ASSESSING BIODIVERSITY OF PHYTOPLANKTON COMMUNITIES FROM OPTICAL REMOTE SENSING

ASSESSING BIODIVERSITY OF PHYTOPLANKTON COMMUNITIES FROM

OPTICAL REMOTE SENSING

Julia Uitz, Dariusz Stramski, and Rick A. ReynoldsScripps Institution of OceanographyUniversity of California San Diego

NASA Biodiversity Team Meeting – May 2010 – Washington DC

WHY STUDYING PHYTOPLANKTON DIVERSITY?

•Phytoplankton diversity influences many important biogeochemical processes▫Photosynthetic efficiency▫Fate of carbon fixed via photosynthesis▫Marine biological pump of carbon

•Key questions to be addressed▫Understanding of marine biogeochemical

cycles and modeling capabilities▫Distribution and variability on scales relevant

to environment and climate changes

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PROJECT OBJECTIVES AND STRATEGY

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OCEAN-COLOR BASED DISCRIMINATION OF DIFFERENT

PHYTOPLANKTON GROUPS•Satellite measurements of ocean color

▫Surface Chla concentration▫Quasi-global spatial scale▫Daily to decade

•New generation of algorithms for discriminating different phytoplankton groups from ocean color▫Dominance (Alvain et al. 2005)▫Surface Chla (Devred et al. 2006; Hirata et al.

2008)▫Vertical profile of Chla (Uitz et al. 2006)

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Conversion to CAbsorbed light energy

OCEAN COLOR-BASED PRIMARY PRODUCTION MODEL

P(t,z) = Chla(z,t) a*(z,t) PAR(z,t) Φc(z,t)

▫ P: Primary production (g C m-3 d-1)

▫ PAR: Irradiance available for photosynthesis (mol quanta m-2 s-1)

▫ Chla: Concentration of chlorophyll a (mg m-3)

▫ a*: Chla-specific absorption coefficient of phytoplankton [m2 (mg Chla)-1]

▫ Φc: Quantum yield of carbon fixation [mol C (mol quanta)-1]

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PRIMARY PRODUCTION AT THE PHYTOPLANTKON GROUP LEVEL

Ppg(t,z) = Chlapg(z,t) apg*(z,t) PAR(z,t) Φc,pg(z,t)

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Pmicro Pnano Ppico

3. Computation of group-specific primary production rates

(Uitz et al. GBC in press)

2. Bio-optical model of Morel (1991) + photophysiological properties of

Uitz et al. (2008)φmicro φnano φpico

Chlamicro Chlanano

1. Computation of Chla vertical profiles from surface Chla (Uitz et al.

2006)Chlapico

METHODOLOGY

Ppg(t,z) = Chlapg(z,t) apg*(z,t) PAR(z,t) Φc,pg(z,t)

(mg m-3)10-year time series of SeaWiFS

surface Chl (1997-2007)

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GLOBAL ANNUAL PRIMARY PRODUCTION

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CLIMATOLOGY OF MICROPHYTOPLANKTON PRODUCTION

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• Boreal winter/Austral summer(Dec-Jan-Feb)

• Boreal summer/Austral winter(Jun-Jul-Aug)

• Temp/subpolar latitudes in summer: high contribution (e.g. Atl Nord >50%)• Near-coastal upwelling systems: 70% (1 g C m-2 d-1)• South Pacific Subtropical Gyre: Minimum contribution (0.02 g C m-2 d-1)

CLIMATOLOGY OF PICOPHYTOPLANKTON PRODUCTION

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• Maximum contribution in oligotrophic subtropical gyres (40-45%)• Contribution reduced to ~15% at high latitudes

CLIMATOLOGY OF NANOPHYTOPLANKTON PRODUCTION

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• Substantial contribution on global scale: 0.07-1 g C m-2 d-1 (30-60%)• Can be found in extremely diverse environmental conditions (subtropical gyres vs. winter subantarctic waters Biodiversity? (see Liu et al. PNAS 2009)

CONCLUSIONS AND PERSPECTIVES

• First climatology of phytoplankton group-specific primary production on global scale over seasonal to interannual scales▫ Significant contribution to our ability to understand

and quantify marine carbon cycle with implications for carbon export

▫ Key elements required to calibrate/validate new biogeochemical models (e.g. Le Quéré et al. 2005)

▫ Benchmark for monitoring responses of marine pelagic ecosystems to climate change

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• Chla-based approaches▫ Describe general trends across various trophic regimes▫ But do not necessarily account for specific local conditions

• New complementary approaches need to be developed• Explore the potential of hyperspectral optical

measurement for discriminating different phytoplankton groups▫ Hyperspectral optical measurements have matured into

powerful technologies in the field of remote sensing▫ Yet remain largely unexplored for open ocean applications

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CONCLUSIONS AND PERSPECTIVES

HYPERSPECTRAL OPTICAL APPROACH

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Evaluation of performance

(Torecilla et al. in prep.)

• “Pilot” study• Small set of stations from Eastern Atlantic open ocean

▫ HPLC pigments▫ Optical data

• Encouraging results▫ Best classification with hyperspectral derivative spectra

• 2nd cruise in the Atlantic Ocean almost completed!

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HYPERSPECTRAL OPTICAL APPROACH

THANK YOU FOR YOUR ATTENTION

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ASSESSING BIODIVERSITY OF PHYTOPLANKTON COMMUNITIES FROM OPTICAL REMOTE SENSING

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