Impacts of data quantity on fisheries stock assessment

Understanding population dynamics of fish stocks is essential in developing optimal fisheries management strategies. This is often obtained through fitting mathematical models to information/data collected from the fisheries to estimate vital fisheries parameters and their uncertainties. The quantity of fisheries information, often positively related to economic and social values of fisheries, is one of the most important factors influencing the quality of fisheries parameter estimation. We classify the data quantity into two categories: diversity of the information, defined as the number of sources from which the information about a fisheries variable is collected, and number of observations made for a given fisheries variable. Using an abalone fishery as an example, we demonstrate the importance of data quantity in stock assessment and management. Deficiency in data quantity tends to yield biased assessment of the status of fisheries stock and increase the uncertainty in stock assessment, subsequently complicating the identification of an optimal management strategy. This study suggests that there is a need to determine the relative importance of different types of fisheries data for stock assessment in allocating sampling effort to ensure that the most critical information is collected.