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Extension of biomass estimates to pre-assessment periods using density dependent surplus production approach
Stockholm University, Faculty of Science, Stockholm University Baltic Sea Centre.
Number of Authors: 2
2017 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 12, no 11, e0186830Article in journal (Refereed) Published
Abstract [en]

Biomass reconstructions to pre-assessment periods for commercially important and exploitable fish species are important tools for understanding long-term processes and fluctuation on stock and ecosystem level. For some stocks only fisheries statistics and fishery dependent data are available, for periods before surveys were conducted. The methods for the backward extension of the analytical assessment of biomass for years for which only total catch volumes are available were developed and tested in this paper. Two of the approaches developed apply the concept of the surplus production rate (SPR), which is shown to be stock density dependent if stock dynamics is governed by classical stock-production models. The other approach used a modified form of the Schaefer production model that allows for backward biomass estimation. The performance of the methods was tested on the Arctic cod and North Sea herring stocks, for which analytical biomass estimates extend back to the late 1940s. Next, the methods were applied to extend biomass estimates of the North-east Atlantic mackerel from the 1970s (analytical biomass estimates available) to the 1950s, for which only total catch volumes were available. For comparison with other methods which employs a constant SPR estimated as an average of the observed values, was also applied. The analyses showed that the performance of the methods is stock and data specific; the methods that work well for one stock may fail for the others. The constant SPR method is not recommended in those cases when the SPR is relatively high and the catch volumes in the reconstructed period are low.

Place, publisher, year, edition, pages
2017. Vol. 12, no 11, e0186830
National Category
Other Natural Sciences
Identifiers
URN: urn:nbn:se:su:diva-149807DOI: 10.1371/journal.pone.0186830ISI: 000414997800005OAI: oai:DiVA.org:su-149807DiVA: diva2:1167368
Available from: 2017-12-18 Created: 2017-12-18 Last updated: 2017-12-18Bibliographically approved

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Tomczak, Maciej T.
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CiteExportLink to record
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