Predicting current and future global distributions of whale sharks

The Vulnerable (IUCN) whale shark spans warm and temperate waters around the globe. However, their present‐day and possible future global distribution has never been predicted. Using 30 years (1980–2010) of whale shark observations recorded by tuna purse‐seiners fishing in the Atlantic, Indian and Pacific Oceans, we applied generalized linear mixed‐effects models to test the hypothesis that similar environmental covariates predict whale shark occurrence in all major ocean basins. We derived global predictors from satellite images for chlorophyll a and sea surface temperature, and bathymetric charts for depth, bottom slope and distance to shore. We randomly generated pseudo‐absences within the area covered by the fisheries, and included fishing effort as an offset to account for potential sampling bias. We predicted sea surface temperatures for 2070 using an ensemble of five global circulation models under a no climate‐policy reference scenario, and used these to predict changes in distribution. The full model (excluding standard deviation of sea surface temperature) had the highest relative statistical support (wAIC_c = 0.99) and explained ca. 60% of the deviance. Habitat suitability was mainly driven by spatial variation in bathymetry and sea surface temperature among oceans, although these effects differed slightly among oceans. Predicted changes in sea surface temperature resulted in a slight shift of suitable habitat towards the poles in both the Atlantic and Indian Oceans (ca. 5°N and 3–8°S, respectively) accompanied by an overall range contraction (2.5–7.4% and 1.1–6.3%, respectively). Predicted changes in the Pacific Ocean were small. Assuming that whale shark environmental requirements and human disturbances (i.e. no stabilization of greenhouse gas emissions) remain similar, we show that warming sea surface temperatures might promote a net retreat from current aggregation areas and an overall redistribution of the species.     

Predicting the distributions of Pouteria adolfi-friederici and Prunus africana tree species under current and future climate change scenarios in Ethiopia

Distributions of potential ranges of plant species are not yet fully known in Ethiopia where high climatic variability and vegetation types are found. This study was undertaken to predict distributions of suitable habitats of Pouteria adolfi-friederici and Prunus africana under current and two future climate scenarios (RCP 4.5 and RCP 8.5 in 2050 and 2070) in Ethiopia. Eleven environmental variables with less correlation coefficients (r < 0.7) were used to make the prediction. Shifting in extents of habitat suitability and effects of elevation, solar radiation and topographic position in relation to the current and future climatic scenarios were statistically analysed using independent t-test and linear model. We found decreasing area of highly suitable habitat from 0.51% to 0.46%, 0.36% and 0.33%, 0.24% for Prunus africana and 1.13% to 1.02%, 0.77% and 0.76%, 0.60% for Pouteria adolfi-friederici, under RCP 4.5 and RCP 8.5 by 2050 and 2070 respectively. Moist and dry afromontane forests are identified as the most suitable habitat for both species. Overall, our results suggest that climate change can promote dynamic suitable habitat niches under different future climate scenarios. Therefore, biodiversity conservation strategies should take into account habitat suitability dynamics issues and identify where to conserve species before implementing conservation practices.     

Warming and provenance limit tree recruitment across and beyond the elevation range of subalpine forest

Climate niche models project that subalpine forest ranges will extend upslope with climate warming. These projections assume that the climate suitable for adult trees will be adequate for forest regeneration, ignoring climate requirements for seedling recruitment, a potential demographic bottleneck. Moreover, local genetic adaptation is expected to facilitate range expansion, with tree populations at the upper forest edge providing the seed best adapted to the alpine. Here, we test these expectations using a novel combination of common gardens, seeded with two widely distributed subalpine conifers, and climate manipulations replicated at three elevations. Infrared heaters raised temperatures in heated plots, but raised temperatures more in the forest than at or above treeline because strong winds at high elevation reduced heating efficiency. Watering increased season‐average soil moisture similarly across sites. Contrary to expectations, warming reduced Engelmann spruce recruitment at and above treeline, as well as in the forest. Warming reduced limber pine first‐year recruitment in the forest, but had no net effect on fourth‐year recruitment at any site. Watering during the snow‐free season alleviated some negative effects of warming, indicating that warming exacerbated water limitations. Contrary to expectations of local adaptation, low‐elevation seeds of both species initially recruited more strongly than high‐elevation seeds across the elevation gradient, although the low‐provenance advantage diminished by the fourth year for Engelmann spruce, likely due to small sample sizes. High‐ and low‐elevation provenances responded similarly to warming across sites for Engelmann spruce, but differently for limber pine. In the context of increasing tree mortality, lower recruitment at all elevations with warming, combined with lower quality, high‐provenance seed being most available for colonizing the alpine, portends range contraction for Engelmann spruce. The lower sensitivity of limber pine to warming indicates a potential for this species to become more important in subalpine forest communities in the coming centuries.     

