Assessing consistency of fish survey data

uncertainties in the estimation of mackerel icefish (Champsocephalus gunnari) abundance at South Georgia

Niall G. Fallon*, Martin A. Collins, C. Tara Marshall, Paul G. Fernandes

*Corresponding author for this work

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2 Citations (Scopus)
4 Downloads (Pure)

Abstract

Mackerel icefish (Champsocephalus gunnari) is a semi-pelagic finfish species inhabiting shelf areas in the Southern Ocean. The population at South Georgia is currently exploited by pelagic trawlers fishing close to the seabed. Annual catches peaked at 150,000 t in 1983 and have declined since the mid-to-late 1980s. Bottom-trawl surveys have been conducted since 1987, providing a time series of abundance and size distribution for use in assessing the status of the stock and setting quotas. Food web models suggest that estimates of the biomass from survey data are substantially lower than the amount of icefish required by the local ecosystem. The aim of this study was to assess the uncertainty around current estimates of density and variance, using alternative nonparametric stratified bootstrapping methods. The stratified rescaling bootstrap estimator was identified as the most appropriate method of those tested: in comparison with the existing method, confidence intervals and the inter-annual variability of the estimates were reduced. Numbers-at-age were estimated from mixture distribution models fitted to length-disaggregated density data in order to determine whether individual cohorts were consistently detected by the surveys. Estimates of numbers-at-age could not consistently delineate cohorts in successive years indicating that survey-based estimates of density were biased. These biases may have arisen because the trawl gear did not select individuals of all sizes equally, or because sampling was restricted to the demersal component of the stock. Estimates of abundance of the pelagic component of the stock should be derived from acoustic data to improve the assessment.

Original languageEnglish
Pages (from-to)593-603
Number of pages11
JournalPolar Biology
Volume39
Issue number4
Early online date20 Oct 2015
DOIs
Publication statusPublished - Apr 2016

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Perciformes
Uncertainty
Fishes
uncertainty
fish
Food Chain
fishing boats
Acoustics
Oceans and Seas
Biomass
food webs
Ecosystem
confidence interval
acoustics
time series analysis
oceans
methodology
Confidence Intervals
Surveys and Questionnaires
Champsocephalus gunnari

Keywords

  • Mackerel icefish
  • Stratified bootstrap
  • Trawl survey

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)

Cite this

Assessing consistency of fish survey data : uncertainties in the estimation of mackerel icefish (Champsocephalus gunnari) abundance at South Georgia. / Fallon, Niall G.; Collins, Martin A.; Marshall, C. Tara; Fernandes, Paul G.

In: Polar Biology, Vol. 39, No. 4, 04.2016, p. 593-603.

Research output: Contribution to journalArticle

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title = "Assessing consistency of fish survey data: uncertainties in the estimation of mackerel icefish (Champsocephalus gunnari) abundance at South Georgia",
abstract = "Mackerel icefish (Champsocephalus gunnari) is a semi-pelagic finfish species inhabiting shelf areas in the Southern Ocean. The population at South Georgia is currently exploited by pelagic trawlers fishing close to the seabed. Annual catches peaked at 150,000 t in 1983 and have declined since the mid-to-late 1980s. Bottom-trawl surveys have been conducted since 1987, providing a time series of abundance and size distribution for use in assessing the status of the stock and setting quotas. Food web models suggest that estimates of the biomass from survey data are substantially lower than the amount of icefish required by the local ecosystem. The aim of this study was to assess the uncertainty around current estimates of density and variance, using alternative nonparametric stratified bootstrapping methods. The stratified rescaling bootstrap estimator was identified as the most appropriate method of those tested: in comparison with the existing method, confidence intervals and the inter-annual variability of the estimates were reduced. Numbers-at-age were estimated from mixture distribution models fitted to length-disaggregated density data in order to determine whether individual cohorts were consistently detected by the surveys. Estimates of numbers-at-age could not consistently delineate cohorts in successive years indicating that survey-based estimates of density were biased. These biases may have arisen because the trawl gear did not select individuals of all sizes equally, or because sampling was restricted to the demersal component of the stock. Estimates of abundance of the pelagic component of the stock should be derived from acoustic data to improve the assessment.",
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note = "Acknowledgments The authors wish to thank the crews, fishermen and scientists who conducted the various surveys from which data were obtained, and Mark Belchier and Simeon Hill for their contributions. This work was supported by the Government of South Georgia and South Sandwich Islands. Additional logistical support provided by The South Atlantic Environmental Research Institute with thanks to Paul Brickle. Thanks to Stephen Smith of Fisheries and Oceans Canada (DFO) for help in constructing bootstrap confidence limits. Paul Fernandes receives funding from the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland), and their support is gratefully acknowledged. MASTS is funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions. We also wish to thank two anonymous referees for their helpful suggestions on earlier versions of this manuscript.",
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N1 - Acknowledgments The authors wish to thank the crews, fishermen and scientists who conducted the various surveys from which data were obtained, and Mark Belchier and Simeon Hill for their contributions. This work was supported by the Government of South Georgia and South Sandwich Islands. Additional logistical support provided by The South Atlantic Environmental Research Institute with thanks to Paul Brickle. Thanks to Stephen Smith of Fisheries and Oceans Canada (DFO) for help in constructing bootstrap confidence limits. Paul Fernandes receives funding from the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland), and their support is gratefully acknowledged. MASTS is funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions. We also wish to thank two anonymous referees for their helpful suggestions on earlier versions of this manuscript.

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