Dynamic macroecology and the future for biodiversity

Reliable projections of climate‐change impacts on biodiversity are vital in formulating conservation and management strategies that best retain biodiversity into the future. While recent modelling has focussed largely on individual species, macroecology has the potential to add significant value to these efforts, by incorporating important community‐level constraints and processes. Here we show how a new dynamic macroecological approach can project climate‐change impacts collectively across all species in a diverse taxonomic group, overcoming shortfalls in our knowledge of biodiversity, while incorporating the key processes of dispersal and community assembly. Our approach applies a recently published technique (DynamicFOAM) to predict the present composition of every community, which form the initial conditions for a new metacommunity model (M‐SET) that projects changes in composition over time, under specified climate and habitat scenarios. Applying this approach at fine resolution to plant biodiversity in Tasmania (2,051 species; 1,157,587 communities), we project high average turnover in community composition from 2010 to 2100 (mean Sorensen's dissimilarity = 0.71 (±7.0 × 10^?5)), with major reductions in species richness (32.9 (±0.02) species lost per community) and no plant species benefitting from climate change in the long term. We also demonstrate how our modelling approach can identify habitat likely to be of high value for retaining rare and poorly reserved species under climate change. Our analyses highlight the potential value of this dynamic macroecological approach, that incorporates key ecological processes in projecting climate change impacts for all species simultaneously and uses simple macroecological inputs that can be derived even for highly diverse and poorly studied taxa.     

Forecasting fine‐scale changes in the food‐web structure of coastal marine communities under climate change

Climate change is inducing deep modifications in local communities worldwide as a consequence of individualistic species range shifts. Understanding how complex interaction networks will be reorganized under climate change represents a major challenge in the fields of ecology and biogeography. However, forecasting the potential effects of climate change on local communities, and more particularly on food‐web structure, requires the consideration of highly structuring processes, such as trophic interactions. A major breakthrough is therefore expected by combining predictive models integrating habitat selection processes, the physiological limits of marine species and their trophic interactions. In this study, we forecasted the potential impacts of climate change on the local food‐web structure of the highly threatened Gulf of Gabes ecosystem located in the south of the Mediterranean Sea. We coupled the climatic envelope and habitat models to an allometric niche food web model, hence taking into account the different processes acting at regional (climate) and local scales (habitat selection and trophic interactions). Our projections under the A2 climate change scenario showed that future food webs would be composed of smaller species with fewer links, resulting in a decrease of connectance, generality, vulnerability and mean trophic level of communities and an increase of the average path length, which may have large consequences on ecosystem functioning. The unified framework presented here, by connecting food‐web ecology, biogeography and seascape ecology, allows the exploration of spatial aspects of interspecific interactions under climate change and improves our current understanding of climate change impacts on local marine food webs.     

Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful?

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.     

Modelling the effects of climate change on the distribution and production of marine fishes: accounting for trophic interactions in a dynamic bioclimate envelope model

Climate change has already altered the distribution of marine fishes. Future predictions of fish distributions and catches based on bioclimate envelope models are available, but to date they have not considered interspecific interactions. We address this by combining the species‐based Dynamic Bioclimate Envelope Model (DBEM) with a size‐based trophic model. The new approach provides spatially and temporally resolved predictions of changes in species' size, abundance and catch potential that account for the effects of ecological interactions. Predicted latitudinal shifts are, on average, reduced by 20% when species interactions are incorporated, compared to DBEM predictions, with pelagic species showing the greatest reductions. Goodness‐of‐fit of biomass data from fish stock assessments in the North Atlantic between 1991 and 2003 is improved slightly by including species interactions. The differences between predictions from the two models may be relatively modest because, at the North Atlantic basin scale, (i) predators and competitors may respond to climate change together; (ii) existing parameterization of the DBEM might implicitly incorporate trophic interactions; and/or (iii) trophic interactions might not be the main driver of responses to climate. Future analyses using ecologically explicit models and data will improve understanding of the effects of inter‐specific interactions on responses to climate change, and better inform managers about plausible ecological and fishery consequences of a changing environment.     

