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Open AccessArticle

Determining a Carbon Reference Level for a High-Forest-Low-Deforestation Country

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International Institute for Applied Systems Analysis (IIASA), 2361 Laxenburg, Austria
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KU Leuven - Catholic University of Leuven, 3000 Leuven, Belgium
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Sustainable Development Solutions Network (SDSN), 75009 Paris, France
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Technical REDD+ Secretariat (ST-REDD), Ministry of the Environment (MINEPDED), Yaoundé, Cameroon
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UNIQUE forestry and land use GmbH, 79098 Freiburg, Germany
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Albert Ludwig University of Freiburg, 79085 Freiburg im Breisgau, Germany
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US Forest Service (USFS), P.O. Box 14 Brazzaville, Republic of Congo
*
Author to whom correspondence should be addressed.
Forests 2019, 10(12), 1095; https://doi.org/10.3390/f10121095
Received: 30 September 2019 / Revised: 19 November 2019 / Accepted: 20 November 2019 / Published: 2 December 2019
(This article belongs to the Special Issue Remote Sensing Technology Applications in Forestry and REDD+)
Research Highlights: A transparent approach to developing a forest reference emissions level (FREL) adjusted to future local developments in Southern Cameroon is demonstrated. Background and Objectives: Countries with low historical deforestation can adjust their forest reference (emission) level (FREL/FRL) upwards for REDD+ to account for likely future developments. Many countries, however, find it difficult to establish a credible adjusted reference level. This article demonstrates the establishment of a FREL for southern Cameroon adjusted to societal megatrends of strong population—and economic growth combined with rapid urbanization. It demonstrates what can be done with available information and data, but most importantly outlines pathways to further improve the quality of future FREL/FRL’s in light of possibly accessing performance-based payments. Materials and Methods: The virtual FREL encompasses three main elements: Remotely sensed activity data; emission factors derived from the national forest inventory; and the adjustment of the reference level using a land use model of the agriculture sector. Sensitivity analysis is performed on all three elements using Monte Carlo methods. Results: Deforestation during the virtual reference period 2000–2015 is dominated by non-industrial agriculture (comprising both smallholders and local elites) and increases over time. The land use model projections are consistent with this trend, resulting in emissions that are on average 47% higher during the virtual performance period 2020–2030 than during the reference period 2000–2015. Monte Carlo analysis points to the adjustment term as the main driver of uncertainty in the FREL calculation. Conclusions: The available data is suitable for constructing a FREL for periodic reporting to the UNFCCC. Enhanced coherence of input data notably for activity data and adjustment is needed to apply for a performance-based payment scheme. Expanding the accounting framework to include forest degradation and forest gain are further priorities requiring future research. View Full-Text
Keywords: REDD+; Cameroon; reference level; deforestation; agriculture; forest baseline REDD+; Cameroon; reference level; deforestation; agriculture; forest baseline
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MDPI and ACS Style

Pirker, J.; Mosnier, A.; Nana, T.; Dees, M.; Momo, A.; Muys, B.; Kraxner, F.; Siwe, R. Determining a Carbon Reference Level for a High-Forest-Low-Deforestation Country. Forests 2019, 10, 1095.

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