MaxEnt model-based prediction of potential distribution of Liriodendron chinense in China

Abstract

Objective The aim is to scientifically and rationally develop protective measures for Liriodendron chinense. Method Maximum Entropy Model (MaxEnt) and Geographic Information System (ArcGIS)were adopted to predict the potential distribution areas of L. chinense, and to explore the dominant environmental factors of L. chinense under various climate change scenarios. Result The mean AUC of the training data was 0.973, and the AUC of the test data reached 0.953, indicating that MaxEnt model had a good predicting ability. The annual precipitation, precipitation of wettest quarter, min temperature of coldest month, precipitation of seasonality and monthly mean temperature difference were predicted to be five main factors affecting the distribution of L. chinense, with a total contribution rate of over 80%. The intensity of human activities was 2.3%. Then MaxEnt model was imported into GIS to classify the suitable areas, and the results showed that the highly suitable distribution areas of L. chinense ranged from south of Daba Mountain to the north-central part of Guizhou in Southwest China; its southernmost part extended to the hilly area in the southern part of Zhejiang Province and the northern part of Fujian Province while its northernmost part reached the Tianmu Mountain in East China, which was similar with the investigation before. Meanwhile, the distribution of L. chinense in China under different RCP scenarios of the 2050s and 2070s was simulated. The study showed that the potential distribution area would move to higher latitudes, and the area would remain stable and then decline with the growth of the year. In 2070s under the climate scenario of RCP 8.5, the distribution area of L. chinense would decrease by 5.3% compared with the current period. These were consistent with the results of previous studies on the reduction of biogenic suitable area in the context of global warming. Conclusion The predictions indicated that climate change would affect the distribution of L. chinense populations, and would provide a reference for the future cultivation and ex-situ conservation of L. chinense too.