Multi-level ecological planning: Integrating conservation, trade-offs, and vegetation sensitivity for the Gansu NFPP

Abstract

Enhancing the sustainability and resource efficiency of large-scale ecological restoration programs, such as China's Natural Forest Protection Project (NFPP), requires advanced decision-support tools. Planning is often hindered by the complex interplay of multiple ecosystem services (ESs), their trade-offs, and environmental constraints, leading to potentially inefficient or maladaptive interventions. This study develops a multi-level spatial decision framework to guide cleaner and more effective ecological management in the Gansu section of the NFPP (GS-NFPPA). We quantified four key ESs (Net Primary Productivity, Water Yield, Sand Fixation, and Soil Conservation) from 2000 to 2020 and used Ordered Weighted Averaging (OWA) to identify priority Ecological Conservation Areas (ECAs), trade-off analysis for Ecological Trade-off Areas (ETAs), and constraint line analysis for vegetation (NDVI) driven Ecological Sensitive Areas (ESAs). Unlike single-objective approaches, this framework innovatively integrates conservation priorities, ES trade-offs, and nonlinear vegetation sensitivity, enabling a shift from broad-stroke conservation to targeted, resource-efficient interventions. Our results show significant overall ES improvement across the GS-NFPPA. The framework identified optimal ECAs covering approximately 10.92 % of the region, critical ETAs with intense ES competition covering 9.23 %, and land-use-specific NDVI thresholds that define ESAs where ES provision can decline. The spatial overlay of these zones pinpointed "Comprehensive Key Areas" where high conservation value, trade-offs, and sensitivity converge, demanding the most sophisticated management. This integrated multi-level framework provides a robust scientific basis for targeted, differentiated ecological management strategies. This preventative and evidence-based approach offers a transferable model for enhancing the sustainability of large-scale environmental programs globally.