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Seasonal, Interannual, and Decadal Variability of Peruvian Anchovy Population Dynamics

This proposal defense presents a comprehensive study on the population dynamics of the Peruvian anchovy, the world's largest single species fishery, which represents up to 20% of global fish catch. It aims to model and analyze seasonal, interannual, and decadal variability in anchovy dynamics using the ROMS-CoSINE model combined with an Individual-Based Model (IBM). Critical questions addressed include the influence of environmental factors on anchovy growth, recruitment, and mortality, as well as the impacts of ocean currents and events like El Niño. The study is vital for understanding fishery management and sustainability.

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Seasonal, Interannual, and Decadal Variability of Peruvian Anchovy Population Dynamics

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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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