Integrated models show a transient opportunity for sustainable management by tropical forest dwellers
2019
Nearly 25% of world’s poor are dependent on forests, with 0.5–1 billion smallholders managing trees. This extensive human use of forests points to the need for sustainable timber management (STM) at smallholder scales. Similar to other tropical regions, households in the Amazon Estuary have harvested timber informally with minimal management for decades. This research provides a comprehensive look at the ecological and economic sustainability of forest use by local smallholders by integrating detailed plant demography, microeconomic, management and land use models at a whole watershed and community scale.In terms of conservation outcomes, resulting models show that forest management results in extensive harvests that allow for faster tree population recovery. In terms of economic outcomes, management also improves the long-term viability of the local timber industry in all scenarios considered. However, with respect to harvest regulations, given the costs of legalizing these small informal operations, legalization may indirectly lead to heavier ecological impacts as households need to harvest more to keep economic returns similar to the predominant alternative land use in the region (açaí palm fruit agroforestry).Despite a fast-growing and resource-rich forest, an increasing extent of degraded forest area reduces the ecological and economic prospects for long-term management. Consequently, for this and other similar tropical forests, the viability of STM should not be evaluated as a binary and static yes or no response but instead as a moving window of opportunity that occurs when ecological, economic and policy conditions are met. Integrated model projections show that regionally-derived and ecologically-based sustainable management guidelines widen this window of opportunity by delivering the best ecological and economic outcomes under a range of scenarios considered.
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Эту запись предоставил National Agricultural Library