Individual-scale inference to anticipate climate-change vulnerability of biodiversity

Anticipating how biodiversity will respond to climate change is challenged by the fact that climate variables affect individuals in competition with others, but interest lies at the scale of species and landscapes. By omitting the individual scale, models cannot accommodate the processes that determine future biodiversity. We demonstrate how individual-scale inference can be applied to the problem of anticipating vulnerability of species to climate. The approach places climate vulnerability in the context of competition for light and soil moisture. Sensitivities to climate and competition interactions aggregated from the individual tree scale provide estimates of which species are vulnerable to which variables in different habitats. Vulnerability is explored in terms of specific demographic responses (growth, fecundity and survival) and in terms of the synthetic response (the combination of demographic rates), termed climate tracking. These indices quantify risks for individuals in the context of their competitive environments. However, by aggregating in specific ways (over individuals, years, and other input variables), we provide ways to summarize and rank species in terms of their risks from climate change.     

Evolutionary tracking is determined by differential selection on demographic rates and density dependence

Recent ecological forecasts predict that ~25% of species worldwide will go extinct by 2050. However, these estimates are primarily based on environmental changes alone and fail to incorporate important biological mechanisms such as genetic adaptation via evolution. Thus, environmental change can affect population dynamics in ways that classical frameworks can neither describe nor predict. Furthermore, often due to a lack of data, forecasting models commonly describe changes in population demography by summarizing changes in fecundity and survival concurrently with the intrinsic growth rate (r). This has been shown to be an oversimplification as the environment may impose selective pressure on specific demographic rates (birth and death) rather than directly on r (the difference between the birth and death rates). This differential pressure may alter population response to density, in each demographic rate, further diluting the information combined to produce r. Thus, when we consider the potential for persistence via adaptive evolution, populations with the same r can have different abilities to persist amidst environmental change. Therefore, we cannot adequately forecast population response to climate change without accounting for demography and selection on density dependence. Using a continuous‐time Markov chain model to describe the stochastic dynamics of the logistic model of population growth and allow for trait evolution via mutations arising during birth events, we find persistence via evolutionary tracking more likely when environmental change alters birth rather than the death rate. Furthermore, species that evolve responses to changes in the strength of density dependence due to environmental change are less vulnerable to extinction than species that undergo selection independent of population density. By incorporating these key demographic considerations into our predictive models, we can better understand how species will respond to climate change.     

Climate change and spotted owls: potentially contrasting responses in the Southwestern United States

Developing strategies that reduce the impacts of climate change on biodiversity will require projections of the future status of species under alternative climate change scenarios. Demographic models based on empirical data that link temporal variation in climate with vital rates can improve the accuracy of such predictions and help guide conservation efforts. Here, we characterized how population dynamics and extinction risk might be affected by climate change for three spotted owl (Strix occidentalis) populations in the Southwestern United States over the next century. Specifically, we used stochastic, stage‐based matrix models parameterized with vital rates linked to annual variation in temperature and precipitation to project owl populations forward in time under three IPCC emissions scenarios relative to contemporary climate. Owl populations in Arizona and New Mexico were predicted to decline rapidly over the next century and had a much greater probability of extinction under all three emissions scenarios than under current climate conditions. In contrast, owl population dynamics in Southern California were relatively insensitive to predicted changes in climate, and extinction risk was low for this population under all scenarios. The difference in predicted climate change impacts between these areas was due to negative associations between warm, dry conditions and owl vital rates in Arizona and New Mexico, whereas cold, wet springs reduced reproduction in Southern California. Predicted changes in population growth rates were mediated more by weather‐induced changes in fecundity than survival, and were generally more sensitive to increases in temperature than declines in precipitation. Our results indicate that spotted owls in arid environments may be highly vulnerable to climate change, even in core parts of the owl's range. More broadly, contrasting responses to climate change among populations highlight the need to tailor conservation strategies regionally, and modeling efforts such as ours can help prioritize the allocation of resources in this regard.     

