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Stacking is the process of overlaying inferred species potential distributions for multiple species based on outputs of bioclimatic envelope models (BEMs). The approach can be used to investigate patterns and processes of species richness. If data limitations on individual species distributions are inevitable, but how do they affect inferences of patterns and processes of species richness? We investigate the influence of different data sources on estimated species richness gradients in China. We fitted BEMs using species distributions data for 334 bird species obtained from (1) global range maps, (2) regional checklists, (3) museum records and surveys, and (4) citizen science data using presence-only (Mahalanobis distance), presence-background (MAXENT), and presence–absence (GAM and BRT) BEMs. Individual species predictions were stacked to generate species richness gradients. Here, we show that different data sources and BEMs can generate spatially varying gradients of species richness. The environmental predictors that best explained species distributions also differed between data sources. Models using citizen-based data had the highest accuracy, whereas those using range data had the lowest accuracy. Potential richness patterns estimated by GAM and BRT models were robust to data uncertainty. When multiple data sets exist for the same region and taxa, we advise that explicit treatments of uncertainty, such as sensitivity analyses of the input data, should be conducted during the process of modeling.

[Aim]: If communities have a ceiling determining the number of species that can coexist, then the ability of alien species to establish at any given location should be related to the quantity of vacant niches available. We developed a new approach to estimate the extent to which niches are vacant and then explored the relationship between vacant niches and alien species., [Location]: Global with focal tests in Europe and North America., [Taxon]: Birds., [Methods]: Drawing on a global classification of trophic structures for birds, we cal-culated a ‘vacant niche ratio’ metric to quantify the expected level of saturation (i.e. number of vacant niches) for each 1° × 1° grid cell globally, based on the difference between expected and observed numbers of bird species for all trophic guilds. Next, we used random forests to examine if the presence of plant-invertivore (whose food source represents plants, seeds, fruits and invertebrates) and granivore alien bird spe-cies was associated with the vacant niche ratio across well-sampled regions., [Results]: In Europe, we found a significant relationship between alien species and vacant niches, with greater numbers of alien species being found in communities that offered greater numbers of vacant niches overall, and across habitat types. In North America, we found no significant relationship between plant-invertivores and vacant niches, while for granivores, we found that areas with fewer vacant niches had greater numbers of alien species, especially in forests. However, vacant niches alone correctly predict 69% of the presence of alien bird species when combining both regions and trophic guilds., [Main conclusions]: Most regions of the world have unsaturated bird communities, with the level of saturation in communities varying within regions and trophic guilds. We found that although often- neglected, vacant niches are likely to be, at least par-tially, related with the successful establishment of alien bird species.

Spatial turnover of biological communities is determined by both dispersal and environmental constraints. However, we lack quantitative predictions about how these factors interact and influence turnover across genealogical scales. In this study, we have implemented a predictive framework based on approximate Bayesian computation (ABC) to quantify the signature of dispersal and environmental constraints in community turnover. First, we simulated the distribution of haplotypes, intra-specific lineages and species in biological communities under different strengths of dispersal and environmental constraints. Our simulations show that spatial turnover rate is invariant across genealogical scales when dispersal limitation determines the species ranges. However, when environmental constraint limits species ranges, spatial turnover rates vary across genealogical scales. These simulations were used in an ABC framework to quantify the role of dispersal and environmental constraints in 16 empirical biological communities sampled from local to continental scales, including several groups of insects (both aquatic and terrestrial), molluscs and bats. In seven datasets, the observed genealogical invariance of spatial turnover, assessed with distance–decay curves, suggests a dispersal-limited scenario. In the remaining datasets, the variance in distance–decay curves across genealogical scales was best explained by various combinations of dispersal and environmental constraints. Our study illustrates how modelling spatial turnover at multiple genealogical scales (species and intraspecific lineages) provides relevant insights into the relative role of dispersal and environmental constraints in community turnover.

Networks describe nodes connected by links, with numbers of links per node, the degree, forming a range of distributions including random and scale-free. How network topologies emerge in natural systems still puzzles scientists. Based on previous theoretical simulations, we predict that scale-free food webs are favourably selected by random disturbances while random food webs are selected by targeted disturbances. We assume that lower human pressures are more likely associated with random disturbances, whereas higher pressures are associated with targeted ones. We examine these predictions using 351 empirical food webs, generally confirming our predictions. Should the topology of food webs respond to changes in the magnitude of disturbances in a predictable fashion, consistently across ecosystems and scales of organisation, it would provide a baseline expectation to understand and predict the consequences of human pressures on ecosystem dynamics.

Humans have moved species away from their native ranges since the Neolithic, but globalization accelerated the rate at which species are being moved. We fitted more than half million distribution models for 610 traded bird species on the CITES list to examine the separate and joint effects of global climate and land-cover change on their potential end-of-century distributions. We found that climate-induced suitability for modelled invasive species increases with latitude, because traded birds are mainly of tropical origin and much of the temperate region is ‘tropicalizing.’ Conversely, the tropics are becoming more arid, thus limiting the potential from cross-continental in vasion by tropical species. This trend is compounded by forest loss around the tropics since most traded birds are forest dwellers. In contrast, net gains in forest area across the temperate region could compound climate change effects and increase the potential for colonization of low-latitude birds. Climate change has always led to regional redistributions of species, but the combination of human transportation, climate, and land-cover changes will likely accelerate the redistribution of species globally, increas ing chances of alien species successfully invading non-native lands. Such process of biodiversity homogenization can lead to emergence of non-analogue communities with unknown environmental and socioeconomic consequences.