Mechanistic variables can enhance predictive models of endotherm distributions: the American pika under current,past, and future climates

How climate constrains species’ distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat‐balance model, to convert macroclimate data to pika‐specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8–19% less habitat loss in response to annual temperature increases of ~3–5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect: climate‐imposed restrictions on activity. This more complete understanding is necessary to inform climate adaptation actions, management strategies, and conservation plans.     

Mutualism influences species distribution predictions for a bromeliad‐breeding anuran under climate change

Ecological niche models, or species distribution models, have been widely used to identify potentially suitable areas for species in future climate change scenarios. However, there are inherent errors to these models due to their inability to evaluate species occurrence influenced by non‐climatic factors. With the intuit to improve the modelling predictions for a bromeliad‐breeding treefrog (Phyllodytes melanomystax, Hylidae), we investigate how the climatic suitability of bromeliads influences the distribution model for the treefrog in the context of baseline and 2050 climate change scenarios. We used point occurrence data on the frog and the bromeliad (Vriesea procera, Bromeliaceae) to generate their predicted distributions based on baseline and 2050 climates. Using a consensus of five algorithms, we compared the accuracy of the models and the geographic predictions for the frog generated from two modelling procedures: (i) a climate‐only model for P. melanomystax and V. procera; and (ii) a climate‐biotic model for P. melanomystax, in which the climatic suitability of the bromeliad was jointly considered with the climatic variables. Both modelling approaches generated strong and similar predictive power for P. melanomystax, yet climate‐biotic modelling generated more concise predictions, particularly for the year 2050. Specifically, because the predicted area of the bromeliad overlaps with the predictions for the treefrog in the baseline climate, both modelling approaches produce reasonable similar predicted areas for the anuran. Alternatively, due to the predicted loss of northern climatically suitable areas for the bromeliad by 2050, only the climate‐biotic models provide evidence that northern populations of P. melanomystax will likely be negatively affected by 2050.     

Biotic interactions influence the projected distribution of a specialist mammal under climate change

Aim

To measure the effects of including biotic interactions on climate‐based species distribution models (SDMs) used to predict distribution shifts under climate change. We evaluated the performance of distribution models for an endangered marsupial, the northern bettong (Bettongia tropica), comparing models that used only climate variables with models that also took into account biotic interactions.

Location

North‐east Queensland, Australia.

Methods

We developed separate climate‐based distribution models for the northern bettong, its two main resources and a competitor species. We then constructed models for the northern bettong by including climate suitability estimates for the resources and competitor as additional predictor variables to make climate + resource and climate + resource + competition models. We projected these models onto seven future climate scenarios and compared predictions of northern bettong distribution made by these differently structured models, using a ‘global’ metric, the I similarity statistic, to measure overlap in distribution and a ‘local’ metric to identify where predictions differed significantly.

Results

Inclusion of food resource biotic interactions improved model performance. Over moderate climate changes, up to 3.0 °C of warming, the climate‐only model for the northern bettong gave similar predictions of distribution to the more complex models including interactions, with differences only at the margins of predicted distributions. For climate changes beyond 3.0 °C, model predictions diverged significantly. The interactive model predicted less contraction of distribution than the simpler climate‐only model.

Main conclusions

Distribution models that account for interactions with other species, in particular direct resources, improve model predictions in the present‐day climate. For larger climate changes, shifts in distribution of interacting species cause predictions of interactive models to diverge from climate‐only models. Incorporating interactions with other species in SDMs may be needed for long‐term prediction of changes in distribution of species under climate change, particularly for specialized species strongly dependent on a small number of biotic interactions.     

Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks

Macroecological models for predicting species distributions usually only include abiotic environmental conditions as explanatory variables, despite knowledge from community ecology that all species are linked to other species through biotic interactions. This disconnect is largely due to the different spatial scales considered by the two sub‐disciplines: macroecologists study patterns at large extents and coarse resolutions, while community ecologists focus on small extents and fine resolutions. A general framework for including biotic interactions in macroecological models would help bridge this divide, as it would allow for rigorous testing of the role that biotic interactions play in determining species ranges. Here, we present an approach that combines species distribution models with Bayesian networks, which enables the direct and indirect effects of biotic interactions to be modelled as propagating conditional dependencies among species’ presences. We show that including biotic interactions in distribution models for species from a California grassland community results in better range predictions across the western USA. This new approach will be important for improving estimates of species distributions and their dynamics under environmental change.     

