Classification and ordination of macroinvertebrate ... - Springer Link

Hydrobiologia 171: 59-78 (1989) O Kluwer Academic Publishers

Classification and ordination of macroinvertebrate assemblages to predict stream acidity in upland Wales K. R. Wade1, S. J. 0rmerod2 & A. S. Gee3 ' Welsh Water Authority, South Eastern District Laboratory. Tremains House, Coychurch Road, Bridgend, Mid Glamorgan, CF31 2AR, Wales, U. K. 2UWIST, Department of Applied Biology, c/o South Western District Laboratory, Penyfai House, 19 Penyfai Lane, Llanelli, Dyfed, SA15 4EL, Wales, U.K. Welsh Water Authority, South Western Division, Hawthorn Rise, Have$ordwest, Dyfed, SA61 2BH, Wales, U.K. Received 2 January 1987; in revised form 6 October 1987; accepted 20 November 1987

Key words: acid streams, macroinvertebrate, indicator species, ordination, classification, coniferous forest

Abstract Macroinvertebrates were collected from rimes at 104 sites in upland Wales during April and July 1984. Species assemblages were ordinated by DECORANA, classified by TWINSPAN and related to stream chemistry and other environmental factors using correlation and multiple discriminant analysis. DECORANA axis 1 was most strongly correlated with pH and aluminium concentration whilst axis 2 correlated with stream gradient and flow. Four TWINSPAN site groups established in each season were also principally related to pH and aluminium concentration, and reflected overall taxon-richness; differences between groups were most apparent during spring, when catchment forest cover and taxon-richness were also related. A dichotomous key based on indicator species was established for each season with the coleopteran Hydraena gracilis Germar and the Ephemeroptera, including Baetis rhodani Pictet, important indicators at Level 1. We propose that these indicator systems may be used for the rapid detection and assessment of acid waters throughout Wales, and that the methodology is applicable generally. Introduction Large areas of northern Britain and Wales are subject to episodes or substantial depositions of acidity from the atmosphere (Fowler et al., 1982; Harriman & Morrison, 1982; Sutcliffe etal., 1982; Stoner et al., 1984; Welsh Water unpublished). Many such areas are underlain by basepoor rocks and, in some instances, afforestation with conifers has represented a further acidifying influence on streams and lakes (Harriman

& Morrison, 1982; Stoner & Gee, 1985). As a consequence of concern over the acidities of surface-waters in Wales (Stoner et al., 1984; Stoner & Gee, 1985; Ormerod et al., 1985; Ormerod & Edwards, 1985), Welsh Water began, in 1984, a programme of investigation into this topic in which the study of benthic macroinvertebrates has figured prominently. In addition to the value of macroinvertebrate assemblages as bio-indicators of stream conditions (Wright et al., 1984), several genera have high conservation value

(Jenkins et al., 1984) and some provide an important source of food for riverine vertebrates (Hawkins et al., 1983; Stoner et al., 1984; Ormerod et al., 1985; Ormerod et al. 1986). In this paper, we describe spatial patterns in invertebrate assemblages, revealed by techniques of ordination and classification and correlate these with stream chemistry and other environmental variables. We describe an indicator system, based on invertebrate species, which permits the rapid detection and assessment of acid waters throughout Wales. We also propose a method by which invertebrate assemblages can be forecast in conjunction with hydrological models of catchment acidification (Cosby et al., 1986, Whitehead et al., 1986) and this will be expanded in a subsequent paper (Ormerod et al., in press). A companion deals with stream macroflora (Ormerod et al., 1987a).

Ystwyth and Rheidol, locally influenced by mine drainage, all the rivers are free from major polluting discharges.

