Project summary/abstract the mid-atlantic bight (MAB) is a dynamic ocean region with strong seasonal cycles

The National Oceanic and Atmospheric Administration awarded a Cooperative Agreement of $159,998 to the New Jersey Sea Grant Consortium on August 1, 2026, under the Sea Grant Support program (CFDA 11.417).

The recipient will quantify interannual variability of the Mid-Atlantic Bight cold pool—including timing of presence, volume, and average temperature in the spring—using the DOPPIO regional ocean modeling system. The project will also quantify interannual variability in timing and location of longfin squid spring inshore migration and test whether squid migration timing is determined by specific oceanographic metrics associated with cold pool formation. The research addresses a gap in understanding connections between the annual cold pool seasonal cycle and longfin squid migration patterns, with implications for fishery management and economics as the cold pool warms and shrinks under long-term climate change.

Performance occurs at Highlands, New Jersey, with a period of performance from August 1, 2026, through July 31, 2028. Sea Grant Support funds applied research combined with extension activities to transfer knowledge from laboratory to user communities managing ocean, coastal, and Great Lakes resources.

Thermal seasonal variability in the MAB is dominated by a distinctly cold, nutrient-rich, pool of bottom water that forms annually known as the cold pool. The timing of the annual cold pool spring formation, summer intensification, and fall breakdown can all vary significantly from year to year. This interannual evolution of the MAB cold pool supports ecological services for a variety of commercially targeted species, including longfin squid (doryteuthis (amerigo) pealii). Longfin squid are a short-lived demersal species that perform seasonal cross-shelf migrations in the spring. Connections with and the relative timing between the onset of cold pool formation and longfin squid inshore spring migration remain poorly understood. Recent observational and modeling studies have indicated that the MAB cold pool is warming and shrinking, amplifying the year-to-year variability in the cold pool seasonal phenology. These long term to seasonal scale changes to the spatial extent and the hydrography of the cold pool may significantly alter the spring inshore migration of longfin squidchanges that could have implications for the management and economics of the squid fishery. Given this GAP in understanding and in collaboration with regional fisheries stakeholders, i propose a cooperative research project that will test the following hypothesis: the timing of spring migration of longfin squid is determined by specific oceanographic metrics (i.e. temperature, stratification, etc.) associated with the timing of the cold pool setup across the mid-shelf. To test this hypothesis, i will: 1. Quantify the interannual variability of the MAB cold pool including timing of presence, volume, and average temperature, in the spring using the doppio regional ocean modeling system (roms)-based model. 2. Quantify the interannual variability in the timing and location of longfin squid spring inshore migration using long-term independent trawl surveys. 3. Assess the impact of cold pool metrics on the longfins shelf-wide distribution in the spring with species distribution models. Using the doppio ocean model, independent fisheries trawl data from the shelf break to the coast, and species distribution models, such as the vector-autoregressive spatial temporal model (vast), i will integrate highly resolved ocean and longfin squid data to explore how a key MAB ocean feature influences the timing and interannual variability of seasonal inshore squid migration. The proposed research is responsive to the needs of the community and the upcoming longfin research track assessment in 2026, ensuring that IT aligns with both scientific and industry priorities. Expected results will define a mechanistic link between MAB cold pool dynamics and the spatial ecology of local longfin populations. Taking a community-centered approach ensures the findings of this work will not only be scientifically robust, but also practically relevant for the needs of all fisheries stakeholders involved.