Disregarding topographical heterogeneity biases species turnover assessments based on bioclimatic models

We investigated whether the inclusion of topographical heterogeneity in bioclimatic envelope models would significantly alter predictions of climate change – induced broad-scale butterfly species range size changes in Europe. Using generalized additive models, and data on current climate and species distributions and two different climate scenarios (HadCM3A2 and HadCM3B2) for the period 2051–2080, we developed predictions of the currently suitable area and potential range size changes of 100 European butterfly species. The inclusion of elevation range increased the predictive accuracy of climate-only models for 86 of the 100 species. The differences in projected future distributions were most notable in mountainous areas, where the climate–topography models projected only ca. half of the species losses than the climate-only models. By contrast, climate–topography models estimated double the losses of species than climate-only models in the flatlands regions. Our findings suggest that disregarding topographical heterogeneity may cause a significant source of error in broad-scale bioclimatic modelling. Mountainous regions are likely to be even more important for future conservation of species than had until now been predicted, based on bioclimatic envelope models that did not take an explicit account of elevational range of grid squares.     

Inclusion of soil data improves the performance of bioclimatic envelope models for insect species distributions in temperate Europe

Aim To analyse the effect of the inclusion of soil and land‐cover data on the performance of bioclimatic envelope models for the regional‐scale prediction of butterfly (Rhopalocera) and grasshopper (Orthoptera) distributions. Location Temperate Europe (Belgium). Methods Distributional data were extracted from butterfly and grasshopper atlases at a resolution of 5 km for the period 1991–2006 in Belgium. For each group separately, the well‐surveyed squares (n = 366 for butterflies and n = 322 for grasshoppers) were identified using an environmental stratification design and were randomly divided into calibration (70%) and evaluation (30%) datasets. Generalized additive models were applied to the calibration dataset to estimate occurrence probabilities for 63 butterfly and 33 grasshopper species, as a function of: (1) climate, (2) climate and land‐cover, (3) climate and soil, and (4) climate, land‐cover and soil variables. Models were evaluated as: (1) the amount of explained deviance in the calibration dataset, (2) Akaike’s information criterion, and (3) the number of omission and commission errors in the evaluation dataset. Results Information on broad land‐cover classes or predominant soil types led to similar improvements in the performance relative to the climate‐only models for both taxonomic groups. In addition, the joint inclusion of land‐cover and soil variables in the models provided predictions that fitted more closely to the species distributions than the predictions obtained from bioclimatic models incorporating only land‐cover or only soil variables. The combined models exhibited higher discrimination ability between the presence and absence of species in the evaluation dataset. Main conclusions These results draw attention to the importance of soil data for species distribution models at regional scales of analysis. The combined inclusion of land‐cover and soil data in the models makes it possible to identify areas with suitable climatic conditions but unsuitable combinations of vegetation and soil types. While contingent on the species, the results indicate the need to consider soil information in regional‐scale species–climate impact models, particularly when predicting future range shifts of species under climate change.     

Potential Changes in the Distributions of Western North America Tree and Shrub Taxa under Future Climate Scenarios

Increases in atmospheric greenhouse gases are driving significant changes in global climate. To project potential vegetation response to future climate change, this study uses response surfaces to describe the relationship between bioclimatic variables and the distribution of tree and shrub taxa in western North America. The response surfaces illustrate the probability of the occurrence of a taxon at particular points in climate space. Climate space was defined using three bioclimatic variables: mean temperature of the coldest month, growing degree days, and a moisture index. Species distributions were simulated under present climate using observed data (1951–80, 30-year mean) and under future climate (2090–99, 10-year mean) using scenarios generated by three general circulation models—HADCM2, CGCM1, and CSIRO. The scenarios assume a 1% per year compound increase in greenhouse gases and changes in sulfate (SO₄) aerosols based on the Intergovernmental Panel on Climate Change (IPCC) IS92a scenario. The results indicate that under future climate conditions, potential range changes could be large for many tree and shrub taxa. Shifts in the potential ranges of species are simulated to occur not only northward but in all directions, including southward of the existing ranges of certain species. The simulated potential distributions of some species become increasingly fragmented under the future climate scenarios, while the simulated potential distributions of other species expand. The magnitudes of the simulated range changes imply significant impacts to ecosystems and shifts in patterns of species diversity in western North America. Received 12 May 2000; accepted 20 December 2000.     

