Improving estimates of population status and trend with superensemble models-Reference-Cited by-同舟云学术

Improving estimates of population status and trend with superensemble models

Published:2017-01-30 Issue:4 Volume:18 Page:732-741
ISSN:1467-2960
Container-title:Fish and Fisheries
language:en
Short-container-title:Fish Fish

Author:

Anderson Sean C¹,Cooper Andrew B¹,Jensen Olaf P²,Minto Cóilín³,Thorson James T⁴,Walsh Jessica C¹,Afflerbach Jamie⁵,Dickey-Collas Mark⁶⁷,Kleisner Kristin M⁸,Longo Catherine⁹,Osio Giacomo Chato¹⁰,Ovando Daniel¹¹,Mosqueira Iago¹⁰,Rosenberg Andrew A¹²,Selig Elizabeth R¹³

Affiliation:

1. School of Resource and Environmental Management; Simon Fraser University; Burnaby BC Canada

2. Institute of Marine & Coastal Sciences; Rutgers University; New Brunswick NJ USA

3. Marine and Freshwater Research Centre; Galway-Mayo Institute of Technology; Galway Ireland

4. Fisheries Resource Analysis and Monitoring Division; Northwest Fisheries Science Center; National Marine Fisheries Service; National Oceanographic and Atmospheric Administration; Seattle WA USA

5. National Center for Ecological Analysis and Synthesis; University of California Santa Barbara; Santa Barbara CA USA

6. International Council for the Exploration of the Sea; Copenhagen Denmark

7. DTU Aqua National Institute of Aquatic Resources; Technical University of Denmark (DTU); Charlottenlund Denmark

8. Ecosystem Assessment Program; Northeast Fisheries Science Center; National Marine Fisheries Service; National Oceanographic and Atmospheric Administration; Woods Hole MA USA

9. Marine Stewarship Council; London UK

10. Unit D.02 Water and Marine Resources; Directorate D - Sustainable Resources; DG Joint Research Centre; European Commission; Ispra Italy

11. Bren School of Environmental Science and Management; University of California Santa Barbara; Santa Barbara CA USA

12. Union of Concerned Scientists; Cambridge MA USA

13. Conservation International; Arlington VA USA

Funder

Gordon and Betty Moore Foundation

Publisher

Wiley

Subject

Management, Monitoring, Policy and Law,Aquatic Science,Ecology, Evolution, Behavior and Systematics,Oceanography

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/faf.12200/fullpdf

Reference60 articles.

1. Error reduction through learning multiple descriptions;Ali;Machine Learning,1996

2. Correlates of vertebrate extinction risk in Canada;Anderson;BioScience,2011

3. Ensemble forecasting of species distributions;Araújo;Trends in Ecology & Evolution,2007

Cited by 69 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. From bottom to up: Effects of fishery improvement projects on the stock trends of multi-specific small-scale fisheries from Mexico;Marine Policy;2024-10

2. Fish weight prediction using empirical and data-driven models in aquaculture systems;2024 IEEE Conference on Control Technology and Applications (CCTA);2024-08-21

3. Empirical validation of integrated stock assessment models to ensuring risk equivalence: A pathway to resilient fisheries management;PLOS ONE;2024-07-02

4. Good practices for surplus production models;Fisheries Research;2024-07

5. The good practices of practicable alchemy in the stock assessment continuum: Fundamentals and principles of analytical methods to support science-based fisheries management under data and resource limitations;Fisheries Research;2024-02