Optimizing MaxEnt to project habitat shifts of Idesia polycarpa var. vestita Diels, a bioenergy tree, in China under climate change scenarios

Abstract

Climate change is reshaping the distribution of plant species worldwide, yet the ecological niche and future habitat trajectories of Idesia polycarpa var. vestita Diels (I. vestita), a dioecious bioenergy tree native to subtropical China, remain unknown. We compiled 241 quality-controlled georeferenced occurrence records and selected ten statistically independent environmental predictors for modeling. We optimized the MaxEnt model feature combination and regularization multiplier (FC = LQ, RM = 0.5) using ENMeval with AICc minimization, and the final model exhibited excellent predictive performance (AUC = 0.945, TSS = 0.831). Minimum temperature of the coldest month (Bio6, 33.4%) and annual precipitation (Bio12, 33.2%) jointly dominated the species’ distribution. The optimal niche comprises mild winters (Bio6: −4.79°C to 1.46°C), abundant precipitation (>600 mm), moderate temperature seasonality (Bio4: 604–884), and mid-to low-elevation mountains (369–2647 m). Under SSP126, total suitable habitat remains stable, whereas under SSP245, SSP370 and SSP585, progressive habitat contraction occurs, with highly suitable areas nearly disappearing by the 2090s under the highest-emission SSP585 scenario. Notably, SSP245 shows a transient expansion followed by delayed contraction, a pattern consistent with the adaptive lag hypothesis in this long-lived tree, though direct demographic validation is currently lacking. Habitat loss concentrates in southern low-elevation margins, whereas gains emerge in the Qinba Mountains and the southeastern Qinghai–Tibet Plateau. The distribution centroid shifts northwestward from Hunan Province toward the Wuling–Wushan mountain system, with displacement increasing with radiative forcing. These findings identify the Qinba and Wuling Mountains as long-term refugia. We therefore recommend prioritizing these areas for in situ germplasm conservation while gradually relocating plantations from climatically vulnerable southern margins toward future high-suitability zones in western Hubei and eastern Chongqing. This optimized MaxEnt framework provides a science-based foundation for industrial planning and climate-adaptive conservation of I. vestita under global change.