coates et al

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Marine Pollution Bulletin 55 (2007) 225–240

Efficacy of a multi-metric fish index as an analysis tool forthe transitional fish component of the Water Framework Directive

Steve Coates *, Adam Waugh, Alice Anwar, Matthew Robson

Environment Agency, Rivers House, Crossness Works, Belvedere Road, Abbeywood, London SE2 9AQ, UK

Abstract

The WFD has introduced an international commitment to assess the ecological status of transitional waters (TWs), within which fishcommunities are a key biological monitoring component. The Transitional Fish Classification Index (TFCI) outlined in this paper uses10 ecological measures to analyse fish populations caught from various ecological niches using a variety of gear types within the Thamesestuary. These reach and method-specific communities are then compared to a reference population created from a ‘healthy’ populationfrom TWs of a similar type. The results indicate a progressive downstream increase the quality of fish communities, consistent with pre-vious work; variation between methods can be accounted for by gear selectivity. Overall, the TFCI is an effective communication tool forconverting ecological information into an easily understood format for managers, policy makers and the general public.� 2006 Elsevier Ltd. All rights reserved.

Keywords: WFD; Thames estuary; IBI; Biological indicators; Ecosystem health; Fish

1. Introduction

The Water Framework Directive (WFD) has introducedan international commitment to assess the ecological statusof transitional waters (estuaries), within which fish commu-nities are a key biological monitoring component (Euro-pean Council Directive, 2000). Fish communities can bedescribed according to a variety of characteristics such ascomposition, trophic structure and diversity of the assem-blage, as well as abundance and biomass of the individuals(Harrison et al., 2000; Lobry et al., 2003; Coates et al.,2004; Harrison and Whitfield, 2004). Trends in one or moreof these community attributes can be used to monitor theecological functioning and ‘health’ of a particular ecosys-tem (Whitfield and Elliott, 2002).

The WFD specifies that the transitional fish quality ele-ment is to be assessed by taking account of the compositionand abundance of the fish fauna and that of disturbance-sensitive taxa. In order to carry out an integrated approach

0025-326X/$ - see front matter � 2006 Elsevier Ltd. All rights reserved.

doi:10.1016/j.marpolbul.2006.08.029

* Corresponding author.E-mail address: [email protected] (S. Coates).

to assess the fish community of the Thames estuary, a num-ber of attributes have been incorporated into a single multi-metric index. This methodology has been used in manyother studies, (Miller et al., 1988; Deegan et al., 1997; Har-rison et al., 2000; USEPA, 2000; Goethals et al., 2002;Borja et al., 2004; Breine et al., 2004).

As part of the assessment of the fish faunal assemblagewithin an estuary, a number of monitoring techniquesand sampling strategies have been developed (Hemingwayand Elliott, 2002). Environment Agency, Thames Regionhas established a long-term monitoring programme basedon the recovery of the Thames estuary, with the initial sur-vey work based on power station fish impingement(Wheeler, 1979; Attrill, 1998; Kirk et al., 2002). However,with the decommissioning of the Thames power stationsand the need to address the data gaps caused by this sin-gle-strand survey approach, a multi-method monitoringprogramme was established (Colclough et al., 2000,2002). This approach combines a variety of methods suchas seine netting, beam trawling and otter trawling. Differ-ent survey techniques have varying gear selectivities so itis important to incorporate a suite of techniques (vonBrandt, 1964) to obtain a comprehensive picture of each

mailto:[email protected]

Table 1Candidate fish metrics

Metric type No. Metric

Species diversity andcomposition

1 ‘Species composition’2 Presence of ‘Indicator Species’

Species abundance 3 Species relative ‘abundance’4 Number of taxa that make up 90% of

the ‘abundance’

Nursery function 5 Number of estuarine resident taxa6 Number of estuarine-dependent marine

taxa

Trophic integrity 7 Functional guild composition8 Number of benthic invertebrate feeding

taxa9 Number of piscivorous taxa

10 Feeding Guild Composition

Metric 1 is based on presence/absence. Metric numbers 3 and 4 are basedon species relative abundance. The remaining metrics are based on thenumber of taxa present.

Table 2Scoring system for metrics 1 and 3, based on percentage similarity of eachsample to reference, calculated using a Bray-Curtis similarity index

Percentage similarity Relative score

0–19.9 120–39.9 240–59.9 360–79.9 480–100 5

226 S. Coates et al. / Marine Pollution Bulletin 55 (2007) 225–240

fish community assessed e.g. benthic, pelagic and marginal.The Thames multi-method monitoring strategy has nowbeen recognised as an example of ‘European Best Practice’in establishing an estuarine fishery-monitoring programme(European Commission, 2000).

Karr (1981) derived the basis of a metric scoring systemfrom work in assessing the ‘Biotic Integrity’ of NorthAmerican fish communities. The principles of the Indexof Biotic Integrity (IBI) established by Karr are widelyaccepted and have been used as a classification tool forfisheries assessment (Harrison and Whitfield, 2004; Borjaet al., 2004; Breine et al., 2004; Coates et al., 2004). Theseprinciples have been used recently for WFD purposeswithin the ‘Fish-based Assessment Method for the Ecolog-ical Status of European Rivers’ (FAME) (Kestemont et al.,2002). To consider the biotic integrity of a water body, acomparison must be made between the data and a ‘refer-ence’ community.

The approach described here aims to devise metrics suit-able for analysing fisheries data that are appropriate for theWFD transitional fish component requirements. Further-more, by using the Thames estuary fish long-term data ina multi-method, reach-based format the efficacy of the met-rics can be examined in detail.

