The ability of climate envelope models to predict the effect of climate change on species distributions

Climate envelope models (CEMs) have been used to predict the distribution of species under current, past, and future climatic conditions by inferring a species' environmental requirements from localities where it is currently known to occur. CEMs can be evaluated for their ability to predict current species distributions but it is unclear whether models that are successful in predicting current distributions are equally successful in predicting distributions under different climates (i.e. different regions or time periods). We evaluated the ability of CEMs to predict species distributions under different climates by comparing their predictions with those obtained with a mechanistic model (MM). In an MM the distribution of a species is modeled based on knowledge of a species' physiology. The potential distributions of 100 plant species were modeled with an MM for current conditions, a past climate reconstruction (21 000 years before present) and a future climate projection (double preindustrial CO₂ conditions). Point localities extracted from the currently suitable area according to the MM were used to predict current, future, and past distributions with four CEMs covering a broad range of statistical approaches: Bioclim (percentile distributions), Domain (distance metric), GAM (general additive modeling), and Maxent (maximum entropy). Domain performed very poorly, strongly underestimating range sizes for past or future conditions. Maxent and GAM performed as well under current climates as under past and future climates. Bioclim slightly underestimated range sizes but the predicted ranges overlapped more with the ranges predicted with the MM than those predicted with GAM did. Ranges predicted with Maxent overlapped most with those produced with the MMs, but compared with the ranges predicted with GAM they were more variable and sometimes much too large. Our results suggest that some CEMs can indeed be used to predict species distributions under climate change, but individual modeling approaches should be validated for this purpose, and model choice could be made dependent on the purpose of a particular study.     

Potential changes in the distributions of latitudinally restricted Australian butterfly species in response to climate change

This study assessed potential changes in the distributions of Australian butterfly species in response to global warming. The bioclimatic program, BIOCLIM, was used to determine the current climatic ranges of 77 butterfly species restricted to Australia. We found that the majority of these species had fairly wide climatic ranges in comparison to other taxa, with only 8% of butterfly species having a mean annual temperature range spanning less than 3 °C. The potential changes in the distributions of 24 butterfly species under four climate change scenarios for 2050 were also modelled using BIOCLIM. Results suggested that even species with currently wide climatic ranges may still be vulnerable to climate change; under a very conservative climate change scenario (with a temperature increase of 0.8–1.4 °C by 2050) 88% of species distributions decreased, and 54% of species distributions decreased by at least 20%. Under an extreme scenario (temperature increase of 2.1–3.9 °C by 2050) 92% of species distributions decreased, and 83% of species distributions decreased by at least 50%. Furthermore, the proportion of the current range that was contained within the predicted range decreased from an average of 63% under a very conservative scenario to less than 22% under the most extreme scenario. By assessing the climatic ranges that species are currently exposed to, the extent of potential changes in distributions in response to climate change and details of their life histories, we identified species whose characteristics may make them particularly vulnerable to climate change in the future.     

The importance of biotic interactions for modelling species distributions under climate change

Aim There is a debate as to whether biotic interactions exert a dominant role in governing species distributions at macroecological scales. The prevailing idea is that climate is the key limiting factor; thus models that use present‐day climate–species range relationships are expected to provide reasonable means to quantify the impacts of climate change on species distributions. However, there is little empirical evidence that biotic interactions would not constrain species distributions at macroecological scales. We examine this idea, for the first time, and provide tests for two null hypotheses: (H₀ 1) – biotic interactions do not exert a significant role in explaining current distributions of a particular species of butterfly (clouded Apollo, Parnassius mnemosyne) in Europe; and (H₀ 2) – biotic interactions do not exert a significant role in predictions of altered species’ ranges under climate change. Location Europe. Methods Generalized additive modelling (GAM) was used to investigate relationships between species and climate; species and host plants; and species and climate + host plants. Because models are sensitive to the variable selection strategies utilised, four alternative approaches were used: AIC (Akaike's Information Criterion), BIC (Bayesian Information Criterion), BRUTO (Adaptive Backfitting), and CROSS (Cross Selection). Results In spite of the variation in the variables selected with different methods, both hypotheses (H₀ 1 and H₀ 2) were falsified, providing support for the proposition that biotic interactions significantly affect both the explanatory and predictive power of bioclimatic envelope models at macro scales. Main conclusions Our results contradict the widely held view that the effects of biotic interactions on individual species distributions are not discernible at macroecological scales. Results are contingent on the species, type of interaction and methods considered, but they call for more stringent evidence in support of the idea that purely climate‐based modelling would be sufficient to quantify the impacts of climate change on species distributions.     

