Abstract:

Background & Aims: Global biodiversity is declining at an unprecedented rate. As a widespread and diverse taxonomic group, birds are crucial indicators, and understanding drivers and consequences of their population dynamics is vital for biodiversity conservation. Passive acoustic monitoring (PAM), a non-invasive technique with high spatiotemporal resolution, offers a revolutionary tool for large-scale, long-term avian diversity surveys. Despite the rapid development of PAM globally, its application in China is currently hampered by scattered projects, heterogeneous equipment, and inconsistent methodologies. This has resulted in a “data island” dilemma, significantly hindering data integration, comparability, and its use for policy of biodiversity and conservation. This study aims to provide a scientific blueprint and implementation guide for establishing a standardized, networked, and intelligent avian acoustic monitoring system in China. 

Method Results: We systematically reviewed the corresponding urgent needs of PAM in light of the global loss of avian biodiversity. We then compared and analyzed the technical development, network construction, and data-sharing experiences of avian PAM both internationally and domestically, identifying the core challenges China faces due to the lack of unified standards. Drawing on successful international PAM practices, we propose a comprehensive framework of standards suitable for China. This framework covers the entire workflow, from monitoring design and core technical parameters to metadata standards and data processing and analysis. 

Perspectives: Finally, we present a series of actionable recommendations and a strategic roadmap for future implementation. These proposals address multiple facets, including top-level design, national network construction, technological innovation, data sharing mechanisms, and essential policy support, charting a clear course for the future of avian acoustic monitoring in the nation.

Key words: passive acoustic monitoring, bird diversity, monitoring standards, data standardization, ecoacoustics