2. Materials and methods

2.1. Selection of metrics

USEPA (2000) define a metric as a ‘‘measurable factorthat represents some aspect of biological assemblage, struc-ture, function, or other community component’’. The selec-tion of the candidate metrics were devised partially on aclassification scheme developed for use in South Africanestuaries (Harrison et al., 2000; Harrison and Whitfield,2004) and from the output of an Environment AgencyR&D report to develop classification tools for the WFD(Coates et al., 2004). These metrics also reflect the ‘norma-tive definitions’ for the assessment of biological quality asdefined by the WFD. The candidate metrics are based uponeither presence/absence data, ‘relative’ abundance data ornumber of taxa present (Table 1). Combined, the metricsprovide an overall Transitional Fish Classification Index(TFCI). The measured element of the TFCI is a relativescore (RS). Created for each metric, the RS indicates thesample’s proximity to an ideal or ‘reference’ community.An RS is created for each sampling occasion. These arethen averaged to create a combined RS for each samplingregime. These are again averaged to create an overall RSfor each reach.

2.1.1. Metric 1 – ‘Species Composition’

A key indicator of the biotic integrity of a faunal com-munity is the composition of species within a sample (Har-rison and Whitfield, 2004). To create the RS, firstly theinherent variability or ‘noise’ within each catch wasreduced by removing all but the 20% most frequent species.

This top quintile was analysed using a Bray-Curtis similar-ity index to determine the percentage similarity of eachsample compared to the reference. An RS of one to fiveis weighted evenly between 0 and 100 (Table 2).

2.1.2. Metric 2 – presence of ‘Indicator Species’

Metric 2 provides a measure of ‘disturbance-sensitivespecies’ termed ‘indicator taxa’ by the WFD and was calcu-lated for each sample. Species were selected on the basis oftheir conservation status and protection under EU legisla-tion (European Council Directive, 1992), their sensitivity todissolved oxygen (Turnpenny et al., 2004), or other traitsthat make them sensitive to disturbance. Lampreys (Lam-

petra fluviatilis & Petromyzon marinus) were selected fortheir sensitivity to water quality and spawning habitatquality, as were Allis shad (Alosa alosa) and Twaite shad(Alosa fallax). Salmonids (Salmo salar and Salmo trutta)were selected for their conservation status and sensitivityto dissolved oxygen (DO) and temperature (T). Smelt(Osmerus eperlanus) were also chosen for their sensitivityto DO and the European eel (Anguilla anguilla) was chosenfor its present sensitivity to anthropogenic exploitation. Allof the above species are sensitive to hydromorphologicalchanges, which have occurred to most UK TWs, theThames being an example of one of the most severelydisturbed.

S. Coates et al. / Marine Pollution Bulletin 55 (2007) 225–240 227

If any of the above taxonomic groups were present, ascore of 1 was assigned to the sample. Scores were adjustedaccording to the sample method and are based upon theprobability of capture for each species per sample tech-nique. Seine net samples, for example, included shads, lam-preys, salmonids, eels and smelt whereas only eels, smeltand lampreys were included for beam and otter trawling.

2.1.3. Metric 3 – species relative ‘abundance’

Similarly to Metric 1, the abundance of species providesan excellent indicator of biotic integrity (Harrison andWhitfield, 2004). Unlike Metric 1 where a presence orabsence of taxa was used to create an RS, the relative abun-dance of individuals per sample was used to create thescore. Similarly to metric 1, only the top quintile of mostabundant species per sample were compared to the refer-ence using a Bray-Curtis similarity index. The RS wasderived from the per cent similarity values. It is calculatedas a percentage of each taxa present in relation to totalnumber or relative abundance caught.

2.1.4. Metric 4 – number of taxa that make up 90% ofabundance

A healthy, unimpacted estuary will contain many specieswithout a dominating presence from one or only a few spe-cies. By considering how many species make up 90% of thecatch, one can determine whether dominating taxa arepresent.

The number of taxa were counted for each sample andranked from the most to the least frequent. The mean num-ber of taxa within the upper quintile (top 20%) was deter-mined and used as the boundary value between RS4 andRS5. Percentages of this value were used to calculate theboundaries for each metric. Each boundary range had anassociated score (Table 3).

2.1.5. Metric 5 – number of estuarine resident taxa

Metrics 5–7 are based on the number of functionalguilds represented by the fish in each sample. Each fish spe-cies was allocated to a ‘Guild’ that best describes its life his-tory characteristics within an estuary (Elliott and Dewailly,1995; Hemingway and Elliott, 2002):

• Estuarine residents (ER) – Fishes that spend their entirelife in estuaries.

• Marine seasonal species (MS) – Fishes that use estuariesfor part of the year.

Table 3Example of scoring system used for metrics 4–6, 8 and 9. Example is basedon the upper quintile having a mean of 6 taxa

Percentage of mean Boundaries RS

0–19.9 <1.19 120–39.9 1.2–2.39 240–59.9 2.4–3.59 360–79.9 3.6–4.79 480–100 4.8+ 5

• Freshwater species (FW) – Fishes that are presentmainly or exclusively at low salinity values.

• Marine juvenile species (MJ) – Fishes that use estuariesas nursery grounds or during juvenile phases of their lifecycle.

• Diadromous species (CA) – Species that migratebetween fresh and salt water during different life stages.

• Marine adventitious species (MA) – Species that areconsidered fully marine but inhabit estuariestemporarily.

For Metric 5 the estuarine resident species were filteredin each sample. The method described above in Metric 4was followed to create a score from one to five.

