Plankton Controls on Suspended Sediments and Water Clarity in Chesapeake Bay

1. Plankton Controls on Suspended Sediments and Water Clarity in Chesapeake Bay W. Michael Kemp Walter R. Boynton University of Maryland Center for Environ. Science Horn Point Laboratory Chesapeake Biological Lab 25 January 2006

2. A) Statistical Analysis of Monitoring VFX data • Relate plankton sinking to environmental variables • Relate inorganic solids sinking to plankton and other variables General Study Design B) Mesocosm Experiments •Manipulate nutrients and clays over algal bloom cycles •Test field derived relationships •Test idea that algae control sinking & suspension of solids C) Incorporate Algorithms into Simulation Models • Dynamic, spatially aggregated scenarios to test algorithms • Transfer tested algorithms to WES model *REVISED in January 2005 DE-EMPHASIZING “C”

3. Sediment Trap Monitoring Program Design • Collection arrays sampling near • surface, bottom, pycnocline • Vertical orientation maintained • Consistent orientation into currents • Collector design with 10:1 aspect • Deployment duration 5-7 days

4. Chlorophyll-a Flux Stock Total Solids Flux Stock Temperature, Salinity Temp Salinity DO, (Secchi)-1 Oxygen (Secchi)-1 Particulate N, P PN PP Sediment Trap Data (VFX): 1985-1992 • Seasonal deployments February • into December • Eight year (+) data record • Clear seasonal and inter-annual • patterns related to plankton • production-respiration balance • Measure sinking and resuspension • of new and recycled particles

5. Chl-a Flux Chl-a Stock TSS Flux TSS Stock Temp Salinity PN:PC PP:PC Seasonal Sequence of Chl-a & TSS Stocks & Fluxes • Plankton Chl-a stocks and fluxes • follow seasonal cycles • Ratio Flux/Stocks is greater in • summer than spring • Control by ecological processes • TSS stocks & flux follow Chl-a • seasonal cycles • Ratio Flux/Stocks is greater in • summer than spring • Clearly, TSS & plankton Chl-a • dynamics are linked

6. Total Solids & Chl-a Fluxes vs. Stocks • Phytoplankton Chl-a stocks & fluxes • are significantly correlated • Weak relation overall, but stronger • by when grouped by season • Similar relationship among years • Total solids stocks and fluxes • are weakly correlated • Strong correlation between Chl-a • flux and solids flux • Strongly suggests that TSS flux is • controlled by plankton processes

7. Proportion of Sinking Flux as Lithogenic Particles • Fluxes of total solids & Chl-a • are strongly correlated • Because TSS & Chl-a sources • differ, suggests same controls • “Non-algal” solids dominate • total mass of sinking particles • Inorganic, non-algal particles • comprise 80% total mass • Non-algal fraction more variable • in summer

8. • Seasonal and interannual patterns of plankton Chl-a deposition follows plankton production and grazing cycles • Chl-a sinking can be predicted from Chl-a stocks, temperature, (season) and nutrient conditions (diatom cycles) • Sinking of inorganic solids can be predicted from Chl-a sinking rates and TSS stocks • WQ model simulations of algal and solids sinking should be compared to sediment trap data • Multivariate regression equations developed could be used to model sinking of both algae and inorganic solids • Need to consider possible regional variations in these processes Summary of Data Synthesis

9. Mesocosm Studies: Phytoplankton-TSS Interactions • Experiments using replicate 1 m3 MEERC mesocosms with controlled light, temperature and mixing • Simulate spring and summer bloom conditions, add clay to maintain background TSS • Manipulate nutrients to create bloom and crash of algal biomass • Test for evidence of algal processes regulating TSS levels & sinking rates

10. Chlorophyll, TSS, Light Experiments: Protocol #1 • Need to develop protocols for • many aspects of experiment • For example, delivering clay in • relation to mixing cycles • Once or twice daily? • Mixing cycle seems to have • greater impact of TSS levels • than does clay delivery, per se

11. Chlorophyll, TSS, Light Experiments: Protocol #1 • Use of sensor systems to provide continuous data for key variables • Very high chlorophyll-a levels because of growth medium added with algal cultures • Mixed algal assemblages; difficulties in establishing diatom dominance • Spiking data associated with spurious electrical signals; need to be filtered out

12. Chlorophyll, TSS, Light Experiments: Protocol #1 • Despite problems some interesting initial results • TSS levels seem to accumulate with algal bloom development • Algal levels are too high to tell; cells comprise too large a fraction of TSS to infer control • Need more controlled lower level algal bloom dominated by diatoms

13. #3: Clay #3: Nutrients #3: Clay + Nutrients Chlorophyll, TSS, Light Experiments: Protocol #3 • Two protocol experiments later, we are approaching a controlled system • Sensor systems well behaved, with filtration routines in place • Algal community composition controlled by manipulation Si:N ratio, temperature, mixing • Two replicated experiments planned for winter-spring 2006

14. Concluding Comments • Statistical relationships for modeling sinking rates of Chl-a and inorganic solids are nearly finished; available for WES model in couple of months • Optimistic about results of two mesocosm experiments planned for winter-spring of 2006; results used to test statistical models and to test idea of algal control of inorganic solid suspension in addition to sinking of solids • Unless we are told otherwise, we will continue to follow advice from a previous PI meeting and de-emphasize our proposed simulation modeling while increasing emphasis on producing data and statistical relationships useful for WES model