Methods Macroinvertebrate collection and identpcation Macroinvertebrates were collected from rimes at 104 sites during April and July 1984, by 3 kick samples of 1 minute duration taken with a standard handnet (aperture 25 x 25 cm, mesh pore size 1.0 mm). Samples were preserved in 4% formaldehyde solution. Taxa were identified where possible to species (i.e. excluding Chironomidae and Hydracarina) and assigned to one of three abundance categories (1 = 1-9,2 = 10-99; 3 = 2 100 individuals per sample). Environmental data

Study area Covering a total area of 4000 km2 and an altitudinal range of 50-500 m 0.D., the study extended throughout the upper reaches of 16 river systems in west, mid and north Wales (Fig. 1). The bedrock underlying this area is mainly Ordovician and Silurian shales, grits and mudstones which are relatively impermeable and resistant to chemical weathering. Soils are predominantly brown podzolics, ferric stagnopodzols and oligomorphic peats and, as a result of these catchment characteristics the quality of surface runoff is generally acidic (< 10 mg Ca COJ - ' ; < p H 5.5). Historically, the predominant vegetation was deciduous woodland, but it has been progressively cleared over 5000 years. During the past 30-50 years, there has been extensive afforestation with conifers (mostly Sitka Spruce Picea sitchensis Carriere) on former rough pastures, plantations now comprising 20% of the land use and 90% of the woodland area in upland Wales (Parry & Sinclair, 1985). With the exception of metal pollution in the

The dominant substratum type was recorded at each sampling location and assigned to one of five categories; 1 = boulders and cobbles 64 > 256 mm; 2 = cobbles 64-256 mm; 3 = cobbles and pebbles 16-256 mrn; 4 = pebbles 16-64 mm; 5 = pebbles and gravel 2-64 mm. Stream gradients, altitude and percentage catchment afforestation were derived from Ordnance Survey maps (O.S. 1 : 50000 series). Mean discharge rates for each stream were calculated from catchment drainage characteristics and rainfall data. Water quality data were based on weekly samples collected from biological sampling sites between October 1983 and September 1984. Stream waters were filtered on site through a 0.45 pm Millipore membrane and acidified with nitric acid for dissolved metal determinations. In the laboratory, metals were determined by preconcentration and atomic absorbtion spectrophotometry. pH was determined using a combination pH electrode; the analytical methods have been described by Stoner et al. (1984) and the chemical data are the subject of a separate report (Welsh Water unpublished).

Fig. 1. The study area and sampling locations m. The inset shows solid geology indicating the extent of Ordovician and Silurian sediments in Wales (shaded).

Statistical analysis Macroinvertebrates. In order to reduce macroinvertebrate data into units which could be related to environmental variables, species assemblages were classified and ordinated respectively using the FORTRAN procedures TWINSPAN and DECORANA (Hill, 1979a; Hill, 1979b). Separate analyses were performed on data from April and July. Classification by TWINSPAN arranges site groups into a hierarchy on the basis of their taxonomic composition; species are classified simultaneously on the basis of their occurrence in site groups. Indicator species are also identified, these showing the greatest preference for a given sitegroup at any given division. In our study, the TWINSPAN classification was weighted according to the three abundance categories using the 'pseudospecies' concept (Hill, 1979a). In ordination by DECORANA, sites are arranged into an objective order, those sites with

similar taxonomic composition occurring most closely together. An axis score is produced which can be used in relating the ordination to environmental factors. In our study, DECORANA was used after invoking the 'downweighting' option in order to minimise the influence of rare species (Hill, 1979b). Relationships between macroinvertebrates and environmental variables. In allcases of further analysis, environmental variables were approximately transformed to give the closest approximations to normality; this was assessed graphically using MINITAB (Ryan et al., 1985). Relationships between TWINSPAN classification and environmental variables (winter and summer mean concentrations) were undertaken by Multiple Discriminant Analysis (MDA) using the SPSS routine Discriminant (Klecka, 1975; SPSS Inc., 1983). The procedure identifies linear combinations of variables which discriminate most strongly between site groups defined a-priori

Table 1 Numbers of macroinvertebrate taxa collected from unpolluted sites in each of the principal catchments in April and July 1984

Catchment

No. of sites

Macroinvertebrate taxa April Mean

Alaw Glaslyn Conwy Clwyd Dee Dwyryd Mawddach Dyfi Dysynni Rheidol WY~ Ystwyth Aeron Teifi Tywi Cothi (Tywi) Eastern Cleddau Gwaun Ebbw

July Range

Mean

Range

on the basis of classification; contributions by individual variables to the discrimination are judged according to weighting coefficients and on the basis of correlations with the discriminant function. In our study, variables entered into each MDA were selected to minimise multicolinearity, previously identified by correlation and Principal Components Analysis. Following examples in other similar studies, a step-wise MDA was not undertaken (Green and Vascotto, 1978; Wright et al., 1984), and the number of discriminant functions which had a statistically significant input was determined by testing against Wilk's lambda, transformed into Chi2 (Klecka, 1975).

