Metacommunity Composition of Web-Spiders in a Fragmented Neotropical Forest: Relative Importance of Environmental and Spatial Effects

The distribution of beta diversity is shaped by factors linked to environmental and spatial control. The relative importance of both processes in structuring spider metacommunities has not yet been investigated in the Atlantic Forest. The variance explained by purely environmental, spatially structured environmental, and purely spatial components was compared for a metacommunity of web spiders. The study was carried out in 16 patches of Atlantic Forest in southern Brazil. Field work was done in one landscape mosaic representing a slight gradient of urbanization. Environmental variables encompassed plot- and patch-level measurements and a climatic matrix, while principal coordinates of neighbor matrices (PCNMs) acted as spatial variables. A forward selection procedure was carried out to select environmental and spatial variables influencing web-spider beta diversity. Variation partitioning was used to estimate the contribution of pure environmental and pure spatial effects and their shared influence on beta-diversity patterns, and to estimate the relative importance of selected environmental variables. Three environmental variables (bush density, land use in the surroundings of patches, and shape of patches) and two spatial variables were selected by forward selection procedures. Variation partitioning revealed that 15% of the variation of beta diversity was explained by a combination of environmental and PCNM variables. Most of this variation (12%) corresponded to pure environmental and spatially environmental structure. The data indicated that (1) spatial legacy was not important in explaining the web-spider beta diversity; (2) environmental predictors explained a significant portion of the variation in web-spider composition; (3) one-third of environmental variation was due to a spatial structure that jointly explains variation in species distributions. We were able to detect important factors related to matrix management influencing the web-spider beta-diversity patterns, which are probably linked to historical deforestation events.     

Effect of field sampling design on variation partitioning in a dendritic stream network

Variation partitioning is one of the most frequently used method to infer the importance of environmental (niche based) and spatial (dispersal) processes in metacommunity structuring. However, the reliability of the method in predicting the role of the major structuring forces is less known. We studied the effect of field sampling design on the result of variation partitioning of fish assemblages in a stream network. Along with four different sample sizes, a simple random sampling from a total of 115 stream segments (sampling objects) was applied in 400 iterations, and community variation of each random sample was partitioned into four fractions: pure environmentally (landscape variables) explained, pure spatially (MEM eigenvectors) explained, jointly explained by environment and space, and unexplained variance. Results were highly sensitive to sample size. Even at a given sample size, estimated variance fractions had remarkable random fluctuation, which can lead to inconsistent results on the relative importance of environmental and spatial variables on the structuring of metacommunities. Interestingly, all the four variance fractions correlated better with the number of the selected spatial variables than with any design properties. Sampling interval proved to be a fundamentally influential sampling design property because it affected the number of the selected spatial variables. Our findings suggest that the effect of sampling design on variation partitioning is related to the ability of the eigenvectors to model complex spatial patterns. Hence, properties of the sampling design should be more intensively considered in metacommunity studies.     

Multivariate analysis of a fine-scale breeding bird atlas using a geographical information system and partial canonical correspondence analysis: environmental and spatial effects

Aim To assess the relative roles of environment and space in driving bird species distribution and to identify relevant drivers of bird assemblage composition, in the case of a fine‐scale bird atlas data set. Location The study was carried out in southern Belgium using grid cells of 1 × 1 km, based on the distribution maps of the Oiseaux nicheurs de Famenne: Atlas de Lesse et Lomme which contains abundance for 103 bird species. Methods Species found in < 10% or > 90% of the atlas cells were omitted from the bird data set for the analysis. Each cell was characterized by 59 landscape metrics, quantifying its composition and spatial patterns, using a Geographical Information System. Partial canonical correspondence analysis was used to partition the variance of bird species matrix into independent components: (a) ‘pure’ environmental variation, (b) spatially‐structured environmental variation, (c) ‘pure’ spatial variation and (d) unexplained, non‐spatial variation. Results The variance partitioning method shows that the selected landscape metrics explain 27.5% of the variation, whilst ‘pure’ spatial and spatially‐structured environmental variables explain only a weak percentage of the variation in the bird species matrix (2.5% and 4%, respectively). Avian community composition is primarily related to the degree of urbanization and the amount and composition of forested and open areas. These variables explain more than half of the variation for three species and over one‐third of the variation for 12 species. Main conclusions The results seem to indicate that the majority of explained variation in species assemblages is attributable to local environmental factors. At such a fine spatial resolution, however, the method does not seem to be appropriated for detecting and extracting the spatial variation of assemblages. Consequently, the large amount of unexplained variation is probably because of missing spatial structures and ‘noise’ in species abundance data. Furthermore, it is possible that other relevant environmental factors, that were not taken into account in this study and which may operate at different spatial scales, can drive bird assemblage structure. As a large proportion of ecological variation can be shared by environment and space, the applied partitioning method was found to be useful when analysing multispecific atlas data, but it needs improvement to factor out all‐scale spatial components of this variation (the source of ‘false correlation’) and to bring out the ‘pure’ environmental variation for ecological interpretation.     

