ESTIMATING THE MEAN AND VARIANCE FROM HIGHLY SKEWED MARINE DATA

The spatial distribution of marine organisms is highly patchy. Because of this patchy distribution, data from marine abundance surveys are h ighly skewed and have a large variance. Compounding the problem of est imating the mean abundance from such data, is that occasionally a rela tively huge catch will occur. These large catches are not ''outliers'' but do dominate the estimates of the mean and variance. A lognormal m odel of the nonzero survey values (a Delta-distribution) is used to mo del survey data. The estimators, based on the lognormal model, appear to be much more efficient for marine data than the usual sample estima tors. In particular, the lognormal-based estimators provide reasonable estimates for data sets that contain a very large catch. The properti es and efficiency of the Delta-distribution estimators are examined an d the techniques are applied to various marine data sets.