Recovery of crustacean zooplankton communities from acid and metal ...

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Recovery of crustacean zooplankton communities from acid and metal contamination: comparing manipulated and reference lakes1 Norman D. Yan, Wendel Keller, Keith M. Somers, Trevor W. Pawson, and Robert E. Girard

Abstract: By comparing long-term changes in the crustacean zooplankton communities of three experimentally limed lakes near the Sudbury, Ontario, metal smelters with both temporal and spatial reference lakes distant from Sudbury, we (i) demonstrate the value of reference lakes for studies of recovery, (ii) compare univariate versus multivariate indicators of recovery, and (iii) determine if the pace of recovery was regulated by the severity of acid and metal contamination. The reference lakes provide recovery targets and norms of interannual variability. As indicators of damage and recovery, the performance of the univariate metrics was richness = diversity > evenness > abundance. Multivariate metrics were developed by projecting the Sudbury data onto a correspondence analysis of the spatial reference data. Univariate and multivariate approaches were equally sensitive for metrics based on species presence; however, the multivariate metrics incorporating the relative abundances of taxa were the best overall performers. While the two more acidic (pH 4.5) lakes had not recovered 15 years after neutralization, the zooplankton of Nelson Lake, the least acidic (pH 5.7) of the experimental lakes, recovered completely within 10 years of liming. This augurs well for the recovery of zooplankton in thousands of moderately acidic North American lakes, should international reductions in SO2 emissions reverse their acidification. Résumé : En comparant les changements survenus à long terme dans les communautés de crustacés zooplanctoniques de trois lacs expérimentalement chaulés situés près des usines métallurgiques de Sudbury (Ontario) avec des valeurs temporelles et spatiales mesurées dans des lacs de référence situés à distance de Sudbury, nous (i) démontrons l’utilité des lacs de référence dans l’étude de la restauration d’un bassin lacustre, (ii) comparons des indicateurs de restauration univariés et multivairés et (iii) déterminons si la rapidité de la restauration dépend de la gravité de la pollution acide et métallique. Les lacs de référence nous ont permis d’établir des objectifs de restauration ainsi que des normes de variabilité interannuelle. La performance des mesures univariées comme indicateurs de détérioration et de restauration peut être représentée comme suit : richesse = diversité > uniformité > abondance. Nous avons obtenu les valeurs multivariées en mettant en relation les données recueillies à Sudbury et les résultats d’une analyse des correspondances appliquée aux données de référence spatiales. Les approches univariée et multivariée se sont révélées d’une sensibilité égale avec les mesures relatives à la présence des espèces; toutefois, c’est avec les mesures multivariées incluant l’abondance relative des taxons que nous avons obtenu la meilleure performance d’ensemble. Les deux lacs les plus acides (pH de 4,5) n’étaient pas restaurés 15 ans après la neutralisation, mais le zooplancton du lac Nelson, le moins acide (pH de 5,7) des lacs expérimentaux était complètement restauré 10 ans après le chaulage. Ces résultats laissent espérer que, si les mesures internationales de réduction des émissions de SO2 avaient pour effet de renverser l’acidification, le zooplancton serait restauré dans les milliers de lacs moyennement acidifiés de l’Amérique du Nord. [Traduit par la Rédaction]

Introduction Acid precipitation has damaged thousands of lakes and streams in North America (Schindler et al. 1989). The principal acid source is SO2 emitted to the atmosphere during the

combustion of S-bearing fossil fuels and metallic ores (Baker et al. 1991). In recognition of the cause of the problem, the governments of Canada and the United States have legislated substantial reductions in atmospheric emissions of SO2. It is widely expected that many acidified lakes and streams will

Received August 16, 1995. Accepted January 17, 1996. J13041 N.D. Yan,2 K.M. Somers, T.W. Pawson, and R.E. Girard. Ontario Ministry of Environment and Energy, Science and Technology Branch, Dorset Research Centre, Dorset, ON P0A 1E0, Canada. W. Keller. Ontario Ministry of Environment and Energy, Co-operative Freshwater Ecology Unit, 199 Larch Street, Sudbury, ON P3E 5P9, Canada. 1 2

This paper is dedicated to the late Dr. Bill Geiling, who generated the data. Author to whom all correspondence should be addressed. e-mail: [email protected]

Can. J. Fish. Aquat. Sci. 53: 1301–1327 (1996).

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Table 1. Selected morphometric and premanipulation chemical data from the experimental lakes.

Latitude (N) Longitude (W) Distance from smelters (km) Mean depth (m) Maximum depth (m) Lake area (ha) Water residence time (years) Total P (µg⋅L–1) pH Ca (mg⋅L–1) Total Cu (µg⋅L–1) Total Ni (µg⋅L–1)

Hannah

Middle

Nelson

46°21′ 81°02′ 4.3 4.0 8.5 27.3 1.7 5.7 4.29 11.4 1108 1865

46°26′ 81°02′ 5.0 6.2 15.0 28.2 1.2 7.3 4.40 9.8 496 1068

46°44′ 81°05′ 28 11.6 51.0 309 4.6 4.6 5.73 4.4 22 17

Note: Chemical values are ice-free season averages of weekly to fortnightly data for 1973 for Middle Lake, 1974 for Hannah Lake, and 1974 for Nelson Lake (from Yan and Miller 1984). Residence times are means of measured values in 1978 and 1979 (from Scheider 1984).

recover as a result of the legislation (Jeffries et al. 1992) and that additional damage will be prevented. Unfortunately, the recovery of acidified lakes cannot be guaranteed. There is little doubt that the acidity of precipitation will decline when emissions of SO2 are reduced (Hedin et al. 1987; Dillon et al. 1988) and that lake water acidity will, eventually, follow suit (Dillon et al. 1986; Battarbee et al. 1988; Keller et al. 1992a). However, we are not yet certain how aquatic biota will respond to the improvements in water quality. A large number of factors may influence rates of recovery of biota from acidification (Cairns 1990; Detenbeck et al. 1992). Few of them have been studied. Schindler et al. (1991) proposed that the best way to investigate the recovery of lakes was to compare the results of whole-lake restoration experiments with data from spatial and temporal reference lakes. The restoration experiments examine recovery at the only scale, the whole lake, at which all withinlake processes that might influence recovery can be studied. The reference lake data serve three purposes. The temporal reference data provide a yardstick for determining if changes in the experimental lakes are unusual in rate, magnitude, or direction (Carpenter et al. 1989). The spatial reference data provide recovery targets, and tests of the realism (sensu Schindler et al. 1991) of the whole-lake experiments. To our knowledge, only Schindler et al. (1991) and Keller et al. (1992b) have adopted this comparative approach to the study of recovery of aquatic biota from acidification. Schindler and colleagues decreased inputs of acid to an experimentally acidified lake in northwestern Ontario and compared the results with reference lakes near Sudbury, Ontario. Keller and colleagues neutralized the acidified Bowland Lake and compared changes in the zooplankton with both temporal and spatial reference data from south-central Ontario lakes. Here, we compare experimental lakes with temporal and spatial reference lakes to examine long-term recovery of crustacean zooplankton communities from acid and metal contamination. We have three objectives. First, we illustrate the three uses of the temporal and spatial reference data. Secondly, we compare the sensitivity of univariate and multivariate metrics of community damage, change, and recovery to identify the

ones that are useful indicators of recovery. We expect that the multivariate metrics will be superior, because unlike their univariate counterparts, they incorporate patterns of interspecies covariation (Warwick and Clarke 1991). Thirdly, we compare the rates of recovery of zooplankton communities in lakes that differ in the severity of stress, i.e., acidity and metal contamination. The severity of stress is a potentially important regulator of recovery that has received little study (Henrikson et al. 1985; Poff and Ward 1990). Specifically, we describe changes in the crustacean zooplankton communities of three experimental lakes that have occurred in the 14–16 years since CaCO3 and Ca(OH)2 were first added. We compare these changes with 10 years of data from three nonacidic (pH > 6.0) temporal reference lakes and with 1 year of data from 47 spatial reference lakes. Twenty-two of these lakes have pH > 6.0 and provide our recovery targets.

Description of study lakes The experimental lakes are located near Sudbury, Ontario, an area extensively damaged by SO2 and metal emissions from Cu and Ni smelters during this century (reviewed by Keller 1992). The majority of existing studies of biological recovery from acidification have been performed in Sudbury-area lakes, because reductions in local industrial emissions of SO2 and toxic metals have led to improvements in water quality in many lakes (Gunn and Keller 1990; Keller et al. 1992a; Nicholls et al. 1992; Locke et al. 1994). In the early and middle 1970s, CaCO3 and Ca(OH)2 were added to four Sudbury lakes that varied in pH and metal levels in an attempt to determine if reductions in acid inputs would permit biological recovery (Dillon et al. 1979; Yan and Dillon 1984). One of the lakes, Lohi Lake, reacidified within a few years (Yan and Dillon 1984) and is not considered here. The pH levels of Middle, Hannah, and Nelson lakes, the other three experimental lakes, have remained above 6.0 until the present. Experimental lakes The three experimental lakes are primarily used for recreation. There are several summer cottages on the shores of Nelson Lake and both summer cottages and permanent dwellings on the shores of Middle and Hannah lakes. Selected geographic, morphometric, and premanipulation data from the lakes are provided in Table 1 and detailed elsewhere (Yan and Miller 1984; Scheider 1984). The outflow of Hannah Lake feeds into Middle Lake. Prior to manipulation, the severity of contamination of the lakes was related to their distance from the smelters. Hannah Lake is closest to the emission sources and was very acidic and contaminated with metals prior to manipulation (Table 1). Middle Lake was as acidic as Hannah Lake but only half as contaminated with metals. Nelson Lake was furthest from the smelters and was the least contaminated of the three lakes prior to manipulation. Middle and Hannah lakes acidified 60–70 years ago when the first tall stacks were erected near Sudbury (Dixit et al. 1987). No fish survived acidification (Yan and Dillon 1984). At the time of its manipulation, Nelson Lake did support several fish species (Gunn et al. 1988), but the degradation of the fishery was apparent in the scarcity of lake trout (Salvelinus © 1996 NRC Canada

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Fig. 1. Long-term changes in pH, Ca, TP, and Cu in the experimental lakes. Data are ice-free season averages of weekly to twice-monthly samples prior to 1980 (Yan and Dillon 1984; Yan and Lafrance 1984) and monthly samples thereafter.

