Enabling large-scale forest restoration in Minas Gerais state, Brazil

Abstract

Large-scale forest restoration is a cornerstone of Brazil’s new Forest Code and a key element in its National Determined Contribution (NDC) to emissions reduction. But the path to this target remains unclear due to a lack of information on its economics and implementation challenges. Here, we begin to fill this gap by developing a spatially-explicit model for Minas Gerais state that estimates the costs and benefits of native vegetation regeneration under different restoration approaches. Our results show that 36% (0.7 million ha) of the Forest Code debt in Minas Gerais can be restored using only passive restoration, at a cost of US$ 175 ± 47 million. Adding low-cost assisted natural regeneration would increase that number to 75% (1.5 million ha) at a cost of US$ 776 ± 137 million over a 20 yr period. This would result in a potential sequestration of 284 MtCO _2 e. However, including the intensive planting methods needed to restore the remaining 25% of highly degraded areas—to fully solve the Forest Code debt and result in a potential sequestration of 345 MtCO _2 e—would more than double the costs to US$ 1.7 ± 0.3 billion. Our results emphasize the need to implement regional policies that take advantage of the natural regeneration potential as well as prioritize the restoration of areas key to ecosystem services.

Keywords

• passive restoration
• assisted natural regeneration
• Brazil’s Forest Code
• spatial optimization model
• Dinamica EGO