Projected changes in distributions of Australian tropical savanna birds under climate change using three dispersal scenarios

Identifying the species most vulnerable to extinction as a result of climate change is a necessary first step in mitigating biodiversity decline. Species distribution modeling (SDM) is a commonly used tool to assess potential climate change impacts on distributions of species. We use SDMs to predict geographic ranges for 243 birds of Australian tropical savannas, and to project changes in species richness and ranges under a future climate scenario between 1990 and 2080. Realistic predictions require recognition of the variability in species capacity to track climatically suitable environments. Here we assess the effect of dispersal on model results by using three approaches: full dispersal, no dispersal and a partial-dispersal scenario permitting species to track climate change at a rate of 30 km per decade. As expected, the projected distributions and richness patterns are highly sensitive to the dispersal scenario. Projected future range sizes decreased for 66% of species if full dispersal was assumed, but for 89% of species when no dispersal was assumed. However, realistic future predictions should not assume a single dispersal scenario for all species and as such, we assigned each species to the most appropriate dispersal category based on individual mobility and habitat specificity; this permitted the best estimates of where species will be in the future. Under this "realistic" dispersal scenario, projected ranges sizes decreased for 67% of species but showed that migratory and tropical-endemic birds are predicted to benefit from climate change with increasing distributional area. Richness hotspots of tropical savanna birds are expected to move, increasing in southern savannas and southward along the east coast of Australia, but decreasing in the arid zone. Understanding the complexity of effects of climate change on species' range sizes by incorporating dispersal capacities is a crucial step toward developing adaptation policies for the conservation of vulnerable species.     

Climate,competition and connectivity affect future migration and ranges of European trees

Aim Species ranges have adapted during the Holocene to altering climate conditions, but it remains unclear if species will be able to keep pace with recent and future climate change. The goal of our study is to assess the influence of changing macroclimate, competition and habitat connectivity on the migration rates of 14 tree species. We also compare the projections of range shifts from species distribution models (SDMs) that incorporate realistic migration rates with classical models that assume no or unlimited migration. Location Europe. Methods We calibrated SDMs with species abundance data from 5768 forest plots from ICP Forest Level 1 in relation to climate, topography, soil and land‐use data to predict current and future tree distributions. To predict future species ranges from these models, we applied three migration scenarios: no migration, unlimited migration and realistic migration. The migration rates for the SDMs incorporating realistic migration were estimated according to macroclimate, inter‐specific competition and habitat connectivity from simulation experiments with a spatially explicit process model (TreeMig). From these relationships, we then developed a migration cost surface to constrain the predicted distributions of the SDMs. Results The distributions of early‐successional species during the 21st century predicted by SDMs that incorporate realistic migration matched quite well with the unlimited migration assumption (mean migration rate over Europe for A1fi/GRAS climate and land‐use change scenario 156.7 ± 79.1 m year^?1 and for B1/SEDG 164.3 ± 84.2 m year^?1). The predicted distributions of mid‐ to late‐successional species matched better with the no migration assumption (A1fi/GRAS, 15.2 ± 24.5 m year^?1 and B1/SEDG, 16.0 ± 25.6 m year^?1). Inter‐specific competition, which is higher under favourable growing conditions, reduced range shift velocity more than did adverse macroclimatic conditions (i.e. very cold or dry climate). Habitat fragmentation also led to considerable time lags in range shifts. Main conclusions Migration rates depend on species traits, competition, spatial habitat configuration and climatic conditions. As a result, re‐adjustments of species ranges to climate and land‐use change are complex and very individualistic, yet still quite predictable. Early‐successional species track climate change almost instantaneously while mid‐ to late‐ successional species were predicted to migrate very slowly.     

An attack on two fronts: predicting how changes in land use and climate affect the distribution of stream macroinvertebrates

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Climate and land use changes will degrade the configuration of the landscape for titi monkeys in eastern Brazil

