Improving estimates of CO2 emissions under REDD+ in the Colombian Amazon: Better understanding for climate change mitigation
Navarrete Encinales, Diego Alejandro
Thesis or dissertation
University of Exeter
Land-cover change is the second most important source of anthropogenic greenhouse gases (GHG) emissions, generating around 7-14% of the total carbon dioxide (CO2) emissions around the world. More than one million km2 of tropical forests were lost during the period 2000-2012 around the world, from which forests-to-pasture conversion was the most common land-use change in key regions such as the Amazon. Strategies to mitigate climate change by reducing deforestation and forest degradation (e.g. REDD+) require country- or region-specific information on carbon (C) stocks in forests and their dynamics with land-cover change, in order to develop accurate Forest Reference Emission Levels (FRELs) to be submitted to the UNFCCC as benchmarks for assessing the performance of countries participating in REDD+ activities. Nevertheless, FREL development is incipient and their elaboration is mostly based on highly uncertain Tier 1 information from IPCC. In this research I present the first region-specific Tier 3 information and emission factors on soil, dead wood and below-ground biomass C pools and their dynamics during 20 years of forest-to-pasture conversion under different management practices in the Colombian Amazon. Based on these region-specific Tier 3 emission factors on C stocks in forests and their change after pasture establishment, I report for the first time the net CO2 emissions from forest-to-pasture conversion in the Colombian Amazon. The results also demonstrate that Tier 3 region-specific information is 70% higher and is substantially more accurate than estimates based on using IPCC Tier 1 information, which emphasizes the urgency for countries implementing REDD+ to develop improved data and methodologies. The information reported here will contribute to strengthening the REDD+ National Strategy of Colombia, by supplying accurate data and models that can be included within the next Colombian FREL.
AXA Research Fund
PhD in Geography