-1Research article

Landscape position, local environmental factors, and the structure of molluscan

assemblages of lakes

Jani Heino1,* and Timo Muotka2,31Research Department, Finnish Environment Institute, University of Oulu, P.O. Box 413, FIN-90014, Fin-land; 2Research Department, Finnish Environment Institute, P.O. Box 140, FIN-00251 Helsinki, Finland;3Department of Biology, University of Oulu, P.O. Box 3000, FIN-90014, Finland; *Author for correspondence(e-mail: jani.heino@ymparisto.fi)

Recived 8 November 2004; accepted in revised form 23 August 2005

Key words:Assemblage structure, Dispersal, Environmental filters, Fingernail clams, Snails, Species richness

Abstract

Biotic communities are structured by both regional processes (e.g., dispersal) and local environmentalconditions (e.g., stress). We examined the relative importance of landscape position (position within thehydrologic flow system and distance from other lakes) and local environmental factors in determining theassemblage structure of lake-dwelling snails and fingernail clams in a boreal landscape. Both landscapeposition and local environmental factors were highly influential in structuring the molluscan assemblages.In canonical correspondence analysis, 53.6% of snail and 48.2% of fingernail clam assemblage compositionwere accounted for by both sets of variables. The pure effects of landscape position were higher than thoseof environmental variables, and a considerable amount of variability was shared by the two sets of vari-ables. In regression analysis, 95.5% of snail and 62.2% of fingernail clam species richness was accounted forby the explanatory variable groups, with most of the variability being related to shared effects, followed bylandscape position. The effects of landscape position on species composition suggest that passive dispersalincreases the similarity of molluscan assemblages in adjacent lakes. This process does not lead to an overallhomogenisation of assemblage composition across the landscape, however, because local conditions set astrong environmental filter, excluding species that arrive at an unsuitable lake. These environmental filtersmay reflect either extinction probability (area, productivity) or species niche differences (calcium levels,abiotic stress). Landscape position may also be important in maintaining the species richness of lake-dwelling molluscan assemblages. By providing potential colonists, nearby source lakes are likely to beimportant in countering local extinctions. Our test of the relative importance of landscape position andlocal drivers of assemblage structure was partly confounded by their co-variation. Nevertheless, studyingthe relationship between landscape position and local variables is useful because it can tell us about theimportance of local and regional processes in shaping lake communities.

Introduction

Traditionally, ecologists have emphasised the roleof local processes and species’ niche differences indetermining the structure of biotic communities,

and local and regional processes have been con-sidered largely independent. Current views, how-ever, acknowledge that the structure of localcommunities is the sum of multiple factors, witheffects of both local (e.g., predation, stress) and

Landscape Ecology (2006) 21:499–507 � Springer 2006

DOI 10.1007/s10980-005-2377-x

regional (e.g., dispersal, connectivity) factors (Holt1993; Huston 1999; Hubbell 2001; Mouquet andLoreau 2003). Disentangling the relative impor-tance of these factors to community structure haspresented a formidable challenge for ecologistsstudying the organisation and variability of bioticcommunities. Recent evidence from both theoret-ical and empirical studies, and from terrestrial andfreshwater realms, has clearly shown that under-standing the structure of ecological communities incomplex landscapes requires a simultaneousexamination of local habitat characteristics andamong-site dispersal and connectivity. In the ter-restrial realm, many studies have shown theimportance of patch isolation and connectivity tovertebrate communities in fragmented forests (e.g.,Forman 1995). In the freshwater realm, localenvironmental factors were long regarded as themajor determinants of community structure(Bohonak and Jenkins 2003), and only recently hasthe importance of dispersal, habitat isolation andlandscape connectivity been given more emphasis(Magnuson et al. 1998; Vaughn and Taylor 2000).

The position of lakes within a landscape hasrecently gained increased interest from both lim-nological and ecological perspectives. Althoughlimnologists have long known that headwaterlakes high in the landscape differ from lakes lowerin the landscape, recent advances have greatlyexpanded our understanding of the organisation oflake districts (Sorrano et al. 1999; Riera et al.2000). Thus, headwater lakes are typically smaller,tend to have lower pH and ionic concentrations,and are less connected to the drainage system thanlakes lower in the landscape.

