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MODELING PHYTOPLANKTON COMMUNITY STRUCTURE: PIGMENTS AND SCATTERING PROPERTIES Stephanie Dutkiewicz 1 Anna Hickman 2, Oliver Jahn 1, Watson Gregg 3, Mick.

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Presentation on theme: "MODELING PHYTOPLANKTON COMMUNITY STRUCTURE: PIGMENTS AND SCATTERING PROPERTIES Stephanie Dutkiewicz 1 Anna Hickman 2, Oliver Jahn 1, Watson Gregg 3, Mick."— Presentation transcript:

1 MODELING PHYTOPLANKTON COMMUNITY STRUCTURE: PIGMENTS AND SCATTERING PROPERTIES Stephanie Dutkiewicz 1 Anna Hickman 2, Oliver Jahn 1, Watson Gregg 3, Mick Follows 1 1. Massachusetts Institute of Technology 2. University of Essex 3. NASA Goddard Space Flight Center stephanie dutkiewicz http://ocean.mit.edu/~stephd

2 http://darwinproject.mit.edu modeling the marine ecosystem nutrients light many (100+) phytoplankton zooplankton detritus some sinks out to depths Darwin Project Model (Follows et al., Science 2007) PO4 NO3 Fe Si randomly assigned growth rates grazing rates

3 http://darwinproject.mit.edu modeling the marine ecosystem nutrients light phytoplankton zooplankton detritus some sinks out to depths PO4 NO3 Fe Si grazing rates randomly assigned growth rates Darwin Project Model (Follows et al., Science 2007) environment 1

4 http://darwinproject.mit.edu modeling the marine ecosystem Darwin Project Model (Follows et al., Science 2007) nutrients light phytoplankton zooplankton detritus some sinks out to depths PO4 NO3 Fe Si grazing rates environment 2 randomly assigned growth rates

5 http://darwinproject.mit.edu log10 (biomass) Initial Biomass of 100 phytoplankton types

6 http://darwinproject.mit.edu log10 (biomass) Annual Biomass after 10 years simulation

7 stephanie dutkiewicz http://ocean.mit.edu/~stephd EMERGENT COMMUNITY By putting in appropriate trait trade-offs, environment selects the appropriate community structure: -K versus r strategies (Dutkiewicz et al, GBC, 2009) - nitrogen fixing (Monteiro et al, GBC, 2010,2011) - nitrate assimilation ability (Bragg et al, PlosOne 2010) -size/grazing pressure (Ward et al. in prep) - pigments/absorption (Hickman et al, MEPS, 2010) Phytoplankton Functional Types

8 stephanie dutkiewicz http://ocean.mit.edu/~stephd EMERGENT COMMUNITY Phytoplankton Functional Types By putting in appropriate trait trade-offs, environment selects the appropriate community structure: -K versus r strategies (Dutkiewicz et al, GBC, 2009) - nitrogen fixing (Monteiro et al, GBC, 2010,2011) - nitrate assimilation ability (Bragg et al, PlosOne 2010) -size/grazing pressure (Ward et al. in prep) - pigments/absorption (Hickman et al, MEPS, 2010)

9 stephanie dutkiewicz http://ocean.mit.edu/~stephd (Data courtesy: M. Zubkov, J. Heywood) (Hickman et al, MEPS, 2010) AMT15 Vertical distribution of phytoplankton types OBSERVATIONS ONE DIMENSIONAL MODEL

10 stephanie dutkiewicz http://ocean.mit.edu/~stephd Pigments as trait Different pigment allow absorption of light at different wavebands wavelength (nm) Culture date from L. Moore, D. Suggett Absorption Spectra: Solid (PS specific); dashed (all pigments) ONE DIMENSIONAL MODEL (Hickman et al, MEPS, 2010)

11 stephanie dutkiewicz http://ocean.mit.edu/~stephd (Data courtesy: M. Zubkov, J. Heywood) (Hickman et al, MEPS, 2010) AMT15 Vertical distribution of phytoplankton types OBSERVATIONSMODEL ONE DIMENSIONAL MODEL

12 stephanie dutkiewicz http://ocean.mit.edu/~stephd more sophisticated treatment of light stream: - spectral surface input (OASIM – Watson Gregg) - radiative transfer code: 3 light streams (Iterative solver Oliver Jahn: following Aas, 1987; Ackelson et al 1994, Gregg and Casey, 2009) - resolve absorption, scattering and backscattering NEW DEVELOPMENTS