Aim Invasive alien species (IAS) can cause profound impacts on ecosystem function and diversity, human health, well-being and livelihoods. Climate change is an important driver of biological invasions, so it is critical to develop models and climate-driven scenarios of IAS range shifts to establish preventive measures. In this study, we analyse how projected changes in the frequency and magnitude of climate extreme events could affect the spread of the six most widely distributed invasive vertebrate species in the Iberian Peninsula. Location Iberian Peninsula. Taxa Red avadavat (Amandava amandava), common waxbill (Estrilda astrild), monk parakeet (Myiopsitta monachus), rose-ringed parakeet (Psittacula krameri), American mink (Neovison vison) and pond slider (Trachemys scripta). Methods We followed best-practice standards for species distribution models (SDMs) regarding handling of the response and predictor variables, model building and evaluation using metrics that assess different facets of model performance. We used an ensemble approach with four modelling methods of varying complexity, including both regression-based and tree-based machine-learning algorithms. We analysed five regional models for current (1971–2000) and future climate (2021–2050). We used principal components analysis to assess consensus among model outputs and positively weighed predictions from well-performing models. Results Selected models showed high consensus and good predictive capacity on block cross-validation areas. Generalized Linear Models and Generalized Additive Models scored highest in reliability (calibration), but Bayesian Additive Regression Trees provided the best balance between calibration and discrimination capacity. Forecasts include visible changes in environmental favourability, with losses generally outweighing the gains, but with some areas becoming more favourable for several species. Main conclusions Increased frequency and/or intensity of climate extreme events asso, Gobierno de Castilla-La Mancha, Foundation for Science and Technology (FCT), Depto. de Biodiversidad, Ecología y Evolución, Fac. de Ciencias Biológicas, TRUE, pub

Species are reportedly shifting their distributions poleward and upward in several parts of the world in response to climate change. The extent to which other factors might play a role driving these changes is still unclear. Land-cover change is a major cause of distributional changes, but it cannot be discarded that distributional dynam-ics might be at times caused by other mechanisms (e.g. dispersal, ecological drift). Using observed changes in the distribution of 82 breeding birds in Great Britain be-tween three time periods 1968–72 (t1), 1988–91 (t2) and 2007–2011 (t3), we exam-ine whether observed bird range shifts between t1-t2 and t1-t3 are best explained by climate change or land-cover change, or whether they are not distinguishable from what would be expected by chance. We found that range shifts across the rear edge of northerly distributed species in Great Britain are best explained by climate change, while shifts across the leading edge of southerly distributed species are best explained by changes in land-cover. In contrast, at the northern and southern edges of Great Britain, range dynamics could not be distinguished from that expected by chance. The latter observation could be a consequence of boundary effects limiting the direction and magnitude of range changes, stochastic demographic mechanisms neither associated with climate nor land-cover change or with complex interactions among factors. Our results reinforce the view that comprehensive assessments of climate change effects on species range shifts need to examine alternative drivers of change on equal footing and that null models can help assess whether observed patterns could have arisen by chance alone.

[Aim]: Invasive alien species (IAS) can cause profound impacts on ecosystem function and diversity, human health, well- being and livelihoods. Climate change is an important driver of biological invasions, so it is critical to develop models and climate- driven scenarios of IAS range shifts to establish preventive measures. In this study, we analyse how projected changes in the frequency and magnitude of climate extreme events could affect the spread of the six most widely distributed invasive vertebrate species in the Iberian Peninsula., [Location]: Iberian Peninsula., [Taxa]: Red avadavat (Amandava amandava), common waxbill (Estrilda astrild), monk parakeet (Myiopsitta monachus), rose- ringed parakeet (Psittacula krameri), American mink (Neovison vison) and pond slider (Trachemys scripta)., [Methods]: We followed best- practice standards for species distribution models (SDMs) regarding handling of the response and predictor variables, model building and evaluation using metrics that assess different facets of model performance. We used an ensemble approach with four modelling methods of varying complexity, including both regression- based and tree- based machine- learning algorithms. We analysed five regional models for current (1971– 2000) and future climate (2021– 2050). We used principal components analysis to assess consensus among model outputs and positively weighed predictions from well- performing models., [Results]: Selected models showed high consensus and good predictive capacity on block cross- validation areas. Generalized Linear Models and Generalized Additive Models scored highest in reliability (calibration), but Bayesian Additive Regression Trees provided the best balance between calibration and discrimination capacity. Forecasts include visible changes in environmental favourability, with losses generally outweighing the gains, but with some areas becoming more favourable for several species., [Main conclusions]: Increased frequency and/or intensity of climate extreme events associated with ongoing climate change are projected to reduce overall invasion risk for the species examined although increases in favourability should be expected locally.

Ecological Niche Models (ENMs) have different performances in predicting potential geographic distributions. Here we meta-analyzed the likely effects of climate change on the potential geographic distribution of 1,205 bird species from the Neotropical region, modeled using eight ENMs and three Atmosphere-Ocean General Circulation Models (AOGCM). We considered the variability in ENMs performance to estimate a weighted mean difference between potential geographic distributions for baseline and future climates. On average, potential future ranges were projected to be from 25.7% to 44.5% smaller than current potential ranges across species. However, we found that 0.2% to 18.3% of the total variance in range shifts occurred “within species” (i.e., owing to the use of different modeling techniques and climate models) and 81.7% to 99.8% remained between species (i.e., it could be explained by ecological correlates). Using meta-analytical techniques akin to regression, we also showed that potential range shifts are barely predicted by bird biological traits. We demonstrated that one can combine and reduce species-specific effects with high uncertainty in ENMs and also explore potential causes of climate change effect on species using meta-analytical tools. We also highlight that the search for powerful correlates of climate change-induced range shifts can be a promising line of investigation.