All above factors are considered important forthe distribution of lake-dwelling organisms. Forfish, both local environmental (e.g., lake area,water pH) and landscape variables (e.g., streamconnections, distance to other lakes) have beenfound important in determining communitystructure (Magnuson et al. 1998; Olden et al.2001). In general, isolated headwater lakes withadverse abiotic conditions support low-diversityfish communities, whereas larger, more connectedlowland lakes are more diverse. Further, thepresence of large piscivores may have importantconsequences to fish community structure,especially if there are no stream connections topotential colonisation sources to counter preda-tion-induced extinctions (Tonn and Magnuson

1982; Olden et al. 2001). For zooplankton, Pinel-Alloul et al. (1995) found that species compositionwas related to both local environmental factorsand spatial position of a lake, but also that most ofthe variability was accounted for by spatially-structured gradients in environmental conditions.Cottenie et al. (2003) found that both local envi-ronmental factors and spatial position contributedindependently to zooplankton species compositionin a set of interconnected ponds. By contrast,zooplankton species richness in the same set ofponds was primarily related to environmentalvariables, suggesting that species composition andspecies richness may be regulated by partly dif-ferent processes (Cottenie and De Meester 2003).For snails, Lewis and Magnuson (2000) found thatboth lake environmental factors and landscapeposition were strongly related to species’ distribu-tions and species richness, and that isolatedheadwater lakes with low calcium concentrationgenerally supported few snail species. This findingis well in line with Aho (1978a) who found thatsnail species richness was affected by both lakeenvironmental factors and distance to a potentialcolonisation source, a large lowland lake.

We examined the distribution patterns of lake-dwelling molluscan assemblages across a boreallandscape. We were specifically interested in therelative importance of lake environmental factorsand landscape position in determining the speciescomposition and species richness of freshwatersnails and fingernail clams. Further, we divided thelandscape position of a lake into two components:(i) lakescape position, i.e., position of a lake inrelation to the path of water flow within thedrainage system, and (ii) spatial position, i.e., thegeographical co-ordinates of the lake. Both thesecomponents may be important with regard to thedispersal of organisms across the landscape. Forinstance, lakescape position could be closelyrelated to the distribution of organisms that relyon stream connections for dispersal (e.g., fish),whereas spatial position might show a strongerrelationship with the distribution of organismsrelying mainly on passive zoochory for among-lake dispersal (e.g., various invertebrates; seereview by Figuerola and Green (2002)). Amongfreshwater molluscs, snails could be presumed toutilise both active dispersal via stream networks(Lewis and Magnuson 2000) and passive dispersalmediated by waterfowl (e.g., Boag 1986), whereas

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fingernail clams should rely mainly on passiveamong-lake dispersal (e.g., Aho 1966).

Based on published information on the distri-bution patterns of lake-dwelling organisms at thelandscape level (see above), we formulated a seriesof hypotheses. Hypothesis 1: species assemblagesare governed primarily by local, within-lake fac-tors. (1a) If these factors are unrelated to land-scape position, then most variance will beexplained by local factors. Alternatively, (1b) ifthese factors are related to landscape position,then most variance will be explained by the sharedeffects of landscape position and within-lake fac-tors. Hypothesis 2: species assemblages are gov-erned primarily by dispersal, and most variancewill therefore be explained by landscape positionvariables. (2a) If dispersal is mainly via streamnetworks, then most variance will be explained bylakescape position alone. (2b) If, by contrast, dis-persal is mainly passive and overland, then mostvariance will be explained by spatial position.Hypothesis 3: both within-lake factors and dis-persal are important in shaping species assem-blages, and variance will be evenly divided betweenpure landscape position, pure local factors, andshared variation. Additionally, it must be stressedthat all these hypotheses pertain to relatively fineand recent time scales. As our test material, were-analysed Aho’s (1966) data on snail and fin-gernail clam assemblages in a boreal lake district.

Materials and methods

Study area and data set

The lakes studied by Aho (1966) are located insouthern Finland (centred on 61�26¢ N, 23�40¢ E).The region is characterised by variable topogra-phy, but absolute altitudinal differences amongthe lakes are slight (lake altitudes range from 77to 126 m above sea level). Bedrock consistsmainly of mica gneiss and some granite, and it iscovered by morainic drifts and clay. Vegetationconsists mainly of spruce (Picea abies) and pine(Pinus sylvestris) dominated coniferous forests,with some fields, scattered peatlands, and mixedforests close to water bodies. Lakes range fromthose with humic, low nutrient and soft water tothose with more nutrient-rich and harder water(Table 1).

