salinity levels are less than
3,000mgL-1 with seawater representing levels of 35,000 mgL-1 (Nielsen et al., 2003).
Freshwater invertebrates which are commonly found in rivers include both the immature and
adult stages of aquatic beetles (Coeloptera), mayflies (Ephemeroptera), caddis flies
(Tricoptera), damselflies and dragonflies(Odonata), snails (Gastropoda), clams (Bivalvia),
true flies (Diptera) and true bugs (Hemiptera). Those frequently considered to be
estuarine/marine include aquatic worms (Oligochaeta), polychaetes, sponges, cnidarians,
leeches (Hirudinae), crustaceans (Malacostraca), marine snails and marine bivalves. The
presence and/or absence of any of these species can be used to assess the water quality of
transitional waters. However; because the salinity levels vary greatly in transitional waters
there is often a mixture of both freshwater and estuarine species present. The
macroinvertebrate species which demonstrate the greatest sensitivities to even slight salinity
increases primarily consist of insects including stoneflies, mayflies, caddis flies, true bugs,
and dragonflies as well as pulmonate snails and isopods (Hart et al., 1991, Rutherford and
Kefford, 2005). Those which are considered to be relevantly tolerant to increased salinities
include crustaceans, beetles and dipteran flies (Dunlop et al., 2005, Hart et al., 1991).
Oligochaetes are also known to have relatively low tolerances to salinity levels (Rutherford
and Kefford, 2005). Salinity has been proven to have the most significant effect on
community structure in comparison to other environmental variables (Mattson et al., 2011).
The freshwater biota tend to stay in the lowest saline conditions and salinity increases that
exceed 1000mgL-1 are predicted to have adverse impacts on invertebrates (Nielsen et al.,
2003, Hart et al., 1991). These taxa can be grouped based on their sensitivities to pollution.
Aquatic worms, leeches, midge larvae and snails without operculum’s are considered to be

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the most tolerant of organic pollution (Mason, 2002). Dragonflies, damselflies, beetles
(immature and adult), crustaceans, clams, alderflies , true bugs, alderflies, crane flies ad
blackflies are all considered to be moderately tolerant of organic pollution (Maltby, 1995,
Bloor and Banks, 2006, Wenn, 2008). Finally the macroinvertebrates considered to be highly
sensitive to organic pollution include mayflies, stoneflies, snails with operculum’s and caddis
flies (Wenn, 2008, Hall Jr et al., 2006, Mason, 2002). The presence of these highly sensitive
organisms, in abundant numbers, is indicative of pristine water quality conditions in
freshwaters.
In conjunction with the WFD various monitoring programmes have been established by
member states to meet the requirements of the Directive and national regulations for all
member states were enforced. For Ireland, European Communities (Water Policy)
Regulations 2003 were established. Under article 10(1) of the policy the Environmental
Protection Agency (EPA) are required to prepare a monitoring programme with the ultimate
goal of meeting the objective of the WFD (EPA, 2006). In order for this assessment to be
carried out specific criteria for each water body must be established which is specified by the
WFD. New ecological classification systems for water bodies are required because past
ones are not WFD compliant. It is greatly important to establish a standardized protocol
involving field sampling, sample processing and identification processes for all quality
assessments (Birk et al., 2012).
As pertaining to the WFD, assessment methods are required for different water groups and
different Biological Quality Elements (BQEs) such as phytoplankton, benthic invertebrates,
fish and aquatic flora. The assessment of the benthic invertebrate quality element shall
consider abundance, level of diversity and the presence and/or absence of pollution tolerant
and disturbance sensitive taxa. The ES for each water body will be assigned based on their
biological, hydromorphological and physico-chemical quality elements. The health of a BQE
is assessed by comparing the measured conditions (observed value) against those
described for reference (undisturbed) conditions which will be reported as Ecological Quality
Ratios (EQRs). The objective of establishing reference conditions is to enable the
assessment of the BQEs over periods of time and across the geographical extents (Muxika
et al., 2007, Borja et al., 2009). EQRs are expressed as decimal values ranging from zero to
one with ‘high’ status being represented by values close to one (>0.74) and ‘bad’ status by
values close to zero (<0.25). The EQRs are then divided into the five ecological status
classes defined by the WFD (high, good, moderate, poor or bad) by a numerical value.
These classes are defined by changes in the biological community in response to
disturbances. Once the EQR score and ecological status classes have been calculated, an

6
assessment must be made to consider the certainty of the classification which usually
involves biotic indices (BI).
Over the years various biotic indices have been produced throughout Europe. The WFD
demand an integrated approach for assessing water quality involving biological, physico-
chemical and pollution elements together to allow ecological assessment to be carried out at
an ecosystem level rather than just a species or chemical level (Borja et al., 2008). At
present, very few studies have used an integrated methodology for assessments (Borja et
al., 2000, Borja et al., 2009). The WFD does not specify which metrics or indices should be
used to assess BQEs and as a result many countries adapted their own individual methods
which led to the establishment of hundreds of methods (Birk et al., 2012, Borja et al., 2009).
The level of agreement between classifications using different EQRs is well underway for
coastal waters; however issues remain with transitional and estuarine waters (Elliott and
Quintino, 2007, Kennedy et al., 2011).
Birk et al. (2012) carried out a review of 297 biological methods from 28 EU countries which
are used to implement the WFD. Of these methods only 19% were methods relating to
transitional waters. This study found that more than half the methods were based on benthic
invertebrates (26%) or macroscopic plants (28%), followed by phytoplankton (21%), fish
(15%) and phytobenthos (10%). This study identified a total of nine metrics of which fish-
based methods had the highest number of metrics. For rivers, sensitivity and trait metrics
were the dominant features for assessment and for other water body’s abundance methods
prevailed. Over half (56%) of the methods used focused on detecting eutrophication and
organic pollution, which are the main causes of degradation in transitional waters.
The WFD Monitoring Programme (EPA, 2006) identified a total of 196 transitional water
bodies in Ireland. For transitional waters, four main groups or BQEs are used to assess the
biological quality; phytoplankton, angiosperms and macroalgae, invertebrates and fish. In
terms of fish, these are only to be assessed for transitional waters. The WFD requires the
assessment criteria for the BQEs to include the composition and abundance of benthic
invertebrate and fish fauna; composition, abundance and biomass of phytoplankton and the
composition and abundance of other organic aquatic flora such as angiosperms and
macroalgae.
Biotic indices are used globally for determining the quality of an ecosystem by examining the
types of organisms present within the area. To date there has been no inter-calibration for
assessing systems relating to transitional waters as a result of the multitude of methods
developed by member states and challenges relating to the heterogeneity of the waters
(Borja et al., 2009).Species diversity indices can be used to compare assemblages within

