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Journal of Plankton Research plankt.oxfordjournals.org J. Plankton Res. (2015) 37(1): 75– 89. First published online October 23, 2014 doi:10.1093/plankt/fbu094 Environmental filtering of crustacean zooplankton communities in fishless boreal lakes: expectations and exceptions M. U. MOHAMED ANAS1*, KENNETH A. SCOTT2 AND BJÖRN WISSEL1 1 DEPARTMENT OF BIOLOGY, UNIVERSITY OF REGINA, REGINA, SK, CANADA S4S SK, CANADA S4S 0A2 AND 2SASKATCHEWAN MINISTRY OF ENVIRONMENT, REGINA, 5W6 *CORRESPONDING AUTHOR: [email protected] and [email protected] Received May 1, 2014; accepted October 1, 2014 Corresponding editor: Beatrix E. Beisner To test the paradigm that large-bodied zooplankton species dominate in fishless lakes, we evaluated crustacean zooplankton composition of 53 fishless boreal lakes across a broad geographic scale (north-west Saskatchewan, Canada) in relation to contemporary environmental factors. Lake productivity, acid – base status and intensity of invertebrate predation were the three major environmental filters of crustacean zooplankton composition of the survey lakes, while lake morphometry and drainage basin characteristics likely had indirect effects by influencing the variations in above environmental factors. The traditionally expected dominance of large-bodied zooplankton species in fishless conditions only occurred in well-buffered shallow lakes with higher productivity and intense invertebrate predation. Daphnia pulex was dominant in more eutrophic lakes, while higher abundances of Holopedium gibberum were favored by relatively mesotrophic conditions. In exception to the traditional view, small-bodied species dominated in 57% of survey lakes as influenced by interactions of biotic and abiotic factors. Bosmina longirostris and cyclopoid copepods dominated less productive, deeper lakes with low invertebrate predation. Predominance of Leptodiaptomus minutus was supported under unfavorable environmental conditions for other species, i.e. poor buffering capacity and/or low calcium concentration. The present study demonstrates that exceptions to the generally expected species composition in fishless lakes can be caused by interactions among abiotic and biotic factors. KEYWORDS: fishless lakes; crustacean zooplankton; environmental filters; classification and ordination analysis available online at www.plankt.oxfordjournals.org # The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please email: [email protected] JOURNAL OF PLANKTON RESEARCH j VOLUME 37 I N T RO D U C T I O N j NUMBER 1 j PAGES 75 – 89 j 2015 preferentially prey on small-bodied zooplankton species, there is evidence that they may preferentially prey on large-bodied species (Wissel and Benndorf, 1998; Pagano et al., 2003). This is be particularly true when larger chaoborids (e.g. C. trivittatus) are the dominant predators (Young and Riessen, 2005). Probably, small body size is actually a competitive advantage under such conditions by reducing the encounter frequency with Chaoborus predators (Riessen and Young, 2005). It is also feasible that other anti-predator strategies, such as morphological and behavioral adaptations, are more important than the size refuge to withstand invertebrate predation in these habitats (O’Brien and Schmidt, 1979; Riessen et al., 1988; Kats and Dill, 1998). Further, several field, laboratory and model-based studies indicate contrasting competitive outcomes between large- and small-bodied zooplankton taxa under fishless conditions depending on quantity and quality of algal resources. Small-bodied species are likely favored and numerically dominant when resource abundance is limited (Lynch, 1978; Smith and Cooper, 1982; Romanovsky and Feniova, 1985; Tessier and Goulden, 1985) and resource quality (in terms of algal composition and algal stoichiometry, i.e. C : N : P ratio) is sub-optimal for large-bodied species (Gliwicz and Lampert, 1990; Steiner, 2003; Steiner and Roy, 2003; Weidman et al., 2014). Finally, abiotic factors (e.g. pH, temperature, light intensity) can also influence the zooplankton community structure of fishless aquatic habitats directly by sorting species based on differential physiological tolerances, or indirectly by interacting with biotic conditions such as primary production and invertebrate predation (Arnott and Vanni, 1993; Steiner, 2004; Weidman et al., 2014). In our previous work, we analyzed a broadscale zooplankton survey which included both fish-bearing and fishless boreal lakes in NW Saskatchewan to evaluate indicator properties of zooplankton communities in relation to potential regional environmental changes (Anas et al., 2013, 2014). Broadly, these studies indicated that large-bodied species were more dominant in fishless lakes, with top-down control determining the size structure of crustacean zooplankton communities. The goal of the present study was to focus solely on environment – species relationships in fishless lakes of this region to test if the size structure of zooplankton communities of these lakes is in fact variable and dependent on several biotic and abiotic factors. A better understanding of these relationships in fishless lakes is important for several reasons: From an ecological and conservation perspective, the importance of fishless lakes is beginning to be more recognized due to their unique biotic communities (Stoks and Mcpeek, 2003; Knapp et al., 2007a, b; Drouin et al., 2009; Schilling et al., 2009), and a considerable number of such