We considered 22 headwater lakes and one largelake, Lake Pyhajarvi (111.5 km2), which acts as apotential colonisation source for the smaller lakes(Figure 1). The headwater lakes are connected toLake Pyhajarvi by narrow (mostly less than 2 mwide), high-gradient forest streams, which havenot been used for boat traffic (H. Toivonen,Finnish Environment Institute, personal commu-nication). The landscape position of the lakes isrelated to local lake conditions such that the mostisolated headwater lakes are more acidic and havelower calcium concentration and less macrophytes,and consequently more depauperate molluscanassemblages, than lakes lower in the landscape (seeAho 1978b; Heino and Muotka 2005). All but oneof the molluscan species occurring in the smallerlakes also occurred in Lake Pyhajarvi (Aho 1966).Snails (Gastropoda) and fingernail clams(Bivalvia: Sphaeriidae) were sampled at one ormore stations in each lake, depending on lake size.Samples from macrophyte beds (4 m2) and stonysubstrates (0.5 h visual search) were taken fromeach station. Further details of the samplingmethods can be found in Aho (1966). Snails werefound in 19 lakes, and fingernail clams in 21 lakes.One lake did not harbour any snails or fingernailclams, and species richness among the other lakesvaried considerably (Table 1). To facilitate com-parison between patterns of assemblage composi-tion and species richness, only lakes where snailsand clams occurred were included in the analyses.

Table 1. Mean (±1 SE) and range of the environmental vari-

ables and the species richness of snails and clams in the 21 study

lakes.

Variable Mean SE Min. Max.

Isolation (km) 3.78 0.42 0.75 6.60

Number of upstream lakes 2.16 0.66 0 10

Area (ha) 9.56 3.62 0.3 79.0

Colour (mg Pt/l) 62.09 5.18 30 120

Humic substances

(KMnO4, mg/l)

48.18 2.37 30.20 71.90

Electrolytic conductivity

(v20)47.47 2.96 28 70

Hardness (�dH) 0.96 0.07 0.47 1.39

Alkalinity (ml HCl/l) 0.17 0.02 0.02 0.37

pH 6.28 0.12 5 7

Snails 5.57 0.95 0 14

Fingernail clams 4.04 0.54 1 10

Data compiled from Aho (1966). Isolation was measured as the

shortest linear distance to the large source lake.

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Data on lake area and water chemistry (Table 1)were derived from the original publication (Aho1966). Aho (1966) did not give pH values for twoof the lakes, and for each lake the mean pH of therespective lake type (Heino and Muotka 2005) wasused. Isolation was measured for each lake as thestraight-line distance to Lake Pyhajarvi (DIST-MAIN). The number of upstream lakes (UPLA-KES) was used as a proxy for a lake’s position alonga lake chain and was derived from maps. If neces-sary, environmental variables were logarithmically

transformed to improve normality and reduceheteroscedasticity.

Statistical methods

Variability in species composition and speciesrichness was partitioned between two groups ofexplanatory variables. (i) Local environmentalvariables, including lake area, water pH, alkalin-ity, conductivity, hardness, colour, and humic

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Figure 1. Locations of the lakes in the study landscape. The arrows denote the direction of the stream flow from the study lakes to

Lake Pyhajarvi. The star in the inset shows the location of the study landscape in the south boreal ecoregion in Finland.

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substances (KMnO4 consumption). (ii) Landscapeposition variables included both lakescape posi-tion and spatial position variables. Lakescapevariables were lake altitude, distance to the mainlake (DISTMAIN), and number of lakes upstream(UPLAKES). Spatial variables were north (x) andeast coordinates (y). Further, x and y coordinateswere centred on their respective means, and a thirdorder polynomial was constructed from the origi-nal co-ordinates to provide nine variables (x, y, x2,y2, xy, x2y, xy2, x3, y3) describing the spatiallocation of each lake. These multiple spatial vari-ables do not have a straightforward ecologicalinterpretation, but they do indicate the generaldegree of importance of spatial patterning, andthey allow one to model more complex patterns ofspecies distributions than mere north and eastcoordinates (Borcard et al. 1992; Legendre 1993).