Land use changes have profound effects on populations of Neotropical primates, and ongoing climate change is expected to aggravate this scenario. The titi monkeys from eastern Brazil (Callicebus personatus group) have been particularly affected by this process, with four of the five species now allocated to threatened conservation status categories. Here, we estimate the changes in the distribution of these titi monkeys caused by changes in both climate and land use. We also use demographic‐based, functional landscape metrics to assess the magnitude of the change in landscape conditions for the distribution predicted for each species. We built species distribution models (SDMs) based on maximum entropy for current and future conditions (2070), allowing for different global circulation models and contrasting scenarios of glasshouse gas concentrations. We refined the SDMs using a high‐resolution map of habitat remnants. We then calculated habitat availability and connectivity based on home‐range size and the dispersal limitations of the individual, in the context of a predicted loss of 10% of forest cover in the future. The landscape configuration is predicted to be degraded for all species, regardless of the climatic settings. This include reductions in the total cover of forest remnants, patch size and functional connectivity. As the landscape configuration should deteriorate severely in the future for all species, the prevention of further loss of populations will only be achieved through habitat restoration and reconnection to counteract the negative effects for these and several other co‐occurring species.     

Forecasting the combined effects of future climate and land use change on the suitable habitat of Davidia involucrata Baill

Accurately predicting the future distribution of species is crucial for understanding how species will response to global environmental change and for evaluating the effectiveness of current protected areas (PAs). Here, we assessed the effect of climate and land use change on the projected suitable habitats of Davidia involucrata Baill under different future scenarios using the following two types of models: (a) only climate covariates (climate SDMs) and (b) climate and land use covariates (full SDMs). We found that full SDMs perform significantly better than climate SDMs in terms of both AUC (p < .001) and TSS (p < .001) and also projected more suitable habitat than climate SDMs both in the whole study area and in its current suitable range, although D. involucrate is predicted to loss at least 26.96% of its suitable area under all future scenarios. Similarly, we found that these range contractions projected by climate SDMs would negate the effectiveness of current PAs to a greater extent relative to full SDMs. These results suggest that although D. involucrate is extremely vulnerability to future climate change, conservation intervention to manage habitat may be an effective option to offset some of the negative effects of a changing climate on D. involucrate and can improve the effectiveness of current PAs. Overall, this study highlights the necessity of integrating climate and land use change to project the future distribution of species.     

Modeling plant species distributions under future climates: how fine scale do climate projections need to be?

Recent studies suggest that species distribution models (SDMs) based on fine‐scale climate data may provide markedly different estimates of climate‐change impacts than coarse‐scale models. However, these studies disagree in their conclusions of how scale influences projected species distributions. In rugged terrain, coarse‐scale climate grids may not capture topographically controlled climate variation at the scale that constitutes microhabitat or refugia for some species. Although finer scale data are therefore considered to better reflect climatic conditions experienced by species, there have been few formal analyses of how modeled distributions differ with scale. We modeled distributions for 52 plant species endemic to the California Floristic Province of different life forms and range sizes under recent and future climate across a 2000‐fold range of spatial scales (0.008–16 km²). We produced unique current and future climate datasets by separately downscaling 4 km climate models to three finer resolutions based on 800, 270, and 90 m digital elevation models and deriving bioclimatic predictors from them. As climate‐data resolution became coarser, SDMs predicted larger habitat area with diminishing spatial congruence between fine‐ and coarse‐scale predictions. These trends were most pronounced at the coarsest resolutions and depended on climate scenario and species' range size. On average, SDMs projected onto 4 km climate data predicted 42% more stable habitat (the amount of spatial overlap between predicted current and future climatically suitable habitat) compared with 800 m data. We found only modest agreement between areas predicted to be stable by 90 m models generalized to 4 km grids compared with areas classified as stable based on 4 km models, suggesting that some climate refugia captured at finer scales may be missed using coarser scale data. These differences in projected locations of habitat change may have more serious implications than net habitat area when predictive maps form the basis of conservation decision making.     

The future distribution of river fish: The complex interplay of climate and land use changes,species dispersal and movement barriers

