The spatial structure of variation in salamander survival,body condition and morphology in a headwater stream network

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Multilevel landscape utilization of the Siberian flying squirrel: Scale effects on species habitat use

Animals use and select habitat at multiple hierarchical levels and at different spatial scales within each level. Still, there is little knowledge on the scale effects at different spatial levels of species occupancy patterns. The objective of this study was to examine nonlinear effects and optimal‐scale landscape characteristics that affect occupancy of the Siberian flying squirrel, Pteromys volans, in South‐ and Mid‐Finland. We used presence–absence data (n = 10,032 plots of 9 ha) and novel approach to separate the effects on site‐, landscape‐, and regional‐level occupancy patterns. Our main results were: landscape variables predicted the placement of population patches at least twice as well as they predicted the occupancy of particular sites; the clear optimal value of preferred habitat cover for species landscape‐level abundance is a surprisingly low value (10% within a 4 km buffer); landscape metrics exert different effects on species occupancy and abundance in high versus low population density regions of our study area. We conclude that knowledge of regional variation in landscape utilization will be essential for successful conservation of the species. The results also support the view that large‐scale landscape variables have high predictive power in explaining species abundance. Our study demonstrates the complex response of species occurrence at different levels of population configuration on landscape structure. The study also highlights the need for data in large spatial scale to increase the precision of biodiversity mapping and prediction of future trends.     

What's your move? Movement as a link between personality and spatial dynamics in animal populations

Recent studies have established the ecological and evolutionary importance of animal personalities. Individual differences in movement and space‐use, fundamental to many personality traits (e.g. activity, boldness and exploratory behaviour) have been documented across many species and contexts, for instance personality‐dependent dispersal syndromes. Yet, insights from the concurrently developing movement ecology paradigm are rarely considered and recent evidence for other personality‐dependent movements and space‐use lack a general unifying framework. We propose a conceptual framework for personality‐dependent spatial ecology. We link expectations derived from the movement ecology paradigm with behavioural reaction‐norms to offer specific predictions on the interactions between environmental factors, such as resource distribution or landscape structure, and intrinsic behavioural variation. We consider how environmental heterogeneity and individual consistency in movements that carry‐over across spatial scales can lead to personality‐dependent: (1) foraging search performance; (2) habitat preference; (3) home range utilization patterns; (4) social network structure and (5) emergence of assortative population structure with spatial clusters of personalities. We support our conceptual model with spatially explicit simulations of behavioural variation in space‐use, demonstrating the emergence of complex population‐level patterns from differences in simple individual‐level behaviours. Consideration of consistent individual variation in space‐use will facilitate mechanistic understanding of processes that drive social, spatial, ecological and evolutionary dynamics in heterogeneous environments.     

How do similarities in spatial distributions and interspecific associations affect the coexistence of Quercus species in the Baotianman National Nature Reserve,Henan, China

Congeneric species often have similar ecological characteristics and use similar resources. These similarities may make it easier for them to co‐occur in a similar habitat but may also lead to strong competitions that limit their coexistence. Hence, how do similarities in congeneric species affect their coexistence exactly? This study mainly used spatial point pattern analysis in two 1 hm² plots in the Baotianman National Nature Reserve, Henan, China, to compare the similarities in spatial distributions and interspecific associations of Quercus species. Results revealed that Quercus species were all aggregated under the complete spatial randomness null model, and aggregations were weaker under the heterogeneous Poisson process null model in each plot. The interspecific associations of Quercus species to non‐Quercus species were very similar in Plot 1. However, they can be either positive or negative in different plots between the co‐occurring Quercus species. The spatial distributions of congeneric species, interspecific associations with non‐Quercus species, neighborhood richness around species, and species diversity were all different between the two plots. We found that congeneric species did have some similarities, and the closely related congeneric species can positive or negative associate with each other in different plots. The co‐occurring congeneric species may have different survival strategies in different habitats. On the one hand, competition among congenerics may lead to differentiation in resource utilization. On the other hand, their similar interspecific associations can strengthen their competitive ability and promote local exclusion to noncongeneric species to obtain more living space. Our results provide new knowledge for us to better understand the coexistence mechanisms of species.     

