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

4

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

5

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

Donegal River 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

BM

WP

Sc

ore

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

05

101520253035404550

TO

-A

SU

IR-A

SU

IR-B

SU

IR-C

SU

IR-D

SU

IR-E

SU

IR-G

SLA

-A

SLA

-B

SLA

-C

SLA

-D

BA

R-A

BA

R-B

BA

R-C

BA

R-D

BA

R-E

BA

R-F

GW

EE

-A

BA

N-C

BA

N-D

BM

WP

Sc

ore

s

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

BA

R-E

BW

A-A

BW

A-B

BW

A-C

BW

A-D

BW

A-E

BW

A-G

SLA

-A

BM

WP

Sc

ore

s

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 SamplesGroup average

SLA-A

LEE-B

BAN-A

TO-A

BWA-I

SLA-C

SLA-D

BAR-H

BAR-E

GWEE-A

GWEE-B

Sa

mp

les

100 80 60 40 20 0

Similarity

Transform: Square root

Resemblance: S17 Bray Curtis similarity

SalinityMedium

Low

High

43

abundances found at all sites for the kick samples. Cluster four joined the rivers Lee (LEE-B)

and Bandon (BAN-A) at 50% which is related to similar species diversity. The final Slaney

site (SLA-A) was shown to have a low similarity to SLA-C (39%) and SLA-D (44%) mostly

relating to the low abundances found here.

The following dendogram illustrates the similarities found among the core samples with

salinity groups of Low <1, Medium 2-6 and High 13-27 across the 22 sites sampled (Figure

12).

Figure 12. Dendogram illustrating the similarities between the 22 sites assessed via core samples using the

Bray-Curtis similarity coefficient on square root transformed data with the salinity groups as factors with Low <1,

Medium 2-6 and High 13-27.

The dendogram identifies six main clusters with the core samples. Working up the

dendogram the first main cluster groups five sites at 50% similarity. These were all grouped

together because the subclass Oligochaeta dominates each site within the cluster at low

abundances ranging from 10-60 individuals. The second cluster includes a further five sites

which were also grouped together based on the larger Oligochaete abundances ranging

from 220-1000 individuals at a similarity of 40%. Cluster three includes the only Gweebarra

site (GWEE-A) showing no similarity to other groups. This is the only site which was largely

dominated by the crustacean Corophium multisetosum. Cluster four includes the three

remaining Slaney sites which are grouped together at 25% based on their high abundances

of the mayfly Ephemerella ignita (which were only found at the Slaney sites) and

Core Samples

Group average

BAN-D

BAN-B

BAN-E

SUIR-B

BAN-C

SUIR-G

SUIR-E

BAR-B

SLA-B

SLA-C

SLA-D

GWEE-A

SUIR-C

BAR-D

TO-A

BAR-A

BAR-C

SUIR-D

BAR-F

SLA-A

SUIR-A

BAR-E

Sam

ple

s

100 80 60 40 20 0

Similarity



SalinityLow

Medium

High

44

Oligochaetes. Cluster five forms at 20% including SUIR-B, C and D as well as BAN-C and

BAR-B which all had the lowest abundances and diversity of species primarily comprising of

Oligochaetes. The final cluster grouped the remaining river Bandon sites together at a lower

similarity level of approximately 15% based on the presence of polychaetes from the family

Nereidae which only occurred at BAN-B,D &E as well as GWEE-A in the core samples.

The grab samples had much lower species richness and abundance in comparison to the

kick and core samples. The dendogram for the grab samples highlights two main clusters

with one large cluster linking them together (Figure 13).

Figure 13. Dendogram illustrating the similarities between the 8 sites assessed via grab samples using the Bray-

Curtis similarity coefficient on square root transformed data with the salinity groups as factors with Low <1 and

Medium 5.

