Machine learning for modeling North Atlantic right whale presence to support offshore wind energy development in the U.S. Mid-Atlantic.

The Mid-Atlantic region is set to be one of the first and largest contributors to the offshore wind energy goals of the United States. Yet, the same region is home to a diverse marine ecosystem comprising important marine species such as the critically endangered North Atlantic right whale (NARW). To support the responsible development and operation of the planned offshore wind farms, there is a need for high-resolution modeling of NARW presence, i.

Sensitivity of marine fish thermal habitat models to fishery data sources.

Statistical models built using different data sources and methods can exhibit conflicting patterns. We used the northern stock of black sea bass () as a case study to assess the impacts of using different fisheries data sources and laboratory-derived physiological metrics in the development of thermal habitat models for marine fishes. We constructed thermal habitat models using generalized additive models (GAMs) based on various fisheries datasets as input, including the NOAA Northeast Fisheries Science Center (NEFSC) bottom trawl surveys, various inshore fisheries-independent trawl surveys (state waters), NEFSC fisheries-dependent observer data, and laboratory-based physiological metrics.