Quantifying the Evolution of Giant Panda Habitats in Sichuan Province under Different Scenarios

• Published in: Diversity (Basel) 2022-10, Vol.14 (10), p.865
• Main Authors: Song, Zhenjiang, Wu, Baoshu, Xiong, Wenguang, Gao, Lan, Li, Yi
• Format: Article
• Language: English
• Subjects: Aging; Ailuropoda melanoleuca; Analysis; Cellular automata; Cellular structure; Classification; Endangered & extinct species; Endangered species; Environmental aspects; Environmental quality; Farms; Farmworkers; Geospatial data; Giant panda; giant panda habitat; Habitats; Hidden Markov models; Households; Labor; Labor force; Land use; Landscape; landscape pattern; LUCC; Markov chains; Markov processes; Methods; Natural areas; Nature reserves; Pandas; Population; Protection and preservation; Regression models; Remote sensing; Resource utilization; resource utilization behavior; Simulation; Spatial analysis; structure of the labor force; Transfer matrices; Wildlife conservation; Wildlife habitats
• ISSN: 1424-2818; 1424-2818
• DOI: 10.3390/d14100865

The giant panda (Ailuropoda melanoleuca) is a relic species in China and a flagship species in the field of endangered wildlife conservation. The conservation of the giant panda’s habitat has gained widespread attention for this reason. Historically, Chinese Giant Panda Nature Reserves are surrounded by communities and the resource utilization behavior of households disturbs the giant panda habitat. Changes in these communities and in Giant Panda Nature Reserves began around 2010, with the feminization and aging of the farm labor force. These changes brought different resource utilization behaviors that led to different evolutionary tendencies in giant panda habitats. This research study assesses the impact of these tendencies based on data from the fourth survey of the giant panda in the Sichuan Province and from geographic information data. The paper aims to uncover the internal mechanisms of farmers’ resource utilization behavior in terms of the changes wrought to giant panda habitats. The paper simulates the future habitat of the giant panda based on the LUCC (land use/cover change) model to identify anticipated changes in future landscape patterns and the habitat quality of giant pandas under the current scenarios. The paper analyzes the spatial-temporal change of landscape patterns through the land use transfer matrix, based on the Markov model. The results of the scenario analyses illustrate the spatial and temporal difference in habitat quality. The driving mechanism for landscape pattern change is explored using the logistic regression model. The paper simulates the variation tendency of giant panda habitats under differential labor force structures and resource utilization behavior based on the CA (cellular automata) model, with the robustness of the results verified by participatory experiment. Through four scenarios of simulated farm labor force structure and resource utilization behavior, results suggest that the quality of giant panda habitats in the future will be relatively high when workforce feminization and aging is intense and resource utilization behavior is weakened. The simulated results confirm that the current agricultural labor force structure can reduce the intensity of resource utilization behavior. In this scenario, disturbance to giant panda habitats would decrease and their quality would improve.