2.1.6. Metric 6 – number of estuarine-dependent marine taxa

For this metric, fish that are dependent on estuaries dur-ing the early life phases or during particular parts of theyear (marine juveniles or marine seasonal) were treated inthe similarly to Metric 4.

2.1.7. Metric 7 – functional guild composition

An unimpacted, healthy estuary should contain speciesof fish that represent all functional guilds (Elliott andDewailly, 1995; Hemingway and Elliott, 2002), althoughone must account for the fact that an estuary is highly het-erogeneous. It is therefore unlikely to catch freshwater spe-cies in the lower estuary, for instance. So Metric 7 wasadjusted according to the section of the transitional water(TW) analysed. All functional guilds apart from the fresh-water taxa were scored in the mid and lower data sets andin the upper TW, all guilds were scored except marineadventitious species. Scores were assigned according tothe number of taxa present (Table 4).

2.1.8. Metric 8 – number of benthic invertebrate feeding taxa

Feeding guilds have been used for some time as a way toevaluate fish communities and structure (e.g. Goldman andTalbot, 1976). Increased levels of anthropogenic stress havealso been shown to remove one of more of the feedingguilds (Harrison and Whitfield, 2006). The feeding guildsused for metrics 8–10 were developed by Whitfield (1998):benthic invertebrate feeders, zooplankton feeders, piscivo-rous feeders and detritus feeders. For this metric, fishcaught that are considered to feed exclusively or mainlyon bottom-dwelling invertebrates were considered for anal-ysis. RS creation and score allocation was derived in a sim-ilar fashion to metric 4.

Table 4Scoring system for metric 7 showing the score assigned according to thenumber of taxa present

Number of taxa Score

0–1 12 23 3

Table 5Scoring system for metric 10 showing the score assigned according to thenumber of feeding guilds present

No. of guilds present Score

0 11 22 33 44 5


2.1.9. Metric 9 – number of piscivorous taxa

For this metric, only fish caught that are recognised asonly or exclusively feeding on other fish were analysed(Hemingway and Elliott, 2002). The method used to createthe RS and score for metric 4 was used.

2.1.10. Metric 10 – feeding guild composition

The premise of metric 7, that a healthy estuary shouldcontain certain functional guilds of fish, is presented herefor feeding guilds. For an estuary to be considered of goodquality in terms of fish species, a member of each guildshould be represented in each sample (Table 5).

2.2. Method-specific reference

An ideal reference community is derived from the samesite at the same time of year using the same methods, dur-ing a period when the environment is pristine and noanthropogenic changes have occurred. For many waterbodies, samples have only been taken after significantchanges in hydrology and morphology are present so no‘reference’ data is available for the actual site analysed.Such a situation exists for the Thames estuary. Londonwas the first city in the world to witness changes from a lessagrarian towards a more urban society during the indus-trial revolution. At this point 150 years ago, changes inwater quality, community structure and hydrology began,causing a change away from a ‘reference’ community(Wheeler, 1979).

Spatial and temporal variations in fish communities canlead to bias in both sampling and analysis and can result ina false representation of the ecosystem measured (Malavasiet al., 2004). Therefore the data was compared to a refer-ence community that was limited spatially, temporallyand by type.

The Thames TW is defined by UK typology (UK TAG,2004; Vincent et al., 2002) of ecotype E4T3 i.e. the water-body is within the North Sea (WFD Ecoregion 4) and isa fully mixed, polyhaline, macrotidal, sheltered estuarywith extensive intertidal areas (Type 3). All available datafrom all TWs of E4T3 was used as a reference againstwhich to compare the Thames data.

The abundance data for each of these TWs (Thames,Medway, Swale, Humber, Great Ouse and the Wash) wasdivided into three reaches or ‘bodies of surface water’(WFD Ref Article 2.9). These reaches represent an upper,

middle and lower section consistent with local samplingdivisions, salinity changes and the fish community changesfrom freshwater to marine species. The data was alsogrouped by spring and autumn, to take into account sea-sonal variation. The data for each separate sample method(seine net, beam and otter trawl) was aggregated by sam-pling gear for all E4T3 TWs to form a ‘method-specific’reference. Therefore nine separate reference communitieswere created to compare against each sampling occasion.The reference community used to compare the Thames(upper reach) spring 1993 seine netting raw results is sum-marised in Table 7. The reference data was ranked, thendivided into quintiles and the mean species richness forthe upper quintile calculated (Fig. 1). This mean was thenused as a ‘reference’ for calculating metrics 1 and 3. Tables8–17 list the reference figure used to create the RS. Theserelative scores were then averaged per year.

2.3. Metric scoring

Karr et al. (1986) assigned grades of 1, 3 or 5 to quantifythe metric scores to develop a scoring system of bioticintegrity. This approach has been adapted to a 1, 2, 3, 4or 5 system as the five bands corresponded more appropri-ately to the ecological status bands of the WFD (WFD CISWorking Group 2.4 (COAST), 2003; Vincent et al., 2002).

Once the metrics had been calculated for each method-specific reference for each reach, the sample-level data werecompared to its ecotype ‘reach-reference’. For example, theupper Thames seine net samples were compared against areference value of all E4T3 upper seine net samples. Eachmetric was scored according to its respective reference, withthe exception of metrics 2, 7 and 10, which were baseddirectly on the number of taxa present.

