Abstract
Efforts to reduce emissions from deforestation and forest degradation and enhancing forest carbon stocks (REDD+) have evolved over the past decade. Early REDD+ programs and local/subnational projects used various interventions (i.e. enabling measures, disincentives and incentives), implemented by government, the commercial and non-commercial private sector, but are currently understudied vis-à-vis their effectiveness to address site-specific drivers of deforestation and forest degradation (DD). We assess how well REDD+ interventions addressed DD at five project sites in Peru (1), Brazil (1), Vietnam (1) and Indonesia (2). Our study design includes an integrated assessment of remotely sensed, spatially modelled, and locally reported drivers. First, we observe follow-up land use from high resolution imagery as proxy for direct deforestation drivers. Second, spatial Random Forest modelling of DD drivers allows for influence quantification of topographic, climatic and proximity variables at each site. Third, we report direct and indirect DD drivers from pre-intervention surveys and semi-structured interviews with five REDD+ implementers, 40 villages and 1200 households. Data gathered included perceived changes in forest cover and quality, and their causes. We found general agreement between observed, modelled and reported local DD drivers, yet some were inadequately addressed by interventions. Intra-site differences in drivers underscores the importance of analysing micro-level DD drivers. Our interdisciplinary approach reveals the complexities of local direct and indirect DD drivers, and the complementarity of remotely sensed, spatially modelled and locally reported methods for driver identification. A better understanding of the alignment between DD drivers and REDD+ interventions is vital for practitioners and policy makers to enhance the effectiveness, efficiency, equity and co-benefits of REDD+ at the local level.
Highlights
Deforestation and other land use changes contribute significantly to carbon emissions (IPCC, 2006)
In Indonesia-Ketapang Community Carbon Pool (KCCP), tree plantations constitute of oil palm plantations, unlike the tree planta tions in Vietnam Cat-Tien
We only report relative shares of forest change patterns observed by remote sensing, as the area of interests of the remote sensing analysis are based on rectangular buffers around the REDD+ initiative areas and comprise most likely of more than the study villages’ area of influence
Summary
Deforestation and other land use changes contribute significantly to carbon emissions (IPCC, 2006). Efforts to reduce emissions from defor estation and forest degradation and to enhance carbon stocks (REDD+) were embedded in the Paris Agreement (UNFCCC, 2015). The approach of Kaimowitz and Angelsen (1998) is more similar to Geist and Lambin’s, the focus differs by concentrating on the economics behind the immediate and underlying factors. It is important to monitor drivers of defor estation and forest degradation (DD) at the local level because they differ across space and time (Rudel, 2007; Rudel et al, 2009; Defries et al, 2010; Hosonuma et al, 2012; De Sy et al, 2015; Curtis et al, 2018)
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