Disregarding the edaphic dimension in species distribution models leads to the omission of crucial spatial information under climate change: the case of Quercus pubescens in France

Species distribution modelling is an easy, persuasive and useful tool for anticipating species distribution shifts under global change. Numerous studies have used only climate variables to predict future potential species range shifts and have omitted environmental factors important for determining species distribution. Here, we assessed the importance of the edaphic dimension in the niche‐space definition of Quercus pubescens and in future spatial projections under global change over the metropolitan French forest territory. We fitted two species distribution models (SDM) based on presence/absence data (111 013 plots), one calibrated from climate variables only (mean temperature of January and climatic water balance of July) and the other one from both climate and edaphic (soil pH inferred from plants) variables. Future predictions were conducted under two climate scenarios (PCM B2 and HadCM3 A2) and based on 100 simulations using a cellular automaton that accounted for seed dispersal distance, landscape barriers preventing migration and unsuitable land cover. Adding the edaphic dimension to the climate‐only SDM substantially improved the niche‐space definition of Q. pubescens, highlighting an increase in species tolerance in confronting climate constraints as the soil pH increased. Future predictions over the 21st century showed that disregarding the edaphic dimension in SDM led to an overestimation of the potential distribution area, an underestimation of the spatial fragmentation of this area, and prevented the identification of local refugia, leading to an underestimation of the northward shift capacity of Q. pubescens and its persistence in its current distribution area. Spatial discrepancies between climate‐only and climate‐plus‐edaphic models are strengthened when seed dispersal and forest fragmentation are accounted for in predicting a future species distribution area. These discrepancies highlight some imprecision in spatial predictions of potential distribution area of species under climate change scenarios and possibly wrong conclusions for conservation and management perspectives when climate‐only models are used.     

Climate change is the primary driver of white‐tailed deer (Odocoileus virginianus) range expansion at the northern extent of its range; land use is secondary

Quantifying the relative influence of multiple mechanisms driving recent range expansion of non‐native species is essential for predicting future changes and for informing adaptation and management plans to protect native species. White‐tailed deer (Odocoileus virginianus) have been expanding their range into the North American boreal forest over the last half of the 20th century. This has already altered predator–prey dynamics in Alberta, Canada, where the distribution likely reaches the northern extent of its continuous range. Although current white‐tailed deer distribution is explained by both climate and human land use, the influence each factor had on the observed range expansion would depend on the spatial and temporal pattern of these changes. Our objective was to quantify the relative importance of land use and climate change as drivers of white‐tailed deer range expansion and to predict decadal changes in white‐tailed deer distribution in northern Alberta for the first half of the 21st century. An existing species distribution model was used to predict past decadal distributions of white‐tailed deer which were validated using independent data. The effects of climate and land use change were isolated by comparing predictions under theoretical “no‐change between decades” scenarios, for each factor, to predictions under observed climate and land use change. Climate changes led to more than 88%, by area, of the increases in probability of white‐tailed deer presence across all decades. The distribution is predicted to extend 100 km further north across the northeastern Alberta boreal forest as climate continues to change over the first half of the 21st century.     

Simulating climate change impacts on forests and associated vascular epiphytes in a subtropical island of East Asia

Aim This study aims to assess the impact of climate change on forests and vascular epiphytes, using species distribution models (SDMs). Location Island of Taiwan, subtropical East Asia. Methods A hierarchical modelling approach incorporating forest migration velocity and forest type–epiphyte interactions with classical SDMs was used to model the responses of eight forest types and 237 vascular epiphytes for the year 2100 under two climate change scenarios. Forest distributions were modelled and modified by dominant tree species’ dispersal limitations and hypothesized persistence under unfavourable climate conditions (20 years for broad‐leaved trees and 50 years for conifers). The modelled forest projections together with 16 environmental variables were used as predictors in models of epiphyte distributions. A null method was applied to validate the significance of epiphyte SDMs, and potential vulnerable species were identified by calculating range turnover rates. Results For the year 2100, the model predicted a reduction in the range of most forest types, especially for Picea and cypress forests, which shifted to altitudes c. 400 and 300 m higher, respectively. The models indicated that epiphyte distributions are highly correlated with forest types, and the majority (77–78%) of epiphyte species were also projected to lose 45–58% of their current range, shifting on average to altitudes c. 400 m higher than currently. Range turnover rates suggested that insensitive epiphytes were generally lowland or widespread species, whereas sensitive species were more geographically restricted, showing a higher correlation with temperature‐related factors in their distributions. Main conclusions The hierarchical modelling approach successfully produced interpretable results, suggesting the importance of considering biotic interactions and the inclusion of terrain‐related factors when developing SDMs for dependant species at a local scale. Long‐term monitoring of potentially vulnerable sites is advised, especially of those sites that fall outside current conservation reserves where additional human disturbance is likely to exacerbate the effect of climate change.     

