Understanding niche evolution, dynamics, and the response of species to climate change requires knowledge of the determinants of the environmental niche and species range limits. Mean values of climatic variables are often used in such analyses. In contrast, the increasing frequency of climate extremes suggests the importance of understanding their additional influence on range limits. Here, we assess how measures representing climate extremes (i.e., interannual variability in climate parameters) explain and predict spatial patterns of 11 tree species in Switzerland. We find clear, although comparably small, improvement (؉20% in adjusted D 2 , ؉8% and ؉3% in cross-validated True Skill Statistic and area under the receiver operating characteristics curve values) in models that use measures of extremes in addition to means. The primary effect of including information on climate extremes is a correction of local overprediction and underprediction. Our results demonstrate that measures of climate extremes are important for understanding the climatic limits of tree species and assessing species niche characteristics. The inclusion of climate variability likely will improve models of species range limits under future conditions, where changes in mean climate and increased variability are expected.climate change ͉ ecological niche ͉ generalized additive model ͉ geographic range ͉ species distribution models T he understanding of the principles and mechanisms that shape distribution patterns has long been a focus in biogeographical, ecological, and evolutionary research. The ecological niche concept, coined and initially developed by Grinnell (1), is the foundation for our understanding of the processes that shape the geographical distributions of species (2). Conceptual clarifications with regards to using the concept for the explanation of species ranges have been presented by several authors (3, 4). Climatic variables are often used to predict biogeographical patterns (5), and considerable effort has been put into improving methods to describe the response of species along climate gradients (6-8). These methods of species distribution or niche modeling are frequently used for conservation management (9-12), prediction of the likely effects of global change (13-16), and, increasingly, assessment of niche characteristics in the study of niche evolution (17)(18)(19)(20). These studies in general use monthly or annual climatic means to analyze species distribution patterns. To date, little attention has been paid to the question of how climatic extremes, i.e., the long-term, interannual variation around mean values, could help to explain species distributions. There are two major reasons that highlight the importance of including climatic variability in niche analyses and models. First, ongoing climate change not only affects means but also extremes (21). Second, niche evolution often results in changes of the stress tolerance of evolving clades (22, 23). Thus, both adaptation and possible future response of species to c...

Aim Species ranges have adapted during the Holocene to altering climate conditions, but it remains unclear if species will be able to keep pace with recent and future climate change. The goal of our study is to assess the influence of changing macroclimate, competition and habitat connectivity on the migration rates of 14 tree species. We also compare the projections of range shifts from species distribution models (SDMs) that incorporate realistic migration rates with classical models that assume no or unlimited migration. Location Europe.Methods We calibrated SDMs with species abundance data from 5768 forest plots from ICP Forest Level 1 in relation to climate, topography, soil and land-use data to predict current and future tree distributions. To predict future species ranges from these models, we applied three migration scenarios: no migration, unlimited migration and realistic migration. The migration rates for the SDMs incorporating realistic migration were estimated according to macroclimate, interspecific competition and habitat connectivity from simulation experiments with a spatially explicit process model (TreeMig). From these relationships, we then developed a migration cost surface to constrain the predicted distributions of the SDMs. ResultsThe distributions of early-successional species during the 21st century predicted by SDMs that incorporate realistic migration matched quite well with the unlimited migration assumption (mean migration rate over Europe for A1fi/GRAS climate and land-use change scenario 156.7 Ϯ 79.1 m year -1 and for B1/SEDG 164.3 Ϯ 84.2 m year -1 ). The predicted distributions of mid-to late-successional species matched better with the no migration assumption (A1fi/GRAS, 15.2 Ϯ 24.5 m year -1 and B1/SEDG, 16.0 Ϯ 25.6 m year -1 ). Inter-specific competition, which is higher under favourable growing conditions, reduced range shift velocity more than did adverse macroclimatic conditions (i.e. very cold or dry climate). Habitat fragmentation also led to considerable time lags in range shifts. Main conclusionsMigration rates depend on species traits, competition, spatial habitat configuration and climatic conditions. As a result, re-adjustments of species ranges to climate and land-use change are complex and very individualistic, yet still quite predictable. Early-successional species track climate change almost instantaneously while mid-to late-successional species were predicted to migrate very slowly.