Freshwater biodiversity at regional extent: determinants of macroinvertebrate taxonomic richness in headwater streams

We studied spatial variation of macroinvertebrate species richness in headwater streams at two spatial extents, within and across drainage systems, and assessed the relative importance of three groups of variables (local, landscape and regional) at each extent. We specifically asked whether the same variables proposed to control broad‐scale richness patterns of terrestrial organisms (temperature, topographic variability) are important determinants of species richness also in streams, or whether environmental factors effective at mainly local scales (in‐stream heterogeneity, potential productivity) constrain species richness in local communities. We used forward selection with two stopping criteria to identify the key environmental and spatial variables at each study extent. Eigenvector‐based spatial filtering was applied to evaluate spatial patterns in species richness, and variation partitioning was used to assess the amount of variation in richness attributable to purely environmental and spatial components. A prime regulator of richness variation at the bioregion extent was elevation range (increasing richness with higher topographic variability), whereas hydrological stability and temperature were unimportant. Water chemistry variables, particularly water color, exhibited strong spatially‐structured variation across drainage systems. Local environmental variables explained most of the variation in species richness at the drainage‐system extent, reflecting gradients in total phosphorus and water color (negative effect on richness). The importance of the pure spatial component was strongly region‐dependent, with a peak (60%) in one drainage system, suggesting the presence of unmeasured environmental factors. Our results emphasize the need for spatially‐explicit, regional studies to better understand geographical variation of freshwater biodiversity. Future studies need to relate species richness not only to local factors but also to broad‐scale climatic variables, recognizing the presence of spatially‐structured environmental variation.     

A model of geographical, environmental and regional variation in vegetation composition of pyrogenic grasslands of Florida

Aim To develop a landscape‐level model that partitions variance in plant community composition among local environmental, regional environmental, and purely spatial predictive variables for pyrogenic grasslands (prairies, savannas and woodlands) throughout northern and central Florida. Location North and central Florida, USA. Methods We measured plant species composition and cover in 271 plots throughout the study region. A variation‐partitioning model was used to quantify components of variation in species composition associated with the main and interaction effects of soil and topographic variables, climate variables and spatial coordinates. Partial correlations of environmental variables with community variation were identified using direct gradient analysis (redundancy analysis and partial redundancy analysis) and Monte Carlo tests of significance. Results Community composition was most strongly related to edaphic variables at local scales in association with topographic gradients, although geographically structured edaphic, climatic and pure spatial effects were also evident. Edaphic variables explained the largest portion of total variation explained (TVE) as a main effect (48%) compared with the main effects of climate (9%) and pure spatial factors (9%). The remaining TVE was explained by the interaction effect of climate and spatial factors (13%) and the three‐way interaction (22%). Correlation analyses revealed that the primary compositional gradient was related to soil fertility and topographic position corresponding to soil moisture. A second gradient represented distinct geographical separation between the Florida panhandle and peninsular regions, concurrent with differences in soil characteristics. Gradients in composition corresponded to species richness, which was lower in the Florida peninsula. Main conclusions Environmental variables have the strongest influence on the species composition of Florida pyrogenic grasslands at both local and regional scales. However, the limited distributions of many plant taxa suggest historical constraints on species distributions from one physiographical region to the other (Florida panhandle and peninsula), although this pattern is partially confounded by regionally spatially structured environmental variables. Our model provides insight into the relative importance of local‐ and regional‐scale environmental effects as well as possible historical constraints on floristic variation in pine‐dominated pyrogenic grasslands of the south‐eastern USA.     