How much does climate change threaten European forest tree species distributions?

Although numerous species distribution models have been developed, most were based on insufficient distribution data or used older climate change scenarios. We aimed to quantify changes in projected ranges and threat level by the years 2061–2080, for 12 European forest tree species under three climate change scenarios. We combined tree distribution data from the Global Biodiversity Information Facility, EUFORGEN, and forest inventories, and we developed species distribution models using MaxEnt and 19 bioclimatic variables. Models were developed for three climate change scenarios—optimistic (RCP2.6), moderate (RCP4.5), and pessimistic (RPC8.5)—using three General Circulation Models, for the period 2061–2080. Our study revealed different responses of tree species to projected climate change. The species may be divided into three groups: “winners”—mostly late‐successional species: Abies alba, Fagus sylvatica, Fraxinus excelsior, Quercus robur, and Quercus petraea; “losers”—mostly pioneer species: Betula pendula, Larix decidua, Picea abies, and Pinus sylvestris; and alien species—Pseudotsuga menziesii, Quercus rubra, and Robinia pseudoacacia, which may be also considered as “winners.” Assuming limited migration, most of the species studied would face a significant decrease in suitable habitat area. The threat level was highest for species that currently have the northernmost distribution centers. Ecological consequences of the projected range contractions would be serious for both forest management and nature conservation.     

When and where to move: Dynamic occupancy models explain the range dynamics of a food nomadic bird under climate and land cover change

Globally, long‐term research is critical to monitor the responses of tropical species to climate and land cover change at the range scale. Citizen science surveys can reveal the long‐term persistence of poorly known nomadic tropical birds occupying fragmented forest patches. We applied dynamic occupancy models to 13 years (2002–2014) of citizen science‐driven presence/absence data on Cape parrot (Poicephalus robustus), a food nomadic bird endemic to South Africa. We modeled its underlying range dynamics as a function of resource distribution, and change in climate and land cover through the estimation of colonization and extinction patterns. The range occupancy of Cape parrot changed little over time (ψ = 0.75–0.83) because extinction was balanced by recolonization. Yet, there was considerable regional variability in occupancy and detection probability increased over the years. Colonizations increased with warmer temperature and area of orchards, thus explaining their range shifts southeastwards in recent years. Although colonizations were higher in the presence of nests and yellowwood trees (Afrocarpus and Podocarpus spp.), the extinctions in small forest patches (≤227 ha) and during low precipitation (≤41 mm) are attributed to resource constraints and unsuitable climatic conditions. Loss of indigenous forest cover and artificial lake/water bodies increased extinction probabilities of Cape parrot. The land use matrix (fruit farms, gardens, and cultivations) surrounding forest patches provides alternative food sources, thereby facilitating spatiotemporal colonization and extinction in the human‐modified matrix. Our models show that Cape parrots are vulnerable to extreme climatic conditions such as drought which is predicted to increase under climate change. Therefore, management of optimum sized high‐quality forest patches is essential for long‐term survival of Cape parrot populations. Our novel application of dynamic occupancy models to long‐term citizen science monitoring data unfolds the complex relationships between the environmental dynamics and range fluctuations of this food nomadic species.     

