Temporal and spatial concordance in community composition of phytoplankton, zooplankton,...

Temporal and spatial concordance in communitycomposition of phytoplankton, zooplankton,macroinvertebrate, crayfish, and fish on thePrecambrian Shield1

Michelle F. Bowman, Ron Ingram, Ron A. Reid, Keith M. Somers, Norman D. Yan,Andrew M. Paterson, George E. Morgan, and John M. Gunn

Abstract: Concordance among communities dictates how broadly we can extrapolate results derived from a set of eco-systems. We used Mantel tests to evaluate the degree of concordance in community composition among phytoplankton,zooplankton, benthic macroinvertebrate, crayfish, and fish in eight lakes near Dorset, Ontario, Canada. Spatial concor-dance across lakes at the decadal scale was stronger (mean Mantel r = 0.51, standard deviation (SD) = 0.20) than bothintra-annual agreement (mean Mantel r = 0.38, SD = 0.20) and temporal concordance within a single lake (mean Man-tel r = 0.20, SD = 0.15). The degree of temporal concordance was not related to climatic fluctuations, with the excep-tion of increased spatial synchrony in phytoplankton communities in 1997. Strength of overall spatial concordance wasmost commonly related to variability in chemical attributes of the study lakes. An understanding of the determinants ofconcordance among taxon groups is germane to the advancement of ecology in general, as well as biodiversity conser-vation strategies, ecosystem monitoring, and impact diagnosis.

Résumé : La concordance entre les communautés détermine dans quelle mesure on peut extrapoler les résultats obte-nus dans un ensemble d’écosystèmes. Nous utilisons des tests de Mantel pour évaluer l’importance de la concordancedans la composition de peuplements de phytoplancton, de zooplancton, de macroinvertébrés benthiques, d’écrevisses etde poissons dans huit lacs près de Dorset, Ontario, Canada. La concordance spatiale entre les lacs à l’échelle desdécennies est plus forte (r moyen de Mantel = 0,51; écart type (SD) = 0,20) qu’à la fois l’accord entre les années(r moyen de Mantel = 0,38; SD = 0,20) et la concordance temporelle au sein d’un même lac (r moyen de Mantel =0,20; SD = 0,15). L’importance de la concordance temporelle n’est pas reliée aux fluctuations climatiques, àl’exception d’un synchronisme spatial accru dans les communautés de phytoplancton en 1997. La force de la concor-dance spatiale globale est le plus souvent reliée à la variabilité des caractéristiques chimiques des lacs étudiés. Lacompréhension des facteurs déterminants de la concordance entre les groupes de taxons est d’intérêt pour le progrèsde l’écologie en général, de même que pour les stratégies de conservation de la biodiversité, pour la surveillance desécosystèmes et pour l’identification des impacts.

[Traduit par la Rédaction] Bowman et al. 932

Introduction

Concordance between taxonomic groups (e.g., planktonand fish) refers to agreement in the relative similarity ofcommunity attributes (e.g., richness, composition) over timeor space. For example, if the taxonomic richness of bothplankton and fish were relatively low at time a, high at time

b, and intermediate at time c, the responses of the twogroups would be considered temporally concordant. Concor-dant patterns in species distributions among taxon groupscan result from common preferences and adaptations, bioticinteractions, common environmental determinants, covarianceof different environmental determinants, or historical factors(Heino 2002). Although concordance of species richness

Can. J. Fish. Aquat. Sci. 65: 919–932 (2008) doi:10.1139/F08-034 © 2008 NRC Canada

919

Received 2 June 2007. Accepted 29 January 2008. Published on the NRC Research Press Web site at cjfas.nrc.ca on 17 April 2008.J20033

M.F. Bowman.2,3 Department of Zoology, University of Toronto, 25 Harbord Street, Toronto, ON M5S 3G5, Canada.R. Ingram, R.A. Reid, K.M. Somers, and A.M. Paterson. Dorset Environmental Science Centre, Ontario Ministry of theEnvironment, 1026 Bellwood Acres Road, Dorset, ON P0A 1E0, Canada.N.D. Yan. Department of Biology, York University, 4700 Keele Street, Toronto, ON M3J 1P3, Canada.G.E. Morgan and J.M. Gunn. Cooperative Freshwater Ecology Unit, Department of Biology, Laurentian University, 1222 RamseyLake Road, Sudbury, ON P3E 2C6, Canada.

1This article is part of the series “Transforming understanding of factors that regulate aquatic ecosystems on the southern CanadianShield”.

2Corresponding author (e-mail: [email protected]).3Present address: Toxicology Centre, University of Saskatchewan, 44 Campus Drive, Saskatoon, SK S7N 5B3, Canada.

among various freshwater aquatic groups can be variableand unpredictable (e.g., Allen et al. 1999a; Heino et al.2005; but see Heino 2002), strong concordance in commu-nity composition among groups has been documented (e.g.,Allen et al. 1999b; Paavola et al. 2006). The typical ap-proach in community ecology of focusing on one taxonomicgroup limits the scope of interpretation and the generality ofecological understanding and ignores the fact that differentgroups can interactively affect ecosystem processes (Magnu-son et al. 1990; Allen et al. 1999a, 1999b).

It is important to consider the spatial scales at which vari-ous communities respond to natural and anthropogenic gra-dients when evaluating concordance. Paavola et al. (2003,2006) found that concordance in community structureamong stream bryophyte, invertebrate, and fish communitieswas strong across multiple drainage systems and ecoregionsbut variable and generally weak in individual drainages andecoregions. In contrast, Heino (2002) suggested that strongmechanistic links between interacting aquatic groups (e.g.,macrophytes, invertebrates, and fish) can strengthen concor-dance among groups at a local scale. Similarly, Jackson andHarvey (1993) suggested that strong biotic interactions werelikely the explanation for strong concordance between inver-tebrate and fish communities in lakes of the Dorset (Ontario,Canada) area, even though the community composition ofeach group was associated with a different set of environ-mental characteristics.

Concordance among aquatic groups in relation to climaticgradients has also been considered, and as with spatial scale,it is not clear how climatic changes will affect concordance.Rusak et al. (2008) found that climatic fluctuations can in-crease the spatial synchrony of certain, common zooplank-ton species in Dorset-area lakes. Similarly, Bowman et al.(2006) documented strong concordance in Dorset-areamacroinvertebrate communities in streams following droughtevents in 1998 and 2001. Conversely, Lento et al. (2008)showed that littoral macroinvertebrate communities inDorset-area lakes did not respond coherently to these clima-tic fluctuations. Although species distributions are generallyunder strong climatic control, all groups of freshwater or-ganisms are unlikely to show concordant shifts in responseto changes in climate (Heino 2002).