7
and between transitional water systems (Ponti et al., 2012). The Shannon-Wiener Index (H)
and Evenness (E) are widely used to measure diversity in aquatic systems. This index
incorporates species richness and the proportion of each species within the aquatic
community. Many biotic indices have been developed to assess both riverine and estuarine
waters. Some of the estuarine/marine biotic indices include Azti’s Marine Biotic Index (AMBI)
(Borja et al., 2000), Multivariate-AMBI (Muxika et al., 2007), Bentix (Simboura and Zenetos,
2002) and the Biological Quality Index (BQI) (Rosenberg et al., 2004). Two indices, the
Infaunal Quality Index (Prior et al., 2004) and Benthic Opportunistic Polychaetes Amphipod
Index (Gesteira and Dauvin, 2000) were developed specifically for the assessment of coastal
and transitional waters with M-AMBI being further developed to assess coastal and
transitional waters (Borja et al., 2009). The Infaunal Quality Index (IQI) was developed to
assess transitional waters by the UK-Ireland Benthic Invertebrate Subgroup of the UK-
Ireland Marine Task Team (EPA, 2006). This is a multi-metric tool which comprises three
different metrics; Simpson’s Evenness, AMBI and the number of taxa (NIEA, 2009). A study
carried out by Muxika & Bald (2007), demonstrated that the use of different metrics should
be objective tools in carrying out ecological assessments to meet WFD requirements. The
riverine biotic indices commonly used include the Biological Monitoring Working Party
(BMWP) score system (Chesters and Britain, 1980), River Invertebrate Prediction and
Classification Scheme (RIVPACS) (Wright et al., 1993) and the Irish Q-value system which
was created by the EPA in conjunction with the WFD.
As eutrophication relating to anthropogenic activities is the main driver behind poor water
quality in Europe it is of utmost importance to rectify this issue. Although transitional waters
in Ireland are ranked among Europe’s top five, the TFTWs are greatly understudied in
Ireland and ecological assessments need to be carried out in order to meet the objectives of
the WFD. It is also greatly significant to develop accurate methods for assessing water
quality as many have been suggested with little validation being carried out for transitional
waters. Determining both the accuracy of biotic indices and the appropriate one(s) to be
used for the TFTW are of great value. The purpose of this study is 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 number of biotic indices
will then be 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 will also be carried out to
determine if high, medium and low salinity levels do in fact cause differences in
macrobenthic community structure.

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2. Materials and Methods
2.1 Site Descriptions
For this study a total of eight rivers were assessed including a total of 33 sites via kick, core
and grab sampling. These sites comprise of the rivers Tolka, Barrow, Slaney, Lee, Bandon,
Gweebarra, Munster Blackwater and Suir which are all located throughout different parts of
Ireland (Figure 1). For a full list of the sites assessed within each river and exact locations
see Appendix 1.
Figure 1. Map of Ireland showing the rivers sampled during this study.
Dublin
Cork
DonegalRiver Gweebarra
River Slaney
River Barrow
Munster Blackwater
River
River Lee
River Suir
River Tolka
River Bandon

9
The River Tolka originates in Co. Meath and is the second largest river flowing into Dublin
City where its course is urban for approximately 12km before entering the Tolka estuary. The
river runs over postglacial tills and gravels with its substratum primarily consisting of
carboniferous limestone and Silurian sandstone (Buggy and Tobin, 2003). A wide variety of
pollution sources enter the river including agricultural run-off, both treated and untreated
sewerage effluents, storm water run-off and general litter from the public (CRFB, 2008b).
Throughout time the river Tolka has been noted for having high concentrations of the heavy
metal tributyltin (TBT) and many fish kills have been reported relating to pollution (Buggy and
Tobin, 2006). A recent fish kill occurred in July, 2014 where hundreds of fish were killed from
a pollution source over a 2km stretch in north side Dublin. Under the WFD water categories
the EPA have classified the river Tolka as being of a moderate status which needs to be
improved to at least good ecological status by 2015 (CRFB, 2008b). The River Basin
Management Plan for Co. Dublin designates the river Tolka as heavily modified due to the
various modifications for both flood defences and navigation (Council, 2009). The plan also
notes that little studies have been carried out to assess the potential impacts these
modifications have had on the river.
The River Slaney is located in southeast Ireland where it rises in Co. Wicklow and flows
southerly over 117km down to Wexford Harbour. The river flows over granite bedrock with a
substratum consisting of medium to fine sands. The transitional waters have been succumb
to various anthropogenic impacts such as channelization and shipping pressures (CRFB,
2009b). The river has been exposed to nutrient enrichments via agricultural runoff and
sewage effluents and is considered to be slightly polluted receiving an EPA Q-value of 3-4
indicating moderate to good status based on macroinvertebrate communities (McGarrigle et
al., 2010, Ecofact, 2010).
The Munster Blackwater River is one of the largest rivers in Ireland stretching for 168km
from County Kerry easterly towards counties Cork and Waterford where it drains into the
Celtic Sea. The Blackwater Estuary was listed on the RAMSAR List of Wetlands of
International Importance in June of 1996. Its geology primarily consists of carboniferous
limestone with a substrate of cobble and gravel. Various sources of diffuse pollution occur
within the river from agriculture, forestry, treated wastewater and urban landuses; however
the EPA classed the river as good ecological status receiving a Q-value of 4 (EPA, 2011a).
The Rivers Suir and Barrow form part of The Three Sisters along with the River Nore (not
assessed here) which all meet in County Waterford before discharging into the Irish Sea.
The River Suir rises in north Tipperary and flows eastward for 185km onto Waterford
Harbour. The river consists of carboniferous limestone and red sandstone with a coarse

10
sandy substratum. Agricultural diffuse and municipal pollution contribute greatly to the water
quality within the river (EPA, 2012a). The EPA noted an improvement in the water quality in
the Suir as it received a Q-value of 3 indicating poor ecological status in 2008 and a Q-value
of 3-4 in 2011 indicating moderate status (EPA, 2011b). The river Barrow is Ireland’s second
largest river next to the river Shannon. It runs for 192km from the Slieve Bloom Mountains in
County Laois eastwards to Waterford Harbour. The river runs over glacial stills with a
substrate comprising of sandstone sand and gravel. The river receives a Q-value of 3-4
which is a moderate ecological status largely relating to municipal and agricultural diffuse
(EPA, 2012c).
The Gweebarra River is located in west County Donegal where it stretches for approximately
32km into a 16km estuary named the Gweebarra Bay. In 2009 the water quality was of good
ecological condition (CRFB, 2009a) where it declined to a moderate status in 2012 primarily
relating to sewage inputs and agricultural run-off (Kelly et al., 2012).
Both the rivers Lee and Bandon are located in west County Cork. The River Lee is 90km in
length and flows through Cork City. The Bandon is approximately 72km in length and flows
into Kinsale Harbour before entering the sea. They flow over sandstone bedrock with a clay-
slate substrate. Both rivers are at risk of not achieving good ecological status by 2015 have
with a WFD status of moderate ecological quality primarily relating to diffuse pressures and
structural changes to the water bodies for the shipping industry (CRFB, 2008a, EPA, 2008).
2.2 Field sampling methods
Macroinvertebrate composition was assessed for the sites by kick, core and grab sampling.
All samples were placed in buckets and the live samples were analysed in the lab. Hydro-
morphological characteristics of the rivers such as salinity, temperature and oxygen levels
were also recorded to determine the potential impacts on macroinvertebrate communities in
transitional waters.
The kick samples were carried out following the EPA’s benthic macroinvertebrate protocols
described by Barbour et al. (1999). They were carried out using nets with a 1x1m frame and
500µ mesh size. The samples were carried out in 100m stretches which best represented
the rivers characteristics. Sampling commenced downstream of this stretch finishing
upstream with three kicks taken per replicate. For the kicks at least three replicates were
taken for each sample point. Sediment was disturbed by foot approximately one square
meter downstream on the 100m reach. The net was positioned against the flow so any
dislodged macroinvertebrates were carried into the net by the current. After each kick, clean
water was passed through the net to get rid of unwanted debris.