An empirical test of the relative and combined effects of land‐cover and climate change on local colonization and extinction

Land‐cover and climate change are two main drivers of changes in species ranges. Yet, the majority of studies investigating the impacts of global change on biodiversity focus on one global change driver and usually use simulations to project biodiversity responses to future conditions. We conduct an empirical test of the relative and combined effects of land‐cover and climate change on species occurrence changes. Specifically, we examine whether observed local colonization and extinctions of North American birds between 1981–1985 and 2001–2005 are correlated with land‐cover and climate change and whether bird life history and ecological traits explain interspecific variation in observed occurrence changes. We fit logistic regression models to test the impact of physical land‐cover change, changes in net primary productivity, winter precipitation, mean summer temperature, and mean winter temperature on the probability of Ontario breeding bird local colonization and extinction. Models with climate change, land‐cover change, and the combination of these two drivers were the top ranked models of local colonization for 30%, 27%, and 29% of species, respectively. Conversely, models with climate change, land‐cover change, and the combination of these two drivers were the top ranked models of local extinction for 61%, 7%, and 9% of species, respectively. The quantitative impacts of land‐cover and climate change variables also vary among bird species. We then fit linear regression models to test whether the variation in regional colonization and extinction rate could be explained by mean body mass, migratory strategy, and habitat preference of birds. Overall, species traits were weakly correlated with heterogeneity in species occurrence changes. We provide empirical evidence showing that land‐cover change, climate change, and the combination of multiple global change drivers can differentially explain observed species local colonization and extinction.     

Forecasting the future of biodiversity: a test of single‐ and multi‐species models for ants in North America

The geographic distributions of many taxonomic groups remain mostly unknown, hindering attempts to investigate the response of the majority of species on Earth to climate change using species distributions models (SDMs). Multi‐species models can incorporate data for rare or poorly‐sampled species, but their application to forecasting climate change impacts on biodiversity has been limited. Here we compare forecasts of changes in patterns of ant biodiversity in North America derived from ensembles of single‐species models to those from a multi‐species modeling approach, Generalized Dissimilarity Modeling (GDM). We found that both single‐ and multi‐species models forecasted large changes in ant community composition in relatively warm environments. GDM predicted higher turnover than SDMs and across a larger contiguous area, including the southern third of North America and notably Central America, where the proportion of ants with relatively small ranges is high and where data limitations are most likely to impede the application of SDMs. Differences between approaches were also influenced by assumptions regarding dispersal, with forecasts being more similar if no‐dispersal was assumed. When full‐dispersal was assumed, SDMs predicted higher turnover in southern Canada than did GDM. Taken together, our results suggest that 1) warm rather than cold regions potentially could experience the greatest changes in ant fauna under climate change and that 2) multi‐species models may represent an important complement to SDMs, particularly in analyses involving large numbers of rare or poorly‐sampled species. Comparisons of the ability of single‐ and multi‐species models to predict observed changes in community composition are needed in order to draw definitive conclusions regarding their application to investigating climate change impacts on biodiversity.     

From climate change predictions to actions – conserving vulnerable animal groups in hotspots at a regional scale

Current climate change is a major threat to biodiversity. Species unable to adapt or move will face local or global extinction and this is more likely to happen to species with narrow climatic and habitat requirements and limited dispersal abilities, such as amphibians and reptiles. Biodiversity losses are likely to be greatest in global biodiversity hotspots where climate change is fast, such as the Iberian Peninsula. Here we assess the impact of climate change on 37 endemic and nearly endemic herptiles of the Iberian Peninsula by predicting species distributions for three different times into the future (2020, 2050 and 2080) using an ensemble of bioclimatic models and different combinations of species dispersal ability, emission levels and global circulation models. Our results show that species with Atlantic affinities that occur mainly in the North‐western Iberian Peninsula have severely reduced future distributions. Up to 13 species may lose their entire potential distribution by 2080. Furthermore, our analysis indicates that the most critical period for the majority of these species will be the next decade. While there is considerable variability between the scenarios, we believe that our results provide a robust relative evaluation of climate change impacts among different species. Future evaluation of the vulnerability of individual species to climate change should account for their adaptive capacity to climate change, including factors such as physiological climate tolerance, geographical range size, local abundance, life cycle, behavioural and phenological adaptability, evolutionary potential and dispersal ability.     