habitats exist across the boreal Shield ecozone (Kurek The high taxonomic diversity in zooplankton communities is only partially expressed in individual freshwater habitats, and the differences in zooplankton community structures among systems is largely associated with specific environmental conditions (Havens and Hanazato, 1993; Wellborn et al., 1996; Gyllström et al., 2005). In some cases, zooplankton communities respond strongly to a single environmental factor (Sternberger and Lazorchak, 1994), such as predation (Brooks and Dodson, 1965; McQueen et al., 1986; Jeppesen et al., 1997), chemical (acids, pesticides or trace metals) stress (Havens and Hanazato, 1993; Xu, 1999; Anas et al., 2013) and nutrient enrichment (Gannon and Stemberger, 1978; Carpenter et al., 1985). Yet often, zooplankton assemblages are influenced by multiple factors, which may confound clear zooplankton–environment associations (Wellborn et al., 1996). Since the classic work by Hrbáček et al. (1961) and Brooks and Dodson (1965), numerous studies have shown that predation by planktivorous fishes and invertebrates can be a major factor structuring zooplankton community composition (Hall et al., 1976; Zaret, 1980; Carpenter, 1988). Based on this paradigm, zooplankton communities subjected to fish predation are dominated by smallbodied species as visually oriented, planktivorous fishes preferentially prey on large-bodied species (Zaret, 1980; Kerfoot and Sih, 1987). In the absences of planktivorous fishes, large-bodied zooplankton species commonly dominate, which is a result of (i) gape-limited, invertebrate planktivores preying on small-bodied species and/or (ii) competitive exclusion of small-bodied zooplankton species by superior, large-bodied species (Hall et al., 1976). This expected pattern of zooplankton communities in fishless lakes has been supported by a large body of evidence from broadscale zooplankton surveys that included both fishless and fish-bearing lakes (e.g. Patalas, 1971; Keller and Conlon, 1994; Donald et al., 2001; Knapp et al., 2007b; Anas et al., 2014). Yet, exceptions to this pattern, i.e. dominance of small-bodied species in the absence of planktivorous fish have been detected in a limited number of lake surveys (O’Brien et al., 1979; Malkin et al., 2006; Drouin et al., 2009). Hence, determinants of size structure of zooplankton communities in fishless lakes can be more complex than the commonly assumed topdown control framework. In fact, experimental studies suggest that a number of factors can potentially contribute to variations in size structure of zooplankton communities during the absence of fish. First, invertebrate predators such as Chaoborus spp. can constrain the size structure of zooplankton communities in the absence of planktivorous fish. In contrast to the well-established pattern that gape-limited predators 76 M. U. M. ANAS ET AL. j ZOOPLANKTON COMMUNITIES OF FISHLESS BOREAL LAKES et al., 2010). In addition, the lakes of this region are of particular interest, as they may be exposed to large-scale environmental stressors, notably acidifying/eutrophying emissions from the Athabasca oil sands region and climate change (Jeffries et al., 2010; Scott et al., 2010; Anas et al., 2014). The climate is subarctic with mean annual, July and January temperatures of 2.3, 16 and 2248C, respectively. Mean annual precipitation is between 450 and 530 mm, with 288 and 318 mm falling as rain between May and September. The prevailing wind is from the W-NW (Shewchuck, 1986; Acton et al., 1998). Lake selection METHOD The present study lakes are a subset from a survey of 244 headwater lakes in northwest Saskatchewan conducted from 2007 to 2009 in order to evaluate the status of lakes in relation to potential effects of atmospheric emissions from Athabasca oil sands operations. A detailed description of lake selection criteria for this survey is given in Scott et al. (2010) and Anas et al. (2014). Of the 244 survey lakes, 53 lakes were classified as “fishless” based on the presence of larvae of the phantom midge Chaoborus americanus and used for the subsequent data analyses. Chaoborus americanus is a robust indicator of fishless conditions, owing to its larger size, strong pigmentation and lack of diel vertical migration (Von Ende, 1979; Wissel et al., 2003; Sweetman and Smol, 2006; Garcia and Mittelbach, 2008). Of the 53 lakes, 16 were sampled in all 3 years, 17 were sampled twice and 20 were sampled once. Study area The sampling area intersected three ecoregions, namely, Athabasca Plain, Churchill River Upland and MidBoreal Upland (Fig. 1). Of these, Athabasca Plain and Churchill River Upland are physiographic divisions of the Boreal Shield ecozone, while the Mid-Boreal Upland is part of the Boreal Plain ecozone. The landscape changes from flat to strongly rolling, with distinctive upland areas. Localized relief can be as much as 90 m but is generally ,60 m. The elevation of the study lakes ranges from 210to 554 m a.s.l. In respect to vegetation, Jackpine (Pinus banksiana)/lichen forest with variable canopy closure predominates on well-drained sand plains and till ridges throughout the area. A more complete description of the survey domain, together with the derivation and summary of catchment-specific environmental factors is given in Scott et al. (2010). Fig. 1. Sampling domain and locations of the 53 fishless survey lakes (based on presence of C. americanus) in north-west Saskatchewan, showing their distribution across three ecoregions [AP, Athabasca Plain; CRU, Churchill River Upland (AP & CRU ¼ Boreal Shield); MBU, Mid-Boreal Upland (Boreal Plain); AOSR, Athabasca Oil Sands Region—portion of approximate active mining area is shown]. 