11
The core samples were carried out using standard corers of 8cm in diameter and 30cm in
length. Each sample was taken at a depth of approximately 15-20cm. A total of three cores
were taken per replicate with one replicate being taken for most of the sites. Once cores
were retrieved they were rinsed through a 500µ sieve to remove loose sediment and retain
the macro-benthic organisms.
Only eight sites were assessed for the grab samples which were mainly taken from small
vessels. For this a Peterson Grab Sampler of 12x12inches in size was used weighing
approximately 23kg. The grabs were penetrated by weight and reached depths from 10-
20cm. A weighted approach was chosen to guarantee the same penetration depths for all
sites. As with the core samples one replicate was taken for these sites. For all three
methods the cleaned samples were placed in concealed containers and the live samples
were analysed in the lab.
2.3 Laboratory methods
Once samples reached the lab they were placed in formalin and stained with Rose Bengal.
After this all invertebrates were removed and placed into appropriately labelled containers
based by sample sites and preserved in 70% alcohol. Following this, the invertebrates were
all identified to the nearest taxonomic levels under a stereoscopic microscope using various
identification keys. The invertebrates were first identified to family level using the books by
Merritt and Cummins (1996), Pawley et al. (2011) and Dobson et al. (2012). For this study
macroinvertebrates from the subclass Oligochaeta and family Chironomidae were identified
to family level. All other invertebrates were identified to species level using the following
books: Tricoptera (Wallace et al., 1990, Edington and Hildrew, 1995), Ephemeroptera (Elliott
et al., 1988), Malacostraca (Gledhill et al., 1993), Coleoptera (Friday, 1988, Holland, 1972),
Hirudinea (Elliott and Mann, 1979), Plecoptera (Hynes and Association, 1940), Bivalvia
(Killeen et al., 2004) and Gastropoda (Macan and Cooper, 1977). Data was recorded into
Excel files for further analysis with biotic indices and PRIMER.

12
2.4 Biotic Indices
For this assessment a total of seven widely used biotic indices were chosen to assess the
water quality. To assess diversity the Shannon-Wiener Index (H’) and its Evenness (E) were
computed. Then freshwater indices were used to determine water quality which involved the
Biological Monitoring Working Party (BMWP) and corresponding Average Score Per Taxon
(ASPT) aswell as the EPA’s Q-values. The Ephemeroptera, Plecoptera and Tricoptera (EPT)
taxa richness index was also applied to determine the presence of the species most
sensitive to pollution and salinity increases. A marine index was also applied, Azti’s Marine
Biotic Index (AMBI) and the Multivariate-AMBI to represent the fauna considered to be
marine. The BMWP and ASPT are more frequently applied for kick samples; however
various studies have incorporated the biotic index for core and grab samples (Le Thuy et al.,
Bartram and Ballance, 1996, Rybak and SADŁEK, 2010). For this study all biotic indices
were applied to each sample regardless of the sampling method; as the aim is to determine
which biotic indices (if any) best represent transitional fauna.
Shannon Wiener Index (H) and Evenness (E)
The Shannon-Wiener index is widely used to measure diversity. This index incorporates
species richness and the proportion of each species within the aquatic community. Where H
is the Shannon Diversity Index, S is species richness and Pi is the proportion of species (i)
relative to the total number of species (Pi).
Higher values of H indicate a greater diversity of species with lower values indicating that all
species are similar. These values typically range from 0-4.6 depending on the sample size.
The Shannon-Wiener values can indicate the levels of environmental stress within an
aquatic system with lower scores indicating poor environmental conditions and high
environmental stress (Mason, 2002). For this study a Shannon score (H) of less than one
was interpreted to indicate extremely polluted waters (Chapman et al., 1996, Wenn, 2008).
Using both species richness (S) and the Shannon-Wiener index (H) the measurement of
evenness (E) can be computed.
Evenness is simply a measure of abundance similarities among the different species. These
values range from 0-1 with a score of 1 representing complete evenness. The score

13
decreases with dissimilarities observed with the abundances indicating that they are not
evenly distributed among species.
BMWP and ASPT
The Biological Monitoring Working Party (BMWP) and corresponding Average Score Per
Taxon (ASPT) biotic index is widely used for biological water quality assessment throughout
the UK and Ireland. The index was developed by the BMWP in 1976 (Environment, 1976).
The BMWP and ASPT is described following the guidelines provided by Hawkes (1998).This
index is typically used for kick samples where each family is assigned a score based on their
sensitivity to pollution. Rather than looking at abundances, the BMWP records the presence
or absence of these families from the samples. Invertebrates with high tolerances to pollution
receive low scores and those with lower tolerances receive high scores. The BMWP score is
calculated by summing up all of the scores for the families for each sample. High scores
greater than 100 represent unpolluted rivers and those with less than 10 describe heavily
polluted rivers (Table 1). The revised BMWP score sheet was used for this analysis which
was adapted from the original sheet provided by Walley and Hawkes (1997). This sheet was
obtained from the methods manual of the software Species Diversity and Richness (SDR-IV)
which was written by Seaby and Henderson (2006). From the BMWP the Average Score
Per Taxon (ASPT) can also be calculated which is the average of BMWP scores, this score
ranges from 0-10 also indicating good water quality with higher scores (Table 1).
BMWP ASPT Category Interpretation WFD
0-10 3.9 or less Very poor Heavily polluted Bad
11-40 4.0-4.9 Poor Polluted or impacted Poor
41-70 5.0-5.9 Moderate Moderately impacted Moderate
71-100 6.0-6.9 Good Clean but slightly impacted Good
Over 100 Over 7 Very good Unpolluted, unimpacted High
Table 1. Interpretation of BMWP and ASPT scores including the WFD water quality status (Seaby
and Henderson, 2006, Wenn, 2008).