Using fuzzy logic to determine the vulnerability of marine species to climate change

Marine species are being impacted by climate change and ocean acidification, although their level of vulnerability varies due to differences in species' sensitivity, adaptive capacity and exposure to climate hazards. Due to limited data on the biological and ecological attributes of many marine species, as well as inherent uncertainties in the assessment process, climate change vulnerability assessments in the marine environment frequently focus on a limited number of taxa or geographic ranges. As climate change is already impacting marine biodiversity and fisheries, there is an urgent need to expand vulnerability assessment to cover a large number of species and areas. Here, we develop a modelling approach to synthesize data on species‐specific estimates of exposure, and ecological and biological traits to undertake an assessment of vulnerability (sensitivity and adaptive capacity) and risk of impacts (combining exposure to hazards and vulnerability) of climate change (including ocean acidification) for global marine fishes and invertebrates. We use a fuzzy logic approach to accommodate the variability in data availability and uncertainties associated with inferring vulnerability levels from climate projections and species' traits. Applying the approach to estimate the relative vulnerability and risk of impacts of climate change in 1074 exploited marine species globally, we estimated their index of vulnerability and risk of impacts to be on average 52 ± 19 SD and 66 ± 11 SD, scaling from 1 to 100, with 100 being the most vulnerable and highest risk, respectively, under the ‘business‐as‐usual' greenhouse gas emission scenario (Representative Concentration Pathway 8.5). We identified 157 species to be highly vulnerable while 294 species are identified as being at high risk of impacts. Species that are most vulnerable tend to be large‐bodied endemic species. This study suggests that the fuzzy logic framework can help estimate climate vulnerabilities and risks of exploited marine species using publicly and readily available information.     

The impact of climate change on the distribution of two threatened Dipterocarp trees

Two ecologically and economically important, and threatened Dipterocarp trees Sal (Shorea robusta) and Garjan (Dipterocarpus turbinatus) form mono‐specific canopies in dry deciduous, moist deciduous, evergreen, and semievergreen forests across South Asia and continental parts of Southeast Asia. They provide valuable timber and play an important role in the economy of many Asian countries. However, both Dipterocarp trees are threatened by continuing forest clearing, habitat alteration, and global climate change. While climatic regimes in the Asian tropics are changing, research on climate change‐driven shifts in the distribution of tropical Asian trees is limited. We applied a bioclimatic modeling approach to these two Dipterocarp trees Sal and Garjan. We used presence‐only records for the tree species, five bioclimatic variables, and selected two climatic scenarios (RCP4.5: an optimistic scenario and RCP8.5: a pessimistic scenario) and three global climate models (GCMs) to encompass the full range of variation in the models. We modeled climate space suitability for both species, projected to 2070, using a climate envelope modeling tool “MaxEnt” (the maximum entropy algorithm). Annual precipitation was the key bioclimatic variable in all GCMs for explaining the current and future distributions of Sal and Garjan (Sal: 49.97 ± 1.33; Garjan: 37.63 ± 1.19). Our models predict that suitable climate space for Sal will decline by 24% and 34% (the mean of the three GCMs) by 2070 under RCP4.5 and RCP8.5, respectively. In contrast, the consequences of imminent climate change appear less severe for Garjan, with a decline of 17% and 27% under RCP4.5 and RCP8.5, respectively. The findings of this study can be used to set conservation guidelines for Sal and Garjan by identifying vulnerable habitats in the region. In addition, the natural habitats of Sal and Garjan can be categorized as low to high risk under changing climates where artificial regeneration should be undertaken for forest restoration.     

Regional and global climate risks for reef corals: Incorporating species-specific vulnerability and exposure to climate hazards

Climate change is driving rapid and widespread erosion of the environmental conditions that formerly supported species persistence. Existing projections of climate change typically focus on forecasts of acute environmental anomalies and global extinction risks. The current projections also frequently consider all species within a broad taxonomic group together without differentiating species-specific patterns. Consequently, we still know little about the explicit dimensions of climate risk (i.e., species-specific vulnerability, exposure and hazard) that are vital for predicting future biodiversity responses (e.g., adaptation, migration) and developing management and conservation strategies. Here, we use reef corals as model organisms (n = 741 species) to project the extent of regional and global climate risks of marine organisms into the future. We characterise species-specific vulnerability based on the global geographic range and historical environmental conditions (1900–1994) of each coral species within their ranges, and quantify the projected exposure to climate hazard beyond the historical conditions as climate risk. We show that many coral species will experience a complete loss of pre-modern climate analogs at the regional scale and across their entire distributional ranges, and such exposure to hazardous conditions are predicted to pose substantial regional and global climate risks to reef corals. Although high-latitude regions may provide climate refugia for some tropical corals until the mid-21st century, they will not become a universal haven for all corals. Notably, high-latitude specialists and species with small geographic ranges remain particularly vulnerable as they tend to possess limited capacities to avoid climate risks (e.g., via adaptive and migratory responses). Predicted climate risks are amplified substantially under the SSP5-8.5 compared with the SSP1-2.6 scenario, highlighting the need for stringent emission controls. Our projections of both regional and global climate risks offer unique opportunities to facilitate climate action at spatial scales relevant to conservation and management.     

