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.     

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.     

Climate change disrupts core habitats of marine species

Driven by climate change, marine biodiversity is undergoing a phase of rapid change that has proven to be even faster than changes observed in terrestrial ecosystems. Understanding how these changes in species composition will affect future marine life is crucial for conservation management, especially due to increasing demands for marine natural resources. Here, we analyse predictions of a multiparameter habitat suitability model covering the global projected ranges of >33,500 marine species from climate model projections under three CO₂ emission scenarios (RCP2.6, RCP4.5, RCP8.5) up to the year 2100. Our results show that the core habitat area will decline for many species, resulting in a net loss of 50% of the core habitat area for almost half of all marine species in 2100 under the high-emission scenario RCP8.5. As an additional consequence of the continuing distributional reorganization of marine life, gaps around the equator will appear for 8% (RCP2.6), 24% (RCP4.5), and 88% (RCP8.5) of marine species with cross-equatorial ranges. For many more species, continuous distributional ranges will be disrupted, thus reducing effective population size. In addition, high invasion rates in higher latitudes and polar regions will lead to substantial changes in the ecosystem and food web structure, particularly regarding the introduction of new predators. Overall, our study highlights that the degree of spatial and structural reorganization of marine life with ensued consequences for ecosystem functionality and conservation efforts will critically depend on the realized greenhouse gas emission pathway.     

Distributional range shifts of Western Atlantic benthic Sargassum species (Fucales,Phaeophyceae) under future climate change scenarios

Climate change is altering the world’s marine biota, in particular, their geographic distribution. Sargassum species are foundation species that play critical ecological roles in tropical benthic communities, providing food, habitat heterogeneity and shelter for a wide range of marine organisms. To understand how future changes in abiotic variables could affect the distribution of Sargassum species along the Western Atlantic Ocean, we performed Ecological Niche Models (ENM) for 12 benthic Sargassum species. We projected present and future habitat suitability distributions under the RCP 4.5 and RCP 8.5 IPCC scenarios. We fit ENM and created ensembles from different algorithms. Our results predict changes in species latitudinal range (niche suitability) in the order of 0.5˚ to 8.1˚ northward, and 0˚ to 5.5˚ southward. Six species are likely to reduce their suitability area from 10% to 80%, while other six species are likely to expand their suitability area from 4% to 168%. Overall, changes in suitability area and latitudinal ranges will increase at larger latitudes for most species while suitability areas will decrease at lower latitudes for half of the species. This pattern is consistent with the expected tropicalization of temperate latitudes following global warming. Such changes can produce considerable losses in ecosystem services maintained by healthy Sargassum beds, particularly at lower latitudes. Our findings highlight the need to improve Sargassum conservation policies and management strategies to avoid the negative effects caused by losses in Sargassum forests.     

Predicting the future of forests in the Mediterranean under climate change,with niche‐ and process‐based models: CO2 matters!

Assessing the potential future of current forest stands is a key to design conservation strategies and understanding potential future impacts to ecosystem service supplies. This is particularly true in the Mediterranean basin, where important future climatic changes are expected. Here, we assess and compare two commonly used modeling approaches (niche‐ and process‐based models) to project the future of current stands of three forest species with contrasting distributions, using regionalized climate for continental Spain. Results highlight variability in model ability to estimate current distributions, and the inherent large uncertainty involved in making projections into the future. CO₂ fertilization through projected increased atmospheric CO₂ concentrations is shown to increase forest productivity in the mechanistic process‐based model (despite increased drought stress) by up to three times that of the non‐CO₂ fertilization scenario by the period 2050–2080, which is in stark contrast to projections of reduced habitat suitability from the niche‐based models by the same period. This highlights the importance of introducing aspects of plant biogeochemistry into current niche‐based models for a realistic projection of future species distributions. We conclude that the future of current Mediterranean forest stands is highly uncertain and suggest that a new synergy between niche‐ and process‐based models is urgently needed in order to improve our predictive ability.     