Winter climate change and coastal wetland foundation species: salt marshes vs. mangrove forests in the southeastern United States

We live in an era of unprecedented ecological change in which ecologists and natural resource managers are increasingly challenged to anticipate and prepare for the ecological effects of future global change. In this study, we investigated the potential effect of winter climate change upon salt marsh and mangrove forest foundation species in the southeastern United States. Our research addresses the following three questions: (1) What is the relationship between winter climate and the presence and abundance of mangrove forests relative to salt marshes; (2) How vulnerable are salt marshes to winter climate change‐induced mangrove forest range expansion; and (3) What is the potential future distribution and relative abundance of mangrove forests under alternative winter climate change scenarios? We developed simple winter climate‐based models to predict mangrove forest distribution and relative abundance using observed winter temperature data (1970–2000) and mangrove forest and salt marsh habitat data. Our results identify winter climate thresholds for salt marsh–mangrove forest interactions and highlight coastal areas in the southeastern United States (e.g., Texas, Louisiana, and parts of Florida) where relatively small changes in the intensity and frequency of extreme winter events could cause relatively dramatic landscape‐scale ecosystem structural and functional change in the form of poleward mangrove forest migration and salt marsh displacement. The ecological implications of these marsh‐to‐mangrove forest conversions are poorly understood, but would likely include changes for associated fish and wildlife populations and for the supply of some ecosystem goods and services.     

Quantifying multiple pressure interactions affecting populations of a recreationally and commercially important freshwater fish

The expanding human global footprint and growing demand for freshwater have placed tremendous stress on inland aquatic ecosystems. Aichi Target 10 of the Convention on Biological Diversity aims to minimize anthropogenic pressures affecting vulnerable ecosystems, and pressure interactions are increasingly being incorporated into environmental management and climate change adaptation strategies. In this study, we explore how climate change, overfishing, forest disturbance, and invasive species pressures interact to affect inland lake walleye (Sander vitreus) populations. Walleye support subsistence, recreational, and commercial fisheries and are one of most sought‐after freshwater fish species in North America. Using data from 444 lakes situated across an area of 475 000 km² in Ontario, Canada, we apply a novel statistical tool, R‐INLA, to determine how walleye biomass deficit (carrying capacity—observed biomass) is impacted by multiple pressures. Individually, angling activity and the presence of invasive zebra mussels (Dreissena polymorpha) were positively related to biomass deficits. In combination, zebra mussel presence interacted negatively and antagonistically with angling activity and percentage decrease in watershed mature forest cover. Velocity of climate change in growing degree days above 5°C and decrease in mature forest cover interacted to negatively affect walleye populations. Our study demonstrates how multiple pressure evaluations can be conducted for hundreds of populations to identify influential pressures and vulnerable ecosystems. Understanding pressure interactions is necessary to guide management and climate change adaptation strategies, and achieve global biodiversity targets.     

Spatial heterogeneity of climate and land-cover constraints on distributions of tick-borne pathogens

Aim To compare the geographical distributions of two tick‐borne pathogens vectored by different tick species, to examine the relative importance of climate, land cover and host density in structuring these distributions, and to assess the spatial variability of these environmental constraints across the species ranges. Location South‐central and south‐eastern North America. Methods Presence/absence data for two tick‐borne pathogens, Ehrlichia chaffeensis and Anaplasma phagocytophilum, were obtained for 567 counties from a regional data base based on white‐tailed deer (Odocoileus virginianus) serology. Environmental variables describing climate, land cover and deer density were calculated for these counties. Global logistic regression analysis was used to screen the environmental variables and select a parsimonious subset of predictors. Local analysis was carried out using geographically weighted regression (GWR) to explore spatial variability in the parameters of the regression models. Cluster analysis was applied to the GWR output to identify zones with distinctive species–habitat relationships. Results Global habitat models for E. chaffeensis and A. phagocytophilum included temperature, humidity, precipitation and forest cover as explanatory variables. The E. chaffeensis model also included forest fragmentation, whereas the A. phagocytophilum model included deer density. Local analyses revealed that climate was the primary correlate of pathogen presence in the eastern portion of the study area, whereas forest cover and fragmentation constrained the western range boundaries. Habitat relationships for all variables were weak in and around the Mississippi Delta. Main conclusions Efforts to model pathogen and disease ranges, and to predict shifts in response to global change should consider future scenarios of land‐cover change as well as climate change, and should address the possibility of spatial heterogeneity in species–habitat relationships. The methods presented here outline an approach for objectively delineating geographical zones with similar species–environment relationships, which can then be used to stratify landscapes for the purposes of further explanatory and predictive modelling.     

