An index of biotic integrity to assess biological impacts of salmonid farm effluents on receiving waters

Aquaculture, 119 (1994) 219-235 Elsevier Science B.V., Amsterdam

219

AQUA 30098

An index of biotic integrity to assess biological impacts of salmonid farm effluents on receiving waters Thierry OberdorWb and Jean Pierre Percher” ‘Sepia International, Departement Environnement, Saint Quentin, Yvelines, France bLaboratoire d’lchtyologie g&a&aleet appliqut!e,M&urn National d’Histoire Naturelle, Paris, France “Conseil SupMew de la P&he, DtGgation Regionale no2, Bretagne-Basse Normandie, Cesson-St%ignt!,France (Accepted

15 September

1993 )

ABSTRACT A major issue for water resource management is the assessment of environmental degradation of lotic ecosystems. In order to quantify the extent of resource degradation resulting from anthropogenic disturbances, a fish-based index, the Index of Biotic Integrity (IBI), has been used throughout North America and recently in Europe. The IBI is based on the assumption that fish assemblage attributes change in a characteristic fashion with stream degradation. In this study, using data from 1979 to 1991, we analysed the impact of 9 salmonid farm effluents on fish assemblages in some Brittany streams. Annual production of these farms varied between 2 and 300 tons. The data were first computed using a principal components analysis. Ordination of the points indicated longitudinal changes in fish assemblages from upstream to downstream and separated sites sampled upstream from sites sampled downstream from the fish farms. Depending on stream size, we found, downstream from trout farms, an increase in both density and biomass of most species, extirpation of sensitive ones (Cot&s gobio L. ), and appearance of pollution-tolerant (Rutilus rutilus L. ) and exotic forms ( Oncorhynchus mykiss W.). Finally, we modified the IBI and compared it with chemical variables to illustrate how this index can be applied to quantify disturbances of the quality of stream water induced by fish farms. This IBI, baaed on 10 fish assemblage attributes, showed close agreement with these independent chemical measurements.

INTRODUCTION

The intensive culture of freshwater fish, reprqsented mostly by rainbow trout (Oncurhynchus m#ks), is an expanding enterprise in France. In 199 1, approximately 40 000 tons of salmonids were produced, and this will probably increase in the near future. According to Liao ( 1970), FaurC (1977), BergCorrespondence to: Dr. T. Oberdorff, Sepia International, Departement enue Gustave Eiffel, 78 182 Saint Quentin, Yvelines Cedex, France.

00448486/94/$07.00

Environnement,

0 1994 Elsevier Science B.V. All rights reserved.

SSDZ0044-8486(93)E0231-W

14 Av-

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T. OBERDORFF AND J.P. PORCHER

heim and Selmer-Olsen ( 1978), and Kendra ( 199 1) waste products from freshwater fish farming include residual food, fecal material, soluble metabolites (e.g., ammonia), drugs and other chemicals, pathogenic bacteria and parasites. Nevertheless, the biological pollution impact induced by intensive fish farming on the receiving water body is often difficult to assess because of the high rate of waste dilution. Relatively little has been done to evaluate the ecological impact of fish farm wastes on the biota of streams or rivers, except by Szluha ( 1974) who analysed periphyton production in a North American river downstream from a fish hatchery, and by Kendra ( 199 1) who assessed the quality of salmonid hatchery efktents using invertebrate assemblages. Both of these authors found substantial changes upstream and downstream from these effluents. Another tool, based on fish assemblages, for assessing the impact of fish farm effhtents on receiving water is the Index of Biotic Integrity (IBI ). The IBI is based on the assumption that fish assemblage attributes change in a characteristic fashion with stream or river degradation. Originally proposed by Karr ( 198 1) and later refined by Fausch et al. ( 1984) and Karr et al. ( 1986), the IBI is composed of a number of fish assemblage metrics ( 10 in this study) classified into 3 groups: ( 1) species richness and composition, (2) trophic composition, (3) fish abundance and condition. Each metric is scored according to the value expected in an undisturbed or less disturbed stream of similar size in the same geographic region. A rating of 5, 3 or 1 is then assigned to each metric, according to whether its value approximates ( 5 ), deviates moderately from (3), or strongly deviates from ( 1), the value expected at reference sites. The IBI is the sum of the 10 ratings and varies from 10 to 50 in 5 quality classes: excellent (48-50); good (38-42); fair (3034); poor ( 18-24); and very poor (less than 14). A classification of “no fish” is assigned when repeated sampling finds no fish. Developed for streams in the midwestern USA, the IBI has been tested in several other regions of North America (Leonard and Orth, 1986; Fausch and Schrader, 1987; Hughes and Gammon, 1987; Steedman, 1988; Crumby et al., 1990) and recently in Europe (Oberdorff and Hughes, 1992 ). These applications have confirmed that the IBI approach is useful, but that metrics must be modified with respect to regional differences in fish assemblage structure. This study was designed to document useful modifications in the IBI for application to Brittany streams and to test the IBI to quantify relationships between fish assemblage structure and fish farm e&tents. IBI scores also were compared against independent chemical measurements performed upstream and downstream from two commercial salmonid farms localized in the same stream.