Climate warming moderates the impacts of introduced sportfish on multiple dimensions of prey biodiversity

Human‐assisted introductions of exotic species are a leading cause of anthropogenic change in biodiversity; however, context dependencies and interactions with co‐occurring stressors impede our ability to predict their ecological impacts. The legacy of historical sportfish stocking in mountainous regions of western North America creates a unique, natural quasiexperiment to investigate factors moderating invasion impacts on native communities across broad geographic and environmental gradients. Here we synthesize fish stocking records and zooplankton relative abundance for 685 mountain lakes and ponds in the Cascade and Canadian Rocky Mountain Ranges, to reveal the effects of predatory sportfish introduction on multiple taxonomic, functional and phylogenetic dimensions of prey biodiversity. We demonstrate an innovative analytical approach, combining exploratory random forest machine learning with confirmatory multigroup analysis using multivariate partial least‐squares structural equation models, to generate and test hypotheses concerning environmental moderation of stocking impacts. We discovered distinct effects of stocking across different dimensions of diversity, including negligible (nonsignificant) impacts on local taxonomic richness (i.e. alpha diversity) and trophic structure, in contrast to significant declines in compositional uniqueness (i.e. beta diversity) and body size. Furthermore, we found that stocking impacts were moderated by cross‐scale interactions with climate and climate‐related land‐cover variables (e.g. factors linked to treeline position and glaciers). Interactions with physical morphometric and lithological factors were generally of lesser importance, though catchment slope and habitat size constraints were relevant in certain dimensions. Finally, applying space‐for‐time substitution, a strong antagonistic (i.e. dampening) interaction between sportfish predation and warmer temperatures suggests redundancy of their size‐selective effects, meaning that warming will lessen the consequences of introductions in the future and stocked lakes may be less impacted by subsequent warming. While both stressors drive biotic homogenization, our results have important implications for fisheries managers weighing the costs/benefits of stocking—or removing established non‐native populations—under a rapidly changing climate.     

Drivers of future alien species impacts: An expert‐based assessment

Understanding the likely future impacts of biological invasions is crucial yet highly challenging given the multiple relevant environmental, socio‐economic and societal contexts and drivers. In the absence of quantitative models, methods based on expert knowledge are the best option for assessing future invasion trajectories. Here, we present an expert assessment of the drivers of potential alien species impacts under contrasting scenarios and socioecological contexts through the mid‐21st century. Based on responses from 36 experts in biological invasions, moderate (20%–30%) increases in invasions, compared to the current conditions, are expected to cause major impacts on biodiversity in most socioecological contexts. Three main drivers of biological invasions—transport, climate change and socio‐economic change—were predicted to significantly affect future impacts of alien species on biodiversity even under a best‐case scenario. Other drivers (e.g. human demography and migration in tropical and subtropical regions) were also of high importance in specific global contexts (e.g. for individual taxonomic groups or biomes). We show that some best‐case scenarios can substantially reduce potential future impacts of biological invasions. However, rapid and comprehensive actions are necessary to use this potential and achieve the goals of the Post‐2020 Framework of the Convention on Biological Diversity.     

A trait‐based approach for predicting species responses to environmental change from sparse data: how well might terrestrial mammals track climate change?

Estimating population spread rates across multiple species is vital for projecting biodiversity responses to climate change. A major challenge is to parameterise spread models for many species. We introduce an approach that addresses this challenge, coupling a trait‐based analysis with spatial population modelling to project spread rates for 15 000 virtual mammals with life histories that reflect those seen in the real world. Covariances among life‐history traits are estimated from an extensive terrestrial mammal data set using Bayesian inference. We elucidate the relative roles of different life‐history traits in driving modelled spread rates, demonstrating that any one alone will be a poor predictor. We also estimate that around 30% of mammal species have potential spread rates slower than the global mean velocity of climate change. This novel trait‐space‐demographic modelling approach has broad applicability for tackling many key ecological questions for which we have the models but are hindered by data availability.     

Projecting climate change impacts on species distributions in megadiverse South African Cape and Southwest Australian Floristic Regions: Opportunities and challenges

Increasing evidence shows that anthropogenic climate change is affecting biodiversity. Reducing or stabilizing greenhouse gas emissions may slow global warming, but past emissions will continue to contribute to further unavoidable warming for more than a century. With obvious signs of difficulties in achieving effective mitigation worldwide in the short term at least, sound scientific predictions of future impacts on biodiversity will be required to guide conservation planning and adaptation. This is especially true in Mediterranean type ecosystems that are projected to be among the most significantly affected by anthropogenic climate change, and show the highest levels of confidence in rainfall projections. Multiple methods are available for projecting the consequences of climate change on the main unit of interest – the species – with each method having strengths and weaknesses. Species distribution models (SDMs) are increasingly applied for forecasting climate change impacts on species geographic ranges. Aggregation of models for different species allows inferences of impacts on biodiversity, though excluding the effects of species interactions. The modelling approach is based on several further assumptions and projections and should be treated cautiously. In the absence of comparable approaches that address large numbers of species, SDMs remain valuable in estimating the vulnerability of species. In this review we discuss the application of SDMs in predicting the impacts of climate change on biodiversity with special reference to the species‐rich South West Australian Floristic Region and South African Cape Floristic Region. We discuss the advantages and challenges in applying SDMs in biodiverse regions with high levels of endemicity, and how a similar biogeographical history in both regions may assist us in understanding their vulnerability to climate change. We suggest how the process of predicting the impacts of climate change on biodiversity with SDMs can be improved and emphasize the role of field monitoring and experiments in validating the predictions of SDMs.     

