Range expansion through fragmented landscapes under a variable climate

Ecological responses to climate change may depend on complex patterns of variability in weather and local microclimate that overlay global increases in mean temperature. Here, we show that high‐resolution temporal and spatial variability in temperature drives the dynamics of range expansion for an exemplar species, the butterfly Hesperia comma. Using fine‐resolution (5 m) models of vegetation surface microclimate, we estimate the thermal suitability of 906 habitat patches at the species' range margin for 27 years. Population and metapopulation models that incorporate this dynamic microclimate surface improve predictions of observed annual changes to population density and patch occupancy dynamics during the species' range expansion from 1982 to 2009. Our findings reveal how fine‐scale, short‐term environmental variability drives rates and patterns of range expansion through spatially localised, intermittent episodes of expansion and contraction. Incorporating dynamic microclimates can thus improve models of species range shifts at spatial and temporal scales relevant to conservation interventions.     

Quantifying the activity levels and behavioural responses of butterfly species to habitat boundaries

1. The ability of species' to undergo climate‐driven range shifts across fragmented landscapes depends on their dispersal ability as well as the structure of the landscape. For species' range shifts to occur, individuals must first leave suitable habitat to seek new habitat; this is likely to depend on the rate of movement of individuals within habitat and the likelihood that a boundary is crossed, once it is encountered. For three species of butterfly with contrasting histories of recent range expansion, we examined the propensity of individuals to move within a habitat and their responses to habitat boundaries. 2. We quantified the extent to which Plebejus argus (Linnaeus) (a declining habitat specialist), Aricia agestis (Schiffermuller) (an expanding generalist) and Polymmatus icarus (Rottemburg) (a geographically ubiquitous generalist) crossed habitat boundaries into unsuitable habitat and moved within suitable habitat. The observed movement was then related to individual and environmental conditions. 3. Species differed in their activity levels in accordance within their recent distribution patterns (P. icarus > A. agestis > P. argus). Our results for P. argus suggest that movement may be motivated by nectar‐seeking, and that males generally move more than females. All three species tended to avoid crossing habitat boundaries; however the proportion of individuals crossing habitat boundaries did not differ significantly among species. 4. We conclude that levels of activity within a habitat, which will affect the frequency with which individuals encounter habitat boundaries, rather than behavioural responses to the boundaries, may be important drivers of distribution change.     

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.     

Cold range edges of marine fishes track climate change better than warm edges

Species around the world are shifting their ranges in response to climate change. To make robust predictions about climate‐related colonizations and extinctions, it is vital to understand the dynamics of range edges. This study is among the first to examine annual dynamics of cold and warm range edges, as most global change studies average observational data over space or over time. We analyzed annual range edge dynamics of marine fishes—both at the individual species level and pooled into cold‐ and warm‐edge assemblages—in a multi‐decade time‐series of trawl surveys conducted on the Northeast US Shelf during a period of rapid warming. We tested whether cold edges show stronger evidence of climate tracking than warm edges (due to non‐climate processes or time lags at the warm edge; the biogeography hypothesis or extinction debt hypothesis), or whether they tracked temperature change equally (due to the influence of habitat suitability; the ecophysiology hypothesis). In addition to exploring correlations with regional temperature change, we calculated species‐ and assemblage‐specific sea bottom and sea surface temperature isotherms and used them to predict range edge position. Cold edges shifted further and tracked sea surface and bottom temperature isotherms to a greater degree than warm edges. Mixed‐effects models revealed that for a one‐degree latitude shift in isotherm position, cold edges shifted 0.47 degrees of latitude, and warm edges shifted only 0.28 degrees. Our results suggest that cold range edges are tracking climate change better than warm range edges, invalidating the ecophysiology hypothesis. We also found that even among highly mobile marine ectotherms in a global warming hotspot, few species are fully keeping pace with climate.     

