A new zoning index for detecting areas of biological importance applied to a temperate forest in Central Mexico

Biodiversity conservation is a priority because it is the cornerstone of ecosystem services and natural cycles, providing essential resources for the development of humans and other species. Several indices have been proposed to prioritize areas needing protection. However, some require specific information while others are based on subjective categorical variables, are limited to a particular plant community or cannot be represented at a spatial scale. We de-veloped an Index of Importance for Biological Conservation (InICoB), which was applied to a temperate forest in central Mexico but can be used for any plant community by adjusting some of its parameters. The proposed index is objec-tive, based on quantitative indicators of vegetation composition and structure, and can be spatially projected. InICoB was tested and validated on a temperate cloud forest (CF) and its associated communities: advanced secondary vegeta-tion (ASV) / coffee plantations (CP), agriculture, and induced grasslands. Life forms, presence of endemic, climax, native and protected species, diversity, structural complexity, and complementarity were used as indicators in its con-struction. InICoB was calculated for 63 sampling units (SUs), and a geostatistical model was incorporated for its interpolation with environmental and social variables as predictors. The results show that InICoB adequately evaluated the different environmental units that cover the locality. Significant differences were observed between the forest and the secondary/induced vegetation. The highest value of InICoB (0.91) was found in the CF, and the lowest in induced vegetation (0.3). The geostatistical model showed that occupation of the land, distance to town, and slope have an important influence on InICoB. The advantages of InICoB include the use of quantitative indicators that can be applied to any plant community. Additionally, it is flexible with respect to the data collected, it can be calculated only with the presence/absence of species or it can include forest measurement data. Furthermore, it is easy to interpret and can be spatially represented in a raster layer that can be added to a geo-graphic information system. Therefore, it can be a very helpful tool in decision-making for land use planning and evaluation of the effects of human activities on plant communities.