14
EPT Taxa Richness
To further emphasize the presence of families of invertebrates representative of high water
quality and least tolerant to organic pollution, the Ephemeroptera (mayflies), Plecoptera
(stoneflies) and Tricoptera (caddis flies) or EPT taxa richness was calculated for all sites. For
this interpretation, sites with high numbers of any of these families were considered to be of
good water quality and sites with low numbers representing poor water quality (Wenn, 2008).
The EPT taxa richness values typically range from 0-12 with the higher values indicating less
organic pollution and pristine water conditions. Typically these families are most diverse in
natural streams and tend to decline with disturbances.
EPA Q-values
In Ireland, the biological water quality via macroinvertebrates in rivers is assessed using Q-
values which are based on the relative proportions of pollution sensitive species to tolerant
macroinvertebrates resident at a river site, as described by the EPA (EPA, 2007). For the
Irish assessment procedure (Table 2), benthic macroinvertebrates have been divided into
five indicator groups (A, B, C, D, E) with Group A representing the sensitive forms and
Group E the most tolerant forms. The presence or absence of these groups from a river can
be classed into the Q-system (Q1-Q5) with Q1 representing bad status and has the least
groups present and Q5 representing high status and the most groups present. Group
composition plays an important role in the Q-system.
Q-values EQR EPA Interpretation WFD
Q5 1.0 Unpolluted High
Q4-5 0.9 Unpolluted High
Q4-5 0.8 Unpolluted Good
Q3-4 0.7 Slightly polluted Moderate
Q3 0.6 Moderately polluted Poor
Q2-3 0.5 Moderately polluted Poor
Q2 0.4 Seriously polluted Bad
Q1-2 0.3 Seriously polluted Bad
Q1 0.2 Seriously polluted Bad
Table 2. The EPA’s Q-values, associated Ecological Quality Ratios (EQRs) and WFD interpretation
as described by (EPA, 2007, Williams, 2009).

15
AMBI and MAMBI
Both the AZTI Marine Biotic Index (AMBI) and Multivariate-AMBI biotic indices are widely
used in the EU (Teixeira et al., 2012). AMBI, also known as the Biotic Coefficient (BC) index,
is a measure of the overall pollution sensitivity of a benthic assemblage which was
developed by Borja et al. (2000). A multivariate approach was also developed for AMBI
known as the M-AMBI which incorporates the Shannon-Wiener index and species richness
(Muxika et al., 2007). The AMBI was established to assess the quality of Europe’s coastal
and estuarine waters by investigating the responses of soft-bottom benthic communities to
both anthropogenic and natural disturbances in the environment (Muxika et al., 2007). The
AMBI index was developed to assess marine invertebrates which will identify the species in
transitional waters considered to be marine and their indication of the water quality for these
water bodies. Both AMBI and M-AMBI define species based on five ecological groups (EG);
EGI – species very sensitive to disturbance, EGII – species indifferent to disturbance, EGIII -
species tolerant to disturbance, EGIV – second-order opportunistic species and EGV – first-
order opportunistic species (Muxika et al., 2007). The AMBI scores range from 0-7 with high
scores representing disturbed waters and low values indicating undisturbed pristine
conditions (Table 3). The M-AMBI is translated for the WFD with scores ranging from 0-1,
with low scores indicating bad ecological status and higher scores demonstrating high
ecological status (Table 3). For this project the AMBI and M-AMBI analysis was carried out
using the online AMBI index software Version 5.0 following the instructions developed by
Borja et al. (2012) using the most recent species list for March 2012.
AMBI AMBI Quality M-AMBI M-AMBI Quality
0-1 Undisturbed 0-0.1 Bad
2 Slightly disturbed 0.2-0.3 Poor
3-4 Moderately disturbed 0.4-0.5 Moderate
5-6 Heavily disturbed 0.6-0.7 Good
7 Extremely disturbed 0.8-1 High
Table 3. AMBI and M-AMBI scores along with their associated water quality status (Borja et al.,
2012).

16
Statistical Analysis
To analyse and determine any patterns within the invertebrate community structures various
tests were carried out using the PRIMER Version 6 software. The PRIMER analysis was
interpreted following the user manual written by Clarke and Gorley (2006). The invertebrate
communities were all analysed separately based on the sampling method (kick, core and
grab).To determine similarities among community structures within sites a hierarchical
cluster analysis was carried out including the salinity ranges as factors. For this the Bray-
Curtis similarity coefficient was used to form a dendogram which illustrated clusters based
upon group similarities. Once significant relationships were established an analysis of
similarities (ANOSIM) was carried out via one way ANOVA to determine statistically
significant similarities between the community structures and salinity groups. Following this
analysis a similarity percentage analysis (SIMPER) was carried out to identify the species
contributing most to the dissimilarities and similarities found between the sample groups. To
demonstrate these species graphically, non-parametric multidimensional scaling (MDS) plots
were used to superimpose the distribution of the most abundant taxa found within each of
the three sampling methods over the sites and salinity groups.

17
3. Results
3.1 Community Structure in Transitional Waters
From the seven transitional waterways assessed a total of 8,892 invertebrates were
collected via kick samples from 11 sites (see Appendix 2). All invertebrates were identified
down to the nearest taxonomic level which represented 68 species from 51 families. From
the overall total, 2489 invertebrates were collected from Munster Blackwater River, 2285
from the River Barrow, 2466 from the River Tolka, 739 from the River Slaney, 496 from the
River Bandon, 258 form the River Lee and 159 from the Gweebarra River. In terms of
abundance, annelids from the subclass Oligochaeta accounted for the largest proportion of
the sample representing 59% of the total invertebrates collected. A majority of this proportion
(49%) was collected from the Munster Blackwater River (27%) and the River Tolka (22%)
with the remaining five sites accounting for the last 10% of the total Oligochaete population.
When looking at the sites individually the subclass Oligochaeta dominated three of the
sample sites, accounting for 96% of the total abundance collected from within the Munster
Blackwater River, 79% within the River Tolka and 29% within the River Slaney. For the River
Barrow both Gammaridae and Oligochaetes dominated the site equally both representing
29% of the sample. It is important to note that a total of 28 individuals of the invasive Asian
Clam, Corbicula fluminea, were found in the River Barrow. The Asian Clam represents 74%
of the total bivalves found in the Barrow making it the dominant species. Gammarus were
also the most frequently encountered species found in the River Lee accounting for 60% of
the overall sample. The most frequently encountered species found in the Gweebarra River
was the crustacean from the family Mysidae, Mysis relicta which represented 97% of the
sample. For the River Bandon, the mayfly Caenis horaria accounted for 40% of the sample
with diptera larvae from the family Chironomidae accounting for 32% of the sample. In
general the subclass Oligochaeta dominated four of the sample sites followed by
crustaceans from the families Gammaridae and Mysidae accounting for the rest.

