RESEARCH ARTICLE


Empirical Estimation of Accumulation-Induced Change in Gill Net Catchability: Mind the Observation Errors



Timo J. Marjomäki1, *, Marko Paloniemi2, Tapio Keskinen3, Jonna Kuha1, Juha Karjalainen1
1 University of Jyväskylä, Department of Biological and Environmental Science, P.O.Box 35, 40014 University of Jyväskylä, Finland;
2 Etelä-Pohjanmaan Kalatalouskeskus ry, Huhtalantie 2, 60220 Seinäjoki, Finland;
3 Natural Resources Institute Finland; Survontie 9 A, 40500 Jyväskylä, Finland


Article Metrics

CrossRef Citations:
2
Total Statistics:

Full-Text HTML Views: 492
Abstract HTML Views: 427
PDF Downloads: 0
Total Views/Downloads: 919
Unique Statistics:

Full-Text HTML Views: 285
Abstract HTML Views: 270
PDF Downloads: 0
Total Views/Downloads: 555



© 2015 Marjomäki et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the University of Jyväskylä, Department of Biological and Environmental Science, P.O.Box 35, 40014 University of Jyväskylä, Finland; Tel: +358 50 428 5274; E-mail: timo.j.marjomaki@jyu.fi


Abstract

We analyzed cumulative catches for 24 h gill net exposures divided into 4*6 h, 2*12 h and 1*24 h soak time treatments to estimate the reduction in its catchability due to accumulation of fish. The effects of loss of catch during net lifting, disturbance effect and fouling were eliminated as far as possible to reveal the true effect of accumulation. First we applied simple nonparametric and parametric tests in comparison of treatments. As expected, considerable reduction in catchability took place along with the increase in soak time, indicated by significantly lower total 24 h catches from longer soaks in comparison with shorter ones. The reduction was more pronounced for roach than for perch. Further, we compared a functional relationship regression (FRR), admitting correctly observation error variance also in the x-axis variable, with ordinary least squares regression (OLS) in modelling the relationship between cumulative 24 h catches for different treatments. We estimated the between-replicates proportional observation error variance within a treatment and found it to be similar in different treatments. Therefore the variance ratio could be assumed to be close to 1 enabling the use of major axis solution FRR. In this particular case the incorrect use of OLS obviously gives a seriously biased result, exacerbating the negative effect of accumulation for high x-axis values in comparison with FRR. We recommend the use of FRR for any analysis comparing different notoriously low precision fish abundance proxies.

Keywords: Accumulation, bias, catchability, error in variables, saturation.