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.     

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.     

Habitat characteristics and the distribution of Odonata in a lowland river catchment in eastern England

The influence of habitat characteristics on the distribution of larval and adult Odonata communities in a lowland river in eastern England was studied. There was a longitudinal distribution of Odonata, with larval assemblages being influenced directly by marginal flow velocity, biochemical oxygen demand (BOD) and phosphate concentrations and indirectly by shade and cover of floating vegetation. Adult populations responded directly to shade, reed cover, amenity-managed land use and bank height, and indirectly to BOD and ammonia concentrations. Distribution patterns were strongly associated with both natural changes along the river system and management impacts. River management practices locally disrupted the natural displacement of species along the river, but whilst some forms of human interference on river systems were beneficial to species richness, the effects on stenotopic species were disadvantageous. To conserve Odonata management emphasis should be on the maintenance of suitable conditions for river specialists.     

Population trends influence species ability to track climate change

Shifts of distributions have been attributed to species tracking their fundamental climate niches through space. However, several studies have now demonstrated that niche tracking is imperfect, that species’ climate niches may vary with population trends, and that geographic distributions may lag behind rapid climate change. These reports of imperfect niche tracking imply shifts in species’ realized climate niches. We argue that quantifying climate niche shifts and analyzing them for a suite of species reveal general patterns of niche shifts and the factors affecting species’ ability to track climate change. We analyzed changes in realized climate niche between 1984 and 2012 for 46 species of North American birds in relation to population trends in an effort to determine whether species differ in the ability to track climate change and whether differences in niche tracking are related to population trends. We found that increasingly abundant species tended to show greater levels of niche expansion (climate space occupied in 2012 but not in 1980) compared to declining species. Declining species had significantly greater niche unfilling (climate space occupied in 1980 but not in 2012) compared to increasing species due to an inability to colonize new sites beyond their range peripheries after climate had changed at sites of occurrence. Increasing species, conversely, were better able to colonize new sites and therefore showed very little niche unfilling. Our results indicate that species with increasing trends are better able to geographically track climate change compared to declining species, which exhibited lags relative to changes in climate. These findings have important implications for understanding past changes in distribution, as well as modeling dynamic species distributions in the face of climate change.     

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.     

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.     

Do climate envelope models transfer? A manipulative test using dung beetle introductions

Climate envelope models (CEMs) are widely used to forecast future shifts in species ranges under climate change, but these models are rarely validated against independent data, and their fundamental assumption that climate limits species distributions is rarely tested. Here, we use the data on the introduction of five South African dung beetle species to Australia to test whether CEMs developed in the native range can predict distribution in the introduced range, where the confounding effects of dispersal limitation, resource limitation and the impact of natural enemies have been removed, leaving climate as the dominant constraint. For two of the five species, models developed in the native range predict distribution in the introduced range about as well as models developed in the introduced range where we know climate limits distribution. For the remaining three species, models developed in the native range perform poorly, implying that non-climatic factors limit the native distribution of these species and need to be accounted for in species distribution models. Quantifying relevant non-climatic factors and their likely interactions with climatic variables for forecasting range shifts under climate change remains a challenging task.     

Probabilistic spatio‐temporal assessment of vegetation vulnerability to climate change in Swaziland

In a spatially explicit climate change impact assessment, a Bayesian network (BN) model was implemented to probabilistically simulate future response of the four major vegetation types in Swaziland. Two emission scenarios (A2 and B2) from an ensemble of three statistically downscaled coupled atmosphere‐ocean global circulation models (CSIRO‐Mk3, CCCma‐CGCM3 and UKMO‐HadCM3) were used to simulate possible changes in BN‐based environmental envelopes of major vegetation communities. Both physiographic and climatic data were used as predictors representing the 2020s, 2050s and the 2080s periods. A comparison of simulated vegetation distribution and the expert vegetation map under baseline conditions showed an overall correspondence of 97.7% and a Kappa coefficient of 0.966. Although the ensemble projections showed comparable trends during the 2020s, the results from the A2 storyline were more drastic indicating that grassland and the Lebombo bushveld will be impacted negatively as early as the 2020s with about 1 °C temperature increase. The bioclimatically suitable areas of all but one vegetation type decline drastically after about 2 °C warming, more so under the more severe A2 scenario and in particular during the 2080s. The sour bushveld is the only vegetation type that initially responds positively to warming by possibly encroaching to the highly vulnerable grassland areas. Vulnerability of vegetation is increased by the limited ability to migrate into suitable climates due to close affinity to certain geological formations and the fragmentation of the landscape by agriculture and other land uses. This is expected to have serious impacts on biodiversity in the country. Under warmer climates, the likely vegetation types to emerge are uncertain due to future novel combinations of climate and bedrock lithology. The strengths and limitations of the BN approach are also discussed.     