Once the metrics were calculated, the scores weretotalled for each sample and a ‘Relative Score’ (RS) wasgenerated using the following formula:

RS ¼ Total score of the 10 metrics

Maximum score possible

2.4. Sample methods

Historically, estuarine fish monitoring in the UK hasconcentrated on localised surveys within impacted, indus-trialised estuaries (CEFAS, 2004; Rogers and Millner,1996). Since 2002, the multi-method approach has beenconsidered a more effective way of assessing the ‘ecologicalstatus’ of a TW across the UK (Coates et al., 2004).

The use of fish communities in estuaries as indicators ofbiotic integrity has received much attention from manyauthors (Harrison and Whitfield, 2004; Karr, 1981; Karret al., 1986; USEPA, 2000). Using fish as environmentalindicators has many advantages including relative ease ofidentification and presence in most estuaries.

The Thames estuary is one of the few TWs in the UKthat has robust data sets using the multi-method approach

Table 6Thames (upper reach) spring 1993 seine netting raw results

Battersea Chelseacreek

Hammersmith Putney Battersea Brentford Chelseacreek

Chiswick Hammersmith Putney Richmond TeddingtonWeir

No. timescaught

Sum

Abramis brama 1 9 0 0 0 1 80 0 0 0 0 0 4 91Alburnus spp. 0 0 0 0 0 0 0 0 0 0 0 0 0 0Anguilla anguilla 0 1 1 0 1 1 0 0 3 6 1 0 7 14Atherina presbyter 0 0 0 1 0 0 1 0 0 0 0 0 2 2Barbatula barbatula 0 0 0 0 0 0 0 0 0 0 0 0 0 0Barbus barbus 0 0 0 0 0 0 0 0 0 0 0 0 0 0Chelon labrosus 0 0 0 0 0 0 0 0 0 0 0 0 0 0Clupea harengus 0 0 0 0 0 0 0 0 0 0 0 0 0 0Cottus gobio 0 0 0 0 0 0 0 0 0 0 0 0 0 0Cyprinus carpio 0 0 0 0 0 0 0 0 0 0 0 0 0 0Dicentrarchus labrax 0 0 0 0 0 0 0 0 0 0 0 0 0 0Esox lucius 0 0 0 0 0 0 0 0 0 0 0 0 0 0Gadus morhua 0 0 0 0 0 0 0 0 0 0 0 0 0 0Gasterosteus aculeatus 0 0 2 0 0 0 0 0 0 0 0 0 1 2Gobio gobio 0 0 0 0 0 1 0 0 0 0 0 0 1 1Leuciscus cephalus 0 0 0 0 0 0 0 0 0 0 0 0 0 0Leuciscus leuciscus 0 0 0 3 0 14 5 9 4 0 17 8 7 60Liza ramada 0 0 0 0 0 0 3 0 0 0 0 0 1 3Merlangius merlangus 0 0 0 0 0 0 0 0 0 0 0 0 0 0Osmerus eperlanus 0 0 0 0 0 0 0 0 0 0 0 0 0 0Perca fluviatilis 0 0 0 0 1 3 1 6 0 1 0 8 6 20Phoxinus phoxinus 0 0 0 0 0 0 0 0 0 0 0 0 0 0Platichthys flesus 1 4 1 2 12 0 1 4 51 72 0 1 10 149Pleuronectes platessa 0 0 0 0 0 0 0 0 0 0 0 0 0 0Pomatoschistus

microps

0 0 0 0 0 0 0 0 0 0 0 0 0 0

Pomatoschistus

minutus

0 0 0 0 0 0 0 0 0 0 0 0 0 0

Pungitius pungitius 0 0 0 0 0 0 0 0 0 0 0 0 0 0Rutilus rutilus 1 7 1 0 1 36 31 1 7 1 19 5 11 110Salmo salar 0 0 0 0 0 0 0 0 0 0 2 0 1 2Salmo trutta 0 0 0 0 0 0 0 0 0 1 0 0 1 1Scardinius

erythrophthalmus

0 0 0 0 0 0 0 0 0 0 0 0 0 0

Solea solea 0 0 0 0 0 0 0 0 0 0 0 0 0 0Sprattus sprattus 0 0 0 0 0 0 0 0 0 0 0 0 0 0Syngnathus rostellatus 0 0 0 0 0 0 0 0 0 0 0 0 0 0Tinca tinca 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Total abundance persurvey (N)

3 21 5 6 15 56 122 20 65 81 39 22 52 455

No. of species persurvey (S)

3 4 4 3 4 6 7 4 4 5 4 4 12 12

S.

Co

ates

eta

l./

Ma

rine

Po

llutio

nB

ulletin

55

(2

00

7)

22

5–

24

0229

Table 7E4T3 (upper reach) spring seine netting results

Functional guild Rare/threatened Feeding guild n % Relative richness Total abundance

Abramis brama FW BI 49 38.6 414Alburnus spp. FW Y Z 26 20.5 622Anguilla anguilla CA Y P 56 44.1 145Atherina presbyter MJ Z 29 22.8 217Barbatula barbatula FW BI 1 0.8 1Barbus barbus FW BI 1 0.8 7Chelon labrosus MS D 4 3.1 32Clupea harengus MJ Z 1 0.8 27Cottus gobio FW Y BI 4 3.1 4Cyprinus carpio FW BI 3 2.4 5Dicentrarchus labrax MJ P 46 36.2 904Esox lucius FW P 1 0.8 1Gadus morhua MJ P 0 0.0 0Gasterosteus aculeatus CA Z 40 31.5 111Gobio gobio FW D 13 10.2 67Leuciscus cephalus FW P 5 3.9 47Leuciscus leuciscus FW Z 100 78.7 3490Liza ramada CA D 10 7.9 34Merlangius merlangus MJ P 0 0.0 0Osmerus eperlanus CA Y Z 30 23.6 872Perca fluviatilis FW P 49 38.6 215Phoxinus phoxinus FW Z 6 4.7 7Platichthys flesus ER BI 102 80.3 2798Pleuronectes platessa MJ BI 0 0.0 0Pomatoschistus microps ER BI 41 32.3 972Pomatoschistus minutus ER BI 24 18.9 415Pungitius pungitius CA Z 3 2.4 3Rutilus rutilus FW Z 103 81.1 4579Salmo salar CA Y P 3 2.4 5Salmo trutta CA P 6 4.7 6Scardinius erythrophthalmus FW Z 1 0.8 1Solea solea MJ BI 0 0.0 0Sprattus sprattus MS Z 3 2.4 31Syngnathus rostellatus ER Z 0 0.0 0Tinca tinca FW BI 1 0.8 1

