Management strategies for short lived species: The case of Australia's Northern Prawn Fishery: 2. Choosing appropriate management strategies using input controls |
| |
| Institution: | 1. CSIRO, P.O. Box 76, Cleveland, Qld 4163, Australia;2. School of Aquatic and Fishery Sciences, Box 355020, University of Washington, Seattle, WA 98195-5020, USA;3. CSIRO, GPO Box 1538, Hobart, TAS 7001, Australia;4. MRL/TAFI, University of Tasmania, Private Bag 49, Hobart, TAS 7001, Australia;1. Stockholm Resilience Center, Stockholm University, 10691 Stockholm, Sweden;2. Swedish University of Agricultural Sciences, Department of Aquatic Resources, Institute of Marine Research, 54330 Lysekil, Sweden;1. Marine Mammal Commission, Bethesda, MD, USA;2. NOAA Fisheries Southwest Fisheries Science Center, La Jolla, CA, USA;1. School of Environmental and Forest Sciences, University of Washington and The Nature Conservancy, Seattle, WA, United States;2. School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA, United States;3. NOAA Fisheries, Northwest Fisheries Science Center, United States;4. College of Earth, Ocean, and Environment, Emeritus, University of Delaware, United States;5. Fisheries and Oceans Canada, Canada;6. School of Fisheries & Ocean Sciences, University of Alaska Fairbanks, United States;7. Coastal and Marine Laboratory, Florida State University, United States;8. School of Life Sciences and Julie Ann Wrigley Global Institute of Sustainability, Arizona State University, United States;9. Department of Marine and Environmental Sciences, Northeastern University, United States;10. University of Maryland Center for Environmental Science, United States;11. Department of Marine and Coastal Sciences, Rutgers University, United States;12. Institute of Hydrobiology and Fisheries Sciences, University of Hamburg, Germany;13. Horn Point Laboratory, University of Maryland Center for Environmental Science, Cambridge, MD, United States;14. Department of Environmental Science and Policy, University of California Davis, United States;15. CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia;1. CSIRO Oceans and Atmosphere Flagship, Ecosciences Precinct, Dutton Park, QLD, 4750, Australia;2. CSIRO Oceans and Atmosphere Flagship, Castray Esplanade, Hobart, TAS, 7001, Australia;3. School of Aquatic and Fishery Sciences, Box 355020, University of Washington, Seattle, WA, 98195, USA;4. National Marine Fisheries Service, Pacific Islands Fisheries Science Center, Honolulu, HI, 96818, USA;5. Joint Institute for Marine and Atmospheric Research, University of Hawaii—NOAA Fisheries, Honolulu, HI, 96818, USA;6. National Marine Fisheries Service, Northwest Fisheries Science Center, 2725 Montlake Blvd. East, Seattle, WA, 98112, USA;7. National Marine Fisheries Service, Alaska Fisheries Science Center, 7600 Sand Point Way NE, Seattle, WA, 98115, USA;8. National Marine Fisheries Service, Northeast Fisheries Science Center, 166 Water Street, Woods Hole, MA 02543, USA;9. National Marine Fisheries Service, Southeast Fisheries Science Center, 75 Virginia Beach Drive, Miami, FL, 33149-1099, USA;10. Prager Consulting, 2124 SE Grant Street, Portland, OR, 97214, USA;11. National Marine Fisheries Service, Southeast Fisheries Science Center, 101 Pivers Island Road, Beaufort, NC, 28516, USA |
| |
| Abstract: | A Management Strategy Evaluation framework is used to evaluate management strategies based on input controls for the fishery for two tiger prawn species (Penaeus esculentus and Penaeus semisulcatus) in Australia's Northern Prawn Fishery. Three “assessment procedures” are considered and two forms of decision rule. The performance of the management strategies is evaluated in terms of whether stocks are left at (or above) the spawning stock size at which Maximum Sustainable Yield is achieved (SMSY), the long-term discounted total catch and the extent of inter-annual variation in catches. The focus of the analysis is on management strategies based on the current method of stock assessment because an alternative method of assessment based on a biomass dynamics model is found to be highly variable. None of the management strategies tested is able to leave the spawning stock size of P. esculentus near SMSY if the target effort level used in the management strategy is set to EMSY. Accounting for stock structure through the application of a spatially- (stock-) structured assessment approach fails to resolve this problem. Since the assessment method is generally close to unbiased, the failure to leave the stocks close to SMSY is because the measure of control is total effort and the two species are found (and caught) together. Reducing the target effort level to below EMSY increases the final stock size, but the reduced risk comes at a cost of reduced catches. The best management strategy in terms of leaving both species close to SMSY is found to be one that changes the timing of the fishing season so that effort is shifted from P. esculentus to P. semisulcatus and sets more precautionary effort targets for P. esculentus. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