Understanding the mechanisms driving geographic range sizes of species is a central issue in ecology, but remarkably few rules link physiology with the distributions of species. Maximal metabolic rate (MMR) during exercise is an important measure of physiological performance. It sets an upper limit to sustained activity and locomotor capacity, so MMR may influence ability to migrate, disperse and maintain population connectivity. Using both conventional ordinary least squares (OLS) analyses and phylogenetically generalized least squares (PGLS), we tested whether MMR helps explain geographic range size in 51 species of placental mammals. Log body mass alone (OLS r =.074, p =.053; PGLS r =.016, p =.373) and log MMR alone (OLS r =.140, p =.007; PGLS r =.061, p =.081) were weak predictors of log range size. However, multiple regression of log body mass and log MMR accounted for over half of the variation in log range size (OLS R =.527, p <.001). The relationship was also strong after correcting for the phylogenetic non-independence (PGLS R =.417, p <.001). In analyses restricted to rodents (34 species), neither log body mass alone (OLS r =.004, p =.720; PGLS r =.003, p =.77) nor log MMR alone was useful in predicting log geographic range size (OLS r =.008, p =.626; PGLS r =.046, p =.225), but multiple regressions of log body mass and log MMR accounted for roughly a third to a half of the variation in log range size (OLS R =.443, p <.001, PGLS R =.381, p <.001). Mass-independent MMR is a strong predictor of mass-independent geographic range size in placental mammals. The ability of body mass and MMR to explain nearly 50% of the variation in the geographic ranges of mammals is surprising and powerful, particularly when neither variable alone is strongly predictive. A better understanding of MMR during exercise may be important to understanding the limits of geographic ranges of mammals, and perhaps other animal groups.

Intraspecific genetic variability is critical for species adaptation and evolution and yet it is generally overlooked in projections of the biological consequences of climate change. We ask whether ongoing climate changes can cause the loss of important gene pools from North Atlantic relict kelp forests that persisted over glacial–interglacial cycles. We use ecological niche modelling to predict genetic diversity hotspots for eight species of large brown algae with different thermal tolerances (Arctic to warm temperate), estimated as regions of persistence throughout the Last Glacial Maximum (20,000 YBP), the warmer Mid‐Holocene (6,000 YBP), and the present. Changes in the genetic diversity within ancient refugia were projected for the future (year 2100) under two contrasting climate change scenarios (RCP2.6 and RCP8.5). Models predicted distributions that matched empirical distributions in cross‐validation, and identified distinct refugia at the low latitude ranges, which largely coincide among species with similar ecological niches. Transferred models into the future projected polewards expansions and substantial range losses in lower latitudes, where richer gene pools are expected (in Nova Scotia and Iberia for cold affinity species and Gibraltar, Alboran, and Morocco for warm‐temperate species). These effects were projected for both scenarios but were intensified under the extreme RCP8.5 scenario, with the complete borealization (circum‐Arctic colonization) of kelp forests, the redistribution of the biogeographical transitional zones of the North Atlantic, and the erosion of global gene pools across all species. As the geographic distribution of genetic variability is unknown for most marine species, our results represent a baseline for identification of locations potentially rich in unique phylogeographic lineages that are also climatic relics in threat of disappearing.

Criticism has been levelled at climate-change-induced forecasts of species range shifts that do not account explicitly for complex population dynamics. The relative importance of such dynamics under climate change is, however, undetermined because direct tests comparing the performance of demographic models vs. simpler ecological niche models are still lacking owing to difficulties in evaluating forecasts using real-world data. We provide the first comparison of the skill of coupled ecological-niche-population models and ecological niche models in predicting documented shifts in the ranges of 20 British breeding bird species across a 40-year period. Forecasts from models calibrated with data centred on 1970 were evaluated using data centred on 2010. We found that more complex coupled ecological-niche-population models (that account for dispersal and metapopulation dynamics) tend to have higher predictive accuracy in forecasting species range shifts than structurally simpler models that only account for variation in climate. However, these better forecasts are achieved only if ecological responses to climate change are simulated without static snapshots of historic land use, taken at a single point in time. In contrast, including both static land use and dynamic climate variables in simpler ecological niche models improve forecasts of observed range shifts. Despite being less skilful at predicting range changes at the grid-cell level, ecological niche models do as well, or better, than more complex models at predicting the magnitude of relative change in range size. Therefore, ecological niche models can provide a reasonable first approximation of the magnitude of species' potential range shifts, especially when more detailed data are lacking on dispersal dynamics, demographic processes underpinning population performance, and change in land cover.