Mean 21.7 17.1 458.1Total 761 599.2 16033

(TWs = 3; years = 11; sampling occasions = 127; total species = 35).

Fig. 1. Example of species richness against rank, generated for each‘reference’ list. Lines denote divisions into five equal quintiles. The meanrichness of the upper quintile was used to generate a reference forcalculating metrics 1 and 3.


designed to assess both the pelagic and benthic communi-ties using seine nets, otter trawls and beam trawls at a vari-ety of locations throughout the estuary.

The Thames estuary also provides the largest long-termUK fish data set (Colcough, pers. com.), incorporating arange of sampling techniques and monitoring sites fromfreshwater to marine. Fig. 2 displays the sites sampled. Sitelocations were chosen mainly on their substrate regime andease of access. A stable shingle shore allows researchers togain purser underfoot when pulling in the seine net andprevents a build up of material in the net, which can causethe net to roll and loose fish. A firm and even riverbed alsoproves a better site for trawling, since less inorganic matteris disturbed. The sites allowed an extended sampling win-dow, ranging from almost freshwater upstream to almostmarine downstream.

This approach combines a variety of methods such asseine netting, beam trawling and otter trawling. Differentsurvey techniques have varying gear selectivities so it isimportant to incorporate a suite of techniques to obtaina comprehensive picture of each fish community assessede.g. benthic, pelagic and marginal.

Table 8Metric 1 – ‘Species Composition’



Chiswick Hammersmith Putney Richmond Teddingtonweir

Rutilus rutilus 1 1 1 0 1 1 1 1 1 1 1 1Leuciscus leuciscus 0 0 0 1 0 1 1 1 1 0 1 1Platichthys flesus 1 1 1 1 1 0 1 1 1 1 0 1Abramis brama 1 1 0 0 0 1 1 0 0 0 0 0Anguilla anguilla 0 1 1 0 1 1 0 0 1 1 1 0Perca fluviatilis 0 0 0 0 1 1 1 1 0 1 0 1Pomatoschistus

microps

0 0 0 0 0 0 0 0 0 0 0 0

Dicentrarchus

labrax

0 0 0 0 0 0 0 0 0 0 0 0

Total 3 4 3 2 4 5 5 4 4 4 3 4Reference 6.5 6.5 6.5 6.5 6.5 6.5 6.5 6.5 6.5 6.5 6.5 6.5% Similarity 54.55 66.67 54.55 40.00 66.67 76.92 76.92 66.67 66.67 66.67 54.55 66.67Relative score 3 4 3 3 4 4 4 4 4 4 3 4

Table 9Metric 2 – presence of ‘Indicator Species’

Battersea Chelsea creek Hammersmith Putney Battersea Brentford Chelsea creek Chiswick Hammersmith Putney Richmond Teddingtonweir

Osmerus

eperlanus

0 0 0 0 0 0 0 0 0 0 0 0

Salmo salar 0 0 0 0 0 0 0 0 0 0 1 0

Total 0 0 0 0 0 0 0 0 0 0 1 0Reference 2 2 2 2 2 2 2 2 2 2 2 2% Similarity 0 0 0 0 0 0 0 0 0 0 1 0Relative score 1 1 1 1 1 1 1 1 1 1 3 1

S.

Co

ates

eta

l./

Ma

rine

Po

llutio

nB

ulletin

55

(2

00

7)

22

5–

24

0231

Table 10Metric 3 – species relative ‘abundance’




Anguilla anguilla 0 4.761 20 0 6.666 1.785 0 0 4.615 7.407 2.564 0Dicentrarchus

labrax

0 0 0 0 0 0 0 0 0 0 0 0

Leuciscus leuciscus 0 0 0 50 0 25 4.098 45 6.153 0 43.58 36.36Osmerus eperlanus 0 0 0 0 0 0 0 0 0 0 0 0Platichthys flesus 33.33 19.04 20 33.33 80 0 0.819 20 78.46 88.88 0 4.545Pomatoschistus

microps

0 0 0 0 0 0 0 0 0 0 0 0

Pomatoschistus

minutus

0 0 0 0 0 0 0 0 0 0 0 0

Rutilus rutilus 33.33 33.33 20 0 6.666 64.28 25.40 5 10.76 1.234 48.71 22.72

Reference 100 100 100 100 100 100 100 100 100 100 100 100% Similarity 56.81 44.75 45.20 52.21 49.59 22.96 24.29 46.09 56.53 42.27 23.36 31.24Relative score 3 3 3 3 3 2 2 3 3 3 2 2

Table 11Metric 4 – number of taxa that make up 90% of abundance




1 33.33 42.86 40.00 50.00 80.00 64.29 65.57 45.00 78.46 88.89 48.72 36.362 33.33 33.33 20.00 33.33 6.67 25.00 25.41 30.00 10.77 7.41 43.59 36.363 33.33 19.05 20.00 16.67 6.67 5.36 4.10 20.00 6.15 1.23 5.13 22.734 4.76 20.00 0.00 6.67 1.79 2.46 5.00 4.62 1.23 2.56 4.555 1.79 0.826 1.79 0.827 0.82

No. taxa to make90%

3 3 3 2 2 2 2 3 2 1 2 3

Reference 5 5 5 5 5 5 5 5 5 5 5 5Relative score 4 4 4 3 3 3 3 4 3 2 3 4

232S

.C

oa

teset

al.