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MATERIALS AND METHODS

Study area Brittany streams are characterized by low gradients (usually under 100160 ), short lengths, low thermal annual variations ( 6-20 ‘C ) , and moderate acidity (pH 6-7 ) . The area is underlain mostly by granites, schists, and sandstone, and has not been greatly affected by human activities in recent history. Land use is mostly agricultural with some grazing of livestock. Human population density is low ( < 100 inh./km2) and water quality of streams was, until recently, considered good (Bagliniere, 1979; Maisse and Baglinibre, 199 1) despite an increase in inorganic nutrient salt (especially nitrates) concentrations in the water due to an increase in agricultural and grazing practices. In this study, we examined 9 trout farms of different annual production in 6 Brittany streams (Fig. 1). Fish assemblages were sampled upstream and downstream from the location of each farm (Table 1) . Sampling procedure We used data from 1979 to 199 1 for the analyses. Fish sampling was performed for the 18 sites during low flow periods (September to October). This

Fig. 1. Map of the area studied showing the approximate location of the salmonid farms.

T. OBERDORFF AND J.P. PORCHER

222 TABLE 1

Location and sampling dates of the 9 salmonid farms retained for this study, with their annual production, their catchment area, and the codes used for factor analysis Streams

Salmonid farm codes

Annual production (tons)

Catchment area (l&

Pont 1’AbbC (1979) Porn 1’Abbt (1919) Aulne (1991) Aulne (1991) Auhte (1991) Jet (1983) Elom (1984) Scorff ( 1980) Jaudy(1991)

PAI PA2 AU1 AU2 AU3 JEl EL1 SC1 JAl

40 120 40 200 300 25 120 150 2

23 29 21 220 330 38 29 33 23

is not the season of maximum fish farm production but represents the period of least dilution. Each site was electrofished by wading in a downstream-upstream direction. The equipment comprised a control box delivering a pulsed direct current (200-500 V ) via hand-held anodes ( l-3 depending on stream width) and a braided wire cathode. Power was supplied by a portable generator. Fish were identified by species, measured to the nearest millimeter (fork length), weighed, and then released. The De Lury catch-effort method (De Lury, 1947) was employed to estimate total fish assemblage in each sample. This method estimates fish assemblage from repeated sampling using identical fishing efforts (both fishing time and number of anodes kept constant). Lengths of sites surrounding fish farms were chosen > 100 m to encompass the home ranges of the dominant fish species. Wateranalyses For two salmonid farms (located on the Pont l’AbbC River) among the nine studied, samples of water upstream as well as downstream from the production units were taken once during 1979, a few days after the fish sampling. Ten variables were measured: temperature, turbidity, conductivity, pH, oxygen concentration, 5-day biological oxygen demand, NO?, NO?, NH:, and PO:-. Statisticalanalyses Fish density (number of individuals/ 100 m2) and fish biomass (g/ 100 m2) were calculated for each site (see Appendix 1) . To homogenize variances and

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minimize effects of non-normality we used a In (x+ 1) transformation. The final transformed data matrix of species biomass (columns) by sites (rows) was then computed using a principal components analysis. This analysis generates a series of synthetic variables that are weighted linearly by the original variables. Weighting coefficients of the original variables onto the the principal components indicate the relative importance of each variable to each component (synthetic variable). Only the most abundant species were retained for this analysis. This procedure allows co-ordinate comparisons for each station. RESULTS