Following environmental changes, communities disassemble and reassemble in seemingly unpredictable ways. Whether species respond to such changes individualistically or collectively (e.g. as functional groups) is still unclear. To address this question, we used an extensive new dataset for the lake communities in the Azores' archipelago to test whether: 1) individual species respond concordantly within trophic groups; 2) trophic groups respond concordantly to biogeographic and environmental gradients. Spatial concordance in individual species distributions within trophic groups was always greater than expected by chance. In contrast, trophic groups varied non-concordantly along biogeographic and environmental gradients revealing idiosyncratic responses to them. Whether communities respond individualistically to environmental gradients thus depends on the functional resolution of the data. Our study challenges the view that modelling environmental change effects on biodiversity always requires an individualist approach. Instead, it finds support for the longstanding idea that communities might be modelled as a cohort if the functional resolution is appropriate.

Humans have modified species distributions in most of the world's natural ecosystems. Analyses of species distributions tend to ignore these modifications, potentially masking the signatures of natural processes on them. We examine the strength of a classic pattern in ecology – the body mass-latitudinal relationship, aka Bergmann's rule – for all mammal species worldwide using both contemporary and estimated natural distributions. We show that human modifications of mammal species distributions lead to substantially underestimating the strength of the Bergmann's rule. We speculate that other broad-scale ecological patterns might be similarly affected.

Aim: Mapping the distribution and diversity of plant functional traits is critical for projecting future changes to vegetation under global change. Maps of plant functional traits, however, are scarce due very sparse global trait data matrices. A potential solution to this data limitation is to utilize the known levels of phylogenetic signal in trait data to predict missing values. Here we aim to test existing phylogenetic comparative methods for imputing missing trait data for the purpose of producing continental-scale maps of plant functional traits. Location: North America and Europe. Methods: Phylogenetic imputation models and trait data from one continent were used to predict the trait values for tree species on the other continent and to produce trait maps. Predicted maps of trait means, variances and functional diversity were compared with known maps to quantify the degree to which predicted trait values could estimate spatial patterns of trait distributions and diversity. Results: We show that the phylogenetic signal in plant functional trait data can be used to provide robust predictions of the geographical distribution of tree functional diversity. However, predictions for traits with little phylogenetic signal, such as maximum height, are error prone. Lastly, trait imputation methods based on phylogenetic generalized least squares tended to outperform those based on phylogenetic eigenvectors. Main conclusions: It is possible to predict patterns of functional diversity across continental settings with novel species assemblages for most of the traits studied for which we have no direct trait information, thereby offering an effective method for overcoming a key data limitation in global change biology, macroecology and ecosystem modelling.

Aims: The 50th anniversary of the publication of the seminal book, The Theory of Island Biogeography, by Robert H. MacArthur and Edward O. Wilson, is a timely moment to review and identify key research foci that could advance island biology. Here, we take a collaborative horizon-scanning approach to identify 50 fundamental questions for the continued development of the field. Location: Worldwide. Methods: We adapted a well-established methodology of horizon scanning to identify priority research questions in island biology, and initiated it during the Island Biology 2016 conference held in the Azores. A multidisciplinary working group prepared an initial pool of 187 questions. A series of online surveys was then used to refine a list of the 50 top priority questions. The final shortlist was restricted to questions with a broad conceptual scope, and which should be answerable through achievable research approaches. Results: Questions were structured around four broad and partially overlapping island topics, including: (Macro)Ecology and Biogeography, (Macro)Evolution, Community Ecology, and Conservation and Management. These topics were then subdivided according to the following subject areas: global diversity patterns (five questions in total); island ontogeny and past climate change (4); island rules and syndromes (3); island biogeography theory (4); immigration–speciation–extinction dynamics (5); speciation and diversification (4); dispersal and colonization (3); community assembly (6); biotic interactions (2); global change (5); conservation and management policies (5); and invasive alien species (4). Main conclusions: Collectively, this cross-disciplinary set of topics covering the 50 fundamental questions has the potential to stimulate and guide future research in island biology. By covering fields ranging from biogeography, community ecology and evolution to global change, this horizon scan may help to foster the formation of interdisciplinary research network

The increased availability of both open ecological data, and software to interact with it, allows the fast collection and integration of information at all spatial and taxonomic scales. This offers the opportunity to address macroecological questions in a cost‐effective way. In this contribution, we illustrate this approach by forecasting the structure of a stream food web at the global scale. In so doing, we highlight the most salient issues needing to be addressed before this approach can be used with a high degree of confidence.

Sdm is an object‐oriented, reproducible and extensible, platform for species distribution modelling. It uses individual species and community‐based approaches, enabling ensembles of models to be fitted and evaluated, to project species potential distributions in space and time. It provides a standardized and unified structure for handling species distributions data and modelling techniques, and supports markedly different modelling approaches, including correlative, process‐based (mechanistic), agent‐based, and cellular automata. The object‐oriented design of software is such that scientists can modify existing methods, extend the framework by developing new methods or modelling procedures, and share them to be reproduced by other scientists. sdm can handle spatial and temporal data for single or multiple species and uses high performance computing solutions to speed up modelling and simulations. The framework is implemented in R, providing a flexible and easy‐to‐use GUI interface.

