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This study shows that climate change could lead to a major redistribution of vegetation across the Arctic, with important implications for biosphere–atmosphere interactions, as well as for biodiversity conservation and ecosystem services. Woody vegetation is predicted to expand substantially over coming decades, causing more Arctic warming through positive climate feedbacks than previously thought. Climate warming has led to changes in the composition, density and distribution of Arctic vegetation in recent decades 1 , 2 , 3 , 4 . These changes cause multiple opposing feedbacks between the biosphere and atmosphere 5 , 6 , 7 , 8 , 9 , the relative magnitudes of which will have globally significant consequences but are unknown at a pan-Arctic scale 10 . The precise nature of Arctic vegetation change under future warming will strongly influence climate feedbacks, yet Earth system modelling studies have so far assumed arbitrary increases in shrubs (for example, +20%; refs  6 , 11 ), highlighting the need for predictions of future vegetation distribution shifts. Here we show, using climate scenarios for the 2050s and models that utilize statistical associations between vegetation and climate, the potential for extremely widespread redistribution of vegetation across the Arctic. We predict that at least half of vegetated areas will shift to a different physiognomic class, and woody cover will increase by as much as 52%. By incorporating observed relationships between vegetation and albedo, evapotranspiration and biomass, we show that vegetation distribution shifts will result in an overall positive feedback to climate that is likely to cause greater warming than has previously been predicted. Such extensive changes to Arctic vegetation will have implications for climate, wildlife and ecosystem services.

Climate change could be a game-changer for biodiversity conservation, potentially invalidating many established methods including those employed in vulnerability assessments. Now, a simulation study finds that extinction risk due to climate change can be predicted using measurable spatial and demographic variables. Interestingly, most of those variables identified as important are already used in species conservation assessment. There is an urgent need to develop effective vulnerability assessments for evaluating the conservation status of species in a changing climate 1 . Several new assessment approaches have been proposed for evaluating the vulnerability of species to climate change 2 , 3 , 4 , 5 based on the expectation that established assessments such as the IUCN Red List 6 need revising or superseding in light of the threat that climate change brings. However, although previous studies have identified ecological and life history attributes that characterize declining species or those listed as threatened 7 , 8 , 9 , no study so far has undertaken a quantitative analysis of the attributes that cause species to be at high risk of extinction specifically due to climate change. We developed a simulation approach based on generic life history types to show here that extinction risk due to climate change can be predicted using a mixture of spatial and demographic variables that can be measured in the present day without the need for complex forecasting models. Most of the variables we found to be important for predicting extinction risk, including occupied area and population size, are already used in species conservation assessments, indicating that present systems may be better able to identify species vulnerable to climate change than previously thought. Therefore, although climate change brings many new conservation challenges, we find that it may not be fundamentally different from other threats in terms of assessing extinction risks.

Animal‐mediated pollination is a key ecosystem service required to some extent by almost three‐quarters of the leading human food crops in global food production. Anthropogenic pressures such as habitat loss and land‐use intensification are causing shifts in ecological community composition, potentially resulting in declines in pollination services and impacting crop production. Previous research has often overlooked interspecific differences in pollination contribution, yet such differences mean that biodiversity declines will not necessarily negatively impact pollination. Here, we use a novel species‐level ecosystem service contribution matrix along with mixed‐effects models to explore how groups of terrestrial species who contribute differently to crop pollination respond globally to land‐use type, land‐use intensity, and availability of natural habitats in the surrounding landscape. We find that the species whose contribution to crop pollination is higher generally respond less negatively (and in some cases positively) to human disturbance of land, compared to species that contribute less or not at all to pollination. This result may be due to these high‐contribution species being less sensitive to anthropogenic land conversions, which has led humans to being more reliant on them for crop pollination. However, it also suggests that there is potential for crop pollination to be resilient in the face of anthropogenic land conversions. With such a high proportion of food crops requiring animal‐mediated pollination to some extent, understanding how anthropogenic landscapes impact ecological communities and the consequences for pollination is critical for ensuring food security. With a high proportion of crops requiring animal‐mediated pollination to some extent, understanding how anthropogenic landscapes impact communities and pollination provision is critical for ensuring food security. We find that the species most important for crop pollination are responding less negatively (and sometimes positively) to human disturbance of land compared to other animals. This suggests there is potential for crop pollination to be resilient in the face of anthropogenic land conversions.