77 JOURNAL OF PLANKTON RESEARCH j VOLUME 37 Field survey j NUMBER 1 j PAGES 75 – 89 j 2015 We performed hierarchal cluster analysis to identify clusters of lakes based on species composition. First, we preformed hierarchal cluster analysis on species composition using four different methods, i.e. single linkage clustering, complete linkage agglomerative clustering, average agglomerative clustering (unweighted pair-group method using arithmetic averages) and Ward’s minimum variance clustering and subsequently evaluated for the best method/model by calculating cophenetic correlations for distance matrices produced by each method. We selected the outcome of Ward’s minimum variance clustering as the best clustering model as cophenetic correlation was highest for this particular model. Finally, in order to determine the optimum number of clusters for objective interpretation, both average Silhouette widths and Mantel correlation coefficients were calculated for each clustering level from 1 (i.e. all lakes belong to a single cluster) to 53 (i.e. each lake is a separate cluster) (Borcard et al., 2011). To quantify statistically significant relationships between environmental factors and crustacean zooplankton species abundances, redundancy analysis (RDA) was conducted. RDA is a direct gradient analysis technique that performs well with linear species–environmental relationships (Ter Braak and Prentice, 2004). Several lake parameters that could be important in structuring zooplankton communities were incorporated into this analysis as predictors, in2 cluding [TP], [TN], [chlorophyll a], [NHþ 4 -N], [NO3 -N], 22 [DOC], color, pH, [Ca],[ SO4 ], [ANC], C. americanus density, maximum depth, surface area, drainage basin area, % forest area and % bog area in catchment. Prior to the subsequent analyses, all these variables except pH were either log10 (x þ 0.01) or log10 transformed to improve homoscedasticity and normality while average species abundances were Hellinger transformed, which preserves the asymmetrical distance among sites, allowing the use of a Euclidean-based ordination methods such as RDA (Legendre and Gallagher, 2001). Species occurring in ,5% of survey lakes were removed from the ordination analysis (Leps and Smilauer, 2003). After testing for the significance of a global model with the complete set of predictors (P , 0.05), significant predictors were forwardselected by Monte Carlo permutation tests at P , 0.05 with 999 iterations. As forward-selection procedure is too liberal, we added a double stopping criterion (Blanchet et al., 2008) to select the most parsimonious set of predictors from each explanatory variable set. Further, we evaluated for any collinearity among selected predictors (variance inflation factor .3). Subsequently, significance of individual canonical axes of the selected model (with only significant predictors) was tested using permutation tests (1000) and only the significant (P , 0.05) canonical axes were interpreted (Borcard et al., 2011). Selected lakes were sampled by helicopter annually from 2007 to 2009 in late September during the turnover period. After locating the helicopter in the approximate center of the lake, a water sample was collected at 1 m depth for physiochemical factors (generally representing integrated vertical state based on temperature), and zooplankton was sampled by vertical net tows (near bottom to surface) using a conical plankton net (mesh size ¼ 68 mm, diameter ¼ 0.3 m) that was equipped with a flow meter. Laboratory analysis Zooplankton of each lake was enumerated and identified to species except cyclopoid copepods. Whole samples were used for species identification while samples were split for enumeration when necessary. Standard references were used for taxonomic identifications (Hebert, 1995; Sandercock and Scudder, 1996; Aliberti et al., 2009). Subsequently zooplankton densities were calculated by using filtered volumes (based on impeller rotations and diameter of plankton net). The analytical procedures for environmental (chemical) factors are described in Scott et al. (2010). Data analysis We used averages of all environmental factors and species abundances over the 3 survey years for subsequent data analyses as there were no major variations in either environmental factors or species composition of the lakes among survey years (Anas et al., 2014). We performed a principal component analysis (PCA) on standardized (scaled to unit variance) water chemistry variables, i.e. total nitrogen (TN), total phosphorus (TP), chlorophyll a, dissolved organic carbon (DOC), nitrate þ 2– (NO2 3 -N), ammonium (NH4 -N), sulfate (SO4 ), pH, calcium (Ca), charge-balanced acid-neutralizing capacity (ANC) and color. PCA compresses the variance in the data matrix by identifying the correlation structure within the data matrix. In addition, we included two morphometric variables, i.e. maximum water depth and surface area and three catchment variables, i.e. drainage basin area, % forest area in catchment and % bog area in catchment, and C. americanus density as supplementary variables. These supplementary variables had no influence on the principal components of the analysis, yet showed how these variables were correlated to water chemistry. Subsequently, the broken-stick model was used to determine the number of meaningful principal components that represented interesting variation of the data (Borcard et al., 2011). 