Distribution of a giant panda population influenced by land cover

Abstract

The distribution of species and their causes are key questions for population ecology and conservation. Giant pandas (Ailuropoda melanoleuca) in the Daxiangling Mountains, China are part of an isolated population on the edge of the species’ range and little is known regarding their distribution. Based on land cover, topography, human disturbance, and panda occurrence data in 2 national giant panda surveys, we used a species distribution model (i.e., MaxEnt) to simulate habitat distribution changes of the local panda population between 2001 and 2012. During this time the area of coniferous forest and broadleaf forest increased by 16.4% and 5.8%, respectively, whereas the shrub‐grass and agricultural land decreased by 45.1% and 4.0%, respectively. Panda habitat increased from 460.3 km2 in 2001 to 591.3 km2 in 2012. Panda distribution in the Daxiangling Mountains was primarily influenced by land cover, topography, and human activities. Our study demonstrates that habitat recovery in the Daxiangling Mountains created a favorable environment for the local panda population; thus, the boundary of panda reserves should be adjustable based on their use of the landscape. Future research should focus on dispersal and distribution of pandas to better understand their land use for effective conservation. © 2018 The Wildlife Society.

Large‐scale genetic surveys for main extant population of wild giant panda (Ailuropoda melanoleuca) reveals an urgent need of human management

“…Feng ( 2015 ) found that suitable habitats were fragmented in central and northern Mabian Nature Reserve. Unsuitable habitats might be caused by deforestation, road construction and livestock invasion (Feng, 2015 ; Zhang et al, 2018 ; Zhao et al, 2017 ). Fragmented suitable habitats and unsuitable habitats could influence the habitat selection and migration of giant panda.…”

“…Feng (2015) found that suitable habitats were fragmented in central and northern Mabian Nature Reserve. Unsuitable habitats might be caused by deforestation, road construction and livestock invasion (Feng, 2015;Zhang et al, 2018;Zhao et al, 2017).…”

Evaluating the Effects of Climate Change on Spatial Aggregation of Giant Pandas and Sympatric Species in a Mountainous Landscape

“…To identify a subset of environmental variables with minimal multicollinearity, we calculated the pairwise Pearson correlation coefficients for all 22 environmental variables. For a pair of variables with a correlation coefficient |r| > 0.7, we tested all environmental variables in a pairwise way, and retained the variable with the lowest variance inflation factor (VIF) in each pair of variables [ 25 , 40 , 41 , 42 ]. Finally, six variables were used for constructing the SDMs: isothermality (Bio03), annual precipitation (Bio12), precipitation seasonality (Bio15), elevation, slope, and aspect.…”

Dynamic threats of nighttime light-represented human activities to giant pandas and their habitat

“…This finding also echoes previous studies. In recent years the implementation of ecological restoration projects has largely promoted the transfer of rural to urban populations, reduced the rural population in mountainous areas to a certain extent, contributing to restoration of giant panda habitats (Zhang et al, 2018;Li et al, 2019;Han et al, 2022;Li and Song, 2022).…”