Climate‐niche factor analysis: a spatial approach to quantifying species vulnerability to climate change

Climate change vulnerability assessments are an important tool for understanding the threat that climate change poses to species and populations, but do not generally yield insight into the spatial variation in vulnerability throughout a species’ habitat. We demonstrate how to adapt the method of ecological‐niche factor analysis (ENFA) to objectively quantify aspects of species sensitivity to climate change. We then expand ENFA to quantify aspects of exposure and vulnerability to climate change as well, using future projections of global climate models. This approach provides spatially‐explicit insight into geographic patterns of vulnerability, relies only on readily‐available spatial data, is suitable for a wide range of species and habitats, and invites comparison between different species. We apply our methods to a case study of two species of montane mammals, the American pika Ochotona princeps and the yellow‐bellied marmot Marmota flaviventris.     

Are large‐scale distributional shifts of the blue‐winged macaw (Primolius maracana) related to climate change?

Aim To evaluate whether observed geographical shifts in the distribution of the blue‐winged macaw (Primolius maracana) are related to ongoing processes of global climate change. This species is vulnerable to extinction and has shown striking range retractions in recent decades, withdrawing broadly from southern portions of its historical distribution. Its range reduction has generally been attributed to the effects of habitat loss; however, as this species has also disappeared from large forested areas, consideration of other factors that may act in concert is merited. Location Historical distribution of the blue‐winged macaw in Brazil, eastern Paraguay and northern Argentina. Methods We used a correlative approach to test a hypothesis of causation of observed shifts by reduction of habitable areas mediated by climate change. We developed models of the ecological niche requirements of the blue‐winged macaw, based on point‐occurrence data and climate scenarios for pre‐1950 and post‐1950 periods, and tested model predictivity for anticipating geographical distributions within time periods. Then we projected each model to the other time period and compared distributions predicted under both climate scenarios to assess shifts of habitable areas across decades and to evaluate an explanation for observed range retractions. Results Differences between predicted distributions of the blue‐winged macaw over the twentieth century were, in general, minor and no change in suitability of landscapes was predicted across large areas of the species’ original range in different time periods. No tendency towards range retraction in the south was predicted, rather conditions in the southern part of the species’ range tended to show improvement for the species. Main conclusions Our test permitted elimination of climate change as a likely explanation for the observed shifts in the distribution of the blue‐winged macaw, and points rather to other causal explanations (e.g. changing regional land use, emerging diseases).     

Modelling the potential distribution of endangered Prunus africana (Hook.f.) Kalkm. in East Africa

Continued harvesting and climate change are affecting the distributions of many plant species and may lead to numerous extinctions over the next century. Endangered species are likely to be a special concern, but the extent to which they are sensitive to climate is currently unclear. Species distribution modelling, if carefully implemented, can be used to assess climate sensitivity and potential climate change impacts, of tree species. We used MaxEnt algorithm for species distribution modelling to assess the potential distribution and climate change risks for a threatened Prunus africana, in East Africa. Data from different herbaria on its distribution were linked to data on climate to test hypotheses on the factors determining its distribution. Predictive models were developed and projected onto a climate scenario for 2050 to assess climate change risks. Precipitation of driest quarter and annual precipitation appeared to be the main factors influencing its distribution. Climate change was predicted to result in reductions of the species' habitats (e.g. Erasmus et al., Glob. Change Biol. 2002; 8 : 679). Prunus africana distribution is thus highly vulnerable to a warming climate and highlights the fact that both in‐situ and ex‐situ conservation will be a solution to global warming.     

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.     

Modelling changes in the distribution of the critical food resources of a specialist folivore in response to climate change

