Understanding and predicting how species will respond to climate change is crucial for biodiversity conservation. Here, we assessed future climate change impacts on the distribution of a rare and endangered plant species, Davidia involucrate in China, using the most recent global circulation models developed in the sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC6). We assessed the potential range shifts in this species by using an ensemble of species distribution models (SDMs). The ensemble SDMs exhibited high predictive ability and suggested that the temperature annual range, annual mean temperature, and precipitation of the driest month are the most influential predictors in shaping distribution patterns of this species. The projections of the ensemble SDMs also suggested that D. involucrate is very vulnerable to future climate change, with at least one‐third of its suitable range expected to be lost in all future climate change scenarios and will shift to the northward of high‐latitude regions. Similarly, at least one‐fifth of the overlap area of the current nature reserve networks and projected suitable habitat is also expected to be lost. These findings suggest that it is of great importance to ensure that adaptive conservation management strategies are in place to mitigate the impacts of climate change on D. involucrate.

Understanding and predicting how species will respond to global environmental change (i.e., climate and land use change) is essential to efficiently inform conservation and management strategies for authorities and managers. Here, we assessed the combined effect of future climate and land use change on the potential range shifts of the giant pandas (Ailuropoda melanoleuca) in Sichuan Province, China. We used species distribution models (SDMs) to forecast range shifts of the giant pandas by the 2050s and 2070s under four combined climate and land use change scenarios. We also compared the differences in distributional changes of giant pandas among the five mountains in the study area. Our SDMs exhibited good model performance and were not overfitted, with a mean Boyce index of 0.960 0.015 and a mean omission rate of 0.002 0.003, and suggested that precipitation seasonality, annual mean temperature, the proportion of forest cover, and total annual precipitation are the most important factors in shaping the current distribution pattern of the giant pandas. Our projections of future species distribution also suggested a range expansion under an optimistic greenhouse gas emission, while suggesting a range contraction under a pessimistic greenhouse gas emission. Moreover, we found that there is considerable variation in the projected range change patterns among the five mountains in the study area. Especially, the suitable habitat of the giant panda is predicted to increase under all scenarios in the Minshan mountains, while is predicted to decrease under all scenarios in Daxiangling and Liangshan mountains, indicating the vulnerability of the giant pandas at low latitudes. Our findings highlight the importance of an integrated approach that combines climate and land use change to predict the future species distribution and the need for a spatial explicit consideration of the projected range change patterns of target species for guiding conservation and management strategies.

Theaceae is an important family in the phylogeny of angiosperm in China, which are potentially threatened by future changes in climatic and land use conditions. Therefore, understanding and predicting the isolated and combined effects of these two global change factors on Theaceae species is crucial for biodiversity conservation. Here, we assessed the isolated and combined effects of climate and land use change on the distribution shifts of 95 Theaceae species under different future scenarios by comparing projections of three model configurations: (1) dynamics climate and constant land use variables; (2) constant climate and dynamics land use variables; and (3) dynamics climate and dynamics land use variables. We find that all the three types of models predicted range contractions for most of the 95 Theaceae species under all future scenarios. Moreover, we find that climate change has rather strong effect for most species while land use change has nonsignificant or weak effect on future species distributions, although both of these two isolated effects are highly variable across individual species. Finally, the combined effect of these two factors reveals that the land use change may amplify or buffer distribution shifts expected from climate change impact depending on species. These findings emphasize the importance of taking into account the large variability in response to land use change among Theaceae species when developing land‐based conservation strategies in a changing climate.

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.

Understanding the patterns and drivers of different facets of biodiversity is crucial for biodiversity conservation under global environmental change. In this study, we present the first assessment of the patterns of taxonomic, functional and phylogenetic diversity for 171 mammals in the giant panda range and their associations with climate, land use factors and topographic heterogeneity. We found that functional diversity showed a very different pattern with species richness and phylogenetic diversity. Additionally, mammal assemblages were more functionally diverse but phylogenetically similar than expected by chance in very few regions after controlling for species richness. Furthermore, species richness was positively correlated with topographic heterogeneity, the proportion of forest, mean annual temperature and temperature anomaly and negatively correlated with annual precipitation and precipitation anomaly between current and historical periods, while both functional and phylogenetic diversity are predominantly correlated with climate factors. Specifically, higher functional and phylogenetic diversity was mainly found in regions with a lower proportion of cropland, annual precipitation, mean annual temperature and precipitation anomaly between current and historical periods. These results indicate the large mismatches of driving factors between taxonomic diversity and the other diversity facets and the importance of contemporary climate and land use conditions and climate anomaly between current and historical periods in determining mammal functional and phylogenetic diversity in the giant panda range. Overall, our findings highlight the importance of integrating multiple dimensions of diversity to infer the underlying processes determining the spatial pattern of biodiversity and to better inform conservation management and planning.