A new algorithm for estimating gillnet selectivity

Yanli Tang; Liuyi Huang; Changzi Ge; Zhenlin Liang; Peng Sun

doi:10.1007/s00343-010-9256-2

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A new algorithm for estimating gillnet selectivity

Updated：2023-05-16

- A new algorithm for estimating gillnet selectivity
- Journal of Oceanology and Limnology Vol. 28, Issue 2, Pages: 274-279(2010)
- Affiliations：
  
  1. Fisheries College Ocean University of China
  2. Marine College Shandong University at Weihai
- Author bio：
- Funds：
- DOI：10.1007/s00343-010-9256-2
  CLC：
- Online First：20 March 2010，
  
  Published：2010
- Accepted：
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Tang, Y., Huang, L., Ge, C. et al. A new algorithm for estimating gillnet selectivity., Chin. J. Ocean. Limnol. 28, 274–279 (2010). https://doi.org/10.1007/s00343-010-9256-2
DOI：

Tang, Y., Huang, L., Ge, C. et al. A new algorithm for estimating gillnet selectivity., Chin. J. Ocean. Limnol. 28, 274–279 (2010). https://doi.org/10.1007/s00343-010-9256-2 DOI：

摘要

Abstract

The estimation of gear selectivity is a critical issue in fishery stock assessment and management. Several methods have been developed for estimating gillnet selectivity

but they all have their limitations

such as inappropriate objective function in data fitting

lack of unique estimates due to the difficulty in finding global minima in minimization

biased estimates due to outliers

and estimations of selectivity being influenced by the predetermined selectivity functions. In this study

we develop a new algorithm that can overcome the above-mentioned problems in estimating the gillnet selectivity. The proposed algorithms include minimizing the sum of squared vertical distances between two adjacent points and minimizing the weighted sum of squared vertical distances between two adjacent points in the presence of outliers. According to the estimated gillnet selectivity curve

the selectivity function can also be determined. This study suggests that the proposed algorithm is not sensitive to outliers in selectivity data and improves on the previous methods in estimating gillnet selectivity and relative population density of fish when a gillnet is used as a sampling tool. We suggest the proposed approach be used in estimating gillnet selectivity.

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references

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Related Institution

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College of Physical and Environmental Oceanography, Ocean University of China

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