Douglas‐fir plantations in Europe: a retrospective test of assisted migration to address climate change

We evaluate genetic test plantations of North American Douglas‐fir provenances in Europe to quantify how tree populations respond when subjected to climate regime shifts, and we examined whether bioclimate envelope models developed for North America to guide assisted migration under climate change can retrospectively predict the success of these provenance transfers to Europe. The meta‐analysis is based on long‐term growth data of 2800 provenances transferred to 120 European test sites. The model was generally well suited to predict the best performing provenances along north–south gradients in Western Europe, but failed to predict superior performance of coastal North American populations under continental climate conditions in Eastern Europe. However, model projections appear appropriate when considering additional information regarding adaptation of Douglas‐fir provenances to withstand frost and drought, even though the model partially fails in a validation against growth traits alone. We conclude by applying the partially validated model to climate change scenarios for Europe, demonstrating that climate trends observed over the last three decades warrant changes to current use of Douglas‐fir provenances in plantation forestry throughout Western and Central Europe.     

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.     

Habitat connectivity and dispersal ability drive the assembly mechanisms of macroinvertebrate communities in river networks

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Predicting extinction risks under climate change: coupling stochastic population models with dynamic bioclimatic habitat models

Species responses to climate change may be influenced by changes in available habitat, as well as population processes, species interactions and interactions between demographic and landscape dynamics. Current methods for assessing these responses fail to provide an integrated view of these influences because they deal with habitat change or population dynamics, but rarely both. In this study, we linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations under stable and changing climate scenarios in South African fynbos, a global biodiversity hot spot. Results indicate that complex interactions between life history, disturbance regime and distribution pattern mediate species extinction risks under climate change. Our novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change.     

The influence of climate change on the distribution of indigenous forest in KwaZulu-Natal, South Africa

Aims (1) To define the physical correlates of indigenous forest in KwaZulu-Natal province and develop a model, based on climatic parameters, to predict the potential distribution of forest subtypes in the province. (2) To explore the impact of palaeoclimatic change on forest distribution, providing an insight into the regional-scale/historical forces shaping the pattern and composition of present-day forest communities. (3) To investigate potential future shifts in forest distribution associated with projected climate change. Location KwaZulu-Natal province, South Africa. Methods A BIOCLIM-type approach is adopted. Bioclimatic ‘profiles’ for eight different forest subtypes are defined from a series of grid overlays of current forest distribution against nineteen climatic and geographical variables, using ArcInfo GIS grid-based processing. A principal components analysis is performed on a selection of individual forests to identify those variables most significant in distinguishing different forest subtypes. Five models are developed to predict the distribution of forest subtypes from their bioclimatic profiles. Maps of the potential distribution of forest subtypes predicted by these models under current climatic conditions are produced, and model accuracy assessed. One model is applied to two palaeoclimatic scenarios, the Last Glacial Maximum (LGM) (≈18,000 BP ) and the Holocene altithermal (≈7000 BP ), and to projected future climate under a doubling in global atmospheric carbon dioxide. Results Seven variables; altitude, mean annual temperature, annual rainfall range, potential evaporation, annual temperature range, mean annual precipitation and mean winter rainfall, are most important in distinguishing different forest subtypes. Under the most accurate model, the potential present-day distribution of all forest subtypes is more extensive than is actually observed, but is supported by recent historical evidence. During the LGM, Afromontane forest occupied a much reduced and highly fragmented area in the mid-altitude region currently occupied by scarp forest. During the Holocene altithermal, forest expanded in area, with a mixing of Afromontane and Indian Ocean coastal belt forest elements along the present-day scarp forest belt. Under projected climatic conditions, forest shifts in altitude and latitude and occupies an area similar to its current potential and more extensive than its actual current distribution. Main conclusions Biogeographical history and present physical diversity play a major role in the evolution and persistence of the diversity of forest in KwaZulu-Natal. It is important to adopt a long-term and regional perspective to forest ecology, biogeography, conservation and management. The area and altitudinal and latitudinal distribution of forest subtypes show considerable sensitivity to climate change. The isolation of forest by anthropogenic landscape change has limited its radiation potential and ability to track environmental change. Long-term forest preservation requires reserves in climatically stable areas, or spanning altitudinal or latitudinal gradients allowing for forest migration, along with innovative matrix management strategies. Dune, sand, swamp, riverine and lowland forest subtypes are most at risk. Scarp forests are highlighted as former refugia and important for the future conservation of forest biodiversity.     

