Info-Gap Decision Theory for Assessing the Management of Catchments for Timber Production and Urban Water Supply |
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Authors: | Michael A McCarthy David B Lindenmayer |
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Institution: | (1) Australian Research Centre for Urban Ecology, Royal Botanic Gardens Melbourne, c/o The School of Botany, The University of Melbourne, Parkville, VIC, 3010, Australia;(2) Centre for Resource and Environmental Studies, The Australian National University, Canberra, ACT, 0200, Australia |
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Abstract: | While previous studies have examined how forest management is influenced by the risk of fire, they rely on probabilistic estimates
of the occurrence and impacts of fire. However, nonprobabilistic approaches are required for assessing the importance of fire
risk when data are poor but risks are appreciable. We explore impacts of fire risk on forest management using as a case study
a water catchment in the Australian Capital Territory (ACT) (southeastern Australia). In this forested area, urban water supply
and timber yields from exotic plantations are potential joint but also competing land uses. Our analyses were stimulated by
extensive wildfires in early 2003 that burned much of the existing exotic pine plantation estate in the water catchment and
the resulting need to explore the relative economic benefits of revegetating the catchment with exotic plantations or native
vegetation. The current mean fire interval in the ACT is approximately 40 years, making the establishment of a pine plantation
economically marginal at a 4% discount rate. However, the relative impact on water yield of revegetation with native species
and pines is very uncertain, as is the risk of fire under climate change. We use info-gap decision theory to account for these
nonprobabilistic sources of uncertainty, demonstrating that the decision that is most robust to uncertainty is highly sensitive
to the cost of native revegetation. If costs of native revegetation are sufficiently small, this option is more robust to
uncertainty than revegetation with a commercial pine plantation. |
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Keywords: | Economic return Info-gap decision theory Stochastic model Uncertainty |
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