/M

arin

eP

ollu

tion

Bu

lletin5

5(

20

07

)2

25

–2

40

Table 12Metric 5 – number of estuarine resident taxa




Platichthys flesus 1 1 1 1 1 0 1 1 1 1 0 1Pomatoschistus

microps

0 0 0 0 0 0 0 0 0 0 0 0

Pomatoschistus

minutus

0 0 0 0 0 0 0 0 0 0 0 0

Syngnathus

rostellatus

0 0 0 0 0 0 0 0 0 0 0 0

Total 1 1 1 1 1 0 1 1 1 1 0 1Reference 4 4 4 4 4 4 4 4 4 4 4 4Relative score 2 2 2 2 2 1 2 2 2 2 1 2

Table 13Metric 6 – number of estuarine-dependent taxa




Abramis brama 1 1 0 0 0 1 1 0 0 0 0 0Alburnus spp. 0 0 0 0 0 0 0 0 0 0 0 0Barbatula barbatula 0 0 0 0 0 0 0 0 0 0 0 0Barbus barbus 0 0 0 0 0 0 0 0 0 0 0 0Cottus gobio 0 0 0 0 0 0 0 0 0 0 0 0Cyprinus carpio 0 0 0 0 0 0 0 0 0 0 0 0Esox lucius 0 0 0 0 0 0 0 0 0 0 0 0Gobio gobio 0 0 0 0 0 1 0 0 0 0 0 0Leuciscus cephalus 0 0 0 0 0 0 0 0 0 0 0 0Leuciscus leuciscus 0 0 0 1 0 1 1 1 1 0 1 1Perca fluviatilis 0 0 0 0 1 1 1 1 0 1 0 1Phoxinus phoniness 0 0 0 0 0 0 0 0 0 0 0 0Rutilus rutilus 1 1 1 0 1 1 1 1 1 1 1 1Scardinius

erythrophthalmus

0 0 0 0 0 0 0 0 0 0 0 0

Tinca tinker 0 0 0 0 0 0 0 0 0 0 0 0


S.

Co

ates

eta

l./

Ma

rine

Po

llutio

nB

ulletin

55

(2

00

7)

22

5–

24

0233

Table 14Metric 7 – functional guild composition

Battersea Chelsea creek Hammersmith Putney Battersea Brentford Chelsea creek Chiswick Hammersmith Putney Richmond Teddingtonweir

CA 0 1 1 0 1 1 1 0 1 1 1 0ER 1 1 1 1 1 0 1 1 1 1 0 1FW 1 1 1 1 1 1 1 1 1 1 1 1MJ 0 0 0 1 0 0 1 0 0 0 0 0MS 0 0 0 0 0 0 0 0 0 0 0 0

Total 2 3 3 3 3 2 4 2 3 3 2 2Reference 5 5 5 5 5 5 5 5 5 5 5 5

Relative score 2 3 3 3 3 2 4 2 3 3 2 2

Table 15Metric 8 – number of benthic invertebrate feeding taxa




Abramis brama 1 1 0 0 0 1 1 0 0 0 0 0Barbatula barbatula 0 0 0 0 0 0 0 0 0 0 0 0Barbus barbus 0 0 0 0 0 0 0 0 0 0 0 0Cottus gobio 0 0 0 0 0 0 0 0 0 0 0 0Cyprinus carpio 0 0 0 0 0 0 0 0 0 0 0 0Platichthys flesus 1 1 1 1 1 0 1 1 1 1 0 1Pleuronectes

platessa

0 0 0 0 0 0 0 0 0 0 0 0

Pomatoschistus

microps

0 0 0 0 0 0 0 0 0 0 0 0

Pomatoschistus

minutus

0 0 0 0 0 0 0 0 0 0 0 0

Solea solea 0 0 0 0 0 0 0 0 0 0 0 0Tinca tinker 0 0 0 0 0 0 0 0 0 0 0 0

Total 2 2 1 1 1 1 2 1 1 1 0 1Reference 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7

Relative score 3 3 2 2 2 2 3 2 2 2 0 2

234S

.C

oa

teset

al.

/M

arin

eP

ollu

tion

Bu

lletin5

5(

20

07

)2

25

–2

40

Table 16Metric 9 – number of piscivorous taxa




Anguilla anguilla 0 1 1 0 1 1 0 0 1 1 1 0Dicentrarchus

labrax

0 0 0 0 0 0 0 0 0 0 0 0

Esox lucius 0 0 0 0 0 0 0 0 0 0 0 0Gadus morhua 0 0 0 0 0 0 0 0 0 0 0 0Leuciscus cephalus 0 0 0 0 0 0 0 0 0 0 0 0Merlangius

merlangus

0 0 0 0 0 0 0 0 0 0 0 0

Perca fluviatilis 0 0 0 0 1 1 1 1 0 1 0 1Salmo salar 0 0 0 0 0 0 0 0 0 0 1 0Salmo trutta 0 0 0 0 0 0 0 0 0 1 0 0


Table 17Metric 10 – feeding guild composition




Benthicinvertebrate

1 1 1 1 1 1 1 1 1 1 0 1

Detritus 0 0 0 0 0 1 1 0 0 0 0 0Piscavores 0 1 1 0 1 1 1 1 1 1 1 1Zooplankton 1 1 1 1 1 1 1 1 1 1 1 1


S.

