A nonlinear programming approach to the analysis of perturbed marine ecosystems under model parameter uncertainty

Abstract

A general class of applied marine ecosystem problems is modeled using nonlinear programming (NLP) techniques. These problems involve multiple interacting population groups, one or more of which has been perturbed from some approximately known state via man-induced or natural phenomena. Critical ecosystem response characteristics and optimum management strategies are to be determined. The NLP modeling approach is shown to have substantial advantages for treating complex ecosystems and, in particular, for dealing with the practical issue of parameter uncertainty in the dynamic modeling. The NLP modeling approach is demonstrated by analyzing the collapse of the sardine fishery off the Pacific Coast of North America during the 1930's and 1940's. A priori predictions are shown to bound the measured sardine ecosystem response and provide evidence of overfishing as the reason for the collapse.