Methodology to identify ecologically matching areas and its applications in conservation planning

Identifying ecologically matching areas is both challenging and critical for understandingspatial patterns of biodiversity and advancing conservation planning. However, existingapproaches often lack spatial flexibility, overlook shape and size constraints, or rely onlimited environmental parameters, reducing their effectiveness in real-world applications.To address these limitations, we developed and tested a four-step framework for identi-fying ecologically and spatially matching areas. Our framework method involved definingthe parameters for the comparative analyses; assessing similar environmental conditionsbetween target protected areas and potential matching areas, through a modified versionof the multivariate environmental similarity surface (mMESS); simulating randomly dis-tributed polygons that mirror both the shape and surface area of the target protected area;and integrating the simulated polygons with the resulting mMESS to identify areas whereenvironmental similarity, shape, and surface match. Finally, we applied decision criteriato identify real-world matching areas. We tested our approach in both the Northern andthe Central Apennines (Italy), comparing a national park in each of these two regions tosimilar but unprotected areas—specifically excluding national parks, regional parks, andNatura 2000 Network sites. Our framework offers a robust tool for identifying matchingand mismatching areas and enhancing our understanding of these areas’ spatial distribu-tions and environmental conditions to support conservation planning and management.The framework may be applied to a broad range of ecological studies at various scales andhas the potential to guide future conservation efforts and policies.