Premium
A Comparison of Two Methodologies for Estimating Brook Trout Catch and Harvest Rates using Incomplete and Complete Fishing Trips
Author(s) -
Keefe Donald G.,
Perry Robert C.,
Luther J. Glenn
Publication year - 2009
Publication title -
north american journal of fisheries management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 72
eISSN - 1548-8675
pISSN - 0275-5947
DOI - 10.1577/m08-024.1
Subject(s) - estimator , fishing , statistics , salvelinus , trips architecture , fontinalis , estimation , fishery , mathematics , econometrics , trout , fish <actinopterygii> , geography , computer science , biology , economics , management , parallel computing
On the island portion of Newfoundland and Labrador, Canada, the provincial government relies on roving creel surveys to assess the fishery for brook trout Salvelinus fontinalis. The estimation of catch and harvest rates for these surveys requires on‐site interview methods that gather information from incomplete fishing trips. When the objective is to determine total catch, the mean‐of‐ratios estimator is the accepted method for deriving catch rate from incomplete trips, whereas the ratio‐of‐means estimator is the accepted method for deriving catch rate for completed trips. When we compared the two estimators using incomplete and complete trip catch data measured from the same sample of anglers, we found a persistent bias. Catch and harvest rates derived from the mean‐of‐ratios estimator were significantly higher than those obtained with the ratio‐of‐means estimator. Catch rate was higher by 32%, while harvest rate was higher by 39%. When we only used the completed trip data set for both calculations, we found a mean difference of 19% between the two estimators. We also found a second source of error. When we examined individual angler responses for catch and harvest, the estimates revealed a positive bias whereby the incomplete trips showed higher estimates relative to the complete trips (16% and 21%, respectively). These biases appear to be related to the estimation procedure as well as fish and fisher behavior at the individual angler level. We use linear regression analysis to help correct the bias associated with the mean‐of‐ratios estimator.