Stock Assessment: Operational Models in Support of Fisheries Management

被引:56
|
作者
Methot, Richard D., Jr. [1 ]
机构
[1] NOAA Fisheries Serv, Seattle, WA 98112 USA
关键词
Fish stock assessment; population dynamics; fishery management; CATCH; UNCERTAINTY; TRAWL;
D O I
10.1007/978-1-4020-9210-7_9
中图分类号
S9 [水产、渔业];
学科分类号
0908 ;
摘要
Fishery stock assessment models connect ecosystem data to quantitative fishery management. Control rules that calculate annual catch limits and targets from stock assessment results are a common component of US Fishery Management Plans. Ideally, the outcome of such control rules are updated annually on the basis of stock assessment forecasts to track fluctuations in stock abundance. When the stock assessment - fishery management enterprise achieves this level of throughput, they truly are operational models, much as the complex physical models used to routinely update climate forecasts. In reality, many contemporary assessments are closer to an individual scientific investigation than to an operational model. As a result, the review of each stock assessment is extensive and the lag between data acquisition and quota adjustment may extend to several years. If the future stock assessment process is to move towards an operational status, there will need to be changes in three aspects of the process. First, key data streams will themselves need to be made more operational and corporate so that relevant data are immediately available and trusted. Second, stock assessment models need to he made more capable of including diverse relevant data and comprehensively calculating levels of uncertainty, while also being more completely tested, documented, and standardized. The class of models called integrated analysis has these characteristics and is described here, with emphasis on the features of the Stock Synthesis model. Areas of future model development, especially to include more ecosystem and environmental factors, are explored. Third, increased throughput of assessment updates will require streamlining of the extensive review process now routinely required before stock assessment results can serve as the scientific basis for fishery management. Emphasizing review of broadly applicable assessment data and methods, rather than each final result, is a logical step in this streamlining, while maintaining public trust in the final results.
引用
收藏
页码:137 / 165
页数:29
相关论文
共 50 条
  • [31] Stock enhancement as a fisheries management tool
    Brett W. Molony
    R. Lenanton
    G. Jackson
    J. Norriss
    Reviews in Fish Biology and Fisheries, 2005, 13 (4) : 409 - 432
  • [32] Subsidies, Fisheries Management, and Stock Depletion
    Sakai, Yutaro
    LAND ECONOMICS, 2017, 93 (01) : 165 - 178
  • [33] Stock enhancement as a fisheries management tool
    Molony, BW
    Lenanton, R
    Jackson, G
    Norriss, J
    REVIEWS IN FISH BIOLOGY AND FISHERIES, 2003, 13 (04) : 409 - 432
  • [34] Incoherent dimensionality in fisheries management: consequences of misaligned stock assessment and population boundaries
    Berger, Aaron M.
    Deroba, Jonathan J.
    Bosley, Katelyn M.
    Goethel, Daniel R.
    Langseth, Brian J.
    Schueller, Amy M.
    Hanselman, Dana H.
    ICES JOURNAL OF MARINE SCIENCE, 2021, 78 (01) : 155 - 171
  • [35] Stock boundaries for fisheries assessment and management in the Mediterranean: the Balearic Islands as a case study
    Quetglas, Antoni
    Guijarro, Beatriz
    Ordines, Francesc
    Massuti, Enric
    SCIENTIA MARINA, 2012, 76 (01) : 17 - 28
  • [37] Population Models for Assessment and Management of Inland Striped Bass Fisheries
    Allen, Micheal S.
    Gwinn, Daniel
    BIOLOGY AND MANAGEMENT OF INLAND STRIPED BASS AND HYBRID STRIPED BASS, 2013, 80 : 351 - 364
  • [38] MODELS FOR FISHERIES MANAGEMENT
    AGNEW, TT
    COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 1982, 7 (03) : 145 - 154
  • [39] Lessons to be learned by comparing integrated fisheries stock assessment models (SAMs) with integrated population models (IPMs)
    Schaub, Michael
    Maunder, Mark N.
    Kery, Marc
    Thorson, James T.
    Jacobson, Eiren K.
    Punt, Andre E.
    FISHERIES RESEARCH, 2024, 272
  • [40] Stock assessment and end-to-end ecosystem models alter dynamics of fisheries data
    Storch, Laura S.
    Glaser, Sarah M.
    Ye, Hao
    Rosenberg, Andrew A.
    PLOS ONE, 2017, 12 (02):