Assessing oyster population recovery in Chesapeake Bay: Management from a food-web perspective.

1. Assessing oyster population recovery in Chesapeake Bay: Management from a food-web perspective. Richard S. Fulford Denise Breitburg Roger Newell Mike Kemp Mark Luckenbach Place holder for GCRL Place holder for VIMS

2. TroSim-CASM Modeling approach Chesapeake Bay Trophic Simulation Model (TroSim) Multi-species bioenergetic model Based on CASM Model framework Dynamic network model Daily time-step Model single years to view seasonal patterns

3. Modeling Consumption Cmax – Maximum Consumption Rate (g/g/d) wi,j – Preference of consumer i for prey j ai,j – assimilation efficiency of consumer i eating prey j f(t) – temperature adjustment of consumption Consumption follows seasonal patterns in both composition and rate

4. Modeling Energetic Costs and Mortality Rmax – maximum respiratory costs (g/g/d) U – Excretory losses SDA – Costs of consumption f(t) – Temperature adjustment of respiration rsp(i,t) – Consumer and season specific costs of egg production m(i) – Consumer specific natural mortality

5. Model Groups • 6 producer groups (phytoplankton by size) < 2 um, 2-4 um,. 4-10 um, 10-50 um, 50-100 um, > 100 um • 14 Consumer groups in seven categories zooplankton, gelatinous zooplankton, pelagic bacteria, pelagic forage fish, benthic invertebrates, benthic bacteria, benthic omnivorous fishes • 3 larval sub-pools bay anchovy, ctenophores, oysters • Detritus and nutrient pools

6. Data Sources

7. Main bay Model – Mesohaline Baywide average Tributary Model – Patuxent and Choptank Rivers Project Objectives

8. Larval Pools Pelagic Prey Fish Oyster Larvae Bay Anchovy Anchovy Larvae Ctenophore Larvae Atlantic Menhaden Gelatinous Zooplankton Zooplankton Sea Nettles Ctenophores Acartia tonsa Phytoplankton Microzoopnktn Non reef fish < 2 microns Pelagic Bacteria Benthic Reef-assoc. fish 2-4 microns HNAN 4-10 microns Oysters 10-50 mic On-reef inverts 50-100 mic Off-reef inverts > 100 microns Benthic Bacteria N P Si DOC POC Detrital Pools

9. Pelagic Prey Fish Bay Anchovy Atlantic menhaden Gelatinous Zooplankton Sea Nettles Ctenophores Acartia tonsa Phytoplankton Microzoopnktn < 2 microns Zooplankton 2-4 microns “Lost” 4-10 microns Benthic Planktivores 10-50 mic 50-100 mic Oysters > 100 microns Detrital Pools

10. Model Linkage Dynamics Daily N, P, Si and inorganic TSS concentrations Light, temperature and nutrient limitation of primary productivity DO dynamics and water column stratification Benthic-pelagic coupling and sediment resuspension dynamics Daily removals by top piscivores Water Quality Models Fishery Production Models TroSim-CASM Decision Support System - NOAA Coastal Ocean Program Funding

11. Data suggest oyster recoverywill … • reduce phytoplankton biomass and particulate matter in water column • increase water clarity • decrease production of other planktivores • possibly decrease production of higher level consumers via bottom-up effects • Have similar effects as nutrient reduction

12. Modeling Oyster Recovery • Modeled 10X, 25X, and 50X scenarios • Assume threshold relationship between oysters and sea nettles • Assume linear relationship between oyster density, reef-associated fish, and on-reef invertebrates • Assume no relationship between oyster density and off-reef invertebrates Ex. 25X oysters = 25X on-reef inverts, 25X RAF, 10X SN

14. Phytoplankton Biomass Reduction Water quality model output from Noel and Cerco 2005 Table 1 - MD output

15. Change in total annual Production (proportion)

16. Change in total annual Production (proportion)

17. Change in total annual Production (proportion)

18. Oyster Recovery and Detritus

19. Oyster Recovery and Light Penetration

20. Change in total annual Production (proportion)

21. Model results suggest oyster recovery will … • reduce phytoplankton biomass and inorganic particulate matter in water column • improve water clarity locally but reduced effect regionally • decrease production of zooplankton but not menhaden • decrease bay anchovy production by 30-40% yr-1 • likely to affect production of top piscivores • decrease ctenophore production • likely to reduce predation on oyster larvae • Have a larger effect on 2o production than nutrient reduction due to seasonality