Adapting monitoring to a changing seascape: efficiency, flexibility and continuity for bottom trawl surveys
Fishery-independent survey data represents essential information for stock assessment, ecosystem-based fishery management initiatives, and applied ecological research. These data refers to information collected over space and time about populations of marine organisms, such as population abundance and biomass. The data can be used to fit statistical models to obtain multiple products for the assessment and management of marine populations. and can provide a comprehensive and standardized picture of marine populations when collected consistently over time, particularly with respect to gear selectivity and sampling design. However, fluctuations in resources for sampling effort, climate change, and limited spatial-temporal coverage can affect the consistency, precision, and accuracy of fishery-independent survey data. Therefore, it is critical to determine how to design surveys that can provide accurate and precise estimates to inform effective fishery management in the face of all these challenges.
Daniel Vilas, a researcher at SAFS, has been working on a project called “Adapting monitoring to a changing seascape: increasing the efficiency, flexibility, and continuity of bottom trawl surveys in the Bering Sea and beyond” led by Lewis Barnett from the NOAA Alaska Fisheries Science Center (AFSC). His work involves developing a framework for designing efficient and flexible fishery-independent survey sampling design, to effectively monitor ecosystems given limited resources and shifting species distributions.
Environmental factors can influence the physiology, metabolism, growth, reproduction, survival, and behavior of marine fishes and invertebrates, consequently impacting their distribution and phenology. For example, increasing sea temperatures due to climate change can cause shifts in species distributions and drive marine populations to colder and deeper regions. Variation in species distributions over time can also impact the spatial availability of species to sampling by surveys, with consequences for consistency and precision of abundance estimates over time.
The Bering Sea is undergoing major environmental changes, such as warming and high variation among years in seasonal sea ice cover and cold pool extent (the area of the seafloor with bottom temperatures below 2°C). The cold pool extent is a key factor contributing to the redistribution of the Arctic and subarctic demersal communities in the Bering Sea. Genetic analyses and bottom-trawl survey data revealed changes in the distribution of several commercially important species associated with such temperature fluctuation. Given that changing environmental conditions are likely to continue or become more novel in the following years, it is critical to evaluate the abundance of marine populations under feasible future environmental conditions.
The quantitative framework that Daniel is working on consists of building delta-generalized linear mixed models conditioned on historical fishery-independent bottom trawl data and observed sea bottom temperature in the Eastern Bering Sea and Northern Bering Sea for several species such as Pacific cod, halibut, and red king crab. These spatiotemporal operating models are used to simulate observations to evaluate several stratified sampling designs informed by environmental variables. This work aims to facilitate the precise and accurate estimation of abundance under current and future climates to maintain the quality of survey data products for managing marine populations.