namaycush), the extinction of smallmouth bass (Micropterus dolomieu), and the dominance of the littoral zone assemblage by the acid-tolerant yellow perch (Perca flavescens). We manipulated the lakes in three ways. First, CaCO3 and Ca(OH)2 were added to Middle Lake in the fall of 1973, to Hannah Lake in the spring of 1975, and to Nelson Lake in the fall of 1975 and the spring of 1976 (Yan and Dillon 1984). In an attempt to accelerate biological recovery, small amounts of phosphorus were added to Middle Lake during the ice-free seasons of 1975–1978 and to Hannah Lake from 1976 to 1978 (Yan and Lafrance 1984). Finally, fish were stocked into Middle Lake in 1976. Unfortunately, the remaining Cu and perhaps other trace metals prevented their survival (Yan et al. 1979). The limnological changes induced by these manipulations during the 1970s are described by Scheider and Dillon (1976), Yan et al. (1977), Dillon et al. (1979), Yan and Dillon (1984), and Yan and Lafrance (1984). The water quality was immediately improved by the additions of base. Lake water pH rose above 6.0 and concentrations of Cu, Ni, and other toxic metals plummeted (Fig. 1). However, while the appearance of a few new species was encouraging, the zooplankton communities of Middle and Hannah lakes were atypical of nonacidic lakes of any trophic status in 1980, 5 years after additions of base (Yan and Lafrance 1984). Subsequent to our manipulations, there was one additional, indirect manipulation of Middle and Hannah lakes. The municipality of Sudbury launched a reclamation project of the

so-called Sudbury barrens during the 1980s (Lautenbach 1987). Granular limestone and fertilizer were added to the catchments of Middle and Hannah lakes between 1983 and 1984. The rising pH levels of the lakes in the mid–1980s reflect these additions (Fig. 1). The catchment of Nelson Lake was not treated. We attribute the longevity of its circumneutrality (Fig. 1) to continuing generation of alkalinity in the lake and its subcatchments, to declining SO2 emissions from the smelters (Keller et al. 1992a), and to its long water residence time (Table 1). Metal levels continued to decline in Middle and Hannah lakes during the 1980s (Fig. 1), most likely because of the liming of their catchments and the reductions in acid and metal emissions from the smelters (Dillon et al. 1986). Metal levels in many other Sudbury lakes also declined from the mid–1970s to the mid–1980s because of reduced smelter emissions (Keller et al. 1992a). Levels of total phosphorus (TP) rose in response to the fertilization of Middle and Hannah lakes but only during the mid–1970s (Fig. 1), the years of treatment. TP concentrations averaged 5–6 µg⋅L–1 both prior to and after the liming of Nelson Lake (Yan et al. 1977; W. Keller, unpublished data). Because of the short-lived effects of fertilization and the mortality of the stocked fish in Middle Lake, we consider the additions of base to the lakes and their catchments to be the only manipulations with long-term consequences for the experimental lakes. © 1996 NRC Canada

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Table 2. Correlations of input variables on first two components of the separate morphometric and chemical principal components analyses used to select the 47 spatial reference lakes from the 56 candidates (n = 56). Matrix and variables Morphometry matrix % of variance explained Maximum depth Lake area Lake volume Shoreline length Chemistry matrix Variance explained (%) Alkalinity Al Ca Chlorophyll a Cl Dissolved inorganic C Dissolved organic C Fe Secchi depth K Mg Na pH SiO3 SO4 Total P Total N Total inorganic N

Axis 1

Axis 2

79.1 0.669 0.954 0.983 0.916

18.3 0.739 –0.268 0.064 –0.33

40.4 0.862 0.048 0.866 0.442 0.537 0.808 0.597 0.237 –0.497 0.805 0.890 0.796 0.731 0.656 0.405 0.494 0.629 0.380

24.0 0.354 –0.803 0.377 –0.614 0.141 0.057 –0.701 –0.298 0.786 0.135 0.368 0.215 0.592 –0.080 0.562 –0.740 –0.620 –0.066

Reference lakes The 47 spatial reference lakes are located in the County of Haliburton and the districts of Muskoka, Parry Sound, and Nipissing in south-central Ontario. The lakes range widely in area (7.2–769 ha, median 52.4 ha), and maximum (5.8–61 m) and mean depth (1.8–22 m, median 6.9). The lakes are roughly 200 km southeast of Sudbury but within the same biogeographic region for zooplankton (Sprules 1977). The lakes have forested catchments and are used principally for recreation. As is typical of Canadian Shield lakes the spatial reference lakes have low Ca concentrations (1.2 to 4.0 mg⋅L–1) and low Gran alkalinity (–0.11 to 6.23 mg⋅L–1 CaCO3), and they are relatively nutrient poor. TP ranges from 3.7 to 22 µg⋅L–1 with a median of 6.6. Secchi transparency ranges from 1.26 to 9.33 m, mainly because of differences in dissolved organic carbon (DOC) (1.5–8.71 mg⋅L–1 of C) among lakes. While the lakes are largely beyond the influence of the Sudbury smelters (Zeng and Hopke 1994), the pH of the lakes does range widely, from 5.29 to 6.68 with a median of 5.87. Precipitation is acidic in southern Ontario, and the buffering capacity of catchments varies widely (Neary and Dillon 1988). Our 47 spatial reference lakes were selected from 56 candidates chosen to reflect the range in acidity, nutrients, and morphometry of Canadian Shield lakes in south-central Ontario. These 56 lakes were sampled for 1 year each (1983, 1984, 1987, or 1988). Because of the potential for bias if atypical lakes were used to formulate recovery targets, a subset of 47 of these lakes formed our spatial reference set. The selec-

tion was based on separate multivariate patterns of 18 chemical and 4 morphometric variables (Table 2). The chemical data were ice-free season averages of monthly composite samples weighted for the volumes of depth strata within the euphotic zone for chlorophyll and for the entire lake for the other parameters. Using SYSTAT (Wilkinson 1990), we summarized each matrix with a principal components analysis (PCA) of the correlation matrix of ranked data. The first two axes of the PCA on the morphometric data accounted for 99% of the variance in the input matrix and separated a lake size component (large correlations of all four variables but especially area, volume, and shoreline length with axis 1) from a lake depth component (large correlations of maximum depth on axis 2; Table 2). The first two axes of the PCA of the chemical data summarized 64% of the rank-order variation in the 18 chemical variables. We interpret the first axis of the chemistry PCA as an acidity–ionic strength factor because of the strong correlations of alkalinity, Ca, dissolved inorganic C, K, Mg, Na, and pH. We interpret the second component as a eutrophy–dystrophy factor on the basis of correlations of TP, DOC, Secchi depth, and Al (Table 2). The majority of Al is associated with DOC in Canadian Shield lakes (LaZerte 1984). To identify unusual lakes for exclusion, we centred an ellipse on the centroid of bivariate scatterplots of the first two components of each PCA. Assuming normality of each component, the ellipse was scaled to encompass 80% of the data. Six lakes fell outside of each resulting ellipse, with three lakes in common. The nine lakes that fell outside of either ellipse were omitted, leaving the 47 spatial reference lakes (Appendix 1). We selected Harp, Blue Chalk, and Red Chalk lakes from among the spatial references lakes as our temporal reference lakes. These three lakes have dimictic thermal regimes and nutrient-poor, soft, nonacidic waters of high clarity (Molot and Dillon 1991). Middle, Hannah, and Nelson lakes shared these features after manipulation. Yan and Strus (1980) and Yan (1986) provide brief descriptions of the zooplankton assemblages of these lakes.

Methods Sample collection and analysis The reference lakes were visited monthly during the ice-free season. Zooplankton were collected with a metered Dorset Research Centre (DRC) plankton net (McQueen and Yan 1993) at a single station located over the deepest spot in each lake. This 80-µm mesh conical net has a mouth diameter of 12.5 cm, and an open area ratio (porosity × filtering area / mouth area) of 4.4:1. It is equipped with a unidirectional current meter. Sample volumes were calculated using measured haul filtration efficiencies, which averaged 81% in the temporal reference lakes and 84% in the spatial reference lakes. We hauled the net from three to seven fixed depths to the surface of the reference lakes (Girard and Reid 1990), combining the contents of the hauls. The depths were chosen so that lake strata contributed to the composite sample in proportion to their volumes. Composites were preserved with buffered sugar–formalin in the field to a final formalin concentration of 6%. Subsequently a minimum of 250 crustacean zooplankton were identified, counted, and measured (Sprules et al. 1981; Allen and Yan 1994). from each sample. All Cladocera and mature Copepoda were identified to species, and immature copepods were identified to suborder. Samples were collected from Middle and Hannah lakes in each © 1996 NRC Canada

