Logging residues for charcoal production through forest management in the Brazilian Amazon: Economic gains and forest regrowth effects.
2020
Sustainable forest management practices can potentially reverse loss of forest cover due to deforestation, while concomitantly preserving and maintaining biodiversity, and stimulating jobs, income, and forest services. Recent studies found that significant logging residues (i.e., leaves, branches, and buttress roots) suitable for bioenergy production were often left in the felling area, triggering risks of forest fires and increased CO2 emissions due to wildfires or decomposition processes. For impact assessment of forest management practices, we collected primary harvesting data and estimated net primary productivity (NPP) and net ecosystem exchange (NEE) for 13 forest plots in the Brazilian Amazon. We applied a process-based forestry growth model (BGC-Man) to analyze the impacts on forest dynamics of selective logging and removal of logging residues, subject to landscape, soil texture, and daily weather. We explored the following selective logging scenarios: the Legal Reserve (i.e., reference) scenario, a scenario with one cutting cycle over the whole period, and a scenario with three timber rotation periods of 30 years. Two of the later scenarios were complemented with harvesting of the woody logging residues (LR; O≥10 cm) for charcoal production. For each scenario, we computed forest NPP and NEE over a 120-year time horizon. Results suggest that using woody logging residues (i.e., 77% of total LR) for charcoal production would result in an economic gain equivalent to 24-46% of the timber price. Our findings indicate that under scenarios where LR were removed, forest NPP recovered to the reference level and even higher, while income and jobs from harvesting LR for charcoal production were generated. We conclude that sustainable forest management could enhance forest productivity and deliver economic benefit from otherwise unexploited logging residues.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
64
References
1
Citations
NaN
KQI