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Making conservation decisions under uncertainty for the persistence of multiple species
journal contribution
posted on 2007-01-01, 00:00 authored by Emily Nicholson, H P PossinghamPopulation models for multiple species provide one of the few means of assessing the impact of alternative management options on the persistence of biodiversity, but
they are inevitably uncertain. Is it possible to use population models in multiple-speciesconservation planning given the associated uncertainties? We use information-gap decision theory to explore the impact of parameter uncertainty on the conservation decision when planning for the persistence of multiple species. An information-gap approach seeks robust outcomes that are most immune from error. We assess the impact of uncertainty in key model parameters for three species, whose extinction risks under four alternative management scenarios are estimated using a metapopulation model. Three methods are described for making conservation decisions across the species, taking into account uncertainty. We find that decisions based on single species are relatively robust to uncertainty in parameters, although the estimates of extinction risk increase rapidly with uncertainty. When identifying the best conservation decision for the persistence of all species, the methods that rely on the rankings of the management options by each species result in decisions that are similarly robust to uncertainty. Methods that depend on absolute values of extinction risk are sensitive to uncertainty, as small changes in extinction risk can alter the ranking of the alternative scenarios. We discover that it is possible to make robust conservation decisions even when the uncertainties of the multiple-species problem appear overwhelming. However, the decision most robust to uncertainty is likely to differ from the best decision when uncertainty is ignored, illustrating the importance of incorporating uncertainty into the decision-making process.
they are inevitably uncertain. Is it possible to use population models in multiple-speciesconservation planning given the associated uncertainties? We use information-gap decision theory to explore the impact of parameter uncertainty on the conservation decision when planning for the persistence of multiple species. An information-gap approach seeks robust outcomes that are most immune from error. We assess the impact of uncertainty in key model parameters for three species, whose extinction risks under four alternative management scenarios are estimated using a metapopulation model. Three methods are described for making conservation decisions across the species, taking into account uncertainty. We find that decisions based on single species are relatively robust to uncertainty in parameters, although the estimates of extinction risk increase rapidly with uncertainty. When identifying the best conservation decision for the persistence of all species, the methods that rely on the rankings of the management options by each species result in decisions that are similarly robust to uncertainty. Methods that depend on absolute values of extinction risk are sensitive to uncertainty, as small changes in extinction risk can alter the ranking of the alternative scenarios. We discover that it is possible to make robust conservation decisions even when the uncertainties of the multiple-species problem appear overwhelming. However, the decision most robust to uncertainty is likely to differ from the best decision when uncertainty is ignored, illustrating the importance of incorporating uncertainty into the decision-making process.
History
Journal
Ecological applicationsVolume
17Issue
1Pagination
251 - 265Publisher
Ecological Society of AmericaLocation
Philadelphia, P.A.ISSN
1051-0761Language
engPublication classification
C Journal article; C1.1 Refereed article in a scholarly journalCopyright notice
2007, Ecological Society of AmericaUsage metrics
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conservation planninginformation-gap decision theorymulti-criteria decision analysismultiple-species decision makingpopulation viability analysisTumutNew South WalesAustraliaScience & TechnologyLife Sciences & BiomedicineEcologyEnvironmental SciencesEnvironmental Sciences & EcologymetapopulationuncertaintySPATIAL PVA MODELSVIABILITY ANALYSISEXTINCTION RISKMEAN TIMEPOPULATIONMANAGEMENTPREDICTIONSMETAPOPULATIONSSENSITIVITY
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