Identifying core habitats and corridors for giant pandas by combining multiscale random forest and connectivity analysis

Abstract

Habitat loss and fragmentation are widely acknowledged as the main driver of the decline of giant panda populations. The Chinese government has made great efforts to protect this charming species and has made remarkable achievements, such as population growth and habitat expansion. However, habitat fragmentation has not been reversed. Protecting giant pandas in a large spatial extent needs to identify core habitat patches and corridors connecting them. This study used an equal‐sampling multiscale random forest habitat model to predict a habitat suitability map for the giant panda. Then, we applied the resistant kernel method and factorial least‐cost path analysis to identify core habitats connected by panda dispersal and corridors among panda occurrences, respectively. Finally, we evaluated the effectiveness of current protected areas in representing core habitats and corridors. Our results showed high scale dependence of giant panda habitat selection. Giant pandas strongly respond to bamboo percentage and elevation at a relatively fine scale (1 km), whereas they respond to anthropogenic factors at a coarse scale (≥2 km). Dispersal ability has significant effects on core habitats extent and population fragmentation evaluation. Under medium and high dispersal ability scenarios (12,000 and 20,000 cost units), most giant panda habitats in the Qionglai mountain are predicted to be well connected by dispersal. The proportion of core habitats covered by protected areas varied between 38% and 43% under different dispersal ability scenarios, highlighting significant gaps in the protected area network. Similarly, only 43% of corridors that connect giant panda occurrences were protected. Our results can provide crucial information for conservation managers to develop wise strategies to safeguard the long‐term viability of the giant panda population.

A Survey of the Wild Giant Panda Population and Habitat Reflects an Urgent In Situ Conservation Need: A Case of Meigu Dafengding National Nature Reserve

“…It also increased the likelihood of a continued increase in the population. The results complement previous studies demonstrating that ecological corridors are highly connected, link different patches and increase species movement between patches [70,71]. This suggests that conservationists should focus on connectivity between patches so that biodiversity continues to function [72].…”

Giant pandas are losing their edge: Population trend and distribution dynamic drivers of the giant panda

“…Although human disturbance did not emerge as a prominent factor in our results, it should certainly not be overlooked. Without factoring in climate change, other research has underscored the significance of anthropogenic disturbance in the Liangshan Mountains (Li et al, 2019), other mountain (Sun et al, 2022), and even in future projections (Zhigang et al, 2023). Our result might not have highlighted anthropogenic disturbance as a critical factor, likely due to China's conservation efforts, which encompass the prohibition of commercial logging in 1999 and the launch of two major programs—the Natural Forest Conservation Program and the Grain‐to‐Green Program (Li et al, 2013).…”

Prediction of Oncomelania hupensis distribution in association with climate change using machine learning models

“…Previously, studies have been conducted to predict the potential distribution of snails in China; however, large-scale predictions are no longer sufficient to meet the requirements for fine control of snails at this stage [ 14 , 15 ]. Studies have shown that factors influencing species distribution may vary at different scales, leading to differences in distribution ranges and even producing opposite conclusions [ 16 , 17 ]. In addition, there are three types of schistosomiasis-endemic areas in China according to the geographical environment and the epidemiological pattern of schistosomiasis: (1) marshland and lake regions, (2) mountainous and hilly regions, and (3) water network regions [ 18 ].…”