Predicting the impact of climate change on Australia's most endangered snake, Hoplocephalus bungaroides

Aim  To predict how the bioclimatic envelope of the broad-headed snake (BHS) ( Hoplocephalus bungaroides ) may be redistributed under future climate warming scenarios.
Location  South-eastern New South Wales, Australia.
Methods  We used 159 independent locations for the species and 35 climatic variables to model the bioclimatic envelope for the BHS using two modelling approaches – B ioclim and M axent . Predictions were made under current climatic conditions and we also predicted the species distribution under low and high climate change scenarios for 2030 and 2070.
Results  Broad-headed snakes currently encompass their entire bioclimatic envelope. Both modelling approaches predict that suitable climate space for BHS will be lost to varying degrees under both climate warming scenarios, and under the worst case, only 14% of known snake populations may persist.
Main conclusions  Areas of higher elevation within the current range will be most important for persistence of this species because they will remain relatively moist and cool even under climate change and will match the current climate envelope. Conservation efforts should focus on areas where suitable climate space may persist under climate warming scenarios. Long-term monitoring programs should be established both in these areas and where populations are predicted to become extirpated, so that we can accurately determine changes in the distribution of this species throughout its range.     

Exploring consensus in 21st century projections of climatically suitable areas for African vertebrates

Africa is predicted to be highly vulnerable to 21st century climatic changes. Assessing the impacts of these changes on Africa's biodiversity is, however, plagued by uncertainties, and markedly different results can be obtained from alternative bioclimatic envelope models or future climate projections. Using an ensemble forecasting framework, we examine projections of future shifts in climatic suitability, and their methodological uncertainties, for over 2500 species of mammals, birds, amphibians and snakes in sub‐Saharan Africa. To summarize a priori the variability in the ensemble of 17 general circulation models, we introduce a consensus methodology that combines co‐varying models. Thus, we quantify and map the relative contribution to uncertainty of seven bioclimatic envelope models, three multi‐model climate projections and three emissions scenarios, and explore the resulting variability in species turnover estimates. We show that bioclimatic envelope models contribute most to variability, particularly in projected novel climatic conditions over Sahelian and southern Saharan Africa. To summarize agreements among projections from the bioclimatic envelope models we compare five consensus methodologies, which generally increase or retain projection accuracy and provide consistent estimates of species turnover. Variability from emissions scenarios increases towards late‐century and affects southern regions of high species turnover centred in arid Namibia. Twofold differences in median species turnover across the study area emerge among alternative climate projections and emissions scenarios. Our ensemble of projections underscores the potential bias when using a single algorithm or climate projection for Africa, and provides a cautious first approximation of the potential exposure of sub‐Saharan African vertebrates to climatic changes. The future use and further development of bioclimatic envelope modelling will hinge on the interpretation of results in the light of methodological as well as biological uncertainties. Here, we provide a framework to address methodological uncertainties and contextualize results.     

Whole range and regional‐based ecological niche models predict differing exposure to 21st century climate change in the key cool temperate rainforest tree southern beech (Nothofagus cunninghamii)

