1. PHYTOPLANKTON GROWTH RATES AND CARBON BIOMASS FROM SPACE
Michael Behrenfeld, Emmanuel Boss, David Siegel, & Don Shea
Outline:
The ‘Carbon-based’ NPP Approach
Global Results
Focus: Subtropical Gyre
Patterns
Field Comparison
Productivity
Issues
Closing
References:
Behrenfeld, Boss, Siegel, Shea Global
Biogeochem. Cycles, 19, /2004GB002299
Winn, Campbell, Christian, Letelier, Hebel, Dore,
Fujieki, Karl Global Biogeochem. Cycles 9:
Behrenfeld, Boss Deep Sea Research.
50:
Behrenfeld, Prasil, Babin, Bruyant
J. Phycology. 40:4-25.
Garver, Siegel J. Geophys. Res. 102:
18,607-18,625.
NASA Ocean Biology and
Biogeochemistry Program

2. Carbon Approach: [Chlorophyll] = f [biomass, light, nutrients,…]
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
Particulate beam attenuation and particle backscattering
coefficients reflect changes in particle load
Remote sensing ‘inversion’ products: bbp, aph (cDOM)
thus a path to carbon biomass & growth rate from space
References:
Garver, Siegel J. Geophys. Res. 102:
18,607-18,625.

3. Laboratory Chl:C physiology 3 primary factors Light Temperature
Nutrients
Chl:Cmax
Dunaliella tertiolecta
20 oC
Replete nutrients
Exponential growth phase
Geider (1987) New Phytol. 106: 1-34
16 species
= Diatoms
= all other species
Laws & Bannister (1980)
Limnol. Oceanogr. 25:
Thalassiosira fluviatilis
= NO3 limited cultures
= NH4 limited cultures
= PO4 limited cultures
Chl:C (mg mg-1)
Chl:Cmin
Light (moles m-2 h-1)
Laboratory
Chl:Cmax
Temperature (oC)
Chl:Cmin
Low Nutrient stress High
Growth rate (div. d-1)

4. References: 28 Regional BinsNP SP SA NA CP SI NI CA SO L0 L1 L2 L3 L4
SO-all
Variance Level
Chlorophyll
excluded
28 Regional
Bins
References:
Behrenfeld, Boss, Siegel, Shea Global
Biogeochem. Cycles, 19, /2004GB002299

5. Laboratory Space References: Chl:C (mg mg-1) Chl:C (mg mg-1) Chl:Cmax
{median r2 = 0.85}
Chl:C (mg mg-1)
Chl:C (mg mg-1)
Light (moles photons m-2 h-1)
Laboratory
Space
Chl:Cmax
Chl:Cmax
Biogeochem. Cycles, 19, /2004GB002299
Behrenfeld, Boss, Siegel, Shea Global
References:
Temperature (oC)
Chl:Cmin
Chl:Cmin
Low Nutrient stress High
Low Nutrient stress High
Growth rate (div. d-1)
Temperature (oC)

6. max  f (nuts, temp)  g (light)
Relative frequency
Growth rate () =
max  f (nuts, temp)  g (light)
2 divisions d-1
Banse (1991)
1 – exp -3light
Chl:Csat
( Chl:CN,T-max ) Light
Boreal Summer
Boreal Winter
0.5
1.0
1.5
2.0
Growth rate (division d-1)
References:
Behrenfeld, Boss, Siegel, Shea Global
Biogeochem. Cycles, 19, /2004GB002299

7. Oligotrophic Oceans North Atlantic South Atlantic North Pacific
1998
1999
2000
2001
2002
Year
Chlorophyll Scaled Carbon
North Atlantic
Chl:C (right axis)
South Atlantic
North Pacific
South Pacific

8. North Pacific: HOT References: Year
Winn, Campbell, Christian, Letelier,
Hebel, Dore, Fujieki, Karl
Global Biogeochem. Cycles 9:
1998
1999
2000
2001
2002
Year

9. North Pacific & North Atlantic: 14C
HOT
Measured Pbopt
Measured cp:Chl ratio
BATS
Sequential Observation
References:
Behrenfeld, Boss Deep Sea Research. 50:

10. Primary Production …NPP = f [Carbon, Zeu, , g (I0)]… References:
Boreal Winter
Chlorophyll-based
Carbon-based
Boreal Summer
Net Primary Production (mg m-2)
1200
800
400
1500
…NPP = f [Carbon, Zeu, , g (I0)]…
References:
Behrenfeld, Boss, Siegel, Shea Global
Biogeochem. Cycles, 19, /2004GB002299

11. Net Primary Production (Pg C month-1)
1998
1999
2000
2001
2002
Year
North Atlantic
South Atlantic
Net Primary Production (Pg C month-1)
= Chlorophyll-based estimate (VGPM)
= Carbon-based estimate
North Pacific
South Pacific

12. North Pacific: HOT References: Winn, Campbell, Christian, Letelier,
Hebel, Dore, Fujieki, Karl
Global Biogeochem. Cycles 9:

13. DIRECTIONS
f (N,T): linear, zero intercept ‘Ek-independent’ variability**
PIC (e.g., coccoliths) cDOM vs pigment absorption (10 Pg y-1)
Particle size distributions
Species-dependent physiology
New Remote Sensing….
** References:
Behrenfeld, Prasil, Babin, Bruyant
J. Phycology. 40:4-25.

14. Growth Rates, Carbon Biomass,
& Ecosystem Models
THURSDAY
(SS26; 4:30 pm) Patrick Schultz et al. Investigating the balance between phytoplankton growth and loss from space
(SS25; 6:45 pm) Andy Jacobson et al. An inductive ocean ecology model based on satellite observations of phytoplankton carbon biomass.

15. BACKUP

16. 28 Regional Bins bbp (m-1) Chlorophyll (mg m-3)NP SP SA NA CP SI NI CA SO L0 L1 L2 L3 L4
SO-all
Variance Level
Chlorophyll
excluded
28 Regional
Bins
bbp (m-1)
Chlorophyll (mg m-3)
‘physiology domain’
‘biomass domain’
Intercept = bbp from
stable component
of the bacterial population
C = scalar  (bbp – intercept)
= 13,000  (bbp – )
Intercept = m-1
Stramski & Kiefer (1991) Prog.
Oceanogr. 28,
Cho & Azam (1990) Mar. Ecol.
Prog. Ser., 63,
Phytoplankton Carbon = 25 – 35% POC
Eppley et al. (1992) J. Geophys.
Res., 97,
DuRand et al. (2001) Deep-Sea
Res. II, 48,
Gundersen et al. (2001) Deep-Sea
Res. II 48,