The future distribution of river fishes will be jointly affected by climate and land use changes forcing species to move in space. However, little is known whether fish species will be able to keep pace with predicted climate and land use‐driven habitat shifts, in particular in fragmented river networks. In this study, we coupled species distribution models (stepwise boosted regression trees) of 17 fish species with species‐specific models of their dispersal (fish dispersal model FIDIMO) in the European River Elbe catchment. We quantified (i) the extent and direction (up‐ vs. downstream) of predicted habitat shifts under coupled “moderate” and “severe” climate and land use change scenarios for 2050, and (ii) the dispersal abilities of fishes to track predicted habitat shifts while explicitly considering movement barriers (e.g., weirs, dams). Our results revealed median net losses of suitable habitats of 24 and 94 river kilometers per species for the moderate and severe future scenarios, respectively. Predicted habitat gains and losses and the direction of habitat shifts were highly variable among species. Habitat gains were negatively related to fish body size, i.e., suitable habitats were projected to expand for smaller‐bodied fishes and to contract for larger‐bodied fishes. Moreover, habitats of lowland fish species were predicted to shift downstream, whereas those of headwater species showed upstream shifts. The dispersal model indicated that suitable habitats are likely to shift faster than species might disperse. In particular, smaller‐bodied fish (<200 mm) seem most vulnerable and least able to track future environmental change as their habitat shifted most and they are typically weaker dispersers. Furthermore, fishes and particularly larger‐bodied species might substantially be restricted by movement barriers to respond to predicted climate and land use changes, while smaller‐bodied species are rather restricted by their specific dispersal ability.     

The projected effects of climatic and vegetation changes on the distribution and diversity of Southeast Asian bats

Southeast‐Asia (SEA) constitutes a global biodiversity hotspot, but is exposed to extensive deforestation and faces numerous threats to its biodiversity. Climate change represents a major challenge to the survival and viability of species, and the potential consequences must be assessed to allow for mitigation. We project the effects of several climate change scenarios on bat diversity, and predict changes in range size for 171 bat species throughout SEA. We predict decreases in species richness in all areas with high species richness (>80 species) at 2050–2080, using bioclimatic IPCC scenarios A2 (a severe scenario, continuously increasing human population size, regional changes in economic growth) and B1 (the ‘greenest’ scenario, global population peaking mid‐century). We also predicted changes in species richness in scenarios that project vegetation changes in addition to climate change up to 2050. At 2050 and 2080, A2 and B1 scenarios incorporating changes in climatic factors predicted that 3–9% species would lose all currently suitable niche space. When considering total extents of species distribution in SEA (including possible range expansions), 2–6% of species may have no suitable niche space in 2050–2080. When potential vegetation and climate changes were combined only 1% of species showed no changes in their predicted ranges by 2050. Although some species are projected to expand ranges, this may be ecologically impossible due to potential barriers to dispersal, especially for species with poor dispersal ability. Only 1–13% of species showed no projected reductions in their current range under bioclimatic scenarios. An effective way to facilitate range shift for dispersal‐limited species is to improve landscape connectivity. If current trends in environmental change continue and species cannot expand their ranges into new areas, then the majority of bat species in SEA may show decreases in range size and increased extinction risk within the next century.     

Unpacking the mechanisms captured by a correlative species distribution model to improve predictions of climate refugia

Climate refugia are regions that animals can retreat to, persist in and potentially then expand from under changing environmental conditions. Most forecasts of climate change refugia for species are based on correlative species distribution models (SDMs) using long‐term climate averages, projected to future climate scenarios. Limitations of such methods include the need to extrapolate into novel environments and uncertainty regarding the extent to which proximate variables included in the model capture processes driving distribution limits (and thus can be assumed to provide reliable predictions under new conditions). These limitations are well documented; however, their impact on the quality of climate refugia predictions is difficult to quantify. Here, we develop a detailed bioenergetics model for the koala. It indicates that range limits are driven by heat‐induced water stress, with the timing of rainfall and heat waves limiting the koala in the warmer parts of its range. We compare refugia predictions from the bioenergetics model with predictions from a suite of competing correlative SDMs under a range of future climate scenarios. SDMs were fitted using combinations of long‐term climate and weather extremes variables, to test how well each set of predictions captures the knowledge embedded in the bioenergetics model. Correlative models produced broadly similar predictions to the bioenergetics model across much of the species' current range – with SDMs that included weather extremes showing highest congruence. However, predictions in some regions diverged significantly when projecting to future climates due to the breakdown in correlation between climate variables. We provide unique insight into the mechanisms driving koala distribution and illustrate the importance of subtle relationships between the timing of weather events, particularly rain relative to hot‐spells, in driving species–climate relationships and distributions. By unpacking the mechanisms captured by correlative SDMs, we can increase our certainty in forecasts of climate change impacts on species.     

