Incorporating species information to optimize the framework for priority conservation area identification: An...

Establishing nature reserves is vital for mitigating biodiversity loss and restoring ecosystem services. However, constraints in land, manpower, and funding have made prioritizing conservation areas (PCAs) increasingly common. Traditional methods rely on species or habitat suitability, with uncertainty. This study integrates species information with habitat quality to identify PCAs in the Qinling-Daba Mountains. We quantified Biodiversity with MaxEnt and the InVEST Habitat Quality module. We utilized the InVEST model to quantify water yield, the CASA model to estimate carbon sequestration and the RUSLE model to assess soil conservation. And the Zonation model was employed to integrate multiple conservation themes and evaluate protection priorities. Our findings reveal that: (1). Across both single- and multi-theme scenarios, the areas of PCAs were smaller than those of existing nature reserves, while Taibai Mountain and the Fulong Mountain-Shennongding region in the eastern Daba Mountains consistently remained stable core zones. (2). Under single-theme protection, all PCAs exhibited the highest conservation efficiency for soil conservation services and the lowest for carbon sequestration services. PCAs focusing on water yield had the lowest protection cost, whereas those emphasizing soil conservation incurred the highest. (3). Although existing reserves had the lowest patch density, their complex shapes and low aggregation resulted in suboptimal cost efficiency. When biodiversity and water yield were prioritized, costs were lower. In all scenarios, soil conservation services consistently demonstrated the highest and most stable conservation efficiency.