For the grab samples two main clusters are identified. Cluster one has grouped BWA-E,

BWA-G, SLA-A, and BAR-E together at a similarity level of 20%. Within this cluster the two

Munster Blackwater sites are clustered together with a similarity of 32% which is based on

extremely low species diversity and abundances. The BAR-E and SLA-A are grouped at

40% primarily due to the high number of Oligochaetes. Cluster two encompasses the

remaining Blackwater sites at 37% with A & B showing 48% similarity and C & D with 55%

similarity. These four sites are clustered together because of the presence of the gastropod

Potamopyrgus jenkinsi which occurs in high numbers at sites A & B (88) and low numbers at

sites C & D (17).

Grab SamplesGroup average

BWA-C

BWA-D

BWA-A

BWA-B

BAR-E

SLA-A

BWA-E

BWA-G

Sam

ple

s

100 80 60 40 20 0

Similarity



SalinityLow

Medium

45

3.3.2 MDS Analysis for Similarities

A non-parametric multidimensional scaling (MDS) analysis was carried out for the kick, core

and grab samples to graphically demonstrate the relationships between the sites and

demonstrate the inclusion of the >1 salinity factor in linking sites. For this analysis, the

similarities between sites, community structure and salinity groups were computed using the

Bray-Curtis similarity coefficient on the fourth root transformed abundance data, displaying

the data in 2-dimensional plots.

For the kick samples the MDS ordination plot groups the sites together at similarity levels of

20, 40 and 60 percent (Figure 14).

Figure 14. 2-dimensional MDS plot using Bray-Curtis similarity coefficient on fourth root transformed abundance

data for the 11 sites assessed via kick samples across three salinity groups, Low <1, Medium 3-5, and High 27.

As with the dendogram, both Gweebarra sites are grouped alone, as these showed the least

similarity to the other sites. The remaining sites formed one large group at a similarity of

20%, followed by four groups at 40%. SLA-A was grouped alone here because it had much

lower species abundances then the other two Slaney sites. The 60% similarity formed three

main groups which grouped the two Barrow sites together, the two remaining Slaney sites

and the rivers Tolka and Munster Blackwater which is similar to the dendogram. The Lee

and Bandon were grouped together at 40% as they had a similarity of 50%.

Kick SamplesTransform: Fourth root


SalinityMedium

Low

High

Similarity20

40

60

TO-A

LEE-B

GWEE-A

GWEE-B

BAN-A

BWA-I

BAR-HBAR-E

SLA-ASLA-CSLA-D

2D Stress: 0.07

46

Considering the similarity levels were much lower among the core samples the similarity was

fixed at 10, 30 and 50 percent as these best described the data graphically (Figure 15).


data for the 22 sites assessed via core samples across three salinity groups, Low <1, Medium 2-6, and High 13-

27.

As with the dendogram one major group was formed at a similarity level of 10%, followed by

four groups at 30% and six main groups at 50% which are illustrated with more clarity via the

2-dimensional plot.

Core SamplesTransform: Fourth root


SalinityLow

Medium

High

Similarity10

30

50

TO-A

SUIR-A

SUIR-B

SUIR-C

SUIR-D

SUIR-E

SUIR-G

SLA-A

SLA-B

SLA-C

SLA-D

BAR-A

BAR-B

BAR-C

BAR-D

BAR-E

BAR-F

GWEE-A

BAN-B

BAN-C

BAN-D

BAN-E

2D Stress: 0.14

47

For the grab samples the 2-dimensional MDS plot showed that similarities of 30, 40 and 50

percent best fit the data (Figure 16).


data for the 8 sites assessed via kick samples across two salinity groups, Low <1 and Medium 5.

The three main groups found on the dendogram are show to group together at 30%. The

Munster Blackwater sites C and D show the greatest similarity here at 50%, followed by

BWA-A and BWA-B at 40%. The remaining sites are grouped together 30% similarity. There

is much less similarity observed between the grab samples.

Grab SamplesTransform: Fourth root


SalinityLow

Medium

Similarity30

40

50BAR-E

BWA-A

BWA-B

BWA-C

BWA-D

BWA-E

BWA-G

SLA-A

2D Stress: 0.07

48

3.3.3 ANOSIM for Salinity Groups

In order to determine statistically significant similarities between the community structures

and salinity groups an analysis of similarities (ANOSIM) was carried out for all sampling

methods. The maximum permutations were set at 999 for all the sampling methods. The

ANOSIM test showed that there were strong positive linear relationships between the

community structure and differing salinity groups for the kick samples. The overall global R

value was 0.846 with a significance level of p<0.2%. A total of 495 permutations were

carried out (Table 14).

