Potential impacts of climate and landscape fragmentation changes on plant distributions: Coupling multi-temporal satellite imagery with GIS-based cellular automata model

Climate change and landscape fragmentation are considered to be the main treats to biodiversity. In this study, probable alteration of future species distribution was tested based on the association of landscape fragmentation and climate change scenarios compared to the classical approach that assumed an unchanged landscape. Also, projected range shifts including realistic dispersal scenarios were compared with classical models, in which no or full dispersal has been supposed.A GIS-based cellular automata model, MigClim, was implemented to projection of future distribution over the 21st century for three plant species in a study area of the central Germany. For each species, simulations were run for four dispersal scenarios (full dispersal, no dispersal, realistic dispersal, and realistic dispersal with long-distance dispersal events), two landscape fragmentation (static and dynamic change) and two climate change (RCP4.5 and RCP8.5) scenarios. In this research, temporal satellite data were utilized to simulate landscape changes by the use of a hybrid (CA-Markov) model for the years 2020, 2040, 2060 and 2080.A significant difference appears to be between the simulations of realistic dispersal limitations and those considering full or no dispersal for projected future distributions. Although simulations accounting for dispersal limitations produced, for our study area, results that were closer to no dispersal than to full dispersal. Additionally, our results revealed that change in landscape fragmentation is more effective than the climate change impacts on species distributions in this study.     

Forecasting the future of biodiversity: a test of single‐ and multi‐species models for ants in North America

The geographic distributions of many taxonomic groups remain mostly unknown, hindering attempts to investigate the response of the majority of species on Earth to climate change using species distributions models (SDMs). Multi‐species models can incorporate data for rare or poorly‐sampled species, but their application to forecasting climate change impacts on biodiversity has been limited. Here we compare forecasts of changes in patterns of ant biodiversity in North America derived from ensembles of single‐species models to those from a multi‐species modeling approach, Generalized Dissimilarity Modeling (GDM). We found that both single‐ and multi‐species models forecasted large changes in ant community composition in relatively warm environments. GDM predicted higher turnover than SDMs and across a larger contiguous area, including the southern third of North America and notably Central America, where the proportion of ants with relatively small ranges is high and where data limitations are most likely to impede the application of SDMs. Differences between approaches were also influenced by assumptions regarding dispersal, with forecasts being more similar if no‐dispersal was assumed. When full‐dispersal was assumed, SDMs predicted higher turnover in southern Canada than did GDM. Taken together, our results suggest that 1) warm rather than cold regions potentially could experience the greatest changes in ant fauna under climate change and that 2) multi‐species models may represent an important complement to SDMs, particularly in analyses involving large numbers of rare or poorly‐sampled species. Comparisons of the ability of single‐ and multi‐species models to predict observed changes in community composition are needed in order to draw definitive conclusions regarding their application to investigating climate change impacts on biodiversity.     

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.     

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     

Using niche-based modelling to assess the impact of climate change on tree functional diversity in Europe

Rapid anthropogenic climate change is already affecting species distributions and ecosystem functioning worldwide. We applied niche-based models to analyse the impact of climate change on tree species and functional diversity in Europe. Present-day climate was used to predict the distributions of 122 tree species from different functional types (FT). We then explored projections of future distributions under one climate scenario for 2080, considering two alternative dispersal assumptions: no dispersal and unlimited dispersal. The species-rich broadleaved deciduous group appeared to play a key role in the future of different European regions. Temperate areas were projected to lose both species richness and functional diversity due to the loss of broadleaved deciduous trees. These were projected to migrate to boreal forests, thereby increasing their species richness and functional diversity. Atlantic areas provided an intermediate case, with a predicted reduction in the numbers of species and occasional predicted gains in functional diversity. This resulted from a loss in species within the broadleaved deciduous FT, but overall maintenance of the group. Our results illustrate the fact that both species-specific predictions and functional patterns should be examined separately in order to assess the impacts of climate change on biodiversity and gain insights into future ecosystem functioning.     