Modifying the IBI for Brittany streams A total of 11 species were captured during these surveys (Table 2). Several metrics originally used for the IBI (Karr et al., 1986) needed to be modified for application to Brittany streams. Nevertheless, the main components (i.e. species richness and composition, trophic composition, and fish abundance and condition) were retained. Another important component influencing assemblage structure was added: fish biomass. Metrics used during this study included the following: Species richness and composition metric included: total number of native species, number of benthic species, percent of individuals as sculpin, percent of individuals as eel, and brown trout year classes. The number of native species is a measure of the species-richness component of diversity, and usually decreases with increased degradation. Benthic species, for the most part, are sensitive to siltation and benthic oxygen depletion as they feed and reproduce in benthic habitats. The sculpin ( C. gobio L. ) is a particularly intolerant species sensitive to chemical and physical degradation (Verneaux, 198 1). Eel (Anguilla anguilla L. ) is common to all Brittany streams and appears tolerant of many pollutants. Brown trout (Salmo trutta L. ) could be considered as a local indicator species and is sensitive to physical and chemical stream alterations. Trophic composition metric included: percent of individuals as omnivores, and percent of individuals as invertivores. The omnivore metric is designed to measure increasing levels of environmental degradation due to a disruption of the food base. Although invertivores are the dominant trophic guild in Brittany streams, their relative abundance decreases with degradation, in response to variability in food supply due to alteration of the energy base. Fish condition and abundance metric included: percent of individuals with anomalies, catch per 100 m2 of sampling (i.e. fish density), and total biomass. Although no disease data were available for this study, we retained the metric for future investigation because it reflects highly degraded areas

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TABLE 2 Trophic guilds for common freshwater cyclostomes and fishes found during this study, including invertivore (I), piscivore (P), omnivore (0)) filter feeder (FF), benthic species (B ) Family species

Trophic guild

Benthic species

Species code

Petromyzontidae Lampetra planeri

FF

B

LAP

Anguillidae Anguilla anguilla’

I/P

B

ANA

Salmonidae Salmo truttafario Salmo salar* Oncorhynchus mykissw

I/P I/P I/P

SAT SAS ONM

0 0

PHP LEL ABB RUR

Cyprinidae Phoxinus phoxinus Leuciscus leuciscus Abramis brama Rutilus rut&

0 0

Nemacheilinae Barbatula barbatula

I

B

BBB

Cottidae Cottusgobio

I

B

COG

‘Anadromous or catadromous #Exotic species.

species.

(Steedman, 1991). As noticed by Steedman ( 1988) working in the Toronto metropolitan area and by Oberdorffand Hughes ( 1992 ) working on the Seine Basin, very high fish density and biomass were associated with artificially enriched waters and low fish density and biomass more often with strongly degraded systems. Species assignments to trophic guilds were made according to Oberdorff and Hughes ( 1992) and Oberdorff and Percher ( 1992 ) (Table 2). Scoring IBI metrics Criteria for scoring the index of biotic integrity are summarized in Table 3. All metrics were scored relative to regional standards analysed in previous studies (unpublished data and Oberdofl and Percher, 1992) and according to the methods outlined in Karr et al. ( 1986). One measure of species composition (total number of native species) was scored from a maximum spe-

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TABLE 3 Criteria for scoring index of biotic integrity metrics adapted for this study Category

Metric

Scoring criteria 5

Species richness and composition

1. Total number of species (% MSRL) 2. Number of benthic species’ 3. % of individuals as sculpin (intolerant species) 4.96 of individuals as eel and roach (tolerant species) 5. Brown trout year classes

>61

Trophic composition

6. % of individuals as omnivoresb 7. % of individuals as invertivores’


Fish condition and abundance

8. % of individuals with anomaliesd 9. Catch per 100 m* of sampling (% MDL)= 10. Total biomass (g/100 m*)

A metric scored 1 represents the lowest quality, 3 is intermediate, “Excludes Anguilla anguilla (L. ) . bExcludes Phoxinus phoxinus ( L. ) . CExcludes Anguitla anguifla ( L. ) . dDisease, tumors, fin damage, parasites. % of Maximum Density Line.

