Estimating spatio-temporal distribution of fish and gear selectivity functions from pooled scientific survey and commercial fishing data

Guillermo Martin Gonzalez* (Corresponding Author), Rodrigo Wiff, C. Tara Marshall, Thomas Cornulier

*Corresponding author for this work

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Model-based prediction of fish distribution at fine resolutions in space and time has the potential to inform area-based and dynamic forms of management, such as permanent marine protected areas or real-time temporary closures. A major limitation to the spatial and temporal mapping resolution that is achievable is the amount of high quality, standardised data that can be utilized for fitting statistical models. To achieve an adequate spatio-temporal resolution from sparse data, one option is pooling information from several sources, such as scientific surveys and fisheries data. Because surveys and fisheries data usually use different sampling methods, pooling information from different sources requires cross-calibration of catch rates values across multiple gears. However, the individual gear efficiency and selectivity curves (the ratio between catch and availability at a given length) for all fishing gears and species are typically unknown. Using cod (Gadus morhua) in the northern North Sea as a case study, we developed a new formulation of spatio-temporal generalised additive models (GAM) of relative abundance of fish, combining catch data from multiple sources. Differences in gear efficiency and selectivity were internally calibrated within the model by the estimation of the local spatio-temporal variation in abundance. We show that pooling data sources enables the prediction of multi-annual and seasonal spatial variation in cod relative abundance-at-size, at spatio-temporal resolutions that are relevant for informing fishing strategies, e.g., reducing bycatch in real-time, or management objectives, e.g., real-time closed areas. We also show that GAM models fit to catch and effort data can reveal the relative efficiency and selectivity of different survey and commercial gears. The selectivity curve estimates that emerged as a by-product of our analysis are consistent with expert knowledge of the performance of the gears employed for cod. Our analytical approach can therefore serve two useful purposes: to estimate spatio-temporal variation in relative abundance of fish and to estimate relative gear efficiency and selectivity.
Original languageEnglish
Article number106054
Number of pages11
JournalFisheries Research
Early online date30 Jun 2021
Publication statusPublished - 30 Nov 2021

Bibliographical note

This work was part-funded by FISA project Number 01/15 and Fisheries Innovation Scotland (FIS011B). G. Martin Gonzalez is grateful to the scholarship program ‘Becas de La Caixa’ for sponsoring his MSc, where part of this work was developed. R. Wiff was part-funded by CONICYT Project CAPES FB 0002 and by ANID – Programa Iniciativa Científica Milenio –CódigoICN2019_015. We thank Marine Scotland Science for providing the anonymized commercial fishing data. Coby Needle initiated interest in the problem. Barry O’Neill and Rui Catarino assisted with interpreting the selectivity findings. Max Lindmark conducted preliminary analyses of the data as part of his MSc thesis. We are sincerely grateful to two anonymous reviewers whose comments and suggestions greatly improved an early version of this manuscript.


  • Spatio-temporal
  • GAM
  • Cod
  • Selectivity
  • Surveys


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