Variation in the degree of concordance along spatial, cli-matic, and anthropogenic stressor gradients may be relatedto factors associated with the relative body size of organismsamong groups (e.g., physiological, morphological, and be-havioural adaptations; life span; dispersal capabilities). It isgenerally assumed that smaller-bodied organisms such asphytoplankton and small zooplankton will be more sensitiveto shorter-term climatic fluctuations and more localizedstressors, whereas longer-term climatic variability and large-scale stressors would likely have a greater impact on larger-bodied taxa such as fish (Allen et al. 1999b; Hering et al.2006a; Johnson et al. 2007). Consistent with this assump-tion, Allen et al. (1999b) found that larger-bodied assem-blages (benthos, fish, and riparian birds) had strongerassociations with land use than smaller-bodied assemblages(phytoplankton and zooplankton). However, Passy et al.(2004) found that land use became less influential acrossstream diatom, macroinvertebrate, and fish assemblages, andJohnson et al. (2007) found that benthic diatoms, macro-

phytes, invertebrates, and fish all responded similarly atdifferent levels of spatial scale.

We examined concordance in community compositionamong five trophic levels from eight lakes over one decade toimprove our understanding of how spatial scale, climatic fluc-tuations, and size-related factors affect concordance amonggroups. The study lakes represent snapshots along characteris-tic natural and human-impacted gradients in the lake-rich re-gion of central Ontario, Canada. Based on previous studiesconducted in this region (Jackson and Harvey 1993; Bowmanet al. 2006), our predictions were that at this relatively smallgeographic scale, (i) there would be strong concordanceamong taxonomic groups, (ii) groups made up of smaller-bodied organisms (i.e., phytoplankton, zooplankton, and ben-thic macroinvertebrates) would respond to short-term climaticfluctuations, and (iii) the degree of concordance amonggroups would be unrelated to relative body size.

Materials and methods

The eight intensively studied Dorset-area lakes (i.e., the“A” lakes: Blue Chalk (BC), Red Chalk Main (RCM), Chub(CB), Crosson (CN), Heney (HY), Plastic (PC), Dickie(DE), and Harp (HP)) evaluated in this study vary somewhatwith respect to size, type of thermal stratification, geo-graphic proximity, and amount of wetland area in theircatchments (Fig. 1; Table 1). All are first-order lakes exceptRCM, which is a second-order lake located downstream ofBC. All undergo strong thermal stratification and range inarea from 32 to 71 ha and in mean depth from 8 to 17 m, ex-cept for HY, which does not stratify, covers the smallest sur-face area (21 ha), and is the shallowest (mean depth 3 m),and DE, which undergoes weak thermal stratification, hasthe largest area (94 ha), and is the second most shallow(mean depth 5 m). The lakes are located in five main water-sheds and there is a gradient in the amount of wetlandswithin the lake catchments, with DE having the highest per-centage and BC having the lowest (Table 1).

Lakes in the Eastern Forest – Boreal Ecoregion are rela-tively sensitive to acidification and nutrient enrichment dueto naturally low buffering capacity and low nutrient concen-trations, respectively. Two lakes (BC and RCM) are consid-ered reference lakes minimally impacted by human activity;five lakes (CB, CN, DE, HY, and PC) are sensitive to andhave been impacted by regional acid deposition; two lakes(DE and HP) receive phosphorus inputs from shoreline de-velopment, and one lake (HP) contains the nonindigenousBythotrephes zooplankton.

The chemical and clarity characteristics of the lakes re-flected their stressors (Fig. 2). For example, during the studyperiod, less acid-sensitive BC, RCM, and HP had high aver-age pH (>6) and Gran alkalinity (>3 mg·L–1) relative to theother lakes (pH ≤ 6, alkalinity < 2 mg·L–1); HP was distinctbecause of relatively high concentrations of dissolved inor-ganic carbon, potassium, and magnesium (1.6, 0.5, and0.9 mg·L–1, respectively). Average concentrations of chloro-phyll a, dissolved organic carbon, and total phosphorus (4.4,5700, 9.4 µg·L–1, respectively) were relatively high in DE,which is affected by both nutrient inputs and acidification.Of the other acid-stressed lakes, CB and CN had high con-centrations of aluminum (100–110 µg·L–1), and HY and PC

© 2008 NRC Canada

920 Can. J. Fish. Aquat. Sci. Vol. 65, 2008

had low concentrations of calcium (1.6 mg·L–1) and dis-solved inorganic carbon (0.5 mg·L–1). In addition, PC hadthe lowest average alkalinity (0.4 mg·L–1) and highest aver-age Secchi depth (7.1 m) of the lakes. During the 1994 to2003 study period, there was much less variation over timewithin a lake than among the lakes (Fig. 2), and there waslittle change in the chemical characteristics of the studylakes over time relative to the longer-term changes that aredocumented in companion papers in this issue (e.g., Molotand Dillon 2008).

Detailed chemical and biological sampling methods arepresented in various companion papers in this issue (e.g.,Lento et al. 2008; Paterson et al. 2008; Rusak et al. 2008).We selected the time period between 1994 and 2003 to max-imize data availability in all groups and to minimize thepotential effects of changes in sampling methods and fre-quencies on the community composition of phytoplankton(PP), zooplankton (ZP), benthic macroinvertebrates (BMI),and crayfish (CF) groups. However, neither BMI nor CFsampling was conducted in CB, DE, or RCM in 1995. Fish

(F) surveys were conducted once per lake during 2004–2005.

The timing and frequency of sampling and the resolutionof taxonomic identifications were generally consistent withina taxonomic group but varied among groups. PP and ZPsamples were collected at the same time and place (i.e.,deepest spot in each lake) six to eight times over the ice-freeperiod in 1994–2003, except in DE, HP, and PC after 1998when they were collected twice as often. Collections of PPwere volume-weighted euphotic zone samples (e.g., Ingramet al. 2006), whereas ZP samples were volume-weightedwhole-lake samples (e.g., Yan et al. 1996). Compositephytoplankton samples were taken starting at 1 m and thenat each odd metre to the bottom of the euphotic zone; a pre-determined, lake-specific weighting chart was used to deter-mine the volume pumped at each location. Similarly,composite zooplankton samples were collected from three toseven fixed depths, which were chosen so that lake stratacontributed to the composite sample in proportion to theirvolumes. PP samples taken over each ice-free season were

© 2008 NRC Canada

Bowman et al. 921

Fig. 1. Locations of the Dorset A lakes in central Ontario, Canada.

BC RCM CB CN HY PC DE HP

Area (ha) 52.4 44.1 34.4 56.7 21.4 32.1 93.6 71.4Mean Depth (m) 8.5 16.7 8.9 9.2 3.3 7.9 5.0 13.3Thermal stratification S S S S A S W SOntario watershed unit 2EC15 2EC15 2EB9 2EC15 2EB9 2HF10 2EB9 2EB13% Wetland (peat) 0.0 2.9 4.6 7.5 4.0 8.0 12.2 8.7% Wetland (peat and pond) 0.0 5.7 4.6 13.8 4.0 8.0 12.2 9.3

Note: Dorset A lakes: Blue Chalk (BC), Red Chalk Main (RCM), Chub (CB), Crosson (CN), Heney (HY), Plastic (PC), Dickie (DE), Harp (HP). Ther-mal stratification: S, strong; A, absent; W, weak.