Interrelationships between ordination scores for each site and environmental variables were assessed by Principal Components Analysis using the SPSS routine FACTOR (SPSS Inc., 1983). Bivariate relationships were assessed by productmoment correlation using MINITAB (Ryan et al., 1985).

Results

Two hundred and fifteen macroinvertebrate taxa were collected during April and July, approxi-

Table 2. Product-moment correlations between biological and environmental variables (after transformations to approximate normality). All cases n > 88. Variable

DCA score Axis 1

Aluminium (log)

Taxon richness Axis 2

Ephemeroptera

,

Calcium (log) Magnesium (log) Zinc (log) Lead (log)

uv absorbance' (log) Conifer forestry Altitude Gradient (log) Average daily flow (log) Substratum

** p < 0.01 *** p < 0.001 1 measurement of organic acids by UV absorbance at 225 nm

Plecoptera

Trichoptera

All taxa

forest cover, (Kolmogorov-Smirnov, P < 0.05), although this pattern was apparent only in spring (Fig. 2).

mately 175 in each season. The principal groups recorded on both occasions were the Trichoptera and Diptera each comprising 19-25 % of the taxa (excluding Chironomidae), whilst the Plecoptera, Ephemeroptera and Coleoptera each comprised 12-15%. The number of taxa collected varied greatly between sites within each catchment (eg. Teifi, 24-59; Rheidol, 7-24 and Wye, 11-34 taxa, Table 1) and, overall, correlated most strongly with pH and aluminium concentration (Table 2). The number of trichopteran and ephemeropteran species recorded at each site also correlated most strongly with these variables (Table 2). There was some evidence that the taxon richness of invertebrates was related to land use: catchments with > 50% forest cover held streams which had significantly fewer taxa than sites with ~ 5 0 %

I

0

,

,

,

15

,

,

,

30

.

.

,

.

45

Number of taxa (April)

.

Each TWINSPAN classification was concluded at Level 2 after the production of four site groups (Nos. 4,5,6 and 7) and four taxon groups (I, 11, I11 and IV); further divisions did not produce ecologically meaningful results. Following the first classification, two sites from the Alaw and Ebbw catchment were identified as having highly atypical assemblages, and these were excluded from subsequent analyses. In spring, TWINSPAN groups 4 and 5 (41

,

60

I 0

,

,

,

. 15

,

.

, 30

,

.

,

.

45

,

, 60

Number of taxa (July)

Fig. 2. Relationships between macroinvertebrate taxon-richness in (a) spring (b) summer and percentage catchment afforestation (0 = O%, n = 39; 0 = 1-lo%, n > 15; = 11-49%, n > 24; = >50% forest cover, n > 20).

- G a m r u s Pulex Baetls mutlcus Phllopotam~smontanus Hydropsyche lnstabllls Pedlcla rlvosa Baetls rhodanl Ecdyonurus sop Sllo palllpes Tanytarslnl Rhlthrogena semlcolorata Slmullum rheophllum Elmls aeneo Serlcostoma Personatum -Hydraena gracllls Esolus para1 leleplaedus Orectochllus vll losus Hydronsyche ?el lucldula Elseniel la tetroedra Hydropsyche slltalal Chloro~erln trlpunctata Drusus annulatus Potamophy lax SPP Leuctrn ninra L , lnermls Lumbrlculus varleqatus Isoperla grammatlco ~hyocophlla dorsnl is Dlcranota Wledenannla rials alolna Enchytraeldae Llmnlus volckmarl Protonenura meyerl Amohlnemurn sulclcollls Orthocladllnae Phagocata vltto Brachyotera rlsl Chloroperla torrentlum Stylodrllus herlnglanus Dlameslnae Slmullum ornatum group -0ullmnlus tuberculotus - Leuctra h lppo?us Polycentropldae Slmullum latlpes S, brevlcoule gram Tonypod 1nae Prosinullun arvenense P , lnflatum - Nemourn clnerea TWINSPAN GROUPS Fig.3. TWINSPAN classification of sites using spring macroinvertebrate communities.

