Integrated framework for dynamic conservation of bamboo forest in giant panda habitat under climate change

Climate change presents formidable challenges to forest biodiversity and carbon storage. Bamboo forests will be affected particularly in Southwest China's mountainous regions. Bamboo serves as not only a key food resource and habitat for giant panda Ailuropoda melanoleuca but also a potential carbon sink due to its rapid energy-to-matter conversion capability. We employ the MaxEnt model to project the distribution shifts of 20 giant panda foraged bamboo species in Sichuan Province under future climate scenarios, utilizing climate data of 30m resolution. Based on the changes in the diversity and distribution area of bamboo communities caused by climate change, the changing of giant pandas' food resources and the carbon storage of bamboo forests were calculated. The results indicated that the area of bamboo communities is projected to expand by 17.94%-60.88% more than now by the end of the 21st century. We analyzed the energy balance between the dietary needs of giant pandas and the energy provided by bamboo. We predicted that bamboo communities from 2000 to 2150 could support the continuous growth of the giant panda population (6533 wild individuals by 2140-2150 in an ideal state in Sichuan province). However, the species diversity and carbon storage of bamboo forests face out-of-sync fluctuations, both temporally and spatially. This is a critical issue for subalpine forest ecosystem management under climate change. Therefore, we propose a dynamic conservation management framework for giant panda habitats across spatial and temporal scales. This framework aims to facilitate the adaptation of subalpine forest ecosystems to climate change. This innovative approach, which integrates climate change into the conservation strategy for endangered species, contributes a conservation perspective to global climate action, highlighting the interconnectedness of biodiversity preservation and climate mitigation.

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

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.