Predicted range expansion of the invasive fire ant, Solenopsis invicta, in the eastern United States based on the VEMAP global warming scenario

The red imported fire ant, Solenopsis invicta Buren, is an invasive pest from South America that currently occupies much of the south‐eastern USA. Global warming is likely to allow range expansion of many invasive species, including S. invicta. We used a dynamic, ecophysiological model of fire ant colony growth coupled with models simulating climate change to predict the potential range expansion of S. invicta in the eastern USA over the next century. The climate change scenario predicted by the Vegetation–Ecosystem Modelling and Analysis Project (VEMAP) was used in our analyses. Our predictions indicate that the habitable area for S. invicta may increase by c. 5% over the next 40–50 years (a northward expansion of 33 ± 35 km). As the pace of global warming is expected to quicken in the latter half of the century, however, the habitable area for S. invicta in 2100 is predicted to be > 21% greater than it currently is (a northward expansion of 133 ± 68 km). Because the black imported fire ant, S. richteri Forel, occupies higher latitudes than S. invicta, the overall area of the eastern USA infested with invasive Solenopsis species could be greater than that estimated here.     

Cetacean range and climate in the eastern North Atlantic: future predictions and implications for conservation

There is increasing evidence that the distributions of a large number of species are shifting with global climate change as they track changing surface temperatures that define their thermal niche. Modelling efforts to predict species distributions under future climates have increased with concern about the overall impact of these distribution shifts on species ecology, and especially where barriers to dispersal exist. Here we apply a bio‐climatic envelope modelling technique to investigate the impacts of climate change on the geographic range of ten cetacean species in the eastern North Atlantic and to assess how such modelling can be used to inform conservation and management. The modelling process integrates elements of a species' habitat and thermal niche, and employs “hindcasting” of historical distribution changes in order to verify the accuracy of the modelled relationship between temperature and species range. If this ability is not verified, there is a risk that inappropriate or inaccurate models will be used to make future predictions of species distributions. Of the ten species investigated, we found that while the models for nine could successfully explain current spatial distribution, only four had a good ability to predict distribution changes over time in response to changes in water temperature. Applied to future climate scenarios, the four species‐specific models with good predictive abilities indicated range expansion in one species and range contraction in three others, including the potential loss of up to 80% of suitable white‐beaked dolphin habitat. Model predictions allow identification of affected areas and the likely time‐scales over which impacts will occur. Thus, this work provides important information on both our ability to predict how individual species will respond to future climate change and the applicability of predictive distribution models as a tool to help construct viable conservation and management strategies.     

Spatial scale,topography and thermoregulatory behaviour interact when modelling species’ thermal niches

The spatial scale at which climate and species’ occupancy data are gathered, and the resolution at which ecological models are run, can strongly influence predictions of species performance and distributions. Running model simulations at coarse rather than fine spatial resolutions, for example, can determine if a model accurately predicts the distribution of a species. The impacts of spatial scale on a model's accuracy are particularly pronounced across mountainous terrain. Understanding how these discrepancies arise requires a modelling approach in which the underlying processes that determine a species’ distribution are explicitly described. Here we use a process‐based model to explore how spatial resolution, topography and behaviour alter predictions of a species thermal niche, which in turn constrains its survival and geographic distribution. The model incorporates biophysical equations to predict the operative temperature (T_e), thermal‐dependent performance and survival of a typical insect, with a complex life‐cycle, in its microclimate. We run this model with geographic data from a mountainous terrain in South Africa using climate data at three spatial resolutions. We also explore how behavioural thermoregulation affects predictions of a species performance and survival by allowing the animal to select the optimum thermal location within each coarse‐grid cell. At the regional level, coarse‐resolution models predicted lower T_e at low elevations and higher T_e at high elevations than models run at fine‐resolutions. These differences were more prominent on steep, north‐facing slopes. The discrepancies in T_e in turn affected estimates of the species thermal niche. The modelling framework revealed how spatial resolution and topography influence predictions of species distribution models, including the potential impacts of climate change. These systematic biases must be accounted for when interpreting the outputs of future modelling studies, particularly when species distributions are predicted to shift from uniform to topographically heterogeneous landscapes.     