A framework integrating physiology,dispersal and land‐use to project species ranges under climate change

To study the potential effects of climate change on species, one of the most popular approaches are species distribution models (SDMs). However, they usually fail to consider important species‐specific biological traits, such as species’ physiological capacities or dispersal ability. Furthermore, there is consensus that climate change does not influence species distributions in isolation, but together with other anthropogenic impacts such as land‐use change, even though studies investigating the relative impacts of different threats on species and their geographic ranges are still rare. Here we propose a novel integrative approach which produces refined future range projections by combining SDMs based on distribution, climate, and physiological tolerance data with empirical data on dispersal ability as well as current and future land‐use. Range projections based on different combinations of these factors show strong variation in projected range size for our study species Emberiza hortulana. Using climate and physiological data alone, strong range gains are projected. However, when we account for land‐use change and dispersal ability, future range‐gain may even turn into a future range loss. Our study highlights the importance of accounting for biological traits and processes in species distribution models and of considering the additive effects of climate and land‐use change to achieve more reliable range projections. Furthermore, with our approach we present a new tool to assess species’ vulnerability to climate change which can be easily applied to multiple species.     

Predicting Plant Diversity Patterns in Madagascar: Understanding the Effects of Climate and Land Cover Change in a Biodiversity Hotspot

Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar’s plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future.     

Assessing the impacts of climate change and land transformation on Banksia in the South West Australian Floristic Region

Aim To determine the potential combined effects of climate change and land transformation on the modelled geographic ranges of Banksia. Location Mediterranean climate South West Australian Floristic Region (SWAFR). Methods We used the species distribution modelling software Maxent to relate current environmental conditions to occurrence data for 18 Banksia species, and subsequently made spatial predictions using two simple dispersal scenarios (zero and universal), for three climate‐severity scenarios at 2070, taking the impacts of land transformation on species’ ranges into account. The species were chosen to reflect the biogeography of Banksia in the SWAFR. Results Climate‐severity scenario, dispersal scenario, biogeographic distribution and land transformation all influenced the direction and magnitude of the modelled range change responses for the 18 species. The predominant response of species to all climate change scenarios was range contraction, with exceptions for some northern and widespread species. Including land transformation in estimates of modelled geographic range size for the three climate‐severity scenarios generally resulted in smaller gains and larger declines in species ranges across both dispersal scenarios. Including land transformation and assuming zero dispersal resulted, as expected, in the greatest declines in projected range size across all species. Increasing climate change severity greatly increased the risk of decline in the 18 Banksia species, indicating the critical role of mitigating future emissions. Main conclusions The combined effects of climate change and land transformation may have significant adverse impacts on endemic Proteaceae in the SWAFR, especially under high emissions scenarios and if, as expected, natural migration is limiting. Although these results need cautious interpretation in light of the many assumptions underlying the techniques used, the impacts identified warrant a clear focus on monitoring across species ranges to detect early signs of change, and experiments that determine physiological thresholds for species in order to validate and refine the models.     

To Be Or Not to Be? Variable selection can change the projected fate of a threatened species under future climate

Species distribution models (SDMs) are commonly used to project future changes in the geographic ranges of species, to estimate extinction rates and to plan biodiversity conservation. However, these models can produce a range of results depending on how they are parameterized, and over‐reliance on a single model may lead to overconfidence in maps of future distributions. The choice of predictor variable can have a greater influence on projected future habitat than the range of climate models used. We demonstrate this in the case of the Ptunarra Brown Butterfly, a species listed as vulnerable in Tasmania, Australia. We use the Maxent model to develop future projections for this species based on three variable sets; all 35 commonly used so‐called ‘bioclimatic’ variables, a subset of these based on expert knowledge, and a set of monthly climate variables relevant to the species’ primary activity period. We used a dynamically downscaled regional climate model based on three global climate models. Depending on the choice of variable set, the species is projected either to experience very little contraction of habitat or to come close to extinction by the end of the century due to lack of suitable climate. The different conclusions could have important consequences for conservation planning and management, including the perceived viability of habitat restoration. The output of SDMs should therefore be used to define the range of possible trajectories a species may be on, and ongoing monitoring used to inform management as changes occur.     

