Deforestation and degradation of tropical forests produce approximately 8-10% of global greenhouse gas (GHG) emissions (Baccini et al. 2012; Harris et al. 2012). Reducing Emissions from Deforestation and forest Degradation plus (REDD+) was launched as a climate mitigation strategy at the 13th session of the Conference of the Parties (COP13) of the United Nations Framework Convention on Climate Change (UNFCCC) in Bali, in December 2007. It is a performance-based scheme that provides incentives for developing countries to reduce their GHG emissions through reducing deforestation and degradation of forest cover, conserving forest carbon stocks, sustainable forest management and enhancement of carbon...
The requirements, development and implementation of the MRV system in the REDD+ context were reviewed to provide the context for assessing the suitability of the PMRV approach. They were obtained from various IPCC guidelines on MRV (IPCC 2003; IPCC 2006) and published literature on the development of REDD+ (Angelsen et al. 2009; Angelsen et al. 2012). The challenges in the establishment of a credible MRV system were also identified.
For the literature search, we used the Web of Knowledge database, the Google search engine and the Center for International Forestry Research (CIFOR) publications. The Google search led to the discovery...
Forest carbon emissions are calculated by combining the change in forest area and emission factors (IPCC 2006; GOFC-GOLD 2012). The change in forest area (ha) can be estimated from a wall-to-wall mapping or sampling of remote sensing data. Forest degradation generally results in small changes in canopy cover so the areal extent of degradation is more difficult to detect with optical remote sensing than the areal extent of deforestation (DeFries et al. 2007). Airborne laser altimetry (such as light detection and ranging — LiDAR) produces promising results for monitoring degradation (Asner et al. 2010), but some ground-based carbon inventory may...
This chapter reviews the literature on participatory monitoring of forest resources and biodiversity, and the literature on PMRV in the REDD+ context. The first section in this chapter presents the current state of knowledge on participatory monitoring and PMRV. The second section identifies knowledge gaps in the literature.
Participatory monitoring of forest resources and biodiversity by local communities can deliver multiple benefits, such as:
build social capital and empower local people (Hartanto et al. 2002; Danielsen et al. 2005a; Constantino et al. 2012)
improve livelihoods (Klooster and Masera 2000; Chhatre and Agrawal 2009)
reduce forest degradation (Klooster and Masera 2000;...
Indonesia has committed to decrease its GHG emissions by 26% from the ‘business as usual’ development scenario by 2020 through self-funding alone, or by 41% if international assistance is provided. This commitment and Indonesia’s early participation in the REDD+ scheme have enabled REDD+ implementation to progress and reach its readiness phase. We examined the (proposed) multi-level MRV system in Indonesia and MRV implementation at the project level to explore how PMRV can be integrated into the MRV system. This examination looks at the knowledge gaps in participatory reporting and integration of PMRV into a multi-level MRV system, which may make...
The design and implementation of PMRV may benefit from the extensive research and application of participatory monitoring of natural resources and biodiversity. The important lessons learnt from participatory monitoring include the potential incentives required for participation, factors that may contribute to the sustainability of the program and upscaling of the monitoring program. However, participatory monitoring and PMRV have different aims and requirements. A successful participatory monitoring program collects local data that are aligned with the interests of local communities to improve local management decisions that benefit them. The objectives of PMRV are to collect local carbon stock data to improve...
