A Simple Empirical Model Of Data Fouling In Marine Fisheries
Free (open access)
C. M. Wernerheim & R. L. Haedrich
One of the most serious problems facing fisheries managers is how to improve estimates of the distortion (‘fouling’) of commercial landings data resulting from misreporting. Data fouling (legal or illegal) drives a wedge between what is caught and killed at sea, and what is landed and reported to the regulator. This can obscure the true state of the stock causing it to appear healthier than it is, resulting in quotas being set too high. We propose an analytical model of data fouling that can be used with empirical data to estimate what we call the data fouling factor. The model is solved analytically and numerically for the profit maximizing effort level and the associated number of high-grading operations. Some illustrative policy implications are derived. Keywords: misreporting, high-grading, fisheries data, fisheries policy. 1 Introduction The estimation of stock abundance and the determination of quotas alike depend in large measure on accurate and precise statistics on commercial landings. One of the most serious problems facing fisheries managers is how to improve estimates of the distortion resulting from misreporting. Failure to obtain an accurate account from harvesters about activities at sea undermines the reliability of catch data, which can in turn introduce an (avoidable) element of uncertainty into the outcomes of fisheries policy: the greater the inaccuracy in the data the wider the confidence intervals around the estimate of stock size. Our main contention is that unless official landings data are adjusted for the discrepancy
misreporting, high-grading, fisheries data, fisheries policy.