Differences in prey personality mediate trophic cascades

Functional trait approaches in ecology chiefly assume the mean trait value of a population adequately predicts the outcome of species interactions. Yet this assumption ignores substantial trait variation among individuals within a population, which can have a profound effect on community structure and function. We explored individual trait variation through the lens of animal personality to test whether among‐individual variation in prey behavior mediates trophic interactions. We quantified the structure of personalities within a population of generalist grasshoppers and examined, through a number of field and laboratory‐based experiments, how personality types could impact tri‐trophic interactions in a food chain. Unlike other studies of this nature, we used spatial habitat domains to evaluate how personality types mechanistically map to behaviors relevant in predator–prey dynamics and found shy and bold individuals differed in both their habitat use and foraging strategy under predation risk by a sit‐and‐wait spider predator. In the field‐based mesocosm portion of our study, we found experimental populations of personality types differed in their trophic impact, demonstrating that prey personality can mediate trophic cascades. We found no differences in respiration rates or body size between personality types used in the mesocosm experiment, indicating relative differences in trophic impact were not due to variation in prey physiology but rather variation in behavioral strategies. Our work demonstrates how embracing the complexity of individual trait variation can offer mechanistically richer understanding of the processes underlying trophic interactions.     

Can niche‐based distribution models outperform spatial interpolation?

Aim Distribution modelling relates sparse data on species occurrence or abundance to environmental information to predict the population of a species at any point in space. Recently, the importance of spatial autocorrelation in distributions has been recognized. Spatial autocorrelation can be categorized as exogenous (stemming from autocorrelation in the underlying variables) or endogenous (stemming from activities of the organism itself, such as dispersal). Typically, one asks whether spatial models explain additional variability (endogenous) in comparison to a fully specified habitat model. We turned this question around and asked: can habitat models explain additional variation when spatial structure is accounted for in a fully specified spatially explicit model? The aim was to find out to what degree habitat models may be inadvertently capturing spatial structure rather than true explanatory mechanisms. Location We used data from 190 species of the North American Breeding Bird Survey covering the conterminous United States and southern Canada. Methods We built 13 different models on 190 bird species using regression trees. Our habitat‐based models used climate and landcover variables as independent variables. We also used random variables and simulated ranges to validate our results. The two spatially explicit models included only geographical coordinates or a contagion term as independent variables. As another angle on the question of mechanism vs. spatial structure we pitted a model using related bird species as predictors against a model using randomly selected bird species. Results The spatially explicit models outperformed the traditional habitat models and the random predictor species outperformed the related predictor species. In addition, environmental variables produced a substantial R² in predicting artificial ranges. Main conclusions We conclude that many explanatory variables with suitable spatial structure can work well in species distribution models. The predictive power of environmental variables is not necessarily mechanistic, and spatial interpolation can outperform environmental explanatory variables.     

Local dispersal can facilitate coexistence in the presence of permanent spatial heterogeneity

Abstract In the presence of permanent spatial heterogeneity, local dispersal, especially short‐range dispersal, can facilitate coexistence by concentrating low‐density species in the areas where their rates of increase are higher. We present a framework for predicting the effects of local dispersal on coexistence for arbitrary forms of dispersal and arbitrary spatial patterns of environmental variation. Using the lottery model as an example, we find that local dispersal contributes to coexistence by enhancing the effects of environmental variation on scales longer than typical dispersal distances, which can be characterized solely by the variance of the dispersal kernel. Higher moments of the dispersal kernel are not important.     

Why do some species have geographically varying responses to fire history?