Aim An important consideration when planning to conserve a species under climate change is to understand how the distribution of its food resources may also contract or shift under those same climatic conditions. Here, we use a case study to demonstrate a spatial conservation planning approach to inform decisions about where, under climate change, to protect and restore critical food and habitat resources for highly specialized species. Location Eastern Australia. Methods We developed fitted models for the koala (Phascolarctos cinereus) and five of its key eucalypt food trees using the maximum entropy algorithm available in Maxent. We then projected these models using a range of IPCC A1FI climate change scenarios and identified areas with a higher probability of occurrence. We calculated where the koala and its food trees may co‐occur under future climate change. Results The koala and its food trees experienced significant range contractions as climate change progressed, sometimes to regions outside their current distributions. The inland species Eucalyptus camaldulensis and Eucalyptus coolabah contracted from the more arid interior, which is outside the koala range, but persisted in the eastern regions of the koala’s range, while Eucalyptus viminalis, Eucalyptus populnea and Eucalyptus tereticornis contracted eastwards and southwards, with a fragmented distribution. The highest probabilities of overlap between koalas and their food trees were identified in fragmented coastal and southern regions of the koala’s current range. Main conclusions The application of a robust species distribution modelling decision support tool identified important changes, under climate change, in the distribution of a specialist species and its key food trees. These distributions did not change in complete synergy and therefore areas of overlap varied, depending on the food tree species modelled. This is of particular importance in a conservation planning context, when considering targeted protection and restoration of species‐specific habitat resources.     

Shifting ranges and conservation challenges for lemurs in the face of climate change

Geospatial modeling is one of the most powerful tools available to conservation biologists for estimating current species ranges of Earth's biodiversity. Now, with the advantage of predictive climate models, these methods can be deployed for understanding future impacts on threatened biota. Here, we employ predictive modeling under a conservative estimate of future climate change to examine impacts on the future abundance and geographic distributions of Malagasy lemurs. Using distribution data from the primary literature, we employed ensemble species distribution models and geospatial analyses to predict future changes in species distributions. Current species distribution models (SDMs) were created within the BIOMOD2 framework that capitalizes on ten widely used modeling techniques. Future and current SDMs were then subtracted from each other, and areas of contraction, expansion, and stability were calculated. Model overprediction is a common issue associated Malagasy taxa. Accordingly, we introduce novel methods for incorporating biological data on dispersal potential to better inform the selection of pseudo‐absence points. This study predicts that 60% of the 57 species examined will experience a considerable range of reductions in the next seventy years entirely due to future climate change. Of these species, range sizes are predicted to decrease by an average of 59.6%. Nine lemur species (16%) are predicted to expand their ranges, and 13 species (22.8%) distribution sizes were predicted to be stable through time. Species ranges will experience severe shifts, typically contractions, and for the majority of lemur species, geographic distributions will be considerably altered. We identify three areas in dire need of protection, concluding that strategically managed forest corridors must be a key component of lemur and other biodiversity conservation strategies. This recommendation is all the more urgent given that the results presented here do not take into account patterns of ongoing habitat destruction relating to human activities.     

Beyond climate control on species range: The importance of soil data to predict distribution of Amazonian plant species

Aim

To evaluate the relative importance of climatic versus soil data when predicting species distributions for Amazonian plants and to gain understanding of potential range shifts under climate change.

Location

Amazon rain forest.

Methods

We produced species distribution models (SDM) at 5‐km spatial resolution for 42 plant species (trees, palms, lianas, monocot herbs and ferns) using species occurrence data from herbarium records and plot‐based inventories. We modelled species distribution with Bayesian logistic regression using either climate data only, soil data only or climate and soil data together to estimate their relative predictive powers. For areas defined as unsuitable to species occurrence, we mapped the difference between the suitability predictions obtained with climate‐only versus soil‐only models to identify regions where climate and soil might restrict species ranges independently or jointly.

Results

For 40 out of the 42 species, the best models included both climate and soil predictors. The models including only soil predictors performed better than the models including only climate predictors, but we still detected a drought‐sensitive response for most of the species. Edaphic conditions were predicted to restrict species occurrence in the centre, the north‐west and in the north‐east of Amazonia, while the climatic conditions were identified as the restricting factor in the eastern Amazonia, at the border of Roraima and Venezuela and in the Andean foothills.

Main conclusions

Our results revealed that soil data are a more important predictor than climate of plant species range in Amazonia. The strong control of species ranges by edaphic features might reduce species’ abilities to track suitable climate conditions under a drought‐increase scenario. Future challenges are to improve the quality of soil data and couple them with process‐based models to better predict species range dynamics under climate change.     