The influence of environmental factors on the spatial distribution of saxicolous lichens in a Norwegian coastal community

Abstract. The effects of vegetation cover, radiation, micro‐habitat variables and maritime influence on the floristic composition of a saxicolous community in Vingen, western Norway were studied. Particular emphasis is put on the local distribution of Fuscidea cyathoides, Ochrolechia tartarea, Ophioparma ventosa and Pertusaria corallina. Very little of the variation in the lichen community composition is directly related to measured micro‐environmental variables but variance partitioning shows that vegetation cover explains more of the floristic variation than radiation, maritime influence and microhabitat variables. Logistic regression analyses nevertheless indicate that the micro‐environment influences the spatial distribution of the four species. The high fraction of unexplained floristic variation, 91%, is suggested to result from (1) lack of fit of data to the response model; (2) some influential environmental variables that have not been recorded; (3) local historical factors that affect present day distribution and/or (4) apparent randomness in colonization. The results also agree with the view that the four lichen species in this study are able to co‐exist in the long‐term because of different spatial distributions resulting from different strategies with respect to ecology, dispersion and interaction.     

环境筛选和扩散限制在地表和地下螨群落物种共存中的调控作用

识别扩散限制和环境筛选在群落物种共存中的相对作用,是土壤动物群落物种共存机制研究的重要内容,然而少有针对地表和地下土壤动物群落的探讨。在三江平原农田生态系统,设置一个50 m×50 m的空间尺度,探讨环境筛选和扩散限制对地表和地下土壤螨群落物种共存的调控作用。基于Moran特征向量图(MEMs)和变差分解的方法来区分环境筛选和扩散限制的调控作用;采用偏Mantel检验进一步分析环境距离和空间距离的相对贡献;使用RDA分析环境因子对螨群落物种组成的解释能力。变差分解结果表明,空间变量对地表、地下和地表-地下土壤螨群落具有较大的显著方差解释量,而环境变量和空间环境结构的解释量相对较小且不显著;偏Mantel检验没有发现环境距离或空间距离的显著贡献;RDA分析表明土壤p H值、大豆株高和土壤含水量对土壤螨群落具有显著的解释能力,说明环境变量对螨群落物种组成的重要作用。研究表明,在三江平原农田生态系统,地表和地下土壤螨群落物种共存主要受到扩散限制的调控作用,同时环境筛选的调控作用也不容忽视。     

Biodiversity of stream insects in the Malaysian Peninsula: spatial patterns and environmental constraints

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Disentangling the roles of spatial and environmental variables in shaping benthic algal assemblages in rivers of central and northern China

Benthic algae were collected from central and northern Chinese rivers to test the hypothesis that geographic location has significant contributions in shaping algal assemblages. We used Moran’s eigenvector maps (MEM) to model spatial components and variation partitioning to quantify the influences of spatial and environmental variables on regional patterns of algal richness and community composition, respectively. We found that variation in algal richness was attributed to MEM component 2, 8, and 9 and the quadratic term of N–NO₃. Regarding abundance data, latitude, longitude, and MEM component 1, 2, and 7 were important spatial variables. Although P–PO₄, pH, and annual mean temperature were significant environmental variables influencing algal community composition, they were all spatially structured. Among the total explained variance in both algal metrics, spatial proportions were higher than that of environmental variables. We also found that abundant species of Achnanthidium minutissimum, Cocconeis placentula, Cymbella delicatula, Cymbella affinis, Cymbella turgidula, and Synedra ulna displayed clear spatially related patterns. In conclusion, the contributions of spatial and environmental variables to regional variation of algal assemblages are scale-dependent. As for our study scale (~1,000 km), spatial control may be more important. Since spatial effects could obscure local environmental impacts on algal communities, appropriate study scale and statistical methods should be taken into account in algal bioassessment. We recommend inclusion of both algal richness and community composition in study of algal biogeography, due to their different relationships with spatial and environmental variables.     