78 M. U. M. ANAS ET AL. j ZOOPLANKTON COMMUNITIES OF FISHLESS BOREAL LAKES Complementary to RDA, we tested how individual environmental factors varied among the species composition-based lake clusters. The aim of this analysis was to further emphasize the environment – species relationships established using RDA by providing a more simplified and structured view of these relationships. Kruskal – Wallis tests determined if median environmental factors were significantly different among lake clusters based on species composition followed by multiple comparisons of median values (Conover, 1999). The a level (0.05) for multiple comparisons was adjusted using Holm’s correction (Holm, 1979). In addition, we tested if species diversity varied among the lake clusters based on variable dominance by different taxa. First, we calculated the species richness and Shannon’s diversity index for each lake. Subsequently, Kruskal–Wallis tests were performed to determine if these diversity indices were significantly different among lake clusters, followed by multiple comparisons of median values (Conover, 1999). The a level (0.05) for multiple comparisons was adjusted using Holm’s correction (Holm, 1979). Finally, a spatial analysis was performed to identify any spatial structures in species composition caused either by dispersal-related processes or by spatially structured environmental controls. Spatial structuring of communities independent of the influence of environmental factors represents a coarse measure of dispersal processes (Cottenie et al., 2003; Beisner et al., 2006; Gray et al., 2012). First, presence of any linear spatial trends in species data was tested by performing a trend-surface analysis (Borcard and Legendre, 2002). As no significant broadscale linear trends were detected (P . 0.05), subsequently an eigenvectorbased spatial modeling approach was used to identify more complex and non-linear spatial structures (Borcard and Legendre, 2002; Dray et al., 2006). For this, a set of spatial variables (i.e. eigenvectors) was generated using a distancebased Moran’s Eigenvector Mapping (dbMEM) method (Dray et al., 2006) based on X–Y coordinates of each survey lake. This method produces a spectral decomposition of spatial relationships among sampling sites based on the diagonalization of a spatial weighting matrix. The generated spatial variables can be directly linked to the spatial patterns of species and environmental factors (Bellier et al., 2007; Borcard et al., 2011). A truncation distance of 64 km was used (i.e. shortest distance for all survey lakes to remain connected by links smaller than or equal to this distance). This yielded 15 positive dbMEM variables. We used a forward-selection criterion in a RDA to select the minimum subset of significant variables from them, by following the same procedure described above for RDA between environmental factors and species composition. Finally, lake clusters based on species composition were plotted on a map of the study area to provide a visual presentation of existing spatial structures in species composition. All statistical analysis were performed in R version 2.15.3(R Core Team, 2012) using the following packages; (i) “FactoMineR” (Husson et al., 2013) for PCA, (ii) “vegan” (Oksanen et al., 2012) for RDA, associated permutation tests, (iii) “packfor” (Dray et al., 2011) for the forward selection with double stopping criterion, (iv) ‘cluster’ (Maechler et al., 2012) for cluster analysis, (v) “agricolae” (de Mendiburu, 2014) for Kruskal–Wallis test and multiple comparisons of median values and (vi) “PCNM” (Legendre et al., 2012) for generating dbMEM variables. R E S U LT S Limnological characteristics Limnological characteristics varied considerably among the study lakes (Table I). Lake morphometry ranged from shallow lakes with variable size to small and deep “kettle”-type lakes. Trophic state of study lakes ranged from oligotrophic (5th percentile [TP], [TN] and Table I: Limnological characteristics of the 53 survey lakes located in north-west Saskatchewan Variable Mean Median 5th percentile 95th percentile Maximum depth (m) Surface area (ha) Drainage basin area (ha) TN (mg L21) TP (mg L21) 21 ) NHþ 4 -N (mg L 21 ) NO2 3 -N (mg L Chlorophyll a (mg L21) 21 DOC (mg L ) Color (mg L21 Pt) Ca (mg L21) ANC (meq L21) pH 21 ) SO22 4 (mg L 5.89 75.12 670.00 585.54 19.37 52.23 13.38 6.42 8.84 47.58 1.70 179.01 6.77 0.80 3.07 47.48 401.00 514.67 14.00 23.00 2.33 5.07 7.75 24.95 1.46 154.97 6.88 0.73 1.32 8.64 56.20 259.10 4.30 12.60 1.00 1.98 3.76 6.81 0.59 53.48 5.90 0.32 18.46 218.15 2311.20 1328.80 51.40 135.40 84.60 15.39 14.90 127.43 3.55 393.83 7.31 1.59 79 JOURNAL OF PLANKTON RESEARCH j VOLUME 37 [chlorophyll a] 4.3, 259.1 and 1.98mg L21, respectively) to relatively eutrophic conditions (95th percentile [TP], [TN] and [chlorophyll a] 51.4, 1328.8 and 15.39 mg L21, respectively) (Forsberg and Riding, 1980; Carlson and Simpson, 1996). The contribution of inorganic nitrogen species to TN was generally low (median 21 2 , respective[NHþ 4 -N] and [NO3 -N] 23 and 2.33 mg L ly) indicating most of the TN of these lakes was organic. In general, the study lakes were slightly colored (median color 24.95 mg L21 Pt). Accordingly, [DOC] were high (median [DOC] 7.75 mg L21) relative to those recorded for boreal Shield lakes of eastern Canada (Jeffries et al., 2005). For most lakes, pH was in the circum-neutral