Individual-based models as a tool for ecosystem-based approaches to fisheries management
Fish population dynamics are affected by multiple ecosystem drivers, such as food-web interactions, exploitation, density-dependence and the wider environment. While tactical management is still dominated by single-species models that do not explicitly account for these drivers, more holistic ecosystem models are used in strategic management. One way forward in this regard is with individual-based models (IBMs), which provide a single framework in which these drivers can be represented explicitly.
We have developed marine fish IBM that incorporates spatial and temporal variation in food availability, temperature and exploitation. Key features of the model include: (1) realistic energy budgets; (2) representation of the full fish life cycle; (3) a spatially-explicit environment and (4) the incorporation of satellite remote-sensing data to represent the environmental drivers. Individuals are characterised by several state variables, such as life stage, body mass, length and energy reserves. Individual’s state variables change in response to their local food availability, temperature and exploitation pressure, according to their energy budgets. Population measures are calculated as the sum of the individual’s characteristics. To demonstrate the use of the model, we have calibrated it for mackerel (Scomber scombrus) in the North East Atlantic, and used it to test the population consequences of simple hypothetical management scenarios.
Ongoing applications of the model include: investigation of what is driving an expansion of the mackerel summer distribution, and testing the population consequences of realistic management scenarios.