Identifying optimized on-the-ground priority areas for species conservation in a global biodiversity hotspot

Area of Science:

• Conservation Biology
• Biodiversity Management
• Geographic Information Systems (GIS)

Background:

• Protected areas (PAs) globally do not adequately represent threatened species.
• Public species-occurrence databases offer potential for improving conservation planning, but evidence at local scales is limited.

Purpose of the Study:

• To investigate the utility of public species data for enhancing conservation planning at local scales.
• To identify optimized portfolios of priority conservation areas (PCAs) in the Three Parallel Rivers Region of China.

Main Methods:

• Species distribution models and point locations were used to map species distributions.
• Systematic conservation planning was applied to generate three portfolios of PCAs.
• PCAs were compared with existing datasets to assess coverage and complementarity.

Main Results:

• PCAs identified using public data covered more disturbed regions and river valleys compared to existing PAs focused on remote mountains.
• The new PCAs complemented existing ones, identifying priority areas in developed landscapes.
• PCAs in this study had lower PA coverage than existing ones due to PA distribution biases.

Conclusions:

• Conservation planning utilizing limited public species data can enhance local-scale priority-setting.
• This approach is critical for protecting biodiversity in developed landscapes facing significant pressures.
• The findings support integrating species targets into China's national park system through optimized PCA networks.