MigClim: Predicting plant distribution and dispersal in a changing climate

Aim Many studies have forecasted the possible impact of climate change on plant distributions using models based on ecological niche theory, but most of them have ignored dispersal‐limitations, assuming dispersal to be either unlimited or null. Depending on the rate of climatic change, the landscape fragmentation and the dispersal capabilities of individual species, these assumptions are likely to prove inaccurate, leading to under‐ or overestimation of future species distributions and yielding large uncertainty between these two extremes. As a result, the concepts of ‘potentially suitable’ and ‘potentially colonizable’ habitat are expected to differ significantly. To quantify to what extent these two concepts can differ, we developed Mig Clim, a model simulating plant dispersal under climate change and landscape fragmentation scenarios. Mig Clim implements various parameters, such as dispersal distance, increase in reproductive potential over time, landscape fragmentation or long‐distance dispersal. Location Western Swiss Alps. Methods Using our Mig Clim model, several simulations were run for two virtual species by varying dispersal distance and other parameters. Each simulation covered the 100‐year period 2001–2100 and three different IPCC‐based temperature warming scenarios were considered. Results of dispersal‐limited projections were compared with unlimited and no‐dispersal projections. Results Our simulations indicate that: (1) using realistic parameter values, the future potential distributions generated using Mig Clim can differ significantly (up to more than 95% difference in colonized surface) from those that ignore dispersal; (2) this divergence increases under more extreme climate warming scenarios and over longer time periods; and (3) the uncertainty associated with the warming scenario can be as large as the one related to dispersal parameters. Main conclusions Accounting for dispersal, even roughly, can importantly reduce uncertainty in projections of species distribution under climate change scenarios.     

Uncertainties in Predicting Species Distributions under Climate Change: A Case Study Using Tetranychus evansi (Acari: Tetranychidae), a Widespread Agricultural Pest

Many species are shifting their distributions due to climate change and to increasing international trade that allows dispersal of individuals across the globe. In the case of agricultural pests, such range shifts may heavily impact agriculture. Species distribution modelling may help to predict potential changes in pest distributions. However, these modelling strategies are subject to large uncertainties coming from different sources. Here we used the case of the tomato red spider mite (Tetranychus evansi), an invasive pest that affects some of the most important agricultural crops worldwide, to show how uncertainty may affect forecasts of the potential range of the species. We explored three aspects of uncertainty: (1) species prevalence; (2) modelling method; and (3) variability in environmental responses between mites belonging to two invasive clades of T. evansi. Consensus techniques were used to forecast the potential range of the species under current and two different climate change scenarios for 2080, and variance between model projections were mapped to identify regions of high uncertainty. We revealed large predictive variations linked to all factors, although prevalence had a greater influence than the statistical model once the best modelling strategies were selected. The major areas threatened under current conditions include tropical countries in South America and Africa, and temperate regions in North America, the Mediterranean basin and Australia. Under future scenarios, the threat shifts towards northern Europe and some other temperate regions in the Americas, whereas tropical regions in Africa present a reduced risk. Analysis of niche overlap suggests that the current differential distribution of mites of the two clades of T. evansi can be partially attributed to environmental niche differentiation. Overall this study shows how consensus strategies and analysis of niche overlap can be used jointly to draw conclusions on invasive threat considering different sources of uncertainty in species distribution modelling.     

Choice of baseline climate data impacts projected species' responses to climate change

Climate data created from historic climate observations are integral to most assessments of potential climate change impacts, and frequently comprise the baseline period used to infer species‐climate relationships. They are often also central to downscaling coarse resolution climate simulations from General Circulation Models (GCMs) to project future climate scenarios at ecologically relevant spatial scales. Uncertainty in these baseline data can be large, particularly where weather observations are sparse and climate dynamics are complex (e.g. over mountainous or coastal regions). Yet, importantly, this uncertainty is almost universally overlooked when assessing potential responses of species to climate change. Here, we assessed the importance of historic baseline climate uncertainty for projections of species' responses to future climate change. We built species distribution models (SDMs) for 895 African bird species of conservation concern, using six different climate baselines. We projected these models to two future periods (2040–2069, 2070–2099), using downscaled climate projections, and calculated species turnover and changes in species‐specific climate suitability. We found that the choice of baseline climate data constituted an important source of uncertainty in projections of both species turnover and species‐specific climate suitability, often comparable with, or more important than, uncertainty arising from the choice of GCM. Importantly, the relative contribution of these factors to projection uncertainty varied spatially. Moreover, when projecting SDMs to sites of biodiversity importance (Important Bird and Biodiversity Areas), these uncertainties altered site‐level impacts, which could affect conservation prioritization. Our results highlight that projections of species' responses to climate change are sensitive to uncertainty in the baseline climatology. We recommend that this should be considered routinely in such analyses.     

