Potential distribution of Pinus kesiya var. langbianensis in Yunnan province based on maximum entropy model

To predict the potential distribution area of Simao pine (Pinus kesiya var. langbianensis) in Yunnan province and to explore the dominant environmental variables affecting the potential distribution, so as to provide the basis for the matching the site with trees and scientific management of Simao pine.

The actual distribution of Simao pine was determined using National Forest Inventory data from permanent sample plots in Yunnan province. A total of 19 bioclimatic variables, 3 topographic variables and 11 soil variables affecting stand growth were selected to simulate the potential distribution area of Simao pine in Yunnan using the maximum entropy model (Maxent). The accuracy of the model was evaluated by the area under the curve (AUC), and the jackknife method was used to analyse the importance of the influence of environmental variables on the potential distribution area of Simao pine. Finally, the potential distribution area of the Simao pine was classified using the equal interval method based on the logical value of the probability of existence (P).

The Simao pine Maxent model has excellent prediction accuracy, with an average AUC of 0.921 over 10-fold cross-validation. According to the final contribution rate of each variable in the model, the main environmental variables affecting the potential distribution of Simao pine were temperature and precipitation, followed by soil and topographic variables. The jackknife test results showed that the top five dominant environmental variables affecting the potential distribution of Simao pine were mean temperature of driest quarter (Bio9), isothermality (Bio3), precipitation of wettest month (Bio13), mean temperature of wettest quarter (Bio8) and precipitation seasonality (Bio15). The core suitable area of Simao pine was mainly distributed in Puer city, followed by Lincang city and Xishuangbanna Prefecture, and a small amount was distributed in Yuxi city and Honghe Prefecture.

The maximum entropy model could well predict the potential distribution area of Simao pine in Yunnan province, and the selected dominant environmental variables affecting the potential distribution area of Simao pine and their thresholds were reasonable. The formed suitability grade diagram of potential distribution of Simao pine could provide a basis for matching site with trees and scientific management.