Learning and adaptation in the management of waterfowl harvests
A formal framework for the adaptive management of waterfowl harvests was adopted by the U.S. Fish and Wildlife Service in 1995. The process admits competing models of waterfowl population dynamics and harvest impacts, and relies on model averaging to compute optimal strategies for regulating harvest...
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Veröffentlicht in: | Journal of environmental management 2011-05, Vol.92 (5), p.1385-1394 |
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description | A formal framework for the adaptive management of waterfowl harvests was adopted by the U.S. Fish and Wildlife Service in 1995. The process admits competing models of waterfowl population dynamics and harvest impacts, and relies on model averaging to compute optimal strategies for regulating harvest. Model weights, reflecting the relative ability of the alternative models to predict changes in population size, are used in the model averaging and are updated each year based on a comparison of model predictions and observations of population size. Since its inception the adaptive harvest program has focused principally on mallards (
Anas platyrhynchos), which constitute a large portion of the U.S. waterfowl harvest. Four competing models, derived from a combination of two survival and two reproductive hypotheses, were originally assigned equal weights. In the last year of available information (2007), model weights favored the weakly density-dependent reproductive hypothesis over the strongly density-dependent one, and the additive mortality hypothesis over the compensatory one. The change in model weights led to a more conservative harvesting policy than what was in effect in the early years of the program. Adaptive harvest management has been successful in many ways, but nonetheless has exposed the difficulties in defining management objectives, in predicting and regulating harvests, and in coping with the tradeoffs inherent in managing multiple waterfowl stocks exposed to a common harvest. The key challenge now facing managers is whether adaptive harvest management as an institution can be sufficiently adaptive, and whether the knowledge and experience gained from the process can be reflected in higher-level policy decisions. |
doi_str_mv | 10.1016/j.jenvman.2010.10.064 |
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Anas platyrhynchos), which constitute a large portion of the U.S. waterfowl harvest. Four competing models, derived from a combination of two survival and two reproductive hypotheses, were originally assigned equal weights. In the last year of available information (2007), model weights favored the weakly density-dependent reproductive hypothesis over the strongly density-dependent one, and the additive mortality hypothesis over the compensatory one. The change in model weights led to a more conservative harvesting policy than what was in effect in the early years of the program. Adaptive harvest management has been successful in many ways, but nonetheless has exposed the difficulties in defining management objectives, in predicting and regulating harvests, and in coping with the tradeoffs inherent in managing multiple waterfowl stocks exposed to a common harvest. The key challenge now facing managers is whether adaptive harvest management as an institution can be sufficiently adaptive, and whether the knowledge and experience gained from the process can be reflected in higher-level policy decisions.</description><identifier>ISSN: 0301-4797</identifier><identifier>EISSN: 1095-8630</identifier><identifier>DOI: 10.1016/j.jenvman.2010.10.064</identifier><identifier>PMID: 21168259</identifier><identifier>CODEN: JEVMAW</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>Adaptive management ; Anas platyrhynchos ; Animal populations ; Animals ; Anseriformes ; Birds ; Conservation of Natural Resources - methods ; Decision Making ; Decisions ; Dynamic programming ; Environment ; Environmental Policy ; Exposure ; Harvest ; Harvesting ; Learning ; Mallards ; Management ; Mathematical models ; Modelling ; Models, Biological ; Mortality ; Natural resources ; Optimization ; Policies ; Population Dynamics ; Populations ; Raw materials ; Resource management ; U.S.A ; United States ; Waterfowl ; Wildfowl ; Wildlife conservation</subject><ispartof>Journal of environmental management, 2011-05, Vol.92 (5), p.1385-1394</ispartof><rights>2010</rights><rights>Published by Elsevier Ltd.</rights><rights>Copyright Academic Press Ltd. May 2011</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c488t-f81495f840b034491192fabe8adc0b43a22a69c7a2878db939abfb4956c829893</citedby><cites>FETCH-LOGICAL-c488t-f81495f840b034491192fabe8adc0b43a22a69c7a2878db939abfb4956c829893</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jenvman.2010.10.064$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3548,27923,27924,45994</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21168259$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Johnson, Fred A.