18
A total of 2,848 invertebrates were collected from six of the sample sites assessed via core
samples (see Appendix 3). Of this value, 1069 were collected form the River Suir, 879 from
the River Barrow, 391 from the River Tolka, 273 from the Gweebarra River, 219 from the
River Slaney and 17 from the Bandon. Of the total sample collected the subclass
Oligochaeta represented 81% of the total abundance. Oligochaetes dominated four of the
sample sites accounting for 97% of the sample taken from the River Tolka, 96% from the
River Suir, 95% from the River Barrow and 30% from the River Slaney. The most frequently
encountered species found in the Gweebarra River was the amphipod Corophium
multisetosum. The core samples from the Bandon revealed a low abundance of
invertebrates with only 17 individuals being collected of which 9 were polychaetes from the
family Nereidae which represented 53% of the total sample. Polychaetes were only found in
the core samples. Specimens were also present in three of the other rivers of which 2 were
found in the Slaney, 10 in the Barrow and 21 from Gweebarra.
For the grab samples a total of 658 invertebrates were collected from three locations of
which 432 were obtained from the River Barrow, 168 from the Munster Blackwater River and
8 from the River Slaney (see Appendix 4). The subclass Oligochaeta was again the
dominant species found here accounting for 71% of the overall sample. For the River Barrow
Oligochaetes represented 100% of the total sample and 69% of the total abundance for the
River Slaney. The Munster Blackwater River was primarily dominated by a gastropod from
the family Hydrobiidae, Potamopyrgus jenkinsi, which accounted for 63% of the total sample.

19
3.2 Biotic Indices
3.2.1 Shannon Wiener Index
The Shannon Wiener Index (H) and Evenness (E) were calculated for all of the sites
assessed via kick, core and grab sampling methods. The interpretation of these values were
followed from the guidelines described by (Wenn, 2008, Chapman et al., 1996, Mason,
2002).
Table 4 below shows the values obtained for the kick samples. In terms of diversity, the
greatest species richness is found within the two Barrow sites, followed by the Bandon, Lee
and the two Slaney sites (SLA-C and D). All of these sites had relatively high H values which
indicate good water quality particularly for the rivers Barrow and Slaney site C. The three
sites with the lowest H values are the TO-A, GWEE-A and BWA-I. These values indicate that
the number of individuals were mostly from the same species. Both the Tolka and Munster
Blackwater rivers were largely dominated by the subclass Oligochaeta and Gwee-A by the
crustacean Mysis relicta. These low H values are indicative of poor water quality. The
species for these three sites were not evenly distributed as indicated by E. The species were
most evenly distributed for the GWEE-B and three Slaney sites.
Sites S # H' E
TO-A 9 2466 0.703 0.3
BAR-E 31 718 2.193 0.6
BAR-H 38 1464 2.238 0.6
GWEE-A 2 132 0.136 0.2
GWEE-B 10 27 1.683 0.7
BWA-I 8 2489 0.215 0.1
BAN-A 19 460 1.732 0.6
LEE-B 17 258 1.551 0.5
SLA-A 12 98 1.714 0.7
SLA-C 18 238 2.036 0.7
SLA-D 19 323 1.931 0.7
Table 4. Kick samples showing number of species (S), number of individuals (#), Shannon Diversity Index (H)
and Evenness (E). For a guide to sites refer to Appendix 2.

20
The core samples showed a great decrease in species diversity and abundances in
comparison to the kick samples (Table 5). Seven sites were removed for this analysis
because they only had one species present which resulted in H’ values of zero. The sites
removed were the Suir A, C & E, Barrow A & B and Bandon B & E. The highest H values
here are for BAN-D, SLA B, C and D which show the best water quality. The remaining sites
show values closer to zero indicating poorer water quality. A majority of the sites show that
species are quite evenly distributed mostly relating to the low species richness.
Sites S # H' E
TO-A 2 391 0.128 0.2
SUIR-B 3 15 0.628 0.6
SUIR-D 2 11 0.305 0.4
SUIR-G 2 2 0.693 1.0
SLA-A 6 54 0.587 0.3
SLA-B 4 20 1.208 0.9
SLA-C 9 92 1.316 0.6
SLA-D 4 52 1.152 0.8
BAR-C 3 222 0.058 0.1
BAR-D 3 283 0.432 0.4
BAR-E 2 61 0.084 0.1
BAR-F 2 10 0.325 0.5
GWEE-A 3 273 0.820 0.7
BAN-C 3 5 0.950 0.9
BAN-D 3 6 1.011 0.9
Table 5. Core samples showing number of species (S), number of individuals (#), Shannon Diversity Index (H)

21
Similar to the core samples the species diversity is greatly reduced for the grab samples
(Table 6). Only two of the Munster Blackwater sites (BWA-B and E) have H values greater
than one indicating a slight improvement of water quality in comparison to the other sites.
Over all these H values are indicative of poor water quality for all sites. The greatest
evenness is seen for the Munster Blackwater sites B, D, E and G. The remaining sites
indicate that the species are not evenly distributed.
Sites S # H' E
BAR-E 2 432 0.030 0.0
SLA-A 6 58 0.015 0.6
BWA-A 5 67 0.717 0.4
BWA-B 9 71 1.480 0.7
BWA-C 2 12 0.287 0.4
BWA-D 2 10 0.673 1.0
BWA-E 4 6 1.330 1.0
BWA-G 2 2 0.693 1.0
Table 6. Grab samples showing number of species (S), number of individuals (#), Shannon Diversity Index (H)

22
3.2.2 BMWP and ASPT
Both the Biological Monitoring Working (BMWP) scores and Average Score per Taxa
(ASPT) were calculated for all sites. The revised BMWP score sheet was used for this
analysis which was adapted from the original sheet provided by Walley and Hawkes (1997).
Figure 1 below shows the BMWP and ASPT scores computed for the kick samples. The
highest scores indicating very good water quality were for the BAN-A, BAR-E and H. Three
sites represented good water quality (LEE-B, SLA-C & D), two sites were of moderate status
(BWA-I and GWEE-B), two of poor status (TO-A and SLA-A) and the Gweebarra site A was
found to be of very poor status.
Figure 2. Bar chart displaying the BMWP values with the ASPT values above each bar for the kick samples.
5.1
6.3
5.3
5.9 6.1
4.9
5.2 5.5
6.0
4.5
6.2
0
20
40
60
80
100
120
140
BMWPScore
Sites

23
The BMWP scores for the core samples were much lower than those produced for the kick
samples (Figure 3). The lack of scoring taxa resulted in higher ASPT values because there
were less variables to divide the BMWP score by. Both the River Bandon sites B and E were
removed from this analysis because they had no scoring taxa. Both sites only had one
species present from the family Nereidae which is not included in the BMWP score sheet.
The highest status here was of moderate water quality for the River Slaney site D. A majority
of the sample sites (65%) were classed as very poor with the remaining sites being classed
a poor.
Figure 3. Bar chart displaying the BMWP values with the ASPT values above each bar for the core samples.
3.9
3.5
4.6
3.5
4.8
3.5
3.6
5.2
5.9
6.3
5.5
3.5 3.5
3.7 4.8
3.5
3.7
4.8
3.7
3.5
0
5
10
15
20
25
30
35
40
45
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-C
BAN-D
BMWPScores
Sites

