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Relating Distribution and Abundance of Deep-sea Coral Communities to Habitats using Predictive Models and Broad-scale Seafloor Maps

Project Goal

To relate abundance of deep-sea coral communities (DSC) to habitats using predictive models and broad-scale seafloor maps.

Geographic Location

Southern California Bight


Statistical models are being developed to predict densities of some members of DSC off southern California. A variety of models will be considered, and will be based on a number of associated habitat variables (e.g., depth, substratum type, temperature) and abundance data of DSC taxa quantified from visual surveys. Model predictions will be validated using additional datasets not used in the original model development. Model output will be coupled with seafloor habitat maps in a geographical information systems (GIS) environment to predict DSC distribution and abundance on a broader scale. The strong affinities that many DSC have to specific habitat characteristics result in patchy spatial distributions of their abundances. Coverage of habitat maps at resolutions useful to predict DSC occurrence and extrapolate them over broad areas of the seafloor has been limited. Most recently, coastwide seafloor habitat maps of substratum type and depth of varying levels of accuracy and resolution have been developed for assessment of west coast groundfish essential fish habitat; parts of these maps have been improved particularly off California with high-resolution multibeam acoustic data and interpreted habitats.


A post-doctoral scholar (David Huff) has been identified to work on this project and has been contracted through University of California Santa Cruz. A database has been compiled to support our objective of developing statistical models that predict densities of DSC. Several metrics from in-situ data will be used in the predictive modeling, including depth, temperature, sediment types, habitat patch heterogeneity, and DSC counts, density, and sizes. The contracted researcher will use these data to develop and evaluate the models, apply results to broad-based distributional maps of benthic habitats, and to interpret ecological significance of results.

Importance to Management

The development of habitat-based predictive models of DSC distribution and abundance will assist scientists in locating and characterizing DSC ecosystems, and in understanding the biology and ecology of these communities in southern California. Habitat-based predictive models of DSC will assist researchers and managers in understanding habitat requirements of DSC, and in prioritizing areas for future field research and possible protection.


NOAA Southwest Fisheries Science Center Habitat Ecology Team Homepage: http://swfsc.noaa.gov/HabitatEcology/

Fiscal Year 2011 Funding


Point of Contact

Mary Yoklavich, Mary.Yoklavich@noaa.gov

Location of some of the data sources for the initial modeling effort (Footprint and Piggy Banks in the Footprint EFH area of the Channel Island National Marine Sanctuary). Seafloor map is hill-shaded bathymetry derived from a high-resolution multibeam survey conducted by G. Cochrane (USGS Western Region Coastal and Marine Division).

Credit: NOAA Fisheries SWFSC