Draft, updated 10/28/96
1. Real-time or near real-time environmental data needs
1.1. Enhance applications of real-time data to fisheries problems by:
€i) using the historic data to estimate climatological reference fields to serve as a baseline for identifying anomalies in real-time data, and
€ii) analysis of historic data to develop relationships between biological and physical parameters which can then be applied to real time data.
1.2. Determine the degree to which surface data is representative of internal ocean structure (e.g. determine de-correlation scales between satellite SST and internal thermal fields), resulting in a wider application of data derived from remote sensing instrumentation.
1.3. Develop an operational, high spatial resolution, multi-layer, regional circulation model imbedded in a larger scale general circulation model to integrate the diversity of physical data now being collected and enhance our current understanding of biological and fisheries processes.
1.4 Improve the accessibility of near real-time fisheries and resource survey data to complement the growing number of physical data products now available and stimulate new analyses.
1.5 Apply real-time environmental data to adapt survey designs to expected changes in the distribution of the target species and also for adapting real-time management of fisheries.
1.6. Use newly developed multibeam sonar technology in support of fisheries surveys with a near real time, detailed 3-D picture of seafloor characteristics
1.7 Because real-time environmental data may be used to predict fish distributions, it follows that prediction of the distribution of fishing vessels may be feasible. This can lead to improvements in management practices as it relates to minimizing by-catch and aid enforcement.
1.8. Develop secondary derived products (e.g. simulated Lagrangian drifters applied to studies of larval fish transport) from satellite data tailored to fisheries needs.
1.9. Use new satellite technologies (e.g. NOAA-K data which combines visible, thermal and microwave and hence can provide coverage during cloudy periods; SAR, which provides all weather measurements; and ADEOS OCTS which provide ocean color information) to develop products for fisheries use.
1.10. Make available to the civilian community to the greatest extent possible classified near real time data such as in GOODS (NAVOOCEANO) and BATHY (FNMOC).
1.11. Develop a pilot project to promote the near-real time delivery of environmental data from fishing vessels, including both surface weather and marine data and from fishing gear-mounted sensors where feasible.
1.12. Develop capability for real-time access to oceanographic data or processed products (COADS, MOODS, remote sensing) for fisheries management or recruitment prediction purposes.
2. Retrospective working group
2.1. Develop long-term baseline indices that describe the range of natural variability; extend key time series (sea level pressure, wind fields, temperature, salinity, abundance indices) back to 1900 or earlier.
2.2. Inter-calibrate different sampling systems and models.
2.3. Promote efforts for verification and validation of models; use key "Pulse Points" and transects as reference points.
2.4. Provide users with measures of uncertainty in model output variables.
2.5. Improve physical model accuracy of circulation and variability in Arctic, Subarctic, and North Atlantic regions.
2.6. Conduct comparative retrospective analyses at the regional to global scale; this will require southern hemisphere plankton time series.
2.7. Continue atmospheric, oceanographic and biological data rescue and preservation.
2.8. Promote projects for fisheries scientists to work with physical modelers to produce focused model output.
2.9. Create meta-data base to facilitate user accessibility to data.
2.10. Expand use of archival tags and drifting and moored sensors.
2.11. Provide quality control flags to minimize misuse and misinterpretation of data.
2.12. Convene a workshop to address which environmental data products should be accorded highest priority for saving and maintenance relative to applications to fisheries.
2.13 Develop an archive of detailed seafloor data that can be used for retrospective analyses of fishery survey data to identify habitats and species associations.
3. Oceanographic and atmospheric model applications
Note: The working group identified recommendations 3.1-3.5 as highest priority and 3.6-3.10 as high priority.
3.1. Cross-discipline communication- improve two-way communication between modelers and fisheries scientists, and between the scientists and NMFS managers.
3.2. Model validation and credibility. Input fields improved by reanalysis should be used in all models when available, and data assimilation models must be tested with independent data.
3.3. From model output, the research community must develop products that management will need and use. The WG recommended that some dramatic events (e.g., the California sardine crash) be shown as retrospective examples of how model output can be incorporated in management plans for responding to environmental changes that impact fishery populations.
3.4. Proceed with full bio-chemo-physical coupling of models to accurately represent the distributions and dynamics of these variables in areas of biologically dynamic activity of interest to fisheries researchers.
3.5. Identification of useful model parameters; fisheries scientists (in conjunction with modelers) must identify an expanded list of important parameters, possibly in a future workshop.
3.6. NOAA should permanently store output from selected models (including model climatologies, forcing fields) for future applications.
3.7. Define domains appropriate for fisheries research; fisheries researchers must specify space time domains and parameters needed to address fisheries issues, and communicate them to modelers.
3.8. Coupling models of different scales; small spatial-scale models must be nested within larger domain models, for prescribing forcing or open boundary conditions.
3.9. Apply output from estuarine, plume, and nearshore models to fisheries issues; NOS is tasked to develop site-specific models of many US estuaries and bays. NMFS should take advantage of these models for fisheries applications, particularly since many commercial stocks use estuaries and nearshore habitats during some part of their life cycle.
3.10. Incorporate human activities in models (e.g., habitat alteration, streamflow modification); human-induced changes in environmental conditions and habitat contribute to fisheries variability, and must be considered in modeling activity.
4. Data delivery systems, data accessibility criteria, and formats
4.1. Increase the inter-operability among existing environmental data access systems such as MEL, NOAAServer, JGOFS, etc. to allow for cross- organizational searches and data access.
4.2. Distribute inexpensive, easy to use software tools for analyzing, extracting, and manipulating important data sets (e.g. COADS, World Ocean Atlas).
4.3. Develop theme pages that focus on issues that fisheries scientists can recognize (e.g. El Niño Theme Page).
4.4. Enforce a proactive data archival policy to insure that new data are made available to the widest community. Data may be stored and supported locally for project or program use, but must be contributed in a timely manner to a permanent national archive for long-term safe keeping.
4.5. Establish as a high priority that all fisheries relevant data can be accessed through on-line system that enables users to search, browse, order, and receive data and information identified through a user defined discovery process.
4.6. Provide a high band width connection to the Internet for all fisheries users to ensure on-line network access.
5. Partnerships for Fisheries Oceanography
5.2. Establish a fisheries working group under the auspices of the Committee on Environment and Natural Resources (CENR) to encourage interagency cooperation.
5.3. Take advantage of increasing cooperation in remote sensing between NOAA and NASA as an opportunity to raise fisheries/environmental cooperation issues.
5.4. Utilize existing programs (COP, NOAA Cooperative Institutes, NOAA-Navy MOA, etc.) to raise the visibility of issues related to the use of environmental data in fisheries.
5.5. Improve NMFS access to outside experts for modeling and chemical and physical oceanographic expertise.
5.6. Stimulate research on the effects of climate-scale variability on fisheries through existing cross-cutting programs.
5.7 Form an ad hoc or steering committee for environmental data for fisheries science that crosses NOAA line offices and agency boundaries to continue efforts initiated at this workshop.