2020
DOI: 10.1016/j.ecolmodel.2020.109243
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Optimising harvest strategies over multiple objectives and stakeholder preferences

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Cited by 9 publications
(11 citation statements)
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“…where the management outcome is adjusted until a cross-sector overall optimum is achieved (Dowling et al, 2020).…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…where the management outcome is adjusted until a cross-sector overall optimum is achieved (Dowling et al, 2020).…”
Section: Discussionmentioning
confidence: 99%
“…Research and data collection for RF are also considerably lagging behind those for the commercial sector (Freire et al, 2016), presenting challenges for the develop- 3), although objectives regarding value for recreational and charter fishers were often included in numerous regions. The focus on ecological objectives for the RF sector likely mirrors a broader issue regarding limited implementation of the TBL in fishery HSs (Dowling et al, 2020), because articulating operational social objectives is challenging, as is relating economic objectives to the level of harvest.…”
Section: Ta B L Ementioning
confidence: 99%
“…Multi‐objective optimization can provide a useful framework that allows managers to embrace the trade‐off between profitability and stability rather than focus on a single aim (Mendoza and Martins 2006, Sanchirico et al 2008, Halpern et al 2013). Managers together with stakeholders could track quantitative metrics for multiple objectives (e.g., revenue stability, average revenue per vessel per year, and inequality of the fleet), explicitly weigh how important each of those objectives is (possibly uniquely across user groups), and ultimately select a strategy that balances desired outcomes across the different objectives and groups (Dowling et al 2020).…”
Section: Discussionmentioning
confidence: 99%
“…By including temperature in their forecasts for Pacific cod and arrow tooth flounder of the Bering Sea, Holsman et al (2015) estimated that recommended yields were higher in models that included temperature compared to the same models without temperature effects. Secondly, quantitative forecasting provides evidence for initial discussions between stakeholders (e.g., Dowling et al 2020), which helps to prioritize the remainder of the CAP development process. Discussing the results of the biological forecast at this stage offers a valuable opportunity for stakeholders to express their concerns based on their own observations and experiences, some of which scientists and/or other experts might have overlooked.…”
Section: Task 1 (T1): Assessment Of Risks and Opportunitiesmentioning
confidence: 99%