Table 1. Physical characteristics of the Dorset A lakes and their catchments (Girard et al. 2006).

pooled and subsampled, whereas ZP samples were processedindividually and counts were averaged over the ice-free season.

BMI sampling was conducted once in autumn, and CFand F sampling were conducted once in mid-summer. BMIswere collected using a kick-and-sweep method (e.g., Somerset al. 1998). Sediments were disturbed and BMIs were col-lected using a D-frame net (250 µm mesh) between shoreand 1 m depth for a total of 10 min at each site. Five siteswere sampled per lake, and sites were randomly selected inproportion to the predominant nearshore substrate types foreach composite BMI sample per lake. Relative abundancesof CF were estimated using baited minnow traps (e.g.,Somers et al. 1996). Traplines consisted of six traps, 1 mapart. At three shoreline sites in each lake (depositional anderosional zones and a vegetated location), three traplineswere set perpendicular to shore for one night for a total of54 traps per lake. Fish were collected using the methods ofMorgan and Snucins (2005). A stratified random samplingdesign was used in which the sampling units were selectedwithout replacement. The number of depth strata and num-ber of nets within each strata were proportional to the sur-face area and depth of each lake.

The PP taxa were identified to genus, the BMI taxa wereidentified to order or higher (except Diptera, which wereidentified to family), and the taxa in the remaining groupswere identified to species where possible (Appendix A). Thelevel of taxonomic resolution can influence interpretation ofecological data considerably, but numerous studies haveshown that the community structure inferred from genus–species level identifications is maintained when taxa areaggregated to family and order (e.g., Bowman and Bailey1997; Melo 2005; Heino and Soininen 2007). For eachgroup, we converted all data to relative abundances, abun-dance data + 1 were log-transformed to down-weight the in-

fluence of more abundant taxa, and taxa found in fewer than5% of sampling occasions were removed from the analysis.Subsequently, there were 71, 33, 22, 3, and 23 taxa in thePP, ZP, BMI, CF, and F groups, respectively (Appendix A).

Community composition was quantified using χ2 distancematrices, and correspondence analysis (CA) ordination wasused to summarize the main patterns in each χ2 distance ma-trix. The axes scores in CA are based on χ2 distances andare analogous to standard deviations, so the magnitude ofvariation in structure among CA plots can be compared. Forexample, each lake-by-lake distance matrix was comprisedof the distance between each lake and every other lake wheredistance was proportional to relative dissimilarity in commu-nity composition. Euclidean distances from the previousyear in CA space (two axes) were also plotted to determinewhether communities within a taxon group across lakes re-sponded concordantly to climatic fluctuations. We lookedfor consistent responses to the drought events in 1998 and2001 (e.g., Bowman et al. 2006) and (or) variation in thenumber of ice-free days (e.g., Futter 2003).

Mantel tests based on χ2 distances between years wereused to evaluate temporal concordance (i.e., within each lakeover time), and distances between lakes were used to evalu-ate spatial concordance (i.e., within each year across lakes)of community composition among PP, ZP, and BMI groups.Data from 1995 were excluded because of missing values,and CF data were not evaluated because they were not foundin all lakes in all years. Mantel tests are based on the Pearsoncorrelation between corresponding elements in two distancematrices (Mantel 1967). The p value for each Mantel testwas equal to the proportion of times out of 1000 that the ob-served correlation between the two distance matrices beingcompared was lower than the correlation based on a random-ization test.

© 2008 NRC Canada


Fig. 2. The relative similarity of water chemistry and clarity attributes in the Dorset A lakes from 1994 to 2003 summarized using aprincipal components analysis of water chemistry values that were standardized to mean = 0, standard deviation (SD) = 1. VE, varia-tion explained; TKN, total Kjeldahl nitrogen; TP, total phosphorus; DOC, dissolved organic carbon; Chl a, chlorophyll a; Cond., con-ductivity; DIC, dissolved inorganic carbon; Alkal., Gran alkalinity. Years are indicated by the two digit number following the lakeabbreviation (e.g., DE_03 is Dickie Lake in 2003). See Table 1 for lake abbreviations.

In addition to evaluating spatial concordance within eachyear across lakes, we evaluated the overall spatial concor-dance across the study period for all taxon groups. Overallspatial concordance was based on the relative abundances oftaxa within each group averaged across the study period,with the exception of fish composition, which was based onone sampling occasion (i.e., one value per taxon per lake).There were no years that were outliers, and there were no

monotonic trends over time in community composition dur-ing the study period. As for temporal and spatial patterns incommunity composition, overall spatial patterns were quan-tified, illustrated, and evaluated using χ2 distance matrices,CA ordinations, and Mantel tests, respectively.

Four additional data summaries were used to illustratecharacteristics of the overall spatial concordance in commu-nity composition among taxon groups: relative concordance

© 2008 NRC Canada

Bowman et al. 923

Fig. 3. The relative similarity of (a, b) phytoplankton, (c, d) zooplankton, (e, f) benthic macroinvertebrate, (g, h) crayfish, and (i, j)fish community composition over time in the Dorset A lakes summarized using correspondence analyses (VE, variation explained). Toimprove readability, common taxa (i.e., –1.0 < scores for axes 1 and 2 < 1.0) are not shown but identified in Appendix A. Dorset Alakes: Blue Chalk (BC), Red Chalk Main (RCM), Chub (CB), Crosson (CN), Heney (HY), Plastic (PC), Dickie (DE), Harp (HP).

among lakes, concordance among taxa, and sensitivity tostressors. First, Ward’s clustering based on each χ2 distancematrix was used to illustrate the relative similarity amonglakes for each taxon group. Like ordination, clustering is asummary of the overall patterns in a distance matrix. How-ever, clustering produces distinct groupings, whereas theinterpretation of CA plots is more subjective. Second, toillustrate which lakes were more or less concordant in eachpairwise comparison (e.g., PP vs. ZP), we used Procrustesrotations based on the first two CA axes. In Procrustes anal-yses, one ordination (e.g., ZP) is rotated to match a secondordination (e.g., PP) such that the average distance betweenlike points (e.g., lakes) is minimized. Third, distances fromthe origin to each lake in CA space were used to illustratethe taxon groups that were more or less concordant in eachlake (see Legendre and Anderson 1999). Finally, the dis-tance in CA space (two axes) between reference lakes (i.e.,BC, RCM) and impacted lakes (i.e., CB, CN, HY, PC, DE,HP) were averaged for each group and stressor to indicatethe relative sensitivity to stress among taxon groups.