The influence of coarse‐scale environmental features on current and predicted future distributions of narrow‐range endemic crayfish populations

1. A major limitation to effective management of narrow‐range crayfish populations is the paucity of information on the spatial distribution of crayfish species and a general understanding of the interacting environmental variables that drive current and future potential distributional patterns. 2. Maximum Entropy Species Distribution Modeling Software (MaxEnt) was used to predict the current and future potential distributions of four endemic crayfish species in the Ouachita Mountains. Current distributions were modelled using climate, geology, soils, land use, landform and flow variables thought to be important to lotic crayfish. Potential changes in the distribution were forecast by using models trained on current conditions and projecting onto the landscape predicted under climate‐change scenarios. 3. The modelled distribution of the four species closely resembled the perceived distribution of each species but also predicted populations in streams and catchments where they had not previously been collected. Soils, elevation and winter precipitation and temperature most strongly related to current distributions and represented 65–87% of the predictive power of the models. Model accuracy was high for all models, and model predictions of new populations were verified through additional field sampling. 4. Current models created using two spatial resolutions (1 and 4.5 km²) showed that fine‐resolution data more accurately represented current distributions. For three of the four species, the 1‐km² resolution models resulted in more conservative predictions. However, the modelled distributional extent of Orconectes leptogonopodus was similar regardless of data resolution. Field validations indicated 1‐km² resolution models were more accurate than 4.5‐km² resolution models. 5. Future projected (4.5‐km² resolution models) model distributions indicated three of the four endemic species would have truncated ranges with low occurrence probabilities under the low‐emission scenario, whereas two of four species would be severely restricted in range under moderate–high emissions. Discrepancies in the two emission scenarios probably relate to the exclusion of behavioural adaptations from species‐distribution models. 6. These model predictions illustrate possible impacts of climate change on narrow‐range endemic crayfish populations. The predictions do not account for biotic interactions, migration, local habitat conditions or species adaptation. However, we identified the constraining landscape features acting on these populations that provide a framework for addressing habitat needs at a fine scale and developing targeted and systematic monitoring programmes.     

Potential distribution patterns of scorpions in north‐eastern Brazil under scenarios of future climate change

Current predictions about the responses of species to climate change strongly rely on projecting altered environmental conditions on their distributions. In this study, we investigated the effects of future climate change scenarios on the potential distribution of 10 species of scorpions in north‐eastern Brazil in the context of their degree of specialisation to closed (Atlantic and Amazon Forests) and open (Caatinga and Cerrado) habitats. Scorpion species were classified as habitat specialists or generalists according to the IndVal index, and present and future species distribution models were prepared using minimum volume ellipsoids. According to IndVal, four species were classified as closed‐forest specialists (Ananteris mauryi, Tityus brazilae, Tityus pusillus and Tityus neglectus), four as open‐forest specialists (Jaguajir agamemnon, Jaguajir rochae, Physoctonus debilis and Bothriurus rochai), and two as generalists (Tityus stigmurus and Bothriurus asper). All species presented a drastic reduction in potential distribution, ranging from 44% to 72%, when compared with their current distribution. In addition, we found a reduction in scorpion species richness under future climate change scenarios. This finding has implications for scorpion conservation. Further, the results show that climate change may impact the composition of scorpion assemblages in north‐eastern Brazil, revealing important implications for human–scorpion interactions.     

Climate-driven range dynamics of the freshwater limpet, Ancylus fluviatilis (Pulmonata, Basommatophora)

Aim Our aim was to understand the processes that have shaped the present‐day distribution of the freshwater limpet Ancylus fluviatilis sensu stricto in order to predict the consequences of global climate change for the geographical range of this species. Location North‐western Europe. Methods We sampled populations of A. fluviatilis sensu stricto over the entire range of the species (north‐western Europe) and sequenced 16S ribosomal RNA (16S) and cytochrome oxidase subunit I (COI) mitochondrial fragments to perform phylogenetic and phylogeographical analyses. Climatic niche modelling allowed us to infer the climatic preferences of the species. A principal components analysis identified the most important climatic factors explaining the actual range of A. fluviatilis. We also identified which climatic factor was the most limiting at range margins, and predicted the species’ geographical range under a climate change scenario [Community Climate Model 3 (CCM3)]. Results By means of the phylogeographical analysis, we infer that A. fluviatilis sensu stricto occupied northern refuges during the Last Glacial Maximum. We show that the climatic preferences of Baltic populations are significantly different from those of Central European populations. The projection of the occupied area under the CCM3 climate model predicts a moderate poleward shift of the northern range limits, but a dramatic loss of areas currently occupied, for instance in northern Germany and in southern Great Britain. Main conclusions The post‐glacial range dynamics of A. fluviatilis are not governed by niche conservatism. Therefore, we must be cautious about bioclimatic model predictions: the expected impact of climate change could be tempered by the adaptive potential this species has already shown in its evolutionary history. Thus, modelling approaches should rather be seen as conservative forecasts of altered species ranges as long as the adaptive potential of the organisms in question cannot be predicted.     