Groups

R-Significance

Statistic Significance

Level % Actual

Permutations Number

Observed

Low ,High 1 11.1 9 1

Low, Medium 0.75 2.2 45 1

High, Medium 1 33.3 3 1

Table 14. Pairwise tests calculated by ANOSIM with a maximum of 999 permutations for the kick samples via

one-way ANOVA for the 11 sites across three salinity ranges Low <1, Medium 3-5 and High 27.

For all salinity groups the R-statistic value is closer to one than zero, therefore the null

hypothesis that there is no difference in community structure among the salinity groups must

be rejected. The greatest differences are seen when comparing the high salinity groups with

the medium and low groups. This can best be explained by the lack of species found in the

only high salinity site, Gweebarra-A, which only had two species present. These both show

an optimum R value of 1 which indicates a complete difference in community structure

between the two salinity groups. In terms of p-values a significant difference is only found

between the Low, Medium groups with a significance level of 2.2% which is less than 0.05.

As outlined by Clarke and Gorley (2006) low significance levels must be interpreted carefully

because they are very dependent on the number of replicates carried out which are quite low

for the Low, High (9) and High, Medium (3) groups. A low number of replicates may result in

a large R-value and thus a large p-value which indicates that it is more useful to interpret the

R-values in this case (Clarke and Gorley, 2006). Therefore, for the kick samples there is a

significant difference between the community structure and salinity levels.

49

The ANOSIM results for the core samples showed a global R value of 0.078 with a

significance level of 22.8% (Table 15).

Groups

R-Significance

Statistic Significance

Level % Actual

Permutations Number

Observed

Low, Medium 0.075 26.9 999 268

Low, High 0.086 28.8 153 44

Medium, High -0.214 73.3 15 11

Table 15. Pairwise tests calculated by ANOSIM with a maximum of 999 permutations for the core samples via

one-way ANOVA for the 22 sites across three salinity ranges Low <1, Medium 2-6 and High 13-27.

Looking at the R-statistic the group Medium, High shows a very strong negative linear

relationship between community structure and salinity groups. The sites with Low, Medium

and Low, High salinities show almost no linear relationship between the variables as the R-

statistic is close to zero. The R values for all sites are closer to zero than one therefore the

null hypothesis must be accepted indicating that there is no difference between the variables

being tested. The significance levels for all sights did not exhibit any differences either as all

p-values were greater than 0.05. In accordance with the advice described by Clarke and

Gorley (2006) the pairwise comparisons are not significant and should not be interpreted

because the null hypothesis was not rejected.

Considering the salinity groups for the grab samples were not differing with only one site

(SLA-A) representing the medium group and the rest low the ANOSIM test could not be

carried out effectively. This is also related to the lack of species richness and abundances

found with the grab samples. The test results showed a global R value of 0.109 suggesting

there were little differences in community structure between the two salinity groups. The

significance level of the sample was at 50% which is far greater than the acceptable p-

values of less than 0.05.

50

3.3.4 SIMPER Analysis between Salinity Groups

Kick Samples

A Similarity Percentage analysis (SIMPER) was carried out to identify the species which

contributed the most to the differences found between the sample groups. For the kick

samples the groups with salinities of Low and High showed the greatest dissimilarity with a

complete average dissimilarity of 100% (Table 16). The subclass Oligochaeta contributed to

the highest average dissimilarity of 20.5% followed by Mysis relicta 13.1%, the family

Chironomidae at 10.1% and Gammarus duebeni accounting for 51% of the overall

dissimilarity. A further 22 species made up the rest of the dissimilarity seen between the

groups.

Species

Group Low Avg.

Abundance

Group High Avg.