Communities at the extreme: Aquatic food webs in desert landscapes

Studying food webs across contrasting abiotic conditions is an important tool in understanding how environmental variability impacts community structure and ecosystem dynamics. The study of extreme environments provides insight into community‐wide level responses to environmental pressures with relevance to the future management of aquatic ecosystems. In the western Lake Eyre Basin of arid Australia, there are two characteristic and contrasting aquatic habitats: springs and rivers. Permanent isolated Great Artesian Basin springs represent hydrologically persistent environments in an arid desert landscape. In contrast, hydrologically variable river waterholes are ephemeral in space and time. We comprehensively sampled aquatic assemblages in contrasting ecosystem types to assess patterns in community composition and to quantify food web attributes with stable isotopes. Springs and rivers were found to have markedly different invertebrate communities, with rivers dominated by more dispersive species and springs associated with species that show high local endemism. Qualitative assessment of basal resources shows autochthonous carbon appears to be a key basal resource in both types of habitat, although the particular sources differed between habitats. Food‐web variables such as trophic length, trophic breadth, and community isotopic niche size were relatively similar in the two habitat types. The basis for the similarity in food‐web structure despite differences in community composition appears to be broader isotopic niches for predatory invertebrates and fish in springs as compared with rivers. In contrast to published theory, our findings suggest that the food webs of the hydrologically variable river sites may show less dietary generalization and more compact food‐web modules than in springs.     

From projected species distribution to food‐web structure under climate change

Climate change is inducing deep modifications in species geographic ranges worldwide. However, the consequences of such changes on community structure are still poorly understood, particularly the impacts on food‐web properties. Here, we propose a new framework, coupling species distribution and trophic models, to predict climate change impacts on food‐web structure across the Mediterranean Sea. Sea surface temperature was used to determine the fish climate niches and their future distributions. Body size was used to infer trophic interactions between fish species. Our projections reveal that 54 fish species of 256 endemic and native species included in our analysis would disappear by 2080–2099 from the Mediterranean continental shelf. The number of feeding links between fish species would decrease on 73.4% of the continental shelf. However, the connectance of the overall fish web would increase on average, from 0.26 to 0.29, mainly due to a differential loss rate of feeding links and species richness. This result masks a systematic decrease in predator generality, estimated here as the number of prey species, from 30.0 to 25.4. Therefore, our study highlights large‐scale impacts of climate change on marine food‐web structure with potential deep consequences on ecosystem functioning. However, these impacts will likely be highly heterogeneous in space, challenging our current understanding of climate change impact on local marine ecosystems.     

Evaluation of Gangetic dolphin habitat suitability under hydroclimatic changes using a coupled hydrological-hydrodynamic approach

The aquatic ecosystems are an integral part of the global environment and play a critical role in hydrogeological processes in the rivers. In recent decades, the external stressors on the aquatic species have significantly increased due to hydrologic alterations, human activities, and anthropogenic changes to their natural habitat. Global climate change has led to rivers' hydrological flow regime shifts, leading to unsuitable habitat conditions. It is, therefore, crucial to assess the potential implications of climate change on habitat suitability to ensure the long-term sustainability of freshwater species. In this direction, we investigated the association between endangered Gangetic dolphin populations and climate-driven hydrologic flow regime alterations in the Kulsi river, India. We developed a coupled eco-hydraulic framework comprising hydrological and hydrodynamic modeling to study the impact of past and projected climate change scenarios on the habitat suitability of target species. The framework was tested on a 15-km stretch of the Kulsi River, where the dolphin population has significantly declined in recent years. The temporal changes in the Weighted Usable Area (WUA) were analyzed using flow parameters and habitat suitability curves. Our findings suggest that the dolphin population decline coincided with a decrease in WUA, indicating a strong association between flow regimes and habitat suitability. Under climate change scenarios, multi-model climate projections and hydrological-hydrodynamic simulations show a rising trend in precipitation and streamflow in the basin, with substantial uncertainty. Higher flow depth and velocity would enhance WUA (habitat suitability). Still, the proposed river development projects in upstream regions could pose a serious threat to fragile dolphin communities by changing the seasonal flow patterns. The findings of this study can be included in conservation action plans and flow regulations strategies in upstream projects to ensure the long-term survival of endangered species.     

