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Improving the precision of recreational fishing harvest estimates using two-part conditional general linear models

Taylor, S. M., Webley, J. A. C. and Mayer, D. G. (2011) Improving the precision of recreational fishing harvest estimates using two-part conditional general linear models. Fisheries Research, 110 (3). pp. 408-414.

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Article Link(s): http://doi.org/10.1016/j.fishres.2011.05.001

Publisher URL: http://www.scopus.com/inward/record.url?eid=2-s2.0-79960636354&partnerID=40&md5=3ca8532355717571194c84f2ac7601b7

Abstract

As recreational fishing continues to expand, the need to obtain precise harvest estimates is becoming increasingly important for the sustainable management of fisheries. Recreational fishing data are frequently zero-inflated which can present problems for commonly used analyses that assume a normal distribution. In this study, we analysed zero-inflated recreational fishing data collected from a bus-route access point survey in southeastern Queensland, Australia. Using the Time Interval Count method, we compared estimates of the proportion of boats fishing, fishing effort, harvest per unit effort (HPUE) and harvest using sample mean values and mean values derived from a two-part conditional general linear model (CGLM). The CGLM gave more precise estimates of the proportion of boats fishing, fishing effort and HPUE, which formed the basis of the harvest calculations. Differences in harvest estimates using the two methods ranged from 3 to 28% for the five recreational species examined. Relative standard errors for harvest estimated by the CGLM were 65-84% smaller. The results suggest that CGLMs may deliver more precise outputs in other types of recreational fishing surveys that derive effort and catch from zero-inflated data. © 2011 Elsevier B.V.

Item Type:Article
Keywords:Bus route Gamma distribution Precision Recreational catch Right-skewed Survey
Subjects:Aquaculture and Fisheries > Fisheries > Fishery research
Aquaculture and Fisheries > Recreational Fishing (Angling etc)
Deposited On:05 Apr 2019 01:10
Last Modified:05 Apr 2019 01:10

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