Yan et al. year between 1973 and 1989, except 1980. Nelson Lake was visited from 1973 to 1976, and in 1985, 1986, 1990, and 1991. Middle and Hannah lakes were sampled weekly or fortnightly prior to 1980 and monthly thereafter. Nelson Lake was sampled fortnightly in 1975 and 1976 and on a monthly basis in other years. Ice-free seasonal averages of the number of crustacean taxa per visit, their biomass, and crustacean zooplankton community assembly are not sensitive to such changes in sampling frequency (Sprules and Bowerman 1988; Yan and Welbourn 1990; Keller and Yan 1991). Nelson Lake was sampled with a conical tow net in 1973 and 1974 and a Schindler–Patalas trap thereafter. Zooplankton were collected from Middle and Hannah lakes using nonmetered nets in the early 1970s, a 34-L Schindler–Patalas trap in the late 1970s, and the DRC net in the 1980s. Haul filtration efficiency with the DRC net averaged 87% in Hannah Lake and 83% in Middle Lake, similar values to those recorded in the reference lakes. Using six univariate metrics, Yan and Strus (1980) demonstrated that changes in gear did not confound interpretation of the zooplankton data prior to 1980. We recently compared zooplankton data based on Plexiglas trap and DRC net collections in Plastic Lake, one of the spatial reference lakes (Johannsson et al. 1992). While differences between trap- and net-based data were statistically significant, they were orders of magnitude smaller than the temporal changes in the abundances of taxa in the experimental lakes. Therefore, comparisons of the occurrences and relative abundances of taxa in the pre- and post–1980 data are not confounded by the changes in gear. The samples collected from 1973 to 1975 were counted in their entirety for Crustacea, because of the scarcity of animals. Between 1976 and 1984, 350–400 animals were counted from each sample. After 1984, we adopted the reference lake protocol, counting and measuring a minimum of 250 individuals in each sample. Zooplankton data matrices We combined counts of Diaphanosoma brachyurum with Diaphanosoma birgei, and Daphnia catawba with Daphnia pulex to allow for changes in nomenclature over the course of the study (Kor ínek 1981; Dodson 1981). We also combined all species of Ceriodaphnia and Alona to the genus level because uncertainties in their identity were common. To reduce the influence of rare species on the multivariate analyses (Oksanen 1983; ter Braak and Prentice 1988), we excluded 14 species that were present in fewer than 5 of the 56 candidate spatial reference lakes or totalled less than 10 individuals. The taxa deleted were Acroperus harpae, Chydorus bicornutus, Daphnia rosea, Eubosmina coregoni, Leptodora kindti, Ophryoxus gracilis, Scapholeberis kingi, Aglaodiaptomus leptopus, Onychodiaptomus sanguineus, Leptodiaptomus sicilis, Senecella calanoides, Eucyclops agilis, Eucyclops speratus, and Paracyclops fimbriatus poppei. In the experimental lakes, we excluded 10 taxa that were present in only 1 of the 38 lake-years of observation or had a total count of less than 10. These taxa were Acantholeberis curvirostris, Alona sp., Daphnia ambigua, Daphnia dubia, Eubosmina coregoni, Eubosmina tubicen, Eurycercus lamellatus, and Eucylops agilis. The majority of taxa excluded are littoral migrants. We then corrected counts for subsample volumes and summed the counts of each taxon for each year. Appendices 1–3 present the resultant data matrices. By recoding all entries >0 to unity, we could examine both abundance and presence–absence (P–A) data matrices. Univariate and multivariate metrics All univariate metrics were averaged over the ice-free period. The univariate metrics for the crustacean zooplankton were the total crustacean zooplankton abundance (A; animals per litre), species richness _ on each visit (S_; taxa per collection), diversity (H′), and evenness (J′). We employed S, rather than the annual faunal size (St), because S_t is sensitive to changes in sampling and counting protocols, while S is insensitive to changes of the magnitude made in the experimental lakes (Yan and Welbourn 1990). Diversity (H′) was calculated using

1305 the Shannon–Wiener formulation (H′= –Σ pi (log10 pi), where pi is the proportional contribution of the ith species to the total count of all species). Evenness (J′) was calculated as H′/Hmax, where Hmax = log10 St. Immature, i.e., counted but unidentified, copepods were included in the calculation of A but were not included in the calculations of the other metrics. We employed correspondence analysis (CA; Hill 1974) to generate our multivariate recovery metrics for four reasons. The χ2 metric, the input resemblance measure of CA, is appropriate for both count and P–A data (Legendre and Legendre 1983). The underlying Gaussian assumptions of CA are more realistic than the linear or monotonic assumptions of other multivariate methods for reducing the dimensionality of species distribution data, especially if beta diversity is large (Gauch 1982). The results of CA are more robust than other common ordination methods to alternative data standardizations (Jackson 1993). Finally, both sites and taxa can be projected onto the same coordinate space (biplots) to identify the taxa responsible for the separation of lakes. CA can be used to generate a fixed reference frame against which to project independent, so-called passive observations (ter Braak 1987; Kingston et al. 1992). We employed the passive sample concept to generate multivariate metrics for both the temporal reference and manipulated lakes. We began by generating a fixed reference frame using the first three axes of a CA ordination of the spatial reference data (25 taxa in the 47 lakes) for both the P–A and count matrices (Appendix 1). This analysis produced site scores for each reference lake on each axis, and commensurate taxon scores on each axis. The taxon scores are the species-specific weights that, when combined with their associated eigenvalues, can be used to project the sites of an independent site-by-taxa matrix onto the reference frame. Then we projected the 30 temporal reference sites (3 lakes by 10 years; Appendix 2) and the experimental lake sites (3 lakes with 8–16 years of data; Appendix 3) onto the spatial reference frame. The scores for projections of the manipulated lakes were employed as our multivariate metrics. Statistical analyses We began with graphical explorations of the data. For the spatial reference data, we sought correlations of the univariate metrics with lake size, pH, and TP concentration, endeavouring to build stepwise regression models using the three variables as potential predictors. We compared the observed values of the univariate metrics of the experimental lakes with the interquartile ranges for the 22 spatial reference lakes with pH > 6.0. These 22 lakes were termed nonacidic. Damage to zooplankton communities is commonly observed when lake pH falls below 6 (Keller et al. 1990; Havens et al. 1993). For the multivariate metrics we centred ellipses on the means of the passive sample scores for each manipulated and temporal reference lake, scaling the ellipses’ axes to the standard deviations (SDs) of the passive samples and orientations to their covariance. We visually compared the areas of ellipses of the experimental and temporal reference lake projections to compare their variability. Then we examined the trajectories of the projections for the experimental lakes to determine how their communities had changed relative to the spatial reference lakes. Movement of a lake from beyond to within a region of the reference frame occupied by zooplankton communities found in nonacidic, oligotrophic lakes was interpreted as a sign of recovery. These exploratory analyses lead to five testable questions. (1) Prior to their manipulation, did the zooplankton communities of the experimental lakes differ from those of the 22 nonacidic spatial reference lakes? (2) Did temporal variability differ between the experimental and temporal reference lakes? (3) Did the communities of the temporal reference or experimental lakes change monotonically, i.e., unidirectionally, over time? (4) After the manipulation, had the communities of the experimental lakes recovered, i.e., did they resemble the nonacidic, spatial reference lakes? (5) Did communities of Hannah and Middle lakes recover at different rates after the ma© 1996 NRC Canada

1306 nipulation, i.e., did their distance from the mean of the nonacidic reference lakes change? Selecting the appropriate inferential statistics to examine these questions was difficult. We could not match pre- and post-manipulation time series of the experimental and temporal reference lakes to look for differences in paired observations (Carpenter et al. 1989; Eberhardt and Thomas 1991). The reference lake time series began several years after the experimental lakes were manipulated. Instead we assumed that the decade of zooplankton data from the temporal reference lakes was adequate to quantify the normal variability in Canadian Shield zooplankton communities. This assumption is reasonable given the short generation time of zooplankton (Pimm and Redfearn 1988). Using SYSTAT, we adopted the statistical methods that follow. To determine if the experimental lakes were damaged prior to manipulation (question 1), we used a one-way analysis of variance (ANOVA) to detect differences in means between the 5 premanipulation lake-years of data from the experimental lakes and the 22 nonacidic spatial reference lakes. The ANOVA was repeated for each univariate and multivariate metric. To determine if the temporal variation in the communities of the experimental lakes was unusually large (question 2), we used an approach based on Kersting (1988). We ran preselected comparisons between each experimental lake and the three temporal reference lakes based on Levene’s (Manly 1986) and Tukey’s honestly significant difference (HSD) tests. The input univariate data were annual root mean square deviations from each lake’s long-term mean. The input multivariate data were Euclidean distances from each annual mean to the lake’s centroid for the first three axes of the passive samples. We assumed that temporal variability would be greater in the experimental lakes than in the temporal reference lakes and greatest for the most damaged lakes. Hence, the predicted ranking of interannual variation was Blue Chalk = Harp = Red Chalk < Nelson < Middle = Hannah. To determine if the communities changed monotonically over time (question 3), we examined the rank correlation (Spearman’s ρ) of parameter values with ranked year (since manipulation for the experimental lakes). We employed one-tailed tests for the experimental lakes, as we were interested only in unidirectional changes toward the recovery targets. To determine if the zooplankton communities of the experimental lakes had recovered (question 4), we adopted an estimation rather than an inferential approach (Perry 1986; Gardner and Altman 1986). Our interest was to establish whether the metrics from the experimental lakes had values typical of the nonacidic, spatial reference lakes. To test this we subtracted the annual mean values for each metric for each experimental lake from the mean of the nonacidic spatial reference lakes, took the absolute value of this deviation, then divided it by the SD of the metric for the nonacidic spatial reference lakes. Thus, as in a Levene’s test (Manly 1986), differences of the experimental lakes from the mean of the 22 nonacidic communities were expressed in SDs. Differences of less than two SDs were considered an operational indication of recovery of the zooplankton communities, because ± two SDs encompasses 95% of the nonacidic communities. Finally, we wished to determine if Hannah and Middle lakes were recovering at the same pace after the last manipulation (question 5). Hence, we calculated the differences of each Middle and Hannah datum from the mean of the 22 nonacidic, spatial reference lakes for each year after 1978, the last year of fertilization. We then employed a paired t test on the two vectors of differences to determine if the lakes were recovering at different rates.

Results Changes in zooplankton in the experimental lakes The manipulations of the experimental lakes were followed by

