Assessment of habitat suitability, spatiotemporal distribution of Black-necked Crane (Grus nigricollis) and conservation recommendations in Qinghai Province

Qinghai Province is one of the main summering and breeding grouds of Black-necked Cranes (Grus nigricollis), a national first-class protect species in China and a Near Threatened (NT) species on the IUCN Red List. However, systematic and comprehensive research on the spatiotemporal distribution of this high plateau crane species in Qinghai remains inadequate. To address this gap, we integrated multi-source data to clarify its spatial and temporal distribution patterns and potential habitat, providing a scientific basis for targeted conservation. A total of 1 178 valid distribution points from field research and citizen science platforms were used to predict habitat suitablity of Blanc-necked Crane by conducting MaxEnt model. Meanwhile, we used the point density analysis tool in ArcMap (with a 100 km radius) to characterize temporal distribution dynamics. The results show that spatially, suitable habitat of Black-necked Cranes in Qinghai Province are mostly distributed along rivers and lakes, specifically include areas around Qinghai Lake, south slope of the Qilian Mountains, upper reaches of the Yellow River in eastern Qinghai Province, Sanjiangyuan area and the east extension of Qaidam Basin. Total potential suitable habitat is 116 831 km², it accounts for 16.7% of the total area of Qinghai Province, among which there are 2 626.6 km² of highly suitable habitat, accounting for 0.4% of the area of the whole province. Gangca county, Qilian county, Haiyan county, Tianjun county, and Gonghe county are the top five administrative regions with the largest highly suitable areas, each exceeding 300 km². Temporally, April to September constitutes the main residence period for Black-necked Cranes in Qinghai. The surrounding areas of Qinghai Lake, Qilian Mountains and Yushu are the three areas with the highest concentration of records. The distribution from July to August is the most scattered. Notably, 18 records (including single individuals and small groups) confirm that some cranes remain in Qinghai during the overwintering period (December–February), primarily in the Qinghai Lake vicinity and the Sanjiangyuan area. We considered this this previously unreported phenomenon may relate to the physical condition of individuals, local environmental conditions, Climate change, and population migration patterns. Jackknife test results revealed that altitude (contribution rate 31.8%), annual precipitation (18.8%), distance from rivers (16.3%), slope (8.2%), and land cover (7.7%) are the five most influential environmental factors shaping habitat suitability. Annual precipitation positively correlates with habitat suitability, likely by regulating wetland area and water depth. Wetlands and water bodies are the most preferred land cover types, while artificial surfaces (including farmland) also show relatively high suitability, reflecting the cranes’ adaptation to foraging on residual crops. Notably, highly suitable habitats overlap significantly with areas of high grazing intensity, highlighting the need for in-depth research on the coexistence mechanisms between grazing activities and cranes. Although there are potential suitable habitat in every county of Qinghai Province, the black-necked crane still faces multiple conservation challenges: only 28.06% of suitable areas are within existing protected areas; habitat degradation and fragmentation persist due to climate change and anthropogenic activities, and migration connectivity is threatened by power line collisions, a major cause of juvenile mortality. Additionally, the functional roles of most habitats (e.g., stopover, roosting or breeding sites) remain uncharacterized, limiting the effectiveness of conservation measures. To address these issues, we recommend to carry out continuous monitoring based on the spatiotemporal distribution of Black-necked cranes, clarify the functions of each distribution area, build a migration network and identify problems and barriers in the network.