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Enrichment Planting in Selectively Logged Rain Forest: A Combined Ecological and Economic Analysis
We demonstrate how research on innovative agroforestry systems, incorporating new species and management approaches, can benefit from preliminary financial appraisals that include both economic and ecological variables in quantitative cost—benefit models. Model results provide vital information for planning further research, and thus increase the likelihood of finding practical solutions to urgent resource management problems within reasonable funding and time constraints. As a case study, we evaluate the potential of enrichment plantings of three native fruit—producing genera in selectively logged rain forests of Kalimantan, Indonesia. The models use preliminary estimates of 8 ecological parameters (e.g., survival, growth rate, fruit production) and 11 economic parameters (e.g., planting and harvesting costs, market prices) to predict net present value (NPV) over a variety of project durations and discount rates. Sensitivity analyses examine the effect of changes in input parameters. The genera were chosen (1) for ecological complementarity in the use of light resources and (2) to produce fruit at times when commonly harvested species are unavailable in markets. Dialium spp. are canopy trees that produce timber and a relatively nonperishable fruit; Willughbeia spp. are fast—growing lianas that produce fruit; Garcinia spp. are understory fruit trees. Sensitivity analyses indicate that all three genera have potential for substantial positive NPV, and that NPV projections depend heavily upon fruit price, fruit production, age of first reproduction, juvenile survivorship, and harvesting and marketing costs. In addition, these analyses demonstrate that preliminary, combined ecological—economic analysis can guide the selection of species and research strategies for experimental trials.
Enrichment Planting in Selectively Logged Rain Forest: A Combined Ecological and Economic Analysis
We demonstrate how research on innovative agroforestry systems, incorporating new species and management approaches, can benefit from preliminary financial appraisals that include both economic and ecological variables in quantitative cost—benefit models. Model results provide vital information for planning further research, and thus increase the likelihood of finding practical solutions to urgent resource management problems within reasonable funding and time constraints. As a case study, we evaluate the potential of enrichment plantings of three native fruit—producing genera in selectively logged rain forests of Kalimantan, Indonesia. The models use preliminary estimates of 8 ecological parameters (e.g., survival, growth rate, fruit production) and 11 economic parameters (e.g., planting and harvesting costs, market prices) to predict net present value (NPV) over a variety of project durations and discount rates. Sensitivity analyses examine the effect of changes in input parameters. The genera were chosen (1) for ecological complementarity in the use of light resources and (2) to produce fruit at times when commonly harvested species are unavailable in markets. Dialium spp. are canopy trees that produce timber and a relatively nonperishable fruit; Willughbeia spp. are fast—growing lianas that produce fruit; Garcinia spp. are understory fruit trees. Sensitivity analyses indicate that all three genera have potential for substantial positive NPV, and that NPV projections depend heavily upon fruit price, fruit production, age of first reproduction, juvenile survivorship, and harvesting and marketing costs. In addition, these analyses demonstrate that preliminary, combined ecological—economic analysis can guide the selection of species and research strategies for experimental trials.
Enrichment Planting in Selectively Logged Rain Forest: A Combined Ecological and Economic Analysis
Schulze, Peter C. (Autor:in) / Leighton, Mark (Autor:in) / Peart, David R. (Autor:in)
Ecological Applications ; 4 ; 581-592
01.08.1994
12 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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