For partitioning variation in species composi-tion (presence–absence data) among the localenvironment and landscape position, each groupof variables was first screened using forwardselection with Monte Carlo randomisation test incanonical correspondence analysis (CCA; CA-NOCO version 4.5, ter Braak and Smilauer 2002),and only variables significantly (a = 0.05) relatedto species composition were retained in the finalmodels. A series of three CCAs was then runseparately for snails and clams: species matrixconstrained by (1) both environmental and land-scape position variables (a + b + c, followingLegendre and Legendre (1998)), (2) environmentalvariables only (a + b), and (3) landscape positionvariables only (b + c). To obtain the amount ofexplained variation in each analysis, the sum ofcanonical eigenvalues was divided by total inertiaof the species data. Variation in species composi-tion was subsequently partitioned into fractions asfollows: shared environmental and landscape po-sition (b = (a + b) + (b + c)� (a + b + c)),pure environmental (a = (a + b)� (b)), purelandscape position (c = (b + c)� (b)), and unex-plained fractions (d = 1� (a + b + c)). CCAwas used because preliminary detrended corre-spondence analyses (DCA) implied unimodalresponses by species in both snail (DCA axis 1gradient length: 3.453) and fingernail clam (DCAaxis 1 gradient length: 2.873) data.

Linear regression analysis was employed forpartitioning variation in species richness amongthe local environment and landscape position

variables. Each group of explanatory variables wasfirst screened via forward stepwise regression toobtain a reduced set of significant (a = 0.05)variables for the final regression models. Speciesrichness of snails and fingernail clams was subse-quently regressed on (1) both environmental andlandscape position variables (a + b + c), (2)environmental variables only (a + b), and (3)landscape position variables only (b + c). The R2

values from these analyses were subsequently usedin partitioning the variation in species richnessamong shared environmental and landscape posi-tion, pure environmental, pure landscape position,and unexplained fractions as above (see Legendreand Legendre 1998; Boone and Krohn 2000).

Results

Snail species composition was significantly relatedto three environmental variables (in order ofimportance: hardness, conductivity, pH) in theforward selection of CCA. These variablestogether accounted for 33.8% of variation in snailassemblage composition, while the three mostimportant landscape variables (x, x2y, y3)accounted for 36.7% of the variation. Both vari-able groups together accounted for 53.6% of var-iation in snail species composition (Table 2).Variability in species composition was furtherpartitioned into pure environmental (16.9%),shared environmental and landscape (16.9%),pure landscape (19.8%), and unexplained fractions(46.4%) (Figure 2a).

Fingernail clam species composition was signif-icantly related to two environmental and threelandscape variables. The two environmental vari-ables (area, conductivity) accounted for 24.3% ofvariation, while the corresponding figure for thelandscape position variables (y3, y, DISTMAIN)was 39.6%. Both variable groups togetheraccounted for 48.2% of the variation (Table 2).Variability in fingernail clam species compositionwas partitioned among different fractions as fol-lows: pure environmental (8.6%), shared envi-ronmental and landscape (15.6%), pure landscape(23.9%), and unexplained (51.8%) fractions(Figure 2a).

Environmental variables (hardness, area, con-ductivity) accounted for 81.4%, and landscapeposition variables (DISTMAIN, y3, UPLAKES)

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88.8% of the variability in snail species richness.Both variable groups together accounted for95.5% of variation in snail species richness(Table 3). Variation was further partitioned intopure environmental (6.7%), shared environmentaland landscape (74.7%), pure landscape (14.1%),and unexplained (4.5%) fractions (Figure 2b).

For fingernail clams, environmental variables(conductivity, area) accounted for 37.0%, andlandscape position variables (y3, DISTMAIN)60.6% of variability in species richness. Bothvariable groups together accounted for 62.2% ofvariability in clam species richness (Table 3).Variation partitioning showed that pure environ-mental effects were weak (1.6%), and more

variability in clam species richness was related toshared environmental and landscape (35.4%),pure landscape (25.3%), and unexplained (37.8%)fractions (Figure. 2b).

Discussion

Community structure is affected by both localenvironmental factors (e.g., stress, predation) andregional processes (e.g., dispersal, connectivity),with the former filtering subsets of species to localcommunities, and the latter homogenising speciescomposition across landscapes. Influences of bothregional and local factors were also seen in our

Table 2. Results of canonical correspondence analysis for the species composition of snails and fingernail clams.

