Original Article Managing a complex population structure: exploring the importance of information from fisheries-independent sources

Natural resourcemanagers aim tomanage fish stocks at sustainable levels. Often, management of these stocks is based on the results of analytical stock assessments. Accurate catch data, which can be attributed to a specific population unit and reflects the population structure, are needed for these approaches. Often though, the quality of the catch data is compromised when dealing with a complex population structure where fish of different population units mix in a fishery. The herring population units west of the British Isles are prone tomixing. Here, the inability to perfectly allocate the fish caught to the population unit they originate from, due to classification problems, poses problems for management. These mixing proportions are often unknown; therefore, we use simulationmodelling combined withmanagement strategy evaluation to evaluate the role fish-eries-independent surveys can play in an assessment to provide unbiased results, irrespective of population unit mixing and classification success. We show that failure to account for mixing is one of the major drivers of biased estimates of population abundance, affecting biomass referenc