Modelling spatial and environmental effects at the edge of the distribution: the red-backed shrike Lanius collurio in Northern Portugal

This study examined the interplay of spatial and environmental effects shaping the range margin of the red‐backed shrike (Lanius collurio) in northern Portugal. The occurrence of shrikes in 10 × 10 km UTM squares was related to three sets of explanatory variables, reflecting environmental effects (climate and habitat), large‐scale spatial trends, and neighbourhood influences (considering an autologistic term); spatial variables were used as surrogates for historical and demographic factors. Multiple logistic regression models were built for each set, and then variation partitioning based on partial regressions isolated the unique and shared components of explained variation. The environmental model revealed a dominant influence of climate effects, with the occurrence of shrikes increasing with frost and thermal amplitude, declining with insolation, and responding unimodally to rainfall. There was a weaker influence of habitat conditions, though shrikes were more likely with increasing cover by annual crops and pastures, and decreasing forest cover. Only a relatively small proportion of explained variation was due to a ‘pure’ environmental component (10.4%), as most variation explained by environmental factors appeared spatially structured (51.9%). The unique contributions of spatial variables to the overall model were also small, though the neighbourhood effects appeared relatively stronger than large‐scale trends. Taken together, results suggested that the south‐western range margin of the red‐backed shrike was largely determined by spatially structured environmental factors. Nevertheless, there were also ‘pure’ environmental factors determining some isolate occurrences irrespective of any spatial structure, and ‘pure’ spatial factors that appeared to favour the occupation of squares surrounding the core distribution areas irrespective of environmental conditions. These results add to the growing evidence that both environmental and spatial factors need to be considered in predictive modelling of species range margins.     

Partitioning the variation among spatial,temporal and environmental components in a multivariate data set

Abstract We propose a method of partitioning the variation in a multivariate set of data according to (i) environmental variables, (ii) variables describing the spatial structure in the data and (iii) temporal variables. This method is an extension of an existing method for partialling out the spatial component of environmental variation, using canonical analysis. Our proposed method extends this approach by including temporal variables in the analysis. Thus, the partitioning of variation for a data matrix of species’abundances or biomass can include, by our methodology, the following components: (1) pure environmental, (2) pure spatial, (3) pure temporal, (4) pure spatial component of environmental, (5) pure temporal component of environmental, (6) pure combined spatial/temporal component, (7) combined spatial/temporal component of environmental and (8) unexplained. In addition, permutation testing accompanying the analyses allows tests of significance for the relationship between the different components and the species data. We illustrate the method with a set of survey data of penaeid species (prawns) obtained on the far northern Great Barrier Reef, Australia. This extension is a useful tool for multivariate analysis of ecological data from surveys, where space, time and environment commonly overlap and are important influences on observed variation.     

Relative importance of environment, human activity and spatial situation in determining the distribution of terrestrial mammal diversity in Argentina

Aim The partition of the geographical variation in Argentinian terrestrial mammal species richness (SR) into environmentally, human and spatially induced variation. Location Argentina, using the twenty‐three administrative provinces as the geographical units. Methods We recorded the number of terrestrial mammal species in each Argentinian province, and the number of species belonging to particular groups (Marsupialia, Placentaria, and among the latter, Xenarthra, Carnivora, Ungulates and Rodentia). We performed multiple regressions of each group's SR on environmental, human and spatial variables, to determine the amounts of variation explained by these factors. We then used a variance partitioning procedure to specify which proportion of the variation in SR is explained by each of the three factors exclusively and which proportions are attributable to interactions between factors. Results For marsupials, human activity explains the greatest part of the variation in SR. The purely environmental and purely human influences on all mammal SR explain a similarly high proportion of the variation in SR, whereas the purely spatial influence accounts for a smaller proportion of it. The exclusive interaction between human activity and space is negative in carnivores and rodents. For rodents, the interaction between environment and spatial situation is also negative. In the remaining placental groups, pure spatial autocorrelation explains a small proportion of the variation in SR. Main conclusions Environmental factors explain most of the variation in placental SR, while Marsupials seem to be mainly affected by human activity. However, for edentates, carnivores, and ungulates the pure human influence is more important than the pure spatial and environmental influences. Besides, human activity disrupts the spatial structure caused by the history and population dynamics of rodents and, to a lesser extent, of carnivores. The historical events and population dynamics on the one hand, and the environment on the other, cause rodent SR to vary in divergent directions. In the remaining placental groups the autocorrelation in SR is mainly the result of autocorrelation in the environmental and human variables.     