Dispersal based climate change sensitivity scores for European species

Assessments of climate change impacts on species are needed for anticipating potential biodiversity losses. Climate change impacts on species are often simulated with climate envelope models, but most climate envelope models do not account for dispersal limitations. Most studies only consider two extreme (and unrealistic) dispersal options: no dispersal versus full dispersal. This study attempts to include dispersal limitation into the calculation of climate change sensitivity scores for a range of vertebrate and plant species. We calculate climate change sensitivity scores -expressed as an index- by using the 'spatial turnover' of a species under climate change, defined as the projected difference between current and future area occupied by a species within a region, and include a dispersal factor to account for dispersal limitations. We calculate climate sensitivity scores with three dispersal factors: d₀ (no dispersal), d₁ (full dispersal) and with an estimated value of d calculated directly from species specific dispersal data and literature estimates (d_e). We compared climate sensitivity scores across species groups and European bio-geographical regions in order to determine whether explicitly accounting for dispersal limitations causes significant differences in sensitivity for climate change. Our results show that the climate sensitivity scores calculated with d_e differ slightly from d₀ (no dispersal), but differ significantly from d₁ (full dispersal) for the less mobile species groups (amphibian, reptiles, plants). This indicates that assuming full dispersal significantly overestimates the future distribution in Europe under climate change for these species, whereas assuming no dispersal may slightly underestimates this. However, this conclusion could not be drawn for the more mobile birds and mammas: climate sensitivity scores calculated with d_e are approximately intermediate of those calculated with d₀ (no dispersal) and d₁ (full dispersal). This indicates that assuming either no or full dispersal results in poor estimates of the future distribution of these species in Europe under climate change, and that dispersal capacity should therefore always be considered when assessing climate change impacts on these species. Disaggregating climate sensitivity scores per European bio-geographical regions reveals that regional climate sensitivity scores are similar to the European level.     

Ancient woodland indicators signal the climate change risk for dispersal-limited species

The climate change risk to biodiversity operates alongside a range of anthropogenic pressures. These include habitat loss and fragmentation, which may prevent species from migrating between isolated habitat patches in order to track their suitable climate space. Predictive modelling has advanced in scope and complexity to integrate: (i) projected shifts in climate suitability, with (ii) spatial patterns of landscape habitat quality and rates of dispersal. This improved ecological realism is suited to data-rich model species, though its broader generalisation comes with accumulated uncertainties, e.g. incomplete knowledge of species response to variable habitat quality, parameterisation of dispersal kernels etc. This study adopts ancient woodland indicator species (lichen epiphytes) as a guild that couples relative simplicity with biological rigour. Subjectively-assigned indicator species were statistically tested against a binary habitat map of woodlands of known continuity (>250 yr), and bioclimatic models were used to demonstrate trends in their increased/decreased environmental suitability under conditions of ‘no dispersal’. Given the expectation of rapid climate change on ecological time-scales, no dispersal for ancient woodland indicators becomes a plausible assumption. The risk to ancient woodland indicators is spatially structured (greater in a relative continental compared to an oceanic climatic zone), though regional differences are weakened by significant variation (within regions) in woodland extent. As a corollary, ancient woodland indicators that are sensitive to projected climate change scenarios may be excellent targets for monitoring climate change impacts for biodiversity at a site-scale, including the outcome of strategic habitat management (climate change adaptation) designed to offset risk for dispersal-limited species.     

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.     

Effects of climate change on biodiversity: a review and identification of key research issues

Current knowledge of effects of climate change on biodiversity is briefly reviewed, and results are presented of a survey of biological research groups in the Netherlands, aimed at identifying key research issues in this field. In many areas of the world, biodiversity is being reduced by humankind through changes in land cover and use, pollution, invasions of exotic species and possibly climate change. Assessing the impact of climate change on biodiversity is difficult, because changes occur slowly and effects of climate change interact with other stress factors already imposed on the environment. Research issues identified by Dutch scientists can be grouped into: (i) spatial and temporal distributions of taxa; (ii) migration and dispersal potentials of taxa; (iii) genetic diversity and viability of (meta) populations of species; (iv) physiological tolerance of species; (v) disturbance of functional interactions between species; and (vi) ecosystem processes. Additional research should be done on direct effects of greenhouse gases, and on interactions between effects of climate change and habitat fragmentation. There are still many gaps in our knowledge of effects of climate change on biodiversity. An interdisciplinary research programme could possibly focus only on one or few of the identified research issues, and should generate input data for predictive models based on climate change scenarios.     

