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Integrating Ocean Observing Data to Enhance Protected Species Spatial Decision Support Systems

Integrating Ocean Observing Data to Enhance Protected Species Spatial Decision Support Systems. Biodiversity and Ecological Forecasting Team Meeting May 17-19, 2010. Dr. Karin Forney. Dr. Pat Halpin. Presented by: Ben Best (Duke) Elizabeth Becker (NOAA). Project Team Members.

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Integrating Ocean Observing Data to Enhance Protected Species Spatial Decision Support Systems

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  1. Integrating Ocean Observing Data to Enhance Protected Species Spatial Decision Support Systems Biodiversity and Ecological Forecasting Team Meeting May 17-19, 2010 Dr. Karin Forney Dr. Pat Halpin Presented by: Ben Best (Duke) Elizabeth Becker (NOAA)

  2. Project Team Members Ben Best, Ei Fujioka, Pat Halpin, and Jason Roberts Marine Geospatial Ecology Lab Nicholas School of the Environment, Duke University Lisa Ballance, Jay Barlow, Elizabeth Becker, Steven Bograd, Karin Forney, and Jessica Redfern Southwest Fisheries Science Center NOAA - National Marine Fisheries Service Dave Foley and Daniel Palacios Joint Institute for Marine and Atmospheric Research, University of Hawai`i at Manoa Grant/Cooperative Agreement Number:  NNX08AK73G

  3. Cetaceans(whales, dolphins and porpoises) and anthropogenic threats Threats include Ship strikes Fishery bycatch Naval activities Anthropogenic sound Cetaceans protected by US laws MMPA ESA

  4. Cetacean distributions are dynamic Balaenoptera musculus Blue whale

  5. Marine Habitat Modeling Process Data Modeling SDSS Decision

  6. 1991 1993 1996 2001 2005 Ave. Key predictor variables Depth, Slope, SST Sample fin whale densities

  7. Expansion and Enhancement of the SDSS El Niño La Niña Challenge: Marine mammals are highly mobile; distributions change on seasonal, interannual and decadal time scales

  8. Expansion and Enhancement of the SDSS • Incorporate additional covariates derived from remotely-sensed data (varies by region) • Explore the implementation of Nowcast and Forecast capabilities • Update SDSS and release a package of open-source Desktop GIStools for end-users Whale, dolphin and porpoise species: Pacific: 21 species and 1 guild of beaked whales Atlantic: 12 species and five species guilds

  9. Nowcast and Forecast Capability development GHRSST (RSS Inc.): Blended SST Developed by Remote Sensing Systems, Santa Rosa, CA • High-resolution (9 km) infrared data • Microwave (data for cloudy areas) • Optimal interpolation • Pixel-by-pixel error characterization NOWCASTS (tactical) ROMS = Regional Ocean Modeling System Developed for the NASA-funded FAST Project (Chavez, Chai, Chao, Barber and Foley) • Run by Yi Chao's group at JPL • Uses forecast surface fluxes (NCEP) • Monthly mean products with 1-9 month lead time FORECASTS (strategic)

  10. “1991-2005 Climatology” NOWCAST – Dall’s porpoise densityfor novel 2008 survey (July-Nov) “Daily forecast”

  11. NOWCASTS as short-term forecasts (weeks)

  12. FORECAST – Striped dolphin densityROMS: Oct/Nov 2008 (as forecast in July)

  13. Expansion and Enhancement of the SDSS • Incorporate additional covariates derived from remotely-sensed data (varies by region) • Explore the implementation of Nowcast and Forecast capabilities • Update SDSSand release a package of open-source Desktop GIS tools for end-users Whale, dolphin and porpoise species: Pacific: 21 species and 1 guild of beaked whales Atlantic: 12 species and five species guilds

  14. SDSS: Summarize by Region • Select Region by • Drop-down list (OPAREAs, MPAs, EEZ) • Enter polygon coordinates • Draw on map • Return: • Effort, Obs • Min, Max, Mean • Histogram • Coordinates

  15. ROC Curve to Binary Habitat in SDSS Example: baleen guild (fin, blue, sei, Bryde’s) in summer

  16. Example: Species distribution modeling with MGET(Marine Geospatial Ecology Tools) Invoke R from ArcGIS to create plots, etc. Sample time-series imagery Fit models with R, evaluate using ROC analysis, predict maps from satellite images Binary classification (range map) Predicted probability of presence Cutoff = 0.020 True positive rate False positive rate

  17. Additional Derived Covariates Eddies from AVISO Fronts from Pathfinder / GHRSST Isern-Fontanet et al (2006) Cayula, J-F and P Cornillon (1992) Optimal break 27.0 °C Frequency Temperature 28.0 °C Front 25.8 °C Red: Anticyclonic Blue: Cyclonic

  18. Hybrid Coordinate Ocean Model (HYCOM) pros: 1/12 °, cloud-free, 3D, forecast cons: modeled, since 2003, physical only

  19. Hybrid Coordinate Ocean Model (HYCOM) cons: complicated projection

  20. Minimal Loss Decision Mapping Loss Decision

  21. Conclusions and Next Steps • Nowcast and forecast capabilities exceeded expectations • Incorporate additional ecological relevant covariates (e.g. ROMS-CoSiNE) • Foundation for climate-response modeling • Improved SDSS for end-user needs • Reproducibility with desktop GIS

  22. Thank You! Funding • NASA • SERDP • NOAA Project Support • Marine mammal observers, oceanographers, chief scientists, cruise leaders, officers and crew of surveys • Yi Chao (JPL) • Fei Chai (University of Maine) • NOAA Northeast and Southeast Fisheries Science Centers • Websites • SDSS – http://seamap.env.duke.edu • MGET – http://code.env.duke.edu/projects/mget

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