Microclimate species distribution models estimate lower levels of climate-related habitat loss for salamanders

Species distribution models (SDMs) largely rely on free-air temperatures at coarse spatial resolutions to predict habitat suitability, potentially overlooking important microhabitat. Integrating microclimate data into SDMs may improve predictions of organismal responses to climate change and support targeting of conservation assets at biologically relevant scales, especially for small, dispersal-limited species vulnerable to climate-change-induced range loss. We integrated microclimate data that account for the buffering effects of forest vegetation into SDMs at a very high spatial resolution (3 m²) for three plethodontid salamander species in Great Smoky Mountains National Park (North Carolina and Tennessee). Microclimate SDMs were used to characterize potential changes to future plethodontid habitat, including habitat suitability and habitat spatial patterns. Additionally, we evaluated spatial discrepancies between predictions of habitat suitability developed with microclimate and coarse-resolution, free-air climate data. Microclimate SDMs indicated substantial losses to plethodontid ranges and highly suitable habitat by mid-century, but at much more conservative levels than coarse-resolution models. Coarse-resolution SDMs generally estimated higher mid-century losses to plethodontid habitat compared to microclimate models and consistently undervalued areas containing highly suitable microhabitat. Furthermore, microclimate SDMs revealed potential areas of future gain in highly suitable habitat within current species’ ranges, which may serve as climatic microrefugia. Taken together, this study highlights the need to develop microclimate SDMs that account for vegetation and its biophysical effects on near-surface temperatures. As microclimate datasets become increasingly available across the world, their integration into correlative and mechanistic SDMs will be imperative for accurately estimating organismal responses to climate change and helping environmental managers tasked with spatially prioritizing conservation assets.     

Combining physiological threshold knowledge to species distribution models is key to improving forecasts of the future niche for macroalgae

Species distribution models (SDM) are a useful tool for predicting species range shifts in response to global warming. However, they do not explore the mechanisms underlying biological processes, making it difficult to predict shifts outside the environmental gradient where the model was trained. In this study, we combine correlative SDMs and knowledge on physiological limits to provide more robust predictions. The thermal thresholds obtained in growth and survival experiments were used as proxies of the fundamental niches of two foundational marine macrophytes. The geographic projections of these species’ distributions obtained using these thresholds and existing SDMs were similar in areas where the species are either absent‐rare or frequent and where their potential and realized niches match, reaching consensus predictions. The cold‐temperate foundational seaweed Himanthalia elongata was predicted to become extinct at its southern limit in northern Spain in response to global warming, whereas the occupancy of southern‐lusitanic Bifurcaria bifurcata was expected to increase. Combined approaches such as this one may also highlight geographic areas where models disagree potentially due to biotic factors. Physiological thresholds alone tended to over‐predict species prevalence, as they cannot identify absences in climatic conditions within the species’ range of physiological tolerance or at the optima. Although SDMs tended to have higher sensitivity than threshold models, they may include regressions that do not reflect causal mechanisms, constraining their predictive power. We present a simple example of how combining correlative and mechanistic knowledge provides a rapid way to gain insight into a species’ niche resulting in consistent predictions and highlighting potential sources of uncertainty in forecasted responses to climate change.     

The impact of climate change measured at relevant spatial scales: new hope for tropical lizards

Much attention has been given to recent predictions that widespread extinctions of tropical ectotherms, and tropical forest lizards in particular, will result from anthropogenic climate change. Most of these predictions, however, are based on environmental temperature data measured at a maximum resolution of 1 km², whereas individuals of most species experience thermal variation on a much finer scale. To address this disconnect, we combined thermal performance curves for five populations of Anolis lizard from the Bay Islands of Honduras with high‐resolution temperature distributions generated from physical models. Previous research has suggested that open‐habitat species are likely to invade forest habitat and drive forest species to extinction. We test this hypothesis, and compare the vulnerabilities of closely related, but allopatric, forest species. Our data suggest that the open‐habitat populations we studied will not invade forest habitat and may actually benefit from predicted warming for many decades. Conversely, one of the forest species we studied should experience reduced activity time as a result of warming, while two others are unlikely to experience a significant decline in performance. Our results suggest that global‐scale predictions generated using low‐resolution temperature data may overestimate the vulnerability of many tropical ectotherms to climate change.     

