Browsing by Subject "uncertainty"

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    Generic management procedures for data-poor fisheries: forecasting with few data
    (Oxford University Press, 2015) Geromont, Helena F; Butterworth, Doug S
    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.
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    Making management procedures operational—innovations implemented in South Africa
    (Oxford University Press, 2007) Plagányi, Éva E; Rademeyer, Rebecca A; Butterworth, Doug S; Cunningham, Carryn L; Johnston, Susan J
    Operational management procedures (OMPs) have become an indispensable fisheries management tool in South Africa in light of their ability to consider the consequences of the main sources of assessment uncertainty. An overview is provided of the MP approaches applied to the major South African fisheries for hake, sardine and anchovy, and west coast rock lobster. As these are among the first OMPs to be implemented worldwide, some for periods longer than 10 y, they provide useful examples of some of the successes and problems encountered with the approach. Particular emphasis is given to some recent innovations and adaptations. These include moves to (i) joint two-species OMPs for the hake and sardine/anchovy resources; (ii) a reference set of weighted operating models for primary testing and tuning in preference to a single model; (iii) consideration of a “research-conditional” approach for hake to allow greater catches in the short term, conditional on research being implemented to resolve a key uncertainty; and (iv) incorporation of some ecosystem considerations by developing appropriate robustness tests (which link with moves towards an ecosystem approach to fisheries). Key lessons gained from experience over the past decade of OMP implementation in South Africa are summarized.
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    A spatial multi-species operating model of the Antarctic Peninsula krill fishery and its impacts on land-breeding predators
    (2007) Plagányi, Éva E; Butterworth, Doug S
    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.