24
For the grab samples the exactly half of the sites were considered to be of very poor water
quality and the other half of poor status (Figure 4). The BMWP scores were very low with
the highest value occurring at the Munster Blackwater site B at 33.1. As with the core
samples the number of scoring taxa was quite low due to a lack of diversity found with the
grab samples. This also resulted in higher ASPT values as there were fewer scoring taxa to
divide the BMWP score by.
Figure 4. Bar chart displaying the BMWP values with the ASPT values above each bar for the grab samples.
4.0
4.8
4.7
3.8 3.7
4.7
3.6
5.2
0
5
10
15
20
25
30
35
BAR-E
BWA-A
BWA-B
BWA-C
BWA-D
BWA-E
BWA-G
SLA-A
BMWPScores
Sites

25
3.2.3 EPT Taxa Richness
In order to have a closer look presence of the families least tolerant to organic pollution the
Ephemeroptera, Plecoptera and Tricoptera (EPT) taxa richness was calculated for all sites.
Table 7 below shows the number of EPT families present at all the sites assessed via kick
sampling. The Rivers Barrow and Bandon have the highest values here indicating they are
non-disturbed sites in pristine condition. The Lee-B and Slaney-C can be interpreted as
being moderately polluted having medium numbers of the EPT taxa present. The rest of the
sites have quite low numbers of families present therefore may be considered heavily
disturbed and polluted.
Table 7. EPT taxa richness numbers found at the 11 sites assessed via kick samples.
For the core samples the EPT taxa were only found in 5 of the 22 sites assessed and in
quite low numbers (Table 8). The site Slaney-C had the highest number of families present
with the rest of the sites ranging from 1-2. All of the core sample sites would be classed as
polluted by the EPT taxa richness index. Again these samples were characterised by low
species diversity and abundances which may reflect these results.
Table 8. EPT taxa richness numbers found at the 22 sites assessed via core samples.
SITE TO-A BAR-E BAR-H GWEE-A GWEE-B BWA-I BAN-A LEE-B SLA-A SLA-C SLA-D
Ephemeroptera 0 4 4 0 1 0 4 2 1 2 1
Plecoptera 1 0 0 0 1 0 1 0 0 0 0
Tricoptera 1 5 8 0 0 3 5 5 0 3 2
TOTAL 2 9 12 0 2 3 10 7 1 5 3
SITE SUIR-B SLA-A SLA-B SLA-C SLA-D
Ephemeroptera 0 1 1 2 1
Plecoptera 0 0 0 0 0
Tricoptera 1 1 1 2 1
TOTAL 1 2 2 4 2

26
The grab samples demonstrated even lower numbers of these taxa (Table 9). Only three of
the eight had EPT taxa present of which the Slaney-A had one caddis fly, Munster
Blackwater-A had one mayfly and BWA-B had 2 caddis flies. Similar to the core samples, all
of these sites would be classed as highly polluted and disturbed by the EPT richness index.
Table 9. EPT taxa richness numbers found at the 8 sites assessed via grab samples.
3.2.4 EPA Q-values
The Q-values were calculated for all sites following the guidelines described by the EPA
(2007). The Q-values were then used to derive the Ecological Quality Ratios (EQRs) to
further emphasize the water quality classification. The water quality categories designed by
the EPA were transposed to those described by the Water Framework Directive to better
understand the data.
Table 10 below shows the results for the kick samples. The Gweebarra site A was removed
from this assessment because there were too few species present. None of the sites were of
good ecological status which may indicate that these transitional waters will not meet the
WFD requirements for achieving at least good ecological status of all water bodies by 2015
(EC, 2000). A majority of the sites (60%) were of a moderate status with four sites (40%)
described as having poor water quality.
Site Q-value EQR WFD Status
TO-A 3-4 0.5 Moderate
BAN-A 3-4 0.7 Moderate
BWA-I 3 0.6 Poor
BAR-E 3-4 0.7 Moderate
BAR-H 3-4 0.7 Moderate
SLA-A 2-3 0.7 Poor
SLA-C 3-4 0.6 Moderate
SLA-D 3 0.5 Poor
LEE-B 3 0.6 Poor
GWEE-B 3-4 0.7 Moderate
Table 10. EPA Q-values, EQRs and WFD water quality status for the 11 sites assessed via kick sampling.
SITE BWA-A BWA-B SLA-A
Ephemeroptera 1 0 0
Plecoptera 0 0 0
Tricoptera 0 2 1
TOTAL 1 2 1

27
Table 11 below shows the values that were calculated for the core samples. Two of the
River Bandon sites (B and E) were removed from this analysis because too few species
were present. All but two of the sites were classed as bad ecological status based on the
species composition. Slaney sites B and C were considered here to have a poor water
quality.
Table 11. EPA Q-values, EQRs and WFD water quality status for the 22 sites assessed via core sampling.
As with the core samples, the grab samples were mostly classed in the bad ecological
groups with two as poor (Table 12).
BAR-E 1-2 0.3 Bad
SLA-A 1-2 0.3 Bad
BWA-A 2-3 0.5 Poor
BWA-B 2-3 0.5 Poor
BWA-C 1-2 0.3 Bad
BWA-D 1-2 0.3 Bad
BWA-E 1-2 0.3 Bad
BWA-G 1-2 0.3 Bad
Table 12. EPA Q-values, EQRs and WFD water quality status for the 8 sites assessed via grab sampling.
TO-A 2 0.4 Bad
SUIR-A 1 0.2 Bad
SUIR-B 1-2 0.3 Bad
SUIR-C 1 0.2 Bad
SUIR-D 1 0.2 Bad
SUIR-E 1 0.2 Bad
SUIR-G 1-2 0.3 Bad
SLA-A 1-2 0.3 Bad
SLA-B 2-3 0.5 Poor
SLA-C 2-3 0.5 Poor
SLA-D 1-2 0.3 Bad
BAR-A 1 0.2 Bad
BAR-B 1 0.2 Bad
BAR-C 1-2 0.3 Bad
BAR-D 1 0.2 Bad
BAR-E 1 0.2 Bad
BAR-F 1 0.2 Bad
GWEE-A 1 0.2 Bad
BAN-C 1-2 0.3 Bad
BAN-D 1 0.2 Bad

