Measurement error in angler creel surveys.


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Information on fishing effort, catch, harvest, and survival is important for formulating management policies in freshwater fisheries and for understanding the dynamics of aquatic ecosystems. Fisheries managers often use creel surveys to assess fisheries statistics. The mean-of-ratios estimator has been traditionally used for estimating catch rates from incomplete angler trips, whereas the ratio-of-means estimator is preferable for estimating catch rates from completed trips. Recent studies have demonstrated persistent bias when comparing the two estimators based on catch data from incomplete and completed trips from the same sample of anglers; these studies have promoted the use of linear regression models to correct for apparent bias in catch rates based on incomplete trips. However, the reported bias in catch rate estimates may be an artifact of measurement error in incomplete-trip angler surveys rather than bias from the estimates themselves. Furthermore, we contend that ordinary least-squares linear regression is inappropriate to correct for this apparent bias because measurement error is present in both the response variable (e.g., catch rate estimated from completed trips) and the explanatory variable (e.g., catch rate estimated from incomplete trips), leading to low estimates of the slope of the relationship. Alternatively, when both variables contain measurement error, model II regression methods provide less-biased estimates. Using interview data (incomplete trips) from roving creel surveys and a catch card survey (completed trips) conducted on the same sample of anglers, we compared catch rates derived from both estimators. Our results show that linear regression underestimates the slope of the relationship and that model II regression reduces bias and provides a more accurate estimate.
measurement,fisheries,regression analysis,angling,fishery management
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