Modeling plant species distributions under future climates: how fine scale do climate projections need to be?

Recent studies suggest that species distribution models (SDMs) based on fine‐scale climate data may provide markedly different estimates of climate‐change impacts than coarse‐scale models. However, these studies disagree in their conclusions of how scale influences projected species distributions. In rugged terrain, coarse‐scale climate grids may not capture topographically controlled climate variation at the scale that constitutes microhabitat or refugia for some species. Although finer scale data are therefore considered to better reflect climatic conditions experienced by species, there have been few formal analyses of how modeled distributions differ with scale. We modeled distributions for 52 plant species endemic to the California Floristic Province of different life forms and range sizes under recent and future climate across a 2000‐fold range of spatial scales (0.008–16 km²). We produced unique current and future climate datasets by separately downscaling 4 km climate models to three finer resolutions based on 800, 270, and 90 m digital elevation models and deriving bioclimatic predictors from them. As climate‐data resolution became coarser, SDMs predicted larger habitat area with diminishing spatial congruence between fine‐ and coarse‐scale predictions. These trends were most pronounced at the coarsest resolutions and depended on climate scenario and species' range size. On average, SDMs projected onto 4 km climate data predicted 42% more stable habitat (the amount of spatial overlap between predicted current and future climatically suitable habitat) compared with 800 m data. We found only modest agreement between areas predicted to be stable by 90 m models generalized to 4 km grids compared with areas classified as stable based on 4 km models, suggesting that some climate refugia captured at finer scales may be missed using coarser scale data. These differences in projected locations of habitat change may have more serious implications than net habitat area when predictive maps form the basis of conservation decision making.     

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.     

The contributions of topoclimate and land cover to species distributions and abundance: fine‐resolution tests for a mountain butterfly fauna

Aim Models relating species distributions to climate or habitat are widely used to predict the effects of global change on biodiversity. Most such approaches assume that climate governs coarse‐scale species ranges, whereas habitat limits fine‐scale distributions. We tested the influence of topoclimate and land cover on butterfly distributions and abundance in a mountain range, where climate may vary as markedly at a fine scale as land cover. Location Sierra de Guadarrama (Spain, southern Europe) Methods We sampled the butterfly fauna of 180 locations (89 in 2004, 91 in 2005) in a 10,800 km² region, and derived generalized linear models (GLMs) for species occurrence and abundance based on topoclimatic (elevation and insolation) or habitat (land cover, geology and hydrology) variables sampled at 100‐m resolution using GIS. Models for each year were tested against independent data from the alternate year, using the area under the receiver operating characteristic curve (AUC) (distribution) or Spearman's rank correlation coefficient (r_s) (abundance). Results In independent model tests, 74% of occurrence models achieved AUCs of > 0.7, and 85% of abundance models were significantly related to observed abundance. Topoclimatic models outperformed models based purely on land cover in 72% of occurrence models and 66% of abundance models. Including both types of variables often explained most variation in model calibration, but did not significantly improve model cross‐validation relative to topoclimatic models. Hierarchical partitioning analysis confirmed the overriding effect of topoclimatic factors on species distributions, with the exception of several species for which the importance of land cover was confirmed. Main conclusions Topoclimatic factors may dominate fine‐resolution species distributions in mountain ranges where climate conditions vary markedly over short distances and large areas of natural habitat remain. Climate change is likely to be a key driver of species distributions in such systems and could have important effects on biodiversity. However, continued habitat protection may be vital to facilitate range shifts in response to climate change.     

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.     

