Prediction of Potential Suitable Areas of Podocarpus neriifolius in China under Climate Change Scenarios
Studying the potential habitable zones of Podocarpus neriifolius in China under climate change can help in the development of future conservation strategies.In this study,based on the data from 39 effective distribution points and 19 climatic variables,the MaxEnt model,ArcGIS,R software was used to predict the potential habitable zones of P.neriifolius in China under different development paths(SSP126,SSP245,SSP370,SSP585)in the pres-ent(1970-2000)and the future(2050s and 2070s),and to analyze the spatial and temporal variation rules of the habitable zones as well as the migration trajectories of the center of mass quantitatively.The center of mass migration trajectories were analyzed,and finally,the area AUC value under the adopted ROC curve was used to determine the model accuracy.The results showed that:(1)The AUC values of each group of models were greater than 0.972,and the model predictions were excellent.(2)Temperature seasonality,precipitation of driest quarter,temperature annual range,annual mean temperature,and precipitation of wettest month were the dominant climatic factors affecting the distribution of P.neriifolius.(3)Under the former climatic conditions,the total habitable area of P.neriifolius was 89.39×104 km2,accounting for about 9.3%of China's national land area,and was mainly located in Southwest China,South China,and parts of East China.(4)Changes in the total suitable area for P.neriifolius under future cli-mate scenarios are small(within 10%).(5)Under the climate change scenario,the main areas of change in the po-tential habitat of P.neriifolius are concentrated in southeastern Sichuan,western Guangxi,central Guizhou and northern Yunnan.From the present to the future,the distribution center of gravity of the suitable areas of P.neriifolius will change in the direction of migration to the southeast first,and then to the northwest.
Podocarpus neriifoliusMaxent modelclimate changehabitat area
万方数据
维普