Snails Fingernail clams

Final model Variables

in the model

Variable

contribution

Final model Variables

in the model

Variable

contribution

Local environmental variables k = 0.500 Hardness 0.22 k = 0.313 Area 0.19

F = 2.565 Conductivity 0.36 F = 2.896 Conductivity 0.31

p = 0.001 pH 0.50 p = 0.001

R2 = 0.338 R2 = 0.243

Landscape position variables k = 0.542 x 0.21 k = 0.509 y3 0.26

F = 2.899 x2y 0.39 F = 3.708 y 0.38

p = 0.001 y3 0.54 p = 0.001 DISTMAIN 0.51

R2 = 0.367 R2 = 0.396

Both variable groups combined k = 0.792 k = 0.621

F = 2.315 F = 2.804

p = 0.001 p = 0.001

R2 = 0.536 R2 = 0.482

Shown are the sums of canonical eigenvalues (k) for each analysis: local environmental variables, landscape position variables, and

both variable groups together. Variable contribution (increase in k) includes that of the named variable and those preceding it. Total

inertia was 1.476 for snails and 1.286 for clams. Variation explained by each variable group (R2 values, in bold italics) was calculated

by dividing k with total inertia. Fractions of total variation attributable to local environment, shared local environment and landscape

position, landscape position, and unexplained components were determined by subtraction (see text and Figure 2a).

0

20

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Snails Clams

Unexplained

Pure L

Shared E and L

Pure E% v

aria

nce

0

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% v

aria

nce

Snails Clams

(a) (b)

Figure 2. Variation partitioning of the snail and fingernail clam assemblages between landscape position (L) and local environmental

factors (E): (a) species composition, (b) species richness. Shown are four fractions: pure environmental, shared environmental and

landscape position, pure landscape position, and unexplained variation.

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study, where landscape position and local envi-ronmental factors were both highly influential instructuring molluscan assemblages. However,much of the variability in molluscan assemblagecomposition and species richness was shared bythe two groups of variables, implying that land-scape position and local environmental variableswere highly correlated in these headwater lakes.This finding lends support to our hypotheses, andit is consistent with what is known about thelimnology of northern lake districts. Many recentstudies on regional limnology have stressed theintimate association between landscape positionand environmental conditions of lakes. Thus, lakeshigh in the landscape tend to be smaller and moreisolated, and have lower ionic concentrations andpH than lakes lower in the landscape (Kratz et al.1997; Riera et al. 2000). These are also key factorsin structuring biotic assemblages, ranging fromalgae and macrophytes to invertebrates and fish(Tonn and Magnuson 1982; Kratz et al. 1997;Lewis and Magnuson 2000; Quinlan et al. 2003).Such co-variation among landscape position andlocal conditions makes it difficult to infer the rel-ative importance of local and regional drivers ofassemblage structure. Our data also exhibited adistinct gradient in environmental conditionsalong the lake chains (including the single largelake), and this environmental gradient wasreflected in molluscan distributions. The highcontribution of the landscape component toassemblage composition and species richness may,

however, also be related to some unmeasuredenvironmental factors (e.g., macrophyte cover)that typically co-vary with landscape position.

Landscape position may also relate to theimportance of dispersal as a structuring agent ofmolluscan assemblages. Thus, we hypothesised thatlakes close to each other, or close to the large sourcelake, should share similar molluscan assemblages.Evidence for such a relationship was seen in thatspatial location was strongly related to snail speciescomposition, whereas both spatial location andlakescape position (DISTMAIN) were importantcorrelates of fingernail clam species composition(Table 2). Dispersal of freshwater snails and fin-gernail clams is presumed to be mainly passive,waterfowl being their main vectors (Aho 1978a;Boag 1986). Thus, waterfowl may tend to homog-enise molluscan species composition among adja-cent lakes. This mechanism, however, does not leadto completely homogenised faunas on threegrounds: (i) waterfowl abundance and speciesdiversity are correlated with lake characteristics(Nilsson and Nilsson 1978; Elmberg et al. 1993),and some lakes are thus likely to receive more col-onists than others (Aho 1978a); (ii) the frequency ofwaterfowl visits to a lake may be related to its iso-lation, although our study lakes were not likely veryisolated with regard to the potential daily move-ment distances of waterfowl (see Figuerola andGreen 2002); and (iii) local environmental variablesset an environmental filter, removing species thatarrive to an unsuitable lake. Furthermore, for snails

Table 3. Results of regression analyses for the species richness of snails and fingernail clams.