A capacity to predict the effects of fire on biota is critical for conservation in fire‐prone regions as it assists managers to anticipate the outcomes of different approaches to fire management. The task is complicated because species’ responses to fire can vary geographically. This poses challenges, both for conceptual understanding of post‐fire succession and fire management. We examine two hypotheses for why species may display geographically varying responses to fire. 1) Species’ post‐fire responses are driven by vegetation structure, but vegetation – fire relationships vary spatially (the ‘dynamic vegetation’ hypothesis). 2) Regional variation in ecological conditions leads species to select different post‐fire ages as habitat (the ‘dynamic habitat’ hypothesis). Our case study uses data on lizards at 280 sites in a ～ 100 000 km² region of south‐eastern Australia. We compared the predictive capacity of models based on 1) habitat associations, with models based on 2) fire history and vegetation type, and 3) fire history alone, for four species of lizards. Habitat association models generally out‐performed fire history models in terms of predictive capacity. For two species, habitat association models provided good discrimination capacity even though the species showed geographically varying post‐fire responses. Our results support the dynamic vegetation hypothesis, that spatial variation in relationships between fire and vegetation structure results in regional variation in fauna–fire relationships. These observations explain how the widely recognised ‘habitat accommodation’ model of animal succession can be conceptually accurate yet predictively weak.     

At what spatial scales does resource selection vary? A case study of koalas in a semi‐arid region

The conservation of any species requires understanding and predicting the distribution of its habitat and resource use, including the effects of scale‐dependent variation in habitat and resource quality. Consequently, testing for resource selection at the appropriate scales is critical. We investigated how the resource selection process varies across scales, using koalas in a semi‐arid landscape of eastern Australia as a case study. We asked: at what scales does tree selection by koalas vary across regions? We tested the importance of the variation of our ecological predictors at the following scales: (i) the site‐scale (a stand of trees representing an individual koala's perception of local habitat); (ii) the landscape‐scale (10 × 10 km area representing a space within which a population of koalas exists); and (iii) a combination of these scales. We used a mixed‐modelling approach to quantify variation in selection of individual trees by koalas among sites and landscapes within a 1600 km² study area. We found that tree species, and tree height, were the most important factors influencing tree selection, and that their effect did not vary across scales. In contrast, preferences for trees of different condition, which is the state of tree canopy health, did vary across landscapes, indicating spatial variation in the selection of trees with respect to tree condition at the landscape‐scale, but not at the site‐scale. We conclude that resource selection processes can depend on the quality of those resources at different scales and their heterogeneous nature across landscapes, highlighting the consequence of scale‐dependent ecological processes. Designing studies that capture the heterogeneity in habitat and resources used by species that have an extensive distribution is an important prerequisite for effective conservation planning and management.     

From sampling stations to archipelagos: investigating aspects of the assemblage of insular biota

Aim To investigate the formation of nestedness and species co‐occurrence patterns at the local (sampling station), the intermediate (island group), and the archipelago scale. Location The study used data on the distribution of terrestrial isopods on 20 islands of the central Aegean (Greece). These islands are assigned to two distinct subgroups (Kyklades and Eastern islands). Methods The Nestedness Temperature Calculator was used to obtain nestedness values and maximally nested matrices, the EcoSim7 software and a modified version of Sanderson (2000 ) method were used for the analysis of species co‐occurrences. Idiosyncratic temperatures of species and the order of species placement in the maximally nested matrices were used for further comparisons among spatial scales. The relationships of nestedness values with beta‐diversity, habitat diversity and a number of ecological factors recorded for each sampling station were also investigated. Results Significant nestedness was found at all spatial scales. Levels of nestedness were not related to beta‐diversity or habitat diversity. Nestedness values were similar among spatial scales, but they were affected by matrix size. The species that contributed most to the nested patterns within single islands were not the same as those that produce nestedness at the archipelago scale. There was significant variation in the frequency of species occurrence among islands and among spatial scales. There was no direct effect of ecological factors on the shaping of patterns of nestedness within individual islands, but habitat heterogeneity was crucial for the existence of such patterns. Positive associations among species prevailed at all scales when species per station were considered, while negative associations prevailed in the species per island matrices. All associations resulted from the habitat structure of sampling stations and from particularities of geographical distributions. Conclusions There was no clear‐cut distinction between nestedness patterns among spatial scales, even though different species, and partially different factors, contributed to the formation of these patterns in each case. There was a core of species that contributed to the formation of nested patterns at all spatial scales, while the patterns of species associations suggested that biotic interactions are not an important causal factor. The results of this study suggest that locally rare species cannot be widespread at a higher spatial scale, while locally common species can have a restricted distribution.     

