Comparing methods for assessing the effectiveness of subnational REDD+ initiatives

Abstract

The central role of forests in climate change mitigation, as recognized in the Paris agreement, makes it increasingly important to develop and test methods for monitoring and evaluating the carbon effectiveness of REDD+. Over the last decade, hundreds of subnational REDD+ initiatives have emerged, presenting an opportunity to pilot and compare different approaches to quantifying impacts on carbon emissions. This study (1) develops a Before-After-Control-Intervention (BACI) method to assess the effectiveness of these REDD+ initiatives; (2) compares the results at the meso (initiative) and micro (village) scales; and (3) compares BACI with the simpler Before-After (BA) results. Our study covers 23 subnational REDD+ initiatives in Brazil, Peru, Cameroon, Tanzania, Indonesia and Vietnam. As a proxy for deforestation, we use annual tree cover loss. We aggregate data into two periods (before and after the start of each initiative). Analysis using control areas (‘control-intervention’) suggests better REDD+ performance, although the effect is more pronounced at the micro than at the meso level. Yet, BACI requires more data than BA, and is subject to possible bias in the before period. Selection of proper control areas is vital, but at either scale is not straightforward. Low absolute deforestation numbers and peak years influence both our BA and BACI results. In principle, BACI is superior, with its potential to effectively control for confounding factors. We conclude that the more local the scale of performance assessment, the more relevant is the use of the BACI approach. For various reasons, we find overall minimal impact of REDD+ in reducing deforestation on the ground thus far. Incorporating results from micro and meso level monitoring into national reporting systems is important, since overall REDD+ impact depends on land use decisions on the ground.

Keywords

• deforestation
• climate
• forest change
• land cover
• monitoring
• performance assessment