</creatorcontrib><title>Learning and adaptation in the management of waterfowl harvests</title><title>Journal of environmental management</title><addtitle>J Environ Manage</addtitle><description>A formal framework for the adaptive management of waterfowl harvests was adopted by the U.S. Fish and Wildlife Service in 1995. The process admits competing models of waterfowl population dynamics and harvest impacts, and relies on model averaging to compute optimal strategies for regulating harvest. Model weights, reflecting the relative ability of the alternative models to predict changes in population size, are used in the model averaging and are updated each year based on a comparison of model predictions and observations of population size. Since its inception the adaptive harvest program has focused principally on mallards (
Anas platyrhynchos), which constitute a large portion of the U.S. waterfowl harvest. Four competing models, derived from a combination of two survival and two reproductive hypotheses, were originally assigned equal weights. In the last year of available information (2007), model weights favored the weakly density-dependent reproductive hypothesis over the strongly density-dependent one, and the additive mortality hypothesis over the compensatory one. The change in model weights led to a more conservative harvesting policy than what was in effect in the early years of the program. Adaptive harvest management has been successful in many ways, but nonetheless has exposed the difficulties in defining management objectives, in predicting and regulating harvests, and in coping with the tradeoffs inherent in managing multiple waterfowl stocks exposed to a common harvest. The key challenge now facing managers is whether adaptive harvest management as an institution can be sufficiently adaptive, and whether the knowledge and experience gained from the process can be reflected in higher-level policy decisions.</description><subject>Adaptive management</subject><subject>Anas platyrhynchos</subject><subject>Animal populations</subject><subject>Animals</subject><subject>Anseriformes</subject><subject>Birds</subject><subject>Conservation of Natural Resources - methods</subject><subject>Decision Making</subject><subject>Decisions</subject><subject>Dynamic programming</subject><subject>Environment</subject><subject>Environmental Policy</subject><subject>Exposure</subject><subject>Harvest</subject><subject>Harvesting</subject><subject>Learning</subject><subject>Mallards</subject><subject>Management</subject><subject>Mathematical models</subject><subject>Modelling</subject><subject>Models, Biological</subject><subject>Mortality</subject><subject>Natural resources</subject><subject>Optimization</subject><subject>Policies</subject><subject>Population Dynamics</subject><subject>Populations</subject><subject>Raw materials</subject><subject>Resource management</subject><subject>U.S.A</subject><subject>United States</subject><subject>Waterfowl</subject><subject>Wildfowl</subject><subject>Wildlife conservation</subject><issn>0301-4797</issn><issn>1095-8630</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkU1P3DAQhq0KVLa0P6FVxKW9ZOuvxPYJIdQC0kpc2rM1cSbgaONs7ewi_n0ddtsDB-BkafS888rzEPKZ0SWjrP7eL3sMuwHCktOn2ZLW8h1ZMGqqUteCHpEFFZSVUhl1Qj6k1FNKBWfqPTnhjNWaV2ZBzlcIMfhwV0BoC2hhM8Hkx1D4UEz3WOQCuMMBw1SMXfEAE8ZufFgX9xB3mKb0kRx3sE746fCekt8_f_y6vC5Xt1c3lxer0kmtp7LTTJqq05I2VEhpGDO8gwY1tI42UgDnUBungGul28YIA03X5EjtNDfaiFPydb93E8c_29xsB58crtcQcNwmq2ulhFS0fp2sFOPCsOoNZMWp5Exm8tuLJFNKsfxRPaNnz9B-3MaQb_PUrIXkM1TtIRfHlCJ2dhP9APHRMmpnvba3B7121juPs96c-3JYvm0GbP-n_vnMwPkewOxi5zHa5DwGh62P6Cbbjv6Vir-gz7Yn</recordid><startdate>20110501</startdate><enddate>20110501</enddate><creator>Johnson, Fred A.</creator><general>Elsevier Ltd</general><general>Academic Press Ltd</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7SN</scope><scope>7ST</scope><scope>7UA</scope><scope>8BJ</scope><scope>C1K</scope><scope>F1W</scope><scope>FQK</scope><scope>H97</scope><scope>JBE</scope><scope>L.G</scope><scope>SOI</scope><scope>7SU</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope><scope>7X8</scope><scope>7U6</scope><scope>H95</scope></search><sort><creationdate>20110501</creationdate><title>Learning and adaptation in the management of waterfowl harvests</title><author>Johnson, Fred A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c488t-f81495f840b034491192fabe8adc0b43a22a69c7a2878db939abfb4956c829893</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Adaptive management</topic><topic>Anas platyrhynchos</topic><topic>Animal