Simulating climate change impacts on forests and associated vascular epiphytes in a subtropical island of East Asia

Aim This study aims to assess the impact of climate change on forests and vascular epiphytes, using species distribution models (SDMs). Location Island of Taiwan, subtropical East Asia. Methods A hierarchical modelling approach incorporating forest migration velocity and forest type–epiphyte interactions with classical SDMs was used to model the responses of eight forest types and 237 vascular epiphytes for the year 2100 under two climate change scenarios. Forest distributions were modelled and modified by dominant tree species’ dispersal limitations and hypothesized persistence under unfavourable climate conditions (20 years for broad‐leaved trees and 50 years for conifers). The modelled forest projections together with 16 environmental variables were used as predictors in models of epiphyte distributions. A null method was applied to validate the significance of epiphyte SDMs, and potential vulnerable species were identified by calculating range turnover rates. Results For the year 2100, the model predicted a reduction in the range of most forest types, especially for Picea and cypress forests, which shifted to altitudes c. 400 and 300 m higher, respectively. The models indicated that epiphyte distributions are highly correlated with forest types, and the majority (77–78%) of epiphyte species were also projected to lose 45–58% of their current range, shifting on average to altitudes c. 400 m higher than currently. Range turnover rates suggested that insensitive epiphytes were generally lowland or widespread species, whereas sensitive species were more geographically restricted, showing a higher correlation with temperature‐related factors in their distributions. Main conclusions The hierarchical modelling approach successfully produced interpretable results, suggesting the importance of considering biotic interactions and the inclusion of terrain‐related factors when developing SDMs for dependant species at a local scale. Long‐term monitoring of potentially vulnerable sites is advised, especially of those sites that fall outside current conservation reserves where additional human disturbance is likely to exacerbate the effect of climate change.     

The effects of climate change on a mega‐diverse country: predicted shifts in mammalian species richness and turnover in continental Ecuador

Ecuador has some of the greatest biodiversity in the world, sheltering global biodiversity hotspots in lowland and mountain regions. Climate change will likely have a major effect on these regions, but the consequences for faunal diversity and conservation remain unclear. To address this issue, we used an ensemble of eight species distribution models to predict future shifts and identify areas of high changes in species richness and species turnover for 201 mammals. We projected the distributions using two different climate change scenarios at the 2050 horizon and contrasted two extreme dispersal scenarios (no dispersal vs. full dispersal). Our results showed extended distributional shifts all over the country. For most groups, our results predicted that the current diversity of mammals in Ecuador would decrease significantly under all climate change scenarios and dispersal assumptions. The Northern Andes and the Amazonian region would remain diversity hotspots but with a significant decrease in the number of species. All predictions, including the most conservative scenarios in terms of dispersal and climate change, predicted major changes in the distribution of mammalian species diversity in Ecuador. Primates might be the most severely affected because they would have fewer suitable areas, compared with other mammals. Our work emphasizes the need for sound conservation strategies in Ecuador to mitigate the effects of climate change     

Vulnerability of Australian tropical savanna birds to climate change

Assessments of species vulnerability to climate change should increase the effectiveness of interventions in the current decline in biodiversity. Species vulnerability to climate change is a consequence of their sensitivity and adaptive capacity, in combination with their exposure to climate change. We apply a vulnerability assessment framework to 243 bird species inhabiting the tropical savannas of northern Australia. We build on previous vulnerability studies by including detailed data for variables relating to species sensitivity to change (relative abundance, clutch size, sensitivity to fire and distribution area), species adaptive capacity (movement behaviour and dietary breadth) and proportional changes predicted for their geographic range (i.e. exposure to climate change). These are integrated to provide a ranking of vulnerability. Our analysis found that birds of Australian tropical savannas cluster together with high sensitivity, with a few wide‐ranging increasing species with very low sensitivity. Australian tropical savanna birds have a range of adaptive capacities, and the impact of climate change on these species is predicted to be substantial. Two already endangered species are among the most vulnerable. Species largely restricted to Cape York Peninsula (a geographically distinct region) had the greatest overall vulnerability; these species were, in general, sensitive due to small distributions, sensitivity to fire frequency and had a lower capacity for dispersal. It will be important for the future of Australian tropical savanna birds to mitigate ecological threats and maintain extensive areas of suitable habitat to facilitate species dispersal.     

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.     

