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Cullen Agouron 2007

Provided by the SeaWiFS Project, NASA/Goddard Space Flight Center and ORBIMAGE

Measurements and Models of Primary ProductivityMeasurements and Models of Primary Productivity

John J. Cullen

Department of Oceanography, Dalhousie University

Halifax, Nova Scotia, Canada B3H 4J1

Microbial Oceanography: Genomes to BiomesUniversity of Hawai‘i

June 28, 2007

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Cullen Agouron 2007

Outline

• What is marine primary productivity?• Ecological and biogeochemical significance• Scales of variability• Overview of measurements• The need for models• The nature of models• Their reliance on measurements• Hazards of forgetting the limitations of models

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Cullen Agouron 2007

What is marine primary productivity?

Net Primary Productivity (Production)

Net rate of synthesis of organic material from inorganic compounds such as CO2 and water

Chemosynthesis: chemical reducing power comes from reduced inorganic compounds such as H2S and NH3

Photosynthesis: reducing power comes from light energy

Photosynthetic primary production is usually measured and considered to dominate.

g C m-3 h-1 g C m-2 d-1

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Cullen Agouron 2007

Oxygenic Photosynthesis

€

CO 2 + 2H 2 O∗

~8hν ⏐ → ⏐ ⏐ (CH 2O) +H 2O +O∗

2

This process can be quantified by measuring the increase of oxygen, the decrease of CO2, or the increase of organic carbon. For practical reasons, oceanographers measure the incorporation of radioactive 14C into organic compounds; some label water with 18O (stable isotope) and measure its appearance in oxygen.

(Inferences can be made from 17O)

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Cullen Agouron 2007

Ecological and biogeochemical significance

Ecological and biogeochemical significance

marine.rutgers.edu/opp/This is estimated primary productivity

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Cullen Agouron 2007

The ocean accounts for half the The ocean accounts for half the photosynthesis on earth!photosynthesis on earth!

The ocean accounts for half the The ocean accounts for half the photosynthesis on earth!photosynthesis on earth!

marine.rutgers.edu/opp/This is estimated primary productivity

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Cullen Agouron 2007

…and the point is???

9-20600-100050-70Terrestrial

0.02-0.061-235-50Marine

Turnover Time (years)

Total Plant Biomass

(1015 grams)

Net Primary Productivity

(1015 grams/year)

Ecosystem

From Falkowski and Raven 1997 Table 1.1

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Cullen Agouron 2007

The Growth of Phytoplankton

Single Cell Doubled Biomass

DaughterCell

DaughterCellPhotosynthesis

Nutrient Uptake

Cell Division

Result: • More suspended particulate organic matter (food)

• Less dissolved inorganic nutrients (N, P, Si)• Less dissolved inorganic carbon (CO2) –(Oxygen is produced)

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Cullen Agouron 2007

What happens to the new growth?

DaughterCell

DaughterCell

Fates:

Accumulate (Bloom)

Be eaten

Sink

Lysis (blow up)Viruses

ApoptosisCell death site:www.uwm.edu/~berges/celldie/cldeth.htm

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Cullen Agouron 2007

Consumption and Decomposition(deep ocean)

MicrobialDecomposition

ConsumptionRespirationExcretion

Result: • Less suspended particulate organic matter

• More dissolved inorganic nutrients (N, P, Si)• Supersaturated dissolved inorganic carbon (CO2)• Oxygen is consumed

OrganicMatter Nutrients

CO2

DEEP-SEALIFE +

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Cullen Agouron 2007 from a slide by Dave Karl

CO2 is elevated in thedeep oceanbecause nutrients aredepleted at the surfaceand regenerated at depth

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Cullen Agouron 2007

CO2 + Nutrients Organic MatterCO2 + Nutrients Organic Mattersinking

particlesup

wel

ling

and

mix

ing

Bottom

€

106 CO 2 +122 H2O +16 HNO3 + H3PO4 ⏐ → ⏐ [(CH2O)106 +(NH3 )16 +H3PO4 ] +138 O2

Primary production

Decomposition

CO2 + Nutrients Organic MatterCO2 + Nutrients Organic Matter

106 CO2 +122 H2O+16 HNO3 +H3PO4 ← ⏐⏐ [(CH2O)106+(NH3)16+H3PO4 ]+138 O2

CO2

Organic C

Ocean Cycle of Life and Death

– At the Balance Point –

Cullen et al. 2007 – Oceanography Mag.

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Cullen Agouron 2007

Variability and disequilibrium structure food webs and biogeochemical cycles

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Cullen Agouron 2007

QuickTime™ and aSorenson Video 3 decompressorare needed to see this picture.

