Investigating the effect of recruitment variability on length-based recruitment indices for Antarctic krill using an individual-based population dynamics model
Antarctic krill ( Euphausia superba herein krill) is monitored as part of an on-going fisheries observer program that collects length-frequency data. A krill feedback management programme is currently being developed, and as part of this development, the utility of data-derived indices describing po...
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ftunivtasecite:oai:ecite.utas.edu.au:119161 2023-05-15T13:49:03+02:00 Investigating the effect of recruitment variability on length-based recruitment indices for Antarctic krill using an individual-based population dynamics model Thanassekos, S Cox, MJ Reid, K 2014 application/pdf https://doi.org/10.1371/journal.pone.0114378 http://www.ncbi.nlm.nih.gov/pubmed/25470296 http://ecite.utas.edu.au/119161 en eng Public Library of Science http://ecite.utas.edu.au/119161/1/Thanassekos et al 2014.PDF http://dx.doi.org/10.1371/journal.pone.0114378 Thanassekos, S and Cox, MJ and Reid, K, Investigating the effect of recruitment variability on length-based recruitment indices for Antarctic krill using an individual-based population dynamics model, PLoS One, 9, (12) Article e114378. ISSN 1932-6203 (2014) [Refereed Article] http://www.ncbi.nlm.nih.gov/pubmed/25470296 http://ecite.utas.edu.au/119161 Biological Sciences Ecology Population Ecology Refereed Article PeerReviewed 2014 ftunivtasecite https://doi.org/10.1371/journal.pone.0114378 2019-12-13T22:18:22Z Antarctic krill ( Euphausia superba herein krill) is monitored as part of an on-going fisheries observer program that collects length-frequency data. A krill feedback management programme is currently being developed, and as part of this development, the utility of data-derived indices describing population level processes is being assessed. To date, however, little work has been carried out on the selection of optimum recruitment indices and it has not been possible to assess the performance of length-based recruitment indices across a range of recruitment variability. Neither has there been an assessment of uncertainty in the relationship between an index and the actual level of recruitment. Thus, until now, it has not been possible to take into account recruitment index uncertainty in krill stock management or when investigating relationships between recruitment and environmental drivers. Using length-frequency samples from a simulated population where recruitment is known the performance of six potential length-based recruitment indices is assessed, by exploring the index-to-recruitment relationship under increasing levels of recruitment variability (from 10% to 100% around a mean annual recruitment). The annual minimum of the proportion of individuals smaller than 40 mm (F40 min, %) was selected because it had the most robust index-to-recruitment relationship across differing levels of recruitment variability. The relationship was curvilinear and best described by a power law. Model uncertainty was described using the 95% prediction intervals, which were used to calculate coverage probabilities and assess model performance. Despite being the optimum recruitment index, the performance of F40 min degraded under high (>50%) recruitment variability. Due to the persistence of cohorts in the population over several years, the inclusion of F40 min values from preceding years in the relationship used to estimate recruitment in a given year improved its accuracy (mean bias reduction of 8.3% when including three F40 min values under a recruitment variability of 60%). Article in Journal/Newspaper Antarc* Antarctic Antarctic Krill Euphausia superba eCite UTAS (University of Tasmania) Antarctic PLoS ONE 9 12 e114378 |
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eCite UTAS (University of Tasmania) |
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ftunivtasecite |
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English |
topic |
Biological Sciences Ecology Population Ecology |
spellingShingle |
Biological Sciences Ecology Population Ecology Thanassekos, S Cox, MJ Reid, K Investigating the effect of recruitment variability on length-based recruitment indices for Antarctic krill using an individual-based population dynamics model |
topic_facet |
Biological Sciences Ecology Population Ecology |
description |
Antarctic krill ( Euphausia superba herein krill) is monitored as part of an on-going fisheries observer program that collects length-frequency data. A krill feedback management programme is currently being developed, and as part of this development, the utility of data-derived indices describing population level processes is being assessed. To date, however, little work has been carried out on the selection of optimum recruitment indices and it has not been possible to assess the performance of length-based recruitment indices across a range of recruitment variability. Neither has there been an assessment of uncertainty in the relationship between an index and the actual level of recruitment. Thus, until now, it has not been possible to take into account recruitment index uncertainty in krill stock management or when investigating relationships between recruitment and environmental drivers. Using length-frequency samples from a simulated population where recruitment is known the performance of six potential length-based recruitment indices is assessed, by exploring the index-to-recruitment relationship under increasing levels of recruitment variability (from 10% to 100% around a mean annual recruitment). The annual minimum of the proportion of individuals smaller than 40 mm (F40 min, %) was selected because it had the most robust index-to-recruitment relationship across differing levels of recruitment variability. The relationship was curvilinear and best described by a power law. Model uncertainty was described using the 95% prediction intervals, which were used to calculate coverage probabilities and assess model performance. Despite being the optimum recruitment index, the performance of F40 min degraded under high (>50%) recruitment variability. Due to the persistence of cohorts in the population over several years, the inclusion of F40 min values from preceding years in the relationship used to estimate recruitment in a given year improved its accuracy (mean bias reduction of 8.3% when including three F40 min values under a recruitment variability of 60%). |
format |
Article in Journal/Newspaper |
author |
Thanassekos, S Cox, MJ Reid, K |
author_facet |
Thanassekos, S Cox, MJ Reid, K |
author_sort |
Thanassekos, S |
title |
Investigating the effect of recruitment variability on length-based recruitment indices for Antarctic krill using an individual-based population dynamics model |
title_short |
Investigating the effect of recruitment variability on length-based recruitment indices for Antarctic krill using an individual-based population dynamics model |
title_full |
Investigating the effect of recruitment variability on length-based recruitment indices for Antarctic krill using an individual-based population dynamics model |
title_fullStr |
Investigating the effect of recruitment variability on length-based recruitment indices for Antarctic krill using an individual-based population dynamics model |
title_full_unstemmed |
Investigating the effect of recruitment variability on length-based recruitment indices for Antarctic krill using an individual-based population dynamics model |
title_sort |
investigating the effect of recruitment variability on length-based recruitment indices for antarctic krill using an individual-based population dynamics model |
publisher |
Public Library of Science |
publishDate |
2014 |
url |
https://doi.org/10.1371/journal.pone.0114378 http://www.ncbi.nlm.nih.gov/pubmed/25470296 http://ecite.utas.edu.au/119161 |
geographic |
Antarctic |
geographic_facet |
Antarctic |
genre |
Antarc* Antarctic Antarctic Krill Euphausia superba |
genre_facet |
Antarc* Antarctic Antarctic Krill Euphausia superba |
op_relation |
http://ecite.utas.edu.au/119161/1/Thanassekos et al 2014.PDF http://dx.doi.org/10.1371/journal.pone.0114378 Thanassekos, S and Cox, MJ and Reid, K, Investigating the effect of recruitment variability on length-based recruitment indices for Antarctic krill using an individual-based population dynamics model, PLoS One, 9, (12) Article e114378. ISSN 1932-6203 (2014) [Refereed Article] http://www.ncbi.nlm.nih.gov/pubmed/25470296 http://ecite.utas.edu.au/119161 |
op_doi |
https://doi.org/10.1371/journal.pone.0114378 |
container_title |
PLoS ONE |
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9 |
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12 |
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e114378 |
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