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Chesapeake 2000

Chesapeake 2000. Results presented at October 2004 MARS meeting Model accepted by MARS Documentation in progress Acceptance pending with review panel. Population Estimates. Biomass and spatial distribution of oysters in Virginia from field surveys 1998-2002

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Chesapeake 2000

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  1. Chesapeake 2000 • Results presented at October 2004 MARS meeting • Model accepted by MARS • Documentation in progress • Acceptance pending with review panel

  2. Population Estimates • Biomass and spatial distribution of oysters in Virginia from field surveys 1998-2002 • Biomass in Maryland based on Jordan estimate 1991-2001 as per R. Newell • Spatial distribution in Maryland based on Yates bars

  3. Mg C/sq m

  4. Model Assumptions • We use a spatially-uniform mortality rate that represents effect of harvest, disease, and other factors • Our population estimates (existing, ten-fold etc.) look at baywide biomass, not smaller regions

  5. Implications • The conclusions are sound. Oysters have local impact but do not significantly affect anoxia • Quantitative impacts on local scale are uncertain • Production of results on local scale requires thought and model modifications

  6. Ariakensis • We have completed and delivered seven runs ranging from 1x109 to 50x109 kg oyster dry weight. • Documentation in progress • The issues and assumptions regarding spatial distribution for Chesapeake 2000 hold here as well

  7. Ariakensis • We are committed to make three additional runs • One is to have biomass distribution estimated from larval transport and demographic modeling (non-uniform mortality) • Time frame uncertain

  8. Menhaden • The Bay Program wants to do something about menhaden • Very limited budget ($60k) and time frame (?)

  9. Options • Individual-based model (IBM) • Couple to network model (Ecopath)

  10. IBM - Advantages • Best way to account for menhaden distribution and behavior • We have some preliminary coupling of an IBM to the water quality model. Also some in-house expertise • Really exciting to work on

  11. IBM - Disadvantages • Comprehensive programming of fish movement is a demanding task probably beyond available resources. • We would have to adopt some very approximate representation of fish migration and distribution • We lack all the connections (the thing that eats the thing that eats the thing that eats the thing …..)

  12. Ecopath Advantages • Ecopath has all the connections • Some preliminary application of Ecopath to Chesapeake Bay has been conducted • Thought has been given to how a coupling between Ecopath and water quality model should proceed

  13. Ecopath Disadvantages • We don’t know of an existing, well-calibrated, Ecopath model of the bay • Ecopath lacks seasonality and spatial representation.

  14. Annual Net Algal Production and Consumption by Predators

  15. Computed Zooplankton Populations

  16. Option 1, the IBM • Force spatial and temporal distribution of menhaden • Recalibrate model to improve estimate of zooplankton predation, allow specifically for menhaden • Execute various sensitivity scenarios to menhaden grazing and harvest

  17. Option 2, Ecopath • Attempt a “loose” coupling. Information is exchanged indirectly via a human interface • Poll Rob Latour and Jim Hagy for Chesapeake Bay Ecopath Models • Look for the hooks. These may be algal biomass, primary production, predation rates, zooplankton biomass, benthos, etc.

  18. Option 2, Ecopath • Examine the potential “hooks” for consistency. If the models are inconsistent, what can be done? • Give both models a big “push.” e.g. Confirmation Scenario or 1950’s simulation. Are responses consistent? • Alter menhaden population in Ecopath. Try to enforce a similar response in water quality model.

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