‘Drivin' with your eyes closed’: Results from an international, blinded simulation experiment to evaluate spatial stock assessments

Author:

Goethel Daniel R.1ORCID,Berger Aaron M.2ORCID,Hoyle Simon D.3ORCID,Lynch Patrick D.4ORCID,Barceló Caren5ORCID,Deroba Jonathan6ORCID,Ducharme‐Barth Nicholas D.7ORCID,Dunn Alistair8,Fu Dan9,Izquierdo Francisco10ORCID,Marsh Craig11,Xu Haikun12,Correa Giancarlo M.13ORCID,Langseth Brian J.14ORCID,Maunder Mark N.12,McKenzie Jeremy11,Methot Richard D.15,Vincent Matthew T.16ORCID,A'mar Teresa17ORCID,Cardinale Massimiliano18ORCID,Cousido‐Rocha Marta10ORCID,Davies Nick19,Hampton John20ORCID,Minte‐Vera Carolina12ORCID,Urtizberea Agurtzane21ORCID

Affiliation:

1. NOAA, Alaska Fisheries Science Center Juneau Alaska USA

2. NOAA, Northwest Fisheries Science Center Newport Oregon USA

3. National Institute of Water and Atmospheric Research Ltd (NIWA) Nelson New Zealand

4. NOAA, Office of Science and Technology Silver Spring Maryland USA

5. Puget Sound Institute University of Washington‐Tacoma Tacoma Washington USA

6. NOAA, Northeast Fisheries Science Center Woods Hole Massachusetts USA

7. NOAA, Pacific Islands Fisheries Science Center Honolulu Hawaii USA

8. Ocean Environmental Ltd. Wellington New Zealand

9. Indian Ocean Tropical Tuna Commission Victoria Seychelles

10. Instituto Español de Oceanografía (IEO, CSIC), Centro Oceanográfico de Vigo Vigo Pontevedra Spain

11. National Institute of Water and Atmospheric Research Ltd (NIWA) Auckland New Zealand

12. Inter‐American Tropical Tuna Commission La Jolla California USA

13. School of Aquatic and Fishery Sciences University of Washington Seattle Washington USA

14. NOAA, Northwest Fisheries Science Center Seattle Washington USA

15. NOAA, Office of the Science Director Northwest Fisheries Science Center Seattle Washington USA

16. NOAA, Southeast Fisheries Science Center Beaufort North Carolina USA

17. National Institute of Water and Atmospheric Research Ltd (NIWA) Wellington New Zealand

18. Department of Aquatic Resources, Institute of Marine Research Swedish University of Agricultural Sciences Lysekil Sweden

19. Te Takina Ltd. Whangarei New Zealand

20. Pacific Community Noumea Cedex New Caledonia

21. AZTI, Marine Research, Basque Research and Technology Alliance (BRTA) Pasaia Gipuzkoa Spain

Abstract

AbstractSpatial models enable understanding potential redistribution of marine resources associated with ecosystem drivers and climate change. Stock assessment platforms can incorporate spatial processes, but have not been widely implemented or simulation tested. To address this research gap, an international simulation experiment was organized. The study design was blinded to replicate uncertainty similar to a real‐world stock assessment process, and a data‐conditioned, high‐resolution operating model (OM) was used to emulate the spatial dynamics and data for Indian Ocean yellowfin tuna (Thunnus albacares). Six analyst groups developed both single‐region and spatial stock assessment models using an assessment platform of their choice, and then applied each model to the simulated data. Results indicated that across all spatial structures and platforms, assessments were able to adequately recreate the population trends from the OM. Additionally, spatial models were able to estimate regional population trends that generally reflected the true dynamics from the OM, particularly for the regions with higher biomass and fishing pressure. However, a consistent population biomass scaling pattern emerged, where spatial models estimated higher population scale than single‐region models within a given assessment platform. Balancing parsimony and complexity trade‐offs were difficult, but adequate complexity in spatial parametrizations (e.g., allowing time‐ and age‐variation in movement and appropriate tag mixing periods) was critical to model performance. We recommend expanded use of high‐resolution OMs and blinded studies, given their ability to portray realistic performance of assessment models. Moreover, increased support for international simulation experiments is warranted to facilitate dissemination of methodology across organizations.

Publisher

Wiley

Reference45 articles.

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2. Incoherent dimensionality in fisheries management: consequences of misaligned stock assessment and population boundaries

3. Berger A. M. Goethel D. R. Hoyle S. D. Lynch P. D. Barcelo C. Day J. Langseth B. J. Minte‐Vera C. Xu H. Izquierdo F. Fu D. Ducharme‐Barth N. Vincent M. Gruss A. Olmos M. Deroba J. Correa G. McKenzie J. Marsh C. …Mace P.(2024).'Building the (im)perfect beast': Lessons‐learned for developing spatial stock assessment models from an international blinded simulation experiment. Manuscript in preparation.

4. Finding the perfect mismatch: Evaluating misspecification of population structure within spatially explicit integrated population models

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