Abiotic factors such as climate and soil determine the species fundamental niche, which is further constrained by biotic interactions such as interspecific competition. To parameterize this realized niche, species distribution models (SDMs) most often relate species occurrence data to abiotic variables, but few SDM studies include biotic predictors to help explain species distributions. Therefore, most predictions of species distributions under future climates assume implicitly that biotic interactions remain constant or exert only minor influence on large-scale spatial distributions, which is also largely expected for species with high competitive ability. We examined the extent to which variance explained by SDMs can be attributed to abiotic or biotic predictors and how this depends on species traits. We fit generalized linear models for 11 common tree species in Switzerland using three different sets of predictor variables: biotic, abiotic, and the combination of both sets. We used variance partitioning to estimate the proportion of the variance explained by biotic and abiotic predictors, jointly and independently. Inclusion of biotic predictors improved the SDMs substantially. The joint contribution of biotic and abiotic predictors to explained deviance was relatively small (Â9%) compared to the contribution of each predictor set individually (Â20% each), indicating that the additional information on the realized niche brought by adding other species as predictors was largely independent of the abiotic (topo-climatic) predictors. The influence of biotic predictors was relatively high for species preferably growing under low disturbance and low abiotic stress, species with long seed dispersal distances, species with high shade tolerance as juveniles and adults, and species that occur frequently and are dominant across the landscape. The influence of biotic variables on SDM performance indicates that community composition and other local biotic factors or abiotic processes not included in the abiotic predictors strongly influence prediction of species distributions. Improved prediction of species' potential distributions in future climates and communities may assist strategies for sustainable forest management.

Aim During recent and future climate change, shifts in large-scale species ranges are expected due to the hypothesized major role of climatic factors in regulating species distributions. The stress-gradient hypothesis suggests that biotic interactions may act as major constraints on species distributions under more favourable growing conditions, while climatic constraints may dominate under unfavourable conditions. We tested this hypothesis for one focal tree species having three major competitors using broad-scale environmental data. We evaluated the variation of species co-occurrence patterns in climate space and estimated the influence of these patterns on the distribution of the focal species for current and projected future climates.Location Europe.Methods We used ICP Forest Level 1 data as well as climatic, topographic and edaphic variables. First, correlations between the relative abundance of European beech (Fagus sylvatica) and three major competitor species (Picea abies, Pinus sylvestris and Quercus robur) were analysed in environmental space, and then projected to geographic space. Second, a sensitivity analysis was performed using generalized additive models (GAM) to evaluate where and how much the predicted F. sylvatica distribution varied under current and future climates if potential competitor species were included or excluded. We evaluated if these areas coincide with current species co-occurrence patterns.Results Correlation analyses supported the stress-gradient hypothesis: towards favourable growing conditions of F. sylvatica, its abundance was strongly linked to the abundance of its competitors, while this link weakened towards unfavourable growing conditions, with stronger correlations in the south and at low elevations than in the north and at high elevations. The sensitivity analysis showed a potential spatial segregation of species with changing climate and a pronounced shift of zones where co-occurrence patterns may play a major role.Main conclusions Our results demonstrate the importance of species co-occurrence patterns for calibrating improved species distribution models for use in projections of climate effects. The correlation approach is able to localize European areas where inclusion of biotic predictors is effective. The climateinduced spatial segregation of the major tree species could have ecological and economic consequences.

Aim-Understanding the stability of realized niches is crucial for predicting the responses of species to climate change. One approach is to evaluate the niche differences of populations of the same species that occupy regions that are geographically disconnected. Here, we assess niche conservatism along thermal gradients for 26 plant species with a disjunct distribution between the Alps and the Arctic. Location-European Alps and Norwegian Finnmark.Methods-We collected a comprehensive dataset of 26 arctic-alpine plant occurrences in two regions. We assessed niche conservatism through a multispecies comparison and analysed species rankings at cold and warm thermal limits along two distinct gradients corresponding to (1) air temperatures at 2 m above ground level and (2) elevation distances to the tree line (TLD) for the two regions. We assessed whether observed relationships were close to those predicted under thermal limit conservatism.Results-We found a weak similarity in species ranking at the warm thermal limits. The range of warm thermal limits for the 26 species was much larger in the Alps than in Finnmark. We found a stronger similarity in species ranking and correspondence at the cold thermal limit along the gradients of 2-m temperature and TLD. Yet along the 2-m temperature gradient the cold thermal limits of species in the Alps were lower on average than those in Finnmark. Main conclusion-We found low conservatism of the warm thermal limits but a stronger conservatism of the cold thermal limits. We suggest that biotic interactions at the warm thermal limit are likely to modulate species responses more strongly than at the cold limit. The differing biotic context between the two regions is probably responsible for the observed differences in realized niches.