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.     

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.     

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.     

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.     

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.