Spatiotemporally explicit demographic modelling supports a joint effect of historical barriers to dispersal and contemporary landscape composition on structuring genomic variation in a red‐listed grasshopper

Inferring the processes underlying spatial patterns of genomic variation is fundamental to understand how organisms interact with landscape heterogeneity and to identify the factors determining species distributional shifts. Here, we use genomic data (restriction site‐associated DNA sequencing) to test biologically informed models representing historical and contemporary demographic scenarios of population connectivity for the Iberian cross‐backed grasshopper Dociostaurus hispanicus, a species with a narrow distribution that currently forms highly fragmented populations. All models incorporated biological aspects of the focal taxon that could hypothetically impact its geographical patterns of genomic variation, including (a) spatial configuration of impassable barriers to dispersal defined by topographic landscapes not occupied by the species; (b) distributional shifts resulting from the interaction between the species bioclimatic envelope and Pleistocene glacial cycles; and (c) contemporary distribution of suitable habitats after extensive land clearing for agriculture. Spatiotemporally explicit simulations under different scenarios considering these aspects and statistical evaluation of competing models within an Approximate Bayesian Computation framework supported spatial configuration of topographic barriers to dispersal and human‐driven habitat fragmentation as the main factors explaining the geographical distribution of genomic variation in the species, with no apparent impact of hypothetical distributional shifts linked to Pleistocene climatic oscillations. Collectively, this study supports that both historical (i.e., topographic barriers) and contemporary (i.e., anthropogenic habitat fragmentation) aspects of landscape composition have shaped major axes of genomic variation in the studied species and emphasizes the potential of model‐based approaches to gain insights into the temporal scale at which different processes impact the demography of natural populations.     

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.     

In the absence of a “landscape of fear”: How lions,hyenas, and cheetahs coexist

Aggression by top predators can create a “landscape of fear” in which subordinate predators restrict their activity to low‐risk areas or times of day. At large spatial or temporal scales, this can result in the costly loss of access to resources. However, fine‐scale reactive avoidance may minimize the risk of aggressive encounters for subordinate predators while maintaining access to resources, thereby providing a mechanism for coexistence. We investigated fine‐scale spatiotemporal avoidance in a guild of African predators characterized by intense interference competition. Vulnerable to food stealing and direct killing, cheetahs are expected to avoid both larger predators; hyenas are expected to avoid lions. We deployed a grid of 225 camera traps across 1,125 km² in Serengeti National Park, Tanzania, to evaluate concurrent patterns of habitat use by lions, hyenas, cheetahs, and their primary prey. We used hurdle models to evaluate whether smaller species avoided areas preferred by larger species, and we used time‐to‐event models to evaluate fine‐scale temporal avoidance in the hours immediately surrounding top predator activity. We found no evidence of long‐term displacement of subordinate species, even at fine spatial scales. Instead, hyenas and cheetahs were positively associated with lions except in areas with exceptionally high lion use. Hyenas and lions appeared to actively track each, while cheetahs appear to maintain long‐term access to sites with high lion use by actively avoiding those areas just in the hours immediately following lion activity. Our results suggest that cheetahs are able to use patches of preferred habitat by avoiding lions on a moment‐to‐moment basis. Such fine‐scale temporal avoidance is likely to be less costly than long‐term avoidance of preferred areas: This may help explain why cheetahs are able to coexist with lions despite high rates of lion‐inflicted mortality, and highlights reactive avoidance as a general mechanism for predator coexistence.     

Modelling the recent and potential future spatial distribution of the Ring Ouzel (Turdus torquatus) and Blackbird (T. merula) in Switzerland

We present here a multiscale modelling approach to predict the current and future spatial distribution of Ring Ouzel (Turdus torquatus) and Blackbird (T. merula) in Switzerland. Species distribution models (SDMs) are applied on three different scales in order to analyse the scale-dependency of predictors that describe the species’ realised niche. While the models on the macro- and mesoscales (grid of 100 and 1 km², respectively) cover the entire country, our small-scale models are based on a small set of territories. Ring Ouzels occur at altitudes above 1000 m a.s.l. only, while Blackbirds occur from the lowlands up to the timberline. Although both species coexist on the macro- and mesoscales, a direct niche overlap on territory scale is rare. Small-scale differences in vegetation cover and structure seem to play a dominant role in habitat selection. On the macroscale, however, we observed a high dependency on bioclimatic variables that mainly represent the altitudinal range and the related forest structure preferred by both species. Applying the models to climate change scenarios, we predict a decline of suitable habitat for the Ring Ouzel with a simultaneous median altitudinal shift of 440 m until 2070. In contrast, the Blackbird is predicted to benefit from higher temperatures and expand its range to higher elevations. Based on the species distribution models we (1) demonstrate the scale-dependency of environmental predictors, (2) quantify the scale-dependent habitat requirements of Blackbird and Ring Ouzel and (3) predict the altitudinal range shift of both species as related to climate change scenarios.     