Climate change and the future restructuring of Neotropical anuran biodiversity

Climate change is likely to impact multiple dimensions of biodiversity. Species range shifts are expected and may drive changes in the composition of species assemblages. In some regions, changes in climate may precipitate the loss of geographically restricted, niche specialists and facilitate their replacement by more widespread, niche generalists, leading to decreases in β-diversity and biotic homogenization. However, in other regions climate change may drive local extinctions and range contraction, leading to increases in β-diversity and biotic heterogenization. Regional topography should be a strong determinant of such changes as mountainous areas often are home to many geographically restricted species, whereas lowlands and plains are more often inhabited by widespread generalists. Climate warming, therefore, may simultaneously bring about opposite trends in β-diversity in mountainous highlands versus relatively flat lowlands. To test this hypothesis, we used species distribution modelling to map the present-day distributions of 2669 Neotropical anuran species, and then generated projections of their future distributions assuming future climate change scenarios. Using traditional metrics of β-diversity, we mapped shifts in biotic homogenization across the entire Neotropical region. We used generalized additive models to then evaluate how changes in β-diversity were associated with shifts in species richness, phylogenetic diversity and one measure of ecological generalism. Consistent with our hypothesis, we find increasing biotic homogenization in most highlands, associated with increased numbers of generalists and, to a lesser extent, losses of specialists, leading to an overall increase in alpha diversity, but lower mean phylogenetic diversity. In the lowlands, biotic heterogenization was more common, and primarily driven by local extinctions of generalists, leading to lower α-diversity, but higher mean phylogenetic diversity. Our results suggest that impacts of climate change on β-diversity are likely to vary regionally, but will generally lead to lower diversity, with increases in β-diversity offset by decreases in α-diversity.     

Tackling intraspecific genetic structure in distribution models better reflects species geographical range

Genetic diversity provides insight into heterogeneous demographic and adaptive history across organisms’ distribution ranges. For this reason, decomposing single species into genetic units may represent a powerful tool to better understand biogeographical patterns as well as improve predictions of the effects of GCC (global climate change) on biodiversity loss. Using 279 georeferenced Iberian accessions, we used classes of three intraspecific genetic units of the annual plant Arabidopsis thaliana obtained from the genetic analyses of nuclear SNPs (single nucleotide polymorphisms), chloroplast SNPs, and the vernalization requirement for flowering. We used SDM (species distribution models), including climate, vegetation, and soil data, at the whole‐species and genetic‐unit levels. We compared model outputs for present environmental conditions and with a particularly severe GCC scenario. SDM accuracy was high for genetic units with smaller distribution ranges. Kernel density plots identified the environmental variables underpinning potential distribution ranges of genetic units. Combinations of environmental variables accounted for potential distribution ranges of genetic units, which shrank dramatically with GCC at almost all levels. Only two genetic clusters increased their potential distribution ranges with GCC. The application of SDM to intraspecific genetic units provides a detailed picture on the biogeographical patterns of distinct genetic groups based on different genetic criteria. Our approach also allowed us to pinpoint the genetic changes, in terms of genetic background and physiological requirements for flowering, that Iberian A. thaliana may experience with a GCC scenario applying SDM to intraspecific genetic units.     

Upward elevation and northwest range shifts for alpine Meconopsis species in the Himalaya–Hengduan Mountains region

Climate change may impact the distribution of species by shifting their ranges to higher elevations or higher latitudes. The impacts on alpine plant species may be particularly profound due to a potential lack of availability of future suitable habitat. To identify how alpine species have responded to climate change during the past century as well as to predict how they may react to possible global climate change scenarios in the future, we investigate the climatic responses of seven species of Meconopsis, a representative genus endemic in the alpine meadow and subnival region of the Himalaya–Hengduan Mountains. We analyzed past elevational shifts, as well as projected shifts in longitude, latitude, elevation, and range size using historical specimen records and species distribution modeling under optimistic (RCP 4.5) and pessimistic (RCP 8.5) scenarios across three general circulation models for 2070. Our results indicate that across all seven species, there has been an upward shift in mean elevation of 302.3 m between the pre‐1970s (1922–1969) and the post‐1970s (1970–2016). The model predictions suggest that the future suitable climate space will continue to shift upwards in elevation (as well as northwards and westwards) by 2070. While for most of the analyzed species, the area of suitable climate space is predicted to expand under the optimistic emission scenario, the area contracts, or, at best, shows little change under the pessimistic scenario. Species such as M. punicea, which already occupy high latitudes, are consistently predicted to experience a contraction of suitable climate space across all the models by 2070 and may consequently deserve particular attention by conservation strategies. Collectively, our results suggest that the alpine high‐latitude species analyzed here have already been significantly impacted by climate change and that these trends may continue over the coming decades.     