Co

ates

eta

l./

Ma

rine

Po

llutio

nB

ulletin

55

(2

00

7)

22

5–

24

0235


In the upper to mid estuary a 45 · 3.5 m seine net with a5 mm knotless mesh centre and 20 mm wings was deployedfrom the shore with a 17 ft open dory. The net wasdeployed during the low water slack period twice. Thismethod was designed to capture small to large adult activefish within the margins of the river. A 1.52 m (5 0) widebeam trawl with a 20 mm knotless outer mesh and 5 mmknotless cod end, designed to capture demersal species,was trawled for 250 m parallel to the seining site. In themid and lower estuary seine netting & beam trawling wascomplimented by paired 8 m wide otter trawls with a40 mm outer mesh with a 5 mm knotless ‘cod end’ mesh.It was deployed usually during low water slack or on aflooding tide and was used to assess the pelagic & benthicfish community present within the main channel of theThames estuary.

3. Results

Table 6 shows the raw results for Thames (upper reach)spring 1993. Table 7 includes the data for all years forspring seine netting, that was used to create ‘reference’ con-ditions for Table 6 values. Reference conditions were cre-ated in the same way for spring and autumn for seine,beam and otter trawling for the upper, middle and lowerreaches. Tables 8–17 display the metric scores for Thames

Fig. 2. Thames estuary indicating division into separate upper, mid and low

(upper reach) spring 1993 results. The total count, the ref-erence total, % similarity to reference (where appropriate)and the RS is displayed for each metric.

The annual RSs for the upper, mid and lower Thamescompared to the ecotype reference values between 1992and 2004 are shown in Figs. 3–5. It is evident that the rel-ative scores are higher in the lower TW than those in themid TW and those in the mid TW are higher than thosein the upper TW.

Analysing variations between methods, the seine nethas a higher RS compared to the beam trawl in every yearin the upper Thames. The difference between the twomethods is lowest in 1992 and highest in 2000. Similarly,within the mid Thames, the seine net and otter trawl havea higher RS compared to the beam trawl in all years.Otter trawling was introduced in 1997 as part of theCEFAS & EA bass (Dicentrarchus labrax) population sur-vey work. Between 1997 and 2000, the seine net had aslightly higher RS than the otter trawl samples whilst in2002 and 2003, the otter trawl had a higher RS which var-ied between 0.1 and 0.4. Within the lower Thames, thereis a similar pattern evident to that in the mid Thames,where the seine net samples have a higher RS comparedto the beam and otter trawl in most years during the1990s. Again between 2000 and 2003, the otter trawl sam-ples have the highest RS.

er reaches for statistical analysis. Points indicate all sampling locations.

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

92 93 94 95 96 97 98 99 00 01 02 03 04

Year

RS

BeamSeineB & S Mean

Fig. 3. Mean annual relative scores for beam trawl and seine net samples in the upper Thames. Samples were compared against a method-specificreference based on TWs in E4T3. Bars indicate minimum and maximum relative scores per annum.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

92 93 94 95 96 97 98 99 00 01 02 03 04

Year

Mea

n R

S

Beam

Seine

Otter

Mean (B, S & O)

Fig. 4. Mean annual relative scores for beam trawl, seine net and otter trawl samples in the mid Thames. Samples were compared against a method-specific reference based on TWs in E4T3. Bars indicate minimum and maximum relative scores per annum.


Comparing within-method variation along the TW, thebeam trawl samples had a higher RS in most years in thelower Thames than further upstream. In the lower TW,the beam trawl samples also had the greatest range of RS(0.1–0.6). The overall RSs of the seine net samplesincreased slightly between the upper to lower reaches.There was little difference between the RSs of the ottertrawl samples in the mid and lower Thames.

Initial assessment of dissolved oxygen and the relativescores within the upper reaches of the Thames suggest thatthere may be some correlation between the RS and DOconcentration, for example when DO levels are reduced,RSs are also low. This exploratory work will be investi-gated further as part of developing physicochemical stan-dards for WFD in support of the ‘biological qualityelements’ for transitional and coastal waters.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

92 93 94 95 96 97 98 99 00 01 02 03 04

Year

Mea

n R

S

Beam

Seine

Otter

Mean (B, S & O)

Fig. 5. Mean annual relative scores for beam trawl, seine net and otter trawl samples in the lower Thames. Samples were compared against a method-specific reference based on TWs in E4T3. Bars indicate minimum and maximum relative scores per annum.


4. Discussion

Prior analysis indicated that the assessment methodol-ogy used provided a statistically robust way of analysingthe long-term fish data of the Thames (Coates, unpublisheddata). An alternative was to compare each data set againsta ‘multi-method’ reference incorporating all survey tech-niques (Coates et al., 2004). This was initially trialed butbecause it was not possible to have standard ‘sampling-effort’ for each monitoring technique within reference, theresulting assessment of the single-strand data against thereference was not statistically comparable.