sites) were principally from catchments in southwest Wales (Teifi and Cothi) whilst groups 6 and 7 (6 1 sites) were mainly from mid and north Wales (Rheidol, Wye, Mawddach and Conwy catchments). Group 4 sites generally supported > 40 taxa (mean44) and were characterised by taxon groups I and I1 which contained Baetis rhodani, Rhithrogena semicolorata Curtis (Ephemeroptera), Philopotamus montanus Donovan (Trichoptera) and Gammarus pulex L. (Crustacea) (Fig. 3). Sites in group 5 had taxon richnesses which ranged from 22-54 (mean 32) and they had fewer Ephemeroptera than sites in group 4. Contrastingly, Ephemeroptera, Trichoptera and Coleoptera were generally scarce or absent at sites in groups 6 and 7 and average taxon richnesses were 22 (range, 11-34) and 17 (range, 7-36), respectively. The Plecoptera, including Leuctra inermis Kempny, Isoperla grammatica Poda and Brachyptera risi Morton, (taxon group 111), was the most widespread and abundant taxon at group 6 sites, although only Amphinemura sulcicollis Stephens and Chloroperla torrentium Pictet were frequently collected at sites in group 7. Leuctra hippopus Kempny (taxon group IV) was the only widespread species which occurred in greater numbers at sites in group 7 than elsewhere (Fig. 3). In the summer, TWINSPAN groups 4 and 5 contained additional sites from the Mawddach, Conwy and Wye systems previously classified in groups 6 and 7. There was little difference in taxon-richness between groups 4 and 5 (mean 3 1 and 37 taxa, respectively) and between groups 6 and 7 (mean values 21 taxa each). As in the spring, groups 4 and 5 were characterised by mayflies (Baetis rhodani, Ephemerella ignita Poda and Ecdyonurus spp.), with the stoneflies Isoperla grammatica and Chloroperla torrentium occurring mostly in group 5 ((Fig. 4). All these species were poorly represented at sites in groups 6 and 7, although one ephemeropteran, Baetis vemus, Curtis occurred most frequently in group 7 (Fig. 4). A dichotomous key based on indicator species was established for each season with the coleop-

term Hydraena gracilis and the Ephemeroptera, including Baetis rhodani important indicators at Level 1 (Fig. 5).

Relationships between classijication and physicochemistly

The TWINSPAN classification in spring could be related to differences between site groups in pH, calcium, magnesium and aluminium concentrations. Group 4 sites mostly had pH > 6.5 in winter, whilst mean pH values respectively in groups 5, 6 and 7 were 6.1, 5.8 and 5.2. Group 7 also had the lowest concentration of calcium and highest concentrations of aluminium. Such strong differences were not apparent between the chemistry of TWINSPAN site groups in summer, although pH, calcium, magnesium and aluminium concentrations still differed between the two major groups (Figs. 6 & 7). In spring, sites in TWINSPAN groups 6 and 7 were more likely to be drawn from catchments with > 50% forest cover than sites in groups 4 and 5 (Chi2 = 7.3 P < 0.01). Similar concordance between forest cover and summer TWINSPAN groups was not significant (Chi2 = 2.7 P > 0.05). Multiple discriminant analysis (MDA) established that pH and log aluminium, in separate analyses, were the major environmental variables reflecting the TWINSPAN division of sites at Level 1 in spring. These two variables were highly correlated with Function 1 (correlation > 0.76) and had the highest contribution to the Function (standardised coefficient > 0.77). By using either pH or aluminium, and seven other non-correlated variables, 83436% of sites could be classified to the correct TWINSPAN group at Level 1 using environmental data alone (Table 3). At Level 2 (4 site groups), conifer afforestation and stream gradient were also important variables, although differences in water chemistry between site groups were still the strongest discriminators; 58% of sites were successfully classified. (Table 3). In summer, MDA indicated that pH and log aluminium, in separate analyses, were the major environmental variables reflecting the TWINS-

-

Dlstrlbutlon

- kduanurus

,

(-) ),(

(-1 (-1 -1

I

Group 6 ( n = 36)

Group 7 ( n = 25)

(-1 (-1 (-) (-

I

Score 4 -2 Chloroperla t o r r e n t i u n l 1 Isouerla q r m a t i c a Simulium brevicaule gp.2 Pedicia rivosa 1 Arnphinemura s u i c i c o l l i s l 1 Dixa puberula Score Q 2

(-1 (-1

Group 1 ( n = 98)

( b ) Summer

Group 4 ( n = 30)

C

.