Climate and host plant availability impact the future distribution of the bean leaf beetle (Cerotoma trifurcata)

The bean leaf beetle, Cerotoma trifurcata, has become a major pest of soybean throughout its North American range. With a changing climate, there is the potential for this pest to further expand its distribution and become an increasingly severe pest in certain regions. To examine this possibility, we developed bioclimatic envelope models for both the bean leaf beetle, and its most important agronomic host plant, soybean (Glycine max). These two models were combined to examine the potential future pest status of the beetle using climate change projections from multiple general circulation models (GCMs) and climate change scenarios. Despite the broad tolerances of soybean, incorporation of host plant availability substantially decreased the suitable and favourable areas for the bean leaf beetle as compared to an evaluation based solely on the climate envelope of the beetle, demonstrating the importance of incorporating biotic interactions in these predictions. The use of multiple GCM–scenario combinations also revealed differences in predictions depending on the choice of GCM, with scenario choice having less of an impact. While the Norwegian model predicted little northward expansion of the beetle from its current northern range limit of southern Ontario and overall decreases in suitable and favourable areas over time, the Canadian and Russian models predict that much of Ontario and Quebec will become suitable for the beetle in the future, as well as Manitoba under the Russian model. The Russian model also predicts expansion of the suitable and favourable areas for the beetle over time. Two predictions that do not depend on our choice of GCM include a decrease in suitability of the Mississippi Delta region and continued favourability of the southeastern United States.     

Integrating mechanistic and empirical model projections to assess climate impacts on tree species distributions in northwestern North America

Empirical and mechanistic models have both been used to assess the potential impacts of climate change on species distributions, and each modeling approach has its strengths and weaknesses. Here, we demonstrate an approach to projecting climate‐driven changes in species distributions that draws on both empirical and mechanistic models. We combined projections from a dynamic global vegetation model (DGVM) that simulates the distributions of biomes based on basic plant functional types with projections from empirical climatic niche models for six tree species in northwestern North America. These integrated model outputs incorporate important biological processes, such as competition, physiological responses of plants to changes in atmospheric CO₂ concentrations, and fire, as well as what are likely to be species‐specific climatic constraints. We compared the integrated projections to projections from the empirical climatic niche models alone. Overall, our integrated model outputs projected a greater climate‐driven loss of potentially suitable environmental space than did the empirical climatic niche model outputs alone for the majority of modeled species. Our results also show that refining species distributions with DGVM outputs had large effects on the geographic locations of suitable habitat. We demonstrate one approach to integrating the outputs of mechanistic and empirical niche models to produce bioclimatic projections. But perhaps more importantly, our study reveals the potential for empirical climatic niche models to over‐predict suitable environmental space under future climatic conditions.     

The data void in modeling current and future distributions of tropical species

Conserving biodiversity in the face of climate change requires a predictive ecology of species distributions. Nowhere is this need more acute than in the tropics, which harbor the majority of Earth's species and face rapid and large climate and land‐use changes. However, the study of species distributions and their responses to climate change in high diversity tropical regions is potentially crippled by a lack of basic data. We analyzed a database representing more than 800 000 unique geo‐referenced natural history collections to determine what fraction of tropical plant species has sufficient numbers of available collections for use in the habitat or niche models commonly used to predict species responses to climate change. We found that more than nine out of 10 species from the three principle tropical realms are so poorly collected (n < 20 records) that they are essentially invisible to modern modeling and conservation tools. In order to predict the impact of climate change on tropical species, efforts must be made to increase the amount of data available from tropical countries through a combination of collecting new specimens and digitizing existing records.     

Projected bioclimatic distributions in Nearctic Bovidae signal the potential for reduced overlap with protected areas

Assumptions about factors such as climate in shaping species'' realized and potential distributions underlie much of conservation planning and wildlife management. Climate and climatic change lead to shifts in species distributions through both direct and indirect ecological pressures. Distributional shifts may be particularly important if range overlap is altered between interacting species, or between species and protected areas. The cattle family (Bovidae) represents a culturally, economically, and ecologically important taxon that occupies many of the world''s rangelands. In contemporary North America, five wild bovid species inhabit deserts, prairies, mountains, and tundra from Mexico to Greenland. Here, we aim to understand how future climate change will modify environmental characteristics associated with North American bovid species relative to the distribution of extant protected areas. We fit species distribution models for each species to climate, topography, and land cover data using observations from a citizen science dataset. We then projected modeled distributions to the end of the 21st century for each bovid species under two scenarios of anticipated climate change. Modeling results suggest that suitable habitat will shift inconsistently across species and that such shifts will lead to species‐specific variation in overlap between potential habitat and existing protected areas. Furthermore, projected overlap with protected areas was sensitive to the warming scenario under consideration, with diminished realized protected area under greater warming. Conservation priorities and designation of new protected areas should account for ecological consequences of climate change.