Ecological monitoring programmes are designed to detect and measure changes in biodiversity and ecosystems. In the case of biological invasions, they can contribute to anticipating risks and adaptively managing invaders. However, monitoring is often expensive because large amounts of data might be needed to draw inferences. Thus, careful planning is required to ensure that monitoring goals are realistically achieved. Species distribution models (SDMs) can provide estimates of suitable areas to invasion. Predictions from these models can be applied as inputs in optimization strategies seeking to identify the optimal extent of the networks of areas required for monitoring risk of invasion under current and future environmental conditions. A hierarchical framework is proposed herein that combines SDMs, scenario analysis and cost analyses to improve invasion assessments at regional and local scales. We illustrate the framework with Acacia dealbata Link. (Silver-wattle) in northern Portugal. The framework is general and applicable to any species. We defined two types of monitoring networks focusing either on the regional-scale management of an invasion, or management focus within and around protected areas. For each one of these two schemes, we designed a hierarchical framework of spatial prioritization using different information layers (e.g. SDMs, habitat connectivity, protected areas). We compared the performance of each monitoring scheme against 100 randomly generated models. In our case study, we found that protected areas will be increasingly exposed to invasion by A. dealbata due to climate change. Moreover, connectivity between suitable areas for A. dealbata is predicted to increase. Monitoring networks that we identify were more effective in detecting new invasions and less costly to management than randomly generated models. The most cost-efficient monitoring schemes require 18% less effort than the average networks across all of the 100 tested options. Synthes

The notion that conservation areas are static geographical units for biodiversity conservation should be revised when planning for climate-change adaptation. Since species are expected to respond to climate change by shifting their distributions, conservation areas can lose the very same species that justified their designation. Methods exist to take into account the potential effects of climate on spatial priorities for conservation. One of such methods involves the identification of time-ordered linkages between conservation areas (hereafter termed climate-change corridors), thus enabling species tracking their suitable changing climates. We critically review and synthesise existing quantitative approaches for spatial conservation planning under climate change. We extend these approaches focusing on the identification of climate-change corridors, using three alternative models that vary on the objective function (minimum cost or maximum benefit sought) and on the nature of conservation targets (area-based or persistence probabilities). The three models for establishing climate-change corridors are illustrated with a case study involving two species distributed across the Iberian Peninsula. The species were modelled in relation to climate-change scenarios using ensembles of bioclimatic models and theoretical dispersal kernels. The corridors obtained are compared for their location, the temporal sequence of priorities, and the effectiveness with which solutions attain persistence and cost objectives. By clearly framing the climate-change corridors problem as three alternative models and providing the corresponding mathematical descriptions and solving tools, we offer planners a wide spectrum of models that can be easily adapted to a variety of conservation goals and constraints.

Aim: Bioclimatic envelope models are widely used to describe changes in climatically suitable areas for species under future climate scenarios. Climate change metrics are applied independently of species data to characterize the spatio-temporal dynamics of climate, and have also been used as indicators of the exposure of species to climate change. Here, we investigate whether these two approaches provide qualitatively similar indications about where biodiversity is potentially most exposed to climate change. Location: Sub-Saharan Africa., Methods: We compared a range of climate change metrics for sub-Saharan Africa with ensembles of bioclimatic envelope models for 2723 species of amphibians, snakes, mammals and birds. For each taxonomic group, we performed three comparisons between the two approaches: (1) is projected change in local climatic suitability (models) greater in grid cells with larger temporal differences in local climate (metrics); (2) are projected losses or gains of climatically suitable areas (models) greater for species in grid cells with climates that are projected to be less or more available in the future, respectively (metrics); and (3) are projected shifts in the position of climatically suitable areas (models) greater for species in grid cells with climates projected to move farther in space (metrics)?, Results: The changes in climatic suitability projected by the bioclimatic envelope models covaried with the climatic changes measured with the metrics. Agreement between the two approaches was found for all taxonomic groups, although it was stronger for species with a narrower climatic envelope breadth., Main conclusions: For sub-Saharan African vertebrates, projected patterns of exposure to climate change given by climate change metrics alone were qualitatively comparable to bioclimatic model projections of changes in areas of suitable climate for species. Assessments based on climate change metrics can thus be useful for making first-cut inferences about the potential effects of climate change on regions with poorly known biodiversity.

Aim: To assess gaps in the representation of taxonomic, phylogenetic and functional diversity among coastal fishes in Mediterranean marine-protected areas (MPAs)., Location: Mediterranean Sea, Methods: We first assessed gaps in the taxonomic representation of the 340 coastal fish species in Mediterranean MPAs, with representation targets (the species range proportion to be covered by MPAs) set to be inversely proportional to species’ range sizes. We then asked whether MPAs favoured representation of phylogenetically and functionally more distinct species or whether there was a tendency to favour less distinctive ones. We finally evaluated the overall conservation effectiveness of the MPAs using a metric that integrates species’ phylogenetic and functional relationships and targets achievement. The effectiveness of the MPA system at protecting biodiversity was assessed by comparison of its achievements against a null model obtained by siting current MPAs at random over the study area., Results: Among the coastal fish species analysed, 16 species were not covered by any MPA. All the remaining species only partially achieved the pre-defined representation target. The current MPA system missed fewer species than expected from siting MPAs at random. However, c. 70% of the species did not achieve better protection in the current MPAs than expected from siting MPAs at random. Functional and evolutionary distinctiveness were weakly correlated with target achievement. The observed coverage of taxonomic, phylogenetic and functional diversity was not different or lower than expected from siting MPAs at random., Main conclusions: The Mediterranean MPA system falls short in meeting conservation targets for coastal fish taxonomic diversity, phylogenetic diversity and functional diversity. Mediterranean MPAs do not encompass more biodiversity than expected by chance. This study reveals multiple ongoing challenges and calls for regional collaboration for the extension of the Mediterranean system of MPAs to meet international commitments and reduce the ongoing loss of marine biodiversity.