Scales of variability:Scales of variability:The co-occurrence of light and nutrients explainsThe co-occurrence of light and nutrients explains

patterns of primary productivity in the seapatterns of primary productivity in the sea

Scales of variability:Scales of variability:The co-occurrence of light and nutrients explainsThe co-occurrence of light and nutrients explains

patterns of primary productivity in the seapatterns of primary productivity in the sea

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Typical Structure of Chl and PP

Sikes - MS 320 - Rutgers

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Starting Point: The 14C method for measuring primary productivity

HOT website

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0

10

20

30

40

50

0 1 2 3 4 5D

epth

(m

)

Productivity (mgC m-3 d-1)

± s.e.

The 14C method for measuring primary productivity

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Cullen Agouron 2007

An incredibly useful tool for time series and process studies

HOT website

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Cullen Agouron 2007

Interaction of physiology and vertical mixing is a big twist

27.45

27.50

27.55

27.60

0.0

0.1

0.2

0.3

0.4

050

100150

Den

sity (

σt

)

Beam

c - c

w (m

-1 )

Dep

th (m

)

Denman, K. L., and A. E. Gargett (1983), Time and space scales of vertical mixing and advection of phytoplankton in the upper ocean, Limnol. Oceanogr., 28, 801-815.

Lewis, M. R., et al. (1984), Relationships between vertical mixing and photoadaptation of phytoplankton: similarity criteria, Mar. Ecol. Prog. Ser., 15, 141-149.

Cullen, J. J., and M. R. Lewis (1988), The kinetics of algal photoadaptation in the context of vertical mixing, J. Plankton Res., 10, 1039-1063.

Franks, P. J. S., and J. Marra (1994), A simple new formulation for phytoplankton photoresponse and an application in a wind-driven mixed-layer model, Marine Ecology Progress Series, 111, 145-153.

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Cullen Agouron 2007

Vertical mixing and temporal scales of measurements

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Cullen Agouron 2007

Ideally, the 14C method measures net primary productivity

0

10

20

30

40

50

0 1 2 3 4 5

Dep

th (

m)

Productivity (mgC m-3 d-1)

± s.e.

12 - 24 h incubations

Sometimes, it does

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Cullen Agouron 2007

The measurement is subject toartifacts and biases

0

10

20

30

40

50

0 1 2 3 4 5

Dep

th (

m)

Productivity (mgC m-3 d-1)

± s.e.

12 - 24 h incubations

Overestimation due to exclusion of UV-B

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Cullen Agouron 2007

The measurement is subject toartifacts and biases

0

10

20

30

40

50

0 1 2 3 4 5

Dep

th (

m)

Productivity (mgC m-3 d-1)

± s.e.

12 - 24 h incubations

Underestimation due to static incubation at excessive irradiance

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Cullen Agouron 2007

The measurement is subject toartifacts and biases

0

10

20

30

40

50

0 1 2 3 4 5

Dep

th (

m)

Productivity (mgC m-3 d-1)

± s.e.

12 - 24 h incubations

Underestimation due to dilution of intracellular DIC with respired cellular C

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Cullen Agouron 2007

The measurement is subject toartifacts and biases

0

10

20

30

40

50

0 1 2 3 4 5

Dep

th (

m)

Productivity (mgC m-3 d-1)

± s.e.

12 - 24 h incubations

Overestimation due to unnatural accumulation of biomass (disruption or exclusion of grazers)

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Cullen Agouron 2007

The measurement is subject toartifacts and biases

0

10

20

30

40

50

0 1 2 3 4 5

Dep

th (

m)

Productivity (mgC m-3 d-1)

± s.e.

12 - 24 h incubations

Underestimation due to food-web cycling

(microbial respiration and excretion)

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Cullen Agouron 2007

The measurement is subject toartifacts and biases

0

10

20

30

40

50

0 1 2 3 4 5

Dep

th (

m)

Productivity (mgC m-3 d-1)

12 - 24 h incubations

Overestimation due to inadequate time for respiration to be measured

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Cullen Agouron 2007

…and that’s not all:

0

10

20

30

40

50

0 1 2 3 4 5

Dep

th (

m)

Productivity (mgC m-3 d-1)

12 - 24 h incubations

Toxicity

Relief of iron limitation

Exposure to bright light

Disruption of fragile cells

for Simulated in situ:

Poor match of irradiance

Inappropriate temperature

Possible diel bias

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Cullen Agouron 2007

Productivity normalized to Chl is biased by:

0

10

20

30

40

50

0 1 2 3 4 5

Dep

th (

m)

Productivity (mgC m-3 d-1)

12 - 24 h incubations

Changes in Chl during incubations

Inadequate extraction of Chl by 90% acetone

Interference from Chl b(fluorometric acid-ratio method)

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Cullen Agouron 2007

and in general…

0

10

20

30

40

50

0 1 2 3 4 5

Dep

th (

m)

Productivity (mgC m-3 d-1)

12 - 24 h incubations

Irradiance is not controlled

Respiration is not accurately measured

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Cullen Agouron 2007

The measurement has its limitations

0

10

20

30

40

50

0 1 2 3 4 5

Dep

th (

m)

Productivity (mgC m-3 d-1)

± s.e.