Vulnerability of European freshwater catchments to climate change

Climate change is expected to exacerbate the current threats to freshwater ecosystems, yet multifaceted studies on the potential impacts of climate change on freshwater biodiversity at scales that inform management planning are lacking. The aim of this study was to fill this void through the development of a novel framework for assessing climate change vulnerability tailored to freshwater ecosystems. The three dimensions of climate change vulnerability are as follows: (i) exposure to climate change, (ii) sensitivity to altered environmental conditions and (iii) resilience potential. Our vulnerability framework includes 1685 freshwater species of plants, fishes, molluscs, odonates, amphibians, crayfish and turtles alongside key features within and between catchments, such as topography and connectivity. Several methodologies were used to combine these dimensions across a variety of future climate change models and scenarios. The resulting indices were overlaid to assess the vulnerability of European freshwater ecosystems at the catchment scale (18 783 catchments). The Balkan Lakes Ohrid and Prespa and Mediterranean islands emerge as most vulnerable to climate change. For the 2030s, we showed a consensus among the applied methods whereby up to 573 lake and river catchments are highly vulnerable to climate change. The anthropogenic disruption of hydrological habitat connectivity by dams is the major factor reducing climate change resilience. A gap analysis demonstrated that the current European protected area network covers <25% of the most vulnerable catchments. Practical steps need to be taken to ensure the persistence of freshwater biodiversity under climate change. Priority should be placed on enhancing stakeholder cooperation at the major basin scale towards preventing further degradation of freshwater ecosystems and maintaining connectivity among catchments. The catchments identified as most vulnerable to climate change provide preliminary targets for development of climate change conservation management and mitigation strategies.     

Dispersal limitations increase vulnerability under climate change for reptiles and amphibians in the southwestern United States

Species conservation plans frequently rely on information that spans political and administrative boundaries, especially when predictions are needed of future habitat under climate change; however, most species conservation plans and their requisite predictions of future habitat are often limited in geographical scope. Moreover, dispersal constraints for species of concern are not often incorporated into distribution models, which can result in overly optimistic predictions of future habitat. We used a standard modeling approach across a suite of 23 taxa of amphibians and reptiles in the North American deserts (560,024 km² across 13 ecoregions) to assess impacts of climate change on habitat and combined landscape population dispersal simulations with species distribution modeling to reduce the risk of predicting future habitat in areas that are not available to species given their dispersal abilities. We used 3 general circulation models and 2 representative concentration pathways (RCPs) to represent multiple scenarios of future habitat potential and assess which study species may be most vulnerable to changes forecasted under each climate scenario. Amphibians were the most vulnerable taxa, but the most vulnerable species tended to be those with the lowest dispersal ability rather than those with the most specialized niches. Under the most optimistic climate scenario considered (RCP 2.6; a stringent scenario requiring declining emissions from 2020 to near zero emissions by 2100), 76% of the study area may experience a loss of >20% of the species examined, while up to 87% of the species currently present may be lost in some areas under the most pessimistic climate scenario (RCP 8.5; a scenario wherein greenhouse gases continue to increase through 2100 based on trajectories from the mid-century). Most areas with high losses were concentrated in the Arizona and New Mexico Plateau ecoregion, the Edwards Plateau in Texas, and the Southwestern Tablelands in New Mexico and Texas, USA. Under the most pessimistic climate scenario, all species are predicted to lose some existing habitat, with an average of 34% loss of extant habitat across all species. Even under the most optimistic scenario, we detected an average loss of 24% of extant habitat across all species, suggesting that changing climates may influence the ranges of reptiles and amphibians in the Southwest.     