Results

Of the taxon groups sampled over time, variation in PPcommunities was most strongly related to year and variationin ZP communities was most strongly related to lake(Fig. 3). There was a concordant shift in PP communities in

all lakes between 1996 and 1997 (Figs. 3a, 3b, and 4a). Theshifts in PP community composition between 1994–1996and 1997–2003 included a decrease in Gymnodinium andPeridinium dinoflagellates. The ZP communities in HP weredistinct from other ZP communities due in part to higherabundances of three species that were not found in any ofthe other lakes: the large, hypolimnetic, glacial relict taxaSenecella calanoides and Leptodiaptomus sicilis and the re-cent invader Bythotrephes longimanus (Figs. 3c, 3d). Highabundances of Daphnia retrocurva and the chydoridsAlonella and Alona contributed to the unique community ofshallow HY. The communities of the nonacidic BC and RClakes were very stable, could not be distinguished from eachother, and were characterized by acid-sensitive taxa (Havenset al. 1993), including Daphnia mendotae and Daphniadubia.

Temporal and spatial patterns in the benthic invertebratecommunities were not as pronounced as the patterns in theplankton communities. High abundances of gastropods in allyears and turbellarians in some years contributed to the hightemporal variability in HP and set these BMI communitiesapart from those in other lakes (Figs. 3e, 3f). All three CFspecies were consistently found in BC and RCM (Figs. 3g,3h). The community composition in the remaining lakes wasmore variable because CF were below detection levels insome years and only one or two of the three species werecaught in other years. For example, there were no crayfish

© 2008 NRC Canada


Fig. 3 (concluded).

caught in HP in 1994, 1996, or 1997 and either Orconectespropinquus or Cambarus bartoni or both were caught in theremaining years. Therefore, temporal variability was highestfor CF communities in HP but temporal variability of CF inother lakes was comparable with that of the other taxongroups (Fig. 4).

Of the fish caught in the eight-lake survey, yellow perchwas the most abundant and was found in all lakes except CB.Pumpkinseed and smallmouth bass were also found in highabundances. CB and HP lakes had the highest abundances ofslimy sculpin and smallmouth bass, and CN and HY had rela-tively high abundances of brown bullhead, pumpkinseed, andyellow perch (Figs. 3i, 3j). Common shiner and spoonheadsculpin were only found in BC and RCM, and rock bass wereonly found in DE and PC.

Significant (i.e., p < 0.05) temporal concordance in com-munity composition between groups was less prevalent thanspatial concordance (i.e., 8.3% vs. 22.2% of comparisons,respectively; Table 2). Comparisons of PP vs. BMI in BCand ZP vs. BMI in HP showed significant concordance overtime, but otherwise, there was a lack of concordance amonggroups. There was significant spatial concordance in one ortwo of the three pairwise comparisons among PP, ZP, andBMI community structure in 5 of the 10 years (i.e., 1994,1996, and 1999 to 2001). For example, PP vs. ZP spatialconcordance was significant in three cases and approachedsignificance (i.e., 0.05 < p < 0.10) in four other cases. Spa-tial concordance was not more prevalent in years with warmeror colder winters and (or) summer drought.

Overall spatial concordance of community compositionwas high among PP, ZP, BMI, and F (i.e., Mantel r = 0.47 to0.85, p < 0.05) but not in pairwise comparisons that includedCF (Mantel r = 0.20 to 0.40, p > 0.05; Table 3). Althoughthe strongest community concordance among groups was be-tween PP and ZP (r = 0.85), the degree of concordanceamong groups was not consistently related to the relativebody size of taxa within groups (Table 3). For example, thecommunity composition of the ZP group was more concor-dant with F (r = 0.71) than with BMI (r = 0.61) communi-ties.

The summaries of overall spatial concordance showed thatthe reference lakes BC and RCM had very similar communi-ties across taxon groups (Figs. 3, 5, and 6). Cluster analysisfor each taxon group suggested that the hydrologically con-nected BC and RCM had communities that were similar toone another and distinct from communities in other lakes, al-though CN was included in this group when the classifica-tion was based on ZP community structure (Fig. 5).Similarly, BC and RCM were consistently close to one an-other and the origin (i.e., the average community) in CAspace (Figs. 6a1–6a5). The BMI group was least concordantwith the other groups in BC and RCM (Figs. 6b, 6c). For ex-ample, the Procrustes comparison between ZP and BMIshowed that the community composition between the twogroups was more concordant (i.e., like lakes were closertogether in the plot) for CN, HP, or PC than for BC or RCM(see Fig. 6b5). Similarly, the distance between the origin andBC and RCM in the CA based on BMI community structurewas the largest of the taxon groups (Fig. 6c).

For all taxon groups, stressed lakes were distinct from ref-erence lakes, but HY and HP typically had the most unusual

© 2008 NRC Canada

Bowman et al. 925

Fig. 4. The distance from previous year in correspondence analy-sis space of the Dorset A lakes from 1994 to 2003 for the(a) phytoplankton, (b) zooplankton, (c) benthic macroinvertebrate,and (d) crayfish groups illustrating shifts in community composi-tion over time within a lake. Dorset A lakes: Blue Chalk (BC),Red Chalk Main (RCM), Chub (CB), Crosson (CN), Heney (HY),Plastic (PC), Dickie (DE), Harp (HP).

communities (Figs. 5, 6). HY and HP were most often thefirst lakes to branch out in the lake classifications (Figs. 5a–5e) and (or) were on the outer edge of CA plots (Figs. 6a1–6a5), furthest from the origin (Fig. 6c). For example, thecluster analyses based on PP and ZP and CA plots based onPP, ZP, and BMI suggested that HY and HP had the mostdistinct communities. The cluster analyses based on fish andthe CA plots based on crayfish and fish also suggested thatHY and HP were unusual. The remaining stressed lakes(CB, CN, PC, and DE) were less unusual than HY and HPbut still distinct from the reference lakes. However, the firstof CB, CN, PC, or DE to branch out in cluster diagrams(Fig. 5) and their distances from the origin in the CA plots(Figs. 6a, 6c) varied across the taxon groups. The magnitudeof response or effect size was comparable among groups

(Table 4), suggesting that there was no relationship betweenrelative taxon size and sensitivity to various stressors.

During the study period, only Cambarus bartoni werefound in DE and only in 2002; this resulted in DE havingthe most unusual crayfish community in the lake classifica-tion (Fig. 5d). Similarly, the Procrustes comparisons showedthat the community structure of the CF group in DE was al-ways relatively different from the structure of the other taxongroups in DE (Figs. 6b3, 6b6, 6b8, 6b10). The facts that CF inDE were much further from the origin than other taxa in DEbut CF in the other lakes were not further from the originthan other taxa (Figs. 6a, 6c) show that the unusual crayfishcommunity in DE was the main reason for the lack of con-cordance between CF and other taxon groups.