Environmental drivers of ant species richness and composition across the Argentine Pampas grassland

Understanding the underlying mechanisms causing diversity patterns is a fundamental objective in ecology and science‐based conservation biology. Energy and environmental‐heterogeneity hypotheses have been suggested to explain spatial changes in ant diversity. However, the relative roles of each one in determining alpha and beta diversity patterns remain elusive. We investigated the main factors driving spatial changes in ant (Hymenoptera, Formicidae) species richness and composition (including turnover and nestedness components) along a 500 km longitudinal gradient in the Pampean region of Argentina. Ants were sampled using pitfall traps in 12 sample sites during the summer. We performed a model selection approach to analyse responses of ant richness and composition dissimilarity to environmental factors. Then, we computed a dissimilarity partitioning of the contributions of spatial turnover and nestedness to total composition dissimilarity. Temporal habitat heterogeneity and temperature were the primary factors explaining spatial patterns of epigean ant species richness across the Pampas. The distance decay in species composition similarity was best accounted by temperature dissimilarity, and turnover had the greatest contribution to the observed beta diversity pattern. Our findings suggest that both energy and environmental‐heterogeneity‐related variables are key factors shaping richness patterns of ants and niche‐based processes instead of neutral processes appear to be regulating species composition of ant assemblages. The major contribution of turnover to the beta diversity pattern indicated that lands for potential reconversion to grassland should represent the complete environmental gradient of the Pampean region, instead of prioritizing a single site with high species richness.     

Uncertainty in ensemble forecasting of species distribution

Species distribution modelling has been widely applied in order to assess the potential impacts of climate change on biodiversity. Many methodological decisions, taken during the modelling process and forecasts, may, however, lead to a large variability in the assessment of future impacts. Using measures of species range change and turnover, the potential impacts of climate change on French stream fish species and assemblages were evaluated. Our main focus was to quantify the uncertainty in the projections of these impacts arising from four sources of uncertainty: initial datasets (Data), statistical methods [species distribution models (SDM)], general circulation models (GCM), and gas emission scenarios (GES). Several modalities of the aforementioned uncertainty sources were combined in an ensemble forecasting framework resulting in 8400 different projections. The variance explained by each source was then extracted from this whole ensemble of projections. Overall, SDM contributed to the largest variation in projections, followed by GCM, whose contribution increased over time equalling almost the proportion of variance explained by SDM in 2080. Data and GES had little influence on the variability in projections. Future projections of range change were more consistent for species with a large geographical extent (i.e., distribution along latitudinal or stream gradients) or with restricted environmental requirements (i.e., small thermal or elevation ranges). Variability in projections of turnover was spatially structured at the scale of France, indicating that certain particular geographical areas should be considered with care when projecting the potential impacts of climate change. The results of this study, therefore, emphasized that particular attention should be paid to the use of predictions ensembles resulting from the application of several statistical methods and climate models. Moreover, forecasted impacts of climate change should always be provided with an assessment of their uncertainty, so that management and conservation decisions can be taken in the full knowledge of their reliability.     

Evaluation of habitat suitability index models by global sensitivity and uncertainty analyses: a case study for submerged aquatic vegetation

Habitat suitability index (HSI) models are commonly used to predict habitat quality and species distributions and are used to develop biological surveys, assess reserve and management priorities, and anticipate possible change under different management or climate change scenarios. Important management decisions may be based on model results, often without a clear understanding of the level of uncertainty associated with model outputs. We present an integrated methodology to assess the propagation of uncertainty from both inputs and structure of the HSI models on model outputs (uncertainty analysis: UA) and relative importance of uncertain model inputs and their interactions on the model output uncertainty (global sensitivity analysis: GSA). We illustrate the GSA/UA framework using simulated hydrology input data from a hydrodynamic model representing sea level changes and HSI models for two species of submerged aquatic vegetation (SAV) in southwest Everglades National Park: Vallisneria americana (tape grass) and Halodule wrightii (shoal grass). We found considerable spatial variation in uncertainty for both species, but distributions of HSI scores still allowed discrimination of sites with good versus poor conditions. Ranking of input parameter sensitivities also varied spatially for both species, with high habitat quality sites showing higher sensitivity to different parameters than low‐quality sites. HSI models may be especially useful when species distribution data are unavailable, providing means of exploiting widely available environmental datasets to model past, current, and future habitat conditions. The GSA/UA approach provides a general method for better understanding HSI model dynamics, the spatial and temporal variation in uncertainties, and the parameters that contribute most to model uncertainty. Including an uncertainty and sensitivity analysis in modeling efforts as part of the decision‐making framework will result in better‐informed, more robust decisions.     

