Modeling Habitat Suitability of Snow Leopards in Yanchiwan National Reserve, China

Abstract

Snow leopards (Panthera uncia) are elusive predators inhabiting high-altitude and mountainous rugged habitats. The current study was conducted in the Yanchiwan National Nature Reserve, Gansu Province, China, to assess the habitat suitability of snow leopards and identify key environmental factors inducing their distribution. Field data collected between 2019 and 2022 through scat sampling and camera trapping techniques provided insights into snow leopard habitat preferences. Spatial distribution and cluster analyses show distinct hotspots of high habitat suitability, mostly concentrated near mountainous landscapes. While altitude remains a critical determinant, with places above 3300 m showing increased habitat suitability, other factors such as soil type, human footprint, forest cover, prey availability, and human disturbance also play important roles. These variables influence ecological dynamics and are required to assess and manage snow leopard habitats. The MaxEnt model has helped us to better grasp these issues, particularly the enormous impact of human activities on habitat suitability. The current study highlights the importance of altitude in determining snow leopard habitat preferences and distribution patterns in the reserve. Furthermore, the study underscores the significance of considering elevation in conservation planning and management strategies for snow leopards, particularly in mountainous regions. By combining complete environmental data with innovative modeling tools, this study not only improves local conservation efforts but also serves as a model for similar wildlife conservation initiatives around the world. By understanding the environmental factors driving snow leopard distribution, conservation efforts can be more efficiently directed to ensure the long-term survival of this endangered species. This study provides valuable insights for evidence-based conservation efforts to safeguard the habitats of snow leopards amidst emerging anthropogenic pressure and environmental fluctuations.

Keywords: Yanchiwan National Nature Reserve; environmental impact; maximum entropy modeling; snow leopard; species conservation.

Figure 1

Map of the study area, representing Yanchiwan National Nature Reserve.

Figure 2

Map of study area showing the occurrence of snow leopards in Yanchiwan National Nature Reserve.

Figure 3

Map of the study area showing the distribution of various vegetation types. Each color represents a different vegetation type, coded numerically in the legend. The study area is outlined in black.

Figure 4

Map of the study area showing the distribution of various vegetation types. Each color represents a different vegetation type, coded numerically in the legend. The study area is outlined in black.

Figure 5

Correlation coefficients among various environmental variables used in the study, including bioclimatic factors, human footprint, elevation, land use, soil type, and vegetation. The color scale from blue to red indicates the strength and direction of correlations, with red representing a strong positive correlation and blue a strong negative correlation.

Figure 6

AUC values for the maximum entropy values.

Figure 7

Spatial distribution of habitat suitability for snow leopards.

Figure 8

Response curves for environmental variables in snow leopard habitat.

Figure 9

Jack-knife of regularized training gain for snow leopard habitat suitability model.

Figure 10

Spatial distribution of snow leopards in the study area, showing the areas of highest habitat suitability and potential human impact zones.

Figure 11

Cluster analysis of snow leopards in the study area.

Figure 12

(a): Annual peak temperatures from 2019 to 2022. This graph illustrates the highest recorded temperatures in each year, reflecting annual climatic variations. (b): Yearly altitude range for different vegetation types from 2019 to 2022. This graph displays the altitude variations where different vegetation types are most prevalent, illustrating changes in vegetation distribution patterns over time. (c): Changes in human proximity to various vegetation types from 2019 to 2022. Each point indicates the average distance of human activities from areas dominated by specific vegetation types, highlighting potential impacts on habitat disturbances.

Figure 12

(a): Annual peak temperatures from 2019 to 2022. This graph illustrates the highest recorded temperatures in each year, reflecting annual climatic variations. (b): Yearly altitude range for different vegetation types from 2019 to 2022. This graph displays the altitude variations where different vegetation types are most prevalent, illustrating changes in vegetation distribution patterns over time. (c): Changes in human proximity to various vegetation types from 2019 to 2022. Each point indicates the average distance of human activities from areas dominated by specific vegetation types, highlighting potential impacts on habitat disturbances.