Change and stasis in marine hybrid zones in response to climate warming

Aim We test the prediction that hybrid zones between warm‐ and cold‐adapted species will move towards the territory formerly occupied by the cold‐adapted species in response to a warming climate. We use multiple tests of this prediction to distinguish amongst potential mechanistic hypotheses of responses to climate change. Location We sampled 97 locations on the Atlantic coast of Spain and France and the English Channel that span three hybrid zones formed between two species of marine mussels (Mytilus galloprovincialis and M. edulis). Methods Mussels were sampled in 2005–07 and analysed at a nuclear gene (Glu‐5′) that is diagnostically differentiated between the subject species. Results were compared to those of studies made in the same region over the past two decades. Historical change in sea surface temperature (SST) was analysed using National Oceanic and Atmospheric Administration (NOAA) Optimum Interpolation Daily SST. Species distribution models (random forest and maximum entropy) of the current distribution of mussels were constructed and validated by hindcasting the historical distributions of these species. Validated models were used in combination with forecasts of SST to predict changes in mussel distribution to 2050 and 2100. Results We show that over the past two decades two of the hybrid zones in France have not changed in either position or shape. The third hybrid zone, however, has shifted in the predicted direction, c. 100 km eastward into the warming English Channel. Species distribution modelling strongly implicates changes in winter cold SST as driving this change in the position of one of the hybrid zones. Forecasts of future SST indicate that rapid changes in distribution will occur over the next century. Main conclusions Hybrid zones can be used to conduct repeated tests of ecological responses to climate change and can be valuable in sorting among prospective mechanistic hypotheses that underlie that change. Winter temperatures, but not seasonal high temperature, appear to control the distribution of both species. Species distribution modelling indicates that the collapse of these hybrid zones is imminent, with the rapid expansion of the subtropical species in response to continuing SST warming.     

Linking habitat use to range expansion rates in fragmented landscapes: a metapopulation approach

Temperature increases because of climate change are expected to cause expansions at the high latitude margins of species distributions, but, in practice, fragmented landscapes act as barriers to colonization for most species. Understanding how species distributions will shift in response to climate change therefore requires techniques that incorporate the combined effects of climate and landscape‐scale habitat availability on colonization rates. We use a metapopulation model (Incidence Function Model, IFM) to test effects of fine‐scale habitat use on patterns and rates of range expansion by the butterfly Hesperia comma. At its northern range margin in Britain, this species has increased its breadth of microhabitat use because of climate warming, leading to increased colonization rates. We validated the IFM by reconstructing expansions in five habitat networks between 1982 and 2000, before using it to predict metapopulation dynamics over 100 yr, for three scenarios based on observed changes to habitat use. We define the scenarios as “cold‐world” (only hot, south‐facing 150–250° hillsides are deemed warm enough), “warm‐world” in which 100–300° hillsides can be populated, and “hot‐world”, where the background climate is warm enough to enable use of all aspects (as increasingly observed). In the simulations, increased habitat availability in the hot‐world scenario led to faster range expansion rates, and to long‐term differences in distribution size and pattern. Thus, fine‐scale changes in the distribution of suitable microclimates led to landscape‐scale changes in population size and colonization rate, resulting in coarse‐scale changes to the species distribution. Despite use of a wider range of habitats associated with climate change, H. comma is still expected to occupy a small fraction of available habitat in 100 yr. The research shows that metapopulation models represent a potential framework to identify barriers to range expansion, and to predict the effects of environmental change or conservation interventions on species distributions and persistence.     

