Understanding Measurement Reporting and Verification Systems for REDD+ as an Investment for Generating Carbon Benefits

Abstract

Reducing emissions from forests-generating carbon credits-in return for REDD+ (Reducing Emissions from Deforestation and forest Degradation) payments represents a primary objective of forestry and development projects worldwide. Setting reference levels (RLs), establishing a target for emission reductions from avoided deforestation and degradation, and implementing an efficient monitoring system underlie effective REDD+ projects, as they are key factors that affect the generation of carbon credits. We analyzed the interdependencies among these factors and their respective weights in generating carbon credits. Our findings show that the amounts of avoided emissions under a REDD+ scheme mainly vary according to the monitoring technique adopted; nevertheless, RLs have a nearly equal influence. The target for reduction of emissions showed a relatively minor impact on the generation of carbon credits, particularly when coupled with low RLs. Uncertainties in forest monitoring can severely undermine the derived allocation of benefits, such as the REDD+ results-based payments to developing countries. Combining statistically-sound sampling designs with Lidar data provides a means to reduce uncertainties and likewise increases the amount of accountable carbon credits that can be claimed. This combined approach requires large financial resources; we found that results-based payments can potentially pay-off the necessary investment in technologies that would enable accurate and precise estimates of activity data and emission factors. Conceiving of measurement, reporting and verification (MRV) systems as investments is an opportunity for tropical countries in particular to implement well-defined, long-term forest monitoring strategies.

Use of Multi-Temporal LiDAR to Quantify Fertilization Effects on Stand Volume and Biomass in Late-Rotation Coastal Douglas-Fir Forests

“…While more research is needed to determine the optimal sampling intensity and distribution for operational application, the fusion of the traditional sample design with a LiDAR area-based approach could offer the optimal design for a carbon verification context. As verification projects often balance the need for accuracy with project cost [21], the fusion of these two methods provides the flexibility to leverage plot-level observations to gain insights into the wider treatment area. This method should also become more accessible, particularly with the increased availability of multiple LiDAR acquisitions and the use of UAV-based LiDAR systems [65].…”

The biopolitics of carbon accounting in Indonesia’s forests

“…But for many countries, MRV remains a complex and institutionally challenging undertaking. It requires the collection, aggregation and then processing of spatial data and information from multiple sources, followed by modelling using standardised methodologies and rules (Di Lallo et al, 2017).…”

“…MRV allows countries to accurately map the ongoing and cyclical death and regeneration of the forest, identifying the locations where this occurs and the socioeconomic and governance conditions that drive these changes. Once operational, these systems are also designed to shape national policy debates and decision making, such as advising on forest management practices and land-use planning, and supporting the incountry distribution of incentives or co-benefits to multiple recipients (Di Lallo et al, 2017;Korhonen-Kurki et al, 2013). In Indonesia, the central government and bilateral partners have expended considerable resources to set-up the Indonesian National Carbon Accounting System (INCAS).…”