Islands,mainland, and terrestrial fragments: How isolation shapes plant diversity

The fragmentation of natural habitats is a major threat for biodiversity. However, the impact and spatial scale of natural isolation mechanisms leading to species loss, compared to anthropogenic fragmentation, are not clear, mainly due to differences between fragments and islands, such as matrix permeability. We studied a 500 km² Mediterranean region in France, including urban habitat fragments, continuous habitat, and continental‐shelf islands. On the basis of 295 floristic relevés, we built species–area relationships to compare isolation in fragments after urbanization, with continuous habitat and continental‐shelf islands. We assumed either no dispersal, infinite dispersal, or estimated intermediate levels of habitat reachability through graph theory. Isolation mechanisms occurred in fragments but with a lower strength than in near‐shore islands, and most importantly affected perennial plants. Annual plants were less affected, probably due to their smaller size and shorter life cycle. Isolation occurred at landscape level in fragments and at patch level in islands. The amount of reachable habitat (accounting for spatial configuration) explained local species richness in both systems, but the amount of habitat (no consideration of spatial configuration) was already a good predictor. These results suggest an important role of habitat amount around fragments in mitigating the isolation effects observed in near‐shore islands, and the importance of carefully considering different functional groups.     

Distribution, abundance, and individual strategies: a multi-scale analysis of dasyurid marsupials in arid central Australia

We investigated the effects of different environmental factors on the distribution and abundance of 6 species of dasyurid marsupials using a multiple‐scale analysis. Data collected in the spinifex dunefields of the Simpson Desert, Australia, were analysed at 3 spatial scales spanning more than 5 orders of magnitude: “metasite” (covering an area of 1000–2000 km²), site (2–12 km²) and grid (0.01 km²). Temporal variability was also investigated, using data collected in March, April, and May in 4 consecutive years from 1997 to 2000. Both abiotic and biotic factors influenced the capture rates of different species at different times and spatial scales. At the coarsest spatial scale, Dasycercus cristicauda (mulgara) was consistently limited in its distribution by the intensity of rainfall, probably as an indirect result of increased grazing pressure from pastoral activity and a higher density of feral predators in high rainfall areas. However, at the finest spatial scale, this partly carnivorous species was scarce in areas of dense spinifex, perhaps because such habitats yield lowest returns during foraging, and was more common in areas where small invertebrate prey were abundant. Factors affecting the distribution of the most abundant dasyurid species in the study area, Sminthopsis youngsoni (lesser hairy‐footed dunnart), could not be identified at any scale; we conclude that this reflects the opportunistic foraging strategies and flexible habitat requirements of this insectivorous species. Both Ningaui ridei (wongai ningaui) and Sminthopsis hirtipes (hairy‐footed dunnart) were less abundant throughout the study region. For N. ridei, a spinifex specialist, predictors of occurrence could be identified only at the finest scale of analysis; at the grid level, a close positive association was detected in 2 of the 4 study years between capture rate and spinifex cover. For S. hirtipes, all 3 levels of spatial analysis revealed a negative association between capture rate and both rainfall and spinifex density. For the rarely‐caught S. crassicaudata (fat‐tailed dunnart) and Planigale tenuirostris (narrow‐nosed planigale), no clear results were obtained at any spatial scale, and we interpret this to indicate that the study region represents sub‐optimal habitat for these species. Given that different factors affected the distribution and abundance of dasyurids at different spatial scales over time, we conclude that a multiple‐scale approach to population and community analysis is vital to accurately identify which environmental processes shape population and community dynamics. Understanding the interplay between regional and local processes will be crucial for management of existing species populations and for prediction of their distributions and abundances in future.     