range and only 7% of the lakes had a pH below 6. Yet, the wide range in ANC indicated that acid sensitivity of the lakes varied from highly sensitive (,50 meq L21) to insensitive (.200 meq L21) (Sullivan, 2002), reflecting the underlying geological acid sensitivity gradient (Scott et al., 2010). Variation in [Ca] (which was the major base cation) was closely related to that of ANC. Based on the broken-stick model, the first two principal components of the PCA (which collectively explained 54% of the variation) were selected to represent the variation in water chemistry (Fig. 2). The first principal component (PC-1) corresponded to nutrient status (TN, TP, 2 NHþ 4 -N and NO3 -N) and acid – base status (ANC and Ca) of the study lakes. Meanwhile, the density of C. americanus and surface area of lakes [supplementary variables (Supplementary data)] were positively correlated to j NUMBER 1 j PAGES 75 – 89 j 2015 higher nutrient loadings along PC-1. On the other hand, PC-2 mostly represented the variation in DOC and correlated factors. The positive correlation of color with DOC along PC-2 indicated the greater importance of allocthonous DOC in these lakes (Wetzel, 1983). This was further emphasized by the positive correlation of % peatland in the catchment (supplementary variables) to PC-2. In the meantime, pH was negatively associated with PC-2 mostly representing the organic acidity (Kahl et al., 1989), while negative association of maximum depth (supplementary variables) indicated higher [DOC] in shallow lakes. The positive relationship of [chlorophyll a] to PC-2, but not PC-1 (nutrient status) was somewhat unexpected. This relationship may reflect autochthonous DOC production within lakes via primary production (Wetzel, 2001), yet autochthonous DOC is only of a minor importance in these systems given the greater importance of colored DOC of allochthonous origin. In addition, two supplementary variables (Supplementary data), i.e. drainage basin area and % forest area in catchment were not related to either PC. Variations in species composition Hierarchal cluster analysis identified five relatively different clusters based on the species composition. Five clusters were the optimum number for interpretation as both average Silhouette width and Mantel correlation coefficient were highest at this particular level (Supplementary data, Fig. S1). Individual clusters were mostly separated based on a single dominant species/taxon in each cluster (Fig. 3). Clusters 1 and 2 were each dominated by one large-bodied species, i.e. Daphnia pulex and Holopedium gibberum, respectively. In contrast, Clusters 3, 4 and 5 were each dominated by one small-bodied species/taxa, i.e. Bosmina longirostris, cyclopoid spp., and Leptodiaptomus minutus, respectively. Environmental predictors of species composition RDA between species assemblages and environmental factors identified significant (P , 0.05) environment – species relationships along the first three axes, which collectively explained 30% of the total variation in species composition (Fig. 4). Kruskal – Wallis tests and subsequent multiple comparisons detected significant differences for several individual environmental factors among the five clusters (based on species compositions), further emphasizing the strong environment– species relationships identified by RDA (Supplementary data, Fig. S2). Only the relatively stronger environment – species relationships are described below. Fig. 2. Principal components analysis (PCA) on limnological variables of 53 fishless lakes. Variables indicated by dash-lined arrows and italicized labels were supplementary variables of the analysis. 80 M. U. M. ANAS ET AL. j ZOOPLANKTON COMMUNITIES OF FISHLESS BOREAL LAKES Fig. 3. Heat map and dendrogram of hierarchical cluster analysis based on relative abundances of crustacean zooplankton taxa/species of 53 fishless lakes of north-west Saskatchewan; Ward’s minimum variance clustering method was used for the analysis. Color intensities of the heat map are proportional to relative abundances of species/taxa. Daphnia pulex (Cluster 1) dominated more productive lakes (Fig. 4a and b; along RDA-2 and Supplementary data, Fig. S2c, d and e) with relatively higher concentrations of inorganic nitrogen species, i.e. NO2 3 -N (Fig. 4c and d; along RDA-3 and Supplementary data, Fig. S2a) and NHþ 4 -N (Supplementary data, Fig. S2b). Furthermore, these lakes were well buffered (Fig. 4a and b; along RDA-1 and Supplementary data, Fig. S2f), somewhat shallow (Fig. 4a and b; along RDA-2 and Supplementary data, Fig. S2l) and had relatively small drainage basins (Fig. 4a and b; along RDA-2 and Supplementary data, Fig. S2m). In addition, these lakes also had relatively higher densities of C. americanus (Fig. 4a and b; along RDA-1 and Supplementary data, Fig. S2i). However, while there were significant variations in C. americanus density per unit volume among lake clusters based on species composition, such variations were not evident for C. americanus density per unit area (Supplementary data, Fig. S2j). Rationale for this discrepancy is discussed below. Holopedium gibberum-dominated lakes (Cluster 2) were somewhat similar to D. pulex-dominated lakes in terms of productivity (Supplementary data, Fig. S2c, d and e), lake morphometry (Fig. 4c and d; along RDA-1 and Supplementary data, Fig. S2k and l), acid sensitivity (Fig. 4c and d; along RDA-1 and Supplementary data, Fig. S2f ) and C. americanus density (Fig. 4c and d; along RDA-1 and Supplementary