1. Ecological Modeling: Algae -Why? - Who? - What? - How?

2. Who? Who?

3. What? What?

4. Examples of Models with Algal Modeling Included CIAO- Coupled Ice Atmosphere Ocean Model CIAO- Coupled Ice Atmosphere Ocean Model ERSEM- European Regional Seas Ecosystem Model ERSEM- European Regional Seas Ecosystem Model CE QUAL CE QUAL DSSAMt DSSAMt HSPF HSPF WASP WASP Aquatox Aquatox Ecosim Ecosim FFFMSIPaAG, FFFMSIPaAG, John’s Model, John’s Model, Don’s model Don’s model …………..Yada, Yada, Yada, …………..Yada, Yada, Yada,

5. What is typically modeled? - Phytoplankton - Periphyton

6. Pennate Diatoms

7. Centric Diatoms

8. Filamentous Green Algae

9. Chrysophyte

10. Cryptophyte

11. Dinoflagellates

12. Filamentous Cyanobacteria

13. Coccoid Cyanobacteria

14. Red Algae

15. Brown Algae

16. The point is that is…. it is a Diverse “Group” – –Size (pico, nano,micro) – –Physiologically – –Biochemically – –Life Histories – –And Therefore, Ecosystem Function!!

17. The How: Algal Population Growth Formula dA/dt =  max (T)A*MIN(NLIM)* LightLIM - grazing +/- advection/dispersion +/- settling Be a bit skeptical: ask can the equations capture “algal” physiologies and community dynamics that you are after?

18. uMax Usually set by Temperature: Usually set by Temperature: –Eppley 1972 (most common*) Other approaches Other approaches –species-genera specific temperature relationships – Multiple T opt, T max T min, fxns 0 1 2 3 4 5 6 7 010203040 Temperature ( o C)  max 0 1 2 3 4 5 6 7 010203040 Temperature ( o C)  max

19. Nutrient Limitation Monod kinetics Monod kinetics Usually applied as the single most limiting nutrient (Leibig’s “Law of The Minimum” improperly invoked). Usually applied as the single most limiting nutrient (Leibig’s “Law of The Minimum” improperly invoked). –Half saturation coefficients (ks) and nutrient concentrations are all that are needed.   =  max *(N/(K s +N)

20. Challenges: –How to set the K s. –What nutrient concentration to use: bulk or microscale? Half Saturation Constants Figure 1. Model formulation for velocity enhancement in DSSAMt (Caupp et al 1998). Figure 2. Predictions from biofilm theory using hypothetical model parameters.

21. Light Photosynthesis versus Irradiance Curves (PE curves) Photosynthesis versus Irradiance Curves (PE curves) –E k is needed. Challenges: Challenges: –How to calculate effective E. –How to set E k (remember….. plants/algae physiologically adapt). EkEkEkEk P max

22. Effective E: Effective E: –Typically Calculated by 1 st order attenuation accounting for water+ constituents –E d or E od, or E o ? –PAR, PUR, or PHAR?

23. Integrate over depth and time for applicable Dt. Integrate over depth and time for applicable Dt. WASP 6 manual

24. Note: dA/dt =  max(T)A*MIN(NLIM)* LightLIM This is “net primary production” Also, this is the “net cellular growth rate” Equation readily allows addition of other environmental constraints such as salinity, pH, etc….

25. Grazing Zero Order loss term/Constant Zero Order loss term/Constant First order loss term First order loss term Kinetics based on constant grazer biomass/abundance but accounts for monod kinetics Kinetics based on constant grazer biomass/abundance but accounts for monod kinetics Kinetics with grazer abundance predicted as well (Lotkka- Volterra, NPZ models) Kinetics with grazer abundance predicted as well (Lotkka- Volterra, NPZ models)

26. Other losses…. Settling? Settling? Mortality- Mortality- –Viral, fungal, Ecotox pollutants (e.g. phototoxins, LD 50 ’s) other..? Drift/scour (fxn velocity and biomass) Drift/scour (fxn velocity and biomass)

27. Algal Algorithms embedded in spatial models Algal Algorithms embedded in spatial models

28. Still Not Very Satisfying.... Uncertainties in Temperature and  max Uncertainties in Temperature and  max –can lead to large variations in accumulation rates and biomass.. (exponentially compounding uncertainty) Treatment of K s ’s and E k ’s as constants Treatment of K s ’s and E k ’s as constants Transient luxury uptake of nutrients rarely accounted for (e.g. Carbon storage and growth at night, i.e. “unbalanced” growth). Transient luxury uptake of nutrients rarely accounted for (e.g. Carbon storage and growth at night, i.e. “unbalanced” growth). Minimal Constraints on loss terms Minimal Constraints on loss terms Stability issues Stability issues

29. Other Approaches… More Empirical Relationships More Empirical Relationships –e.g. TP vs. Chlorophyll a Quantum Yield Approach Quantum Yield Approach –E o *A*  = Primary Production

30. Free stuff I (Heather/Laurel) will post Stella models I (Heather/Laurel) will post Stella models http://www.hps-inc.com/ http://www.hps-inc.com/ http://www.hps-inc.com/ Download isee Player (its free) Download isee Player (its free)

31. Background Readings Eppley 1972 Eppley 1972 Chapra pages 603-615 Chapra pages 603-615 Brush et al. 2002 Brush et al. 2002 Chapra 742-747 (Solar Radiation and light extinction sections) Chapra 742-747 (Solar Radiation and light extinction sections) WASP Manual WASP Manual Kirk: Light and Photosynthesis in the sea Kirk: Light and Photosynthesis in the sea Sverdrup: Conditions for phytoplankton blooms Sverdrup: Conditions for phytoplankton blooms