Can. J. Fish. Aquat. Sci. Vol. 53, 1996

large changes in zooplankton community composition. Until the mid–1980s, the changes in the communities were remarkably concordant in Middle and Hannah lakes. Prior to additions of base, the dominant member of the zooplankton communities was Bosmina longirostris, a small, acid-tolerant (Havens 1992) herbivore (Fig. 2). Its abundance plummeted in relative and absolute terms immediately after base additions. The abundance of the normally littoral Chydorus sphaericus exploded to fill the vacant, pelagic grazer niche for the remainder of the 1970s (Fig. 2). Leptodiaptomus minutus, the most common zooplankter in Ontario and the dominant taxon in acidic lakes that have low levels of metals (Sprules 1975; Yan and Strus 1980), colonized the two lakes in the early 1980s. In the latter half of the 1980s, the communities of Middle and Hannah lakes diverged. Both lakes were colonized by Diaphanosoma sp. and the acid-sensitive (Keller et al. 1990) Daphnia galeata mendotae in the mid–1980s, but these two taxa established large populations only in Hannah Lake. By contrast, the zooplankton community of Middle Lake was dominated by the three small herbivores B. longirostris, Chydorus sphaericus, and Leptodiaptomus minutus throughout the 1980s. There were also large changes in the zooplankton of Nelson Lake 10 years after the additions of base. For example, the acid-tolerant (Yan and Strus 1980) Cyclops vernalis disappeared (Table 3). Several zooplankton species that are commonly found in nonacidic lakes across Ontario (Keller and Pitblado 1989) colonized the lake. These included the acidsensitive Daphnia galeata mendotae, Skistodiaptomus oregonensis, and Epischura lacustris (Keller et al. 1990; Schindler et al. 1991; Havens et al. 1993), the metal-sensitive Holopedium gibberum (Lawrence and Holoka 1987), the hypolimnetic Eubosmina longispina, and Diaphanosoma sp. Univariate metrics of recovery In their review, Marmorek and Korman (1993) noted that acidification lowers species richness but commonly has little effect on the total abundance of zooplankton. Our spatial reference data supported this generalization. The univariate metrics differed in their relationship with acidity among the spatial reference lakes. The product–moment _correlations of these metrics with pH decreased in the order S (r = 0.73, P < 0.01), H′ (r = 0.58, P < 0.01), J′ (r = 0.35, P < 0.02), and A (r = –0.37, P < 0.02). In stepwise multiple regression models including pH and lake area as predictors, the inclusions of area improved _ the predictability of S and H′ but not J′ and A (Fig. 3). The negative correlation between zooplankton A and pH is counterintuitive, because acidification is not accompanied by increases in zooplankton standing stocks (Marmorek and Korman 1993). We hypothesized that our negative correlation was an artifact of three factors: the positive correlation of pH with lake depth, the inclusion of all depths in our sampling protocol, and volumetric expressions of A that included profundal waters, which in deep lakes would have very low zooplankton abundance. To test for this potential artifact, we calculated the partial correlation of A with pH correcting for maximum depth. It was not significant (r = –0.23, P > 0.1). Therefore, the observed negative correlation between A and pH does not imply that acidification is followed by increases in zooplankton abundance. The four univariate metrics provided different insights into © 1996 NRC Canada

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Fig. 2. Annual changes in the relative abundances of dominant crustacean taxa in Middle and Hannah lakes. Species are Bosmina longirostris (B long), Chydorus sphaericus (C sph), Cyclops vernalis (C vern), Diaphanosoma sp. (Diap), Daphnia galeata mendotae (Dgm), Leptodiaptomus minutus (L min), Orthocyclops modestus (O mod), and Simocephalus serrulatus (S ser).

the initial degree of damage in the experimental lakes and the recovery of their zooplankton communities _ after manipulation. The more sensitive metrics (H′ and S) indicated that the zooplankton community of Nelson Lake was altered by the lake’s acidity but that it had fully recovered by the mid–1980s. In contrast, these metrics suggested that the zooplankton communities of Middle and Hannah lakes were still severely disturbed 14–16 years _ after the additions of base. The richness (S) of the zooplankton community of Nelson Lake recovered after manipulation, but _ it did not recover in Middle and Hannah lakes. Values of S were unusually low in

the experimental lakes prior to manipulation (Table 4, Fig. 4), a faunal impoverishment indicative of _acid and metal contamination (question 1). The variability in S in Middle and Hannah lakes did not exceed that of the temporal reference lakes during the study (question 2; P = 0.52–0.89 in the six preplanned comparisons). This reflects the_relatively modest, albeit significant (Table 5), increases in S in Middle and Hannah lakes _ during the study (question 3; Fig. 4). In contrast,S was much more variable in Nelson Lake than in the three temporal reference lakes (question 2; P < 0.001 in the three comparisons). This was a manifestation of the substantial and nearly continu© 1996 NRC Canada

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Table 3. Abundance (A; number per litre averaged over the ice-free season) of common zooplankton taxa in Nelson Lake.

Chydorus sphaericus Cyclops vernalis Calanoid copepodid Mesocyclops edax Bosmina longirostris Leptodiaptomus minutus Leptodora kindti Cyclops bicuspidatus thomasi Tropocyclops extensus Daphnia retrocurva Eubosmina longispina Nauplii Cyclopoid copepodid Daphnia longiremis Cyclops scutifer Daphnia pulex Skistodiaptomus oregonensis Daphnia galeata mendotae Holopedium gibberum Diaphanosoma spp. Epischura lacustris Total abundance

1973

1974

1975

1976

0.003 0.004 2.876 0.032 0.864 0.290

0.049

0.018 0.014 8.032 0.243 1.376 2.897 0.015 0.047 0.101

0.01 0.016 4.950 0.093 4.731 3.682 0.012 1.216 0.850

19.18 2.572 0.031 0.296

10.76 2.471 0.367 0.551

0.004

17.48 0.207 0.830 0.931 0.008 0.064

6.747 1.958

0.938 3.377

12.8

23.9

34.8

29.7

1985

1.957 0.055 0.244 0.295 0.04 0.03 0.023 1.053 0.708 2.999 0.010 0.008 0.003 0.002 0.576 0.218 0.122 0.013 8.35

1986

1990

0.002

0.009

1991

1.032 0.006 0.353 0.197 0.002 0.033 0.034 0.002 0.238 0.459 2.220 0.019 0.226 0.025 0.145 0.792 0.512 0.012 0.053 6.36

4.481 0.094 0.094 0.957 0.009 0.067 0.034

2.578 0.019 0.206 0.426

28.62 17.67 0.536 1.06 0.006 0.022 1.009 0.141 0.045 0.107 55.0

14.27 1.357 0.057 0.371

0.120 0.153

0.532 0.524 0.183 0.056 20.9

Note: Taxa are listed in rank order of their year of maximum abundance (Σ(AiY)/Σ Ai, where Ai is the abundance for the ith year and Y is the chronological rank of the year).

_ ous increase in S in Nelson Lake after manipulation (Table 5, Fig. 4). _ In Nelson Lake,S increased to 9 taxa per collection in 1985 and 1986 and to 10 taxa per collection in 1990 and 1991. These values are within the interquartile range of 9–10.5 species per collection for the 22 nonacidic spatial reference lakes (Fig. 4). The difference between Nelson Lake and the nonacidic reference lakes was much less than two SDs (our operational definition of recovery; question 4) from 1985 to 1991 for both mean daily (Fig. 5) and the _ total annual richness (which is not illustrated). In summary, S of the zooplankton community of Nelson Lake was damaged by acidification, but it recovered from damage during this study. The additions of phosphorus between 1975 and 1978 had no effect on the exceptionally low _ species richness of Middle and Hannah lakes (Fig. 4). While S did increase steadily during the 1980s (Table 5), the lakes supported only five zooplankton species per collection by 1989, much _ lower than the target level (question 4; Fig. 4). While the S of the zooplankton communities of Middle and Hannah lakes was improving, it had clearly not recovered by 1989. Finally, no differences between _ Middle and Hannah lakes were detected in the S or St data after manipulation (question 5; Table 4). Changes in the diversity (H′) of zooplankton in the experimental lakes provided different insights to those for richness. _ As for S, levels of H′ were very low prior to manipulation (Table 4, Fig. 6). The variation in H′ in Nelson Lake exceeded that of the three temporal reference lakes (P = 0.003–0.012 in three comparisons), while that of Middle and Hannah lakes _ did not (P = 0.08–0.75). However, the responses of H′ and S differed for Middle Lake in other ways. H′ increased over time in Nelson and Hannah lakes, but not in Middle Lake (Fig. 6, Table 5). The temporal changes in H′, while significant in the

temporal reference lakes (Table 5), were small in comparison with those in Nelson Lake (Fig. 6). H′ increased monotonically in Nelson Lake, reaching target levels by 1985. In contrast, H′ remained below the target values throughout the study for Middle and Hannah lakes, falling short of the mean value in the nonacidic spatial reference lakes by at least three SDs (Fig. 5). H′ diverged in Middle and Hannah lakes in the later years of the study; the differences approached significance (P = 0.075; Table 4) over the entire postmanipulation period. Evenness (J′) was not as reliable an indicator_of disturbance of the zooplankton communities as was H′ or S. Values of J′ were lower, on average, in the experimental lakes than in the nonacidic spatial reference lakes prior to manipulation (Table 4). Although J′ increased in Nelson Lake over time (Table 5), values were within the range observed in the nonacidic spatial reference lakes in 1974 prior to manipulation (Figs. 5 and 7). Furthermore, levels of J′ were within the range of the nonacidic spatial reference lakes the year of base additions in Hannah Lake and the year after additions in Middle Lake (Fig. 7). Values plummeted thereafter, reflecting the dominance of the community by Chydorus sphaericus (Fig. 2). Evenness did not differ between Middle and Hannah lakes for the postmanipulation period (Table 4), but for the last 5 years of the study, J′ was higher in Hannah Lake than in Middle Lake (Fig. 7). Indeed, levels in Hannah Lake were within or near the target range (i.e., within two SDs of mean J′ for the nonacidic spatial reference lakes) after 1985 (Fig. 5). Abundance (A) was the poorest indicator of disturbance. The mean value for the experimental lakes did not differ from that of the nonacidic spatial reference lakes prior to manipulation (Table 4), levels being obviously low only in Hannah Lake (Fig. 8). Abundance was more variable in Hannah Lake than in the three temporal reference lakes (P = 0.001–0.02 in © 1996 NRC Canada

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_ Fig. 3. Scattergrams of ice-free season estimates of diversity (H′), richness (S), evenness (J′), and abundance (A) of crustacean zooplankton versus pH in the 47 spatial reference lakes. Symbols represent lake areas of >100 (m), 10–100 (r), and 6) spatial reference lakes (question 1) and paired t tests to determine if Middle and Hannah lakes recovered at different rates after manipulation (question 5). Question 1 Metric

_ Mean richness (S) Diversity (H′) Evenness (J′) Abundance (A) CA on counts, axis I CA on counts, axis II CA on counts, axis III CA on P–A, axis I CA on P–A, axis II CA on P–A, axis III

Question 5

F

P

Paired t

P

128 97.6 48.6 3.06 22.7 4.43 9.38 14.1 4.98 45.6

6.0.

