Prediction of the potential distribution of Piptanthus nepalensis in China under future climate scenarios
Year: 2025
Type: article
Abstract: Introduction Climate change is driving unprecedented shifts in ecosystems, altering species distributions, abundance, and richness. This study aims to predict the potential distribution of the alpine endemic species Piptanthus nepalensis in China under current and future climate scenarios and assess its response to climate change. Methods We employed the Maximum Entropy (MaxEnt) model, rigorously optimized using ENMeval, to predict distribution patterns. Key environmental variables were selected for model calibration. Model performance was evaluated using the Area Under the Receiver Operating Characteristic Curve (AUC). Results The optimized MaxEnt model demonstrated excellent predictive performance (AUC = 0.985). Key findings are: (1) The current total suitable habitat area is 25.78 × 104 km2, with high-suitability zones (6.90 × 104 km2) concentrated along the Sichuan-Yunnan-Tibet border; (2) Under future climate scenarios, low-suitability areas expand (peaking at 31.29 × 104 km2 under SSP370-2050s), while high-suitability areas contract substantially (declining to 3.92 × 104 km2 under SSP585-2050s); (3) Habitat quality is negatively correlated with climate emission intensity. High-suitability zones show relative stability under SSP126 (core retention rate: 0.71%–0.83%) but exhibit pronounced “expansion-contraction oscillations” under SSP585. Discussion These results highlight the significant threat climate change poses to P. nepalensis, particularly under high-emission scenarios. Conservation efforts should prioritize the core Sichuan-Yunnan-Tibet regions and closely monitor ecological risks associated with expanding low-suitability habitats. This study provides critical scientific insights for the climate-adaptive management of alpine endemic species.
Authors: Ye Yanhui, Jing Aohang, Han Yanying
Language: English
Subfield: Ecological Modeling
Field: Environmental Science
Domain: Physical Sciences
SDGs: Climate action, Life on land
Open Access status: gold
Estimated APC paid: $2,353
Funder: Division of Graduate Education
OpenAlex ID: W4413303138