[Responses of Larix gmelinii geographical distribution to future climate change: a simulation study].

With warmth index, coldness index, humidity index, mean annual precipitation, minimum temperature in January, and maximum temperature in July as environmental variables, and by using Generalized Linear Model (GLM), Stepwise Generalized Linear Model (SGLM), Generalized Additive Model (GAM), and Classification and Regression Tree (CART), this paper simulated the geographical distribution of Larix gemelinii under the conditions of future climate change. Cohen's Kappa and the area under the Receiver Operating Characteristic curve were used to evaluate the performance of the models, and the most suitable model was selected to predict the geographical distribution. The results showed that all the test models except GLM could simulate the geographical distribution of L. gmelinii very well, and GAM performed best. Climate change would result in a reduction in the suitable area of L. gmelinii by 58.1% under SRES-A2 scenario and by 66.4% under SRES-B2 scenario in 2020. The suitable area of L. gmelinii would be further reduced by 99.7% under SRES-A2 scenario and by 97.9% under SRES-B2 scenario in 2050, and completely disappeared under both scenarios in 2100.