The dream and the reality: meeting decision-making time frames while incorporating ecosystem and economic models into management strategy evaluation ,

Atlantic herring (Clupea harengus) in the Northwest Atlantic have been managed with interim harvest control rules (HCRs). A stakeholder-driven management strategy evaluation (MSE) was conducted that incorporated a broad range of objectives. The MSE process was completed within 1 year. Constant catch...

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Bibliographic Details
Published in:Canadian Journal of Fisheries and Aquatic Sciences
Main Authors: Deroba, Jonathan J., Gaichas, Sarah K., Lee, Min-Yang, Feeney, Rachel G., Boelke, Deirdre, Irwin, Brian J.
Format: Article in Journal/Newspaper
Language:English
Published: Canadian Science Publishing 2019
Subjects:
Online Access:http://dx.doi.org/10.1139/cjfas-2018-0128
http://www.nrcresearchpress.com/doi/full-xml/10.1139/cjfas-2018-0128
http://www.nrcresearchpress.com/doi/pdf/10.1139/cjfas-2018-0128
Description
Summary:Atlantic herring (Clupea harengus) in the Northwest Atlantic have been managed with interim harvest control rules (HCRs). A stakeholder-driven management strategy evaluation (MSE) was conducted that incorporated a broad range of objectives. The MSE process was completed within 1 year. Constant catch, conditional constant catch, and a biomass-based (BB) HCR with a 15% restriction on the interannual change in the quota could achieve more stable yields than BB HCRs without such restrictions, but could not attain as high of yields and resulted in more negative outcomes for terns (Sterna hirundo; a predator of herring). A similar range of performance could be achieved by applying a BB HCR annually every 3 years or every 5 years. Predators (i.e., dogfish (Squalus acanthias), bluefin tuna (Thunnus thynnus), and terns) were generally insensitive to the range of HCRs. While median net revenues were sensitive to some HCRs, time series analysis suggests that most HCRs produced a stable equilibrium of net revenue. To meet management needs, some aspects of the simulations were less than might be considered scientifically ideal, but using “models of intermediate complexity” were informative for managers and formed a foundation for future improvements.