Discussion

Average relative abundances of taxa over the study pe-riod provided descriptions of community structure thatwere spatially concordant across taxonomic groups and re-flected natural and anthropogenic differences in the biolog-ical, chemical, and physical characteristics among lakes.Communities in stressed lakes, particularly HP and HY,were consistently distinct from reference communitiesacross taxon groups. The water chemistry characteristics ofHP are distinct from both the reference and other stressedlakes, and HP is the only lake that contains glacial relictand introduced zooplankton. HY is the smallest of thestudy lakes and the only lake that does not stratify. In theother stressed lakes (i.e., CB, CN, PC, and DE), the waterchemistry characteristics were consistently distinct from

© 2008 NRC Canada


PP vs. ZP PP vs. BMI ZP vs. BMI

r p r p r pNo. of ice-free days

Temporal concordanceBC –0.37 0.911 0.53 0.030 –0.36 0.881 —RCM 0.08 0.315 0.03 0.462 –0.26 0.814 —CB 0.20 0.211 –0.07 0.630 0.07 0.396 —CN 0.19 0.211 0.11 0.371 0.16 0.257 —HY –0.04 0.529 0.25 0.202 0.10 0.299 —PC 0.11 0.323 –0.32 0.863 0.16 0.271 —DE –0.41 0.953 0.29 0.157 –0.15 0.718 —HP –0.01 0.463 0.14 0.267 0.48 0.012 —

Spatial concordance1994 0.47 0.026 0.40 0.156 0.48 0.032 2331996 0.61 0.010 0.40 0.156 0.61 0.092 2341997 0.56 0.054 0.39 0.190 0.61 0.074 2161998* 0.17 0.283 0.17 0.294 0.31 0.165 2471999 0.47 0.083 0.57 0.022 0.34 0.192 2312000 0.49 0.079 0.65 0.070 0.64 0.007 2472001* 0.56 0.021 –0.14 0.744 –0.03 0.527 2442002 0.05 0.402 0.23 0.125 0.11 0.318 2302003 0.58 0.066 0.33 0.124 0.06 0.382 233

Note: Dorset A lakes: Blue Chalk (BC), Red Chalk Main (RCM), Chub (CB), Crosson (CN), Heney (HY), Plastic (PC), Dickie (DE), Harp (HP).Values in bold and italic represent p < 0.05 and p < 0.10, respectively.

*Drought years.

Table 2. The Mantel correlations (r) and α levels (p) associated with concordance in community composition among phytoplankton(PP), zooplankton (ZP), and benthic macroinvertebrate (BMI) groups within lakes across years and within years across lakes.

PP ZP BMI Crayfish Fish

PP — 0.85 0.61 0.34 0.47ZP 0.001 — 0.61 0.28 0.71BMI 0.024 0.043 — 0.40 0.61Crayfish 0.113 0.166 0.119 — 0.20Fish 0.046 0.001 0.007 0.211 —

Note: Community composition was based on averages of relative abun-dances of taxa from 1994 to 2003 for all groups except for fish composi-tion, which was based of data collected in 2004 or 2005. Correlationswith a p values <0.05 are in bold.

Table 3. The Mantel correlations (above diagonal) and α levels(below diagonal) associated with overall spatial concordance incommunity composition among phytoplankton (PP), zooplankton(ZP), and benthic macroinvertebrate (BMI) groups.

those of reference lakes, whereas at least one of the physi-cal attributes (i.e., size, stratification type, and geographicproximity) was comparable with those of the reference

lakes. The main reason for the lack of overall spatial con-cordance between the CF and other taxon groups was dueto an unusual Cambarus bartoni only CF population in DE,the lake stressed by both nutrient additions and acidifica-tion. Cambarus bartoni populations significantly and con-sistently declined to low (often undetectable) levels over adecade ago in several lakes (e.g., DE) where they wereprevalent (Keith Somers, unpublished data), and since then,their true abundances have been difficult to estimate. Ourresults are consistent with those of Johnson et al. (2007),who found that stream chemistry characteristics reflectiveof human impact were strong determinants of concordantdiatom, macrophyte, invertebrate, and fish communitieswithin ecoregions.

Unlike overall spatial concordance among the PP, ZP, andBMI groups based on mean abundances across years, spatialconcordance in a given year was not consistently strong.There was significant (i.e., p < 0.05) spatial concordance inonly 11%–33% of the pairwise comparisons among PP, ZP,and BMI over 9 years (22%–78% for p < 0.10). Paavola etal. (2003, 2006) also reported variable and (or) weak concor-dance among macroinvertebrate, bryophyte, and fish groupswithin boreal stream drainages. Our findings suggest that es-timates of community composition based on several yearsmay provide a better description of true community structurethan estimates based on a single year. However, numerousother factors may have contributed to the lack of spatial con-cordance among taxon groups within a given year. For exam-ple, concordance at local scales is thought to be strengthenedby biological interactions (Jackson and Harvey 1993; Heino2002). The lack of spatial concordance that we observed atan annual time scale may be related to discrepancies in thetiming and frequency of sampling among taxon groups. PPand ZP community structure was derived from samples col-lected at least six to eight times over the ice-free period,whereas the structure of the remaining groups was derivedfrom samples taken once in summer (CF and F) or autumn(BMI). Therefore, concordance resulting from biological in-teractions may have been masked by averaging communitycomposition over time for PP and ZP groups and by dispari-ties in when the various groups were sampled. However, anynatural or human-influenced attribute of the taxon or ecosys-tem that differentially affects taxonomic groups, for example,history (e.g., historical acidification or eutrophication), taxonpreferences and tolerances (e.g., hypolimnetic fish), lag ef-fects, or environmental determinants (e.g., dispersal capabili-ties), can lead to a lack of concordance.

Temporal concordance in community composition bothwithin and among taxon groups was less prevalent than spatialconcordance in the Dorset-area lakes during the study period.We observed a concordant shift in PP community structure in1997 that persisted throughout the remainder of the study pe-riod in all study lakes, but there were no concordant temporalshifts in community composition in the other taxon groups. ThisPP community shift did not correspond to drought events in theecoregion. In addition, none of the water chemistry or clarityattributes in 1997 was outside the normal range (i.e., outsidemean + 2 standard deviations) of attributes measured duringthe study period. However, the number of ice-free days in 1997(i.e., 216) was the lowest recorded during the study period.These findings are consistent with the prediction that smaller-

© 2008 NRC Canada

Bowman et al. 927

Fig. 5. Ward’s clustering of the Dorset A lakes based on (a) phyto-plankton, (b) zooplankton, (c) benthic macroinvertebrates, (d) cray-fish, and (e) fish community composition averaged over the studyperiod illustrating relative similarity among lakes for each taxongroup. Dorset A lakes: Blue Chalk (BC), Red Chalk Main (RCM),Chub (CB), Crosson (CN), Heney (HY), Plastic (PC), Dickie (DE),Harp (HP).