Seasonal habitat selection and space use by a semi‐free range herbivore in a heterogeneous savanna landscape

Understanding factors that influence habitat selection in heterogeneous landscapes is fundamental for establishing realistic models on animal distribution to inform rangeland management. In this study, we tested whether seasonal variation in habitat selection within the home range of a large herbivore was influenced by constraints such as, distances from water and central place using semi‐free range cattle (Bos taurus) as a case study. We also tested whether shifts in space use over time were dependent on spatial scale and on the overall abundance of resources. We predicted that distance from water significantly influenced dry season habitat selection while the influence of the central place on habitat selection was season‐independent. We also predicted that shifts in space use over time were spatial scale‐dependent, and that large herbivores would include more diverse habitats in their home ranges during the dry season, when water and food resources are less abundant. Multinomial logit models were used to construct habitat selection models with distances from water and central place as habitat‐specific constraints. Results showed significant variations in habitat selection between the dry and wet season. As predicted, the effect of distance from central place was season‐independent, while the effect of water was not included in the top dry season models contrary to expectation. A diverse range of habitats were also selected during the dry season including agricultural fields. Results also indicated that shifts in space use were spatial scale dependent, with core areas being more sensitive to changes than the home range. In addition, shifts in space use responded to temporal changes in habitat composition. Overall, our results suggest that semi‐free range herbivores adopt different foraging strategies in response to spatial‐temporal changes in habitat availability.     

Niche specificity influences gene flow across fine‐scale habitat mosaics in Succulent Karoo plants

While the tempo of diversification in biodiversity hotspots has received much attention, the spatial scale of diversification has often been overlooked. Addressing this deficiency requires understanding the drivers of population divergence and the spatial scales at which they operate in species‐rich clades and ecosystems. South Africa's Succulent Karoo (SK) hotspot provides an excellent system for such research, being both compact (ca. 110,000 km²) and home to spectacular in‐situ radiations, such as the ruschioid Aizoaceae. Here we use GBS to document genetic structure in two co‐occurring ruschioid species, at both coarse (>10 km) and fine (<500 m) spatial scales. Where Ruschia burtoniae shows strong between‐population genetic differentiation and no gene flow, Conophytum calculus shows weak differentiation, with high levels of admixture suggesting recent or ongoing gene flow. Community analysis and transplant experiments reveal that R. burtoniae occupies a narrow, low‐pH edaphic niche, and at scales of a few hundred metres, areas of elevated genetic turnover correspond to patches of edaphically unsuitable habitat. In contrast, C. calculus occupies a broader niche and exhibits isolation‐by‐distance without a habitat effect. We suggest that edaphic specialisation, coupled with highly restricted seed and pollen dispersal in heterogeneous landscapes, has played a major role in driving rapid diversification at small spatial scales in this system. However, the contrasting patterns in our study species show that these factors do not influence all organisms uniformly, being strongly modulated by lineage‐specific traits that influence both the spatial scale of gene flow and habitat specificity.     