Fig. 7. Long-term changes in evenness of the crustacean zooplankton assemblages of the temporal reference and experimental lakes. A notched box plot (see Fig. 4) of evenness in the 22 spatial reference lakes with pH > 6.0 is provided.

of lakes of similar acidity prior to its manipulation, and (iii) sources of colonists and barriers to their distribution are not unique for Nelson Lake. We cannot immediately dismiss the first of these concerns. While experimental additions of base and reductions of acid input both decrease acidity, they may have different effects on lake water Ca. Aqueous Ca concentrations fall when acidity decreases in response to declines in SO2 emissions (Keller et al. 1992a). In contrast the experimental neutralization of Nelson Lake increased its Ca concentration from 4.1 mg⋅L–1 in 1975 to 5.4 mg⋅L–1 in 1976 (Yan et al. 1977). This difference may be important because Ca increases the tolerance of biota to acidity (Ingersoll et al. 1990). We do not believe these differences in Ca chemistry reduce the general applicability of the Nelson Lake findings, for four reasons. First, Ca influences acid sensitivity to a much smaller extent in nonacidic than in acidic waters (Ingersoll et al. 1990). Secondly, the Ca content of Daphnia spp., the most Ca rich of freshwater zooplankton, is not depressed in acidic lakes, by

comparison with levels in animals reared in hard waters (Yan et al. 1989). Thirdly, Ca is not a good predictor of zooplankton community composition in nonacidic (pH > 6) lakes in Ontario (Keller and Pitblado 1989). Finally, and most importantly, the long-term Ca pattern in Nelson Lake is one of decline (Fig. 1). The zooplankton recovery in the lake accompanied this decline, not the small increase induced by additions of base. Therefore, we have satisfied the first criterion for broad application of the Nelson Lake results. The second and third criteria are less problematic. The zooplankton community of Nelson Lake was, in fact, typical of lakes of pH 5.5–6.0 prior to its manipulation (Figs. 10 and 11). It was acid stressed. Nineteen years ago we did not recognize the stressed condition of the community (Yan et al. 1977), because we lacked the context of the reference lake data. Finally, we have no reason to believe that Nelson Lake is unique in terms of access to potential colonists. The recovery of the zooplankton community of Nelson Lake assumes broader significance given its similarity with other acid-stressed lakes prior to manipulation. Half of the 20 000 lakes in Ontario with a pH < 6.0 have a pH > 5.5 (Neary et al. 1990). They are moderately acidic, as was Nelson Lake prior to its manipulation. The complete recovery of the zooplankton of Nelson Lake, added to a growing body of evidence from other Sudbury area lakes (Keller and Yan 1991; Keller et al. 1992c; Locke et al. 1994), augurs well for the recovery of the zooplankton in thousands of acidified lakes in Ontario. Of course this assumes that emissions of SO2 will be reduced across North America and that the acidity of lakes will decline in consequence (Minns et al. 1992). © 1996 NRC Canada

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Can. J. Fish. Aquat. Sci. Vol. 53, 1996 Table 6. Spearman’s rank correlation coefficients of limnological variables with correspondence analysis scores for the spatial reference data set (n = 47). Count data % of variance explained Lake area Lake volume Mean depth Maximum depth Elevation Al Dissolved organic C Secchi depth Total P Gran alkalinity pH Mg Ca

Presence–absence data

Axis I

Axis II

Axis III

Axis I

Axis II

Axis III

24.1 –0.51 –0.55 –0.46 –0.41 –0.06 0.53 0.50 –0.56 0.54 –0.14 –0.35 –0.16 –0.25

15.4 0.40 0.51 0.60 0.65 0.23 –0.34 –0.21 0.24 –0.33 0.56 0.58 0.47 0.39

10.4 0.07 0.08 0.14 0.12 –0.46 0.01 0.16 –0.17 0.13 0.10 0.07 0.26 0.19

16.6 0.56 0.70 0.75 0.75 0.25 –0.49 –0.48 0.49 –0.60 0.39 0.53 0.34 0.35

12.9 –0.19 –0.24 –0.28 –0.28 0.22 0.11 –0.01 –0.02 0.12 –0.21 –0.24 –0.32 –0.21

12.0 –0.14 –0.18 –0.23 –0.21 –0.14 0.07 –0.24 0.28 –0.30 –0.41 –0.37 –0.42 –0.47

Univariate versus multivariate indicators of recovery Univariate and multivariate descriptions of spatial and temporal patterns in community structure differ in one fundamental way. Multivariate metrics are based on interspecies covariation patterns. Univariate metrics, being summed across taxa, ignore the species interrelationships. In consequence, multivariate methods are more sensitive than univariate ones at discriminating among communities observed at different sites or times (Warwick and Clarke 1991). In consequence, we expected the multivariate methods to be superior to our univariate methods at detecting both stress and recovery in the experimental lakes and at identifying differences among their zooplankton communities. In examining the sensitivity of our univariate and multivariate metrics, we must take care to pair metrics calculated from _ analogous data. Hence, we compared changes in S in the experimental lakes with the passive samples based on P–A data. Each is based solely on the occurrences, not the abundances, of taxa. Similarly, we compared the CA projections generated from the count data with the changes in A, H′, and J′, because these metrics were calculated from abundances of taxa. Our expectation of the greater sensitivity of the multivariate metrics was confirmed for the count-based statistics but not for those based on occurrences of taxa. Table 7 summarizes the results of our comparisons of univariate and multivariate metrics for the five questions posed. (1) Were the experimental lakes damaged before manipulation? (2) Were the experimental lakes unusually variable? (3) Did the communities of the experimental lakes change monotonically? (4) Did the communities recover from damage? (5) Did Middle and Hannah lakes differ? We used the sum of the number of positive answers to the questions and their subquestions as a simple descriptor of the comparative sensitivity of the metrics. Its maximum possible value is 12. For the P–A data, the multivariate and univariate metrics had similar overall sensitivity (Table 7), with a sum of six positive responses. The multivariate metric detected a significantly greater variability in occurrence of taxa in Middle and Hannah lakes than in all three temporal reference lakes. This was not detected in the data (question 2). However, monotonic

_ increases over time were apparent in S (Fig. 4), but not in the CA on the P–A data for Middle Lake (Table 7). The greater sensitivity of the multivariate metrics was obvious for the count data. The CA on counts produced 9 of 12 possible positive responses, a much higher total than all of the univariate metrics (Table 7). The multivariate metric detected several important patterns in the data; namely (i) that the experimental lakes were damaged by acidification, (ii) that Middle and Hannah lakes were unusually variable, (iii) that monotonic change was more common in the experimental than in the temporal reference lakes, (iv) that Nelson and Hannah lakes recovered, and (v) that the communities of Middle and Hannah lakes diverged during the 1980s. Each of the univariate metrics failed to detect several of these patterns (Table 7). Total abundance was a particularly poor performer, not even detecting damage in the experimental lakes prior to manipulation. The insensitivity of total plankton abundance to acidification is well documented (Marmorek and Korman 1993). The performance of the four univariate metrics in the manipulated lakes was similar to the rank of the correlations of the metrics with pH in the spatial reference data _set. The strength of these _correlations declined in the order S > H′ > A > J′ (Fig. 3). S and H′ were strongly positively related with pH in the spatial reference data set, in agreement with the literature (Locke 1992; Marmorek and Korman 1993), and performed relatively well as indicators of damage and recovery in our study (Table 7). Evenness detected fewer of _ the important patterns in the experimental lakes’ data than S or H′. Abundance was the poorest of the univariate metrics at detecting the patterns in the manipulated lakes that were evident in the multivariate data (Table 7). The partial correlation of A with pH, correcting for depth, was not significant in the spatial reference lakes. The two classes of multivariate metrics differed in their responsiveness to community change. The passive sample scores based on the P–A data for Middle and Hannah lakes did not change monotonically over time (question 3; Table 7). Those scores based on the count data did change monotonically for two of the three axes. Furthermore, the count-based multivariate metric, which was correlated with acidity in the © 1996 NRC Canada

Yan et al. Fig. 9. A multivariate comparison of the temporal variability of the experimental and temporal reference lakes. The experimental lakes are Nelson (Nn), Middle (Me), and Hannah (Hh); the temporal reference lakes are Blue Chalk (Bc), Red Chalk (Rc), and Harp (Hp). The ellipses are centred on the means of the (undisplayed) scores of experimental and the temporal reference lake projections against either the count or P–A data from the 47 (displayed) spatial reference lakes. The major axes of the ellipses are determined by the standard deviations of axis scores and set to encompass 95% of the data (assuming normality). The orientation of the ellipses is determined by the covariance of the projected scores. The three panels are projections of (A) abundance-based metrics in Nelson and the three temporal reference lakes, (B) P–A-based metrics in the experimental and temporal reference lakes, and (C) abundance metrics in Middle and Hannah and the temporal reference lakes. The CA axis selected as the ordinate in each panel was the one most strongly correlated with acidity among the spatial reference lakes. CA axis III was selected as the abscissa in B and C as the passive samples for Me and Hh lakes were most variable on this axis.

1315 Fig. 10. (A) Taxon–lake biplot of the first two axes of the correspondence analysis of the count data from the 47 lake spatial reference data set. Only those 17 taxa observed in Nelson Lake and the spatial reference lakes are included. 1, Bosmina longirostris; 2, Chydorus sphaericus; 3, Daphnia galeata mendotae; 4, Daphnia longiremis; 5, Daphnia pulex; 6, Daphnia retrocurva; 7, Diaphanosoma sp.; 8, Holopedium gibberum; 9, Eubosmina longispina; 10, Leptodiaptomus minutus; 11, Skistodipatomus oregonensis; 12, Epischura lacustris; 13, Cyclops scutifer; 14, Cyclops vernalis; 15, Mesocyclops edax; 16, Cyclops bicuspidatus thomasi; 17, Tropocyclops extensus). (B) Projection of the Nelson Lake count data against the spatial reference data set, with lines joining successive years.

was the multivariate one that incorporated the relative abundances of taxa. We recommend this as a useful indicator of recovery of zooplankton from acidification. Such approaches are also proving to be very useful for assessment of the biological state of other communities, for example, of the benthos in Great Lakes’ sediments (Reynoldson et al. 1995).

spatial reference lakes (axis II), diverged in Middle and Hannah lakes after manipulation, while the P–A-based metric (axis I) did not (Table 4). Hence, the best of the metrics of recovery

Recovery and the severity of stress There are a large number of factors that influence the rate of recovery of biota from any stress. These include the severity, duration, and timing of the stress; the chemical and biological condition of the habitat after the stress has been removed; the time since its removal; the availability of refuges; the distances to sources of potential colonists; the barriers to their dispersal and successful colonization; and the life histories and dispersal abilities of the stressed organisms (Cairns 1990; Niemi et al. © 1996 NRC Canada

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Fig. 11. (A) Taxon–lake biplot of the first two axes of the correspondence analysis of the P–A matrix for the 47 spatial reference lakes. Scores for only those 17 taxa observed in Nelson Lake are included. Boxed numbers correspond to species listed in Fig. 10A. (B) Projection of the Nelson Lake P–A data against the spatial reference frame. (C) Scattergram of axis I scores from the spatial reference lakes and the Nelson Lake projection versus lake water pH. (D) Scattergram of axis I scores from the spatial reference lakes and the Nelson Lake projections against lake maximum depth. Lines join succesive years in panels B–D.

