Enhanced risk assessment framework integrating distribution dynamics, genetically inferred populations, and...

Assessing the threat status of species in response to global change is critical for biodiversity monitoring and conservation efforts. However, current frameworks, even the IUCN Red List, often neglect critical factors such as genetic diversity and the impacts of climate and land-use changes, hindering effective conservation planning. To address these limitations, we developed an enhanced extinction risk assessment framework using Diploderma lizards as a model. This framework incorporates long-term field surveys, environmental data, and land-use information to predict distributional changes for 10 recently described Diploderma species on the Qinghai-Xizang Plateau, which hold ecological significance but remain underassessed in conservation assessment. By integrating the distribution data and genetically inferred effective population sizes ( Ne), we conducted scenario analyses and used a rank-sum approach to calculate Risk ranking scores (RRS) for each species. This approach revealed significant discrepancies with the IUCN Red List assessments. Notably, D. yangi and D. qilin were identified as facing the highest extinction risk. Furthermore, D. vela, D. batangense, D. flaviceps, D. dymondi, D. yulongense, and D. laeviventre, currently classified as "Least Concern", were found to warrant reclassification as "Vulnerable" due to considerable threat from projected range contractions. Exploring the relationship between morphology and RRS revealed that traits such as snout-vent length and relative tail length could serve as potential predictors of extinction risk, offering preliminary metrics for assessing species vulnerability when comprehensive data are unavailable. This study enhances the precision of extinction risk assessment frameworks and demonstrates their capacity to refine and update risk assessments, especially for lesser-known taxa.