Influence of bioclimatic variables on tree-line conifer distribution in the Greater Yellowstone Ecosystem: implications for species of conservation concern

Aim Tree‐line conifers are believed to be limited by temperature worldwide, and thus may serve as important indicators of climate change. The purpose of this study was to examine the potential shifts in spatial distribution of three tree‐line conifer species in the Greater Yellowstone Ecosystem under three future climate‐change scenarios and to assess their potential sensitivity to changes in both temperature and precipitation. Location This study was performed using data from 275 sites within the boundaries of Yellowstone and Grand Teton national parks, primarily located in Wyoming, USA. Methods We used data on tree‐line conifer presence from the US Forest Service Forest Inventory and Analysis Program. Climatic and edaphic variables were derived from spatially interpolated maps and approximated for each of the sites. We used the random‐forest prediction method to build a model of predicted current and future distributions of each of the species under various climate‐change scenarios. Results We had good success in predicting the distribution of tree‐line conifer species currently and under future climate scenarios. Temperature and temperature‐related variables appeared to be most influential in the distribution of whitebark pine (Pinus albicaulis), whereas precipitation and soil variables dominated the models for subalpine fir (Abies lasiocarpa) and Engelmann spruce (Picea engelmannii). The model for whitebark pine substantially overpredicted absences (as compared with the other models), which is probably a result of the importance of biological factors in the distribution of this species. Main conclusions These models demonstrate the complex response of conifer distributions to changing climate scenarios. Whitebark pine is considered a ‘keystone’ species in the subalpine forests of western North America; however, it is believed to be nearly extinct throughout a substantial portion of its range owing to the combined effects of an introduced pathogen, outbreaks of the native mountain pine beetle (Dendroctonus ponderosae), and changing fire regimes. Given predicted changes in climate, it is reasonable to predict an overall decrease in pine‐dominated subalpine forests in the Greater Yellowstone Ecosystem. In order to manage these forests effectively with respect to future climate, it may be important to focus attention on monitoring dry mid‐ and high‐elevation forests as harbingers of long‐term change.     

Biotic interactions influence the projected distribution of a specialist mammal under climate change

Aim

To measure the effects of including biotic interactions on climate‐based species distribution models (SDMs) used to predict distribution shifts under climate change. We evaluated the performance of distribution models for an endangered marsupial, the northern bettong (Bettongia tropica), comparing models that used only climate variables with models that also took into account biotic interactions.

Location

North‐east Queensland, Australia.

Methods

We developed separate climate‐based distribution models for the northern bettong, its two main resources and a competitor species. We then constructed models for the northern bettong by including climate suitability estimates for the resources and competitor as additional predictor variables to make climate + resource and climate + resource + competition models. We projected these models onto seven future climate scenarios and compared predictions of northern bettong distribution made by these differently structured models, using a ‘global’ metric, the I similarity statistic, to measure overlap in distribution and a ‘local’ metric to identify where predictions differed significantly.

Results

Inclusion of food resource biotic interactions improved model performance. Over moderate climate changes, up to 3.0 °C of warming, the climate‐only model for the northern bettong gave similar predictions of distribution to the more complex models including interactions, with differences only at the margins of predicted distributions. For climate changes beyond 3.0 °C, model predictions diverged significantly. The interactive model predicted less contraction of distribution than the simpler climate‐only model.

Main conclusions

Distribution models that account for interactions with other species, in particular direct resources, improve model predictions in the present‐day climate. For larger climate changes, shifts in distribution of interacting species cause predictions of interactive models to diverge from climate‐only models. Incorporating interactions with other species in SDMs may be needed for long‐term prediction of changes in distribution of species under climate change, particularly for specialized species strongly dependent on a small number of biotic interactions.