The Limits of Single Species Assessment Models

The essence of simple population models is that they can obtain information from contrasts. This can be as simple as a time series of catch and relative abundance showing a coupled pattern with changing levels of catch pushing abundance down or allowing it to grow, or a steeper slope to the size composition in areas or eras with higher catch levels. Integrated analysis models have evolved to a high level of statistical capability to simultaneously extract information from both types of data while taking into account various confounding factors. All models are simplifications of nature based upon simple concepts of population regulation. Models can make inferences about species abundance and sustainable levels of fishing because of these simplifications, especially when data are limited. Single species models generally are structured to take into account random perturbations caused by the larger system in which the species occurs. The limitation of single species models is that they cannot make good predictions when the whole system is shifting on longer time scales, whether through fishery-induced or natural changes in abundance of biologically interacting species, or through long-term shifts in climate. Addressing these factors requires information about those external processes and their effect on fish.