Aim: Understanding the factors that govern species' geographical ranges is of utmost importance for predicting potential range shifts triggered by environmental change. Species ranges are partially limited by their tolerances to extrinsic environmental conditions such as climate and habitat. However, they are also determined by the capacity of species to disperse, establish new populations and proliferate, which are in turn dependent on species intrinsic life-history traits. So far, the contribution of intrinsic factors driving species distributions has been inconclusive, largely because intrinsic and extrinsic factors have not been examined simultaneously in a satisfactory way. We investigate how geographical ranges of plants are determined by both extrinsic environmental factors and species intrinsic life-history traits., Location: Europe., Methods: We compiled a database on plant geographical ranges, environmental tolerances and life-history traits that constitutes the largest dataset analysed to date (1276 species). We used generalized linear modelling to test if range size and range filling (the proportion of climatically suitable area a species occupies) are affected by dispersal distance, habitat breadth and 10 life-history traits related to establishment and proliferation., Results: The species characteristics that were most linked to range limitations of European plant species were dispersal potential, seed bank persistence and habitat breadth (which together explained ≥ 30% of deviance in range filling and range size). Specific leaf area, which has been linked to establishment ability, made a smaller contribution to native range limitations., Main conclusions: Our results can be used to improve estimates of extinction vulnerability under climate change. Species with high dispersal capacity, that can maintain viable seed banks for several years and that can live in an intermediate number of habitats have the fewest non-climatic limitations on their ranges, and are most likely to shift their geographical ranges under climate change. We suggest that climate-change risk assessments should not focus exclusively on dispersal capacity.

A central tenet of ecology and biogeography is that the broad outlines of species ranges are determined by climate, whereas the effects of biotic interactions are manifested at local scales. While the first proposition is supported by ample evidence, the second is still a matter of controversy. To address this question, we develop a mathematical model that predicts the spatial overlap, i.e. co-occurrence, between pairs of species subject to all possible types of interactions. We then identify the scale of resolution in which predicted range overlaps are lost. We found that co-occurrence arising from positive interactions, such as mutualism (+/+) and commensalism (+/0), are manifested across scales. Negative interactions, such as competition (-/-) and amensalism (-/0), generate checkerboard patterns of co-occurrence that are discernible at finer resolutions but that are lost and increasing scales of resolution. Scale dependence in consumer-resource interactions (+/-) depends on the strength of positive dependencies between species. If the net positive effect is greater than the net negative effect, then interactions scale up similarly to positive interactions. Our results challenge the widely held view that climate alone is sufficient to characterize species distributions at broad scales, but also demonstrate that the spatial signature of competition is unlikely to be discernible beyond local and regional scales. © 2013 The Authors.

© 2014 The Authors. Species are the unit of analysis in many global change and conservation biology studies; however, species are not uniform entities but are composed of different, sometimes locally adapted, populations differing in plasticity. We examined how intraspecific variation in thermal niches and phenotypic plasticity will affect species distributions in a warming climate. We first developed a conceptual model linking plasticity and niche breadth, providing five alternative intraspecific scenarios that are consistent with existing literature. Secondly, we used ecological niche-modeling techniques to quantify the impact of each intraspecific scenario on the distribution of a virtual species across a geographically realistic setting. Finally, we performed an analogous modeling exercise using real data on the climatic niches of different tree provenances. We show that when population differentiation is accounted for and dispersal is restricted, forecasts of species range shifts under climate change are even more pessimistic than those using the conventional assumption of homogeneously high plasticity across a species' range. Suitable population-level data are not available for most species so identifying general patterns of population differentiation could fill this gap. However, the literature review revealed contrasting patterns among species, urging greater levels of integration among empirical, modeling and theoretical research on intraspecific phenotypic variation.

© 2014 John Wiley & Sons Ltd. Aim: Species distribution models (SDM) can be used to predict the location of unknown populations from known species occurrences. It follows that how the data used to calibrate the models are collected can have a great impact on prediction success. We evaluated the influence of different survey designs and their interaction with the modelling technique on SDM performance. Location: Iberian Peninsula. Methods: We examine how data recorded using seven alternative survey designs (random, systematic, environmentally stratified by class and environmentally stratified using P-median, biased due to accessibility, biased by human density aggregation and biased towards protected areas) could affect SDM predictions generated with nine modelling techniques (BIOCLIM, Gower distance, Mahalanobis distance, Euclidean distance, GLM, MaxEnt, ENFA and Random Forest). We also study how sample size, species' characteristics and modelling technique affected SDM predictive ability, using six evaluation metrics. Results: Survey design has a small effect on prediction success. Characteristics of species' ranges rank highest among the factors affecting SDM results: the species with lower relative occurrence area (ROA) are predicted better. Model predictions are also improved when sample size is large. Main conclusions: The species modelled - particularly the extent of its distribution - are the largest source of influence over SDM results. The environmental coverage of the surveys is more important than the spatial structure of the calibration data. Therefore, climatic biases in the data should be identified to avoid erroneous conclusions about the geographic patterns of species distributions.

