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A selection of nonparametric statistical methods for assessing trends in trawl survey indicators as part of an ecosystem approach to fisheries management (EAFM)

Published online by Cambridge University Press:  17 June 2009

John Cotter
John Cotter*
Affiliation:
Centre for Environment, Fisheries and Aquaculture Science Lowestoft, NR33 0HT, UK
*
[email protected]
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Abstract

A selection of ten uni- and multivariate, nonparametric statistical methods thought to be useful for assessing trends in indicators estimated from trawl surveys is described. Nonparametric methods make minimal assumptions about the data and can therefore be suitable when parametric modelling methods, as typically preferred by fisheries scientists, are not suitable. The various methods described are sensitive to a variety of specific features of a trend thereby allowing many different forms of variation over time to be identified, e.g. changes in level, sloping straight or curved lines, and differing cyclicities. In contrast, model-based investigations can be constrained in this regard if the single model which is adopted and fitted to the trend is a simplification of its form.

Keywords

QuantilesRuns testMann-Kendall statisticSpearman correlationJonckeere testNonparametric slope estimatorCochran QAligned rank testDietz-Killeen multivariate trend test
Type
Research Article
Information
Aquatic Living Resources , Volume 22 , Issue 2: Fish Stock Assessments Using Surveys and Indicators , April 2009 , pp. 173 - 185
Copyright
© EDP Sciences, IFREMER, IRD, 2009

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