Forest Protection and Permanence of Reduced Emissions

McCallister, M., Krasovskiy, A. ORCID: https://orcid.org/0000-0003-0940-9366, Platov, A., Golub, A.A., Pietracci, B., & Leslie, G. (2021). Forest Protection and Permanence of Reduced Emissions. Environmental Defense Fund Economics Discussion Paper Series, EDF EDP 21-08 10.2139/ssrn.3964985.

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Abstract

Tropical forests are essential for climate change mitigation. As awareness grows over the use of credits from reduced emissions from deforestation and forest degradation (REDD+) and other nature-based climate solutions within both voluntary and compliance carbon markets, key concerns about the long-term durability of the reductions, or their permanence, arise for countries, corporations, regulators and policy makers. The paper seeks to analyze an efficient means of distribution and application of different policy pathways to slow down and stop deforestation and explore the longevity of reductions via modeling. The impact of policies like REDD+ most likely will have a time limitation. At some point tropical nations will take more responsibility to protect forests. REDD+ should constitute an initial intervention that will help tropical nations shock to a zero-deforestation trajectory.

To establish conditions of permanence, we conduct numerical analyses using a model based on a cellular automata algorithm that learns from historical deforestation patterns and other spatial features in the Brazilian state of Mato Grosso. The model simulates future deforestation, first applying policy to reduce deforestation and then relaxing the policy intervention.

Our simulations show that policies that are successful in reducing deforestation and related emissions from business as usual may have long-term positive consequences on an avoided deforestation trajectory even after potential policy reversals. Some accumulated gains could be lost but sizable benefits will remain, assuring permanence of emissions reduction during the policy implementation and potentially even after policies are relaxed. Hence, permanence depends both on the probability of policy reversals and the risk of emissions rebounding.

Our results are important for advancing the understanding around the unsettled debate on the permanence of avoided emissions. Further, this paper argues that as policies to prevent deforestation or reduce emissions otherwise are reversible, permanence should be understood and discussed in a probabilistic and time-dependent framework.

Item Type: Other
Uncontrolled Keywords: Deforestation, REDD+ permanence, jurisdictional approach, machine learning
Research Programs: Biodiversity and Natural Resources (BNR)
Biodiversity and Natural Resources (BNR) > Agriculture, Forestry, and Ecosystem Services (AFE)
Depositing User: Luke Kirwan
Date Deposited: 24 Nov 2021 13:31
Last Modified: 24 Nov 2021 13:31
URI: http://pure.iiasa.ac.at/17654

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