Defining priorities areas for biodiversity conservation and trading forest certificates in the Cerrado biome in Brazil

Abstract

Habitat loss and natural vegetation fragmentation are signi cant causes of global biodiversity decline, impacting plant and animal species negatively. This issue is worrisome in the private areas of Cerrado in Brazil, which is the second-largest biome, considered a hotspot for biodiversity conservation, and a provider of ecosystem services. Herein, we present a novel integrated approach to de ne priority areas for biodiversity conservation and environmental compensation in Cerrado, using multicriteria analysis. Our approach combines variables like deforestation projection, integral index of connectivity, threatened species occurrence, and environmental information of rural properties, ranking the importance of remaining native vegetation for biodiversity conservation and forest certi cate issuance. Landscape metrics were used to observe and predict land use and land cover changes from 1988 to 2038. We found a loss of native vegetation in the Cerrado superior to 20% between 1988 and 2018, associated with increased of its fragmentation and its connectivity loss, especially after 2008. Natural cover was replaced mostly by pasture and more recently by agriculture Moreover, we determined that is expected a loss of native vegetation of around 55% by 2038 in Cerrado. The proposed approach can predict the consequences of future changes in the landscape of the private areas in the Cerrado biome. It should be replicated in other ecosystems, supporting the decision-making process for biodiversity protection.

Multi-Criteria Prioritization of Watersheds for Post-Fire Restoration Using GIS Tools and Google Earth Engine: A Case Study from the Department of Santa Cruz, Bolivia

“…To aggregate the classified and scored variables, a Weighted Linear Combination (WLC) method was applied. This method has been validated for forest restoration and conservation by a number of authors [43,[49][50][51]. It consists of multiplying each standardized criterion's spatial layer (i.e., pixels) by an assigned weight and then summing the weighted criteria to produce a final result layer.…”