Adult survival and reproductive rate are linked to habitat preference in territorial,year‐round resident Song Sparrows Melospiza melodia

Individual animal fitness can be strongly influenced by the ability to recognize habitat features which may be beneficial. Many studies focus on the effects of habitat on annual reproductive rate, even though adult survival is typically a greater influence on fitness and population growth in vertebrate species with intermediate to long lifespans. Understanding the effects of preferred habitat on individuals over the annual cycle is therefore necessary to predict its influences on individual fitness. This is particularly true in species that are resident and territorial year‐round in the temperate zone, which may face potential trade‐offs between habitat that maximizes reproduction and that which maximizes non‐breeding season (‘over‐winter’) survival. We used a 37‐year study of Song Sparrows Melospiza melodia residing territorially year‐round on a small island to examine what habitat features influenced adult over‐winter survival, how site‐specific variation in adult survival vs. annual reproductive rate influenced long‐term habitat preference, and if preferred sites on average conferred higher individual fitness. Habitat features such as area of shrub cover and exposure to intertidal coastline predicted adult over‐winter survival independent of individual age or sex, population size, or winter weather. Long‐term habitat preference (measured as occupation rate) was better predicted by site‐specific annual reproductive rate than by expected over‐winter survival, but preferred sites maximized fitness on average over the entire annual cycle,. Although adult over‐winter survival had a greater influence on population growth (λ) than did reproductive rate, the influence of reproductive rate on λ increased in preferred sites because site‐specific variation in reproductive rate was higher than variation in expected over‐winter survival. Because preferred habitats tended to have higher mean site‐specific reproductive and adult survival rates, territorial birds in this population do not appear to experience seasonal trade‐offs in preferred habitat but are predicted to incur substantial fitness costs of settling in less‐preferred sites.     

Trophic disruption: a meta‐analysis of how habitat fragmentation affects resource consumption in terrestrial arthropod systems

Habitat fragmentation is a complex process that affects ecological systems in diverse ways, altering everything from population persistence to ecosystem function. Despite widespread recognition that habitat fragmentation can influence food web interactions, consensus on the factors underlying variation in the impacts of fragmentation across systems remains elusive. In this study, we conduct a systematic review and meta‐analysis to quantify the effects of habitat fragmentation and spatial habitat structure on resource consumption in terrestrial arthropod food webs. Across 419 studies, we found a negative overall effect of fragmentation on resource consumption. Variation in effect size was extensive but predictable. Specifically, resource consumption was reduced on small, isolated habitat fragments, higher at patch edges, and neutral with respect to landscape‐scale spatial variables. In general, resource consumption increased in fragmented settings for habitat generalist consumers but decreased for specialist consumers. Our study demonstrates widespread disruption of trophic interactions in fragmented habitats and describes variation among studies that is largely predictable based on the ecological traits of the interacting species. We highlight future prospects for understanding how changes in spatial habitat structure may influence trophic modules and food webs.     