1

3 33-67

t33

>l >5

1 l-5


<15

1S-30

>30

all

33-67 1000-3000

two l-5 30-70

~67 > 3000

0

one 15 t30

<33 < 1000

5 is highest quality.

ties-richness line (MSRL) (Fausch et al., 1984), which indicates potential species richness as a function of catchment area (Fig. 2a). Details on this method are given in Fausch et al. ( 1984) and Oberdorff and Hughes ( 1992). The same approach was used to assess fish density (number of individuals/ 100 m’). Fish density for Brittany streams tends to decrease as catchment area (stream size) increases (Oberdorff and Percher, 1992). This trend also has been noted for other systems (Larimore and Smith, 1963; Miller et al., 1988). For this metric, a maximum density line (MDL) was designed as a “fair” fish assemblage, because we noticed that high fish density was associated with relatively degradated sites (Fig. 2b). The scoring for all the other metrics was done using as a standard the least disturbed regional sites for the years 1978 to 1982 (Oberdorff and Percher, 1992). As no data were available for the metric, percent of individuals with anomalies, a rating of 3 was arbitrarily assigned to this metric. Upstream and downstream comparisons The first three axes of the principal components analysis accounted for 92%

226

T. OBERDORFFAND

J.P. PORCHER

(a) . /

0

‘I’/‘I’/‘I’I~

0

6

1

Ln

of

catchment

area

03

0

1

2

Ln

3

of

.I

catchment

5

6

7

area

Fig. 2. Maximum species-richness line (MSRL) (a) and maximum density line (MDL) (b), used in determining IBI scores. Lines were drawn relative to regional standards analysed previously by Oberdorff (unpublished data are Oberdofland Percher ( 1992 ).

of the variance (Fig. 3a, b). Axis 1 (50.8% of the variance) separated species with high biomass (Anguilla anguilla L. ) from all the others. Axis 2 (27.6% of the variance) described longitudinal changes in fish assemblage structure as shown by the high relationship between coordinates of this axis and catchment area (r=0.828; P-zO.001) (Fig. 4). Axis 3 (13.6% of the variance) separated sites sampled upstream from sites sampled downstream of fish farm effluents. Considering species, eel (A. anguilla L. ), brown trout (S. truttaL. ) and loach (Burbutuh burbatula L. ) biomass increased greatly downstream from fish farms contrary to s&pin ( C. gobio L. ) and, to a lesser extent, minnow (Phoxinus phuxinus L. ) biomass which decreased significantly. For 4 sites over the 9 sampled downstream of ef’Iluents, the species raised in the farms (0. mykiss) was present in the indigenous fish assemblage. Nevertheless, the density of this species was always low ( < 1 ind./lOO m2).

227

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Fig. 3. Ordinations for species and sites of the Principal Components Analysis for a sites-by-species matrix ( 18 x 5 ) of fishes (in biomass) sampled upstream and downstream from 9 salmonid farms. (a) Axis 1/Axis 2; (b) Axis Z/Axis 3. *Sites sampled downstream from salmonid farms (see Table 1 and Table 2 for station and species codes).

l

496-

0

r=0.828 VJ -

-2,0- . 0 -4,0 3

0 I 4

In (catchment

I 5

6

area)

Fig. 4. Relationships between ln(catchment area) and the second axis of the Principal Components Analysis (r=0.828; P
On 3 other sites we found substantial changes in fish assemblage structure with appearance of species like roach, common bream and date. These species are usually typical of midsized to large rivers and do not represent species expected in such headwater streams (see Appendix 1) . IBI scores for all sites were lower downstream than upstream of fish farm e!Tluents (Fig. 5 ). Variation in IBI scores was correlated with the annual production of these farms and their position along the longitudinal gradient of streams. A multiple regression analysis indicated that both catchment area (CA) and annual fish farm production (PROD) contributed significantly to

T. OBERDORFFAND

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J.P. PORCHER

Stations Fig. 5. IBI total scores for stations upstream and downstream station codes ) .

