Fisheries Research Articles

Identifying capacity limitations and training needs using a stock assessment game

Authors

Andre E. Punt, University of Washington, USA
Catherine M. Dichmont, University of Tasmania
Natalie A. Dowling, Commonwealth Scientific and Industrial Research Organisation
Roy A. Deng, Commonwealth Scientific and Industrial Research Organisation
Sean Pascoe, Commonwealth Scientific and Industrial Research Organisation
Ingrid van Putten, Wageningen University and Research
Pia Bessell-Browne, Commonwealth Scientific and Industrial Research Organisation
Paul Burch, Commonwealth Scientific and Industrial Research Organisation
Owen Burnell, South Australian Research and Development Institute (SARDI)
Rowan Chick, New South Wales Department of Primary Industries
Simon De Lestang, Department of Primary Industries and Regional Development, Western AustraliaFollow
Ainslie Denham, Department of Primary Industries and Regional Development, Western AustraliaFollow
Rubie Evans-Powell, Department of Primary Industries and Regional Development, Western AustraliaFollow
Greg Ferguson, South Australian Research and Development Institute (SARDI)
Ashley M. Fowler, New South Wales Department of Primary Industries
Alise Fox, Fisheries Queensland
Fay Helidoniotis, New South Wales Department of Primary Industries
S. Alex Hesp, Department of Primary Industries and Regional Development, Western AustraliaFollow
Geoffrey Liggins, New South Wales Department of Primary Industries
Deepal G. Pazhayamadom, Department of Agriculture and Fisheries
Hayden T. Schilling, New South Wales Department of Primary Industries
Geoffrey N. Tuck, Commonwealth Scientific and Industrial Research Organisation

Document Type

Article

Publication Date

3-12-2025

Journal Title

Fisheries Research

ISSN

ISSN: 0165-7836, eISSN: 1872-6763

Keywords

Capability, Capacity, Learning Capability, Risk-Free Learning, Simulation, Stock Assessment

Disciplines

Aquaculture and Fisheries | Environmental Monitoring

Abstract

The technical capability of stock assessment analysts, along with characteristics of their operating environment, often limits the development of suitable population dynamics models and affects the accuracy of estimated quantities used for fisheries management. Following a series of training workshops focused on the Stock Synthesis and Stock Assessment Continuum Tool packages, Australian stock assessment scientists were invited to participate in a hypothetical stock assessment “Game” to explore the repercussions , for assessment, of different levels of experience and technical capability in an informal “consequence-free” manner. A fishery data set was generated using a simulation model that represented a stock distributed over 12 regions and harvested by three fishing fleets. The simulation model was made complex by including spatial structure, time-varying selectivity for some fleets, and changes over time in expected recruitment due to the effects of an environmental driver. The analysts self-organized into six (mostly within-agency) groups and reported estimates of current biomass, current depletion and advice regarding the possibility of local depletion. The results of the Game were used to evaluate the approaches used by the various groups and to identify areas where future training would be most beneficial. The results highlighted opportunities for additional training in spatially-explicit population dynamics modelling, the use of methods for pre-processing monitoring data to select appropriate fleet and population structures, as well as the use of methods to provide values related to growth and natural mortality. The groups treated the Game more seriously than was originally intended by the organizers, with several analysts concerned that any errors or assumptions that were mis-matched with the simulated reality may have brought embarrassment to themselves and their agency. Care should therefore be taken that simulation experiments intending to foster collaboration and learning do so in an explicitly understood risk-free environment. Overall, the Game proved valuable in contributing to the development of an Australian community of practice for stock assessment and identifying how to strengthen assessment capabilities.

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Digital Object Identifier (DOI)

https://doi.org/10.1016/j.fishres.2025.107319