Combining population-dynamic and ecophysiological models to predict climate-induced insect range shifts

Hundreds of species are shifting their ranges in response to recent climate warming. To predict how continued climate warming will affect the potential, or “bioclimatic range,” of a skipper butterfly, we present a population‐dynamic model of range shift in which population growth is a function of temperature. We estimate the parameters of this model using previously published data for Atalopedes campestris. Summer and winter temperatures affect population growth rate independently in this species and therefore interact as potential range‐limiting factors. Our model predicts a two‐phase response to climate change; one range‐limiting factor gradually becomes dominant, even if warming occurs steadily along a thermally linear landscape. Whether the range shift accelerates or decelerates and whether the number of generations per year at the range edge increases or decreases depend on whether summer or winter warms faster. To estimate the uncertainty in our predictions of range shift, we use a parametric bootstrap of biological parameter values. Our results show that even modest amounts of data yield predictions with reasonably small confidence intervals, indicating that ecophysiological models can be useful in predicting range changes. Nevertheless, the confidence intervals are sensitive to regional differences in the underlying thermal landscape and the warming scenario.     

Spatial resolution impacts projected plant responses to climate change on topographically complex islands

Aim

Understanding how grain size affects our ability to characterize species responses to ongoing climate change is of crucial importance in the context of an increasing awareness for the substantial difference that exists between coarse spatial resolution macroclimatic data sets and the microclimate actually experienced by organisms. Climate change impacts on biodiversity are expected to peak in mountain areas, wherein the differences between macro and microclimates are precisely the largest. Based on a newly generated fine-scale environmental data for the Canary Islands, we assessed whether data at 100 m resolution is able to provide more accurate predictions than available data at 1 km resolution. We also analysed how future climate suitability predictions of island endemic bryophytes differ depending on the grain size of grids.

Location

Canary Islands.

Time period

Present (1979–2013) and late-century (2071–2100).

Taxa

Bryophytes.

Methods

We compared the accuracy and spatial predictions using ensemble of small models for 14 Macaronesian endemic bryophyte species. We used two climate data sets: CHELSA v1.2 (~1 km) and CanaryClim v1.0 (100 m), a downscaled version of the latter utilizing data from local weather stations. CanaryClim also encompasses future climate data from five individual model intercomparison projects for three warming shared socio-economic pathways.

Results

Species distribution models generated from CHELSA and CanaryClim exhibited a similar accuracy, but CanaryClim predicted buffered warming trends in mid-elevation ridges. CanaryClim consistently returned higher proportions of newly suitable pixels (8%–28%) than CHELSA models (0%–3%). Consequently, the proportion of species predicted to occupy pixels of uncertain suitability was higher with CHELSA (3–8 species) than with CanaryClim (0–2 species).

Main conclusions

The resolution of climate data impacted the predictions rather than the performance of species distribution models. Our results highlight the crucial role that fine-resolution climate data sets can play in predicting the potential distribution of both microrefugia and new suitable range under warming climate.     

Mammalian herbivores confer resilience of Arctic shrub‐dominated ecosystems to changing climate

Climate change is resulting in a rapid expansion of shrubs in the Arctic. This expansion has been shown to be reinforced by positive feedbacks, and it could thus set the ecosystem on a trajectory toward an alternate, more productive regime. Herbivores, on the other hand, are known to counteract the effects of simultaneous climate warming on shrub biomass. However, little is known about the impact of herbivores on resilience of these ecosystems, that is, the capacity of a system to absorb disturbance and still remain in the same regime, retaining the same function, structure, and feedbacks. Here, we investigated how herbivores affect resilience of shrub‐dominated systems to warming by studying the change of shrub biomass after a cessation of long‐term experimental warming in a forest–tundra ecotone. As predicted, warming increased the biomass of shrubs, and in the absence of herbivores, shrub biomass in tundra continued to increase 4 years after cessation of the artificial warming, indicating that positive effects of warming on plant growth may persist even over a subsequent colder period. Herbivores contributed to the resilience of these systems by returning them back to the original low‐biomass regime in both forest and tundra habitats. These results support the prediction that higher shrub biomass triggers positive feedbacks on soil processes and microclimate, which enable maintaining the rapid shrub growth even in colder climates. Furthermore, the results show that in our system, herbivores facilitate the resilience of shrub‐dominated ecosystems to climate warming.     

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.     

