| Multimodel inference and adaptive management. | |
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MedLine Citation:
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PMID: 20961682 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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Ecology is an inherently complex science coping with correlated variables, nonlinear interactions and multiple scales of pattern and process, making it difficult for experiments to result in clear, strong inference. Natural resource managers, policy makers, and stakeholders rely on science to provide timely and accurate management recommendations. However, the time necessary to untangle the complexities of interactions within ecosystems is often far greater than the time available to make management decisions. One method of coping with this problem is multimodel inference. Multimodel inference assesses uncertainty by calculating likelihoods among multiple competing hypotheses, but multimodel inference results are often equivocal. Despite this, there may be pressure for ecologists to provide management recommendations regardless of the strength of their study's inference. We reviewed papers in the Journal of Wildlife Management (JWM) and the journal Conservation Biology (CB) to quantify the prevalence of multimodel inference approaches, the resulting inference (weak versus strong), and how authors dealt with the uncertainty. Thirty-eight percent and 14%, respectively, of articles in the JWM and CB used multimodel inference approaches. Strong inference was rarely observed, with only 7% of JWM and 20% of CB articles resulting in strong inference. We found the majority of weak inference papers in both journals (59%) gave specific management recommendations. Model selection uncertainty was ignored in most recommendations for management. We suggest that adaptive management is an ideal method to resolve uncertainty when research results in weak inference. |
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Authors:
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Sarah E Rehme; Larkin A Powell; Craig R Allen |
Publication Detail:
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Type: Journal Article Date: 2010-10-20 |
Journal Detail:
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Title: Journal of environmental management Volume: 92 ISSN: 1095-8630 ISO Abbreviation: J. Environ. Manage. Publication Date: 2011 May |
Date Detail:
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Created Date: 2011-03-04 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 0401664 Medline TA: J Environ Manage Country: England |
Other Details:
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Languages: eng Pagination: 1360-4 Citation Subset: IM |
Copyright Information:
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Copyright © 2010 Elsevier Ltd. All rights reserved. |
Affiliation:
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Nebraska Cooperative Fish and Wildlife Research Unit, School of Natural Resources, University of Nebraska - Lincoln, NE 68583-0984, USA. |
Export Citation:
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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