A management strategy evaluation (MSE) is a test of management strategies through simulation modeling that typically includes feedback between an estimation model and operating model (Smith, 1994). The operating model represents the underlying population dynamics and the estimation model is generally a stock assessment method that provides estimates of fisheries reference points such as current stock size and measures of productivity. The management strategy links the estimation and operating models, representing anthropogenic impacts on the stock via strategies that aim to control the amount, distribution, and timing of fishing pressure. The result of an MSE is a simulated population representing the “true” impacts of a given strategy on population status and productivity, and the estimated population represented by population dynamic parameters that are estimated within the stock assessment. I propose to use the MSE framework to test different states of nature, representing different underlying population dynamics, while utilizing the management strategy defined by the North Pacific Fisheries Management Council and the current stock assessment for the estimation model. The states of nature will be represented by the two IBM’s, a model with age-dependent reproductive biology and a model that does not explicitly account for age-dependent reproductive biology. The goal of this study is to utilize the IBM-MSE framework to test the extent to which management performance could be affected if estimates of stock productivity were biased because interactions between age-dependent reproductive biology and a variable environment were not considered.

Project Members:

Linsey Arnold, Department of Fisheries and Wildlife, Oregon State University



Fisheries and the Environment (FATE)