Recent studies have shown that fragmentation is an increasing threat to global forests, which has major impacts on biodiversity and the important ecosystem services provided by forested landscapes. Several tools have been developed to evaluate global patterns of fragmentation, which have potential applications for REDD+. We study how canopy height and above ground biomass (AGB) change across several categories of forest edges determined by fragmentation analysis. We use Democratic Republic of Congo (DRC) as an example. An analysis of variance of different edge widths and airborne estimated canopy height found that canopy heights were significantly different in forest edges at a distance of 100 m from the nonforest edge. Biomass was significantly different between fragmentation classes at an edge distance of 300 m. Core forest types were found to have significantly higher canopy height and greater AGB than forest edges and patches, where height and biomass decrease significantly as the level of fragmentation increases. A change analysis shows that deforestation and degradation are increasing over time and biomass loss associated with degradation account for at least one quarter of total loss. We estimate that about 80 % of primary forests are intact, which decreases 3.5 % over the 15 year study period, as primary forest is either deforested or transitioned to forest edge. While the carbon loss per hectare is lower than that of deforestation, degradation potentially affects up to three times more area than deforestation alone. When defining forest degradation by decreased biomass without any loss in forest area, assessing transitions of core forest to edges over time can contribute an important element to REDD+MRV systems. The estimation of changes between different forest fragmentation types and their associated biomass loss can provide an estimate of degradation carbon emission factors. Forest degradation and emissions due to fragmentation are often underestimated and should comprise an essential component of MRV systems.

Stable forests – those not already significantly disturbed nor facing predictable near-future risks of anthropogenic disturbance – may play a large role in the climate solution, due to their carbon sequestration and storage capabilities. Their importance is recognized by the Paris Agreement, but stable forests have received comparatively little attention through existing forest protection mechanisms and finance. Instead, emphasis has been placed on targeting locations where deforestation and forest degradation are happening actively. Yet stopping deforestation and forest degradation does not guarantee durable success, especially outside the geographic scope of targeted efforts. As a result, today’sstable forests may be at risk without additional efforts to secure their long-term conservation. We synthesize the gaps in existing policy efforts that could address the climate-related benefits derived from stable forests, noting several barriers to action, such as uncertainty around the level of climate services that stable forests provide and difficulties describing the real level of threat posed. We argue that resource and finance allocation for stable forests should be incorporated into countries’ and donors’ comprehensive portfolios aimed at tackling deforestation and forest degradation as well as resulting emissions. A holistic and forward-looking approach will be particularly important, given that success in tackling deforestation and forest degradation where it is currently happening will need to be sustained in the long term.

To implement the REDD+ mechanism (Reducing Emissions for Deforestation and Forest Degradation, countries need to prioritize areas to combat future deforestation CO2 emissions, identify the drivers of deforestation around which to develop mitigation actions, and quantify and value carbon for financial mechanisms. Each comes with its own methodological challenges, and existing approaches and tools to do so can be costly to implement or require considerable technical knowledge and skill. Here, we present an approach utilizing a machine learning technique known as Maximum Entropy Modeling (Maxent) to identify areas at high deforestation risk in the study area in Madre de Dios, Peru under a business-as-usual scenario in which historic deforestation rates continue. We link deforestation risk area to carbon density values to estimate future carbon emissions. We quantified area deforested and carbon emissions between 2000 and 2009 as the basis of the scenario.

Reducing deforestation and forest degradation presents a climate-change mitigation opportunity that is critical to meeting the Paris Agreement goals, and to achieving reductions in the atmospheric concentrations of greenhouse gases (GHGs). Reducing Emissions from Deforestation and Forest Degradation (REDD) provides developing countries with results-based financial incentives for reducing deforestation and forest degradation through either non-market payments (payments without generation of carbon credits), or market-based mechanisms (carbon credits). REDD credits have been recently accepted to be used in offsetting programs (e.g., CORSIA) and are being considered under Article 6. However, various publications have questioned whether carbon credits from REDD should be accepted under market-based mechanisms, and have identified issues regarding their environmental integrity and their ability to offset emissions from other sectors. In recent years, REDD implementation has moved from the project level to the national or subnational (jurisdictional) level, and is addressing some of the concerns that have been raised for project-level interventions regarding the robustness of baselines and leakage, for example. In this paper we compare the environmental integrity of credits from REDD programs with that from on-grid renewable energy projects by examining aspects related to permanence, additionality, baselines, uncertainty, and leakage. We show that the environmental integrity of emission reductions sourced from REDD programs has unique strengths, and that those sourced from renewable energy projects have weaknesses of their own. Probably due to a lack of understanding of the respective weaknesses and strengths of these two sources of credits, the emission reductions from REDD programs have been historically questioned and subjected to a level of scrutiny that has not been made with emission reductions from other sectors, such as renewable energy projects. Recognizing the strengths and weaknesses of emission reductions from both types should help decision makers and carbon standards recognize the high quality of emission reductions from REDD programs, and rationalize the current requirements or restrictions imposed.