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The optimal process of self‐sampling in fisheries: lessons learned in the Netherlands a
Author(s) -
Kraan M.,
Uhlmann S.,
Steenbergen J.,
Van Helmond A. T. M.,
Van Hoof L.
Publication year - 2013
Publication title -
journal of fish biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.672
H-Index - 115
eISSN - 1095-8649
pISSN - 0022-1112
DOI - 10.1111/jfb.12192
Subject(s) - sampling (signal processing) , trips architecture , sample (material) , process (computing) , perspective (graphical) , fishery , biology , sample size determination , environmental resource management , statistics , computer science , economics , mathematics , chemistry , filter (signal processing) , chromatography , artificial intelligence , parallel computing , computer vision , operating system
At‐sea sampling of commercial fishery catches by observers is a relatively expensive exercise. The fact that an observer has to stay on‐board for the duration of the trip results in clustered samples and effectively small sample sizes, whereas the aim is to make inferences regarding several trips from an entire fleet. From this perspective, sampling by fishermen themselves (self‐sampling) is an attractive alternative, because a larger number of trips can be sampled at lower cost. Self‐sampling should not be used too casually, however, as there are often issues of data‐acceptance related to it. This article shows that these issues are not easily dealt with in a statistical manner. Improvements might be made if self‐sampling is understood as a form of cooperative research. Cooperative research has a number of dilemmas and benefits associated with it. This article suggests that if the guidelines for cooperative research are taken into account, the benefits are more likely to materialize. Secondly, acknowledging the dilemmas, and consciously dealing with them might lay the basis to trust‐building, which is an essential element in the acceptance of data derived from self‐sampling programmes.