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Plankton Controls on Suspended Sediments and Water Clarity in Chesapeake Bay

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. •Investigate co-variations in water clarity, TSS and phyto-

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Plankton Controls on Suspended Sediments and Water Clarity in Chesapeake Bay

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  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

  2. •Investigate co-variations in water clarity, TSS and phyto- plankton chlorophyll-a •Relate water clarity to TSS and Chl-a concentrations and sinking rates •Relate Chl-a sinking to plankton production cycles •Relate TSS sinking to plankton Chl-a sinking for mid Bay •Test robustness of relationships among years and regions Objectives

  3. Conceptual Model of Processes • Plankton pigments and inorganic • particles contribute to attenuation • of PAR in water column • Concentrations of TSS & Chl-a • affect each other interactively • Plankton affect PAR attenuation • directly (absorption) & indirectly • (sinking rates) • •TSS sinking is affected by algal • excretion & flocculation • •Initially, flocs sink slowly because • of low density of amorphous mix • •Eventually, flocs sink faster due to • increase density and size

  4. Stokes Law of Settling ∆r = density difference (particle - fluid) g = gravitational acceleration d = diameter of particle µ = viscosity of fluid Particle Settling Velocity u = [∆r·g·d 2] (18µ)-1 Thus, particle sinking rate increases with particle density and diameter • Hypothesized plankton control on mineral particle sinking • Mucous excretion binds mineral particles into aggregates • Initial low-density (slow sinking) aggregates • Eventually, large dense (fast sinking) aggregates

  5. Example Diatom-Clay Aggregate SEM image (Hamm 2002)

  6. CB2.2 CB3.3c CB4.3c (Sed Traps) CB6.1 Adapted from www.chesapeakebay.net Monitoring Station Map

  7. Spring bloom May crash Fall bloom Summer peaks Time-Course Chl-a & TSS Stocks and 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

  8. Total Solids & Chl-a Fluxes vs. Stocks • Plankton Chl-a stocks and fluxes • are significantly correlated • Weak relation overall, but stronger • by when grouped by season • Similar relationship among years • Total solids stocks and fluxes • are significantly correlated • Weak relation overall, but stronger • by when grouped by season • Slope of relationship slightly • higher than for Chl-a

  9. Light Attenuation (Kd) & Secchi Depth (ZSD) • Fluxes of total solids & Chl-a • are strongly correlated • Correlations significant only • if fall-winter data excluded • 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

  10. Ratio Chl-a (Total Solids)-1 Variations • Ratio [µg Chl-a (mg TSS)-1] varies • along salinity gradient but is • remarkably consistent overall • Peak ratios in mesohaline • salinity zone (10-15) in summer • May imply that dynamics of TSS • and Chl-a are linked

  11. Light Attenuation & Total Suspended Solids • Diffuse PAR attenuation (Kd) • strongly correlated with TSS • Correlations significant only in • oligohaline & upper mesohaline • Slope & correlation coefficient • decline from upper to lower Bay • TSS range declines from upper • to lower Bay

  12. Light Attenuation & Plankton Chlorophyll-a • Diffuse PAR attenuation (Kd) • weakly correlated with Chl-a • Correlations significant only in • lower mesohaline & polyhaline • Slope & correlation coefficient • increase from upper to lower Bay • (note slope for CB6.1 is 0.016) • Pattern inverse of that for TSS • Implies TSS masking of Chl-a • effect on Kd

  13. • Seasonal and interannual patterns of plankton Chl-a deposition follows plankton production and grazing cycles • Patterns of TSS deposition follow Chl-a deposition cycles • Chl-a & TSS depositions are related to respective concentrations but relationships are weak and vary seasonally • Chl-a & TSS deposition rates are correlated significantly even though non-algal particles comprise 80% of total sinking mass • PAR attenuation controlled by TSS and Chl-a, but algal effects masked in much of the Bay by high TSS • Regional and interannual variations still need to be examined more closely Concluding Comments

  14. A) Statistical Analysis of Monitoring VFX data 1) Related water clarity, plankton, temp, sal and sedimentation. 2) Non-linear multivariate statistics (spatial, temporal aggreg.) General Study Design B) Mesocosm Experiments 1) Use existing facility (1 m3 tanks) 2) Manipulate nutrients, fine-grain particle density 3) Measure concentrations, sinking rates, water clarity C) Incorporate Algorithms into Simulation Models • Dynamic, spatially aggregated scenarios • Scenarios varying nutrient and sediment inputs • Transfer tested algorithms to WES model

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