Using Mountain Lion Habitat Selection in Management

Wildlife agencies are generally tasked with managing and conserving species at state and local levels simultaneously. Thus, it is necessary for wildlife agencies to understand basic ecological processes of a given species at multiple scales to aid decision making at commensurately varied spatial and behavioral scales. Mountain lions (Puma concolor) occur throughout California, USA, and are at the center of a variety of management and conservation issues. For example, they are genetically and demographically at risk in 1 region yet apparently stable and negatively affecting endangered species in another. Currently, no formal plan exists for mountain lions in California to deal with these diverse scenarios involving issues of local mountain lion population viability and problems related to predation of endangered species. To facilitate development of a state-wide management and conservation plan, we quantified habitat selection by mountain lions at 2 spatial scales across the range of environmental conditions in which the species is found in California. Our analyses used location data from individuals (n = 263) collared across the state from 2001–2019. At the home range scale, mountain lions selected habitat to prioritize meeting energetic demands. At the within home range scale, mountain lions avoided areas of human activity. Further, our analyses revealed 165,350–170,085 km², depending on season, of suitable mountain lion habitat in California. Fifty percent of the suitable habitat was on unprotected lands and thus vulnerable to development. These habitat selection models will help in the development of a state-wide conservation and management plan for mountain lions in California by guiding mountain lion population monitoring through time, prioritization of habitat to be conserved for maintaining demographic connectivity and gene flow, and efforts to mediate mountain lion-prey interactions. Our work and application area will help with wildlife policy and management decisions related to depredation problems at the local scale and issues of habitat connectivity at the statewide scale. © 2019 The Wildlife Society.     

Landscape size affects the relative importance of habitat amount,habitat fragmentation,and matrix quality on forest birds

It is important to understand the relative effects of landscape habitat loss, habitat fragmentation, and matrix quality on biodiversity, so that potential management options can be appropriately ranked. However, their effects and relative importance may change with the size of the landscape considered because the multiple (and potentially conflicting) ecological processes that are influenced by landscape structure occur at different spatial scales (e.g. dispersal, predation, foraging). We estimated the relative effects of habitat loss, habitat fragmentation, and matrix quality (measured as the amount of forest, the proportion of forest area contained in large core forests, and the density of roads respectively) on fragmentation‐sensitive forest birds in southern Ontario, Canada using a range of landscape sizes (0.8–310 km²). We used three complementary statistical approaches to estimate relative effects of these correlated landscape factors – 1) multiple regression, 2) information theoretic (AIC) estimates of the most parsimonious model, and 3) multi‐model inference to average effects across all supported models. We controlled for spatial autocorrelation, local habitat, roadside sampling bias, time of day, season, habitat heterogeneity, and the interaction between the effects of habitat amount and fragmentation. We found that relative effects of habitat amount and fragmentation were scale dependent; habitat amount had a consistently positive effect that was consistent over more than two orders of magnitude in landscape area (~1–300 km²). In contrast, the effects of habitat fragmentation depended on the size of the landscape considered. Indeed, for veery Catharus fuscescens, habitat fragmentation had positive effects at one scale and negative effects at another. The effects of matrix quality were generally weak and changed little with scale. For the number of fragmentation sensitive species and the presence of veery, habitat amount was most important in large landscapes and habitat fragmentation in small landscapes but for the presence of ovenbird Seiurus aurocapilla, habitat amount was most important at all scales.     

Identifying refugia and corridors under climate change conditions for the Sichuan snub‐nosed monkey (Rhinopithecus roxellana) in Hubei Province,China

Using a case study of an isolated management unit of Sichuan snub‐nosed monkey (Rhinopithecus roxellana), we assess the extent that climate change will impact the species’ habitat distribution in the current period and projected into the 2050s. We identify refugia that could maintain the population under climate change and determine dispersal paths for movement of the population to future suitable habitats. Hubei Province, China. We identified climate refugia and potential movements by integrating bioclimatic models with circuit theory and least‐cost model for the current period (1960–1990) and the 2050s (2041–2060). We coupled a maximum entropy algorithm to predict suitable habitat for the current and projected future periods. Suitable habitat areas that were identified during both time periods and that also satisfied home range and dispersal distance conditions were delineated as refugia. We mapped potential movements measured as current flow and linked current and future habitats using least‐cost corridors. Our results indicate up to 1,119 km² of currently suitable habitat within the study range. Based on our projections, a habitat loss of 67.2% due to climate change may occur by the 2050s, resulting in a reduced suitable habitat area of 406 km² and very little new habitat. The refugia areas amounted to 286 km² and were located in Shennongjia National Park and Badong Natural Reserve. Several connecting corridors between the current and future habitats, which are important for potential movements, were identified. Our assessment of the species predicted a trajectory of habitat loss following anticipated future climate change. We believe conservation efforts should focus on refugia and corridors when planning for future species management. This study will assist conservationists in determining high‐priority regions for effective maintenance of the endangered population under climate change and will encourage increased habitat connectivity.     