The warmer and drier climates projected for the mid‐ to late‐21st century may have particularly adverse impacts on the cool temperate rainforests of southeastern Australia. Southern beech (Nothofagus cunninghamii; Nothofagaceae), a dominant tree species in these forests, may be vulnerable to minor changes in its climate envelope, especially at the edge of the species range, with Holocene fossil evidence showing local extinction of populations in response to small climate changes. We modelled the stability of this species climate envelope using the maximum entropy algorithm implemented in Maxent and two thresholds of presence/absence by projecting the modern climate envelope onto four Global Circulation Models forecasted for two time periods (2050s and 2070s). The climate envelope, as estimated from the species present climatic range, is predicted to shrink by up to 49% by the 2050s and up to 64% by the 2070s. The greatest predicted reduction is in Victoria with 91–100% of its current range being climatically unsuitable by the 2070s. Climatically similar areas to the species present range are predicted to remain in mountainous areas of western Tasmania, the Northeast Highlands of Tasmania, and the Baw Baw Plateau in the Central Highlands of Victoria. However, region‐specific modelling approaches made very different predictions from the whole‐range based models, especially in the severity of the predicted decline for Victorian populations of N. cunninghamii which occur in much warmer climates than the rest of the species geographical range. This shows that, for widespread species that span a range of climate zones, the exposure of current populations to climate change may be better modelled using a regional based approach. How the species responds to climate change will depend on the species ability to respond to drier and warmer climates and the concomitant increase in fire intensity.     

Range position and climate sensitivity: The structure of among‐population demographic responses to climatic variation

Species’ distributions will respond to climate change based on the relationship between local demographic processes and climate and how this relationship varies based on range position. A rarely tested demographic prediction is that populations at the extremes of a species’ climate envelope (e.g., populations in areas with the highest mean annual temperature) will be most sensitive to local shifts in climate (i.e., warming). We tested this prediction using a dynamic species distribution model linking demographic rates to variation in temperature and precipitation for wood frogs (Lithobates sylvaticus) in North America. Using long‐term monitoring data from 746 populations in 27 study areas, we determined how climatic variation affected population growth rates and how these relationships varied with respect to long‐term climate. Some models supported the predicted pattern, with negative effects of extreme summer temperatures in hotter areas and positive effects on recruitment for summer water availability in drier areas. We also found evidence of interacting temperature and precipitation influencing population size, such as extreme heat having less of a negative effect in wetter areas. Other results were contrary to predictions, such as positive effects of summer water availability in wetter parts of the range and positive responses to winter warming especially in milder areas. In general, we found wood frogs were more sensitive to changes in temperature or temperature interacting with precipitation than to changes in precipitation alone. Our results suggest that sensitivity to changes in climate cannot be predicted simply by knowing locations within the species’ climate envelope. Many climate processes did not affect population growth rates in the predicted direction based on range position. Processes such as species‐interactions, local adaptation, and interactions with the physical landscape likely affect the responses we observed. Our work highlights the need to measure demographic responses to changing climate.     

Limited filling of the potential range in European tree species

The relative roles of environment and history in controlling large‐scale species distributions are important not only theoretically, but also for forecasting range responses to climatic change. Here, we use atlas data to examine the extent to which 55 tree species fill their climatically determined potential ranges in Europe. Quantifying range filling (R/P) as realized/potential range size ratios using bioclimatic envelope modelling we find mean R/P = 38.3% (±30.3% SD). Many European tree species naturalize extensively outside their native ranges, providing support for interpreting the many low R/Ps as primarily reflecting dispersal limitation. R/P increases strongly with latitudinal range centroid and secondarily with hardiness and decreases weakly with longitudinal range centroid. Hence, European tree species ranges appear strongly controlled by geographical dispersal constraints on post‐glacial expansion as well as climate. Consequently, we expect European tree species to show only limited tracking of near‐future climate changes.     