Aim: Climate change can lead to decreased climatic suitability within species' distributions, increased fragmentation of climatically suitable space, and/or emergence of newly suitable areas outside present distributions. Each of these extrinsic threats and opportunities potentially interacts with specific intrinsic traits of species, yet this specificity is seldom considered in risk assessments. We present an analytical framework for examining projections of climate change-induced threats and opportunities with reference to traits that are likely to mediate species' responses, and illustrate the applicability of the framework. Location: Sub-Saharan Africa. Methods: We applied the framework to 195 sub-Saharan African amphibians with both available bioclimatic envelope model projections for the mid-21st century and trait data. Excluded were 500 narrow-ranging species mainly from montane areas. For each of projected losses, increased fragmentation and gains of climate space, we selected potential response-mediating traits and examined the spatial overlap with vulnerability due to these traits. We examined the overlap for all species, and individually for groups of species with different combinations of threats and opportunities. Results: In the Congo Basin and arid Southern Africa, projected losses for wide-ranging amphibians were compounded by sensitivity to climatic variation, and expected gains were precluded by poor dispersal ability. The spatial overlap between exposure and vulnerability was more pronounced for species projected to have their climate space contracting in situ or shifting to distant geographical areas. Our results exclude the potential exposure of narrow-ranging species to shrinking climates in the African tropical mountains. Main conclusions: We illustrate the application of a framework combining spatial projections of climate change exposure with traits that are likely to mediate species' responses. Although the proposed framework carries severa

Climate change is altering phenology and distributions of many species and further changes are projected. Can species physiologically adapt to climate warming? We analyse thermal tolerances of a large number of terrestrial ectotherm (n = 697), endotherm (n = 227) and plant (n = 1816) species worldwide, and show that tolerance to heat is largely conserved across lineages, while tolerance to cold varies between and within species. This pattern, previously documented for ectotherms, is apparent for this group and for endotherms and plants, challenging the longstanding view that physiological tolerances of species change continuously across climatic gradients. An alternative view is proposed in which the thermal component of climatic niches would overlap across species more than expected. We argue that hard physiological boundaries exist that constrain evolution of tolerances of terrestrial organisms to high temperatures. In contrast, evolution of tolerances to cold should be more frequent. One consequence of conservatism of upper thermal tolerances is that estimated niches for cold-adapted species will tend to underestimate their upper thermal limits, thereby potentially inflating assessments of risk from climate change. In contrast, species whose climatic preferences are close to their upper thermal limits will unlikely evolve physiological tolerances to increased heat, thereby being predictably more affected by warming. © 2013 The Authors.

Ecological niche models (ENMs) are the primary tool used to describe and forecast the potential influence of climate change on biodiversity. However, ENMs do not directly account for important biological and landscape processes likely to affect range dynamics at a variety of spatial scales. Recent advances to link ENMs with population models have focused on the fundamental step of integrating dispersal and metapopulation dynamics into forecasts of species geographic ranges. Here we use a combination of novel analyses and a synthesis of findings from published plant and animal case studies to highlight three seldom recognised, yet important, advantages of linking ENMs with demographic modelling approaches: 1) they provide direct measures of extinction risk in addition to measures of vulnerability based on change in the potential range area or total habitat suitability. 2) They capture life-history traits that permit population density to vary in different ways in response to key spatial drivers, conditioned by the processes of global change. 3) They can be used to explore and rank the cost effectiveness of regional conservation alternatives and demographically oriented management interventions. Given these advantages, we argue that coupled methods should be used preferentially where data permits and when conservation management decisions require intervention, prioritization, or direct estimates of extinction risk. © 2013 The Author. Ecography © 2013 Nordic Society Oikos.

A topic of particular current interest is community-level approaches to species distribution modelling (SDM), i.e. approaches that simultaneously analyse distributional data for multiple species. Previous studies have looked at the advantages of community-level approaches for parameter estimation, but not for model selection - the process of choosing which model (and in particular, which subset of environmental variables) to fit to data. We compared the predictive performance of models using the same modelling method (generalised linear models) but choosing the subset of variables to include in the model either simultaneously across all species (community-level model selection) or separately for each species (species-specific model selection). Our results across two large presence/absence tree community datasets were inconclusive as to whether there was an overall difference in predictive performance between models fitted via species-specific vs community-level model selection. However, we found some evidence that a community approach was best suited to modelling rare species, and its performance decayed with increasing prevalence. That is, when data were sparse there was more opportunity for gains from >borrowing strength> across species via a community-level approach. Interestingly, we also found that the community-level approach tended to work better when the model selection problem was more difficult, and more reliably detected >noise> variables that should be excluded from the model. © 2013 The Authors.

The geographic distributions of plant species show marked correlations with the current climate, suggesting that they are likely to shift if climate changes. However, before projecting any such shifts, it is important to establish whether distributions are at equilibrium with the current climate. If they are not, distributional shifts could occur even without climate change, making it difficult to tease apart climate-induced shifts from shifts occurring naturally without climate change. We forecast the geographical distributions of the 10 most common trees occurring in the Iberian Peninsula using a new method that relaxes the species-climate equilibrium assumption implicit in most species distributions models. For each species, we developed a spatially explicit patch occupancy model (SPOM) with climate-dependent extinction rates and with colonization rates that depend on both climate and local seed dispersal. Bayesian methods were used to estimate the colonization, extinction and seed dispersal functions against observed colonization and extinction events recorded in repeat surveys of 46 596 forest plots in the Spanish Forest Inventories (1986-96 and 1997-2007). We then simulated distributional changes between the years 2000-2100. Without climate change, 9 of the 10 species substantially increased in regional frequency. These increases occurred primarily within current ranges, although some species also expanded across their range edges. With climate change, one temperate conifer species and two sub-Mediterranean species would reduce their frequency of occurrence across the studied region, whereas temperate broad-leaved species were unaffected and Mediterranean species were either unaffected or increased their frequency of occurrence. Synthesis. The analysis suggests that these species are substantially out of equilibrium, such that abundances and ranges would increase without climate change. Climate change may increase, decrease, stabilize or shift distributions, i