Validation of species–climate impact models under climate change

Increasing concern over the implications of climate change for biodiversity has led to the use of species–climate envelope models to project species extinction risk under climate‐change scenarios. However, recent studies have demonstrated significant variability in model predictions and there remains a pressing need to validate models and to reduce uncertainties. Model validation is problematic as predictions are made for events that have not yet occurred. Resubstituition and data partitioning of present‐day data sets are, therefore, commonly used to test the predictive performance of models. However, these approaches suffer from the problems of spatial and temporal autocorrelation in the calibration and validation sets. Using observed distribution shifts among 116 British breeding‐bird species over the past ～20 years, we are able to provide a first independent validation of four envelope modelling techniques under climate change. Results showed good to fair predictive performance on independent validation, although rules used to assess model performance are difficult to interpret in a decision‐planning context. We also showed that measures of performance on nonindependent data provided optimistic estimates of models' predictive ability on independent data. Artificial neural networks and generalized additive models provided generally more accurate predictions of species range shifts than generalized linear models or classification tree analysis. Data for independent model validation and replication of this study are rare and we argue that perfect validation may not in fact be conceptually possible. We also note that usefulness of models is contingent on both the questions being asked and the techniques used. Implementations of species–climate envelope models for testing hypotheses and predicting future events may prove wrong, while being potentially useful if put into appropriate context.     

Uncertainty in assessing the impacts of global change with coupled dynamic species distribution and population models

Concern over rapid global changes and the potential for interactions among multiple threats are prompting scientists to combine multiple modelling approaches to understand impacts on biodiversity. A relatively recent development is the combination of species distribution models, land‐use change predictions, and dynamic population models to predict the relative and combined impacts of climate change, land‐use change, and altered disturbance regimes on species' extinction risk. Each modelling component introduces its own source of uncertainty through different parameters and assumptions, which, when combined, can result in compounded uncertainty that can have major implications for management. Although some uncertainty analyses have been conducted separately on various model components – such as climate predictions, species distribution models, land‐use change predictions, and population models – a unified sensitivity analysis comparing various sources of uncertainty in combined modelling approaches is needed to identify the most influential and problematic assumptions. We estimated the sensitivities of long‐run population predictions to different ecological assumptions and parameter settings for a rare and endangered annual plant species (Acanthomintha ilicifolia, or San Diego thornmint). Uncertainty about habitat suitability predictions, due to the choice of species distribution model, contributed most to variation in predictions about long‐run populations.     

Predicting impacts of climate change on biodiversity: a role for semi‐mechanistic community‐level modelling

Aim Robust and reliable predictions of the effects of climate change on biodiversity are required in formulating conservation and management strategies that best retain biodiversity into the future. Significant challenges in modelling climate change impacts arise from limitations in our current knowledge of biodiversity. Community‐level modelling can complement species‐level approaches in overcoming these limitations and predicting climate change impacts on biodiversity as a whole. However, the community‐level approaches applied to date have been largely correlative, ignoring the key processes that influence change in biodiversity over space and time. Here, we suggest that the development of new ‘semi‐mechanistic’ community‐level models would substantially increase our capacity to predict climate change impacts on biodiversity. Location Global. Methods Drawing on an expansive review of biodiversity modelling approaches and recent advances in semi‐mechanistic modelling at the species level, we outline the main elements of a new semi‐mechanistic community‐level modelling approach. Results Our quantitative review revealed a sharp divide between mechanistic and non‐mechanistic biodiversity modelling approaches, with very few semi‐mechanistic models developed to date. Main conclusions We suggest that the conceptual framework presented here for combining mechanistic and non‐mechanistic community‐level approaches offers a promising means of incorporating key processes into predictions of climate change impacts on biodiversity whilst working within the limits of our current knowledge.     

