A spatial multi-species operating model of the Antarctic Peninsula krill fishery and its impacts on land-breeding predators
| dc.contributor.author | Plagányi, Éva E | |
| dc.contributor.author | Butterworth, Doug S | |
| dc.date.accessioned | 2016-04-04T08:56:40Z | |
| dc.date.available | 2016-04-04T08:56:40Z | |
| dc.date.issued | 2007 | |
| dc.date.updated | 2016-04-04T08:54:50Z | |
| dc.description.abstract | The west coast rock lobster assessment of 20061 based on data to 2004 is updated to include data up to 2008. Over the last four years the exploitable biomass trend is upwards for Areas 7 and 8 and the resource as a whole, but downwards for Areas 5+6 and almost level for Areas 1+2 and 3+4. The overall increase since 2006 is significant at the 5% level. While better than median projections at the time the current OMP developed, the increase remains within the 95% probability intervals calculated at the time. An updated version of the Spatial Multi-species Operating Model (SMOM) of krillpredator-fishery dynamics is described. This has been developed in response to requests for scientific advice regarding the subdivision of the precautionary catch limit for krill among 15 small-scale management units (SSMUs) in the Scotia Sea, to reduce the potential impact of fishing on land-based predators. 2. The numerous uncertainties regarding the appropriate choice of parameter values in multi-species models is a major impediment. A pragmatic method proposed involves use of an operating model comprising alternative combinations that essentially try to bound the uncertainty in, for example, the choice of survival rate estimates as well as the functional relationships between predators and prey. 3. The operating model is assumed to simulate the “true” dynamics of the resource and is used to test decision rules for adjusting fishing activities (e.g. catch limits) based on field data forthcoming in the future. 4. An illustrative Management Procedure (MP) that includes a feedback structure is shown to perform better in terms of low risk to predators within each SSMU, than an approach lacking the ability to react and self-correct. 5. This modeling framework provides an example of a method for bounding some of the uncertainty associated with multi-species models used for management. Results are presented as probability envelopes rather than in point estimate form, giving a truer reflection of the uncertainty inherent in outcomes predicted on the basis of multi-species models, as well as highlighting how such probability envelopes could be narrowed given improved data on key parameters such as survival. Results are useful for evaluating the relative merits of different spatial allocations of krill catches. An example is given of 2 how such a framework can be used to develop a management scheme which includes feedback through management control rules. | en_ZA |
| dc.identifier.apacitation | Plagányi, É. E., & Butterworth, D. S. (2007). <i>A spatial multi-species operating model of the Antarctic Peninsula krill fishery and its impacts on land-breeding predators</i> University of Cape Town ,Faculty of Science ,Marine Resource Assessment and Management Group. Retrieved from http://hdl.handle.net/11427/18523 | en_ZA |
| dc.identifier.chicagocitation | Plagányi, Éva E, and Doug S Butterworth <i>A spatial multi-species operating model of the Antarctic Peninsula krill fishery and its impacts on land-breeding predators.</i> University of Cape Town ,Faculty of Science ,Marine Resource Assessment and Management Group, 2007. http://hdl.handle.net/11427/18523 | en_ZA |
| dc.identifier.citation | Plagányi, É., & Butterworth, D. (2007). A spatial multi-species operating model of the Antarctic Peninsula krill fishery and its impacts on land-breeding predators. In Workshop document presented to WG-SAM subgroup of CCAMLR (Commission for the Conservation of Antarctic Marine Living Resources), WG-SAM-07/12. CCAMLR, Hobart, Australia. | en_ZA |
| dc.identifier.ris | TY - Working Paper AU - Plagányi, Éva E AU - Butterworth, Doug S AB - The west coast rock lobster assessment of 20061 based on data to 2004 is updated to include data up to 2008. Over the last four years the exploitable biomass trend is upwards for Areas 7 and 8 and the resource as a whole, but downwards for Areas 5+6 and almost level for Areas 1+2 and 3+4. The overall increase since 2006 is significant at the 5% level. While better than median projections at the time the current OMP developed, the increase remains within the 95% probability intervals calculated at the time. An updated version of the Spatial Multi-species Operating Model (SMOM) of krillpredator-fishery dynamics is described. This has been developed in response to requests for scientific advice regarding the subdivision of the precautionary catch limit for krill among 15 small-scale management units (SSMUs) in the Scotia Sea, to reduce the potential impact of fishing on land-based predators. 2. The numerous uncertainties regarding the appropriate choice of parameter values in multi-species models is a major impediment. A pragmatic method proposed involves use of an operating model comprising alternative combinations that essentially try to bound the uncertainty in, for example, the choice of survival rate estimates as well as the functional relationships between predators and prey. 3. The operating model is assumed to simulate the “true” dynamics of the resource and is used to test decision rules for adjusting fishing activities (e.g. catch limits) based on field data forthcoming in the future. 4. An illustrative Management Procedure (MP) that includes a feedback structure is shown to perform better in terms of low risk to predators within each SSMU, than an approach lacking the ability to react and self-correct. 5. This modeling framework provides an example of a method for bounding some of the uncertainty associated with multi-species models used for management. Results are presented as probability envelopes rather than in point estimate form, giving a truer reflection of the uncertainty inherent in outcomes predicted on the basis of multi-species models, as well as highlighting how such probability envelopes could be narrowed given improved data on key parameters such as survival. Results are useful for evaluating the relative merits of different spatial allocations of krill catches. An example is given of 2 how such a framework can be used to develop a management scheme which includes feedback through management control rules. DA - 2007 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2007 T1 - A spatial multi-species operating model of the Antarctic Peninsula krill fishery and its impacts on land-breeding predators TI - A spatial multi-species operating model of the Antarctic Peninsula krill fishery and its impacts on land-breeding predators UR - http://hdl.handle.net/11427/18523 ER - | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11427/18523 | |
| dc.identifier.vancouvercitation | Plagányi ÉE, Butterworth DS. A spatial multi-species operating model of the Antarctic Peninsula krill fishery and its impacts on land-breeding predators. 2007 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/18523 | en_ZA |
| dc.language | eng | en_ZA |
| dc.publisher.department | Marine Resource Assessment and Management Group | en_ZA |
| dc.publisher.faculty | Faculty of Science | en_ZA |
| dc.publisher.institution | University of Cape Town | |
| dc.subject.other | Antarctic Peninsula | |
| dc.subject.other | krill | |
| dc.subject.other | Management Procedure | |
| dc.subject.other | Multi-species model | |
| dc.subject.other | Operating model | |
| dc.subject.other | predator-prey | |
| dc.subject.other | uncertainty | |
| dc.title | A spatial multi-species operating model of the Antarctic Peninsula krill fishery and its impacts on land-breeding predators | en_ZA |
| dc.type | Working Paper | en_ZA |
| uct.type.filetype | Text | |
| uct.type.publication | Research | en_ZA |
| uct.type.resource | Research paper | en_ZA |