Shifts in the climate space of temperate cyprinid fishes due to climate change are coupled with altered body sizes and growth rates

Predictions of species responses to climate change often focus on distribution shifts, although responses can also include shifts in body sizes and population demographics. Here, shifts in the distributional ranges (‘climate space’), body sizes (as maximum theoretical body sizes, L∞) and growth rates (as rate at which L∞ is reached, K) were predicted for five fishes of the Cyprinidae family in a temperate region over eight climate change projections. Great Britain was the model area, and the model species were Rutilus rutilus, Leuciscus leuciscus, Squalius cephalus, Gobio gobio and Abramis brama. Ensemble models predicted that the species' climate spaces would shift in all modelled projections, with the most drastic changes occurring under high emissions; all range centroids shifted in a north‐westerly direction. Predicted climate space expanded for R. rutilus and A. brama, contracted for S. cephalus, and for L. leuciscus and G. gobio, expanded under low‐emission scenarios but contracted under high emissions, suggesting the presence of some climate‐distribution thresholds. For R. rutilus, A. brama, S. cephalus and G. gobio, shifts in their climate space were coupled with predicted shifts to significantly smaller maximum body sizes and/or faster growth rates, aligning strongly to aspects of temperature‐body size theory. These predicted shifts in L∞ and K had considerable consequences for size‐at‐age per species, suggesting substantial alterations in population age structures and abundances. Thus, when predicting climate change outcomes for species, outputs that couple shifts in climate space with altered body sizes and growth rates provide considerable insights into the population and community consequences, especially for species that cannot easily track their thermal niches.     

Spatio‐temporal variation of biotic factors underpins contemporary range dynamics of congeners

Species’ ranges are complex often exhibiting multidirectional shifts over space and time. Despite the strong fingerprint of recent historical climate change on species’ distributions, biotic factors such as loss of vegetative habitat and the presence of potential competitors constitute important yet often overlooked drivers of range dynamics. Furthermore, short‐term changes in environmental conditions can influence the underlying processes of local extinction and local colonization that drive range shifts, yet are rarely considered at broad scales. We used dynamic state‐space occupancy models to test multiple hypotheses of the relative importance of major drivers of range shifts of Golden‐winged Warblers (Vermivora chrysoptera) and Blue‐winged Warblers (V. cyanoptera) between 1983 and 2012 across North America: warming temperatures; habitat changes; and occurrence of congeneric species, used here as proxy for biotic interactions. Dynamic occupancies for both species were most influenced by spatial relative to temporal variation in temperature and habitat. However, temporal variation in temperature anomalies and biotic interactions remained important. The two biotic factors considered, habitat change and biotic interactions, had the largest relative effect on estimated extinction rates followed by abiotic temperature anomalies. For the Golden‐winged Warbler, the predicted presence of the Blue‐winged Warbler, a hypothesized competitor, most influenced extinction probabilities, contributing to evidence supporting its role in site‐level species replacement. Given the overall importance of biotic factors on range‐wide dynamic occupancies, their consideration alongside abiotic factors should not be overlooked. Our results suggest that warming compounds the negative effect of habitat loss emphasizing species’ need for habitat to adapt to a changing climate. Notably, even closely related species exhibited individual responses to abiotic and biotic factors considered.     

Effects of climate‐driven primary production change on marine food webs: implications for fisheries and conservation

Climate change is altering the rate and distribution of primary production in the world's oceans. Primary production is critical to maintaining biodiversity and supporting fishery catches, but predicting the response of populations to primary production change is complicated by predation and competition interactions. We simulated the effects of change in primary production on diverse marine ecosystems across a wide latitudinal range in Australia using the marine food web model Ecosim. We link models of primary production of lower trophic levels (phytoplankton and benthic producers) under climate change with Ecosim to predict changes in fishery catch, fishery value, biomass of animals of conservation interest, and indicators of community composition. Under a plausible climate change scenario, primary production will increase around Australia and generally this benefits fisheries catch and value and leads to increased biomass of threatened marine animals such as turtles and sharks. However, community composition is not strongly affected. Sensitivity analyses indicate overall positive linear responses of functional groups to primary production change. Responses are robust to the ecosystem type and the complexity of the model used. However, model formulations with more complex predation and competition interactions can reverse the expected responses for some species, resulting in catch declines for some fished species and localized declines of turtle and marine mammal populations under primary productivity increases. We conclude that climate‐driven primary production change needs to be considered by marine ecosystem managers and more specifically, that production increases can simultaneously benefit fisheries and conservation. Greater focus on incorporating predation and competition interactions into models will significantly improve the ability to identify species and industries most at risk from climate change.     