In the absence of a “landscape of fear”: How lions,hyenas, and cheetahs coexist

Aggression by top predators can create a “landscape of fear” in which subordinate predators restrict their activity to low‐risk areas or times of day. At large spatial or temporal scales, this can result in the costly loss of access to resources. However, fine‐scale reactive avoidance may minimize the risk of aggressive encounters for subordinate predators while maintaining access to resources, thereby providing a mechanism for coexistence. We investigated fine‐scale spatiotemporal avoidance in a guild of African predators characterized by intense interference competition. Vulnerable to food stealing and direct killing, cheetahs are expected to avoid both larger predators; hyenas are expected to avoid lions. We deployed a grid of 225 camera traps across 1,125 km² in Serengeti National Park, Tanzania, to evaluate concurrent patterns of habitat use by lions, hyenas, cheetahs, and their primary prey. We used hurdle models to evaluate whether smaller species avoided areas preferred by larger species, and we used time‐to‐event models to evaluate fine‐scale temporal avoidance in the hours immediately surrounding top predator activity. We found no evidence of long‐term displacement of subordinate species, even at fine spatial scales. Instead, hyenas and cheetahs were positively associated with lions except in areas with exceptionally high lion use. Hyenas and lions appeared to actively track each, while cheetahs appear to maintain long‐term access to sites with high lion use by actively avoiding those areas just in the hours immediately following lion activity. Our results suggest that cheetahs are able to use patches of preferred habitat by avoiding lions on a moment‐to‐moment basis. Such fine‐scale temporal avoidance is likely to be less costly than long‐term avoidance of preferred areas: This may help explain why cheetahs are able to coexist with lions despite high rates of lion‐inflicted mortality, and highlights reactive avoidance as a general mechanism for predator coexistence.     

Individual phenotypic variation reduces interaction strengths in a consumer–resource system

Natural populations often show variation in traits that can affect the strength of interspecific interactions. Interaction strengths in turn influence the fate of pairwise interacting populations and the stability of food webs. Understanding the mechanisms relating individual phenotypic variation to interaction strengths is thus central to assess how trait variation affects population and community dynamics. We incorporated nonheritable variation in attack rates and handling times into a classical consumer–resource model to investigate how variation may alter interaction strengths, population dynamics, species persistence, and invasiveness. We found that individual variation influences species persistence through its effect on interaction strengths. In many scenarios, interaction strengths decrease with variation, which in turn affects species coexistence and stability. Because environmental change alters the direction and strength of selection acting upon phenotypic traits, our results have implications for species coexistence in a context of habitat fragmentation, climate change, and the arrival of exotic species to native ecosystems.     

Mechanisms of species coexistence: a field test of theoretical models using intertidal snails

Competitor coexistence is often facilitated by spatial segregation. Traditionally, spatial segregation is predicted to occur when species differ in the habitat in which they are either superior at competing for resources or less susceptible to predation. However, predictions from a behavioural model demonstrate that spatial segregation and coexistence can also occur in the absence of such interspecific trade‐offs in competitive ability and vulnerability to predation. Unlike other models of competitor coexistence this model predicts that when species rank both habitat productivity and ‘riskinesses’ similarly, but differ slightly in their habitat‐specific vulnerabilities to predators, they will tend to segregate across habitats, with the species experiencing the higher ratio of mortality risk across the habitats occurring primarily in the safer habitat. Here, we investigate the hypothesis that intraspecific trade‐offs between resource availability and mortality risk can lead to spatial segregation of competing species by (1) documenting the spatial (i.e. intertidal) distribution of two marine snails, Littorina sitkana and L. subrotundata and (2) performing field experiments to quantify growth and mortality rates of each species at ‘low’ and ‘high’ intertidal heights. Our results indicate that both species agree on the rankings of habitat riskiness and productivity, experiencing higher predation and higher growth in low‐ than in high‐intertidal habitats. However, L. sitkana and L. subrotundata experienced differences in their habitat‐specific mortality risks and growth rates. Despite both species being similarly at risk of predation in high‐intertidal habitats (where mortality was lower), L. subrotundata was subject to significantly higher mortality than L. sitkana at the low‐intertidal height. In contrast, growth rate differences between habitats were greater for L. sitkana than for L. subrotundata. Whereas both species grew at the same rate at the high‐intertidal level (where growth was lower), L. sitkana individuals grew more rapidly than L. subrotundata snails at the low‐intertidal level. As predicted by the behavioural model, the species that experienced the higher ratio of mortality across habitats (i.e. L. subrotundata) occurred exclusively in the safer, high‐intertidal habitat. Taken together, these results provide support for the hypothesis that spatial segregation, and potentially competitor coexistence, can occur in the absence of interspecific trade‐offs in resource acquisition ability or vulnerability to predation.     

