ELLSWORTH – Maine’s Congressional delegation announced last week that the National Oceanic and Atmospheric Administration’s Sea Grant American Lobster Initiative will again receive $2 million in funding to support Gulf of Maine and Georges Bank American lobster research priorities. This is the second consecutive year that the program has received federal money for the research to address critical gaps in knowledge about how American lobster is being impacted by environmental change in the Gulf of Maine.
“Maine’s fishermen and women have been careful stewards of our natural resources for generations,” Sen. Susan Collins (R-Maine) said last week in a statement. “This critical federal funding will build on their efforts to support the health of Maine’s lobster fishery and help ensure its continued success.”
Four of the nine research projects being funded will be conducted by Maine researchers and institutions:
1) Fishing in hot water: Defining sentinel indicators of resilience in the American lobster fishery – University of Maine Orono.
The intent of this research is to develop “sentinel indicators” of resilience for the lobster industry that can be used to detect early signs of vulnerability among harvesters. In pursuit of this research, the authors will use peer-reviewed methods to develop and evaluate sentinel indicators and work closely with the lobster industry, managers, and the Lobster Regional Extension Program to solicit input and distribute results. Although the status of the lobster stock is closely monitored in the Gulf of Maine, no indicators currently exist to detect vulnerability among participants in the industry. Understanding vulnerability is vital to informing future management decisions and coastal community resilience.
2) Incorporating changes in thermal habitat and growth to improve the assessment of American lobster stocks and spatial distribution in the Gulf of Maine, Georges Bank, and Southern New England – University of Maine Orono
The purpose of this project is to develop a modeling framework to assess and forecast spatio-temporal dynamics of American lobster in a changing ecosystem. A forecasting model will be built into the American lobster stock assessment framework that utilizes stock assessment output and projected thermal habitat to predict stock size and catch seasonally. This will allow for simulating multiple future climate scenarios and fishing mortalities in the Gulf of Maine, Georges Bank, and southern New England. Additionally, this work also will enable the testing of the UMaine Lobster Stock Assessment model under previously utilized spatial scales from the Atlantic States Marine Fisheries Commission (ASMFC) to determine if the stock unit assumptions hold true using this stock assessment model.
3) Testing and developing effective non-invasive female maturity assessment methods and protocols for lobster by the Department of Marine Resources.
DMR began conducting female American lobster maturity studies via ovarian staging in 2018. The goal of the work proposed here is to leverage DMR’s recent efforts in order to evaluate and develop two promising non-invasive maturity assessment methodologies and generate publicly accessible instructional materials that would allow for lobster maturity datasets to be easily updated in the future. The research team involves a new collaboration of state agency researchers, members of the lobster industry, an industry trade association, and Canadian researchers. The research will provide insight into the most appropriate maturity assessment approach and provide long-term benefits to researchers who can utilize these methods to update size at maturity datasets regularly as conditions in the Gulf of Maine continue to change.
4) Understanding and improving spatial distribution projections for lobster – Gulf of Maine Research Institute.
This project aims to address the limitations of lobster distribution models and strengthen stakeholders’ trust in the ability of fisheries scientists to accurately quantify, project, explain, and apply lobster distribution and abundance models under future climate conditions.