Accuracy in Detection and Measurement of Overcompensation in Marine Fish Stocks: A Simulation Framework

Fish productivity is often used as an index in stock assessment to set robust management strategies. Fishery scientists are attempting to better understand the underlying mechanisms shaping productivity. One mechanisms is a density dependence process defined as overcompensation. Overcompensation occurs at high abundance at the population or metapopulation scale. Although identified in many species there is little, if any, statistical evidence of overcompensation being detected in marine populations. This study uses simulations to test a method of detecting and measuring overcompensation. Data are simulated with process error and overcompensation varying from low to high levels using parametric relationships (e.g. Shepherd relationship). Then, we fit a model to the data and assess the accuracy in detection and measurement of overcompensation. The study reveals several scenarios under which overcompensation can be detected fairly accurately. The efficiency of detection depends on life history traits, levels of uncertainty in the data and levels of overcompensation. This project will hopefully lead to better understanding of an important ecological process and may lead to a reliable method to detect overcompensation with accuracy. The next step of this study would be to determine the intensity and frequency of overcompensation in marine fish stocks using a meta-analysis.