PJB-2023-389
Predicting suitable habitat for China’s endangered plant Cycas segmentifida using MaxEnt under climate change
Lijuan Wei
Abstract
Demarcating a plant species' actual and potential biogeographical distribution is crucial for understanding the key environmental variables shaping its habitat conditions. We used MaxEnt and QGIS species distribution modeling to predict the likely range of China’s endangered species, Cycas segmentifida, based on 38 validated distribution records and eight selected environmental variables under current climatic conditions. Combined with percentage contribution and permutation importance, the jackknife statistical method was applied to test and evaluate pertinent factors restricting the potential distribution of C. segmentifida. The results showed that Maxent model performed better than random with an average test AUC value of 0.994. According to species response curves, this species preferred habitats with precipitation of the warmest quarter (Bio18) from 540 to 780 mm, and temperature seasonality (Bio4) of 420 to 640 ℃. The current core potential distribution areas are concentrated in Guangxi, Guizhou, and Yunnan provinces in Southwest China. and had the greatest impact on the distribution area of C. segmentifida. The findings could offer scientific guidance to improve the management and conservation of this declining species.
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