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.     

Benchmarking novel approaches for modelling species range dynamics

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species’ range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process‐based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process‐based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species’ response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species.     

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.     

Reducing uncertainty in projections of extinction risk from climate change

Aim Concern over the implications of climate change for biodiversity has led to the use of species–climate ‘envelope’ models to forecast risks of species extinctions under climate change scenarios. Recent studies have demonstrated significant variability in model projections and there remains a need to test the accuracy of models and to reduce uncertainties. Testing of models has been limited by a lack of data against which projections of future ranges can be tested. Here we provide a first test of the predictive accuracy of such models using observed species’ range shifts and climate change in two periods of the recent past. Location Britain. Methods Observed range shifts for 116 breeding bird species in Britain between 1967 and 1972 (t₁) and 1987–91 (t₂) are used. We project range shifts between t₁ and t₂ for each species based on observed climate using 16 alternative models (4 methods × 2 data parameterizations × 2 rules to transform probabilities of occurrence into presence and absence records). Results Modelling results were extremely variable, with projected range shifts varying both in magnitude and in direction from observed changes and from each other. However, using approaches that explore the central tendency (consensus) of model projections, we were able to improve agreement between projected and observed shifts significantly. Conclusions Our results provide the first empirical evidence of the value of species–climate ‘envelope’ models under climate change and demonstrate reduction in uncertainty and improvement in accuracy through selection of the most consensual projections.     

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.     

Integrating ecophysiological models into species distribution projections of European reptile range shifts in response to climate change

Uncertainty in projections of global change impacts on biodiversity over the 21st century is high. Improved predictive accuracy is needed, highlighting the importance of using different types of models when predicting species range shifts. However, this is still rarely done. Our approach integrates the outputs of a spatially‐explicit physiologically inspired model of extinction and correlative species distribution models to assess climate‐change induced range shifts of three European reptile species (Lacerta lepida, Iberolacerta monticola, and Hemidactylus turcicus) in the coming decades. We integrated the two types of models by mapping and quantifying agreement and disagreement between their projections. We analyzed the relationships between climate change and projected range shifts. Agreement between model projections varied greatly between species and depended on whether or not they consider dispersal ability. Under our approach, the reliability of predictions is greatest where the predictions of these different types of models converge, and in this way uncertainty is reduced; sites where this convergence occurs are characterized by both current high temperatures and significant future temperature increase, suggesting they may become hotspots of local extinctions. Moreover, this approach can be readily implemented with other types of models.     

Projecting impacts of global climate and land‐use scenarios on plant biodiversity using compositional‐turnover modelling

Nations have committed to ambitious conservation targets in response to accelerating rates of global biodiversity loss. Anticipating future impacts is essential to inform policy decisions for achieving these targets, but predictions need to be of sufficiently high spatial resolution to forecast the local effects of global change. As part of the intercomparison of biodiversity and ecosystem services models of the Intergovernmental Science‐Policy Platform on Biodiversity and Ecosystem Services, we present a fine‐resolution assessment of trends in the persistence of global plant biodiversity. We coupled generalized dissimilarity models, fitted to >52 million records of >254 thousand plant species, with the species–area relationship, to estimate the effect of land‐use and climate change on global biodiversity persistence. We estimated that the number of plant species committed to extinction over the long term has increased by 60% globally between 1900 and 2015 (from ~10,000 to ~16,000). This number is projected to decrease slightly by 2050 under the most optimistic scenario of land‐use change and to substantially increase (to ~18,000) under the most pessimistic scenario. This means that, in the absence of climate change, scenarios of sustainable socio‐economic development can potentially bring extinction risk back to pre‐2000 levels. Alarmingly, under all scenarios, the additional impact from climate change might largely surpass that of land‐use change. In this case, the estimated number of species committed to extinction increases by 3.7–4.5 times compared to land‐use‐only projections. African regions (especially central and southern) are expected to suffer some of the highest impacts into the future, while biodiversity decline in Southeast Asia (which has previously been among the highest globally) is projected to slow down. Our results suggest that environmentally sustainable land‐use planning alone might not be sufficient to prevent potentially dramatic biodiversity loss, unless a stabilization of climate to pre‐industrial times is observed.     

Forecasting potential routes for movement of endemic birds among important sites for biodiversity in the Albertine Rift under projected climate change

The ability of species to shift their distributions in response to climate change may be impeded by lack of suitable climate or habitat between species’ current and future ranges. We examined the potential for climate and forest cover to limit the movement of bird species among sites of biodiversity importance in the Albertine Rift, East Africa, a biodiversity hotspot. We forecasted future distributions of suitable climate for 12 Albertine Rift endemic bird species using species distribution models based on current climate data and projections of future climate. We used these forecasts alongside contemporary forest cover and natal dispersal estimates to project potential movement of species over time. We identified potentially important pathways for the bird species to move among 30 important bird and biodiversity areas (IBAs) that are both currently forested and projected to provide suitable climate over intervening time periods. We examined the relative constraints imposed by availability of suitable climate and forest cover on future movements. The analyses highlighted important pathways of potential dispersal lying along a north‐south axis through high elevation areas of the Albertine Rift. Both forest availability and climate suitability were projected to influence bird movement through these landscapes as they are affected by future climate change. Importantly, forest cover and areas projected to contain suitable climate in future were often dissociated in space, which could limit species’ responses to climate change. A lack of climatically suitable areas was a far greater impediment to projected movement among IBAs than insufficient forest cover. Although current forest cover appears sufficient to facilitate movement of bird species in this region, protecting the remaining forests in areas also projected to be climatically suitable for species to move through in the future should be a priority for adaptation management.     