Score Score

Score

(+

fl

Score

(+)

(+I (+)

(+)

(+I

Score

>, 3 9

Group 5 ( n s 28)

.

Score

,
, -1

1 Baetis rhodani Ephemerella i g n i t a l Phagocata v i t t a 1 Velia 1 Dicranota

(-1 (-1

(+I (+I (+I

0 Score

>, 1

Group 7 ( n = 12)

Fig. 5. Macroinvertebrate indicators of TWINSPAN site classification in (a) spring and (b) summer. Abundance categories; 1 = 1-9, 2 = 10-99. Indicator scores; ( + ) = + 1, ( - ) = - 1.

Table 3. Multiple discriminant analysis of environmental variables at each TWINSPAN level of division (macroinvertebrate classification; spring). Ranking shown in parentheses.

Level of TWINSPAN division (No. of groups) -

-

1 (2)

-

Variable

Function 1 CORR

Function 1 SDCF

CORR

SDCF

pH Zinc (log) Lead (log) UV Absorbance (log) Conifer forestry Altitude Gradient (log) Substratum Canical correlation Chi squared Percentage correct prediction CORR correlation with discriminant function SDCF standardised discriminant function coefficient *** significant at 5%

Table 4. Multiple discriminant analysis of environmental variables at each TWINSPAN level of division (macroinvertebrate classification; summer). Ranking shown in parentheses.

Level of TWINSPAN division (No. of groups)

1 (2)

Variable

Function 1 CORR

PH Zinc (log) Lead (log) UV Absorbance (log) Conifer forestry Altitude Gradient (log) Substratum

0.74 (1) -0.23 (4) -0.10 (8) 0.21 (5) -0.27 (3) -0.13 (6) 0.11 (7) 0.33 (2)

Canical correlation Chi squared Percentage correct prediction CORR correlation with discriminant function SDCF standardised discriminant function coefficient *** significant at 5%

Function 1 SDCF

CORR

SDCF

Group 5 60

1

Group 7

Fig. 6. Distribution of pH and dissolved aluminium, ((a) October to March, (b) April to September) in relation to TWINSPAN site groups in (a) April and (b) July, respectively; shading corresponds to values at > 70% of sites in each TWINSPAN group. Total number of water samples x 2 000.

Group 4

Group 5

Group 7

PH

Aluminium ( p g I-')

Group 4

Group

5 45 1

Group 6

Group 7

Calcium (pequiv I-')

Magnesium (pequiv I-')

Fig. 7. Distribution of calcium and magnesium ((a) October to March, (b) April to September) in relation to TWINSPAN site groups in (a) April and (b) July respectively; shading corresponds to values at > 70% of sites in each TWINSPAN group. Total number of water samples x 2000.

Group 4

Group 5

Group 6 60

40

20

0

Group 7 60

40

20

0

Calcium

( pequiv

I-'

PAN division of sites at Level 1 (Table 4). Stream gradient was also important at Level 2 and was the strongest discriminator when aluminium was included in the analysis (correlation = 0.66, standardised coefficient = 0.93). In comparison with the spring classification, fewer sites were classified to the correct TWINSPAN group at Level 1 (78-81 %), although 68-71 % of sites were successfully classified at Level 2. Ordination

Further evidence of a close relationship between stream chemistry and invertebrate assemblages was shown by DECORANA. Plots of axis 1 and axis 2 from spring revealed site groupings similar to those shown by TWINSPAN (Fig. 8). Scores

on axis 1 were highly correlated with pH and log aluminium concentration (r > 0.65, P < 0.00 1) whilst scores on axis 2 were correlated with log gradient, log flow and % catchment afforestation (r > 0.46, P < 0.001) (Table 2). Axis 1 could therefore be seen as separating rivers on the basis of acid related factors, whilst axis 2 detected sites on streams of different size. Principal Components Analysis also showed strong relationships between acid related factors and biology. Log aluminium, pH, log calcium, log magnesium and several biological variables all loaded significantly onto Factor 1, which explained 32.5 % of the total variance (Table 5). Factor 2 was highly correlated with log gradient, catchment afforestation (mean loading 0.7 17) and axis 2 ordination scores.

