Predicting the Potential Habitat Distribution of Relict Plant Davidia involucrata in China Based on the MaxEnt Model

Davidia involucrata Baill. 1871 (D. involucrata), as a tertiary relict plant unique to China, is a national Class I protected plant with high economic value. Oil extracted from its seeds and peels can be used for both consumption and industrial purposes. It has become a popular income-earning export tree in China because of its graceful posture and beautiful white bracts. Climate change affects the distribution of the species’ potential habitat areas. Thus, studying its natural distribution pattern and future potential habitat distribution changes has great significance for the sustainable resource utilization and biodiversity conservation of D. involucrata. Here, we employed the MaxEnt model and ArcGIS software to predict the current and future (the 2050s and 2070s) potential habitats of D. involucrata via 130 species distribution records and 37 environmental variables. Meanwhile, we used the jackknife method to assess the importance of environmental factors. Our results showed the following: (1) When the RM = 4 and FC = LQHPT, the MaxEnt model exhibited the lowest complexity and overfitting degree while achieving high model prediction accuracy. The area under the curve (AUC) value of the simulated training was 0.958, indicating an excellent forecast. (2) Under the current climate scenario, D. involucrata was mainly concentrated in eastern Sichuan, western Hubei, northern Guizhou, and northwestern Hunan, with an area of 98.02 × 104 km2. (3) The precipitation in the warmest quarter (Bio18, 30%), mean temperature in the driest quarter (Bio9, 24.4%), annual mean radiation (Bio20, 14.6%), and elevation (ele, 12.7%) were the main environmental factors affecting its habitat distribution; the t contribution was 82.1%. (4) Under different future climate scenarios, the potential habitat area of D. involucrata decreased overall. Compared with the current climate scenario, the areas of potential habitats gradually decreased in both the 2050s and 2070s under the ssp126 and ssp585 climate scenarios but decreased in the 2050s and then increased in the 2070s under the ssp370 climate scenario. Therefore, it is of great significance to track and monitor the existing population or community on the basis of the possible changes in its distribution area. Moreover, the artificial breeding of its seedlings should be considered in the future to improve the quality of its germplasm resources. In summary, our findings can provide a scientific understanding of D. involucrata distribution in China and are conducive to conservation and utilization.