Abundance Contribution

% Cumulative

%

Subclass Oligochaeta 19.2 0.0 20.5 20.5

Mysis relicta 0.0 11.3 13.1 33.6

Chironomidae 8.9 0.0 10.1 43.7

Gammarus duebeni 7.7 0.0 6.9 50.6

Table 16. SIMPER analysis displaying the Low (<1) and High (27) salinity groups with an average dissimilarity of

100% highlighting the primary contributing species for the 11 sites assessed via kick samples.

For the samples grouped High and Medium an average dissimilarity of 86.5% (Table 17)

was computed by the SIMPER analysis with Mysis relicta, subclass Oligochaeta, Gammarus

duebeni and Gammarus pulex accounting for the highest dissimilarities with a cumulative

percent of 61%. The remaining 9 species described the rest of the dissimilarities.

Species

Group High Avg.

Abundance

Group Medium

Avg. Abundance

Contribution %

Cumulative %

Mysis relicta 11.3 1.3 35.6 35.6



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 SamplesTransform: Square root


Subclass Oligochaeta

5

20

35

50

Low

Low

High

Medium

Low

Low

LowLow

Medium

LowLow

2D Stress: 0.03

53

Figure 18. MDS plot showing the square root transformed abundances of the Gammarus duebeni which

contributed most to the dissimilarities over the salinity groups (High-27, Medium- 3-5 and Low- <1) using Bray-

Curtis similarity coefficient for the kick samples.

Figure 18 shows that the abundances for Gammarus duebeni were also highest in the low

salinity groups and they were also completely absent from the high salinity group (GWEE-A)

along with one medium group GWEE-B and two low groups LEE-B, BWA-I and BAN-A. The

abundances were highest at TO-A and BAR-H showing a maximum of 212.

Kick SamplesTransform: Square root


Gammarus duebeni

3

12

21

30

Low

Low

High

Medium

Low

Low

LowLow

Medium

LowLow

2D Stress: 0.03

54

Core Samples

Although there were no statistically significant differences found in relation to community

structure and salinity groups for the core samples, SIMPER analysis was carried out to

demonstrate the species that contributed most to the dissimilarities between the groups. The

highest dissimilarity was seen for the salinity groups Medium and High with 69% (Table 19).

Here the species which contributed mostly to the differences were Corophium multisetosum

(23.5%), subclass Oligochaeta (22%), the families Nereidae (19.4%) and Chironomidae

(17.6%) adding up to a cumulative of 82.5%.

Species

Group Medium

Avg. Abundance

Group High Avg.


% 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.


% 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 SamplesTransform: Square root


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.



Nereidae

0.6

2.4

4.2

6

Low

Low

Low

Low

Low

MediumHigh

Medium

Low

Low

Low

Low

Low

Low

Low

Low

Medium

High

Medium

Low

Low

Low

2D Stress: 0.11

58

Figure 21. MDS plot showing the square root transformed abundances of the family Chironomidae which

contributed most to the dissimilarities over the salinity groups (High-13-27, Medium- 2-6 and Low- <1) using

Bray-Curtis similarity coefficient for the core samples.

The Chironomids are also only present in 6 of the 22 sites assessed and are found in the low

and high salinities but absent from the medium groups. The lack of Chironomids found in the

other sites may be a result of sampling methods or their habitat preferences. They are

present in highest abundances in the SLA-D which had a low salinity, followed by TO-A,

SLA-C and SUIR-B which all had low salinities. A low abundance of the diptera larvae is also

found at the high salinity site, SUIR-G and remaining low salinity site BAR-C.



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 SamplesTransform: Square root


Oligochaeta

3

12

21

30

Low

Low

Low

Low

Low

Low

Low

Medium

2D Stress: 0.06

61

Figure 23. MDS plot showing the square root transformed abundances of the family Chironomidae which

contributed most to the dissimilarities over the salinity groups (Medium- 5 and Low- <1) using Bray-Curtis

similarity coefficient for the grab samples.

The Chironomids contributed significantly to the dissimilarity between the sites; however

they are only present at 3 of the 8 sights. The largest abundances are seen within the

medium group which is the SLA-A, followed by the low group, BWA-A and at the top of the

graph BWA-G.

Grab SamplesTransform: Square root


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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