28
3.2.5 AMBI/M-AMBI
In addition to the freshwater indices used previously, a marine biotic index Azti Marine Biotic
Index (AMBI) was used to assess the waters based on the species considered to be more
tolerant of higher salinities. In accordance with the guidelines given by Borja et al. (2012) all
of the species considered to be fresh water by AMBI were removed from the data leaving a
total of 17 species for the kick samples, 8 for the core and 5 for the grabs.
The AMBI was first calculated for the kick samples (Figure 5). The Munster Blackwater site
(BWA-I) has the hghest AMBI values showing that it’s a heavily disturbed site. The rivers
Tolka-A, Barrow-E, Slaney C and D ar described as moderately polluted showing lower
AMBI values. The rivers Barrow-H, Gweebarra-A, Bandon-A and Slaney-A are reported as
being slightly disturbed. Two of the sites here are reported in the highest water quality level
with a status of undisturbed which include the Gweebarra-B and Lee-B. The M-AMBI was
then calculated for the WFD interpretation (Figure 6). Under the WFD water quality
categories, one site was reported with bad ecological status (BWA-I) and two sites (TO-A
and GWEE-A) with poor status. The sites Gweebarra-B and Bandon-A were shown to have
a moderate pollution status. The remaining six sites all meet the WFD requirements of
achieving good ecological status by 2015 with the river Barrow-H receiving the only high
status and the rest were of good ecological status.
For the AMBI analysis carried out with the core sampes two sample sites were excluded
(BAN-B and E) because no species were present under those listed by the index. Under the
AMBI analysis, 75% of the sites were defined as heavily disturbed with index values from 5-6
(Figure 7). Four of the sites were considered to be moderately disturbed (SUIR-B,G; GWEE-
A and BAN-C). The site showing the highest water quality was the Slaney site C which was
classed as slightly disturbed. The M-AMBI water quality interpretations for the WFD differed
greatly from the AMBI results for the core samples (Figure 8). Although a majority of the
sites (65%) were classed as bad or poor, the remaining 35% of the sites had a much higher
status. Two of the Slaney sites (A and D) were considered to be of a moderate status. The
remaining five sites all met the WFD requirements of achievng atleast good ecological status
with four sites being classed as good (SUIR B,G; GWEE-A and BAN-C) and one Slaney site
(C) being classed as high.

29
The Munster Blackwater site C was excluded from the AMBI analysis for the grab samples
because no species were present. For the grab samples more than half (57%) of the
samples were described as being heavily disturbed (Figure 9). One site was was classed as
moderate (BWA-G) and the remaining two sites (BWA-B and BWA-E) were considered to be
slightly disturbed. As seen with the core samples the WFD interpretation of this data via M-
AMBI completely differed from the AMBI water quality statuses (Figure 10). Half of the
sample met the WFD requirements of achieving atleast good ecological statuses with two
sites being considered as good (BWA-G and SLA-A) and two sites as high (BWA-B and
BWA-E). One site was classed as moderate (BWA-A) with the rest being defined as having a
bad ecological status.

30
Figure 5. AMBI results for the 11 sites assessed via kick samples showing pollution status and biotic index values.
Extremely disturbed
Heavily disturbed
Moderately disturbed
Slightly disturbed
Undisturbed

31
Figure 6. M-AMBI results showing the biotic indices and WFD interpreted water qualities for the 11 sites assessed via kick samples.
TO-A BAR-E BAR-H GWEE-A GWEE-B BWA-I BAN-A LEE-B SLA-A SLA-C SLA-D
STATIONS

32
Figure 7. AMBI results for the 22 sites assessed via core samples showing pollution status and biotic index values.
Extremely disturbed
Heavily disturbed
Slightly disturbed
Undisturbed

33
Figure 8. M-AMBI results showing the biotic indices and WFD interpreted water qualities for the 22 sites assessed via core samples.
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-C BAN-D
STATIONS

34
Figure 9. AMBI results for the 8 sites assessed via grab samples showing pollution status and biotic index values.
Undisturbed
Slightly 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 Samples
Group average
SLA-A
LEE-B
BAN-A
TO-A
BWA-I
SLA-C
SLA-D
BAR-H
BAR-E
GWEE-A
GWEE-B
Samples
100 80 60 40 20 0
Similarity
Transform: Square root
Resemblance: S17 Bray Curtis similarity
Salinity
Medium
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
Samples
100 80 60 40 20 0
Similarity
Salinity
Low
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 Samples
Group average
BWA-C
BWA-D
BWA-A
BWA-B
BAR-E
SLA-A
BWA-E
BWA-G
Samples
100 80 60 40 20 0
Similarity
Salinity
Low
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 Samples
Transform: Fourth root
Salinity
Medium
Low
High
Similarity
20
40
60
TO-A
LEE-B
GWEE-A
GWEE-B
BAN-A
BWA-I
BAR-HBAR-E
SLA-ASLA-C
SLA-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).
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 Samples
Salinity
Low
Medium
High
Similarity
10
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).
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 Samples
Salinity
Low
Medium
Similarity
30
40
50
BAR-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
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
%
Chironomidae 8.9 1.4 9.7 29.0
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 Samples
Subclass Oligochaeta
5
20
35
50
Low
Low
High
Medium
Low
Low
Low
Low
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 Samples
Gammarus duebeni
3
12
21
30
Low
Low
High
Medium
Low
Low
Low
Low
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
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
Nereidae 0.3 1.1 16.2 65.8
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
%
Nereidae 0.5 0.0 8.4 59.2
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
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 Samples
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 Samples
Nereidae
0.6
2.4
4.2
6
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

