Effective management of marine resources requires an understanding of the spatial distribution of biologically important communities. The northwestern Gulf of Mexico contains diverse marine ecosystems at a large range of depths and geographic settings. Presence-only predictive modeling is used to gain an accurate estimate of the dispersion of species across large geographic areas. Similar to prior research, this project deduces that local geographic characteristics provide accurate predictive capacity for determining the probability of occurrence for marine organisms. The highest resolution bathymetric data (10m) available for the region is used to develop raster layers that represent characteristics that have been shown to influence species occurrence in other settings. A georeferenced historical photo record collected via Remotely Operated Vehicle (ROV) is classified according to six commonly found mesophotic habitats across the 18 reefs and banks under consideration for FGBNMS boundary expansion. Using maximum entropy modeling, the influence of local geographic characteristics on the presence of these habitats is measured and a spatial probability distribution is developed for each habitat type across the study area.
