Michael J. Behrenfeld Oregon State University

Transcription

1 Michael J. Behrenfeld Oregon State University

2 global > 15 o C Tidbits Based on Vertically Generalized Production Model (VGPM) Initial increase = 1,930 TgC/yr Subsequent decrease = 190 TgC/yr Global trends dominated by changes in permanently stratified ocean regions (ann. ave. SST < 15 o C)

3 High-latitude anomalies Chlorophyll anomaly NPP anomaly Year Year 07

4 +3 a Year but how good is the chlorophyll-to-npp conversion? Low Latitude SST Anomaly NPP NPP NPP Changes (%) SST Changes ( 0 C ) SST SST b c

5 The chlorophyll-approach problem Carbon fixed per unit chlorophyll Temperature

6 Physiology and Temperature Behrenfeld, M.J., K. Halsey, A. Milligan Proc. Royal Acad. Sci. B

7 A New Solution to an Old Problem Chlorophyll-based approach is a dead end The Carbon-based approach NPP = : H C Scattering coefficients covary with particle abundance Scattering coefficients covary with phytoplankton carbon Chlorophyll variations independent of C are an index of changing cellular pigmentation Chl:C can then be used as an index of the rate term Same satellite input, Different model of physiology path to carbon biomass & growth rate from space The problems with this approach are. 1. We don t measure phytoplankton C in the field 2. We rarely measure phytoplankton growth rates 3. Scattering is not a unique property of algae

8 Can optics yield physiology? D Beam attenuation is the most common measure of particle scattering in the field and its variability is dominated by changes in phytoplankton. S Does the ratio of attenuation:scattering provide information on physiology? Measured Physiology HOT * * Sequential Observation NABE BATS Optical Index of Phytoplankton C:Chl ratio April May June NABE Time Series

9 Optics and phytoplankton carbon Another approach is to look in areas that do not exhibit much variability in growth conditions

10 Optics and phytoplankton carbon The new inversion algorithms provide estimates of particulate backscatter coefficients, not beam attenuation According to Mie Theory, backscatter is dominated by particles less than 1 :m i.e., generally not phytoplankton. Can backscattering be used as an index of phytoplankton carbon? Yes #1: If the particle size spectrum slope is conserved

11 Optics and phytoplankton carbon Yes #2: If phytoplankton contribute more to backscatter than Mie predicts Dall Olmo et al (in prep)

12 Optics and phytoplankton carbon Tropical Pacific 2007 Beam Attenuation Particulate Backscatter Sequential Observation Dall Olmo et al (in prep)

13 Phytoplankton carbon from Space Chl:C (mg mg -1 ) Chl:C max Chl:C min 3 primary factors Light Dunaliella tertiolecta 20 o C Replete nutrients Exponential growth phase Light (moles m -2 h -1 ) Chl:C max Temperature ( o C) Temperature Geider (1987) New Phytol. 106: species = Diatoms = all other species Chl:C min Nutrients Laws & Bannister (1980) Limnol. Oceanogr. 25: Thalassiosira fluviatilis = NO 3 limited cultures Low Nutrient stress High Growth rate (div. d -1 ) = NH 4 limited cultures = PO 4 limited cultures

14 Phytoplankton carbon from Space L0 L1 L2 L3 L4 Chlorophyll Variance Level Chl:C Chl:C Chl:C (mg mg -1 min max ) Laboratory Space Light (moles photons m -2 h -1 ) Temperature ( o C) Chl:C (mg mg -1 ) Chl:C max Chl:C min SO-all Low Nutrient stress High Low Nutrient stress High Growth rate (div. d -1 ) Temperature ( o C)

15 Phytoplankton carbon from Space Westberry et al Global Biogeochem. Cycles (submitted)

16 The Northern Subarctic Current Explanation: North Atlantic deep winter mixing, slow growth rate, nutrient-charged surface layer ý spring stratification, diatom bloom, large grazers can t keep up (lifecycle issues) ý summer nitrate depletion bloom demise North Pacific shallower winter mixing, phytoplankton continue to grow, support microbial loop ý iron limitation of larger phytoplankton, microbial loop limitation of small phytoplankton, no spring/summer bloom Schultz et al (submitted)

17 The Northern Subarctic Schultz et al (submitted)

18 The Northern Subarctic Summer average (June, July, August) Schultz et al (submitted)

19 The Northern Subarctic Schultz et al (submitted)

20 The Northern Subarctic physiology, physiology, physiology Schultz et al (submitted)

21 The Northern Subarctic SERIES Iron Enrichment Experiment (subarctic north Pacific) Schultz et al (submitted)

22 From Chl & C to Primary Production Net Primary Production (NPP) = : H C phyto Growth rate (:) = f (nuts, temp) H g (light) Chl:Csat ( Chl:C N,T-max ) Light 1 exp -3light

23 From Chl & C to Primary Production Mixed layer NPP HOT Year Westberry et al Global Biogeochem. Cycles (submitted)

24 Chlorophyll Variance Level L0 L1 L2 L3 L4 NPP of the North Pacific Variance Level 0 Variance Level 1 Variance Level 2 Variance Level 3 Variance Level 4 SO-all Net Primary Production (Pg C month -1 ) = Carbon-based = Chlorophyll-based (VGPM)

25 Decomposing chlorophyll trends Click here if out of time

26 Heritage Ocean Color Sensors present present present

27 SWIR NIR Visible Ultraviolet 2 SWIR bands 5 nm resolution ( nm) 17 aggregate bands Key Few science products approaches limits on performance Measurement Quality Index potential science return Climate Data Record Quality Insufficient for Climate Data Record CZCS ( ) SeaWiFS ( ) Advanced Mission ( ) MODIS ( ) Desired Trajectory Current trajectory VIIRS ( ) * NOTE: MODIS Aqua climate-quality ocean biology data have only been achieved because SeaWiFS data were available for comparison Measurement Maturity Index no known use for measurement * measured operationally SWIR NIR Visible Extensive science products CZCS SeaWiFS MODIS VIIRS

28 The End Acknowledgements Patrick Schultz Toby Westberry Giorgio Dall Olmo Robert O Malley Allen Milligan Dave Siegel Emmanuel Boss Chuck McClain Jorge Sarmiento