2012Canadian Journal of Fisheries and Aquatic SciencesRequires access

Spawning biomass reference points for exploited marine fishes, incorporating taxonomic and body size information

James T. Thorson, Jason M. Cope, Trevor A. Branch, Olaf P. Jensen

Open publisher page 112 citations

Abstract

Surplus production represents the processes that affect sustainable fishery harvest and is central to the ecology and management of marine fishes. Taxonomy and life history influence the ratio of spawning biomass at maximum sustainable yield to average unfished spawning biomass (SBMSY/SB0), and estimating this ratio for individual stocks is notoriously difficult. We use a database of published landings data and stock assessment biomass estimates and determine that process errors predominate in this data set by fitting a state–space model to data from each stock individually. We then fit multispecies process-error models while treating SBMSY/SB0as a random effect that varies by taxonomic order and maximum length. The estimated SBMSY/SB0 = 0.40 for all 147 stocks is intermediate between the values assumed by the Fox and the Schaefer models, although Clupeiformes and Perciformes have lower and Gadiformes and Scorpaeniformes have higher SBMSY/SB0values. Model selection supports the hypothesis that large-bodied fishes for a given taxonomic order have relatively higher SBMSY/SB0. Results can be used to define reference points for data-poor fisheries or as input in emerging assessment methods.

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What this paper is about

Surplus production represents the processes that affect sustainable fishery harvest and is central to the ecology and management of marine fishes. Taxonomy and life history influence the ratio of spawning biomass at maximum sustainable yield to average unfished spawning biomass (SBMSY/SB0), and estimating this ratio for individual stocks is notoriously difficult. We use a database of published landings data and stock assessment biomass estimates and determine that process errors predominate in this data set by fitting a state–space model to data from each stock individually. We then fit multispecies process-error models while treating SBMSY/SB0as a random effect that varies by taxonomic order and maximum length. The estimated SBMSY/SB0 = 0.40 for all 147 stocks is intermediate between the values assumed by the Fox and the Schaefer models, although Clupeiformes and Perciformes have lower and Gadiformes and Scorpaeniformes have higher SBMSY/SB0values. Model selection supports the hypothesis that large-bodied fishes for a given taxonomic order have relatively higher SBMSY/SB0. Results can be used to define reference points for data-poor fisheries or as input in emerging assessment methods.

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Available abstract

Surplus production represents the processes that affect sustainable fishery harvest and is central to the ecology and management of marine fishes. Taxonomy and life history influence the ratio of spawning biomass at maximum sustainable yield to average unfished spawning biomass (SBMSY/SB0), and estimating this ratio for individual stocks is notoriously difficult. We use a database of published landings data and stock assessment biomass estimates and determine that process errors predominate in this data set by fitting a state–space model to data from each stock individually. We then fit multispecies process-error models while treating SBMSY/SB0as a random effect that varies by taxonomic order and maximum length. The estimated SBMSY/SB0 = 0.40 for all 147 stocks is intermediate between the values assumed by the Fox and the Schaefer models, although Clupeiformes and Perciformes have lower and Gadiformes and Scorpaeniformes have higher SBMSY/SB0values. Model selection supports the hypothesis that large-bodied fishes for a given taxonomic order have relatively higher SBMSY/SB0. Results can be used to define reference points for data-poor fisheries or as input in emerging assessment methods.

Key concepts: Maximum sustainable yield, Stock assessment, Stock (firearms), Fishery, Fisheries management, Biomass (ecology), Environmental science, Biology

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