13 450475500600625650675 a( λ ), b( λ ), b b ( λ ) 525550575700400425 CDOM water a w ( λ ), b w ( λ ), b bw ( λ ) a CDOM ( λ ) a p (λ), b p (λ), b bp ( λ ) detritus a d ( λ ), b d (λ), b bd (λ) Phytoplankton: diatoms coccolithophores large Eukaryotes pico-eukaryotes Synechococcus Prochloroccus Trichodesmium DEVELOPMENTS: RADIATIVE TRANSFER In collaboration with Anna Hickman, Oliver Jahn, Watson Gregg Slide modified from Watson Gregg explicit explicit, under development function of Chl

14 stephanie dutkiewicz http://ocean.mit.edu/~stephd NEW DEVELOPMENTS ADDITIONAL FUNCTONAL TYPES Absorption data from L. Moore, D. Suggett In collaboration with Anna Hickman, Oliver Jahn, Watson Gregg Scattering data from Gregg+Casey, 2009; Morel et al 1993

15 stephanie dutkiewicz http://ocean.mit.edu/~stephd NEW DEVELOPMENTS Model Output: upwelling radiance water leaving radiance backscattering (total, detrital, phytoplankton) absorption (total, CDOM, phytoplankton) forward scattering pigments 450nm 500nm 550nm UPWELLING RADIANCE: July

16 stephanie dutkiewicz http://ocean.mit.edu/~stephd JULY log10 phytoplankon biomass (uMP) log10 backscatter by phytoplankon sum b phym (1/m) Coccolithophore fraction biomass NEW DEVELOPMENTS: PRELIMINARY RESULTS 450nm

17 stephanie dutkiewicz http://ocean.mit.edu/~stephd Remote sensing beginning to resolve aspects of phytoplankton community and functionality: e.g. PHYSAT (Alvain et al), PHYTODAS (Bracher et al), Aiken et al, Sathyendranath et al, Balch et al, Hirata et al, Uitz et al, Giotti+Bricaud, Mouw+Yoder, Kostadinov et al, etc Models also resolving community structure: By resolving optical properties of model ocean can we relate more to the remotely sensed products?

18 stephanie dutkiewicz http://ocean.mit.edu/~stephd SUMMARY We are currently working to include radiative transfer code (spectral) and explicit absorption and backscattering. - will provide a closer link with satellite (and other optical) studies - additional remote sensed products could be used to validate model - potential for data assimilation - model may then help untangle the mechanisms leading to variability and trend observed in satellite products

19 stephanie dutkiewicz http://ocean.mit.edu/~stephd MODELS HELP WITH OBS DESIGN Correlation between model variables Bennington, McKinley, Dutkiewicz, Ullman; GBC, 2009 - pCO2 well correlated with bloom - but year integrated CO2 Flux is not well correlated with biological variability in subpolar

20 stephanie dutkiewicz http://ocean.mit.edu/~stephd MODELS HELP WITH OBS DESIGN Number of years for trend to be visible from natural variability Henson et al, BG, 2010 - 3 models 2000-2100 A2 scenario - average of about 40 years of continuous and consistent measurements needed

21 stephanie dutkiewicz http://ocean.mit.edu/~stephd

22 O2O2 air sea EdEd EsEs (1 -  ) EdEd EsEs EuEu  E d, E s LwLw OASIM: Ocean-Atmosphere Spectral Irradiance Model DEVELOPMENTS: RADIATIVE TRANSFER MODEL Gregg and Casey, 2009 E d = direct irradiance E s = diffuse downwelling E u = upwelling radiance ρ = surface reflectance L w = water leaving radiance CO 2 W V aerosols O3O3

23 Three-Stream Ocean Irradiance Module following Aas(1987), Ackleson et al (1994), Gregg and Casey (2009) Oliver Jahn Iterative solver (repeated down/up integration)

24 Gregg's truncation (downward integration only) Downward decaying modes only (à la Aas) Iterative solver (repeated down/up integration) RADTRANS: approximations EdEd EsEs EuEu EsEs EuEu EdEd EuEu EsEs EdEd LwLw I I Oliver Jahn


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