data, Fig. S2i). Yet, these lakes were different from D. pulex-dominated lakes mostly based on relatively lower concentrations of inorganic nitrogen species, i.e. NO2 3 -N (Fig. 4c and d; along RDA-3 and Supplementary data, Fig. S2a) and NHþ 4 -N (Supplementary data, Fig. S2b). Lakes dominated by B. longirostris (Cluster 3) and cyclopoid spp. (Cluster 4) were relatively deep kettle-type lakes (Fig. 4a and b; along RDA-2, Fig. 4c and d; along RDA-3 and Supplementary data, Fig. S2l). In addition, these lakes were more oligotrophic compared with lakes in Clusters 1 and 2 (Fig. 4a and b; along RDA-2 and 81 JOURNAL OF PLANKTON RESEARCH j VOLUME 37 j NUMBER 1 j PAGES 75 – 89 j 2015 Fig. 4. Crustacean zooplankton–environment relationship for 53 fishless lakes as identified by redundancy analysis (RDA). Average species abundances were Hellinger transformed and environmental factors except pH were log10-transformed. Only significant (P , 0.05) and non-collinear environmental factors (variance inflation factor ,3) were retained in the analysis. (a) Biplot between environmental factors and species (Axis 1 vs. Axis 2); (b) biplot between environmental factors and sites (Axis 1 vs. Axis 2); (c) biplot between environmental factors and species (Axis 1 vs. Axis 3); (d) biplot between environmental factors and sites (Axis 1 vs. Axis 3); site symbols of (b) and (d) refer to lake clusters based on species composition. Axes 1, 2 and 3 explained 15.9, 8.8 and 5.3% of total variation in species composition, respectively. Supplementary data, Fig. S2c, d and e), and had significantly lower C. americanus densities (Fig. 4a and b; along RDA-1, Fig. 4c and d; along RDA-3 and Supplementary data, Fig. S2i). Although not revealed by RDA as a significant relationship, [DOC] and consequently color were significantly lower in B. longirostris-dominant lakes relative to those of cyclopoid-dominant lakes (Supplementary data, Fig. S2n and o). Highly acid-sensitive survey lakes (Fig. 4a and b; along RDA-1 and Supplementary data, Fig. S2f ) with relatively lower pH values (Supplementary data, Fig. S2g) were dominated by L. minutus (Cluster 5). In the meantime, these lakes also had the lowest [Ca] relative to other lake clusters (Supplementary data, Fig. S2h). Further, these lakes were relatively small (Fig. 4a and b; along RDA-2 and Supplementary data, Fig. S2k), shallow (Fig. 4c and 82 M. U. M. ANAS ET AL. j ZOOPLANKTON COMMUNITIES OF FISHLESS BOREAL LAKES Fig. 5. Comparison of (a) species richness (b) Shannon’s diversity index of 53 fishless lakes among lake clusters based on species composition. Median values of the clusters indicated by same letters are not significantly different according to Kruskal–Wallis test followed by multiple comparisons (adj. P , 0.05). (P , 0.05) linear or non-linear spatial structures in species composition. This was further emphasized by the nonexistence of any spatial patterns in the distribution of lake clusters based on species composition in the study area (Fig. 6). DISCUSSION This study identified diverse patterns in crustacean zooplankton community composition in fishless lakes, which were significantly related to variations in both abiotic and biotic factors. In contrast to the existing paradigm, the expected dominance of large-bodied species, such as D. pulex or H. gibberum occurred in only 43% of the study lakes, while small-bodied species including B. longirostris, cyclopoids and L. minutus were dominant in 57% of the lakes. The observed variation in species composition among lakes was due to interactive effects of lake productivity, acid sensitivity, lake morphometry, catchment characteristics and invertebrate predation. Fig. 6. Spatial distribution of the lake clusters based on species composition in the sampling domain. d; along RDA-3 and Supplementary data, Fig. S2l) and had smaller drainage basins (Fig. 4a and b; RDA-axis 2 and Supplementary data, Fig. S2m). In addition, species diversity was lowest in L. minutusdominated lakes (Cluster 5) relative to all other lake clusters. Although species richness did not vary much among clusters (Fig. 5a), the Shannon’s diversity index was significantly lower in L. minutus-dominated lakes (Fig. 5b), which indicates greater dominance by a single species (i.e. L. minutus) in lakes of cluster 5. Dominance of large-bodied species Large-bodied zooplankton species were dominant in 43% of lakes representing the generally expected pattern for fishless lakes (Brooks and Dodson, 1965; Hall et al., 1976). The proposed mechanisms responsible for the reduced abundance of small-bodied species in fishless lakes are still disputed. One argument is that smallbodied species are competitively suppressed by superior large-bodied species monopolizing food resources (Brooks and Dodson, 1965; Hall et al., 1976; DeMott and Kerfoot, 1982; Vanni, 1986). Alternatively, several studies suggest that selective predation by invertebrates alone can account for reduced abundances of small-bodied species, while resource reduction by large-bodied species Spatial structures in species composition Trend-surface analysis and subsequent eigenvector-based spatial modeling did not reveal any statistically significant 83 JOURNAL OF PLANKTON RESEARCH j VOLUME 37 j NUMBER 1 j PAGES 75 – 89 j 2015 densities (Von Ende and Dempsey, 1981). On the other hand, successful colonization of large-bodied species may be hampered by low productivity of these lakes, favoring small-bodied species at reduced competition interactions (Lynch, 1978; Romanovsky