The Potential to Improve the Sustainability of Pelagic Fisheries in the Northeast Atlantic by Incorporating Individual Fish Behavior Into Acoustic Sampling

Abstract

With the increased uncertainty introduced through climate change and fishing pressure, having accurate estimates of fish biomass is essential for global ecosystem and economic health. Acoustic surveys are an efficient way to determine population size for pelagic species in the Northeast Atlantic (NEA), but acoustic population estimates still contain uncertainty and are difficult for some species. For example, Atlantic mackerel (Scomber scombrus) is one of the most valuable fisheries in the NEA and is not monitored acoustically, as mackerel lack the swim bladder that provides the strongest acoustic echo (target strength) at common assessment frequencies. For all pelagic species, and especially for mackerel, behavior is a source of variation in acoustic measurements and therefore in population estimates. Behavior is mediated by both extrinsic and intrinsic factors, such as the environment and the life history of the fish. In turn, behavior affects the density of the shoal and the tilt angle of the fish relative to the survey vessel, affecting their target strength, which affects the biomass estimate. Some fish may also undergo an anti-predator response to survey vessels, changing their behavior in response to the survey. Understanding these behaviors and incorporating them into acoustic stock assessment methods can improve the accuracy of population estimates. Individual-based models (IBM) of fish shoals provide a pathway for incorporating behavior into acoustic methods. IBMs have been used extensively to build theoretical models of fish shoals, but few have been successfully tested in lab or field conditions. As computational power and monitoring technology improve, modeling the collective behavior of pelagic fishes will be possible. Novel, interdisciplinary approaches to data collection and analysis will help translate theoretical IBMs to the fisheries science domain. Beyond acoustic stock assessments, this approach can be used to investigate knowledge gaps in the effects of fisheries-induced evolution and the potential for range shifts under climate change. Further work to synthesize existing models and incorporate field data will help determine how environmental, ecological, physiological, and anthropogenic factors, often affecting both behavior and acoustic surveying, are interconnected. Moving from theoretical models to practical applications will be a valuable tool in tackling the uncertainty that accompanies further fisheries exploitation and warming oceans.