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Yi Xu April 2006

Seasonal Cycle, Interannual and Decadal Variability of Peruvian Anchovy Population Dynamics: A Model Study Ph.D Thesis Proposal Defense. Yi Xu April 2006. Acknowledgements. Advisor: Dr. Fei Chai Committee: Huijie Xue, James McCleave, Andrew Thomas (UMaine)

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Yi Xu April 2006

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  1. Seasonal Cycle, Interannual and Decadal Variability of Peruvian Anchovy Population Dynamics: A Model StudyPh.D Thesis Proposal Defense Yi Xu April 2006

  2. Acknowledgements • Advisor: Dr. Fei Chai • Committee: • Huijie Xue, James McCleave, Andrew Thomas (UMaine) • Kenneth Rose (Louisiana State University) • Francisco Chavez (MBARI) • Ocean Modeling Group: • Guimei Liu, Lei Shi, Steve Cousins, Danya Xu, Yi Du • Others: • Nana Xu (University of Pennsylvania) • Lei Han (Ocean University of China) • Chunbao Miao (NOAA, Washington DC) • Xian Wang (University of Alaska) Funded by NASA & NSF

  3. Outline • Introduction • Questions • Physical, Biogeochemical, and Fish Models • ROMS-CoSINE Model Output Analysis • Development of IBM for Peruvian Anchovy • Case Study 1: Mean Condition • Case Study 2: Seasonal Cycle • Case Study 3: Interannual Variability • Sensitivity Studies • Current and Future Work • Summary

  4. Introductionwhy Peruvian anchovy? • The largest single species in the world’s fisheries • About 18~20% of the world’s fish catch The World’s Fishery Production (unit in million metric tons) Top 10 species (FAO Database 1996)

  5. Introductioncoast of Peru • 0S-20S 70W-85W • Northwestward wind • Strong Upwelling • Cool surface temperature • Highly productive region Wind Ekman Transport

  6. SST anomaly vs Peruvian Anchovy Catch

  7. Anchovy-regime Sardine-regime PDO, PeruvianAnchovyand Sardine Chavez et al., Science, 2003

  8. Questions • What are the key environmental factors regulate Peruvian anchovy growth dynamics? How do these factors vary on seasonal, interannual, and decadal time scale? • How do physical and biological conditions affect Peruvian anchovy recruitment and natural mortality? • What is the role of ocean current in controlling Peruvian anchovy larvae distribution and their growth dynamics? How do El Nino events affect larvae and adult distribution? • What is the impact of Peruvian anchovy on plankton biomass and productivity? • How can we use the model to evaluate and compare natural and fishing mortality of Peruvian anchovy?

  9. Physical, Biogeochemical, and Fish Models • The Circulation Model: • Regional Ocean Model System (ROMS) • The Biogeochemical Model: • Carbon, Nitrogen Silicate Ecosystem (CoSINE) • The Fish Model: • Individual Based Model (IBM)

  10. ROMS • Pacific Ocean • NCEP Forcing • Fine Resolution 50km or 12.5km

  11. Air-Sea Exchange Small Phytoplankton [P1] Micro- Zooplankton [Z1] Biological Uptake Total CO2 [TCO2] Grazing NO3 Uptake NH4 Uptake Predation Nitrate [NO3] Iron Excretion Meso- zooplankton [Z2] Ammonium [NH4] N-Uptake Fecal Pellet Advection & Mixing Iron Grazing Fecal Pellet Diatoms [P2] Lost Iron Detritus-N [DN] Detritus-Si [DSi] Si-Uptake Sinking Silicate [Si(OH)4] Physical Model Dissolution Sinking Sinking CoSINE Carbon, Silicate, Nitrogen Ecosystem Model Chai et al. 2002; Dugdale et al. 2002

  12. ROMS-CoSINE I II III IV Resolution 50km 50km 12.5km 12.5km Grids 34×32×33 34×32×33 166×120×33 166×120×33 Forcing Daily Daily Monthly Daily Output Time Interval Monthly Monthly Monthly 3 days Time Series 1990-2004 1950-2004 Climatology 1950-2004 Status Available N/A Available N/A ROMS-CoSINE Outputextracted data for Coast of Peru

  13. ROMS-CoSINE Output12.5km resolution Temperature (Surface and Vertical Profile)

  14. ROMS-CoSINE OutputModel comparison study----Annual Mean Condition ROMS-CoSINE In-situSeaWiFS Surface Chlorophyll

  15. ROMS-CoSINE OutputModel comparison study---- Seasonal Cycle

  16. Focus: Individual Based Model (IBM) • Mass and energy balance • Connect fish with environmental factors • Track fish growth through entire stages • Track fish population • Track fish movement

  17. Focus: IBM • Growth • For egg and yolk-sac larva: Temperature dependent • From first feeder to adult: Bioenergetic equation • Mortality Natural & Fishing • Movement Currents, Swimming Behavior, Random Effects C-consumption R-respiration S-specific dynamic action F-egestion E-excretion

  18. Anchovy IBM: Input and Output • Input list • Temperature • 4 types of plankton groups • Currents • Biological Parameters of anchovy (growth, food selection coefficients, etc.) • Output list • Growth: length and weight at age • Population dynamics: numbers at age • Movement: trajectories of anchovy schools IBM

  19. Preliminary Results • One fish growth study • Case study 1: Steady State Condition • Case study 2: Seasonal Cycle • Case study 3: Interannual Variability • Sensitivity Study

  20. Case Study 1---Steady State Modeled Anchovy Growth Length@age Lab observation (Palomares et al., 1987) Vitrual Population Analysis (Pauly et al., 1987)

  21. Case Study 2---Seasonal Cycle Growth Length@age Weight@age

  22. Case Study 2---Seasonal Cycle Anchovy Recruitment to 5cm (recruit to fishery) mesozooplankton Recruitment diatom

  23. Strong El Nino Moderate El Nino Case Study 3---Interannual Variability Temperature mesozooplankton diatom Recruitment

  24. Sensitivity Studies Temperature Effects

  25. Sensitivity Studies Food Selection diatom mesozooplankton microzooplankton

  26. Current Work---Population Mortality rate

  27. Current Work---Population • Egg Distribution (Pauly, 1987)

  28. Future Work • 3D Simulation • 4 Different regions • Movement • Direct link fish model with ROMS-CoSINE model • Natural vs Fishing Mortality • Longer time series for PDO study

  29. Summary • ROMS-CoSINE ecosystem model results show promising performance on Peruvian upwelling system. • An IBM for Peruvian anchovy has been developed, based on bioenergetic equations to study its growth through the entire life span. • Three different environmental conditions are examined, the steady state condition, seasonal cycle and interannual variation. The preliminary results show a clear response of anchovy growth dynamics corresponding with physical and biological processes on seasonal and interannual time scale. • Future Work: • Study the population dynamics of Peruvian anchovy and movement behavior in a 3D domain. • Link fish model directly with biogeochemical model, and include feedback processes. • Separate the fishing term from the natural mortality.

  30. --The End--Questions?

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