Dominant climate influences on North American bird distributions

Aim Geographic distributions of species are constrained by several factors acting at different scales, with climate assumed to be a major determinant at broad extents. Recent studies, however, have challenged this statement and indicated that climate may not dominate among the factors governing geographic distributions of species. Here, we argue that these results are misleading due to the lack of consideration of the geographic area that has been accessible to the species. Location North America. Methods We generated null distributions for 75 North American endemic and 19 non‐endemic bird species. For each species, climatic envelopes of observed and null distributions were modelled using neural networks and generalized linear models, and seven climatic predictors. Values of the area under the receiver–operating characteristic curve (AUC) based on models of observed distributions were compared with corresponding AUC values for the null distributions. Results More than 82% of the endemic species showed AUC higher for the observed than for the null distributions, while 63% of the non‐endemic species showed such a pattern. Main conclusions We demonstrate a dominant climatic signal in shaping North American bird distributions. Our results attest to the importance of climate in determining species distributions and support the use of climate‐envelope models for estimating potential distributional areas at the appropriate spatial scales.     

Physiological effects of climate on distributions of endothermic species

Aim Determining the mechanisms underlying climatic limitation of species distributions is essential for understanding responses to current climatic change. Disentangling direct (e.g. physiological) and indirect (e.g. trophic) effects of climate on distributions through occurrence‐based modelling is problematic because most species use the same area for both shelter and food acquisition. By focusing on marine birds that breed on land but feed at sea, we exploit a rare opportunity to dissociate direct from indirect climatic effects on endothermic species. Location Coastal Europe. Methods We developed climate‐response surfaces (CRS) for 13 seabird species in coastal Europe, linking terrestrial climatic variables considered important for heat transfer with presence/absence data across each species’ entire European breeding range. Agreement between modelled and actual distribution was assessed for jackknifed samples using area under the curve (AUC) of receiver operating characteristic plots. Higher AUC values indicated closer correspondence between observed breeding distribution and terrestrial climate. We assessed the influence of several ecological factors on model performance across species. Results Species maximum foraging range and breeding latitude explained the greatest proportion of variation in AUC across species. AUC was positively related to both latitude and foraging range. Main conclusions The positive relationship between foraging range and AUC suggests that species foraging further are more likely to be constrained by environmental heat stress conditions at the breeding site. One plausible explanation is that long foraging trips result in one parent spending long periods in continuous nest attendance, exposed to such conditions. These may include negative impacts through predation and parasitism in addition to physiological responses to the thermal environment, which probably explains why our models performed better for species breeding at higher latitudes, where such species interactions are considered less important. These data highlight the importance of considering physiological impacts of climate for endothermic species, and suggest that widespread oceanographic changes that reduce prey quality and quantity for seabirds at sea may be exacerbated by additional impacts of climate at the breeding site.     

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.     

Validation of species–climate impact models under climate change

Increasing concern over the implications of climate change for biodiversity has led to the use of species–climate envelope models to project species extinction risk under climate‐change scenarios. However, recent studies have demonstrated significant variability in model predictions and there remains a pressing need to validate models and to reduce uncertainties. Model validation is problematic as predictions are made for events that have not yet occurred. Resubstituition and data partitioning of present‐day data sets are, therefore, commonly used to test the predictive performance of models. However, these approaches suffer from the problems of spatial and temporal autocorrelation in the calibration and validation sets. Using observed distribution shifts among 116 British breeding‐bird species over the past ～20 years, we are able to provide a first independent validation of four envelope modelling techniques under climate change. Results showed good to fair predictive performance on independent validation, although rules used to assess model performance are difficult to interpret in a decision‐planning context. We also showed that measures of performance on nonindependent data provided optimistic estimates of models' predictive ability on independent data. Artificial neural networks and generalized additive models provided generally more accurate predictions of species range shifts than generalized linear models or classification tree analysis. Data for independent model validation and replication of this study are rare and we argue that perfect validation may not in fact be conceptually possible. We also note that usefulness of models is contingent on both the questions being asked and the techniques used. Implementations of species–climate envelope models for testing hypotheses and predicting future events may prove wrong, while being potentially useful if put into appropriate context.     

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.     

