Investigating the effect of recruitment variability on length-based recruitment indices for antarctic krill using an individual-based population dynamics model.

Stéphane Thanassekos,Martin J Cox,Keith Reid,Geir Ottersen

doi:10.1371/journal.pone.0114378

Stéphane Thanassekos, Martin J Cox + Show 2 more

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https://doi.org/10.1371/journal.pone.0114378

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Journal: PloS one	Publication Date: Dec 3, 2014
Citations: 2	License type: CC BY 4.0

Affiliation: Australian Antarctic Division

Abstract

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%).

Highlights

Krill is an important link between lower trophic levels and highorder predators such as penguins and whales, in the Antarctic marine ecosystem [1]
The specific goals of this work were to: (i) investigate the relationships between length-based indices and recruitment, (ii) select an optimum recruitment index from a suite of recruitment indices under various levels of recruitment variability; (iii) use a regression analysis to determine the relationship between the recruitment index and absolute recruitment; (iv) determine the performance of the selected recruitment index, and (v) reduce uncertainty in the recruitment index-absolute recruitment relationship by including consecutive index values from preceding years
The size of 40 mm was chosen as an appropriate cut-off to segregate recruits from older cohorts, once recruits became dominant in length frequency distributions ( Fig. 1, after April)

Summary

Introduction

Krill is an important link between lower trophic levels (phytoplankton) and highorder predators such as penguins and whales, in the Antarctic marine ecosystem [1]. Krill has been the focus of both long-term scientific research and commercial fishery Multiple sources of data from scientific surveys and the fishery have generated databases that provide information on key lifehistory characteristics of krill such as growth, mortality and recruitment. Scientific research on krill has focussed on the summer period when logistics and operational factors are more amenable; the commercial fishery for krill operates year-round [5]. The Commission for the Conservation of Antarctic Marine Living Resources Scheme of International Scientific Observation (CCAMLR SISO; www.ccamlr.org), was initiated in 1992 to collect data from the krill fishery, including representative length-frequency data, from commercial captures on board fishing vessels. The database of krill lengths represents an opportunity to investigate krill population dynamics, at scales not typically feasible using data from scientific surveys

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