from 9 salmonid farms (see Table 1 for

the variation of net IBI total score (nIBI = IBI score upstream from farms - IBI score downstream from farms). The multiple regression equation was: nIBI=3.162-0.047CA+O.O75PROD,

with r2=0.626, and

P-values for CA and PROD of 0.045 and 0.022 respectively. This analysis demonstrated that the impact of fish farm emuents on fish assemblages was positively correlated with the production of these farms but negatively correlated with an increase in catchment area. Efsects ofPont lilbbt Riverfish farms Water quality downstream from two salmonid farm effluents, located in the Pont 1’Abbk River, was degraded relative to upstream areas (Fig. 6 ) . For both sites downstream from effluents, substantial increases, compared to upstream sites, were found for turbidity, biological oxygen demand (5-day), ammonia, nitrites, and phosphorus (PO:-), when dissolved oxygen decreased significantly. Receiving water loads at the second salmonid farm were largely derived from the upstream discharge of the first salmonid farm; hence cumulative salmonid farm nutrient loading to the stream was substantial (Fig. 6). It also can be noted that downstream from these two farms, the nitrogen cycle appeared to be seriously perturbed. The analyses carried out showed that there was a high incidence of ammonium and nitrite pollution downstream from fish farms. In a concentrated form, these substances are toxic for

SAJMON

FARMEFFLUENTS

229

200 83

C

5

conductivity

(p siemens)

loo-

o-l,. ,

6Y

I.

I.

I

I.

7

8

9

IO

Distance

from

A

1 11

a

source

(km)

Fig. 6. Variation of physicochemical and IBI values for 4 sites sampled in the Pont l’Abbt River. Black arrows indicate location of the two salmonid farms.

T. OBERDORFF AND J.P. PORCHER

230

ta)

n q

12

3

4

5

6

7

upstream of the firs: farm lBL46 downstream of the first farm lBL36

7

8

9 10 181 metrics

n

upstream of the second farm lBl=30

q

downstream of the second tarm lBl=22

5

2

4

8 *

3

0 ._ L $

2

1

0

12

3

4

5

6

7

8

9

10 IBI metrics

Fig. 7. Metric behavior for 4 stations of the Pont l’Abb6 River located upstream and downstream from two salmonid farms, showing the cumulative impact of farm effluents on fish assemblages (see Table 3 for metrics). (a) Upstream and downstream from the first salmonid farm; (b) upstream and downstream from the second salmonid farm.

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231

fish. Nitrate, which was present at concentration of 17 mg/l upstream from the first farm, disappeared completly downstream from the second farm. This phenomenon could be caused by a lack of oxygen in the water, inducing use of the oxygen contained in nitrates by micro-organisms. This process is apparent in pilot sewage plants when oxygen levels fail to about 1 mg/l and could suggest that local oxygen concentration downstream from the second farm was much lower than the one found, especially near the bottom. We assessed IBI total scores for stations upstream and downstream from these two salmonid farms. IBI total scores were much lower downstream than upstream from the effluent inflow. The highest IBI value occurred upstream from the first salmonid farm with an index value classified as “good”; the lowest IBI value occurred downstream from the second salmonid farm with an index value classified as “poor”. Between these two points, IBI values decreased in a downstream direction, suggesting, as for chemical data, a cumulative impact of the two salmonid farms on the receiving water body (Fig. 6). Analyses of the fish assemblage metrics (Fig. 7a,b) for stations sampled upstream and downstream from the two salmonid farms indicate how IBI metrics responded to water body conditions. Downstream from the first farm, only two species richness and composition metrics (percent of individuals as sculpin and percent of individuals as eel), one trophic composition metric (percent of individuals as invertivores), and one fish condition and abundance metric (total biomass) reflected river perturbation. Immediately downstream from the second fish farm, all values for species richness and composition (only two species were present out of five expected), trophic composition (except for percent of individuals as omnivores), fish abundance, and fish biomass were consistent with river degradation. DISCUSSION

Uneaten food and fish excreta are the main sources of pollution from fish farms. These two parameters act indirectly on the quality of the water body by increasing loads of suspended solids, ammonia, organic nitrogen, total phosphorus, and biological oxygen demand relative to influent waters. Suspended solids are derived from waste food and fish feces. Ammonia is an excretory product of fish metabolism. Organic nitrogen and phosphorus are feed components. Increases in chemical or biological oxygen demand are probably linked to increases in organic suspended solids (Kendra, 199 1) . From the results presented in this study, we can conclude that fish farming can cause both structural and functional changes in wiId fish assemblages. An increase in total abundance and biomass together with changes in species composition towards a greater number of tolerant species was found in the immediate vicinity of the farms. Three main factors could explain these changes in fish assemblage structure downstream from fish farm effluents.

