M-111-4
Assessing the Vulnerability of Benthic Habitat to Fishing Gear Impacts in the Northwest Atlantic

Jonathan H. Grabowski , Marine Science Center, Northeastern University, Nahant, MA
Michelle Bachman , New England Fishery Management Council, Newburyport, MA
Chad Demarest , Social Sciences Branch, NOAA Northeast Fisheries Science Center, Woods Hole, MA
Steve Eayrs , Gulf of Maine Research Institute, Portland, ME
Brad Harris , Environmental Science - Fisheries, Aquatic Science and Technology Lab, Alaska Pacific University, Anchorage, AK
Vincent Malkoski , Massachusetts Division of Marine Fisheries
Dave Packer , Ecosystem Processes Division - Coastal Ecology Branch, NOAA/NMFS/NEFSC James J. Howard Marine Sciences Laboratory, Highlands, NJ
David Stevenson , Habitat Conservation Division, NOAA/NMFS/GARFO, Gloucester, MA
Page Valentine , USGS
The Magnuson-Stevens Fishery Conservation and Management Act (MSA) requires fishery management plans to minimize, to the extent practicable, the adverse effects of fishing on fish habitats.  To meet this requirement, fishery managers would ideally be able to quantify such effects and visualize their distributions across space and time.  The New England Fishery Management Council’s (NEFMC) Habitat Plan Development Team developed a Seabed Area Swept Impact (SASI) model to assess benthic habitat vulnerability as well as historical and future impacts from fishing gear to assist New England fisheries managers achieve the goal of minimizing adverse effects from fishing gear-habitat interactions. Specifically, this model was developed to better understand: (1) the nature of fishing gear impacts on benthic habitats, (2) the spatial distribution of benthic habitat vulnerability to particular fishing gears, and (3) the spatial and temporal distribution of realized adverse effects from fishing activities on benthic habitats.  To achieve this goal, we first conducted a vulnerability assessment of benthic habitat to fishing gear impacts. The assessment serves as a framework for generating and organizing quantitative susceptibility and recovery parameters for use in the spatial SASI model.  Here we discuss the major findings and implications of our modeling efforts.