Increased temperature variation poses a greater risk to species than climate warming

Increases in the frequency, severity and duration of temperature extremes are anticipated in the near future. Although recent work suggests that changes in temperature variation will have disproportionately greater effects on species than changes to the mean, much of climate change research in ecology has focused on the impacts of mean temperature change. Here, we couple fine-grained climate projections (2050–2059) to thermal performance data from 38 ectothermic invertebrate species and contrast projections with those of a simple model. We show that projections based on mean temperature change alone differ substantially from those incorporating changes to the variation, and to the mean and variation in concert. Although most species show increases in performance at greater mean temperatures, the effect of mean and variance change together yields a range of responses, with temperate species at greatest risk of performance declines. Our work highlights the importance of using fine-grained temporal data to incorporate the full extent of temperature variation when assessing and projecting performance.     

Changes in species interactions across a 2.5 km elevation gradient: effects on plant migration in response to climate change

Predicted climate change in the Andes will require plant species to migrate upslope to avoid extinction. Central to predictions of species responses to climate change is an understanding of species distributions along environmental gradients. Environmental gradients are frequently modelled as abiotic, but biotic interactions can play important roles in setting species distributions, abundances, and life history traits. Biotic interactions also have the potential to influence species responses to climate change, yet they remain mostly unquantified. An important interaction long studied in tropical forests is postdispersal seed predation which has been shown to affect the population dynamics, community structure, and diversity of plant species in time and space. This paper presents a comparative seed predation study of 24 species of tropical trees across a 2.5 km elevation gradient in the Peruvian Andes and quantifies seed predation variation across the elevational gradient. We then use demographic modelling to assess effects of the observed variation in seed predation on population growth rates in response to observed increasing temperatures in the area. We found marked variation among species in total seed predation depending on the major seed predator of the species and consistent changes in seed predation across the gradient. There was a significant increase in seed survival with increasing elevation, a trend that appears to be driven by regulation of seed predators via top–down forces in the lowlands giving way to bottom–up (productivity) regulation at mid‐ to high elevations, resulting in a ninefold increase in effective fecundity for trees at high elevations. This potential increase in seed crop size strongly affects modelled plant population growth and seed dispersal distances, increasing population migration potential in the face of climate change. These results also indicate that species interactions can have effects on par with climate in species responses to global change.     

Upward elevation and northwest range shifts for alpine Meconopsis species in the Himalaya–Hengduan Mountains region

Climate change may impact the distribution of species by shifting their ranges to higher elevations or higher latitudes. The impacts on alpine plant species may be particularly profound due to a potential lack of availability of future suitable habitat. To identify how alpine species have responded to climate change during the past century as well as to predict how they may react to possible global climate change scenarios in the future, we investigate the climatic responses of seven species of Meconopsis, a representative genus endemic in the alpine meadow and subnival region of the Himalaya–Hengduan Mountains. We analyzed past elevational shifts, as well as projected shifts in longitude, latitude, elevation, and range size using historical specimen records and species distribution modeling under optimistic (RCP 4.5) and pessimistic (RCP 8.5) scenarios across three general circulation models for 2070. Our results indicate that across all seven species, there has been an upward shift in mean elevation of 302.3 m between the pre‐1970s (1922–1969) and the post‐1970s (1970–2016). The model predictions suggest that the future suitable climate space will continue to shift upwards in elevation (as well as northwards and westwards) by 2070. While for most of the analyzed species, the area of suitable climate space is predicted to expand under the optimistic emission scenario, the area contracts, or, at best, shows little change under the pessimistic scenario. Species such as M. punicea, which already occupy high latitudes, are consistently predicted to experience a contraction of suitable climate space across all the models by 2070 and may consequently deserve particular attention by conservation strategies. Collectively, our results suggest that the alpine high‐latitude species analyzed here have already been significantly impacted by climate change and that these trends may continue over the coming decades.     