bodied taxa will be more sensitive to shorter-term climatic fluc-tuations than larger-bodied taxa (Allen et al. 1999b). However,long-term changes in PP assemblages at the group level werenot significantly related to climatic variables through time (Pat-

erson et al. 2008). Also, Rusak et al. (2008) found that certainzooplankton species responded to climatic fluctuations,whereas overall ZP community structure in our study did notrespond to the same changes. Temporal concordance in com-

© 2008 NRC Canada


Fig. 6. (a1–a5) Correspondence analyses (CA) of the Dorset A lakes based on average community composition over the study period,(b1–b10) Procrustes rotations illustrating lakes that were concordant in each pair-wise comparison, and (c) distances from the origin toeach lake in CA space illustrating taxon groups that were concordant in each lake. Taxa with the highest CA axis scores are identifiedon the CA plots (see Appendix A for full taxon names). Solid squares, phytoplankton; shaded diamonds, zooplankton; solid triangles,macroinvertebrates; ×, crayfish; open circles, fish. Dorset A lakes: Blue Chalk (BC), Red Chalk Main (RCM), Chub (CB), Crosson(CN), Heney (HY), Plastic (PC), Dickie (DE), Harp (HP).

Acidification (n = 10) Development (n = 4) Unusual ZP species (n = 2)

Reference (n = 1) Mean SD Effect sizea Mean SD Effect sizea Mean SD Effect size

PP 0.35 1.56 0.80 1.21 1.40 0.70 1.05 1.98 0.25 1.63ZP 0.65 1.63 0.72 0.97 1.72 0.26 1.06 1.74 0.41 1.08BMI 0.27 2.37 0.42 2.10 2.64 0.53 2.37 3.09 0.09 2.83CFb 0.28 2.32 0.90 2.04 2.65 1.58 2.36 1.28 0.18 1.00F 0.24 1.51 0.45 1.27 2.30 0.67 2.06 2.88 0.09 2.64

aDistance between reference lakes subtracted from the mean distance (between reference and stressed lakes).bn, mean, SD, and effect size without DE for acidification are 8, 1.90, 0.19, and 1.62, respectively, and for eutrophication are 2, 1.28, 0.18, and 1.00,

respectively.

Table 4. The distance in correspondence analysis space (two axes) between reference lakes and the mean distance, standard deviation(SD), and effect size between reference lakes (Blue Chalk and Red Chalk Main) and lakes affected by acidification (Chub, Crosson,Heney, Plastic, and Dickie), shoreline development (Dickie and Harp), and unusual ZP species (Harp), for phytoplankton (PP), zoo-plankton (ZP), benthic macroinvertebrate (BMI), crayfish (CF), and fish (F).

munity composition within and among taxon groups was rareand not stronger in particularly warm or cold years (Lento etal. 2008; this study). Thus, the collective results of this andother Dorset-area studies (Lento et al. 2008; Paterson et al.2008; Rusak et al. 2008) show that the response of individualspecies to climatic changes can be blurred at lower taxonomicresolutions or in summaries of community composition. How-ever, concordant changes in community structure derived froma range of high to low taxonomic resolutions were indicative ofvariability in stress and biological, chemical, or physical char-acteristics of ecosystems in the Dorset area (Bowman et al.2006; Lento et al. 2008; this study).

Neither the degree of concordance among groups nor thestrength of the relationship with various stressors was relatedto the relative body size of taxa in Dorset-area lakes. Be-cause of various physiological, morphological, and behav-ioral adaptations related to taxon size, it is often assumedthat smaller-bodied taxa will respond more rapidly and stronglyto smaller-scale stressors, whereas changes associated withlarger-bodied taxa will be more indicative of larger-scale al-terations (Allen et al. 1999b; Hering et al. 2006a; Johnson etal. 2007). For example, plankton can respond more quicklyto environmental change because of their shorter life spansand high dispersal capabilities (Schindler 1987). In addition,plankton have relatively simple adaptations and higher sur-face to volume ratios, causing them to be more sensitive tolocal-scale changes such as changes in water chemistry (Al-len et al. 1999b). In contrast, larger-bodied taxa such as fishhave relatively more complex adaptations, lower surface tovolume ratio, and lower reproductive potential and dispersalcapabilities. However, the results of this study and other re-cent studies suggest that spatial concordance is not stronglyrelated to relative taxon size (Hering et al. 2006a; Johnson etal. 2007). For example, differences in community structurebetween reference and stressed lakes near Dorset were com-parable among all taxon groups across stressors. Various anal-yses of a large European data set on benthic diatom,macrophyte, invertebrate, and fish communities in streamsshowed that the relative response of various taxon groups isless dependant on taxon size and more dependent on stressortype, ecosystem size and type, and spatial scale (e.g., Heringet al. 2006b; Johnson et al. 2006a, 2007).

Advocates of using multiple taxon groups to detect ecologi-cal change argue that the approach should strengthen infer-ences, while opponents argue that information from varioustaxon groups is often redundant. Also, the most useful indica-tors of biological impact will have low uncertainty and astrong response to stress (Johnson et al. 2007). As is typicalof sensitive species, each CF species occurred in low abun-dances or was absent in stressed, Dorset-area lakes, so thecharacterization of CF community structure in the moststressed lakes was likely the least reliable of the groups. Con-sistent with the findings of Johnson et al. (2007), the taxongroups that we evaluated had comparable amounts of changein community structure with stress. In addition, we couldhave used any of the five taxon groups to distinguish betweenreference lakes and lakes with the most unusual communitieswhen community structure was based on average abundanceover the study period. However, there was little agreementamong taxon groups when there were more subtle differencesamong lakes or when we used annual means to estimate com-

munity structure. Thus, our results suggest that the varioustaxon groups provided unique ecological information. The de-gree of community concordance among freshwater taxa de-pends critically on the scale of study, so ecological inferencesbased on a single ecosystem, occasion, or taxon group shouldbe used with caution (Paavola et al. 2006). Other pertinentconsiderations when evaluating whether various taxon groupsare complementary or redundant include their relationshipwith valued ecosystem attributes (e.g., species at risk,biodiversity, absence of toxic algal blooms, sport-fish stocks),utility as early warning indicators (Johnson et al. 2006b), andunique response(s) for use in impact diagnosis (deZwart et al.2006). The degree of concordance among taxon groups canbe used to select the most appropriate indicator(s) for a givensituation, and the complementary information provided byvarious concordant groups can also be used in a multiple linesof evidence approach to improve the inferential strength ofecological studies (Johnson et al. 2007).