Climate change is predicted to have profound effects on freshwater organisms due to rising temperatures and altered precipitation regimes. Using an ensemble of bioclimatic envelope models (BEMs), we modelled the climatic suitability of 191 stream macroinvertebrate species from 12 orders across Europe under two climate change scenarios for 2080 on a spatial resolution of 5 arc minutes. Analyses included assessments of relative changes in species' climatically suitable areas as well as their potential shifts in latitude and longitude with respect to species' thermal preferences. Climate-change effects were also analysed regarding species' ecological and biological groupings, namely (1) endemicity and (2) rarity within European ecoregions, (3) life cycle, (4) stream zonation preference and (5) current preference. The BEMs projected that suitable climate conditions would persist in Europe in the year 2080 for nearly 99% of the modelled species regardless of the climate scenario. Nevertheless, a decrease in the amount of climatically suitable areas was projected for 57-59% of the species. Depending on the scenario, losses could be of 38-44% on average. The suitable areas for species were projected to shift, on average, 4.7-6.6° north and 3.9-5.4° east. Cold-adapted species were projected to lose climatically suitable areas, while gains were expected for warm-adapted species. When projections were analysed for different species groupings, only endemics stood out as a particular group. That is, endemics were projected to lose significantly larger amounts of suitable climatic areas than nonendemic species. Despite the uncertainties involved in modelling exercises such as this, the extent of projected distributional changes reveals further the vulnerability of freshwater organisms to climate change and implies a need to understand the consequences for ecological function and biodiversity conservation. © 2012 Blackwell Publishing Ltd.

Aim: Although the negative effects of habitat fragmentation have been widely documented at the landscape scale, much less is known about its impacts on species distributions at the biogeographical scale. We hypothesize that fragmentation influences the large-scale distribution of area- and edge-sensitive species by limiting their occurrence in regions with fragmented habitats, despite otherwise favourable environmental conditions. We test this hypothesis by assessing the interplay of climate and landscape factors influencing the distribution of the calandra lark, a grassland specialist that is highly sensitive to habitat fragmentation. Location: Iberia Peninsula, Europe. Methods: Ecological niche modelling was used to investigate the relative influence of climate/topography, landscape fragmentation and spatial structure on calandra lark distribution. Modelling assumed explicitly a hierarchically structured effect among explanatory variables, with climate/topography operating at broader spatial scales than landscape variables. An eigenvector-based spatial filtering approach was used to cancel bias introduced by spatial autocorrelation. The information theoretic approach was used in model selection, and variation partitioning was used to isolate the unique and shared effects of sets of explanatory variables. Results: Climate and topography were the most influential variables shaping the distribution of calandra lark, but incorporating landscape metrics contributed significantly to model improvement. The probability of calandra lark occurrence increased with total habitat area and declined with the number of patches and edge density. Variation partitioning showed a strong overlap between variation explained by climate/topography and landscape variables. After accounting for spatial structure in species distribution, the explanatory power of environmental variables remained largely unchanged. Main conclusions: We have shown here that landscape fragmentation can influenc

Species Temporal Turnover (STT) is one of the most familiar metrics to assess changes in assemblage composition as a consequence of climate change. However, STT mixes two components in one metric, changes in assemblage composition caused by a process of species loss or gain (i.e. the nestedness component) and changes in assemblage composition caused by a process of species replacement (i.e. the species replacement component). Drawing on previous studies investigating spatial patterns of beta diversity, we propose measures of STT that allow analysing each component (species replacement vs. nestedness), separately. We also present a mapping strategy to simultaneously visualize changes in species richness and assemblage composition. To illustrate our approach, we used the Mediterranean coastal fish fauna as a case study. Using Bioclimatic Envelope Models (BEMs) we first projected the potential future climatic niches of 288 coastal Mediterranean fish species based on a global warming scenario. We then aggregated geographically the species-level projections to analyse the projected changes in species richness and composition. Our results show that projected changes in assemblage composition are caused by different processes (species replacement vs. nestedness) in several areas of the Mediterranean Sea. In addition, our mapping strategy highlights that the coastal fish fauna in several regions of the Mediterranean Sea could experience a 'cul-de-sac' effect if exposed to climate warming. Overall, the joint exploration of changes in species richness and composition coupled with the distinction between species replacement and nestedness bears important information for understanding the nature of climate change impacts on biodiversity. These methodological advances should help decision-makers in prioritizing action in the areas facing the greatest vulnerability to climate. © 2012 Blackwell Publishing Ltd.

The species–area relationship is one of the strongest empirical generalizations in geographical ecology, yet controversy persists about some important questions concerning its causality and application. Here, using more accurate measures of island surface size for five different island systems, we show that increasing the accuracy of the estimation of area has negligible impact on the fit and form of the species–area relationship, even though our analyses included some of the most topographically diverse island groups in the world. In addition, we show that the inclusion of general measurements of environmental heterogeneity (in the form of the so-called choros model), can substantially improve the descriptive power of models of island species number. We suggest that quantification of other variables, apart from area, that are also critical for the establishment of biodiversity and at the same time have high explanatory power (such as island age, distance, productivity, energy, and environmental heterogeneity), is necessary if we are to build up a more predictive science of species richness variation across island systems.