Uncertainties in the projection of species distributions related to general circulation models

Ecological Niche Models (ENMs) are increasingly used by ecologists to project species potential future distribution. However, the application of such models may be challenging, and some caveats have already been identified. While studies have generally shown that projections may be sensitive to the ENM applied or the emission scenario, to name just a few, the sensitivity of ENM‐based scenarios to General Circulation Models (GCMs) has been often underappreciated. Here, using a multi‐GCM and multi‐emission scenario approach, we evaluated the variability in projected distributions under future climate conditions. We modeled the ecological realized niche (sensu Hutchinson) and predicted the baseline distribution of species with contrasting spatial patterns and representative of two major functional groups of European trees: the dwarf birch and the sweet chestnut. Their future distributions were then projected onto future climatic conditions derived from seven GCMs and four emissions scenarios using the new Representative Concentration Pathways (RCPs) developed for the Intergovernmental Panel on Climate Change (IPCC) AR5 report. Uncertainties arising from GCMs and those resulting from emissions scenarios were quantified and compared. Our study reveals that scenarios of future species distribution exhibit broad differences, depending not only on emissions scenarios but also on GCMs. We found that the between‐GCM variability was greater than the between‐RCP variability for the next decades and both types of variability reached a similar level at the end of this century. Our result highlights that a combined multi‐GCM and multi‐RCP approach is needed to better consider potential trajectories and uncertainties in future species distributions. In all cases, between‐GCM variability increases with the level of warming, and if nothing is done to alleviate global warming, future species spatial distribution may become more and more difficult to anticipate. When future species spatial distributions are examined, we propose to use a large number of GCMs and RCPs to better anticipate potential trajectories and quantify uncertainties.     

Effects of climate change on species turnover and body mass frequency distributions of South African bird communities

Climate change will lead to substantial shifts in species distributions. Most of the predictions of shifting distributions rely on modelling future distributions with ecological niche models. We used these models to investigate (i) the expected species turnover, loss and gain within bird communities of four South African biomes and (ii) the expected changes in the body mass frequency distributions of these communities. We used distributional data of the Southern African Bird Atlas Project, current climate data and two scenarios of future climate change for 2050 to build ensemble models of bird distributions. Our results indicate that future species loss, gain and turnover within the four biomes will be considerable. Climate change will also have statistically significant effects on body mass frequency distributions, and these effects differ substantially depending on the severity of future climate change. We discuss the possible ecological effects of these predicted changes on ecosystem interactions and functions.     

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.     

Predicting species distribution and abundance responses to climate change: why it is essential to include biotic interactions across trophic levels

Current predictions on species responses to climate change strongly rely on projecting altered environmental conditions on species distributions. However, it is increasingly acknowledged that climate change also influences species interactions. We review and synthesize literature information on biotic interactions and use it to argue that the abundance of species and the direction of selection during climate change vary depending on how their trophic interactions become disrupted. Plant abundance can be controlled by aboveground and belowground multitrophic level interactions with herbivores, pathogens, symbionts and their enemies. We discuss how these interactions may alter during climate change and the resulting species range shifts. We suggest conceptual analogies between species responses to climate warming and exotic species introduced in new ranges. There are also important differences: the herbivores, pathogens and mutualistic symbionts of range-expanding species and their enemies may co-migrate, and the continuous gene flow under climate warming can make adaptation in the expansion zone of range expanders different from that of cross-continental exotic species. We conclude that under climate change, results of altered species interactions may vary, ranging from species becoming rare to disproportionately abundant. Taking these possibilities into account will provide a new perspective on predicting species distribution under climate change.     

Predicted impact of climate change on European bats in relation to their biogeographic patterns

There has been considerable recent interest concerning the impact of climate change on a wide range of taxa. However, little is known about how the biogeographic affinities of taxa may affect their responses to these impacts. Our main aim was to study how predicted climate change will affect the distribution of 28 European bat species grouped by their biogeographic patterns as determined by a spatial Principal Component Analysis. Using presence‐only modelling techniques and climatic data (minimum temperature, average temperature, precipitation, humidity and daily temperature range) for four different climate change scenarios (IPCC scenarios ranging from the most extreme A1FI, A2, B2 to the least severe, B1), we predict the potential geographic distribution of bat species in Europe grouped according to their biogeographic patterns for the years 2020–2030, 2050–2060 and 2090–2100. Biogeographic patterns exert a great influence on a species' response to climate change. Bat species more associated with colder climates, hence northern latitudes, could be more severely affected with some extinctions predicted by the end of the century. The Mediterranean and Temperate groups seem to be more tolerant of temperature increases, however, their projections varied considerably under different climate change scenarios. Scenario A1FI was clearly the most detrimental for European bat diversity, with several extinctions and declines in occupied area predicted for several species. The B scenarios were less damaging and even predicted that some species could increase their geographical ranges. However, all models only took into account climatic envelopes whereas available habitat and species interactions will also probably play an important role in delimiting future distribution patterns. The models may therefore generate ‘best case’ predictions about future changes in the distribution of European bats.     

