A Review of Methods for Prediction of Potential Fish Production with Application to the Great Lakes and Lake Winnipeg

Abstract

Methods for estimating fish production in aquatic ecosystems range from simple empirically derived estimators, such as morphoedaphic indices, to complex ecosystem simulation models. As first-order estimators, the former are attractive to managers because they are simple and relatively inexpensive to apply and interpret. Application of the latter group has been limited because many of the data inputs are difficult and expensive to obtain. Between these extremes are several models, such as the biomass–size spectrum model, that provide useful information for moderate expenditures of time and effort. Existing and new methods are reviewed in the light of production theory and several are applied to Great Lakes and Lake Winnipeg data. Eight empirical models derived from limnological variables were selected from the literature and used to estimate potential fish yield for the Great Lakes and Lake Winnipeg. The models predicted a fairly narrow range of potential yields, but when compared with historic yields, none was consistent for all lakes. The best overall empirically derived estimator of potential yield in the Great Lakes was the morphoedaphic index. Potential fish production estimated from invertebrate production with Borgmann's biomass – size spectrum model was considerably greater than historic yields or the yield estimates from the empirical models. In a third approach, we calculated life history parameters for "small" and "large" fish in the Great Lakes and combined these with Borgmann's production model, empirical information on population production/biomass ratios from the literature, and classical population dynamics theory to estimate potential production and optimum sustained yield for each group. Historic sustained yield, as a percentage of optimum sustained yield, varied from a low of 6 for "small" Lake Ontario fish to 100 for "large" Lake Erie fish.