Modelling strategies for predicting the potential impacts of climate change on the natural distribution of species have often focused on the characterization of a species' bioclimate envelope. A number of recent critiques have questioned the validity of this approach by pointing to the many factors other than climate that play an important part in determining species distributions and the dynamics of distribution changes. Such factors include biotic interactions, evolutionary change and dispersal ability. This paper reviews and evaluates criticisms of bioclimate envelope models and discusses the implications of these criticisms for the different modelling strategies employed. It is proposed that, although the complexity of the natural system presents fundamental limits to predictive modelling, the bioclimate envelope approach can provide a useful first approximation as to the potentially dramatic impact of climate change on biodiversity. However, it is stressed that the spatial scale at which these models are applied is of fundamental importance, and that model results should not be interpreted without due consideration of the limitations involved. A hierarchical modelling framework is proposed through which some of these limitations can be addressed within a broader, scale-dependent context.

Although the systematic utility of ecological niche modeling is generally well known (e.g., concerning the recognition and discovery of areas of endemism for biogeographic analyses), there has been little discussion of applications concerning species delimitation, and to date, no empirical evaluation has been conducted. However, ecological niche modeling can provide compelling evidence for allopatry between populations, and can also detect divergent ecological niches between candidate species. Here we present results for two taxonomically problematic groups of Phelsuma day geckos from Madagascar, where we integrate ecological niche modeling with mitochondrial DNA and morphological data to evaluate species limits. Despite relatively modest levels of genetic and morphological divergence, for both species groups we find divergent ecological niches between closely related species and parapatric ecological niche models. Niche models based on the new species limits provide a better fit to the known distribution than models based upon the combined (lumped) species limits. Based on these results, we elevate three subspecies of Phelsuma madagascariensis to species rank and describe a new species of Phelsuma from the P. dubia species group. Our phylogeny continues to support a major endemic radiation of Phelsuma in Madagascar, with dispersals to Pemba Island and the Mascarene Islands. We conclude that ecological niche modeling offers great potential for species delimitation, especially for taxonomic groups exhibiting low vagility and localized endemism and for groups with more poorly known distributions. In particular, niche modeling should be especially sensitive for detecting recent parapatric speciation driven by ecological divergence, when the environmental gradients driving speciation are represented within the ecological niche models.

Transforming the results of species distribution modelling from probabilities of or suitabilities for species occurrence to presences/absences needs a specific threshold. Even though there are many approaches to determining thresholds, there is no comparative study. In this paper, twelve approaches were compared using two species in Europe and artificial neural networks, and the modelling results were assessed using four indices: sensitivity, specificity, overall prediction success and Cohen's kappa statistic. The results show that prevalence approach, average predicted probability/suitability approach, and three sensitivity-specificity-combined approaches, including sensitivity-specificity sum maximization approach, sensitivity-specificity equality approach and the approach based on the shortest distance to the top-left corner (0,1) in ROC plot, are the good ones. The commonly used kappa maximization approach is not as good as the afore-mentioned ones, and the fixed threshold approach is the worst one. We also recommend using datasets with prevalence of 50% to build models if possible since most optimization criteria might be satisfied or nearly satisfied at the same time, and therefore it's easier to find optimal thresholds in this situation.

This book provides a first synthetic view of an emerging area of ecology and biogeography, linking individual- and population-level processes to geographic distributions and biodiversity patterns. Problems in evolutionary ecology, macroecology, and biogeography are illuminated by this integrative view. The book focuses on correlative approaches known as ecological niche modeling, species distribution modeling, or habitat suitability modeling, which use associations between known occurrences of species and environmental variables to identify environmental conditions under which populations can be maintained. The spatial distribution of environments suitable for the species can then be estimated: a potential distribution for the species. This approach has broad applicability to ecology, evolution, biogeography, and conservation biology, as well as to understanding the geographic potential of invasive species and infectious diseases, and the biological implications of climate change. The authors lay out conceptual foundations and general principles for understanding and interpreting species distributions with respect to geography and environment. Focus is on development of niche models. While serving as a guide for students and researchers, the book also provides a theoretical framework to support future progress in the field.