Where will species go? Incorporating new advances in climate modelling into projections of species distributions

Bioclimatic models are the primary tools for simulating the impact of climate change on species distributions. Part of the uncertainty in the output of these models results from uncertainty in projections of future climates. To account for this, studies often simulate species responses to climates predicted by more than one climate model and/or emission scenario. One area of uncertainty, however, has remained unexplored: internal climate model variability. By running a single climate model multiple times, but each time perturbing the initial state of the model slightly, different but equally valid realizations of climate will be produced. In this paper, we identify how ongoing improvements in climate models can be used to provide guidance for impacts studies. In doing so we provide the first assessment of the extent to which this internal climate model variability generates uncertainty in projections of future species distributions, compared with variability between climate models. We obtained data on 13 realizations from three climate models (three from CSIRO Mark2 v3.0, four from GISS AOM, and six from MIROC v3.2) for two time periods: current (1985–1995) and future (2025–2035). Initially, we compared the simulated values for each climate variable (P, T_max, T_min, and T_mean) for the current period to observed climate data. This showed that climates simulated by realizations from the same climate model were more similar to each other than to realizations from other models. However, when projected into the future, these realizations followed different trajectories and the values of climate variables differed considerably within and among climate models. These had pronounced effects on the projected distributions of nine Australian butterfly species when modelled using the BIOCLIM component of DIVA-GIS. Our results show that internal climate model variability can lead to substantial differences in the extent to which the future distributions of species are projected to change. These can be greater than differences resulting from between-climate model variability. Further, different conclusions regarding the vulnerability of species to climate change can be reached due to internal model variability. Clearly, several climate models, each represented by multiple realizations, are required if we are to adequately capture the range of uncertainty associated with projecting species distributions in the future.     

Using species distributions models for designing conservation strategies of Tropical Andean biodiversity under climate change

Biodiversity in the Tropical Andes is under continuous threat from anthropogenic activities. Projected changes in climate will likely exacerbate this situation. Using species distribution models, we assess possible future changes in the diversity and climatic niche size of an unprecedented number of species for the region. We modeled a broad range of taxa (11,012 species of birds and vascular plants), including both endemic and widespread species and provide a comprehensive estimation of climate change impacts on the Andes. We find that if no dispersal is assumed, by 2050s, more than 50% of the species studied are projected to undergo reductions of at least 45% in their climatic niche, whilst 10% of species could be extinct. Even assuming unlimited dispersal, most of the Andean endemics (comprising ∼5% of our dataset) would become severely threatened (>50% climatic niche loss). While some areas appear to be climatically stable (e.g. Pichincha and Imbabura in Ecuador; and Nariño, Cauca, Valle del Cauca and Putumayo in Colombia) and hence depict little diversity loss and/or potential species gains, major negative impacts were also observed. Tropical high Andean grasslands (páramos and punas) and evergreen montane forests, two key ecosystems for the provision of environmental services in the region, are projected to experience negative changes in species richness and high rates of species turnover. Adapting to these impacts would require a landscape-network based approach to conservation, including protected areas, their buffer zones and corridors. A central aspect of such network is the implementation of an integrated landscape management approach based on sustainable management and restoration practices covering wider areas than currently contemplated.     

The data void in modeling current and future distributions of tropical species

Conserving biodiversity in the face of climate change requires a predictive ecology of species distributions. Nowhere is this need more acute than in the tropics, which harbor the majority of Earth's species and face rapid and large climate and land‐use changes. However, the study of species distributions and their responses to climate change in high diversity tropical regions is potentially crippled by a lack of basic data. We analyzed a database representing more than 800 000 unique geo‐referenced natural history collections to determine what fraction of tropical plant species has sufficient numbers of available collections for use in the habitat or niche models commonly used to predict species responses to climate change. We found that more than nine out of 10 species from the three principle tropical realms are so poorly collected (n < 20 records) that they are essentially invisible to modern modeling and conservation tools. In order to predict the impact of climate change on tropical species, efforts must be made to increase the amount of data available from tropical countries through a combination of collecting new specimens and digitizing existing records.