Individualistic species limitations of climate‐induced range expansions generated by meso‐scale dispersal barriers

Aim Evidence indicates that species are responding to climate change through distributional range shifts that track suitable climatic conditions. We aim to elucidate the role of meso‐scale dispersal barriers in climate‐tracking responses. Location South coast of England (the English Channel). Methods Historical distributional data of four intertidal invertebrate species were logistically regressed against sea surface temperature (SST) to determine a climate envelope. This envelope was used to estimate the expected climate‐tracking response since 1990 along the coast, which was compared with observed range expansions. A hydrodynamic modelling approach was used to identify dispersal barriers and explore disparities between expected and observed climate tracking. Results Range shifts detected by field survey over the past 20 years were less than those predicted by the changes that have occurred in SST. Hydrodynamic model simulations indicated that physical barriers produced by complex tidal currents have variably restricted dispersal of pelagic larvae amongst the four species. Main conclusions We provide the first evidence that meso‐scale hydrodynamic barriers have limited climate‐induced range shifts and demonstrate that life history traits affect the ability of species to overcome such barriers. This suggests that current forecasts may be flawed, both by overestimating range shifts and by underestimating climatic tolerances of species. This has implications for our understanding of climate change impacts on global biodiversity.     

Consequences of warming up a hotspot: species range shifts within a centre of bee diversity

Aim Bees are the most important pollinators of flowering plants and essential ecological keystone species contributing to the integrity of most terrestrial ecosystems. Here, we examine the potential impact of climate change on bees’ geographic range in a global biodiversity hotspot. Location South Africa with a focus on the Cape Floristic Region (CFR) diversity hotspot. Methods  Geographic ranges of 12 South African bee species representing dominant distribution types were studied, and the climate change impacts upon bees were examined with A2 and B2 climate scenarios of HadCM3 model, using MaxEnt for species distribution modelling. Results The predicted levels of climate change‐induced impacts on species ranges varied from little shifts and range expansion of 5–50% for two species to substantial range contractions between 32% and 99% in another six species. Four species show considerable range shifts. Bees of the winter rainfall area in the west of South Africa generally have smaller range sizes than in the summer rainfall area and generally show eastward range contractions toward the dry interior. Bee species prevalent in summer rainfall regions show a tendency for a south‐easterly shift in geographic range. Main conclusions The bee fauna of the CFR is identified as the most vulnerable to climate change due to the high level of endemism, the small range sizes and the island‐like isolation of the Mediterranean‐type climate region at the SW tip of Africa. For monitoring climate change impact on bees, we suggest to establish observatories in the coastal plains of the west coast that are predicted to be worst affected and areas where persistence of populations is most likely. Likely impacts of climate change on life history traits of bees (phenology, sociality, bee‐host plant synchronization) are discussed but require further investigation.     

Priority threat management of invasive animals to protect biodiversity under climate change

Climate change is a major threat to global biodiversity, and its impacts can act synergistically to heighten the severity of other threats. Most research on projecting species range shifts under climate change has not been translated to informing priority management strategies on the ground. We develop a prioritization framework to assess strategies for managing threats to biodiversity under climate change and apply it to the management of invasive animal species across one‐sixth of the Australian continent, the Lake Eyre Basin. We collected information from key stakeholders and experts on the impacts of invasive animals on 148 of the region's most threatened species and 11 potential strategies. Assisted by models of current distributions of threatened species and their projected distributions, experts estimated the cost, feasibility, and potential benefits of each strategy for improving the persistence of threatened species with and without climate change. We discover that the relative cost‐effectiveness of invasive animal control strategies is robust to climate change, with the management of feral pigs being the highest priority for conserving threatened species overall. Complementary sets of strategies to protect as many threatened species as possible under limited budgets change when climate change is considered, with additional strategies required to avoid impending extinctions from the region. Overall, we find that the ranking of strategies by cost‐effectiveness was relatively unaffected by including climate change into decision‐making, even though the benefits of the strategies were lower. Future climate conditions and impacts on range shifts become most important to consider when designing comprehensive management plans for the control of invasive animals under limited budgets to maximize the number of threatened species that can be protected.     