Community assembly processes restrict the capacity for genetic adaptation under climate change

Given the magnitude and rate of ongoing climate change, the physiological capacity of species to tolerate extreme conditions will play a key role in influencing outcomes for biodiversity. It is also possible that species will respond to changes in climate by shifting their physiological tolerances, through genetic adaptation. How these processes influence biodiversity outcomes will be crucial in determining the most suitable management responses to retain diversity into the future. Here we assess how accounting for physiological tolerances, genetic adaptation and community assembly processes such as species replacement, influence projected climate change outcomes for the flora of Tasmania (all 2051 plant species). We incorporate these processes into the M‐SET metacommunity model and compare four different assumptions of species niches: realized niches, broader physiological tolerances and low or high capacity for genetic adaptation. Accounting for physiological tolerances rather than realized niches had the largest impact on projected outcomes, with 358 fewer species extinctions in the hottest climate scenario (mean = 30 extinctions). In contrast, adding the capacity for species physiological tolerances to shift through genetic adaptation resulted in little additional benefits for biodiversity outcomes, even under an optimistic level of adaptive capacity. We find that this is due largely to community assembly processes such as species replacement restricting the ability of species to persist and adapt in situ, as has been suggested from theoretical metacommunity models applied in simple artificial settings. Our results highlight the importance of accounting for species physiological tolerances and community‐level processes in biodiversity projections, while the potential role for genetic adaptation may be small, requiring further exploration in alternative contexts.     

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.     

Climate change impacts on tree ranges: model intercomparison facilitates understanding and quantification of uncertainty

Model-based projections of shifts in tree species range due to climate change are becoming an important decision support tool for forest management. However, poorly evaluated sources of uncertainty require more scrutiny before relying heavily on models for decision-making. We evaluated uncertainty arising from differences in model formulations of tree response to climate change based on a rigorous intercomparison of projections of tree distributions in France. We compared eight models ranging from niche-based to process-based models. On average, models project large range contractions of temperate tree species in lowlands due to climate change. There was substantial disagreement between models for temperate broadleaf deciduous tree species, but differences in the capacity of models to account for rising CO(2) impacts explained much of the disagreement. There was good quantitative agreement among models concerning the range contractions for Scots pine. For the dominant Mediterranean tree species, Holm oak, all models foresee substantial range expansion.     

Individualistic vs community modelling of species distributions under climate change

Studies investigating the consequences of future climate changes on species distributions usually start with the assumption that species respond to climate changes in an individualistic fashion. This assumption has led researchers to use bioclimate envelope models that use present climate-range relationships to characterize species' limits of tolerance to climate, and then apply climate-change scenarios to enable projections of altered species distributions. However, there are techniques that combine climate variables together with information on the composition of assemblages to enable projections that are expected to mimic community dynamics. Here, we compare, for the first time, the performance of GLM (generalized linear model) and CQO (canonical quadratic ordination; a type of community-based GLM) for projecting distributions of species under climate change scenarios. We found that projections from these two methods varied both in terms of accuracy (GLM providing generally more accurate projections than CQO) and in the broad diversity patterns yielded (higher species richness values projected with CQO). Model outputs were also affected by species-specific traits, such as species range size and species geographical positions, supporting the view that methods are sensitive to different degrees of equilibrium of species distributions with climate. This study reveals differences in projections between individual- and community-based approaches that require further scrutiny, but it does not find support for unsupervised use community-based models for investigating climate change impacts on species distributions. Reasons for this lack of support are discussed.     

Biodiversity scenarios neglect future land‐use changes

Efficient management of biodiversity requires a forward‐looking approach based on scenarios that explore biodiversity changes under future environmental conditions. A number of ecological models have been proposed over the last decades to develop these biodiversity scenarios. Novel modelling approaches with strong theoretical foundation now offer the possibility to integrate key ecological and evolutionary processes that shape species distribution and community structure. Although biodiversity is affected by multiple threats, most studies addressing the effects of future environmental changes on biodiversity focus on a single threat only. We examined the studies published during the last 25 years that developed scenarios to predict future biodiversity changes based on climate, land‐use and land‐cover change projections. We found that biodiversity scenarios mostly focus on the future impacts of climate change and largely neglect changes in land use and land cover. The emphasis on climate change impacts has increased over time and has now reached a maximum. Yet, the direct destruction and degradation of habitats through land‐use and land‐cover changes are among the most significant and immediate threats to biodiversity. We argue that the current state of integration between ecological and land system sciences is leading to biased estimation of actual risks and therefore constrains the implementation of forward‐looking policy responses to biodiversity decline. We suggest research directions at the crossroads between ecological and environmental sciences to face the challenge of developing interoperable and plausible projections of future environmental changes and to anticipate the full range of their potential impacts on biodiversity. An intergovernmental platform is needed to stimulate such collaborative research efforts and to emphasize the societal and political relevance of taking up this challenge.     