The loss of species is known to have significant effects on ecosystem functioning, but only recently has it been recognized that species loss might rival the effects of other forms of environmental change on ecosystem processes. There is a need for experimental studies that explicitly manipulate species richness and environmental factors concurrently to determine their relative impacts on key ecosystem processes such as plant litter decomposition. It is crucial to understand what factors affect the rate of plant litter decomposition and the relative magnitude of such effects because the rate at which plant litter is lost and transformed to other forms of organic and inorganic carbon determines the capacity for carbon storage in ecosystems and the rate at which greenhouse gasses such as carbon dioxide are outgassed. Here we compared how an increase in water temperature of 5°C and loss of detritivorous invertebrate and plant litter species affect decomposition rates in a laboratory experiment simulating stream conditions. Like some prior studies, we found that species identity, rather than species richness per se, is a key driver of decomposition, but additionally we showed that the loss of particular species can equal or exceed temperature change in its impact on decomposition. Our results indicate that the loss of particular species can be as important a driver of decomposition as substantial temperature change, but also that predicting the relative consequences of species loss and other forms of environmental change on decomposition requires knowledge of assemblages and their constituent species' ecology and ecophysiology.

We analyzed basal sources, trophic levels, and connectance in dry-season food webs on 4 rivers in the upper Burdekin catchment in the dry tropics of northeastern Australia. The region is characterized by episodic summer rainfall, and most of the annual river flow occurs in a short period. In the dry season, rivers typically contract into a series of water holes of varying permanence and hydrologic connectivity. We used stable-isotope and stomach-content analyses to identify trophic levels of macroinvertebrates and fish, and we used a mixing model (SIAR) to identify foodweb basal sources at each site. We found substantial variability among sites in basal-source contributions, trophic position of individual taxa, and foodweb structure, and sites from the same river often were as different as sites from different rivers. Important basal sources at different sites included allochthonous tree litter, autochthonous algae and macrophytes, and Fe-fixing bacteria. Many relationships between consumers and basal sources were not resolved in the mixing model, mainly because of extensive omnivory or isotopic overlap among sources. Nevertheless, our results show high variability of dry-tropics river communities that extends beyond previously described macroinvertebrate assemblages to the broader food web. However, the main components of the upper trophic levels were similar across sites, such that different lower trophic levels supported similar assemblages of top consumers. These tropical rivers were defined by omnivory and ecological opportunism, which may be adaptations to seasonal hydrological variability.

Background: Clinical studies of osteoarthritis (OA) suggest central sensitization may contribute to the chronic pain experienced. This preclinical study used the monosodium iodoacetate (MIA) model of OA joint pain to investigate the potential contribution of spinal sensitization, in particular spinal glial cell activation, to pain behaviour in this model. Experimental OA was induced in the rat by the intra-articular injection of MIA and pain behaviour (change in weight bearing and distal allodynia) was assessed. Spinal cord microglia (Iba1 staining) and astrocyte (GFAP immunofluorescence) activation were measured at 7, 14 and 28 days post MIA-treatment. The effects of two known inhibitors of glial activation, nimesulide and minocycline, on pain behaviour and activation of microglia and astrocytes were assessed. Results: Seven days following intra-articular injection of MIA, microglia in the ipsilateral spinal cord were activated (p < 0. 05, compared to contralateral levels and compared to saline controls). Levels of activated microglia were significantly elevated at day 14 and 21 post MIA-injection. At day 28, microglia activation was significantly correlated with distal allodynia (p < 0.05). Ipsilateral spinal GFAP immunofluorescence was significantly (p < 0.01) increased at day 28, but not at earlier timepoints, in the MIA model, compared to saline controls. Repeated oral dosing (days 14-20) with nimesulide attenuated pain behaviour and the activation of microglia in the ipsilateral spinal cord at day 21. This dosing regimen also significantly attenuated distal allodynia (p < 0.001) and numbers of activated microglia (p < 0.05) and GFAP immunofluorescence (p < 0.001) one week later in MIA-treated rats, compared to vehicle-treated rats. Repeated administration of minocycline also significantly attenuated pain behaviour and reduced the number of activated microglia and decreased GFAP immunofluorescence in ipsilateral spinal cord of MIA treated rats. Conclusions: Here we provide evidence for a contribution of spinal glial cells to pain behaviour, in particular distal allodynia, in this model of osteoarthritic pain. Our data suggest there is a potential role of glial cells in the central sensitization associated with OA, which may provide a novel analgesic target for the treatment of OA pain.