Improving The NOAA NMFS and ICCAT Atlantic Bluefin Tuna Fisheries Management Decision Support System Final Research Results

Mitchell A. Roffer, Roffer's Ocean Fishing Forecasting Service, roffers@bellsouth.net (Presenter)
John T. Lamkin, NOAA NMFS SEFSC, john.lamkin@noaa.gov
Frank Muller-Karger, Univ. South Florida IMaRS, carib@marine.usf.edu
Barbara A. Muhling, Univ. Miami CIMAS, barbara.muhling@noaa.gov
Walter Ingram, NOAA NMFS SEFSC, walter.ingram@noaa.gov

This report will summarize the work focused on extending Earth science research results to decision support systems in the Ecological Forecasting national priority area. The activity was focused on improving the existing National Oceanic and Atmospheric Administration’s (NOAA) National Marine Fisheries Service (NMFS) decision making system for population assessment and management of Atlantic bluefin tuna (Thunnus thynnus). The research team is a multi-sector and multi-disciplinary team composed of government (NOAA_NMFS), academic (University of South Florida Institute for Marine Remote Sensing) and commercial (Roffer’s Ocean Fishing Forecasting Service, Inc.).

A main goal was to develop environmentally sensitive catchability abundance indices for bluefin tuna (ABT) larvae that are needed to improve the stock assessment of this internationally important species. These were derived, in part, from the innovative use of several earth orbiting satellites (e.g. Aqua, Terra, NOAA, others) and classification tree modeling. A DTREG classification tree modeling approach was used as this approach provided probabilities of catching ABT larvae using non-parametric statistics. The results of twenty three years (1989-2011) of fisheries and oceanographic data (in situ and satellite) will be presented. Among the other goals that were successfully achieved were: 1) to improve the targeted “adaptive” sampling system (i.e., catch more larvae through habitat modeling, satellite remote sensing, and gear technique modifications) and; 2) to extend sampling to other geographic areas. These were achieved through international (e.g. Mexico and Spain) collaborative research, improved sampling site selection through the integration of real-time satellite data analyses and ocean current modeling with the derived habitat model, as well as, net towing modifications.

Presentation Type:  Poster

Session:  Science in Support of Decision Making   (Wed 10:00 AM)

Associated Project(s): 

• Roffer, Mitch: Improving The NOAA NMFS and ICCAT Atlantic Bluefin Tuna Fisheries Management Decision Support System ...details

Poster Location ID: 305