Acknowledgements

The funding for data collection and sample processing wasprovided by the Ontario Ministry of the Environment. Dataanalyses and manuscript preparation was made possiblethrough Natural Sciences and Engineering Research Council ofCanada (NSERC) postdoctoral funding to MFB. The A lakeswere selected by Peter Dillon, former supervisor and currentpartner of the Dorset Environmental Science Centre (DESC).From 1994 to 2003, RI collected many of the thermal stratifi-cation data and samples for water chemistry, phytoplankton,zooplankton, and crayfish; RAR helped collect and supervisedthe processing of benthic macroinvertebrate and crayfish sam-ples; and GEM managed the collection and identification offish. The contributions of Robert Girard included generatingphysical characteristics of the lakes and verifying the accuracyof chemical data. Don Evans and Peter Sutey directed waterchemistry analyses. The plankton data were generated with theassistance of phytoplankton taxonomist Lucja Heintsch, andthe zooplankton data were generated with the assistance of tax-onomists Bill and Dee Geiling. The manuscript was improvedas a result of discussions between MFB and Don Jackson. Wewould also like to acknowledge the numerous past and presentDESC staff, partners, and students who each contributed to as-pects of study design, sample collection, sample processing,data management, and associated research.

References

Allen, A.P., Whittier, T.R., Kaufmann, P.R., Larsen, D.P., O’Connor,R.J., Huges, R.M., Stemberger, R.S., Dixit, S.S., Brinkhurst, R.O.,Herlihy, A.T., and Paulsen, S.G. 1999a. Concordance of taxonomicrichness patterns across multiple lake assemblages in lakes of thenortheastern United States. Can. J. Fish. Aquat. Sci. 56: 2029–2040.

Allen, A.P., Whittier, T.R., Larsen, D.P., Kaufmann, P.R., O’Connor,R.J., Huges, R.M., Stemberger, R.S., Dixit, S.S., Brinkhurst, R.O.,Herlihy, A.T., and Paulsen, S.G. 1999b. Concordance of taxonomiccomposition patterns across multiple lake assemblages: effects ofscale, body size, and land use. Can. J. Fish. Aquat. Sci. 56: 2029–2040.

Bowman, M.F., and Bailey, R.C. 1997. Does taxonomic resolutionaffect the multivariate description of the structure of freshwater

© 2008 NRC Canada

Bowman et al. 929

benthic macroinvertebrate communities? Can. J. Fish. Aquat.Sci. 54: 1802–1807.

Bowman, M.F., Somers, K.M., Reid, R.A., and Scott, L.D. 2006.Temporal response of stream benthic macroinvertebrate commu-nities to the synergistic effects of anthropogenic acidificationand natural drought events. Freshw. Biol. 51: 768–782.

deZwart, D., Dyer, S.D., Posthuma, L., and Hawkins, C.P. 2006.Predictive models attribute effects of fish assemblages to toxic-ity and habitat alteration. Ecol. Appl. 16: 1295–1310.

Futter, M. 2003. Patterns and trends in southern Ontario lake icephenology. Environ. Monit. Assess. 88: 431–444.

Girard, R.E., Clark, B.J., Yan, N.D., Reid, R.A., David, S.M., Ingram,R., and Findeis, J.G. 2006. History of chemical, physical and bio-logical sampling methods, sample locations and lake morphometryfor the Dorset Environmental Science Centre (1973–2005). DorsetEnvironmental Science Centre, 1026 Bellwood Acres Road,Dorset, ON P0A 1E0, Canada.

Havens, K.E., Yan, N.D., and Keller, W. 1993. Lake acidification:effects on crustacean zooplankton populations. Environ. Sci.Technol. 27: 1621–1624.

Heino, J. 2002. Concordance of species richness patterns among mul-tiple freshwater taxa: a regional perspective. Biodivers. Conserv.11: 137–147.

Heino, J., and Soininen, J. 2007. Are higher taxa adequate forspecies-level assemblage patterns and species richness in streamorganisms? Biol. Conserv. 137: 78–89.

Heino, J., Paavola, R., Virtanen, R., and Muotka, T. 2005. Searchingfor biodiversity indicators in running waters: do bryophytes,macroinvertebrates, and fish show congruent diversity patterns?Biodivers. Conserv. 14: 415–428.

Hering, D., Johnson, R.K., and Buffagni, A. 2006a. Linking organ-ism groups — major results and conclusions from the STARproject. Hydrobiologia, 566: 109–113.

Hering, D., Johnson, R.K., Kramm, S., Schmutz, S., Szoszkiewicz,K., and Verdonschot, P.F.M. 2006b. Assessment of Europeanstreams with diatoms, macrophytes, macroinvertebrates, and fish:a comparative metric-based analysis of organism response tostress. Freshw. Biol. 51: 1757–1785.

Ingram, R.G., Girard, R.E., Clark, B.J., Paterson, A.M., Reid, R.A.,and Findeis, J.G. 2006. Dorset Environmental Science Centre: lakesampling methods. Ontario Ministry of the Environment TechnicalReport. Queen’s Printer for Ontario. ISBN 1-4249-2049-3.

Jackson, D.A., and Harvey, H.H. 1993. Fish and benthicinvertebrates — community concordance and community envi-ronment relationships. Can. J. Fish. Aquat. Sci. 50: 2641–2651.

Johnson, R.K., Hering, D., Furse, M.T., and Clarke, R.T. 2006a.Detection of ecological change using multiple organism groups:metrics and uncertainty. Hydrobiologia, 566: 115–137.

Johnson, R.K., Hering, D., Furse, M.T., and Verdonschot, P.F.M.2006b. Indicators of ecological change: comparison of the early re-sponse of four organism groups to stress gradients. Hydrobiologia,566: 139–152.

Johnson, R.K., Furse, M.T., Hering, D., and Sandin, L. 2007. Eco-logical relationships between stream communities and spatialscale: implications for designing catchment-level monitoringprogrammes. Freshw. Biol. 52: 939–958.

Legendre, P., and Anderson, M.J. 1999. Distance-based redundancyanalysis: testing multispecies responses in multifactorial ecologi-cal experiments. Ecol. Monogr. 69: 1–24.

Lento, J., Dillon, P.J., Somers, K.M., and Reid, R.A. 2008. Changesin littoral benthic macroinvertebrate communities in relation towater chemistry in 17 Precambrian Shield lakes. Can. J. Fish.Aquat. Sci. 65: 906–918.

Magnuson, J.J., Benson, B.J., and Kratz, T.K. 1990. Temporal co-herence in the limnology of a suite of lakes in Wisconsin, U.S.A.Freshw. Biol. 23: 145–159.

Mantel, N. 1967. The detection of disease clustering and a general-ized regression approach. Cancer Res. 27: 209–220.

Melo, A.S. 2005. Effects of taxonomic and numeric resolution onthe ability to detect ecological patterns at a local scale usingstream macroinvertebrates. Arch. Hydrobiol. 164: 309–323.

