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Recruitment variability in exploited aquatic populations

Published online by Cambridge University Press:  25 November 2006

Hiro-Sato Niwa
Hiro-Sato Niwa*
Affiliation:
Behavioral Ecology Section, National Research Institute of Fisheries Engineering, 7620-7 Hasaki, Kamisu, Ibaraki 314-0408, Japan
*
[email protected]
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Abstract

While lognormal distributions have been proposed as useful descriptors of recruitment variability, the very nature of the recruitment distributions is still debated.To account quantitatively for recruitment distributions,I here propose a Weibull exponential model;it derives from a simple and natural hypothesis for uncorrelated recruitment processes of spawning, hatching, growth and survival through the early life stages to the point of vulnerability to the fishery.The quantification of Weibull exponentials is particularly important with regards to extrapolations to low recruits that have not yet been observed.To test the Weibull exponential null-hypothesis, I examine annual time-series of recruitment in major aquatic stocks.The Weibull exponential quite describes the bulk (95%) of the recruitment distributions of widely differing stocks,while the remaining 5% of the largest recruits are occurring with a much larger rate than predicted by the Weibull exponential.Further, I study the inter-event times between unusually high numbers in recruitment time-series data and find that intermittent pulses of strong recruitment follow non-Poisson statistics, which arises from year-to-year persistence of the magnitude of recruitment:large (or small) recruits are more likely to be followed by large (or small) recruits.This recruitment clustering effect is confirmed by the rescaled range analysis method.The empirical results imply that individual survivals on recruitment levels are independent of initial cohort sizes but year-to-year recruiting events exhibit long-term correlations.

Keywords

Weibull exponential distributionLognormalStochastic survivorshipEarly life historyNon-Poisson intermittencyRecruitment clustering
Type
Research Article
Information
Aquatic Living Resources , Volume 19 , Issue 3 , July 2006 , pp. 195 - 206
Copyright
© EDP Sciences, IFREMER, IRD, 2006

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