Niche overlap in allotopic and syntopic populations of sexually interacting ground‐hopper species

Abstract There is accumulating evidence that sexual interactions among species (reproductive interference) could have dramatic effects for species’ coexistence. It has been shown that the fitness of individuals can be substantially reduced as a consequence of reproductive interference. This might subsequently lead to displacement of a species (sexual exclusion). On the other hand, some evolutionary and ecological mechanisms might enable species to coexist, such as the divergence of mate recognition systems (reproductive character displacement), habitat partitioning, clumped dispersion patterns or different colonization capabilities. We have previously shown that the two ground‐hopper species Tetrix subulata and Tetrix ceperoi interact sexually in the laboratory as well as in the field. At sites where both species co‐occur niche overlap was high, suggesting that coexistence is maintained by different niche breadths rather than by habitat partitioning. To test the hypothesis that habitat partitioning does not contribute to species’ coexistence, we examined whether allotopic and syntopic populations of these two species differ in niche overlap (competitive release). Our results show that niche overlap is higher in syntopic than in allotopic populations, suggesting that the site‐specific habitat structure (heterogeneity) has a stronger influence on microhabitat utilization than the presence of heterospecifics. Hence, our data do not support the hypothesis that habitat partitioning plays a substantial role for the coexistence of these sexually interacting species.     

Modelling geographical patterns in species richness using eigenvector-based spatial filters

Aim To test the mechanisms driving bird species richness at broad spatial scales using eigenvector‐based spatial filtering. Location South America. Methods An eigenvector‐based spatial filtering was applied to evaluate spatial patterns in South American bird species richness, taking into account spatial autocorrelation in the data. The method consists of using the geographical coordinates of a region, based on eigenanalyses of geographical distances, to establish a set of spatial filters (eigenvectors) expressing the spatial structure of the region at different spatial scales. These filters can then be used as predictors in multiple and partial regression analyses, taking into account spatial autocorrelation. Autocorrelation in filters and in the regression residuals can be used as stopping rules to define which filters will be used in the analyses. Results Environmental component alone explained 8% of variation in richness, whereas 77% of the variation could be attributed to an interaction between environment and geography expressed by the filters (which include mainly broad‐scale climatic factors). Regression coefficients of environmental component were highest for AET. These results were unbiased by short‐scale spatial autocorrelation. Also, there was a significant interaction between topographic heterogeneity and minimum temperature. Conclusion Eigenvector‐based spatial filtering is a simple and suitable statistical protocol that can be used to analyse patterns in species richness taking into account spatial autocorrelation at different spatial scales. The results for South American birds are consistent with the climatic hypothesis, in general, and energy hypothesis, in particular. Habitat heterogeneity also has a significant effect on variation in species richness in warm tropical regions.     