and Feniova, 1985; Vanni, 1986). For instance, it has been suggested that D. pulex can become more vulnerable to predation by C. americanus with decline in productivity, as reduced growth rates may not allow them to achieve a size refuge from Chaoborus predation (Riessen and Young, 2005). The distinction between B. longirostris- versus cyclopoid-dominated lakes was poorly explained by environmental factors. Although cyclopoiddominated lakes had higher [DOC] compared with B. longirostris-dominated lakes, any underlying mechanism for this difference is uncertain. Potentially, predation by cyclopoids on B. longirostris may reduce the relative abundances of B. longirostris (Ha and Hanazato, 2009). Dominance of L. minutus (Cluster 5) is probably the result of suppression of other species due to unfavorable environmental conditions. Relatively low ANC/pH conditions of these lakes were likely unfavorable for acidsensitive zooplankton species while L. minutus, a highly acid-tolerant generalist, can dominate zooplankton communities under acid-stressed conditions (Brett, 1989; Marmorek and Korman, 1993; Havens and Hanazato, 1993). It should be noted however that dominance of L. minutus has been mostly recorded in culturally acidified systems elsewhere, while low ANC/pH of the current set of survey lakes were largely due to low concentrations of base cations. Combined carbonate-poor geology and short hydraulic retention times of these small headwater lakes are likely contributing to the loss of ANC in these systems (Gubala and Driscoll, 1991; Sullivan, 2002). It is also likely that low ambient [Ca] is acting as a barrier for successful colonization of zooplankton species with high physiological demand for Ca such as daphnids (Cairns and Yan, 2009). Further, large-bodied species like daphnids are likely more vulnerable to Chaoborus predation under such unfavorable environmental conditions (Pagano et al., 2003; Riessen et al., 2012). Consequently, the small-bodied generalist L. minutus may be favored in these lakes due to release from the competition from superior species (Brett, 1989). Declined overall zooplankton species diversity is hence a likely result of this predominance by a single tolerant species under unfavorable conditions (Brett, 1989; Marmorek and Korman, 1993; Stenson et al., 1993). is not sufficient to cause the scarcity of small-bodied species (Dodson, 1974; Hall et al., 1976; Zaret, 1980). The scarcity of small-bodied species in many lakes of our survey may invoke either or both of these two alternatives. According to the predation hypothesis, relatively higher C. americanus densities would exert a greater selective predation pressure on small-bodied species in these lakes. If competition is crucial, higher population densities of largebodied zooplankton supported by the relatively eutrophic conditions would competitively suppress small-bodied species by altering the resource base (Romanovsky and Feniova, 1985; Vanni, 1986; Kerfoot et al., 1988). However, the latter option should be less likely for H. gibberumdominated lakes of our survey (discussed below). Dominance of either D. pulex or H. gibberum is likely determined by differences in lake productivity. Typically higher densities of D. pulex are supported by more eutrophic conditions (Romanovsky and Feniova, 1985; Vanni, 1986; Steiner and Roy, 2003; Riessen and Young, 2005), while H. gibberum is largely confined to oligo to mesotrophic lakes (Hamilton, 1958; Pejler, 1965; Hessen et al., 1995). Although D. pulex- and H. gibberum-dominated lakes had comparable [TN] and [TP], it is likely that D. pulexdominated lakes had greater contributions of bioavailable (inorganic) forms of nitrogen as indicated by relatively 2 higher [NHþ 4 -N] and [NO3 -N] (discussed below). These superior food environments may stimulate fast growth rates of D. pulex, allowing them to achieve a size refuge from C. americanus predation (Allan, 1973; Riessen and Young, 2005) or enhance their reproduction leading to increased survivorship from invertebrate predation (Neill and Peacock, 1980). Meanwhile, H. gibberum may be competitively suppressed by increased densities of D. pulex under such conditions (Hessen et al., 1995). On the other hand, D. pulex can be more vulnerable to C. americanus predation in poor food conditions (Allan, 1973; Riessen and Young, 2005). In contrast, H. gibberum is generally highly resistant to Chaoborus predation due to protection provided by its gelatinous capsule and thus likely to thrive in these lakes due to reduced competition from D. pulex (Allan, 1973; Vinyard and Menger, 1980). However, given the close resemblance of these lakes to D. pulex-dominated lakes in terms of most limnological characteristics, it is likely that these lakes would shift to D. pulex dominance upon equivalent nutrient enrichment. Dominance of small-bodied species Predominance of small-bodied B. longirostris and cyclopoids in relatively deep lakes may be attributed to low predation pressure from C. americanus and reduced competition from large-bodied species. The predation pressure from C. americanus is likely low in these lakes owing to their lower Nutrient and productivity dynamics of the survey lakes It is likely that the variation in productivity between large-bodied species (D. pulex and H. gibberum)-dominated 84 M. U. M. ANAS ET AL. j ZOOPLANKTON COMMUNITIES OF FISHLESS BOREAL LAKES lakes and small-bodied species-dominated lakes (B. longirostris and cyclopoids) is related to the differences in lake