The progressive downstream increase in RS and possibleincrease in ecological status could indicate a generalincrease in the health of the ecosystem and therefore inthe diversity and abundance of the fish communities. Thischange is likely to reflect a shift from the urbanised, mor-phologically modified channel of London to that of thelower Thames estuary, which has a more diverse fish com-munity (Astley, 2004; Kirk et al., 2002). Upper reaches ofthe Thames have a greater freshwater influence and sup-port less species diversity than lower reaches (Colcloughet al., 1992, 1993, 2000).

The mid reach of the Thames is highly channelised andprovides few habitats for juvenile and adult fish (Astley,2004; Attrill, 1998). There are also high fluctuations insalinity and so fewer species are able to tolerate thedynamic macro-tidal environment (Colclough et al., 1992,1993, 2000). Channel morphology and habitat nicherequirements are known to influence fish communities(Hemingway and Elliott, 2002). Lower reaches are morestable in terms of salinity and anthropogenic and there isa greater diversity of habitat (Astley, 2004) thereby provid-

ing suitable refuges/food sources to support more diversecommunities (Hemingway and Elliott, 2002).

The variation between the results of the methods in allreaches of the TW is unlikely to be due to variation in sam-pling effort as each method is based upon consistent sam-pling effort and gear selectivity (Coates et al., 2004). Thebeam trawl is likely to produce samples with lower relativescores than the seine net and otter trawl because it targetsbenthic fish communities. It is a much more discriminativetechnique than the other methods and therefore captureslower species diversity than seine and otter trawling (Colc-lough et al., 2000). Seine netting is carried out from theshore and is used for marginal habitat sampling of pelagicspecies and those fish communities utilising this habitat.The otter trawl is towed through the water column andsamples a wide range of benthic and pelagic species, whichwould account for the higher RSs during 2000–2004.

5. Conclusions

Although the patterns evident from the analysis fit withwhat would be biologically expected to happen within theThames TW, the multi-metric tool and assessment outlinedin this paper requires further development as part of WFDimplementation in December 2006.

WFD guidance from Ecostat states that current refer-ence conditions are not valid as they have been derivedfrom TWs that are not at ‘Reference’ or High Status (Euro-pean Council Directive, Section 1.3 (iv), 2000). As the ref-erence sites selected for TW3 within Ecoregion 4 are not‘existing undisturbed sites with only very minor distur-bances’ (WFD CIS Working Group 2.4 (COAST), 2003),the data comparison needs to be revised because it is based


on abundance data from TWs already impacted by certainpressures.

Reference ideally needs to be based on the fish commu-nities found in historically unimpacted sites (Coates,unpublished data). If the abundance data per sample fromthe current analysis were compared to such a pristine refer-ence, the resulting RSs would be particularly low, reflectingpoor conditions compared to an unimpacted situation.Although the method used is statistically robust at the sam-ple level, the inherent temporal and spatial variabilitywould be too high to provide any meaningful results. Fishpopulations do not aggregate spatially within TWs and arehighly variable throughout the year. These biological char-acteristics, coupled with the fact that sampling has not beenhistorically consistent in effort or locality, mean that thedata cannot be analysed at the sample level. Further anal-ysis will therefore involve pooling the data on an annualsurvey basis from all reaches and methods and then com-paring to reference. Two to three years of combined annualsample data may also be used to assess ecological status inthis way.

Although the level of analysis can be revised, there areno ‘reference’ TWs in E4T3 with long-term data setsagainst which the Thames data can be compared. Expertjudgement will therefore need to be used in conjunctionwith existing data to generate a suitable reference for eachof the candidate metrics (European Council Directive,2000).

The assessment of the fish community also has to beconsidered in relation to the assessment of the hydromor-phology of the Thames estuary. The Thames is likely tobe classified as a Heavily Modified Water Body (HMWB)under the WFD and has to meet the requirements of ‘goodecological potential’ (European Council Directive, 2000).The RSs will therefore have to be considered in relationto ‘ecological potential’, rather than in relation to ‘ecolog-ical status’. The criteria for ecological potential require awater body to not deteriorate and will most probably willbe compared to the same reference conditions as those thatare not heavily modified, but the boundary criteria may bedifferent. Confirmation of the ecological potential criteriahave yet to be confirmed by the UK.

Although further development, testing and validation ofthe TFCI is necessary, the current analysis has howeverprovided a valuable insight into comparing differing mon-itoring techniques. The results indicate the varied selectivi-ties of the methods and the benefits of the use of a range ofthese techniques, in order to provide a complete picture offunctionality within transitional waters. Although still at apreliminary stage, these results highlight the importance ofa multi-method sampling regime.

The current analysis of the Thames also highlights thebenefit of dividing large TWs into specific reaches andanalysing each independently. Each section is exposed todifferent anthropogenic pressures and different hydromor-phological regimes such as variations in salinity andhabitats. Fish composition and abundance is highly likely

to vary within each reach and as such, should be analysedseparately.

The TFCI developed here incorporates both structuraland functional attributes of estuarine fish communities. Ithas been tested here to provide both a robust method forassessing the ecological status of transitional waters. Fur-thermore the TFCI could be refined and related to a rangeof environmental pressures such water quality, shorelinereinforcement and flow manipulation once reference condi-tions have been established. Overall, the TFCI is an effec-tive communication tool for converting ecologicalinformation into an easily understood format for environ-mental managers, policy makers and local communitiesand stakeholders.

Acknowledgements

We would like to thank Peter Lloyd, Maxine Clementand Lars Akesson of Environment Agency, Thames Re-gion for their advice and support with the AQMS data.We would also like to thank all our transitional fish col-leagues and associates throughout the UK, Ireland andEurope for their support and guidance in developing theseclassification tools as part of WFD implementation.

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