Generic management procedures for data-poor fisheries: forecasting with few data
| dc.contributor.author | Geromont, Helena F | |
| dc.contributor.author | Butterworth, Doug S | |
| dc.date.accessioned | 2016-03-24T07:34:22Z | |
| dc.date.available | 2016-03-24T07:34:22Z | |
| dc.date.issued | 2015 | |
| dc.date.updated | 2016-03-24T07:30:26Z | |
| dc.description.abstract | The majority of fish stocks worldwide are not managed quantitatively as they lack sufficient data, particularly a direct index of abundance, on which to base an assessment. Often these stocks are relatively “low value”, which renders dedicated scientific management too costly, and a generic solution is therefore desirable. A management procedure (MP) approach is suggested where simple harvest control rules are simulation tested to check robustness to uncertainties. The aim of this analysis is to test some very simple “off-the-shelf” MPs that could be applied to groups of data-poor stocks which share similar key characteristics in terms of status and demographic parameters. For this initial investigation, a selection of empirical MPs is simulation tested over a wide range of operating models (OMs) representing resources of medium productivity classified as severely depleted, to ascertain how well these different MPs perform. While the data-moderate MPs (based on an index of abundance) perform somewhat better than the data-limited ones (which lack such input) as would be expected, the latter nevertheless perform surprisingly well across wide ranges of uncertainty. These simple MPs could well provide the basis to develop candidate MPs to manage data-limited stocks, ensuring if not optimal, at least relatively stable sustainable future catches. | en_ZA |
| dc.identifier | http://dx.doi.org/10.1093/icesjms/fst232 | |
| dc.identifier.apacitation | Geromont, H. F., & Butterworth, D. S. (2015). Generic management procedures for data-poor fisheries: forecasting with few data. <i>ICES Journal of Marine Science</i>, http://hdl.handle.net/11427/18206 | en_ZA |
| dc.identifier.chicagocitation | Geromont, Helena F, and Doug S Butterworth "Generic management procedures for data-poor fisheries: forecasting with few data." <i>ICES Journal of Marine Science</i> (2015) http://hdl.handle.net/11427/18206 | en_ZA |
| dc.identifier.citation | Geromont, H. F., & Butterworth, D. S. (2015). Generic management procedures for data-poor fisheries: forecasting with few data. ICES Journal of Marine Science: Journal du Conseil, 72(1), 251-261. | en_ZA |
| dc.identifier.issn | 1054-3139 | en_ZA |
| dc.identifier.ris | TY - Journal Article AU - Geromont, Helena F AU - Butterworth, Doug S AB - The majority of fish stocks worldwide are not managed quantitatively as they lack sufficient data, particularly a direct index of abundance, on which to base an assessment. Often these stocks are relatively “low value”, which renders dedicated scientific management too costly, and a generic solution is therefore desirable. A management procedure (MP) approach is suggested where simple harvest control rules are simulation tested to check robustness to uncertainties. The aim of this analysis is to test some very simple “off-the-shelf” MPs that could be applied to groups of data-poor stocks which share similar key characteristics in terms of status and demographic parameters. For this initial investigation, a selection of empirical MPs is simulation tested over a wide range of operating models (OMs) representing resources of medium productivity classified as severely depleted, to ascertain how well these different MPs perform. While the data-moderate MPs (based on an index of abundance) perform somewhat better than the data-limited ones (which lack such input) as would be expected, the latter nevertheless perform surprisingly well across wide ranges of uncertainty. These simple MPs could well provide the basis to develop candidate MPs to manage data-limited stocks, ensuring if not optimal, at least relatively stable sustainable future catches. DA - 2015 DB - OpenUCT DP - University of Cape Town J1 - ICES Journal of Marine Science LK - https://open.uct.ac.za PB - University of Cape Town PY - 2015 SM - 1054-3139 T1 - Generic management procedures for data-poor fisheries: forecasting with few data TI - Generic management procedures for data-poor fisheries: forecasting with few data UR - http://hdl.handle.net/11427/18206 ER - | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11427/18206 | |
| dc.identifier.uri | http://icesjms.oxfordjournals.org/content/72/1/251.abstract?keytype=ref&ijkey=mGoDH49NJzGbeaj | |
| dc.identifier.vancouvercitation | Geromont HF, Butterworth DS. Generic management procedures for data-poor fisheries: forecasting with few data. ICES Journal of Marine Science. 2015; http://hdl.handle.net/11427/18206. | en_ZA |
| dc.language | eng | en_ZA |
| dc.publisher | Oxford University Press | 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.source | ICES Journal of Marine Science | en_ZA |
| dc.source.uri | http://icesjms.oxfordjournals.org/ | |
| dc.subject.other | Bayes | |
| dc.subject.other | data-poor | |
| dc.subject.other | generic | |
| dc.subject.other | management procedures | |
| dc.subject.other | simulations | |
| dc.subject.other | target/limit reference points | |
| dc.subject.other | uncertainty | |
| dc.subject.other | yield/risk trade-offs | |
| dc.title | Generic management procedures for data-poor fisheries: forecasting with few data | en_ZA |
| dc.type | Journal Article | en_ZA |
| uct.type.filetype | Text | |
| uct.type.publication | Research | en_ZA |
| uct.type.resource | Article | en_ZA |