Bioclimatic model of tree radial growth: application to the French Mediterranean Aleppo pine forests

The potential effects of global changes on forests are of increasing concern. Dendrochronology, which deals with long-term records of tree growth under natural environmental conditions, can be used to evaluate the impact of climatic change on forest productivity. However, assessment of climatic change impacts must be supported by accurate and reliable models of the relationships between climate and tree growth. In this study, a bioclimatic model is used to explore the relationships between tree radial growth and bioclimatic variables closely related to the biological functioning of a tree. This model is at an intermediate level of complexity between purely empirical and process-based models. The method is illustrated with data for 21 Aleppo pine (Pinus halepensis Mill.) stands grown under a Mediterranean climate in south-east France. The results show that Aleppo pine growth is mainly controlled by soil water availability during the growing season. The bioclimatic variable which best expresses the observed inter-annual tree growth variations is the actual evapotranspiration (AET). Four parameters were adjusted to simulate dendrochronological data: the soil water capacity, the wilting point, the minimum temperature for photosynthesis, and the end of the growing season. The bioclimatic model gives better results than the standard response function and provides better insight into the functional processes involved in tree growth. The convincing results obtained by the bioclimatic model as well as the limited numbers of parameters it requires demonstrate the feasibility of using it to explore future climatic change impacts on Aleppo pine forests.     

Land-cover data improve bioclimatic models for anurans and turtles at a regional scale

Aim We investigated whether accounting for land cover could improve bioclimatic models for eight species of anurans and three species of turtles at a regional scale. We then tested whether accounting for spatial autocorrelation could significantly improve bioclimatic models after statistically controlling for the effects of land cover. Location Nova Scotia, eastern Canada. Methods Species distribution data were taken from a recent (1999–2003) herpetofaunal atlas. Generalized linear models were used to relate the presence or absence of each species to climate and land‐cover variables at a 10‐km resolution. We then accounted for spatial autocorrelation using an autocovariate or third‐order trend surface of the geographical coordinates of each grid square. Finally, variance partitioning was used to explore the independent and joint contributions of climate, land cover and spatial autocorrelation. Results The inclusion of land cover significantly increased the explanatory power of bioclimatic models for 10 of the 11 species. Furthermore, including land cover significantly increased predictive performance for eight of the 11 species. Accounting for spatial autocorrelation improved model fit for rare species but generally did not improve prediction success. Variance partitioning demonstrated that this lack of improvement was a result of the high correlation between climate and trend‐surface variables. Main conclusions The results of this study suggest that accounting for the effects of land cover can significantly improve the explanatory and predictive power of bioclimatic models for anurans and turtles at a regional scale. We argue that the integration of climate and land‐cover data is likely to produce more accurate spatial predictions of contemporary herpetofaunal diversity. However, the use of land‐cover simulations in climate‐induced range‐shift projections introduces additional uncertainty into the predictions of bioclimatic models. Further research is therefore needed to determine whether accounting for the effects of land cover in range‐shift projections is merited.     

Why Would Plant Species Become Extinct Locally If Growing Conditions Improve?

Two assumptions underlie current models of the geographical ranges of perennial plant species: 1. current ranges are in equilibrium with the prevailing climate, and 2. changes are attributable to changes in macroclimatic factors, including tolerance of winter cold, the duration of the growing season, and water stress during the growing season, rather than to biotic interactions. These assumptions allow model parameters to be estimated from current species ranges. Deterioration of growing conditions due to climate change, e.g. more severe drought, will cause local extinction. However, for many plant species, the predicted climate change of higher minimum temperatures and longer growing seasons means, improved growing conditions. Biogeographical models may under some circumstances predict that a species will become locally extinct, despite improved growing conditions, because they are based on an assumption of equilibrium and this forces the species range to match the species-specific macroclimatic thresholds. We argue that such model predictions should be rejected unless there is evidence either that competition influences the position of the range margins or that a certain physiological mechanism associated with the apparent improvement in growing conditions negatively affects the species performance. We illustrate how a process-based vegetation model can be used to ascertain whether such a physiological cause exists. To avoid potential modelling errors of this type, we propose a method that constrains the scenario predictions of the envelope models by changing the geographical distribution of the dominant plant functional type. Consistent modelling results are very important for evaluating how changes in species areas affect local functional trait diversity and hence ecosystem functioning and resilience, and for inferring the implications for conservation management in the face of climate change.     