populations</topic><topic>Animals</topic><topic>Anseriformes</topic><topic>Birds</topic><topic>Conservation of Natural Resources - methods</topic><topic>Decision Making</topic><topic>Decisions</topic><topic>Dynamic programming</topic><topic>Environment</topic><topic>Environmental Policy</topic><topic>Exposure</topic><topic>Harvest</topic><topic>Harvesting</topic><topic>Learning</topic><topic>Mallards</topic><topic>Management</topic><topic>Mathematical models</topic><topic>Modelling</topic><topic>Models, Biological</topic><topic>Mortality</topic><topic>Natural resources</topic><topic>Optimization</topic><topic>Policies</topic><topic>Population Dynamics</topic><topic>Populations</topic><topic>Raw materials</topic><topic>Resource management</topic><topic>U.S.A</topic><topic>United States</topic><topic>Waterfowl</topic><topic>Wildfowl</topic><topic>Wildlife conservation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Johnson, Fred A.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Aqualine</collection><collection>Ecology Abstracts</collection><collection>Environment Abstracts</collection><collection>Water Resources Abstracts</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>International Bibliography of the Social Sciences</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 3: Aquatic Pollution & Environmental Quality</collection><collection>International Bibliography of the Social Sciences</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Environment Abstracts</collection><collection>Environmental Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>MEDLINE - Academic</collection><collection>Sustainability Science Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources</collection><jtitle>Journal of environmental management</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Johnson, Fred A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Learning and adaptation in the management of waterfowl harvests</atitle><jtitle>Journal of environmental management</jtitle><addtitle>J Environ Manage</addtitle><date>2011-05-01</date><risdate>2011</risdate><volume>92</volume><issue>5</issue><spage>1385</spage><epage>1394</epage><pages>1385-1394</pages><issn>0301-4797</issn><eissn>1095-8630</eissn><coden>JEVMAW</coden><abstract>A formal framework for the adaptive management of waterfowl harvests was adopted by the U.S. Fish and Wildlife Service in 1995. The process admits competing models of waterfowl population dynamics and harvest impacts, and relies on model averaging to compute optimal strategies for regulating harvest. Model weights, reflecting the relative ability of the alternative models to predict changes in population size, are used in the model averaging and are updated each year based on a comparison of model predictions and observations of population size. Since its inception the adaptive harvest program has focused principally on mallards (
Anas platyrhynchos), which constitute a large portion of the U.S. waterfowl harvest. Four competing models, derived from a combination of two survival and two reproductive hypotheses, were originally assigned equal weights. In the last year of available information (2007), model weights favored the weakly density-dependent reproductive hypothesis over the strongly density-dependent one, and the additive mortality hypothesis over the compensatory one. The change in model weights led to a more conservative harvesting policy than what was in effect in the early years of the program. Adaptive harvest management has been successful in many ways, but nonetheless has exposed the difficulties in defining management objectives, in predicting and regulating harvests, and in coping with the tradeoffs inherent in managing multiple waterfowl stocks exposed to a common harvest. The key challenge now facing managers is whether adaptive harvest management as an institution can be sufficiently adaptive, and whether the knowledge and experience gained from the process can be reflected in higher-level policy decisions.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>21168259</pmid><doi>10.1016/j.jenvman.2010.10.064</doi><tpages>10</tpages></addata></record> |
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subjects | Adaptive management Anas platyrhynchos Animal populations Animals Anseriformes Birds Conservation of Natural Resources - methods Decision Making Decisions Dynamic programming Environment Environmental Policy Exposure Harvest Harvesting Learning Mallards Management Mathematical models Modelling Models, Biological Mortality Natural resources Optimization Policies Population Dynamics Populations Raw materials Resource management U.S.A United States Waterfowl Wildfowl Wildlife conservation |
title | Learning and adaptation in the management of waterfowl harvests |
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