232

T. OBERDORFF

AND J.P. PORCHER

They were respectively: organic enrichment, inorganic enrichment (eutrophication), and siltation. The increased concentration of organic matter downstream from farm effluents resulted in an increase in the respiratory demand of the microbial population (for the oxidation of the waste) and led to a depletion of the dissolved oxygen in the water. This deoxygenation eliminated the more sensitive species (C. g&o, P. phoxinw) and the effect was a reduction in species richness, with an increase in the population of fish able to tolerate this condition (A. anguillu). This was particularly true for the site downstream from the second farm located on the Pont l’AbbC River. This study was focused on headwater streams characterized by oligotrophic waters where autochthonous production acts as a minor component. These streams are particularly sensitive to allochthonous nutrient enrichment (fish farm wastes) which could induce a shift in the energy base towards autotrophic processes typical of mid-river habitats (Vannote et al., 1980). Symptomatic of this condition in the streams studied was the luxurient growth of filamentous algae downstream from fish farms. The result of this nutrient enrichment and consequent eutrophication of the receiving water is that potential food availability increases for the fish assemblage. Therefore, fish species usually typical of lentic and thus more productive waters can colonize this new artificial habitat. This could explain the occurrence, downstream from some salmonid farm effluents, of species like roach, date, and common bream noticed during this study. The primary influence of increased sedimentation on stream fish is believed to be the disruption of normal reproduction through degradation of spawning ground, and increases in egg and larval fish mortality) (Shirazi et al., 1979; Ran and Dudley, 198 1). The results of this study showed that downstream from salmonid farm effluents, as siltation increased (i.e. suspended solids), the relative abundance and biomass of habitat specialists decreased. This was particularly evident concerning sculpin ( C. gobio L. ) which almost completely disappeared downstream from farm outfalls. The results were not as obvious concerning brown trout (S. truttaL. ) , but we noticed the absence of first age classes downstream from some farm effluents, suggesting that this species was somehow affected by alterations in spawning conditions (Loir-Mongazon, 1980). On the other hand, habitat generalists like eel (A. arzgdlu L. ) and loach (B. barbatuluL. ) were not affected downstream from fish farm efIIuents and their density and biomass increased mainly because of an increase in food availability. In conclusion, the results of this study indicate that salmonid fish farm effluents cause substantial changes in fish assemblages, and that the modified IBI is capable of determining the extent of these effects. As previously shown by Oberdorff and Hughes ( 1992), using such an approach, the biological

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quality of French streams or rivers could be evaluated in a simple and effective way. We believe that sedimentation, organic enrichment and eutrophication may be primarily responsible for the decline in fish assemblage integrity downstream from fish farm effluents. These combined effects of change in trophic status (due to eutrophication), oxygen depletion and siltation all affect the fish assemblages usually present. In areas of naturally low productivity, reduction in suspended solids and nutrient salt loading by sahnonid farms could induce considerable biological recovery of the receiving waters. Improvement could be achieved through improvement of food digestibility by using highquality feed, reduction of feed loss, and reduction of fish loading during critical low-flow period. Implantation of the farms preferentially downstream, where organic and inorganic enrichment act as minor components on fish assemblage structure, could also minimize the impact on the receiving water body.

ACKNOWLEDGEMENTS

This work was supported by Sepia International and the Association Nationale de la Recherche Technique (CIFRE) which provided a fellowship to T.O. This paper is a contribution to the “Agriculture demain” program, supported by the Minis&e de la Recherche et de la Technologie. We are grateful to the Conseil Suptrieur de la P&he for making available data on fish. We thank R. Billard, D. Paugy, B. de Merona, R.M. Hughes, and C. IRveque for their helpful comments on earlier drafts of this manuscript.

REFERENCES

Bagliniere, J.L., 1979. Les principales populations de poissons sur une riviere a salmonides de Bretagne-sud, le Scot% Cybium, 7: 53-74. Bergheim, A. and Selmer-Olsen A.R., 1978. River pollution from large trout farm in Norway. Aquaculture, 14: 267-270. Crumby, W.D., Webb, M.A. and Bulow, F.J., 1990. Changes in biotic integrity of a river in North-Central Tennesse. Trans. Am. Fish. Sot., 119: 885-893. De Lury, D.B., 1947. On the estimation of biological populations. Biometrics, 3: 145-167. Faure, A., 1977. Mise au point sur la pollution engendree par les piscicultures. Pisciculture, 13: 33-35.