Intra‐specific variability and plasticity influence potential tree species distributions under climate change

Aim To assess the effect of local adaptation and phenotypic plasticity on the potential distribution of species under future climate changes. Trees may be adapted to specific climatic conditions; however, species range predictions have classically been assessed by species distribution models (SDMs) that do not account for intra‐specific genetic variability and phenotypic plasticity, because SDMs rely on the assumption that species respond homogeneously to climate change across their range, i.e. a species is equally adapted throughout its range, and all species are equally plastic. These assumptions could cause SDMs to exaggerate or underestimate species at risk under future climate change. Location The Iberian Peninsula. Methods Species distributions are predicted by integrating experimental data and modelling techniques. We incorporate plasticity and local adaptation into a SDM by calibrating models of tree survivorship with adaptive traits in provenance trials. Phenotypic plasticity was incorporated by calibrating our model with a climatic index that provides a measure of the differences between sites and provenances. Results We present a new modelling approach that is easy to implement and makes use of existing tree provenance trials to predict species distribution models under global warming. Our results indicate that the incorporation of intra‐population genetic diversity and phenotypic plasticity in SDMs significantly altered their outcome. In comparing species range predictions, the decrease in area occupancy under global warming conditions is smaller when considering our survival–adaptation model than that predicted by a ‘classical SDM’ calibrated with presence–absence data. These differences in survivorship are due to both local adaptation and plasticity. Differences due to the use of experimental data in the model calibration are also expressed in our results: we incorporate a null model that uses survival data from all provenances together. This model always predicts less reduction in area occupancy for both species than the SDM calibrated with presence–absence. Main conclusions We reaffirm the importance of considering adaptive traits when predicting species distributions and avoiding the use of occurrence data as a predictive variable. In light of these recommendations, we advise that existing predictions of future species distributions and their component populations must be reconsidered.     

Predicting invasions in Australia by a Neotropical shrub under climate change: the challenge of novel climates and parameter estimation

Aim  To test how well species distributions and abundance can be predicted following invasion and climate change when using only species distribution and abundance data to estimate parameters.
Location  Models were developed for the species' native range in the Americas and applied to Australia.
Methods  We developed a predictive model for an invasive neotropical shrub ( Parkinsonia aculeata) using a popular ecophysiological bioclimatic modelling technique (CLIMEX) fitted against distribution and abundance data in the Americas. The effect of uncertainty in model parameter estimates on predictions in Australia was tested. Alternative data sources were used when model predictions were sensitive to uncertainty in parameter estimates. The resulting best-fit model was run under two climate change scenarios.
Results  Of the 19 parameters used, 9 could not be fitted using data from the native range. However, only parameters that lowered temperature or increased moisture requirements for growth noticeably altered the model prediction in Australia. Differences in predictions were dramatic, and reflect climates in Australia that were not represented in the Americas (novel climates). However, these poorly fitted parameters could be fitted post hoc using alternative data sources prior to predicting responses to climate change.
Conclusions  Novel climates prevented the development of a predictive model which relied only on native-range distribution and abundance data because certain parameters could not be fitted. In fact, predictions were more sensitive to parameter uncertainty than to climate change scenarios. Where uncertainty in parameter estimates affected predictions, it could be addressed through the inclusion of alternative data sources. However, this may not always be possible, for example in the absence of post-invasion data.     

Modeling plant species distributions under future climates: how fine scale do climate projections need to be?