Habitat availability and gene flow influence diverging local population trajectories under scenarios of climate change: a place‐based approach

Ecological niche theory holds that species distributions are shaped by a large and complex suite of interacting factors. Species distribution models (SDMs) are increasingly used to describe species’ niches and predict the effects of future environmental change, including climate change. Currently, SDMs often fail to capture the complexity of species’ niches, resulting in predictions that are generally limited to climate‐occupancy interactions. Here, we explore the potential impact of climate change on the American pika using a replicated place‐based approach that incorporates climate, gene flow, habitat configuration, and microhabitat complexity into SDMs. Using contemporary presence–absence data from occupancy surveys, genetic data to infer connectivity between habitat patches, and 21 environmental niche variables, we built separate SDMs for pika populations inhabiting eight US National Park Service units representing the habitat and climatic breadth of the species across the western United States. We then predicted occurrence probability under current (1981–2010) and three future time periods (out to 2100). Occurrence probabilities and the relative importance of predictor variables varied widely among study areas, revealing important local‐scale differences in the realized niche of the American pika. This variation resulted in diverse and – in some cases – highly divergent future potential occupancy patterns for pikas, ranging from complete extirpation in some study areas to stable occupancy patterns in others. Habitat composition and connectivity, which are rarely incorporated in SDM projections, were influential in predicting pika occupancy in all study areas and frequently outranked climate variables. Our findings illustrate the importance of a place‐based approach to species distribution modeling that includes fine‐scale factors when assessing current and future climate impacts on species’ distributions, especially when predictions are intended to manage and conserve species of concern within individual protected areas.     

Uncertainty in predictions of range dynamics: black grouse climbing the Swiss Alps

Empirical species distribution models (SDMs) constitute often the tool of choice for the assessment of rapid climate change effects on species’ vulnerability. Conclusions regarding extinction risks might be misleading, however, because SDMs do not explicitly incorporate dispersal or other demographic processes. Here, we supplement SDMs with a dynamic population model 1) to predict climate‐induced range dynamics for black grouse in Switzerland, 2) to compare direct and indirect measures of extinction risks, and 3) to quantify uncertainty in predictions as well as the sources of that uncertainty. To this end, we linked models of habitat suitability to a spatially explicit, individual‐based model. In an extensive sensitivity analysis, we quantified uncertainty in various model outputs introduced by different SDM algorithms, by different climate scenarios and by demographic model parameters. Potentially suitable habitats were predicted to shift uphill and eastwards. By the end of the 21st century, abrupt habitat losses were predicted in the western Prealps for some climate scenarios. In contrast, population size and occupied area were primarily controlled by currently negative population growth and gradually declined from the beginning of the century across all climate scenarios and SDM algorithms. However, predictions of population dynamic features were highly variable across simulations. Results indicate that inferring extinction probabilities simply from the quantity of suitable habitat may underestimate extinction risks because this may ignore important interactions between life history traits and available habitat. Also, in dynamic range predictions uncertainty in SDM algorithms and climate scenarios can become secondary to uncertainty in dynamic model components. Our study emphasises the need for principal evaluation tools like sensitivity analysis in order to assess uncertainty and robustness in dynamic range predictions. A more direct benefit of such robustness analysis is an improved mechanistic understanding of dynamic species’ responses to climate change.     

Cumulative effects of land use,altered fire regime and climate change on persistence of Ceanothus verrucosus,a rare,fire‐dependent plant species

Mediterranean ecosystems are among the highest in species richness and endemism globally and are also among the most sensitive to climate and land‐use change. Fire is an important driver of ecosystem processes in these systems; however, fire regimes have been substantially changed by human activities. Climate change is predicted to further alter fire regimes and species distributions, leading to habitat loss and threatening biodiversity. It is currently unknown what the population‐level effects of these landscape‐level changes will be. We linked a spatially explicit stochastic population model to dynamic bioclimate envelopes to investigate the effects of climate change, habitat loss and fragm entation and altered fire regime on population abundances of a long‐lived obligate seeding shrub, Ceanothus verrucosus, a rare endemic species of southern California. We tested a range of fire return intervals under the present and two future climate scenarios. We also assessed the impact of potential anthropogenic land‐use change by excluding land identified as developable by local governments. We found that the 35–50 year fire return interval resulted in the highest population abundances. Expected minimum population abundance (EMA) declined gradually as fire return interval increased, but declined dramatically for shorter fire intervals. Simulated future development resulted in a 33% decline in EMA, but relatively stable population trajectories over the time frame modeled. Relative changes in EMA for alternative fire intervals were similar for all climate and habitat loss scenarios, except under the more severe climate scenario which resulted in a change in the relative ranking of the fire scenarios. Our results show climate change to be the most serious threat facing obligate seeding shrubs embedded in urban landscapes, resulting in population decline and increased local extirpation, and that likely interactions with other threats increase risks to these species. Taking account of parameter uncertainty did not alter our conclusions.