morphometry. Greater productivity in the former group should have been supported by the uniform internal nutrient distribution throughout the growing season in these shallow polymictic lakes (Wetzel, 2001). On the other hand, poor productivity of the latter group may be associated with the resistance to nutrient mixing due to thermal stratification of these deeper lakes (Richardson, 1975; Wetzel, 2001; Stefanidis and Papastergiadou, 2012) and/or smaller nutrient pulses relative to the volume of water (lower perimeter to volume ratio) (Leibold and Norberg, 2004). Despite comparable [TN] in D. pulex and H. gibberumdominated lakes, it is likely that D. pulex-dominated lakes were relatively more productive as reflected by their relatively higher dissolved inorganic nitrogen (DIN) concentrations. Several indications suggest that relatively higher [DIN] can be symptomatic of more productive conditions (Park and Marshall, 2000; Quirós, 2003; Bergström, 2010). On the other hand, low absolute [DIN] 2 ([NHþ 4 -N] þ [NO3 ]) can be indicative of either high nutrient turnover under high demand, even though nutrient supply is high or limited nutrient supply and hence, low system productivity (Dodds, 2003). The former is likely in the case of D. pulex-dominated lakes of the present study, given that greater abundances of D. pulex are typically associated with more eutrophic conditions (Romanovsky and Feniova, 1985; Vanni, 1986; Steiner and Roy, 2003; Riessen and Young, 2005). Because many of the factors driving the variability in terrestrial export may operate more strongly in small drainage basins, greater terrestrial export of inorganic nitrogen (mostly NO2 3 -N) may have lead to higher [DIN] in these lakes (Caraco et al., 2003; Inamdar and Mitchell, 2006). On the other hand, our assumption is further supported by the typical association of H. gibberum with relatively oligo to mesotrophic conditions (Hamilton, 1958; Pejler, 1965; Hessen et al., 1995). Variations in lake productivity among survey lakes (discussed above) were not reflected by [chlorophyll a] for several reasons. Primary productivity of lakes enhances in response to increase in nutrients, which will in turn enhance the biomass of grazers. Subsequently, this increased grazer density can exert a reverse cascading effect on phytoplankton (Vanni, 1987; Carpenter et al., 2001). Another possibility is that the increase in nutrients may be causing a shift in food quality (in terms of alterations in phytoplankton composition) rather than a change in food quantity (Vanni, 1987; Hessen et al., 2009). Lastly, the lakes were sampled during fall circulation, during which algal biomass is negatively influenced by the light limitation and declining water temperatures. Therefore, general measures of phytoplankton such as [chlorophyll a] may fail to reflect the effects of nutrient variations on primary production. Variations in Chaoborus americanus densities There are two alternative explanations for the differences in C. americanus densities among lakes. Similar to the present study, several others have shown that relatively higher C. americanus densities are supported in highly productive freshwater habitats (Yan et al., 1982; Wissel et al., 2003; Riessen and Young, 2005; Labaj et al., 2013). In fact, this can be a bottom-up effect, i.e. increased predator survivorship due to enhanced prey (grazer) abundance stimulated by greater productivity of these lakes (Neill and Peacock, 1980). On the other hand, although there were significant variations in C. americanus density per unit volume among lake clusters based on species composition, such variations were not evident for C. americanus density per unit area. This suggests that C. americanus might have equally used all lakes during egg deposition. Therefore, the total number of C. americanus larvae in a lake should only depend on its surface area. Consequently, larval density per unit volume should be high in relatively shallow lakes (given that surface areas of most lakes are more or less similar), as larvae are more concentrated in a smaller volume relative to that of deeper lakes, while exerting a greater predation pressure on zooplankton. Spatial structuring of zooplankton communities The non-existence of any spatial structures in species composition of fishless lakes across the region emphasizes that variations in species composition among fishless lakes was not a result of dispersal limitation, but rather due to localized variations in environmental controls among study lakes. This agrees with the findings of our previous comprehensive spatial analysis which included both fish-bearing and fishless lakes of this region, where we revealed that dispersal of crustacean zooplankton was not strongly limiting across the geographic region and spatial structures of zooplankton distribution were induced by the spatial patterns in environmental controls (Anas et al., 2014). Distribution of fishless lakes in the boreal shield ecozone The present study provides strong evidence that naturally occurring fishless lakes represent a sizeable portion of Canadian boreal Shield lakes. Based on the occurrences of C. americanus, 22% (53 of 244) of the survey lakes were 85 JOURNAL OF PLANKTON RESEARCH j VOLUME 37 j NUMBER 1 j PAGES 75 – 89 j 2015 REFERENCES classified as fishless. This is consistent with an estimate of fishless lakes for eastern parts of the boreal Shield (20%) using a similar approach (Kurek et al., 2010). 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