Recent studies suggest that species distribution models (SDMs) based on fine‐scale climate data may provide markedly different estimates of climate‐change impacts than coarse‐scale models. However, these studies disagree in their conclusions of how scale influences projected species distributions. In rugged terrain, coarse‐scale climate grids may not capture topographically controlled climate variation at the scale that constitutes microhabitat or refugia for some species. Although finer scale data are therefore considered to better reflect climatic conditions experienced by species, there have been few formal analyses of how modeled distributions differ with scale. We modeled distributions for 52 plant species endemic to the California Floristic Province of different life forms and range sizes under recent and future climate across a 2000‐fold range of spatial scales (0.008–16 km²). We produced unique current and future climate datasets by separately downscaling 4 km climate models to three finer resolutions based on 800, 270, and 90 m digital elevation models and deriving bioclimatic predictors from them. As climate‐data resolution became coarser, SDMs predicted larger habitat area with diminishing spatial congruence between fine‐ and coarse‐scale predictions. These trends were most pronounced at the coarsest resolutions and depended on climate scenario and species' range size. On average, SDMs projected onto 4 km climate data predicted 42% more stable habitat (the amount of spatial overlap between predicted current and future climatically suitable habitat) compared with 800 m data. We found only modest agreement between areas predicted to be stable by 90 m models generalized to 4 km grids compared with areas classified as stable based on 4 km models, suggesting that some climate refugia captured at finer scales may be missed using coarser scale data. These differences in projected locations of habitat change may have more serious implications than net habitat area when predictive maps form the basis of conservation decision making.     

The projected effects of climatic and vegetation changes on the distribution and diversity of Southeast Asian bats

Southeast‐Asia (SEA) constitutes a global biodiversity hotspot, but is exposed to extensive deforestation and faces numerous threats to its biodiversity. Climate change represents a major challenge to the survival and viability of species, and the potential consequences must be assessed to allow for mitigation. We project the effects of several climate change scenarios on bat diversity, and predict changes in range size for 171 bat species throughout SEA. We predict decreases in species richness in all areas with high species richness (>80 species) at 2050–2080, using bioclimatic IPCC scenarios A2 (a severe scenario, continuously increasing human population size, regional changes in economic growth) and B1 (the ‘greenest’ scenario, global population peaking mid‐century). We also predicted changes in species richness in scenarios that project vegetation changes in addition to climate change up to 2050. At 2050 and 2080, A2 and B1 scenarios incorporating changes in climatic factors predicted that 3–9% species would lose all currently suitable niche space. When considering total extents of species distribution in SEA (including possible range expansions), 2–6% of species may have no suitable niche space in 2050–2080. When potential vegetation and climate changes were combined only 1% of species showed no changes in their predicted ranges by 2050. Although some species are projected to expand ranges, this may be ecologically impossible due to potential barriers to dispersal, especially for species with poor dispersal ability. Only 1–13% of species showed no projected reductions in their current range under bioclimatic scenarios. An effective way to facilitate range shift for dispersal‐limited species is to improve landscape connectivity. If current trends in environmental change continue and species cannot expand their ranges into new areas, then the majority of bat species in SEA may show decreases in range size and increased extinction risk within the next century.     

Predicting range expansion of the map butterfly in Northern Europe using bioclimatic models

The two main goals of this study are: (i) to examine the range shifts of a currently northwards expanding species, the map butterfly (Araschnia levana), in relation to annual variation in weather, and (ii) to test the capability of a bioclimatic envelope model, based on broad-scale European distribution data, to predict recent distributional changes (2000–2004) of the species in Finland. A significant relationship between annual maximum dispersal distance of the species and late summer temperature was detected. This suggests that the map butterfly has dispersed more actively in warmer rather than cooler summers, the most notable dispersal events being promoted by periods of exceptionally warm weather and southerly winds. The accuracy of the broad-scale bioclimatic model built for the species with European data using Generalized Additive Models (GAM) was good based on split-sample evaluation for a single period. However, the model’s performance was poor when applied to predict range shifts in Finland. Among the many potential explanations for the poor success of the transferred bioclimatic model, is the fact that bioclimatic envelope models do not generally account for species dispersal. This and other uncertainties support the view that bioclimatic models should be applied with caution when they are used to project future range shifts of species.     