Stable isotope analysis as a tool to monitor dietary trends in little penguins Eudyptula minor

Long‐term dietary monitoring of seabirds can be used to relate population fluctuations to at‐sea events. Stomach flushing is a conventional dietary monitoring technique, but has a number of disadvantages. Stable isotope analysis (SIA) is a less invasive method that provides unbiased dietary information over a longer period. We evaluated stable isotope analysis as a potential tool for monitoring long‐term little penguin Eudyptula minor diet. We determined diet composition during the chick feeding stage using stomach flushing and SIA at three separate colonies, using spatial variation in diet as a surrogate for potential temporal variation. Bayesian isotopic mixing models were generated for blood and feathers to evaluate their ability to discriminate broad‐scale (fish, squid, crustaceans) and fine‐scale (individual prey species) diet composition. Differences in stable carbon and nitrogen isotope ratios were found between colonies: broad‐scale isotopic mixing models predicted different proportional contributions of broad taxa (fish, cephalopod, crustacean) to diet than was indicated by stomach samples, reflecting the bias incurred by one‐off stomach contents analysis. Fine‐scale isotopic mixing models predicted proportional contributions of prey items with less certainty. Blood isotopic mixing models had narrower confidence intervals than models for feathers, but trends in δ¹⁵N for feathers mirrored those for blood. Our results suggest that relying on stomach contents analysis to detect shifts in prey consumption in little penguins could be very misleading, resulting in a less‐than‐complete idea of total prey consumption. SIA of little penguin tissues could be used to monitor dietary shifts across dissimilar taxa that may affect population numbers, but would fail to detect shifts between fish species.     

Climate,competition and connectivity affect future migration and ranges of European trees

Aim Species ranges have adapted during the Holocene to altering climate conditions, but it remains unclear if species will be able to keep pace with recent and future climate change. The goal of our study is to assess the influence of changing macroclimate, competition and habitat connectivity on the migration rates of 14 tree species. We also compare the projections of range shifts from species distribution models (SDMs) that incorporate realistic migration rates with classical models that assume no or unlimited migration. Location Europe. Methods We calibrated SDMs with species abundance data from 5768 forest plots from ICP Forest Level 1 in relation to climate, topography, soil and land‐use data to predict current and future tree distributions. To predict future species ranges from these models, we applied three migration scenarios: no migration, unlimited migration and realistic migration. The migration rates for the SDMs incorporating realistic migration were estimated according to macroclimate, inter‐specific competition and habitat connectivity from simulation experiments with a spatially explicit process model (TreeMig). From these relationships, we then developed a migration cost surface to constrain the predicted distributions of the SDMs. Results The distributions of early‐successional species during the 21st century predicted by SDMs that incorporate realistic migration matched quite well with the unlimited migration assumption (mean migration rate over Europe for A1fi/GRAS climate and land‐use change scenario 156.7 ± 79.1 m year^?1 and for B1/SEDG 164.3 ± 84.2 m year^?1). The predicted distributions of mid‐ to late‐successional species matched better with the no migration assumption (A1fi/GRAS, 15.2 ± 24.5 m year^?1 and B1/SEDG, 16.0 ± 25.6 m year^?1). Inter‐specific competition, which is higher under favourable growing conditions, reduced range shift velocity more than did adverse macroclimatic conditions (i.e. very cold or dry climate). Habitat fragmentation also led to considerable time lags in range shifts. Main conclusions Migration rates depend on species traits, competition, spatial habitat configuration and climatic conditions. As a result, re‐adjustments of species ranges to climate and land‐use change are complex and very individualistic, yet still quite predictable. Early‐successional species track climate change almost instantaneously while mid‐ to late‐ successional species were predicted to migrate very slowly.     