Tests of species‐specific models reveal the importance of drought in postglacial range shifts of a Mediterranean‐climate tree: insights from integrative distributional,demographic and coalescent modelling and ABC model selection

Past climate change has caused shifts in species distributions and undoubtedly impacted patterns of genetic variation, but the biological processes mediating responses to climate change, and their genetic signatures, are often poorly understood. We test six species‐specific biologically informed hypotheses about such processes in canyon live oak (Quercus chrysolepis) from the California Floristic Province. These hypotheses encompass the potential roles of climatic niche, niche multidimensionality, physiological trade‐offs in functional traits, and local‐scale factors (microsites and local adaptation within ecoregions) in structuring genetic variation. Specifically, we use ecological niche models (ENMs) to construct temporally dynamic landscapes where the processes invoked by each hypothesis are reflected by differences in local habitat suitabilities. These landscapes are used to simulate expected patterns of genetic variation under each model and evaluate the fit of empirical data from 13 microsatellite loci genotyped in 226 individuals from across the species range. Using approximate Bayesian computation (ABC), we obtain very strong support for two statistically indistinguishable models: a trade‐off model in which growth rate and drought tolerance drive habitat suitability and genetic structure, and a model based on the climatic niche estimated from a generic ENM, in which the variables found to make the most important contribution to the ENM have strong conceptual links to drought stress. The two most probable models for explaining the patterns of genetic variation thus share a common component, highlighting the potential importance of seasonal drought in driving historical range shifts in a temperate tree from a Mediterranean climate where summer drought is common.     

Impact of landscape predictors on climate change modelling of species distributions: a case study with Eucalyptus fastigata in southern New South Wales,Australia

Aim We consider three questions. (1) How different are the predicted distribution maps when climate‐only and climate‐plus‐terrain models are developed from high‐resolution data? (2) What are the implications of differences between the models when predicting future distributions under climate change scenarios, particularly for climate‐only models at coarse resolution? (3) Does the use of high‐resolution data and climate‐plus‐terrain models predict an increase in the number of local refugia? Location South‐eastern New South Wales, Australia. Methods We developed two species distribution models for Eucalyptus fastigata under current climate conditions using generalized additive modelling. One used only climate variables as predictors (mean annual temperature, mean annual rainfall, mean summer rainfall); the other used both climate and landscape (June daily radiation, topographic position, lithology, nutrients) variables as predictors. Predictions of the distribution under current climate and climate change were then made for both models at a pixel resolution of 100 m. Results The model using climate and landscape variables as predictors explained a significantly greater proportion of the deviance than the climate‐only model. Inclusion of landscape variables resulted in the prediction of much larger areas of existing optimal habitat. An overlay of predicted future climate on the current climate space indicated that extrapolation of the statistical models was not occurring and models were therefore more robust. Under climate change, landscape‐defined refugia persisted in areas where the climate‐only model predicted major declines. In areas where expansion was predicted, the increase in optimal habitat was always greater with landscape predictors. Recognition of extensive optimal habitat conditions and potential refugia was dependent on the use of high‐resolution landscape data. Main conclusions Using only climate variables as predictors for assessing species responses to climate change ignores the accepted conceptual model of plant species distribution. Explicit statements justifying the selection of predictors based on ecological principles are needed. Models using only climate variables overestimate range reduction under climate change and fail to predict potential refugia. Fine‐scale‐resolution data are required to capture important climate/landscape interactions. Extrapolation of statistical models to regions in climate space outside the region where they were fitted is risky.     

Evidence that climate sets the lower elevation range limit in a high‐elevation endemic salamander

A frequent assumption in ecology is that biotic interactions are more important than abiotic factors in determining lower elevational range limits (i.e., the “warm edge” of a species distribution). However, for species with narrow environmental tolerances, theory suggests the presence of a strong environmental gradient can lead to persistence, even in the presence of competition. The relative importance of biotic and abiotic factors is rarely considered together, although understanding when one exerts a dominant influence on controlling range limits may be crucial to predicting extinction risk under future climate conditions. We sampled multiple transects spanning the elevational range limit of Plethodon shenandoah and site and climate covariates were recorded. A two‐species conditional occupancy model, accommodating heterogeneity in detection probability, was used to relate variation in occupancy with environmental and habitat conditions. Regional climate data were combined with datalogger observations to estimate the cloud base heights and to project future climate change impacts on cloud elevations across the survey area. By simultaneously accounting for species’ interactions and habitat variables, we find that elevation, not competition, is strongly correlated with the lower elevation range boundary, which had been presumed to be restricted mainly as a result of competitive interactions with a congener. Because the lower elevational range limit is sensitive to climate variables, projected climate change across its high‐elevation habitats will directly affect the species’ distribution. Testing assumptions of factors that set species range limits should use models which accommodate detection biases.     