Woody plants and the prediction of climate-change impacts on bird diversity

Current methods of assessing climate-induced shifts of species distributions rarely account for species interactions and usually ignore potential differences in response times of interacting taxa to climate change. Here, we used species-richness data from 1005 breeding bird and 1417 woody plant species in Kenya and employed model-averaged coefficients from regression models and median climatic forecasts assembled across 15 climate-change scenarios to predict bird species richness under climate change. Forecasts assuming an instantaneous response of woody plants and birds to climate change suggested increases in future bird species richness across most of Kenya whereas forecasts assuming strongly lagged woody plant responses to climate change indicated a reversed trend, i.e. reduced bird species richness. Uncertainties in predictions of future bird species richness were geographically structured, mainly owing to uncertainties in projected precipitation changes. We conclude that assessments of future species responses to climate change are very sensitive to current uncertainties in regional climate-change projections, and to the inclusion or not of time-lagged interacting taxa. We expect even stronger effects for more specialized plant–animal associations. Given the slow response time of woody plant distributions to climate change, current estimates of future biodiversity of many animal taxa may be both biased and too optimistic.     

Climate change and range restriction of common salamanders in eastern Canada and the United States

The sensitivity of amphibian species to shifts in environmental conditions has been exhibited through long-term population studies and the projection of ecological niche models under expected conditions. Species in biodiversity hotspots have been the focus of ample predictive modeling studies, while, despite their significant ecological value, wide-ranging and common taxa have received less attention. We focused on predicting range restriction of the spotted salamander (Ambystoma maculatum), blue-spotted salamander (A. laterale), four-toed salamander (Hemidactylium scutatum), and red-backed salamander (Plethodon cinereus) under future climate scenarios. Using bias-corrected future climate data and biodiversity database records, we developed maximum entropy (MaxEnt) models under current conditions and for climate change projections in 2050 and 2070. We calculated positivity rates of species localities to represent proportions of habitat expected to remain climatically suitable with continued climate change. Models projected under future conditions predicted average positivity rates of 91% (89–93%) for the blue-spotted salamander, 23% (2–41%) for the spotted salamander, 4% (0.7–9%) for the four-toed salamander, and 61% (42–76%) for the red-backed salamander. Range restriction increased with time and greenhouse gas concentration for the spotted salamander, four-toed salamander, and red-backed salamander. Common, widespread taxa that often receive less conservation resources than other species are at risk of experiencing significant losses to their climatic ranges as climate change continues. Efforts to maintain populations of species should be focused on regions expected to experience fewer climatic shifts such as the interior and northern zones of species' distributions.     

FATE‐HD: a spatially and temporally explicit integrated model for predicting vegetation structure and diversity at regional scale

During the last decade, despite strenuous efforts to develop new models and compare different approaches, few conclusions have been drawn on their ability to provide robust biodiversity projections in an environmental change context. The recurring suggestions are that models should explicitly (i) include spatiotemporal dynamics; (ii) consider multiple species in interactions and (iii) account for the processes shaping biodiversity distribution. This article presents a biodiversity model (FATE‐HD) that meets this challenge at regional scale by combining phenomenological and process‐based approaches and using well‐defined plant functional groups. FATE‐HD has been tested and validated in a French National Park, demonstrating its ability to simulate vegetation dynamics, structure and diversity in response to disturbances and climate change. The analysis demonstrated the importance of considering biotic interactions, spatio‐temporal dynamics and disturbances in addition to abiotic drivers to simulate vegetation dynamics. The distribution of pioneer trees was particularly improved, as were all undergrowth functional groups.     

Severe Loss of Suitable Climatic Conditions for Marsupial Species in Brazil: Challenges and Opportunities for Conservation

A wide range of evidences indicate climate change as one the greatest threats to biodiversity in the 21st century. The impacts of these changes, which may have already resulted in several recent species extinction, are species-specific and produce shifts in species phenology, ecological interactions, and geographical distributions. Here we used cutting-edge methods of species distribution models combining thousands of model projections to generate a complete and comprehensive ensemble of forecasts that shows the likely impacts of climate change in the distribution of all 55 marsupial species that occur in Brazil. Consensus projections forecasted range shifts that culminate with high species richness in the southeast of Brazil, both for the current time and for 2050. Most species had a significant range contraction and lost climate space. Turnover rates were relatively high, but vary across the country. We also mapped sites retaining climatic suitability. They can be found in all Brazilian biomes, especially in the pampas region, in the southern part of the Brazilian Atlantic Forest, in the north of the Cerrado and Caatinga, and in the northwest of the Amazon. Our results provide a general overview on the likely effects of global climate change on the distribution of marsupials in the country as well as in the patterns of species richness and turnover found in regional marsupial assemblages.