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Dynamic Habitat Mapping of Pelagic Tuna and Shark Species for Improved Fisheries Management

Dynamic Habitat Mapping of Pelagic Tuna and Shark Species for Improved Fisheries Management. System Science Applications (D. Kiefer), Interamerican Tropical Tuna Commission (M. Hinton), Southwest Fisheries Science Center (S. Kohin), JPL (E. Armstrong). Decision Support.

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Dynamic Habitat Mapping of Pelagic Tuna and Shark Species for Improved Fisheries Management

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  1. Dynamic Habitat Mapping of Pelagic Tuna and Shark Species for Improved Fisheries Management System Science Applications (D. Kiefer), Interamerican Tropical Tuna Commission (M. Hinton), Southwest Fisheries Science Center (S. Kohin), JPL (E. Armstrong)

  2. Decision Support • Improve and automate IATTC’s determination of Eastern Pacific Ocean tuna habitat and recruitment as inputs to it stock assessment model. • Improve and automate SWFSC Pelagics Group’s determination of California Current albacore and blue, thresher, and mako shark habitat for stock assessment and conservation.

  3. PHAM Habitat Analysis Process Flow Fishery Data Sets Satellite Imagery GHRSST (SST) 28km AVISO (SSH) 28km GLOBE COLOR (Chl-a) 9km QUICKSCAT (Wind) 28km & Ocean Models NASA ECCO2 18km • GIS Data Services • Satellite/Model Data Integration • FishTracker Algorithm • Temporal & Spatial Data Matching- drifter algorithm Import Data Visualization and preliminary selection of habitat variables • Statistical Tools • Analysis of Variance • Cross Correlation • EOF Analysis • Regression Analysis Determine quantitative relationships between oceanographic variables and species distribution • Functional & statistical relationships between environmental variables and species presence and abundance Use oceanographic data to predict species distributions User Fisheries Management Decisions Stock Assessment Closures Export / Interpret Data Dynamic Maps of Distribution

  4. SKJ Distribution of purse seine catches BET YFT

  5. PHAM screen of habitat analysis interface, map of calculated spawning sites, and graphical results of analysis

  6. GHRSST Sea Surface Temperature

  7. SST Frontal Probability Index: June 1988 Data source: GHRSST Level 4 .25deg AVHRR_OI SST (Reynolds)

  8. Velocity Vector Image PHAM screen of NASA’s ECCO-2 global circulation model and graphical results of analysis. Drifter algorithm for spawning sites.

  9. NASA ECCO2 Global Circulation Model – Mixed Layer Depth

  10. Chlorophyll GHRSST Distributions generated from PHAM output

  11. PHAM screen of critical habitat of skipjack tuna as calculated from habitat analysis and current satellite imagery.

  12. Juvenile Drift 7/1/2003 PHAM map of skipjack spawning sites (7/21/03) calculated from NASA’s ECCO-2 global circulation model and fisheries age structure analysis of catch.

  13. A Simple Loophole Algorithm of Transforming SOI into SS2 Calculations of Bigeye Recruitment Predicated Bigeye Recruits reversal

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