Resource selection by an ectothermic predator in a dynamic thermal landscape

Predicting the effects of global climate change on species interactions has remained difficult because there is a spatiotemporal mismatch between regional climate models and microclimates experienced by organisms. We evaluated resource selection in a predominant ectothermic predator using a modeling approach that permitted us to assess the importance of habitat structure and local real‐time air temperatures within the same modeling framework. We radio‐tracked 53 western ratsnakes (Pantherophis obsoletus) from 2010 to 2013 in central Missouri, USA, at study sites where this species has previously been linked to prey population demographics. We used Bayesian discrete choice models within an information theoretic framework to evaluate the seasonal effects of fine‐scale vegetation structure and thermal conditions on ratsnake resource selection. Ratsnake resource selection was influenced most by canopy cover, canopy cover heterogeneity, understory cover, and air temperature heterogeneity. Ratsnakes generally preferred habitats with greater canopy heterogeneity early in the active season, and greater temperature heterogeneity later in the season. This seasonal shift potentially reflects differences in resource requirements and thermoregulation behavior. Predicted patterns of space use indicate that ratsnakes preferentially selected open habitats in spring and early summer and forest–field edges throughout the active season. Our results show that downscaled temperature models can be used to enhance our understanding of animal resource selection at scales that can be addressed by managers. We suggest that conservation of snakes or their prey in a changing climate will require consideration of fine‐scale interactions between local air temperatures and habitat structure.     

Modelling breeding habitat preferences of Bonelli’s eagle (Hieraaetus fasciatus) in relation to topography, disturbance, climate and land use at different spatial scales

Predictive models on breeding habitat preferences of Bonelli’s eagle (Hieraaetus fasciatus; Aves: Accipitridae) have been performed at four different spatial scales in Castellón province, East of Iberian Peninsula. The scales considered were: (1) nest site scale (1×1 km² Universal Transverse Mercator (UTM) square containing the nest); (2) near nest environment (3×3 km² UTM square); (3) home range scale (5×5 km² UTM square); and (4) landscape level scale (9×9 km² UTM square containing the above mentioned ones). Topographic, disturbance, climatic and land use factors were measured on a geographic information system (GIS) at occupied and unoccupied UTM squares. Logistic regression was performed by means of a stepwise addition procedure. We tested whether inclusion of new subset of variables improved the models by increasing the area under the receiver operator characteristic plot. At nest site scale, only topographic factors were considered as the most parsimonious predictors. Probability of species occurrence increases with slope in craggy areas at lower altitudes. At the 3×3 km² scale, climate and disturbance variables were included. At home range and landscape level scales, models included climate, disturbance, topographic and land use factors. Higher temperatures in January, template ones in July, higher rainfall in June, lower altitudes and higher slope in the sample unit increase probability of occurrence of Bonelli’s eagle at broadest scales. The species seems to prefer disperse forests, scrubland and agricultural areas. From our results, we consider that there is a hierarchical framework on habitat selection procedure. We suggest that it is necessary to analyse what key factors are affecting Bonelli’s eagle nest-site selection at every study area to take steps to ensure appropriate conservation measures. The combination of regression modelling and GIS will become a powerful tool for biodiversity and conservation studies, taking into account that application depends on sampling design and the model assumptions of the statistical methods employed. Finally, predictive models obtained could be used for the efficient monitoring of this scarce species, to predict range expansions or identify suitable locations for reintroductions, and also to design protected areas and to help on wildlife management.