气候变化与生物多样性之间的复杂关系和反馈机制

气候变化与生物多样性丧失是人类社会正在经历的两大变化。气候变化影响生物多样性的方方面面, 是导致生物多样性丧失的一个主要驱动因子; 反过来, 生物多样性丧失会加剧气候变化。因此, 阻止甚至扭转气候变化和生物多样性丧失是当前人类社会亟需解决的全球性问题,但我们对气候变化与生物多样性之间的复杂关系和反馈机制尚缺乏清晰认识。本文总结了近年气候变化与生物多样性变化的研究进展, 重点概述了不同组织层次、空间尺度和维度的生物多样性对气候变化的响应和反馈等相关领域的研究进展和存在的主要问题。结果发现多数研究关注气候变化对生物多样性的直接影响, 涉及到生物多样性的不同组织层次、维度和营养级, 但针对气候变化间接影响的研究仍然较少, 机理研究同样需要加强; 生物多样性对生态系统功能影响的环境依赖和尺度推演、生物多样性对生态系统多功能性的作用机理和量化方法是当前研究面临的挑战; 生物多样性对生态系统响应气候变化的作用机制尚无统一的认识; 生物多样性对气候变化的正、负反馈效应是国内外研究的盲点。最后, 本文展望了未来发展方向和需要解决的关键科学问题, 包括多因子气候变化对生物多样性的影响; 减缓和适应气候变化的措施如何惠益于生物多样性保护; 生物多样性与生态系统功能的理论如何应用到现实世界; 生物多样性保护对实现碳中和目标的贡献。     

Exploring consensus in 21st century projections of climatically suitable areas for African vertebrates

Africa is predicted to be highly vulnerable to 21st century climatic changes. Assessing the impacts of these changes on Africa's biodiversity is, however, plagued by uncertainties, and markedly different results can be obtained from alternative bioclimatic envelope models or future climate projections. Using an ensemble forecasting framework, we examine projections of future shifts in climatic suitability, and their methodological uncertainties, for over 2500 species of mammals, birds, amphibians and snakes in sub‐Saharan Africa. To summarize a priori the variability in the ensemble of 17 general circulation models, we introduce a consensus methodology that combines co‐varying models. Thus, we quantify and map the relative contribution to uncertainty of seven bioclimatic envelope models, three multi‐model climate projections and three emissions scenarios, and explore the resulting variability in species turnover estimates. We show that bioclimatic envelope models contribute most to variability, particularly in projected novel climatic conditions over Sahelian and southern Saharan Africa. To summarize agreements among projections from the bioclimatic envelope models we compare five consensus methodologies, which generally increase or retain projection accuracy and provide consistent estimates of species turnover. Variability from emissions scenarios increases towards late‐century and affects southern regions of high species turnover centred in arid Namibia. Twofold differences in median species turnover across the study area emerge among alternative climate projections and emissions scenarios. Our ensemble of projections underscores the potential bias when using a single algorithm or climate projection for Africa, and provides a cautious first approximation of the potential exposure of sub‐Saharan African vertebrates to climatic changes. The future use and further development of bioclimatic envelope modelling will hinge on the interpretation of results in the light of methodological as well as biological uncertainties. Here, we provide a framework to address methodological uncertainties and contextualize results.     

Traits explain community disassembly and trophic contraction following experimental environmental change

Many ecosystems are currently undergoing dramatic changes in biodiversity due to habitat loss and climate change. Responses to global change at the community level are poorly understood, as are the impacts of community disassembly on ecosystem‐level processes. Uncertainties remain regarding the patterns of extirpation and persistence under single vs. multiple forms of environmental change. Here, we use a trait‐based and food web approach to examine the effects of experimentally changing moisture, temperature and habitat ‘openness’ on a functionally important group of microarthropods associated with a boreal forest floor bryosphere (detrital moss) system. Overall, the outcome of community disassembly was mediated by the correlation between our environmental factors and species traits, particularly body size. Minor increases in summer temperatures maintained greater species richness, whereas drought stress had a significant negative effect on community‐level abundance and richness. These effects were reflected in modifications to the community‐wide body‐size spectra. Habitat openness alleviated biodiversity loss in the larger‐bodied species of the most abundant taxonomic group, but did not fully mitigate the effects of drought. The most striking result of this experiment was an overall contraction of the food web among persistent species under drought stress (i.e. those not extirpated by environmental change). These results suggest that major changes in boreal microarthropod community structure are likely to occur in response to common forms of global change. Moreover, the contraction in trophic structure even amongst tolerant species suggests that ecosystem function within the bryosphere can be altered by environmental change.