From climate change predictions to actions – conserving vulnerable animal groups in hotspots at a regional scale

Current climate change is a major threat to biodiversity. Species unable to adapt or move will face local or global extinction and this is more likely to happen to species with narrow climatic and habitat requirements and limited dispersal abilities, such as amphibians and reptiles. Biodiversity losses are likely to be greatest in global biodiversity hotspots where climate change is fast, such as the Iberian Peninsula. Here we assess the impact of climate change on 37 endemic and nearly endemic herptiles of the Iberian Peninsula by predicting species distributions for three different times into the future (2020, 2050 and 2080) using an ensemble of bioclimatic models and different combinations of species dispersal ability, emission levels and global circulation models. Our results show that species with Atlantic affinities that occur mainly in the North‐western Iberian Peninsula have severely reduced future distributions. Up to 13 species may lose their entire potential distribution by 2080. Furthermore, our analysis indicates that the most critical period for the majority of these species will be the next decade. While there is considerable variability between the scenarios, we believe that our results provide a robust relative evaluation of climate change impacts among different species. Future evaluation of the vulnerability of individual species to climate change should account for their adaptive capacity to climate change, including factors such as physiological climate tolerance, geographical range size, local abundance, life cycle, behavioural and phenological adaptability, evolutionary potential and dispersal ability.     

Recalculating route: dispersal constraints will drive the redistribution of Amazon primates in the Anthropocene

Climate change will redistribute the global biodiversity in the Anthropocene. As climates change, species might move from one place to another, due to local extinctions and colonization of new environments. However, the existence of permeable migratory routes precedes faunal migrations in fragmented landscapes. Here, we investigate how dispersal will affect the outcome of climate change on the distribution of Amazon's primate species. We modeled the distribution of 80 Amazon primate species, using ecological niche models, and projected their potential distribution on scenarios of climate change. Then, we imposed landscape restrictions to primate dispersal, derived from a natural biogeographical barrier to primates (the main tributaries of the Amazon river) and an anthropogenic constraint to the migration of many canopy‐dependent animals (deforested areas). We also highlighted potential conflict zones, i.e. regions of high migration potential but predicted to be deforested. Species response to climate change varied across dispersal limitation scenarios. If species could occupy all newly suitable climate, almost 70% of species could expand ranges. Including dispersal barriers (natural and anthropogenic), however, led to range expansion in only less than 20% of the studied species. When species were not allowed to migrate, all of them lost an average of 90% of the suitable area, suggesting that climate may become unsuitable within their present distributions. All Amazon primate species may need to move as climate changes to avoid deleterious effects of exposure to non‐analog climates. The effect of climate change on the distribution of Amazon primates will ultimately depend on whether landscape permeability will allow climate‐driven faunal migrations. The network of protected areas in the Amazon could work as ‘stepping stones’ but most are outside important migratory routes. Therefore, protecting important dispersal corridors is foremost to allow effective migrations of the Amazon fauna in face of climate change and deforestation.     

全球变化情景下的中国木本植物受威胁物种名录

生物多样性正面临快速丧失的风险, 气候和土地利用变化已成为生物多样性的主要威胁之一。受威胁物种名录是区域和全球生物多样性保护的重要基础数据, 也是保护区规划的基础。作为一个生物多样性大国, 中国已开展了高等植物受威胁状况的系统性评估, 建立了受威胁植物名录, 为植物多样性保护规划提供了支撑。但由于数据和方法限制, 现有受威胁植物名录制定时未定量考虑全球变化对植物分布的潜在影响, 因而可能低估物种的受威胁等级及未来生物多样性的丧失风险。本研究基于高精度的木本植物分布数据和物种分布模型, 评估了未来气候和土地利用变化对木本植物分布的潜在影响。基于每个物种适宜分布区大小的变化, 并依据IUCN红色名录评估指标A3c的阈值标准, 更新了木本植物的受威胁等级, 补充了未来中国潜在受威胁木本植物名录。结果显示: 综合不同的气候变化情景(RCP 2.6、RCP 6.0和RCP 8.5)和扩散情景(完全扩散、20 km/10年、不扩散), 约12.9%-40.5%的木本植物被评估为受威胁物种。该名录将为制定木本植物保护优先级、开展保护区规划、提升全球变化情景下的生物多样性保护成效提供基础数据, 也为其他类群制定全面的受威胁物种名录提供参考。     

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.     

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.     