1990; Detenbeck et al. 1992). These factors may act individually or in combination to influence the recovery of aquatic biota in formerly acidified lakes. To our knowledge, none of the factors have been explicitly examined in the context of recovery from acidification, although the importance of several has been acknowledged (Nyberg 1984; Henrikson et al. 1985; Keller and Yan 1991; Keller et al. 1992a). Because we were unable to isolate the severity of stress from several other potential regulators of recovery in our experimental design, we can only partially address the third objective of the paper. All of the metrics indicated that the zooplankton community of Nelson Lake has fully recovered, while that of Middle Lake has not. The behaviour of Hannah Lake is intermediate, with some metrics suggesting recovery and others, continuing stress (Table 7). The recovery of Nelson Lake may, in fact, be attributable to its less severe contamination. However, we cannot discount additional possibilities, namely, that the Nelson Lake community recovered because (i) it acidified more recently, (ii) the quality of its habitat was better after the manipu-

lations, (iii) distances to sources of colonists were shorter, or (iv) barriers to their dispersal were smaller than for Middle and Hannah lakes. Middle and Hannah lakes have been acidic for six or more decades (Dixit et al. 1987). As suggested by the continuing presence of lake trout, Nelson Lake probably acidified more recently, possibly permitting more rapid recovery. Unfortunately, paleolimnological assessments of the history of acidification of Nelson Lake have not been performed. Secondly, the recovery of Nelson Lake’s zooplankton may be attributable to its more suitable recent habitat (in this case water) quality. Copper is toxic to zooplankton in the 20–50 µg⋅L–1 range (Winner 1985). Such levels were recorded in Middle and Hannah lakes after additions of base but not in Nelson Lake (Fig. 1). Thirdly, the restoration of a normal fish community (Casselman and Gunn 1992) may also have promoted the recovery of zooplankton in Nelson Lake, while its continuing absence, the recent presence of yellow perch notwithstanding, may be delaying recovery in Middle and Hannah lakes. Ny© 1996 NRC Canada

Yan et al. Fig. 12. (A) Taxon–lake biplot of the second two axes of the correspondence analysis of the count data from the spatial reference lakes. Only those seven taxa important in Middle and Hannah lakes are plotted. Projection of the Middle Lake (B) and Hannah Lake (C) count matrices against the spatial reference data. Lines join successive years in Figs. 12B and 12C.

berg (1984) noted that zooplankton communities might not recover from acidification until normal predator communities were reestablished. Finally, the recovery of Nelson Lake may be related to the availability of colonists. There are more sources of potential colonists (nonacidic lakes) in the region of Nelson Lake than near Middle and Hannah lakes. In addition, the size of the endogenous pool of colonists (viable resting stages in lake sediments; Carvalho and Wolf 1989) is probably larger in Nelson Lake than in Middle and Hannah lakes, Nelson Lake being larger and less severely and more recently acidified. The difference in recovery between Hannah and Middle lakes in the latter half of the 1980s may also be attributable to differences in water quality. From 1985 to 1989, Cu levels in Middle Lake declined from 37 to 28 µg⋅L–1, while levels in Hannah Lake declined from 31 to 22 µg⋅L–1. On average, Cu levels in Hannah Lake were 6 µg⋅L–1 lower than in Middle Lake during this period. Because the pH and Ca levels in Hannah Lake were also higher than in Middle Lake it is likely that the waters of Middle Lake were more toxic to zooplankton than those of Hannah 15 years after additions of base (Winner 1985). Yan et al. (1996) examine this hypothesis in detail. Our results contribute to a growing body of information on

1317 Fig. 13. (A) Taxon–lake biplot of the first and third axes of the correspondence analysis of the P–A data from the spatial reference lakes. Only those six taxa that were important in Middle and Hannah lakes are plotted. Scattergrams of axis I on axis III scores for the CA of the P–A data from the spatial reference lakes with projections of the Middle (B) and Hannah (C) data are also included, with lines joining successive years.

the recovery of zooplankton from disturbances. Niemi et al. (1990) recently reviewed 81 studies in this field. They noted that zooplankton recover quickly (3 years) from such longer term disturbances. Our results support this generalization and provide a caution for future studies of recovery of zooplankton from long-term, multiple stresses. It is clear that long-term study is warranted to assess recovery in such situations. The zooplankton of Middle and Hannah lakes have not recovered 15 years after additions of base. It is doubtful that reliable information on the ultimate recovery of zooplankton communities from press disturbances can be gleaned from studies of only a few years duration, such as our earlier work on Nelson Lake (Yan et al. 1977). There is a need to study the factors that limit the recovery of aquatic biota from acidification, if the beneficial impacts of reduction in North American emissions of SO2 are to be predicted. Advantage should be taken of both natural experiments © 1996 NRC Canada

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Table 7. Summary of the results of the statistical analyses addressing the five questions dealing with recovery. _ Question Lake S CA on P–A A CA on count

H′

J′

1 2 2 2 3 3 3 3 4 4 4 5 ΣY

Y N N Y Ya N Y Y N N Y N 6

Y Y N N Y (1 of 3 lakes) N N Y N Y Y N 5

Middle Hannah Nelson Temporal reference Middle Hannah Nelson Middle Hannah Nelson

Y N N Y N Y Y Y N N Y N 6

Y Y Y N N N Y (1 of 3 axes) Y (2 of 3 axes) N Yb Y Y (1 of 3 axes) 6

N N Y Y (2 of 3 lakes) N N Y N — — — Y 3

Y Y Y N Y (3 of 9 axes) Y (2 of 3 axes) Y (2 of 3 axes) Y (2 of 3 axes) N Y Y Y (1 of 3 axes) 9

Note: The questions are as follows. (1) Were the zooplankton communities of the experimental lakes disturbed (different from the 22 nonacidic spatial reference lakes) prior to treatment (see Table 4)? (2) Were the zooplankton communities of the experimental lakes more variable than the temporal reference lakes (see Results section)? (3) Did the communities of the experimental and temporal reference lakes change monotonically over time (see Table 5)? (4) After the manipulation, did the communities of the experimental lakes recover, i.e., did they no longer differ from the 22 nonacidic, spatial reference lakes (see Fig. 5)? (5) Did the communities of Hannah and Middle lakes differ in their rates of recovery (see Table 4)? Question 4 was not addressed if the parameter was insensitive to acid stress. The number of yes (Y) answers is summed to an overall metric of parameter sensitivity. A Y is indicated if more than half the possible entries were Ys for the question. The exception is question 5 for the CA on counts. If a difference of Hannah from Middle Lake was detected on axis II, the axis correlated with acidity, we included this positive response in the total. a H′ increased in Harp Lake, but actually decreased in the other two temporal reference lakes (Fig. 6). b After 1984, CA P–A scores on axes I–III generally deviated by less than two SDs from the mean of the nonacidic lakes (Fig.5), although scores on axis I remained negative.

where water quality is improving in response to reductions in acid deposition (e.g., Keller et al. 1992a; Locke et al. 1994) and whole lake experiments such those of Schindler et al. (1991) and those presented herein. One of the goals of the S emission control legislation in North America is the restoration of acidified lakes. Implicit in the goal of this, as in other, environmental legislation (Karr 1990) is the protection and (or) restoration of natural floras and faunas, including zooplankton. Our results indicate that multivariate methods should be employed in the assessment of such recovery.

Acknowledgements We thank Martyn Futter for advice on data-base design; Garry Allen for software development; Joan Baker for thoughts on the limitations of liming studies; Bill Geiling and Claudiu Tudorancea for counting innumerable zooplankton samples; Charlie Chun, Don Evans, Peter Sutey, and Peter Grauds for analysis of water quality samples; and a long list of summer students for their work over two decades. Greg Mierle, Martyn Futter, Roy Stein, Andrea Locke, Bob Bailey, and Tom Frost provided helpful comments on early drafts. This study was funded by the Ontario Ministry of Environment and Energy’s Acid Precipitation in Ontario Study.

References Allen, G., and Yan, N.D. 1994. ZEBRA2, zooplankton enumeration and biomass routines for APIOS: a semi-automated sample processing system for zooplankton ecologists. Ontario Ministry of the Environment and Energy, Dorset, Ont. Baker, L.A., Herlihy, A.R., Kaufmann, P.R., and Eilers, J.M. 1991.

