Abstract

National parks play a crucial role in global biodiversity preservation, with China’s Giant Panda National Park (GPNP) serving as a key stronghold for protecting unique flora and fauna endemic to diverse mountainous regions. This study focused on unraveling the dynamics of diversity within local giant panda populations and their sympatric species in the Ya’an section of the GPNP. Five specific local population patches (LPPs) were selected as subjects, utilizing data from the 4th National Giant Panda Survey. Through identification, classification, and analysis of observed species within each LPP, α and β diversity patterns were revealed, leading to actionable recommendations. A comprehensive record of 34 species spanning 5 orders and 16 families was documented. Notably, 8 species were under the first-class of the National Key Protected Wildlife List in China, and the IUCN Red List has identified 3 species – Rhinopithecus roxellana, Moschus berezovskii, and Ailurus styani – as endangered, showing its high biodiversity and conservation significance. While α-diversity assessment highlighted the DaxianglingA2 (DXLA2) with the highest Shannon-Wiener and Simpson’s indices, the QionglaishanA3 (QLSA3) exhibited greater species richness. However, these differences lacked statistical significance (P > 0.05). The Jaccard similarity coefficient indicated a stronger turnover process compared to nestedness. The dominance of turnover in total β-diversity accentuated the importance of encompassing all five LPPs in conservation strategies. The study underscored the imperative of conservation management for each LPP, with a focus on enhancing habitat connectivity between disparate small LPPs to prevent species extinction by fostering species exchange and gene flow. This pioneering research shed light on spatial utilization patterns and diversity drivers for local giant panda populations and their sympatric species within the GPNP. It provides valuable references to appraise conservation strategy effectiveness and offers scientific backing to optimize biodiversity conservation and management within national parks and protected areas.

Full Text
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