Biodiversity is essential for ecosystem resilience and human well-being, yet it faces accelerating threats from habitat loss, climate change, and human activities. Conservation models often inadequately address the intertwined ecological and socio-economic drivers of biodiversity loss, leaving a gap between theoretical frameworks and real-world implementation. This study introduces an advanced Pressure-State-Response (PSR) model, developed through extensive fieldwork and leveraging Geographic Information Systems (GIS) and remote sensing technologies. The model integrates ecological indicators with socio-economic factors, including stakeholder engagement, education, and local economic conditions, creating a dynamic, context-specific approach to conservation. By adopting a Multi-Criteria Decision Analysis (MCDA) framework, specifically the Analytic Hierarchy Process (AHP), the enhanced PSR model prioritizes biodiversity hotspots based on ecological urgency and socio-economic resilience. It overcomes limitations of traditional models by incorporating customizable criteria and fostering equitable conservation strategies. The approach optimizes resource allocation, ensuring interventions target areas of highest biodiversity value while balancing local development needs. This study provides a replicable and adaptable methodology for conservation planning, addressing 21st-century challenges of biodiversity loss and socio-ecological complexity. By aligning conservation priorities with sustainable development goals, the model advances a transformative framework that bridges science, policy, and practice, offering global applicability for safeguarding biodiversity and ecosystem services.
Biodiversity Conservation Pressure-State-Response (PSR) Model Multi-Criteria Decision Analysis (MCDA) Geographic Information Systems (GIS) Sustainable Development
Primary Language | English |
---|---|
Subjects | Conservation and Biodiversity |
Journal Section | Research articles |
Authors | |
Early Pub Date | December 8, 2024 |
Publication Date | December 30, 2024 |
Submission Date | December 1, 2024 |
Acceptance Date | December 8, 2024 |
Published in Issue | Year 2024 Volume: 8 Issue: 2 |