Snails Fingernail clams

Final model Variables

in the model

Cumulative

R2Final model Variables

in the model

Cumulative R2

Local environmental variables R2 = 0.814 Hardness 0.492 R2 = 0.370 Conductivity 0.197

F3, 15 = 21.864 Area 0.747 F2, 18 = 5.297 Area 0.370

p<0.001 Conductivity 0.814 p = 0.016

Landscape position variables R2 = 0.888 DISTMAIN 0.587 R2 = 0.606 y3 0.374

F3, 15 = 39.740 y3 0.793 F2, 18 = 13.832 DISTMAIN 0.606

p<0.001 UPLAKES 0.888 p<0.001

Both variable groups combined R2 = 0.955 R2 = 0.622

F6, 12 = 42.256 F4, 16 = 6.577

p<0.001 p = 0.002

Shown are results for analyses where species richness was modelled by local environmental variables, landscape position variables, and

both variable groups together. Individual variables for each variable group were selected via forward selection procedure, and

cumulative coefficient of determination (R2) includes the contribution of the named variable and those preceding it. Fractions of total

variation attributable to local environmental, shared local environmental and landscape position, landscape position, and unexplained

components were determined by subtraction based on R2 values of the final regression models (see text and Figure 2b).

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that also are capable of active dispersal, streamconnections may facilitate among-lake dispersal(Lewis and Magnuson 2000). If this dispersal routewas important in affecting the species compositionof snail assemblages in our study area, one wouldhave expected lakescape position variables (DIST-MAIN, UPLAKES, ALTITUDE) to be importantfor snails. However, none of the lakescape variablesappeared important for snail species compositionwhich was instead more closely related to spatialvariables.

The environmental variables (hardness, con-ductivity, lake area) that appeared important instructuring snail and fingernail clam assemblageshave often been found influential in other studieson lake-dwelling snails (Aho 1978b; Bronmark1985; Savage and Gazey 1987; Lewis andMagnuson 2000). For example, calcium concen-tration of lake water is known to relate strongly tothe distribution of snails at various scales (Briers2003 and references therein) and, given their lowcalcium level, most of our study lakes shouldrepresent non-optimal conditions for most snailspecies. Indeed, Aho (1978b) suggested that thecritical limit for the occurrence of many snailspecies is water hardness of 1.0 �dH or 7.1 mg Ca/l, a value slightly higher than the average value forour study lakes. Furthermore, conductivity relatesto lake productivity, and productivity likely affectsthe distributions of both algae-grazing snails andsuspension-feeding clams. It thus appears thatvariables related to extinction probability (area,productivity) and niche differences (calciumrequirements, abiotic stress) act as strong envi-ronmental filters, selecting subsets of species fromthose available in the regional species pool toco-occur in local assemblages.

As expected, species composition and speciesrichness of the molluscan assemblages showedpartly differing patterns. Although the relation-ships of these two assemblage characteristics tolocal environmental variables were rather similar,they were significantly related to partly differinglandscape variables. For snails, species composi-tion was more closely related to spatial positionthan to lakescape position of a lake, whereasalmost the reverse was true for species richness. Apotential reason for this discrepancy is that snailspecies composition of a lake is more affected bypassive dispersal processes mediated by waterfowlvisiting adjacent lakes, whereas species richness is

intimately linked to the presence of and distance topotential recolonisation sources. That is, shortdistance to a large source lake and position low ina lake chain are potentially important factors,buffering local extinctions through recurrent col-onisation, and thereby maintaining species rich-ness in local assemblages. A correspondingmechanism has been suggested for lake fishassemblages, and connections to other lakes areoften a prerequisite for maintaining fish species inlakes, where abiotic stress or predation has led tolocal extinctions (Tonn and Magnuson 1982;Olden et al. 2001).

Our study included only two groups of mainlypassively dispersing organisms, so any generalisa-tions to the distribution patterns of lake-dwellingorganisms in general are unjustified. Nevertheless,we might expect a decreasing role of local envi-ronmental control and increasing role of landscapeposition from organisms capable of active aerialdispersal (e.g., aquatic insects) to passive dispers-ers (e.g., snails and fingernail clams), and to thoserelying exclusively on stream connections foramong-lake dispersal (e.g., fish). Testing this ideawould require a simultaneous examination of dif-ferent groups of organisms across the same land-scape. Finally, we believe that studying therelationship between landscape position and lakeconditions is likely to be useful because it mayreveal the relative importance of local and regionalprocesses as factors shaping lake communities.

Acknowledgements

This study was supported by the Academy ofFinland (Grant No. 209196 to JH and Grant No.206151 to TM). We warmly acknowledge thecontributions of T. Lipasto at various stages of thework. Comments by three anonymous reviewersand T. Kratz are also acknowledged. We expressour sincere gratitude to a pioneering malacologist,Jorma Aho, who originally collected the materialused in this study.

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