Group 7

Axis 1

150

DCA Scores 100

Axis 2

DCA Scores

Fig.8. DECORANA (D. C. A.) ordination using spring macroinvertebrate communities; polygons enclose all sites in each TWINSPAN group.

Table 5. Factor loadings of variables on Components 1 and 2 established by Principal Components Analysis; ranking shown in parentheses.

Variable

Factor loadings Component 1

-

-

Component 2

-

pH Aluminium (log) Calcium (log) Magnesium (log) Zinc (log) Lead (log) UV Absorbance (log) Conifer forestry Altitude Gradient (log) Average daily flow (log) Substratum DCA axis 1 scores DCA axis 2 scores Ephemeropteran taxa Plecopteran taxa Trichopteran taxa Total no. of taxa

% variance explained

32.5

14.3

Discussion It is well known that base-poor, acidic, streams in temperate areas have impoverished macroinvertebrate faunas (Sutcliffe & Carrick, 1973; Townsend et al., 1983, Stoner et al., 1984; Simpson et al., 1985). Moreover, studies in several geographical areas have classified invertebrates using TWINSPAN and related site groups to stream acidity (Townsend etal., 1983; Ormerod & Edwards, 1987; Weatherley & Ormerod, 1987). A similar pattern was apparent in this study, in which pH and aluminium concentration were the variables most closely related to the ordination, classification and taxon richness of macroinvertebrates. Elsewhere in Wales, such relationships are known to have consequences for birds dependent on aquatic macroinvertebrates as a food source (Ormerod et al., 1985, 1986). Populations of salmonid fish are also limited in acidic Welsh streams and, whilst the toxic effects of acid-related factors are probably important,

influences on fish through the scarcity of invertebrate food cannot be excluded (Bown, 1983; Hawkins et al., 1983; Stoner et al., 1984; Ormerod et al., 1987b; Welsh Water unpublished). Several empirical and experimental studies have indicated the biological importance of episodic changes in acidity and related factors (Driscoll et al., 1980; Hall et al., 1980, 1985; Zischke et al., 1983; Ormerod et al., 1987b). In this study, the more pronounced differences between invertebrate assemblages occurred in April, a period preceded by seasonal extremes of low pH and high concentrations of aluminium (Gee & Stoner, in press). Our data are, therefore, consistent with an influence on invertebrates, either directly or indirectly, through seasonal extremes. For example, sites in TWINSPAN groups 5 and 6 d i e r e d markedly in their relative frequencies of winter samples with low pH ( < 6.0) and higher concentrations of aluminium (>45 pgl - ' ) (Fig. 6). The invertebrate species which were absent from the more acidic sites, e.g. Baetis rhodani, Gammarus pulex, Hydropsyche instabilis Curtis, Hydraena gracilis; Group I, (Fig. 3) were also absent in other studies involving streams with low or fluctuating pH (Sutcliffe & Carrick, 1973; Townsend et al., 1983; Stoner et al., 1984; Ormerod & Edwards, 1987). However, it is noteworthy that one species, B. vernus, from the normally acid intolerant genus Baetis, occurred during July in the acidic TWINSPAN group 7 (Fig. 4). This species overwinters at the egg stage before hatching in April (Macan, 1979) and such a life-cycle may prevent exposure of the nymph to low pH events. Autecological studies of such adaptations in life-cycle and diet which permit the colonisation of acidic streams during the summer would prove useful in Baetis vemus and other species. Whilst it is not possible from our data to determine the nature of any causal relationships between acid-related factors and macroinvertebrates, behavioural avoidance of acid waters, differences in trophic status, direct physiological action by low pH or toxicity through elevated metal concentrations are all likely. For example, Costa (1967) showed by laboratory experiment

