Abstract
Climate change significantly influences changes in ecological phenomena and processes, such as species distribution and phenology, thus accelerating the rate of species extinction or prosperity. Climate change is considered to be one of the most important threats to global biodiversity in the 21st century and will pose significant challenges to biodiversity conservation in the future. The use of niche modelling to predict changes in the suitable distribution of species under climate change scenarios is becoming a hot topic of biological conservation. In this study, we use data from China’s National Forest Continuous Inventory as well as specimen collection data of Cunninghamia lanceolata (Lamb.) Hook to run optimized Maxent models to predict potential suitable distribution of the species in the present day, 2050s, and 2070s under different climate change scenarios in China. In the modeling process, the most important uncorrelated variables were chosen, and the sample-size-adjusted Akaike information criterion (AICc) was used to select the optimal combination of feature type and regularization multiplier. Variable selection reduced the number of variables used and the complexity of the model, and the use of the AICc reduced overfitting. Variables relating to precipitation were more important than temperature variables in predicting C. lanceolata distribution in the optimal model. The predicted suitable distribution areas of C. lanceolata were different for the different periods under different climate change scenarios, with the centroids showing a degree of northward movement. The suitable distribution area is predicted to become more fragmented in the future. Our results reveal the climate conditions required for the suitable distribution of C. lanceolata in China and the likely changes to its distribution pattern in the future, providing a scientific basis for the sustainable management, protection, and restoration of the suitable habitat of this economically important tree species in the context of climate change.
Highlights
Climate is the main factor determining the distribution pattern of plants, and changes in this distribution pattern are a direct reflection of climate change [1,2,3,4,5]
The predicted suitable distribution areas of C. lanceolata were different for the different periods under different climate change scenarios, with the centroids showing a degree of northward movement
We used present-day occurrence data to predict the potential suitable distribution area of C. lanceolata in China based on an optimized Maxent model under different climate change scenarios
Summary
Climate is the main factor determining the distribution pattern of plants, and changes in this distribution pattern are a direct reflection of climate change [1,2,3,4,5]. The Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) indicates that the annual mean temperature of the Earth’s surface has increased by 0.85 ◦ C over the past 130 years (1880–2012). While the mean temperature of the past 60 years (1951–2012) has increased by 0.72 ◦ C. The mean global surface temperature is predicted to increase by an additional 0.3–4.8 ◦ C by the end of the 21st century, according to simulations of greenhouse gas emission scenarios [6]. Quantitative analysis of climate factors and predictions of climate change impacts on potential suitable species distributions have become key to biogeography and global change research [8,10,11]
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