Differential effects of past climate warming on mountain and flatland species distributions: a multispecies North American mammal assessment

Aim The magnitude of predicted range shifts during climate change is likely to be different for species living in mountainous environments compared with those living in flatland environments. The southern edges of ranges in mountain species may not shift northwards during warming as populations instead migrate up available elevational gradients; overall latitudinal range appears therefore to expand. In contrast, flatland species should shift range centroids northwards but not expand or contract their latitudinal range extent. These hypotheses were tested utilizing Late Pleistocene and modern occurrence data. Location North America. Methods The location and elevation of modern and Late Pleistocene species occurrences were collected from data bases for 26 species living in mountain or flatland environments. Regressions of elevation change over latitude, and southern and northern range edges were calculated for each species for modern and fossil data sets. A combination of regressions and anova s were used to test whether flatland species shift range edges and latitudinal extents more than mountain species do. Results Flatland species had significantly larger northward shifts at southern range edges than did mountain‐dwelling species from the Late Pleistocene to the present. There was also a significant negative correlation between the amount of change in the latitude of the southern edge of the range and the amount of elevational shifting from the Late Pleistocene to the present. Although significant, only c. 25% of the variance could be explained by this relationship. In addition, there was a weak indication that overall range expansion was less in flatland‐dwelling than in mountain‐dwelling species. Main conclusions The approach used here was to examine past species’ range responses to warming that occurred after the last ice ages as a means to better predict potential future responses to continued warming. The results confirm predictions of differential southern edge and overall range shifts for species occupying mountain and flatland regions in North America. The findings may be broadly applicable in other regions, thus allowing better modelling of future range and distribution related responses.     

What factors shape female phenotypes of a poleward‐moving damselfly at the edge of its range?

Individuals at the expansion front during a climate‐driven range expansion are expected to differ phenotypically from those individuals in core populations. Little information is known about the joint, potentially opposing, effects of stressful conditions at the range edge versus evolutionary changes that take place during range expansion in shaping the phenotypes at the range front. We investigated the effect of range expansion on immune function, body condition and flight‐related morphology (flight muscle ratio, wing loading, and wing aspect ratio) of field‐collected females of the poleward‐moving damselfly Coenagrion scitulum. Individuals at the expansion front had a lower body condition, which indicated more stressful conditions at the range edge. Despite the counteracting effect of the shorter growth season, the higher flight muscle ratios at the expansion front indicated a strong selection for dispersal ability during range expansion. The current study suggests that models need to incorporate the interplay of stressful conditions and evolutionary processes at the expansion front to arrive at robust predictions of future species distributions under global warming. © 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 112 , 556–568.     

Fine‐scale climate change: modelling spatial variation in biologically meaningful rates of warming

The existence of fine‐grain climate heterogeneity has prompted suggestions that species may be able to survive future climate change in pockets of suitable microclimate, termed ‘microrefugia’. However, evidence for microrefugia is hindered by lack of understanding of how rates of warming vary across a landscape. Here, we present a model that is applied to provide fine‐grained, multidecadal estimates of temperature change based on the underlying physical processes that influence microclimate. Weather station and remotely derived environmental data were used to construct physical variables that capture the effects of terrain, sea surface temperatures, altitude and surface albedo on local temperatures, which were then calibrated statistically to derive gridded estimates of temperature. We apply the model to the Lizard Peninsula, United Kingdom, to provide accurate (mean error = 1.21 °C; RMS error = 1.63 °C) hourly estimates of temperature at a resolution of 100 m for the period 1977–2014. We show that rates of warming vary across a landscape primarily due to long‐term trends in weather conditions. Total warming varied from 0.87 to 1.16 °C, with the slowest rates of warming evident on north‐east‐facing slopes. This variation contributed to substantial spatial heterogeneity in trends in bioclimatic variables: for example, the change in the length of the frost‐free season varied from +11 to ?54 days and the increase in annual growing degree‐days from 51 to 267 °C days. Spatial variation in warming was caused primarily by a decrease in daytime cloud cover with a resulting increase in received solar radiation, and secondarily by a decrease in the strength of westerly winds, which has amplified the effects on temperature of solar radiation on west‐facing slopes. We emphasize the importance of multidecadal trends in weather conditions in determining spatial variation in rates of warming, suggesting that locations experiencing least warming may not remain consistent under future climate change.