Climate change and plant dispersal along corridors in fragmented landscapes of Mesoamerica

Climate change is a threat to biodiversity, and adaptation measures should be considered in biodiversity conservation planning. Protected areas (PA) are expected to be impacted by climate change and improving their connectivity with biological corridors (BC) has been proposed as a potential adaptation measure, although assessing its effectiveness remains a challenge. In Mesoamerica, efforts to preserve the biodiversity have led to the creation of a regional network of PA and, more recently, BC. This study evaluates the role of BC for facilitating plant dispersal between PA under climate change in Mesoamerica. A spatially explicit dynamic model (cellular automaton) was developed to simulate species dispersal under different climate and conservation policy scenarios. Plant functional types (PFT) were defined based on a range of dispersal rates and vegetation types to represent the diversity of species in the region. The impacts of climate change on PA and the role of BC for dispersal were assessed spatially. Results show that most impacted PA are those with low altitudinal range in hot, dry, or high latitude areas. PA with low altitudinal range in high cool areas benefit the most from corridors. The most important corridors cover larger areas and have high altitude gradients. Only the fastest PFT can keep up with the expected change in climate and benefit from corridors for dispersal. We conclude that the spatial assessment of the vulnerability of PA and the role of corridors in facilitating dispersal can help conservation planning under a changing climate.     

Do climate envelope models transfer? A manipulative test using dung beetle introductions

Climate envelope models (CEMs) are widely used to forecast future shifts in species ranges under climate change, but these models are rarely validated against independent data, and their fundamental assumption that climate limits species distributions is rarely tested. Here, we use the data on the introduction of five South African dung beetle species to Australia to test whether CEMs developed in the native range can predict distribution in the introduced range, where the confounding effects of dispersal limitation, resource limitation and the impact of natural enemies have been removed, leaving climate as the dominant constraint. For two of the five species, models developed in the native range predict distribution in the introduced range about as well as models developed in the introduced range where we know climate limits distribution. For the remaining three species, models developed in the native range perform poorly, implying that non-climatic factors limit the native distribution of these species and need to be accounted for in species distribution models. Quantifying relevant non-climatic factors and their likely interactions with climatic variables for forecasting range shifts under climate change remains a challenging task.     

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.     

Predicting future distributions of mountain plants under climate change: does dispersal capacity matter?

Many studies have investigated the potential impacts of climate change on the distribution of plant species, but few have attempted to constrain projections through plant dispersal limitations. Instead, most studies published so far have simplified dispersal as either unlimited or null. However, depending on the dispersal capacity of a species, landscape fragmentation, and the rate of climatic change, these assumptions can lead to serious over- or underestimation of the future distribution of plant species.
To quantify the discrepancies between simulations accounting for dispersal or not, we carried out projections of future distribution over the 21st century for 287 mountain plant species in a study area of the western Swiss Alps. For each species, simulations were run for four dispersal scenarios (unlimited dispersal, no dispersal, realistic dispersal, and realistic dispersal with long-distance dispersal events) and under four climate change scenarios.
Although simulations accounting for realistic dispersal limitations did significantly differ from those considering dispersal as unlimited or null in terms of projected future distribution, the unlimited dispersal simplification did nevertheless provide good approximations for species extinctions under more moderate climate change scenarios. Overall, simulations accounting for dispersal limitations produced, for our mountainous study area, results that were significantly closer to unlimited dispersal than to no dispersal. Finally, analysis of the temporal pattern of species extinctions over the entire 21st century revealed that important species extinctions for our study area might not occur before the 2080–2100 period, due to the possibility of a large number of species shifting their distribution to higher elevation.     

气候变化对7种乔木植物分布的潜在影响

利用CART（classification and regression tree,分类和回归树）生态位模型,采用A2和B2气候情景,分析了气候变化对秦岭冷杉、祁连圆柏、楠木、麦吊云杉、马尾树、领春木和连香树分布范围及空间格局的影响。结果显示：气候变化下,这些植物目前适宜分布范围呈现缩小趋势;新适宜及总适宜分布范围,连香树、马尾树、楠木和祁连圆柏呈现减少趋势,秦岭冷杉在1991-2020年及2021-2050年时段呈现减少趋势,之后增加,其它植物呈现增加趋势。气候变化下,马尾树目前适宜分布的东南部一些区域将不再适宜,新适宜分布区将向西南、北部、西部和东北部一些区域扩展;秦岭冷杉目前适宜分布的东南部和东部一些区域将不再适宜,新适宜分布区将向西南部、西北部和西部一些区域扩展;其它植物目前适宜分布的东部、东南部、南部及东北部一些区域将不再适宜,新适宜分布区将向西部和西南部一些区域扩展。气候变化下,这些植物适宜分布范围与年均气温和降水量变化相关性并不一致,一些植物适宜分布范围与年均气温和降水量变化相关系数不显著。另外,一些植物适宜范围与年降水量和年均气温变化多元线性回归关系决定系数较小。结果说明,气候变化下,目前适宜范围缩小,新适宜范围主要向高海拔扩展,不同植物适宜分布范围与年均气温和年降水量变化的关系不同。     

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.