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 Samples
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
%
Nereidae 0.0 1.3 13.6 45.5
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
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 Samples
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 Samples
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.
Station TO-A LEE-B GWEE-A GWEE-B BAN-A BWA-I BAR-H BAR-E SLA-A SLA-C SLA-D
Erpobdella testacea 0 2 0 0 1 2 0 0 0 0 0
Glossiphonia complanata 0 0 0 0 0 0 3 2 0 28 3
Glossiphonia heteroclita 0 0 0 0 0 20 0 0 0 6 4
Glossiphonia marginata 0 0 0 0 0 0 1 0 0 0 0
Haementeria costata 0 1 0 0 0 0 0 0 0 0 0
Neridae 0 0 0 0 0 0 0 0 1 0 0
Subclass Oligochaeta 1938 13 0 3 4 2380 359 313 45 81 91
Acari/Hydrachnidea 0 0 0 1 0 0 12 2 0 2 0
Agrion virgo 0 0 0 0 0 0 0 2 0 0 0
Antrhipsodes albifrons 0 4 0 0 0 0 0 0 0 0 0
Antrhipsodes cinerus 0 2 0 0 6 1 2 4 0 1 1
Aphelocheirus aestivalis 0 0 0 0 0 0 21 10 0 0 6
Aselus aquaticus 10 8 0 0 12 0 15 15 0 3 2
Caenis horaria 0 2 0 0 194 0 135 101 0 0 0
Subfamily Ceratopogoninae 0 0 0 0 1 0 0 0 0 0 0
Ceraclea fulva 0 0 0 0 0 0 3 0 0 0 0
Cheumatopsuche lepida 0 0 0 0 1 0 2 0 0 0 0
Chironomidae 225 8 0 1 160 82 48 35 3 85 87
Corphium multisetosum 0 0 0 0 0 0 27 4 0 0 0
Cyrnus trimaculatus 0 0 0 0 1 0 0 0 0 0 0
Drusus annulatus 1 0 0 0 0 0 0 0 0 0 0
Ecdyonurus insignis 0 0 0 1 1 0 0 0 0 0 0
Elmis aenea 0 0 0 1 5 0 26 5 3 0 0
Ephemera danica 0 0 0 0 0 0 6 9 0 1 0
Ephemerella ignita 0 11 0 0 49 0 83 45 3 31 55
Gammarus pulex 0 0 4 14 0 0 0 0 0 0 0
Gammarus duebeni 285 0 0 0 0 0 546 95 23 44 28
Gammarus lacustris 0 154 0 0 21 0 25 0 0 0 0
Heptagenia sulphurea 0 0 0 0 1 0 1 0 0 0 0
Hydrophyche angustipennis 0 0 0 0 0 0 0 24 0 0 0
Hydropsyche instablis 0 0 0 0 0 0 5 0 0 0 0
Hydropsyche siltalai 0 3 0 0 5 0 26 15 0 0 0
Lepidostoma hirtum 0 35 0 0 10 1 22 54 0 5 4
Limnephilidae 0 0 0 0 0 0 0 0 0 2 0
Limnious volckmari 0 1 0 1 1 0 15 9 1 0 4
Limoniidae, Antocha spp. 0 0 0 0 0 0 19 2 0 0 0
Mysis relicta 0 0 128 0 0 0 0 0 7 0 0
Palaemonidae/Palaemonetes varians 0 0 0 0 0 0 0 0 4 0 0
Perlididae 1 1 0 3 0 0 0 0 0 0 0
Taenioptergidae 0 0 0 0 1 0 0 0 0 0 0
Polycentropus flavomaculatas 0 0 0 0 0 0 2 0 0 0 0
Potamonectes griseostriatus 0 0 0 1 1 0 0 0 1 13 15
Sialis lutaria 0 0 0 0 0 0 0 1 0 0 0

82
Appendix 2 continued…
Station TO-A LEE-B GWEE-A GWEE-B BAN-A BWA-I BAR-H BAR-E SLA-A SLA-C SLA-D
Spercheidae 0 0 0 1 0 0 0 0 0 0 0
Sphaeroma hookeri 0 0 0 0 0 0 0 0 4 0 0
Sericostoma personatum 0 1 0 0 0 0 0 0 0 0 0
Tinodes waeneri 0 0 0 0 0 1 5 6 0 0 0
Bithynia leachii 0 0 0 0 0 0 2 0 0 0 0
Corbicula fluminea 0 0 0 0 0 0 20 8 0 0 0
Lymnea peregra 0 0 0 0 0 0 0 0 0 1 1
Lymnea (Galba) truncatula 0 0 0 0 0 0 0 1 0 0 0
Viviparus viviparus 1 0 0 0 0 0 0 2 0 0 0
Valvata cristata 1 0 0 0 0 0 1 0 0 1 0
Valvata macrostoma 0 0 0 0 0 0 0 0 0 0 0
Valvata piscinalis 4 0 0 0 0 0 1 0 0 0 0
Acroloxus lacustris 0 1 0 0 0 0 0 0 0 0 5
Potamopyrgus jenkinsi 0 11 0 0 21 2 0 0 0 0 0
Succinea putris 0 0 0 0 0 0 3 5 0 0 0
Theodoxus fluviatiles 0 0 0 0 0 0 12 13 0 0 0
Sphaeriidae, Pisidium spp. 0 0 0 0 0 0 6 3 0 2 0
Sphaerium rivicola 0 0 0 0 0 0 0 1 0 0 0
Pseudamnicola confusa 0 0 0 0 0 0 6 6 3 0 13
Planorbis contortus 0 0 0 0 0 0 3 0 0 0 0
Unio tumidus 0 0 0 0 0 0 0 0 0 0 1
Zonitoides nitidus 0 0 0 0 0 0 2 0 0 0 0
Anguilla anguilla 0 0 0 0 0 0 3 17 0 2 2
Lampetra planeri 0 0 0 0 0 0 0 0 0 0 1
Phylum Mystery 0 0 0 0 0 0 0 0 1 5 4

83
Appendix 3. Invertebrate species found for the core samples.
Station Tolka 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
Nereidae 0 0 0 0 0 0 0 2 0 0 0 0 0 0 10 0 0 26 1 0 3 5
Oligochaeta 380 40 2 1000 10 1 1 47 5 32 14 300 3 220 250 60 9 61 0 1 3 0
Anthripsodes cinerus 0 0 0 0 0 0 0 0 3 2 0 0 0 0 0 0 0 0 0 0 0 0
Chironomidae 10 0 12 0 0 0 1 0 0 9 22 0 0 1 0 0 0 0 0 0 0 0
Gammarus duebeni 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Gammarus pulex 0 0 0 0 0 0 0 0 0 43 0 0 0 0 0 0 0 0 0 0 0 0
Hydropsyche siltalai 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Corophium multisetosum 0 0 0 0 1 0 0 0 0 0 0 0 0 0 10 0 0 186 0 0 0 0
Lepidostoma hirtum 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Mysis relicta 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
Heptagenia sulphurea 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0
Tinodes waeneri 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0
Gammarus zaddichi 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Ephemerella ignita 0 0 0 0 0 0 0 1 10 33 16 0 0 0 0 0 0 0 0 0 0 0
Potamonectes griseotriatus 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0
Succinea putris 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Acroloxus lacustris 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
Bithynia leachii 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
Potamopyrgus jenkinsi 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0
Corbicula fluminea 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0

84
Appendix 4. Invertebrate species found for the grab samples.
Stations BAR-E BWA-A BWA-B BWA-C BWA-D BWA-E BWA-G SLA-A
Oligochaeta 430 1 4 0 4 2 1 40
Anthripsodes albifrons 0 0 1 0 0 0 0 0
Anthripsodes cinerus 0 0 2 0 0 0 0 0
Gammarus duebeni 2 2 1 0 0 2 0 1
Caens horaria 0 3 0 0 0 0 0 0
Chironomidae 0 0 5 0 0 0 1 10
Corophium multisetosum 0 0 20 0 0 2 0 0
Elmis aenea 0 1 0 0 0 0 0 0
Lepidostoma hirtum 0 0 0 0 0 0 0 2
Limnious volckmari 0 0 2 0 0 0 0 0
Mysis relicta 0 0 0 0 0 0 0 3
Potamopyrgus jenkinsi 0 54 34 11 6 0 0 0
Pisidium sp. 0 0 2 1 0 0 0 0
Pseudamnicola confusa 0 0 0 0 0 0 0 2

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