Reinforcing and expanding the predictions of the disturbance vicariance hypothesis in Amazonian harlequin frogs: a molecular phylogenetic and climate envelope modelling approach

The disturbance vicariance hypothesis (DV) has been proposed to explain speciation in Amazonia, especially its edge regions, e.g. in eastern Guiana Shield harlequin frogs (Atelopus) which are suggested to have derived from a cool-adapted Andean ancestor. In concordance with DV predictions we studied that (i) these amphibians display a natural distribution gap in central Amazonia; (ii) east of this gap they constitute a monophyletic lineage which is nested within a pre-Andean/western clade; (iii) climate envelopes of Atelopus west and east of the distribution gap show some macroclimatic divergence due to a regional climate envelope shift; (iv) geographic distributions of climate envelopes of western and eastern Atelopus range into central Amazonia but with limited spatial overlap. We tested if presence and apparent absence data points of Atelopus were homogenously distributed with Ripley’s K function. A molecular phylogeny (mitochondrial 16S rRNA gene) was reconstructed using Maximum Likelihood and Bayesian Inference to study if Guianan Atelopus constitute a clade nested within a larger genus phylogeny. We focused on climate envelope divergence and geographic distribution by computing climatic envelope models with MaxEnt based on macroscale bioclimatic parameters and testing them by using Schoener’s index and modified Hellinger distance. We corroborated existing DV predictions and, for the first time, formulated new DV predictions aiming on species’ climate envelope change. Our results suggest that cool-adapted Andean Atelopus ancestors had dispersed into the Amazon basin and further onto the eastern Guiana Shield where, under warm conditions, they were forced to change climate envelopes.     

Model-based uncertainty in species range prediction

Aim Many attempts to predict the potential range of species rely on environmental niche (or ‘bioclimate envelope’) modelling, yet the effects of using different niche‐based methodologies require further investigation. Here we investigate the impact that the choice of model can have on predictions, identify key reasons why model output may differ and discuss the implications that model uncertainty has for policy‐guiding applications. Location The Western Cape of South Africa. Methods We applied nine of the most widely used modelling techniques to model potential distributions under current and predicted future climate for four species (including two subspecies) of Proteaceae. Each model was built using an identical set of five input variables and distribution data for 3996 sampled sites. We compare model predictions by testing agreement between observed and simulated distributions for the present day (using the area under the receiver operating characteristic curve (AUC) and kappa statistics) and by assessing consistency in predictions of range size changes under future climate (using cluster analysis). Results Our analyses show significant differences between predictions from different models, with predicted changes in range size by 2030 differing in both magnitude and direction (e.g. from 92% loss to 322% gain). We explain differences with reference to two characteristics of the modelling techniques: data input requirements (presence/absence vs. presence‐only approaches) and assumptions made by each algorithm when extrapolating beyond the range of data used to build the model. The effects of these factors should be carefully considered when using this modelling approach to predict species ranges. Main conclusions We highlight an important source of uncertainty in assessments of the impacts of climate change on biodiversity and emphasize that model predictions should be interpreted in policy‐guiding applications along with a full appreciation of uncertainty.     

Potential impacts of climate change on the distributions and diversity patterns of European mammals

The Intergovernmental Panel on Climate Change (IPCC) predicts an increase in global temperatures of between 1.4°C and 5.8°C during the 21st century, as a result of elevated CO₂ levels. Using bioclimatic envelope models, we evaluate the potential impact of climate change on the distributions and species richness of 120 native terrestrial non-volant European mammals under two of IPCC’s future climatic scenarios. Assuming unlimited and no migration, respectively, our model predicts that 1% or 5–9% of European mammals risk extinction, while 32–46% or 70–78% may be severely threatened (lose > 30% of their current distribution) under the two scenarios. Under the no migration assumption endemic species were predicted to be strongly negatively affected by future climatic changes, while widely distributed species would be more mildly affected. Finally, potential mammalian species richness is predicted to become dramatically reduced in the Mediterranean region but increase towards the northeast and for higher elevations. Bioclimatic envelope models do not account for non-climatic factors such as land-use, biotic interactions, human interference, dispersal or history, and our results should therefore be seen as first approximations of the potential magnitude of future climatic changes.