234

T. OBERDORFF AND J.P. PORCHER

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235

SALMON FARM EFFLUENTS

APPENDIX

1

Total density and biomass by species for the 18 sites studied Site/

ANA

Species biomass

COG

BAB

SAT

PHP

RUR

SAS

ONM

LAP

LEL

ABB

biomass

biomass

biomass

biomass

biomass

biomass

biomass

biomass

biomass

biomass

PA1

520.8

12.7

6.7

884.1

0

0

0

0

0

0

0

PAl*

4378.1

3.3

6.9

861.1

1.3

0

0

3.3

0

0

0

PA2

1912

0

3.4

280.4

2.7

0

0

0

0

0

0

PA28

18947.3

0

0

187

0

0

0

0

0

0

0

900

908

15.6

0

0

0

134.9

0

0

0

0

0

0

0

0

0

0

0

0

2.5

0

0

AU1

32.4

898.8

AUl’

1133.3

5.9

106.3

3923.5

AU2

49.2

11.1

26.7

886.6

50.9

AUF

2352.7

0

46.4

871.8

128.3

0

0

37.3

0

0

AU3

616.5

16.7

50.4

220.9

104.3

3325

62.7

0

0

251.7

0

AU3’

1125.2

0

162.8

405.9

74

237442.9

36.1

0

0

5718.5

JEl

209.7

18

0

737.2

0

28.6

0

0

0

0

JEl*

1464.7

18

6.7

1590.7

2.2

17.4

0

0

0

0

0

ELI

211.1

1.5

11.9

718.4

2.9

0

106.1

0

0

0

0

4556.4

6.2

55.6

4807

1.9

0

515.8

0

0

0

0

0

83

ELI*

0

SC1

1147

4.5

58.3

2215.6

SC10

4446.7

0

0.2

54.3

0

102.4

191.1

167.2

89.9

1005.3

0

0

0

2949.1

75.5

15.8

3385.5

0

0

0

JAI JAI*

Site/

ANA

Species density

5.6

0

8.4

0

0

66.8

0

0 115

5.4 291

0 1270.4

0

0 922

0

0

0

0

COG

BAB

SAT

PHP

RUR

SAS

ONM

LAP

LEL

ABB

density

density

density

density

density

density

density

density

density

density

PA1

5.7

2.8

1.5

29.1

0

0

0

0

0

0

0

PAl*

25.3

0.7

1.3

10.4

0.4

0

0

0.1

0

0

0

PA2

11

0

0.6

4.6

0.7

0

0

0

0

0

0

PAF

91.4

0

0

0.9

0

0

0

0

0

0

0

AU1

0.9

496.9

237.8

3.1

0

0

0

48.9

0

0

AUl*

13.3

0.5

22.9

32.5

0

0

0

0

0

0

0

AU2

0.3

2.5

5.1

14.7

14.2

0

0

0

0.6

0

0

0

8.9

7.2

35.6

0

0

0.3

2.1

0

0 0

AU2*

10

40

AU3

3.2

8.1

19

3.1

49.8

13.2

1.2

0

0

11

AU3*

6.7

0

29.4

2.5

32.8

439.5

0.8

0

0

135.3

0

JEl

2.6

4.5

0

26.7

0

0

1

0

0

0

0

JEl*

12.3

7

1.6

43.6

1.1

0.2

0

0

0

0

0

EL1

0.5

1

1.8

17.9

0.8

0

3.2

0

0

0

0

ELI*

34.5

1

9.8

44.9

0.6

0

7.8

0

0

0

0

SC1

15.8

1

11.2

30.4

1.6

0

7.7

0

0

0

0

SC10

42

0

0.2

0.6

0

1.4

0

0.4

0

13.1

2

1.2

70.9

11.4

36.1

0

0

0

0

2.4

26.8

11.6

2.4

83.4

0

0

0

1.2

JAl JAI*

See Table 1 for site codes and Table 2 for species codes. *Sites sampled downstream from fish farms.

84

0

0

0

0