Acidic lakes and streams in the United States: the role of acidic deposition. Science (Washington, D.C.), 252: 1151–1154. Battarbee, R.W., Flower, R.J., Stevenson, A.C., Jones, V.J., Harriman, R., and Appleby, P.G. 1988. Diatom and chemical evidence for reversibility of acidification of Scottish lochs. Nature (London), 332: 530–532. Bender, E.A., Case, T.J., and Gilpin, M.E. 1984. Perturbation experiments in community ecology: theory and practice. Ecology, 65: 1–13. Cairns, J. 1990. Lack of a theoretical basis for predicting rate and pathways of recovery. Environ. Manage. 14: 517–526. Carpenter, S.R. 1989. Replication and treatment strength in wholelake experiments. Ecology, 70: 453–463. Carpenter, S.R., Frost, T.M., Heisey, D., and Kratz, T.K. 1989. Randomized intervention analysis and the interpretation of wholeecosystem experiments. Ecology, 70: 1142–1152. Carvalho, G.R., and Wolf, H.G. 1989. Resting eggs of lake Daphnia. I. Distribution, abundance and hatching of eggs collected from various depths in lake sediments. Freshwater Biol. 22: 459–470. Casselman, J.M., and Gunn, J.M. 1992. Dynamics in year-class strength, growth, and calcified-structure size of native lake trout (Salvelinus namaycush) exposed to moderate acidification and whole-lake neutralization. Can. J. Fish. Aquat. Sci. 49(Suppl. 1): 102–113. Detenbeck, N.E., DeVore, P.W., Niemi, G.J., and Lima, A. 1992. Recovery of temperate-stream fish communities from disturbance: a review of case studies and synthesis of theory. Environ. Manage. 16: 33–53. Dillon, P.J., Yan, N.D., Scheider, W.A., and Conroy, N. 1979. Acidic lakes in Ontario, Canada: characterization, extent and responses to base and nutrient additions. Ergeb. Limnol. 13: 317–336. Dillon, P.J., Reid, R.A., and Girard, R. 1986. Changes in the chemistry of lakes near Sudbury, Ontario, following reductions of SO2 emissions. Water Air Soil Pollut. 31: 59–65. Dillon, P.J., Lusis, M., Reid, R., and Yap, D. 1988. Ten-year trends in sulphate, nitrate and hydrogen deposition in central Ontario. Atmos. Environ. 22: 901–905. Dixit, S.S., Dixit, A.S., and Evans, R.D. 1987. Paleolimnological evi© 1996 NRC Canada

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1320 lon, P.J., Underwood, J.K. and Whelpdale, D.M. 1992. Expected reduction in damage to Canadian lakes under legislated and proposed decreases in sulphur dioxide emissions. In Canadian Global Change Program No. 92–1. Royal Society of Canada, Ottawa, Ont. Molot, L.A., and Dillon, P.J. 1991. Nitrogen/phosphorus ratios and the prediction of chlorophyll in phosphorus-limited lakes in central Ontario. Can. J. Fish. Aquat. Sci. 48: 140–145. Neary, B.P., and Dillon, P.J. 1988. Effects of sulphur deposition on lake-water chemistry in Ontario, Canada. Nature (London), 333: 340–343. Neary, B.P, Dillon, P.J., Munro, J.R., and Clark, B.J. 1990. The acidification of Ontario lakes: an assessment of their sensitivity and current status with respect to biological damage. Ontario Ministry of the Environment, Dorset, Ont. Nicholls, K.H., Nakamoto, L., and Keller, W. 1992. Phytoplankton of Sudbury area lakes (Ontario) and relationships with acidification status. Can. J. Fish. Aquat. Sci. 49(Suppl. 1): 40–51. Niemi, G.J., DeVore, P., Detenbeck, N., Taylor, D., Lima, A., Pastor, J., Yount, J.D., and Naiman, R.J. 1990. Overview of case studies on recovery of aquatic systems from disturbance. Environ. Manage. 14: 571–588. Nyberg, P. 1984. Impacts of Chaoborus predation on planktonic crustacean communities in some acidified and limed forest lakes in Sweden. Rep. Inst. Freshwater Res. Drottningholm, 61: 154–166. Oksanen, J. 1983. Ordination of boreal heath-like vegetation with principal components analysis, correspondence analysis and multidimensional scaling. Vegetatio, 52: 181–189. Patalas, K. 1990. Diversity of the zooplankton communities in Canadian lakes as a function of climate. Verh. Int. Ver. Theor. Angew. Limnol. 24: 360–368. Perry, J.N. 1986. Multiple-comparison procedures: a dissenting view. J. Econ. Entomol. 79: 1149–1155. Pimm, S.L., and Redfearn, A. 1988. The variability of population densities. Nature (London), 334: 613–614. Poff, N.L., and Ward, J.V. 1990. Physical habitat template of lotic systems: recovery in the context of historical pattern of spatiotemporal heterogeneity. Environ. Manage. 14: 629–645. Reynoldson, T.B., Bailey, R.C., Day, K.E., and Norris, R.H. 1995. Biological guidelines for freshwater sediment based on BEnthic Assessment of SedimenT (the BEAST) using a multivariate approach for predicting biological state. Aust. J. Ecol. 20: 198–219. Scheider, W., and Dillon, P.J. 1976. Neutralization and fertilization of acidified lakes near Sudbury, Ontario. Water Pollut. Res. J. Can. 11: 93–100. Scheider, W.A. 1984. Lake water budgets in areas affected by smelting practices near Sudbury, Ontario, In Environmental impacts of smelters. Edited by J. Nriagu. J. Wiley & Sons, Inc., New York. pp. 155–194. Schindler, D.W. 1987. Detecting ecosystem responses to anthropogenic stress. Can. J. Fish. Aquat. Sci. 44: 6–25. Schindler, D.W., Kasian, S.E.M, and Hesslein, R.H. 1989. Losses of biota from american aquatic communities due to acid rain. Environ. Monit. Assess. 12: 269–285. Schindler, D.W., Frost, T.M., Mills, K.H., Chang, P.S.S., Davies, I.J., Findlay, L., Malley, D.F., Shearer, J.A., Turner, M.A., Garrison, P.G., Watras, C.J., Webster, K., Gunn, J.M., Brezonik, P.L., and Swenson, W.A. 1991. Comparisons between experimentallyand atmospherically-acidified lakes during stress and recovery. Proc. R. Soc. Edinb. Sect. B Biol. Sci. 97: 193–227. Smol, J.P. 1992. Paleolimnology: an important tool for effective ecosystem management. J. Aquat. Ecosyst. Health, 1: 49–58. Sprules, W.G. 1975. Midsummer crustacean zooplankton communities in acid-stressed lakes. J. Fish. Res. Board Can. 32: 389–395. Sprules, W.G. 1977. Crustacean zooplankton communities as indicators of limnological conditions: an approach using principal component analysis. J. Fish. Res. Board Can. 34: 962–975.

Can. J. Fish. Aquat. Sci. Vol. 53, 1996 Sprules, W.G., and Bowerman, J.E. 1988. Omnivory and food chain length in zooplankton food webs. Ecology, 69: 418–426. Sprules, W.G., Holtby, L.B., and Griggs, G. 1981. A microcomputer–based measuring device for biological reserch. Can. J. Zool. 59: 1611–1614. Strayer, D., Glitzenstein, J.S., Jones, C.J., Loasa, J., Likens, G.E., McDonnell, M.J., Parker, G.G., and Pickett, S.T.A. 1986. Longterm ecological studies: an illustrated account of their design, operation, and importance to ecology. Occas. Publ. Inst. Ecosyst. Stud. 2. New York Botanical Garden, Mary Flagler Cary Arboretum, Millbrook, N.Y. Swanson, F.J., and Sparks, R.E. 1990. Long-term ecological research and the invisible place. BioScience, 40: 502–508. ter Braak, C.F.J. 1987. CANOCO: a FORTRAN program for canonical community ordination by [partial] [detrended] [canonical] correspondence analysis, principal components analysis and redundancy analysis, version 2.18 edition. TNO Institute of Applied Computer Science, Wageningen, The Netherlands. ter Braak, C.F.J., and Prentice, I.C. 1988. A theory of gradient analysis. Adv. Ecol. Res. 18: 271–317. Tilman, D. 1989. Ecological experimentation: strengths and conceptual problems. In Long-term studies in ecology: approaches and alternatives. Edited by G.E. Likens. Springer-Verlag, New York. pp. 136–157. Warwick, R.M., and Clarke, K.R. 1991. A comparison of some methods for analysing changes in benthic community structure. J. Mar. Biol. Assoc. U.K. 71: 225–244. Wiens, J.A. 1989. Spatial scaling in ecology. Funct. Ecol. 3: 385–398. Wilkinson, L. 1990. SYSTAT, the system for statistics. SYSTAT Inc., Evanston, Ill. Winner, R.W. 1985. Bioaccumulation and toxicity of copper as affected by interactions between humic acid and water hardness. Water Res. 19: 449–455. Yan, N.D. 1986. Empirical prediction of crustacean zooplankton biomass in nutrient-poor Canadian Shield lakes. Can. J. Fish. Aquat. Sci. 43: 788–796. Yan, N.D., and Dillon, P.J. 1984. Experimental neutralization of lakes near Sudbury, Ontario. In Environmental impacts of smelters. Edited by J. Nriagu. J. Wiley & Sons, Inc., New York. pp. 417–456. Yan, N.D., and LaFrance, C.J. 1984. Responses of acidic and neutralized lakes near Sudbury, Ontario, to nutrient enrichment. In Environmental impacts of smelters. Edited by J. Nriagu. J. Wiley & Sons, Inc., New York. pp. 457–521. Yan, N.D., and Miller, G.E. 1984. Effects of deposition of acids and metals on chemistry and biology of lakes near Sudbury, Ontario. In Environmental impacts of smelters. Edited by J. Nriagu. J. Wiley & Sons, Inc., New York. pp. 244–282. Yan, N.D., and Strus, R. 1980. Crustacean zooplankton communities of acidic, metal-contaminated lakes near Sudbury, Ontario. Can. J. Fish. Aquat. Sci. 37: 2282–2293. Yan, N.D., and Welbourn, P.M. 1990. The impoverishment of aquatic communities by smelter activities near Sudbury, Canada. In The earth in transition: patterns and processes of biotic impoverishment. Edited by G.M. Woodwell. Cambridge University Press, Cambrdge, U.K. pp. 477–494. Yan, N.D., Scheider, W.A., and Dillon, P.J. 1977. Chemical and biological changes in Nelson Lake, Ontario, following experimental elevation of lake pH. Water Pollut. Res. J. Can. 12: 213–231. Yan, N.D., Girard, R.E., and LaFrance, C.J. 1979. Survival of rainbow trout, Salmo gairdneri, in submerged enclosures in lakes treated with neutralizing agents near Sudbury, Ontario. Ontario Ministry of the Environment, Dorset, Ont. Yan, N.D., Mackie, G.L., and Boomer, D. 1989. Seasonal patterns in metal levels of the net plankton of three Canadian Shield lakes. Sci. Total Environ. 87–88: 439–461. © 1996 NRC Canada

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1321 Zeng, Y., and Hopke, P.K. 1994. Comparison of the source locations and seasonal patterns for acidic species in precipitation and ambient particles in southern Ontario, Canada. Sci. Total Environ. 143: 245–260.