Bayesian joint models with INLA exploring marine mobile predator–prey and competitor species habitat overlap

Understanding spatial physical habitat selection driven by competition and/or predator–prey interactions of mobile marine species is a fundamental goal of spatial ecology. However, spatial counts or density data for highly mobile animals often (1) include excess zeros, (2) have spatial correlation, and (3) have highly nonlinear relationships with physical habitat variables, which results in the need for complex joint spatial models. In this paper, we test the use of Bayesian hierarchical hurdle and zero‐inflated joint models with integrated nested Laplace approximation (INLA), to fit complex joint models to spatial patterns of eight mobile marine species (grey seal, harbor seal, harbor porpoise, common guillemot, black‐legged kittiwake, northern gannet, herring, and sandeels). For each joint model, we specified nonlinear smoothed effect of physical habitat covariates and selected either competing species or predator–prey interactions. Out of a range of six ecologically important physical and biologic variables that are predicted to change with climate change and large‐scale energy extraction, we identified the most important habitat variables for each species and present the relationships between these bio/physical variables and species distributions. In particular, we found that net primary production played a significant role in determining habitat preferences of all the selected mobile marine species. We have shown that the INLA method is well‐suited for modeling spatially correlated data with excessive zeros and is an efficient approach to fit complex joint spatial models with nonlinear effects of covariates. Our approach has demonstrated its ability to define joint habitat selection for both competing and prey–predator species that can be relevant to numerous issues in the management and conservation of mobile marine species.     

Scaling up from local competition to regional coexistence across two scales of spatial heterogeneity: insect larvae in the fruits of <Emphasis Type="Italic">Apeiba membranacea</Emphasis>

Species that live in patchy and ephemeral habitats can compete strongly for resources within patches at a small scale. The ramifications of these interactions for population dynamics and coexistence at regional scales will depend on the intraspecific and interspecific distributions of individuals among patches. Spatial heterogeneity due to independent aggregation of competitors among patchy habitats is an important mechanism maintaining species diversity. I describe regional patterns of aggregation for four species of insect larvae in the fruits of Apeiba membranacea, a Neotropical rainforest tree. This aggregation results from variation in densities at a small scale (among the fruits under a single tree), compounded by significant variation among trees in both mean densities and degrees of aggregation. Both the degrees of aggregation and mean densities are statistically independent within and across species at both spatial scales. I evaluate the regional consequences of these spatial patterns by using maximum likelihood methods to parameterize a model that includes both explicit measures of the strength of competition and spatial variation at both within- and among-tree spatial scales. Despite strong competitive interactions among these species, during 2 years the observed spatial variation at both scales combined was sufficient to explain the coexistence of these species, although other coexistence mechanisms may also operate simultaneously. The observed spatial variation at small spatial scales may not be sufficient for coexistence, indicating the importance of considering multiple sources of spatial heterogeneity when scaling up from experiments that investigate local interactions to regional patterns of coexistence.     

The importance of spatial scale in habitat selection by European beaver

We evaluated habitat selection by European beaver Castor fiber L. across a spatial gradient from local (within the family territory) to a broad, ecoregional scale. Based on aerial photography, we assessed the habitat composition of 150 beaver territories along the main water bodies of the Vistula River delta (northern Poland) and compared these data with 183 randomly selected sites not occupied by the species. The beavers preferred habitats with high availability of woody plants, including shrubs, and avoided anthropogenically modified habitats, such as arable lands. Within a single family territory, we observed decreasing woody plant cover with increasing distance from a colony centre, which suggests that beaver habitat preferences depend on the assessment of both the abundance and spatial distribution of preferred habitat elements. We tested the importance of spatial scale in beaver habitat selection with principal coordinates of neighbour matrices analysis, which showed that the geographical scale explained 46.7% of the variation in habitat composition, while the local beaver density explained only 10.3% of this variability. We found two main spatial gradients that were related to the broad spatial scale: first, the most important gradient was related to the largest distances between beaver sites and was independent of woody plant cover and the local beaver site density. The second most important gradient appeared more locally and was associated with these variables. Our results indicate that European beaver habitat selection was affected by different scale‐related phenomena related 1) to central place foraging behaviour, which resulted in the clumped distribution of woody plants within the territory, and 2) local population density and woody plant cover. Finally, 3) habitat selection occurs independently across the largest spatial scale studied (e.g. between watersheds), which was probably due to the limited natal dispersal range of the animals.