Regional analysis of the impacts of climate change on cheatgrass invasion shows potential risk and opportunity

Interactions between climate change and non-native invasive species may combine to increase invasion risk to native ecosystems. Changing climate creates risk as new terrain becomes climatically suitable for invasion. However, climate change may also create opportunities for ecosystem restoration on invaded lands that become climatically unsuitable for invasive species. Here, I develop a bioclimatic envelope model for cheatgrass ( Bromus tectorum ), a non-native invasive grass in the western US, based on its invaded distribution. The bioclimatic envelope model is based on the Mahalanobis distance using the climate variables that best constrain the species' distribution. Of the precipitation and temperature variables measured, the best predictors of cheatgrass are summer, annual, and spring precipitation, followed by winter temperature. I perform a sensitivity analysis on potential cheatgrass distributions using the projections of 10 commonly used atmosphere–ocean general circulation models (AOGCMs) for 2100. The AOGCM projections for precipitation vary considerably, increasing uncertainty in the assessment of invasion risk. Decreased precipitation, particularly in the summer, causes an expansion of suitable land area by up to 45%, elevating invasion risk in parts of Montana, Wyoming, Utah, and Colorado. Conversely, increased precipitation reduces habitat by as much as 70%, decreasing invasion risk. The strong influence of precipitation conditions on this species' distribution suggests that relying on temperature change alone to project future change in plant distributions may be inadequate. A sensitivity analysis provides a framework for identifying key climate variables that may limit invasion, and for assessing invasion risk and restoration opportunities with climate change.     

Identifying refugia from climate change

This article highlights how the loose definition of the term ‘refugia’ has led to discrepancies in methods used to assess the vulnerability of species to the current trend of rising global temperatures. The term ‘refugia’ is commonly used without distinguishing between macrorefugia and microrefugia, ex situ refugia and in situ refugia, glacial and interglacial refugia or refugia based on habitat stability and refugia based on climatic stability. It is not always clear which definition is being used, and this makes it difficult to assess the appropriateness of the methods employed. For example, it is crucial to develop accurate fine‐scale climate grids when identifying microrefugia, but coarse‐scale macroclimate might be adequate for determining macrorefugia. Similarly, identifying in situ refugia might be more appropriate for species with poor dispersal ability but this may overestimate the extinction risk for good dispersers. More care needs to be taken to properly define the context when referring to refugia from climate change so that the validity of methods and the conservation significance of refugia can be assessed.     

Climatic niche of the Saker Falcon Falco cherrug: predicted new areas to direct population surveys in Central Asia

Accurate species distribution data across remote and extensive geographical areas are difficult to obtain. Here, we use bioclimatic envelope models to determine climatic constraints on the distribution of the migratory Saker Falcon Falco cherrug to identify areas in data-deficient regions that may contain unidentified populations. Sakers live at low densities across large ranges in remote regions, making distribution status difficult to assess. Using presence-background data and eight bioclimatic variables within a species distribution modelling framework, we applied MaxEnt to construct models for both breeding and wintering ranges. Occurrence data were spatially filtered and climatic variables tested for multicollinearity before selecting best fit models using the Akaike information criterion by tuning MaxEnt parameters. Model predictive performance tested using the continuous Boyce index (B) was high for both breeding (B_TEST = 0.921) and wintering models (B_TEST = 0.735), with low omission rates and minimal overfitting. The Saker climatic niche was defined by precipitation in the warmest quarter in the breeding range model, and mean temperature in the wettest quarter in the wintering range model. Our models accurately predicted areas of highest climate suitability and defined the climatic constraints on a wide-ranging rare species, suggesting that climate is a key determinant of Saker distribution across macro-scales. We recommend targeted population surveys for the Saker based on model predictions to areas of highest climatic suitability in key regions with distribution knowledge gaps, in particular the Qinghai-Tibet plateau in western China. Further applications of our models could identify protected areas and reintroduction sites, inform development conflicts, and assess the impact of climate change on distributions.