Fine spatial grain,large spatial extent and biogeography of macrophyte‐associated cladoceran communities across Neotropical floodplains

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Scale specific determinants of tree diversity in an old growth temperate forest in China

The major processes generating pattern in plant community composition depend upon the spatial scale and resolution of observation, therefore understanding the role played by spatial scale on species patterns is of major concern. In this study, we investigate how well environmental (topography and soil variables) and spatial variables explain variation in species composition in a 25-ha temperate forest in northeastern China. We used new variation partitioning approaches to discover the spatial scale (using multi-scale spatial PCNM variables) at which environmental heterogeneity and other spatially structured processes influence tree community composition. We also test the effect of changing grain of the study (i.e. quadrat size) on the variation partitioning results. Our results indicate that (1) species composition in the Changbai mixed broadleaf-conifer forest was controlled mainly by spatially structured soil variation at broad scales, while at finer scales most of the explained variation was of a spatial nature, pointing to the importance of biotic processes. (2) These results held at all sampling grains. However, reducing quadrat size progressively reduced both spatially and environmentally explained variance. This probably partly reflects increasing stochasticity in species abundances, and the smaller proportion of quadrats occupied by each species, when quadrat size is reduced. The results suggest that environmental heterogeneity (i.e. niche processes) and other biotic processes such as dispersal work together, but at different spatial scales, to build up diversity patterns.     

Geographical ecology of Paraguayan bats: spatial integration and metacommunity structure of interacting assemblages

We examined the relative contributions of regional spatial characteristics and local environmental conditions in determining Paraguayan bat species composition. We used a suite of full and partial redundancy analyses to estimate four additive partitions of variance in bat species composition: (a) unexplained variation, (b) that explained purely by spatial characteristics, (c) that explained purely by local environmental conditions and (d) that explained jointly by space and environment. The spatial component to bat species composition was greater than the environmental component and both pure spatial and pure environmental characteristics accounted for significant amounts of variation in bat species composition. Results from variance decomposition suggest that the mass effects model describes metacommunity structure of Paraguayan bats better than species sorting or neutral models. Such mass effects may potentially be general for bats and could explain the inability of purely local factors to fully account for bat community organization. Mass effects also have substantial conservation implications because rescue effects may enhance the persistence of mobile species in fragmented landscapes with relatively few protected sites.     

Spatial and environmental determinants of vascular plant species richness distribution in the Iberian Peninsula and Balearic Islands

Using an exhaustive data compilation, Iberian vascular plant species richness in 50 times 50 UTM grid cells was regressed against 24 explanatory variables (spatial, geographical, topographical, geological, climatic, land use and environmental diversity variables) using Generalized Linear Models and partial regression analysis in order to ascertain the relative contribution of primary, heterogeneous and spatially structured variables. The species richness variation accounted for by these variables is reasonably high (65% of total deviance). Little less than half of this variation is accounted for spatially structured variables. A purely spatial component of variation is hardly significant. The most significant variables are those related to altitude, and particularly maximum altitude, whose cubic response reflects the occurrence of the maximum number of species at the highest altitudes. This result highlighted the importance of Iberian mountains as hotspots of diversity and the relevance of large and small scale historical factors in contemporary plant distribution patterns. Climatic or energy-related variables contributed little, whereas geological (calcareous and acid rocks) and, to a lesser extent, environmental heterogeneity variables (land use diversity and altitude range) seem to be more important.     