Molot, L.A., and Dillon, P.J. 2008. Long-term trends in catchmentexport and lake concentrations of base cations in the Dorset studyarea, central Ontario. Can. J. Fish. Aquat. Sci. 65: 809–820.

Morgan, G.E., and Snucins, E. 2005. Manual of instructions —Nordic index netting. Ontario Ministry of Natural Resources,Cooperative Freshwater Ecology Unit, Laurentian University,Sudbury, ON P3E 2C6, Canada.

Paavola, R., Muotka, T., Virtanen, R., Heino, J., and Kreivi, P.2003. Are biological classifications of headwater streams con-cordant across multiple taxonomic groups? Freshw. Biol. 48:1912–1923.

Paavola, R, Muotka, T., Virtanen, R., Heino, J., Jackson, D., andMaki-Petays, A. 2006. Spatial scale affects community concor-dance among fishes, benthic macroinvertebrates, and bryophytesin streams. Ecol. Appl. 16: 368–379.

Passy, S.I., Bode, R.W., Carlson, D.M., and Novak, M.A. 2004. Com-parative environmental assessment in the studies of benthic diatom,macroinvertebrate, and fish communities. Int. Rev. Hydrobiol. 89:121–138.

Paterson, A.M., Winter, J.G., Nicholls, K.H., Clark, B.J., Ramcharan,C.W., Yan, N.D., and Somers, K.M. 2008. Long-term changes inphytoplankton composition in seven Canadian Shield lakes in re-sponse to multiple anthropogenic stressors. Can. J. Fish. Aquat.Sci. 65: 846–861.

Rusak, J.A., Yan, N.D., and Somers, K.M. 2008. Regional climaticdrivers of synchronous zooplankton dynamics in north-temperate lakes. Can. J. Fish. Aquat. Sci. 65: 878–889.

Schindler, D.W. 1987. Detecting ecosystem response to anthropogenicstress. Can. J. Fish. Aquat. Sci. 44(Suppl. 1): 6–25.

Somers, K.M., Reid, R.A., David, S.M., and Ingram, R.I. 1996.Are relative abundances of orconectid crayfish better indicatorsof water-quality changes than cambarid abundances? Freshw.Crayfish, 11: 249–265.

Somers, K.M., Reid, R.A., and David, S.M. 1998. Rapid biologicalassessments: how many animals are enough? J. N. Am. Benthol.Soc. 17: 348–358.

Yan, N.D., Keller, W., Somers, K.M., Pawson, T.W., and Girard,R.E. 1996. Recovery of crustacean zooplankton communitiesfrom acid and metal contamination: comparing manipulated andreference lakes. Can. J. Fish. Aquat. Sci. 53: 1301–1327.

Appendix A

Table A1 appears on the following page.

© 2008 NRC Canada


© 2008 NRC Canada

Bowman et al. 931

Phytoplankton Zooplankton BMI Crayfish Fish

Achnanthes Acanthocyclops vernalis complex Amphipoda Cambarus bartoni Bluntnose minnow (Pimephales notatus)Anabaena Alona sp. Anisoptera Orconectes propinquus Blacknose shiner (Notropis heterolepis)Aphanocapsa Alonella sp. Ceratopogonidae Orconectes virilis Brown bullhead (Ameriurus nebulosus)Aphanothece Bosmina sp. Chironomidae Burbot (Lota lota)Arthrodesmus Bythotrephes longimanus Coleoptera Common shiner (Luxilux cornutus)Asterionella Unidentified Calanioda Decapoda Creek chub (Semotilus atromaculatus)Bitrichia Chydorus sphaericus Ephemeroptera Golden shiner (Notemigonus crysoleucas)Botryococcus Cyclopoid copepodid Gastropoda Lake herring (Coregonus artedi)Ceratium Cyclopoid nauplius Hemiptera Lake trout (Salvelinus namaycush)Chlamydomonas Cyclops scutifer Hirudinea Lake whitefish (Coregonus clupeaformis)Chromulina Daphnia (galeata) mendotae Lepidoptera Largemouth bass (Micropterus salmoides)Chroococcus Daphnia ambigua Megaloptera Logperch (Percina copelandi)Chrysidiastrum Daphnia dubia Nematoda Mottled sculpin (Cottus bairdi)Chrysochromulina Daphnia longiremis Oligochaeta Northern pike (Esox lucius)Chrysolykos Daphnia pulex Pelecypoda Pumpkinseed (Lepomis gibbosus)Chrysophyte Daphnia retrocurva Plecoptera Rainbow smelt (Osmerus mordax)Chrysosphaerella Daphnia sp. Tabanidae Rainbow trout (Oncorhynchus mykiss)Closterium Diacyclops bicupidatus thomasi Tipulidae Rock bass (Ambloplites rupestris)Codonocladium Diaphanosoma birgei Trichoptera Spoonhead sculpin (Cottus ricei)Coelastrum Epischura lucustris Trombidiformes Slimy sculpin (Cottus cognatus)Coelosphaerium Eubosmina tubicen Turbellaria Smallmouth bass (Micropterus dolomieu)Cosmarium Holopedium glacialis Zygoptera White sucker (Catostomus commersoni)Crucigenia Leptodiaptomus ashlandi Yellow Perch (Perca flavescens)Cryptaulax Leptodiaptomus minutusCryptomonas Leptodiaptomus sicilis

Cyclotella Leptodora kindtii

Dinobryon Mesocyclops edax

Dinophyceae Orthocyclops modestus

Elakatothrix Polyphemus pediculusEpipyxis Senecella calanoides

Gloeocapsa Sida crystallinaGloeocystis Skistodiaptomus oregonensis

Gloeotila Tropocyclops extensusGomphosphaeriaUnidentified green

Gymnodinium

KatablepharisKephyrion

Kirchneriella

Koliella

Lyngbya

MallomonasMelosira

MerismopediaMonoraphidium

Nephrocytium

Ochromonas

OocystisOscillatoria

Pediastrum

Pedinomonas

Peridinium

Pleuromastix

Quadrigula

Rhabdoderma

Rhizochrysis

Table A1. The phytoplankton, zooplankton, benthic macroinvertebrate (BMI), crayfish, and fish taxa found in Dorset A lakes in greaterthan 5% of sampling occasions with common taxa (see Fig. 3 caption) in bold.

© 2008 NRC Canada


Phytoplankton Zooplankton BMI Crayfish Fish

Rhizosolenia

Rhodomonas

Salpingoeca

Scenedesmus

Sphaerozosma

Spiniferomonas

Spondylosium

Staurastrum

Staurodesmus

Synedra

SynuraTabellariaTetraëdron

Tetrastrum

Uroglena

Table A1 (concluded).

Temporal and spatial concordance in community composition of phytoplankton, zooplankton,...

Documents

Transcript of Temporal and spatial concordance in community composition of phytoplankton, zooplankton,...