that Gammarus pulex actively avoided waters of pH < 6.2 and SutclifTe & Carrick (1973) noted that Baetis rhodani did not select acidic tributaries when ovipositing. Alternatively, the scarcity of some algae and the impoverished epilithon in acidic streams probably provide an inadequate diet for scrapers or surface grazers such as Ephemeroptera (Sutcliffe & Carrick, 1973; Ziemann, 1975; Winterbourn et al., 1985; Ormerod et al., 1987a). By contrast, shredders such as some plecopterans and trichopterans may benefit from the decreased rate of detrital breakdown, and increased fungal biomass on leaf litter, at low pH (Egglishhaw, 1964; 1968; Hildrew et al., 1984; Mackay & Kersey, 1985; Van Frankenhuyzen & Geen, 1986). However, some crustaceans suffer disturbances to their osmoregulation, acid-base balance and calcium regulation at low pH (Sutcliffe, 1978; Havas, 1981) and similar mechanisms might explain the scarcity or reduced growth of nymphal Ephemeroptera in acid streams (Komninck et al., 1972; Fiance, 1978). For example, the experimental acidification of a stream resulted in an increased drift amongst some invertebrates and a decline in benthic density which preceded changes in food availability (Hall et al., 1980). Ormerod et al. (1987b) found this effect particularly pronounced in the ephemeropteran Baetis rhodani at pH 5.0 when the aluminium concentration in a stream was experimentally increased to 350 pgl - ' for only 24 hours. Whilst there are few data available on the toxicity of aluminium to invertebrates, enhanced mortality may occur in some species and under some conditions at pH 4.0-5.0 with concentrations of 350-500pg A l l - ' (Havas, 1985; Havas & Likens, 1985; Burton & Allan, 1986; Ormerod et al., 1987b). These concentrations are exceeded in some Welsh streams with pH < 5.0 (Fig. 6). Further data are now required on the forms of aluminium which are likely to have the most pronounced biological effects (c.f. Driscoll et al., 1980). Elsewhere in Wales and in Scotland, drainage from conifer plantations influenced the aluminium concentration and acidity of soft-water streams,

-

with consequent effect on their fish and invertebrate faunas (Harriman & Morrison, 1981; Stoner et al., 1984; Stoner & Gee, 1985; Ormerod & Edwards, 1985). In this study, the extent of catchment afforestation emerged only secondarily to pH and aluminium concentration in relationships with invertebrate assemblages, possibly because no consideration was given to forest age (see also Jones, 1986). Nevertheless, streams from afforested catchments generally supported fewer taxa than those from unafforested catchments (Fig. 2), particularly where waters were softest. Such a pattern would be consistent with an acidifying or aluminium mobilising influence by conifers over a restricted range of soil types, for example those poorest in bases. Further research into the influences of land use and land management on the chemistry and ecology of soft-water streams in Wales is currently in progress. Several authors have emphasised the usefulness of stream invertebrates as bio-indicators and, in Britain, a system was recently proposed for classifying invertebrate assemblages in relation to environmental variables; as a result, the accurate prediction of environmental characteristics from indicator species seems likely (Furse et al., 1984; Wright et al., 1984). Our data shows that a similar system is possible for assessing the acidity of Welsh streams using a few easily identifiable species of invertebrate (Fig. 3,4,5) and this procedure can be rapid and highly cost-effective compared with traditional water quality monitoring. Moreover, linear relationships between invertebrate assemblages and environmental variables, such as those produced by multiple discriminant analysis, provide a method for predicting the biological response of streams to any quantifiable changes. Relationships of this kind could easily be incorporated into hydrological models of watershed acidification thereby permitting the inclusion of biological changes in forecast and simulations (e.g. Cosby et al., 1986; Whitehead et al., 1986; Minns et al., 1986). Such a model is currently being developed (Weatherly & Ormerod, 1987; Ormerod et al., 1987a).

Acknowledgements We wish to thank all those who have contributed to the work reported here, particularly to members of the District Biology and Chemistry Sections and Computer Services of the Welsh Water Authority. We also acknowledge computing facilities provided by The University of Wales Institute of Science and Technology. The Welsh Water Authority approved publication of this paper. Dr. J. H. Stoner and Dr. M. P. Brooker commented on the manuscript. The opinions expressed by the authors do not necessarily reflect those of the Welsh Water Authority.

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