Spatial, environmental and human influences on the distribution of otter (Lutra lutra) in the Spanish provinces

In a previous survey of otters (Lutra lutra L. 1758) in Spain, different causes were invoked to explain the frequency of the species in each province. To find common causes of the distribution of the otter in Spain, we recorded a number of spatial, environmental and human variables in each Spanish province. We then performed a stepwise linear multiple regression of the proportion of positive sites of otter in the Spanish provinces separately on each of the three groups of variables. Geographic longitude, January air humidity, soil permeability and highway density were the variables selected. A linear regression of the proportion of otter presence on these variables explained 62.4% of the variance. We then used the selected variables in a partial regression analysis to specify which proportions of the variation are explained exclusively by spatial, environmental and human factors, and which proportions are attributable to interactions between these components. Pure environmental effects accounted for only 5.5% of the variation, while pure spatial and pure human effects explained 18% and 9.7%, respectively. Shared variation among the components totalled 29.2%, of which 10.9% was explained by the interaction between environmental and spatial factors. Human factors explained globally less variance than spatial and environmental ones, but the pure human influence was higher than the pure environmental one. We concluded that most of the variation in the proportion of occurrences of otter in Spanish provinces is spatially structured, and that environmental factors have more influence on otter presence than human ones; however, the human influence on otter distribution is less structured in space, and thus can be more disruptive. This effect of large infrastructures on wild populations must be taken into account when planning large‐scale conservation policies.     

Importance of spatial autocorrelation in modeling bird distributions at a continental scale

Spatial autocorrelation in species' distributions has been recognized as inflating the probability of a type I error in hypotheses tests, causing biases in variable selection, and violating the assumption of independence of error terms in models such as correlation or regression. However, it remains unclear whether these problems occur at all spatial resolutions and extents, and under which conditions spatially explicit modeling techniques are superior. Our goal was to determine whether spatial models were superior at large extents and across many different species. In addition, we investigated the importance of purely spatial effects in distribution patterns relative to the variation that could be explained through environmental conditions. We studied distribution patterns of 108 bird species in the conterminous United States using ten years of data from the Breeding Bird Survey. We compared the performance of spatially explicit regression models with non-spatial regression models using Akaike's information criterion. In addition, we partitioned the variance in species distributions into an environmental, a pure spatial and a shared component. The spatially-explicit conditional autoregressive regression models strongly outperformed the ordinary least squares regression models. In addition, partialling out the spatial component underlying the species' distributions showed that an average of 17% of the explained variation could be attributed to purely spatial effects independent of the spatial autocorrelation induced by the underlying environmental variables. We concluded that location in the range and neighborhood play an important role in the distribution of species. Spatially explicit models are expected to yield better predictions especially for mobile species such as birds, even in coarse-grained models with a large extent.     

Environmental and spatial variables influence the composition of frog assemblages in sub-tropical eastern Australia

In community ecology, contrasting theories suggest that the distribution and abundance of species, and thus the composition of assemblages, are influenced by i) environmental gradients, or ii) contagious biotic processes such as predation, competition, dispersal and disease. In the former case, sites with similar environments would tend to support similar assemblages, while in the latter, geographically proximate sites would tend to support more similar assemblages than widely separated sites. I investigated the relative influence of environmental variables and spatial position on the composition of frog assemblages at forest streams in sub-tropical eastern Australia using redundancy analysis (RDA) and partial RDA. Data on the maximum abundance of the frog species at 65 survey sites were transformed such that RDA would yield the Hellinger distance between sites. The following analysis identified 11 environmental variables that explained 45% of the variation in the abundance of species at the survey sites (the species matrix), as a proportion of total variance. The geographic co-ordinates of the survey sites accounted for 12%, while the environmental and spatial variables combined accounted for 47% of the variation in the species matrix. Partial redundancy analysis indicated that of the explained variation, 74% was purely environmental, 5% was purely spatial and 21% was spatial environmental variation. This study is the first to quantify the relative influence of environmental and spatial variables on the composition of amphibian assemblages. It provides support for both the environmental control model and the biotic control model of species' distributions and assemblage composition, although environmental variables appear to have the greater effect at this scale of analysis.