Phenotypic distribution models corroborate species distribution models: A shift in the role and prevalence of a dominant prairie grass in response to climate change

Phenotypic distribution within species can vary widely across environmental gradients but forecasts of species’ responses to environmental change often assume species respond homogenously across their ranges. We compared predictions from species and phenotype distribution models under future climate scenarios for Andropogon gerardii, a widely distributed, dominant grass found throughout the central United States. Phenotype data on aboveground biomass, height, leaf width, and chlorophyll content were obtained from 33 populations spanning a ~1000 km gradient that encompassed the majority of the species’ environmental range. Species and phenotype distribution models were trained using current climate conditions and projected to future climate scenarios. We used permutation procedures to infer the most important variable for each model. The species‐level response to climate was most sensitive to maximum temperature of the hottest month, but phenotypic variables were most sensitive to mean annual precipitation. The phenotype distribution models predict that A. gerardii could be largely functionally eliminated from where this species currently dominates, with biomass and height declining by up to ~60% and leaf width by ~20%. By the 2070s, the core area of highest suitability for A. gerardii is projected to shift up to ~700 km northeastward. Further, short‐statured phenotypes found in the present‐day short grass prairies on the western periphery of the species’ range will become favored in the current core ~800 km eastward of their current location. Combined, species and phenotype models predict this currently dominant prairie grass will decline in prevalence and stature. Thus, sourcing plant material for grassland restoration and forage should consider changes in the phenotype that will be favored under future climate conditions. Phenotype distribution models account for the role of intraspecific variation in determining responses to anticipated climate change and thereby complement predictions from species distributions models in guiding climate adaptation strategies.     

Translating niche features: Modelling differential exposure of Argentine reptiles to global climate change

Global climate change affects the distributions of ectotherms and may be the cause of several conservation problems, such as great displacement of climatic suitable spaces for species and, consequently, important reductions of the extent of liveable places, threatening the existence of many of them. Species exposure (and hence vulnerability) to global climate change is linked to features of their climatic niches (such as the relative position of the inhabited localities of each species in the climatic space), and therefore to characteristics of their geographic ranges (such as the extent of the distributions or altitudinal range inhabited by the species). In order to analyze the pattern of response of Argentine reptiles to global climate change, we ran phylogenetic generalized least squares models using species exposure to global climate change as a response variable, and (i) niche properties (breadth and position of the species in the climate space) and (ii) general features of the distribution of species (maximum latitude, altitudinal range, maximum elevation, distributional range and proximity to the most important dispersal barrier) as predictors. Our results suggest that the best way to explain climate change exposure is by combining breadth and position of climatic niche of the species or combining geographic features that are indicators of both niche characteristics. Our best model shows that in our study area, species with the narrowest distributional ranges that also inhabit the highest elevations are the most exposed to the effects of global climate change. In this sense, reptile species from Yungas, Puna and Andes ecoregions could be especially vulnerable to the effects of climate change. We believe that these types of models may represent an interesting tool for determining species and places particularly threatened by the effects of global climate change, which should be strongly considered in conservation planning.     

Can we predict ectotherm responses to climate change using thermal performance curves and body temperatures?

Thermal performance curves (TPCs), which quantify how an ectotherm's body temperature (T_b) affects its performance or fitness, are often used in an attempt to predict organismal responses to climate change. Here, we examine the key – but often biologically unreasonable – assumptions underlying this approach; for example, that physiology and thermal regimes are invariant over ontogeny, space and time, and also that TPCs are independent of previously experienced T_b. We show how a critical consideration of these assumptions can lead to biologically useful hypotheses and experimental designs. For example, rather than assuming that TPCs are fixed during ontogeny, one can measure TPCs for each major life stage and incorporate these into stage‐specific ecological models to reveal the life stage most likely to be vulnerable to climate change. Our overall goal is to explicitly examine the assumptions underlying the integration of TPCs with T_b, to develop a framework within which empiricists can place their work within these limitations, and to facilitate the application of thermal physiology to understanding the biological implications of climate change.