Cetacean range and climate in the eastern North Atlantic: future predictions and implications for conservation

There is increasing evidence that the distributions of a large number of species are shifting with global climate change as they track changing surface temperatures that define their thermal niche. Modelling efforts to predict species distributions under future climates have increased with concern about the overall impact of these distribution shifts on species ecology, and especially where barriers to dispersal exist. Here we apply a bio‐climatic envelope modelling technique to investigate the impacts of climate change on the geographic range of ten cetacean species in the eastern North Atlantic and to assess how such modelling can be used to inform conservation and management. The modelling process integrates elements of a species' habitat and thermal niche, and employs “hindcasting” of historical distribution changes in order to verify the accuracy of the modelled relationship between temperature and species range. If this ability is not verified, there is a risk that inappropriate or inaccurate models will be used to make future predictions of species distributions. Of the ten species investigated, we found that while the models for nine could successfully explain current spatial distribution, only four had a good ability to predict distribution changes over time in response to changes in water temperature. Applied to future climate scenarios, the four species‐specific models with good predictive abilities indicated range expansion in one species and range contraction in three others, including the potential loss of up to 80% of suitable white‐beaked dolphin habitat. Model predictions allow identification of affected areas and the likely time‐scales over which impacts will occur. Thus, this work provides important information on both our ability to predict how individual species will respond to future climate change and the applicability of predictive distribution models as a tool to help construct viable conservation and management strategies.     

Current and future distribution of a parasite with complex life cycle under global change scenarios: Echinococcus multilocularis in Europe

Global change is expected to have complex effects on the distribution and transmission patterns of zoonotic parasites. Modelling habitat suitability for parasites with complex life cycles is essential to further our understanding of how disease systems respond to environmental changes, and to make spatial predictions of their future distributions. However, the limited availability of high quality occurrence data with high spatial resolution often constrains these investigations. Using 449 reliable occurrence records for Echinococcus multilocularis from across Europe published over the last 35 years, we modelled habitat suitability for this parasite, the aetiological agent of alveolar echinococcosis, in order to describe its environmental niche, predict its current and future distribution under three global change scenarios, and quantify the probability of occurrence for each European country. Using a machine learning approach, we developed large-scale (25 × 25 km) species distribution models based on seven sets of predictors, each set representing a distinct biological hypothesis supported by current knowledge of the autecology of the parasite. The best-supported hypothesis included climatic, orographic and land-use/land-cover variables such as the temperature of the coldest quarter, forest cover, urban cover and the precipitation seasonality. Future projections suggested the appearance of highly suitable areas for E. multilocularis towards northern latitudes and in the whole Alpine region under all scenarios, while decreases in habitat suitability were predicted for central Europe. Our spatially explicit predictions of habitat suitability shed light on the complex responses of parasites to ongoing global changes.     

Niche models tell half the story: spatial context and life‐history traits influence species responses to global change

Aim While niche models are typically used to assess the vulnerability of species to climate change, they have been criticized for their limited assessment of threats other than climate change. We attempt to evaluate this limitation by combining niche models with life‐history models to investigate the relative influence of climate change and a range of fire regimes on the viability of a long‐lived plant population. Specifically, we investigate whether range shift due to climate change is a greater threat to an obligate seeding fire‐prone shrub than altered fire frequency and how these two threatening processes might interact. Location Australian sclerophyll woodland and heathland. Methods The study species is Leucopogon setiger, an obligate seeding fire‐prone shrub. A spatially explicit stochastic matrix model was constructed for this species and linked with a dynamic niche model and fire risk functions representing a suite of average fire return intervals. We compared scenarios with a variety of hypothetical patches, a patch framework based upon current habitat suitability and one with dynamic habitat suitability based on climate change scenarios A1FI and A2. Results Leucopogon setiger was found to be sensitive to fire frequency, with shorter intervals reducing expected minimum abundances (EMAs). Spatial decoupling of fires across the landscape reduced the vulnerability of the species to shortened fire frequencies. Shifting habitat, while reducing EMAs, was less of a threat to the species than frequent fire. Main conclusions Altered fire regime, in particular more frequent fires relative to the historical regime, was predicted to be a strong threat to this species, which may reflect a vulnerability of obligate seeders in general. Range shifts induced by climate change were a secondary threat when habitat reductions were predicted. Incorporating life‐history traits into habitat suitability models by linking species distribution models with population models allowed for the population‐level evaluation of multiple stressors that affect population dynamics and habitat, ultimately providing a greater understanding of the impacts of global change than would be gained by niche models alone. Further investigations of this type could elucidate how particular bioecological factors can affect certain types of species under global change.