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Appendix 1. The spatial reference data matrix. Lake Basshaunt Blue Chalk Solitaire Walker Red Chalk East Buck Bigwind Red Chalk Main Smoke Harp Nunikani Westward Poker West Mckay Delano Timberwolf Big Porcupine Sherborne Crown Leech Louisa Kimball Cinder West Crystal Leonard Dickie Gullfeather Little Whetstone Clara Clear Little East End Plastic Bonnechere Fawn Cinder East Chub Loucks Crosson Maggie Shoelace Heney Pincher Windfall Pearceley Skidway Drummer Sunset

1

2

3 204 92 11 17 2 22 161 159 39 95

9 80 20

9 6 4 23

1 175 433 30 167

12 8

155 245

35 47

5

3 47

1 5

2

2

1

3

4

32 100 72 42 15 44 60 71 53 80 14 63 21 17 31 25 18 26 22 5 6 9 7

16

10 26 1 2 10

20

3 17

5

6

7

8

9

42

38 150 42 147 59 23 127 177 79 46 130 8 3 5 130 44

19 69

27 23 71 20 143 72 15 51 1

10 15 4 2

47

19 24 62 3 266

88 32 84 4 7

53 2

23 57 1

42 6

16 4 26

7

65

26

91

3 2

10 101

6

6 95

55

43

4 38 4 20 26 4 1 39 7 10 25 35 18 22

3 14

18 54 3 6 36 2 27 37 2 29

11

2 1 11 1

9 5

15 3 71 61

10

9

8

5 225 1

15 5 3 1 51 13 2 6 2 1

18 1 1 1 1 11 2

19 1

6 12 2

7 6

4 14

1

9 2 1

5 13 9

27 115 6 24 40 1

4 2 44 25 11

2

2 1

10 19

2 2

5 141

1 2

4 70 14

4 2

80 29 1

2 178 27 15 29 5

89 26 1

2 4

5 1

1

31 1

1

Note: Entries are total counts of taxa in each lake corrected for differences among taxa in subsample volumes examined during sample processing. All immature copepods are excluded. Lakes are ordered by pH. Taxa are ordered by their rank correlation with CA axis II scores, the axis correlated with lake-water acidity. The species included are Eubosmina longispina (1), Daphnia dubia (2), Cyclops bicuspidatus thomasi (3), Sida crystallina (4), Daphnia longiremis (5), Daphnia galeata mendotae (6), Skistodiaptomus oregonensis (7), Cyclops scutifer (8), Epischura lacustris ( 9), Chydorus sphaericus (10), Daphnia retrocurva (11), Tropocyclops extensus (12), Bosmina longirostris (13), Polyphemus pediculus (14), Cyclops vernalis (15), Ceriodaphnia sp. (16), Diaphanosoma sp. (17), Daphnia pulex (18), Orthocyclops modestus (19), Alona sp. (20), Eubosmina tubicen (21), Holopedium gibberum (22), Daphnia ambigua (23), Leptodiaptomus minutus (24), and Mesocyclops edax (25).

12 9 18 5 37 204 15 24 9 46 61 60 16 133 7 194 243 25 10 17 26 4 34 199 12 4 65 697 2 174 12 3669 27 17 11 68 30 166 35 4 34 103 110 2 1 103 620 91 +

© 1996 NRC Canada

1323

Yan et al. Appendix 1 (concluded). 13 21 13 10 19 721 14 33 14 49 337 43 36 327 1 75 102 96 5 62 6 3 6 199 58 71 274 16 36 409 1191 28 27 136 123 20 125 102 101 241 684 217 213 9 30 310 64

14

1 2

15

16

1 1

3

4 1

1

12

17

18

19 1

17 5 43 5

286 17 8 37 27 82

16 76 1 141 10 1 15 33 2 22

1

2 1 3

16 4 2 8 26 2 21 48 6 1

20

2

1 15 31 2 5 24 53 32 14 6 3 84 28 235 39 130 65 204

2

93 245

1

19 1

1 1 41

47 67 115 100 1

21

121 91 2 82 128

1

1 1 2 1 6

3

20 16 8 54 39 25 61 65 9 13 352 59 2 139

1 1

37

34 7 26 35 88 115 1 12 71 27 75 28 20 61 11 17 22 34 18 3 9 14 12 77 52 124

55 2

7 1

22

43 26

23

1 4

1

13 5

1

2

11 5 30 24 14 13

3 910 121 2 1 1 5 286

1 7 1

5 1

593

2

165 72

1

1

75 67 1 43

102

387 20 18 88 64 20 98 58 23 1 15 41 173 28 484

112 4 2 4 1

24

25

7 174 58 116 77 46 140 224 22 185 69 768 14 71 15 219 6 122 315 81 118 192 44 309 226 310 43 178 205 47 6 698 22 35 107 221 288 141 246 102 1262 110 169 225 381 110 250

17 13 8 26 14 11 27 4 7 6 6 18 14 23 27 12 5 11 28 44 5 9 47 5 4 36 44 30 50 3 99 19 23 34 14 26 18 19 29 51 17 7 21 31 31 23

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Appendix 2. The zooplankton data from the temporal reference lakes. Lake

Year

1

2

3

Blue Chalk Blue Chalk Blue Chalk Blue Chalk Blue Chalk Blue Chalk Blue Chalk Blue Chalk Blue Chalk Blue Chalk Harp Harp Harp Harp Harp Harp Harp Harp Harp Harp Red Chalk Main Red Chalk Main Red Chalk Main Red Chalk Main Red Chalk Main Red Chalk Main Red Chalk Main Red Chalk Main Red Chalk Main Red Chalk Main

1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989

104 106 151 21 199 700 356 197 214 97 44

22 19 29 42 9 26 25 30 39 58 1

79 40 78 65 97 20 61 38 27 60 36 33 36 27 31 39 17 34 28 62 42 61 47 83 66 52 9 69 30 58

22

164 155 230 82 152 67 94 92 98 23

7 28 20 15 9 11 11 3 25

4

5

2

2 40 3 20 10 26 11 3 12 11 14

21 38 8 22 26 21 12 26 2

6

7

8

9

232 239 106 29 107 127 169 194 91 75 26 30 25 15 19 24 11 46 38 23 174 133 146 90 177 344 413 151 75 147

41 14 43 21 71 44 14 35 59 45

21 14 68 15 23 8 8 4 23 4

35 18 17 2 15 3 3 5 4 5 9 10 3 10 6 3 3 7 7 1 2

7 3 1 2

2 24 22 26 9 15 32 45 33 19 22

121 27 49 34 19 52 22 38 45 6

10

11

12

2 2

2

1 20 30 15 14 11 2 4 3 10 110 347 74 62 26 86 59 126 92 88 4 2 10 3 4 17 21 4 18 5

9 1 2

1 110 132 336 143 129 156 54 5 70 27

1

3 3 1

2 6 7 3 2 2 15 4 5 6

4

4

1

2

Note: Entries are total counts of taxa in each lake-year corrected for difference in subsample volumes counted. All immature copepods have been excluded. Taxa are coded as in Appendix 1.

© 1996 NRC Canada

1325

Yan et al. Appendix 2 (concluded). 13 22 8 28 21 11 11 13 10 3 50 1245 194 255 282 144 273 185 75 240 245 17 8 3 28 14 8 36 5 60 19

14

15

16

17

18

1

1

48 9 28 10 17 23 12 9 18 20 106 89 47 62 68 91 79 55 92 63 88 36 41 30 76 27 54 25 36 9

50 32 46 10 13 24 123 60 40 56

1

2 1 1 1

5 1 2 3 6 4 3

19

21 1 3

1

1 1

64 22 45 47 19 24 16 42 24 27

20

18 13 52 15 25 55 103 37 170 142 10 13 10 4 24 10 153 2 14 13

22 5 4 16 2 7 4 22 31 11 15 22 9 18 17 18 12 2 24 34 18 19 16 12 20 12 21 23 34 43 62

23 1

1 1

1

1 1

24

25

76 191 318 164 102 101 377 172 313 466 52 227 62 58 63 221 199 123 74 148 81 108 158 88 152 158 84 184 1296 219

42 9 28 15 11 26 15 14 13 23 8 3 8 4 4 8 4 3 1 7 6 20 9 4 8 25 8 9 7

© 1996 NRC Canada

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Can. J. Fish. Aquat. Sci. Vol. 53, 1996

Appendix 3. The zooplankton data from the experimental lakes. Lake

Year

Hannah Hannah Hannah Hannah Hannah Hannah Hannah Hannah Hannah Hannah Hannah Hannah Hannah Hannah Hannah Hannah Middle Middle Middle Middle Middle Middle Middle Middle Middle Middle Middle Middle Middle Middle Middle Middle Nelson Nelson Nelson Nelson Nelson Nelson Nelson Nelson

1973 1974 1975 1976 1977 1978 1979 1981 1982 1983 1984 1985 1986 1987 1988 1989 1973 1974 1975 1976 1977 1978 1979 1981 1982 1983 1984 1985 1986 1987 1988 1989 1973 1974 1975 1976 1985 1986 1990 1991

1

2

3

4

5

6

7

8

2

9 4

58 2 1 1 2

122

69 1085 593 1611 4366 2

1

1

45 27

40 8 9 24 116 12 11 6 18

11 6 53 25

6 50 2 9 36 13

177 240 70 115

1 8 4

45 154 2 104 73 88

4 23 9 11

10

11

132 151 159 2 802 5 780 3 044 1 179 306 40 32 10 10 7 23 48 18 607 101 2 622 20 630 4 551 2 234 947 10 50 38 105 40 17 106 45 11 6 24 10 8 1 1

12

2 1

8 1

59 89 10 10 3 33

Note: Entries are total counts of taxa in each lake-year corrected for difference in subsample volumes counted. All immature copepods have been excluded. Taxa are coded as in Appendix 1.

© 1996 NRC Canada

1327

Yan et al. Appendix 3 (concluded). 13

14 571 680 40 6

6 245 31 13 999 1 399 504 4 928 135 1 149 764 18 015 508 52 27 5 1 382 494 12 258 2 386 65 42 1 790 3 073 13 930 1 423 613 368 509 73 102 9 44

15

16

6 108

1

173 58 119 144 18

17

18

19

20

21

22

1

27 171 36 84 3

1

31 428 56 31 135 119 131 1

2 9 339 2410 1049 1152 1251 3433 1258 832 2136

2 1 4 89 421

18 6 2 2 1

25

4

1

16

24

3

1 28

17

23

4

2 100 15 16

6 40

1 1

10 10 13 46 4 3 41

1 9 1

61 135 13 128

12 850 1184 900 1407 3853 1568 548 1085 4680 274 264 998 937 78 66 58 81

62 52 77 11 17 3 9 4

© 1996 NRC Canada