Ecological value (EV) is a term used to characterize the biotic or abiotic elements of a landscape, excluding human influence. Significant criteria for EV estimation can be grouped into two categories: ecological properties (biodiversity and vulnerability) and functional/structural features (fragmentation, connectivity, and resilience). While various methodological frameworks exist for estimating these criteria, few studies integrate all five criteria, and even fewer compare their results with fieldwork data. The objective of this study was to devise a novel spatial modelling tool for EV estimation based on biodiversity, vulnerability, fragmentation, connectivity, and resilience, utilizing data from Neotropical montane forests in west-central Mexico. The model incorporated data on (i) biodiversity and vulnerability estimated through ecological niche models, (ii) fragmentation and connectivity using landscape spatial patterns, and (iii) resilience estimated through the inverse of the vegetation sensitivity index. The results were then compared with fieldwork data. Natural protected areas within the Neotropical montane forests of west-central Mexico exhibited high EVs; however, a substantial portion of these forests lack legal protection. In terms of vegetation types, cloud and semideciduous forests exhibited the highest EV, emphasizing the urgent need for legal protection of these vital ecosystems. The comparison process demonstrated a moderate to high correlation in some criteria between the spatial and fieldwork data, indicating that the spatial model robustly captured the landscape spatial patterns. The spatial modelling tool proposed in this study is not only practical but also reproducible and applicable globally. Its efficacy lies in combining ecological properties with the functional and structural features of the landscape, making it particularly suitable for delineating protected natural areas and contributing to landscape planning efforts.
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