Net production?

Gross production?

Overestimate?

Underestimate?

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Cullen Agouron 2007

But we use it routinely

0

10

20

30

40

50

0 1 2 3 4 5

Dep

th (

m)

Productivity (mgC m-3 d-1)

± s.e.

Water column integral is something like

net primary production

(photosynthesis less losses to respiration)

(extent depends on temperature, light and maybe nutrients)

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Cullen Agouron 2007

…and it has served us very well

Time Series

Karl et al. In the new Steemann Nielsen volume

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Cullen Agouron 2007

Process studies

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Cullen Agouron 2007

Direct Measurements will Never Provide Synoptic

Estimates of Productivity

marine.rutgers.edu/opp/

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Cullen Agouron 2007

Models are required for many applications

Productivity from ocean color

Ecological prediction

Biogeochemical models

Climate change scenarios

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Cullen Agouron 2007

Many share the same basic form

PB / PBmax

KP

AR

. z

0

1

2

3

4

5

6

0 0.5 1

Different

EPAR/Ek

see Talling, Ryther and Yentsch, Rhode, etc.

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Cullen Agouron 2007

Differences are relatively minor, butthey can matter

Behrenfeld and Falkowski 1997a L&O

Dependence on Irradiance

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Cullen Agouron 2007

One approach: model the measurements

Behrenfeld and Falkowski 1997a L&O

Op

tica

l De

pth

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Cullen Agouron 2007

Simplified functions describe major patterns

Behrenfeld and Falkowski 1997a L&O

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Cullen Agouron 2007

Is the measured/modeled pattern real?

0

20

40

60

80

100

0 10 20 30 40

Dep

th (

m)

PB (mg C mg Chl-1 d-1)

Measured near-surface inhibition

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Cullen Agouron 2007

Is the measured/modeled pattern real?

0

20

40

60

80

100

0 10 20 30 40

Dep

th (

m)

PB (mg C mg Chl-1 d-1)

or an artifact offixed-depthincubation?

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Cullen Agouron 2007

Measurements must be made on a shorter time scale

Photosynthetron: Controlled laboratory incubation (Lewis and Smith 1983)

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Cullen Agouron 2007

A comprehensive approach

Approach introduced by Jitts, H. R., A. Morel, and Y. Saijo. 1976. The relation of oceanic primary production to available photosynthetic irradiance. Aust. J. Mar. Freshwater Res. 27: 441-454.

Cullen, J. J., M. R. Lewis, C. O. Davis, and R. T. Barber. 1992. Photosynthetic characteristics and estimated growth rates indicate grazing is the proximate control of primary production in the equatorial Pacific. Journal of Geophysical Research 97: 639-654.

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Cullen Agouron 2007

0

10

20

30

40

50

0 0.08 0.2

Dep

th (

m)

Chlorophyll a (mg m-3)

0

10

20

30

40

50

0 0.4 0.8

Dep

th (

m)

Short-term measurements can detect near surface inhibition

0630 h: Chlorophyll and Pmax

are nearly uniform in the 50-m mixed layerMORNING

PBm . Chl (mg C m-3 h-1)

Principles described by Marra, Harris, Yentsch -- all prior to 1980

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Cullen Agouron 2007

0

10

20

30

40

50

0 0.08 0.2

Dep

th (

m)

Chlorophyll a (mg m-3)

0

10

20

30

40

50

0 0.4 0.8

Dep

th (

m)

PBm . Chl (mg C m-3 h-1)

1215 h: Chlorophyll and Potential Productivityare still nearly uniform in the 50-m mixed layer

Is measured near-surface inhibition real?

Assessment with short-term P vs E

MIDDAY

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Cullen Agouron 2007

0

10

20

30

40

50

0 0.08 0.2

Dep

th (

m)

Chlorophyll a (mg m-3)

0

10

20

30

40

50

0 0.4 0.8

Dep

th (

m)

Surface incubation led to artifact

1530 h: Fixed-depth incubations at the surfaceare “fried” — an artifact of sustained exposure35% underestimation of ML productivity

INCUBATED

PBm . Chl (mg C m-3 h-1)

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Cullen Agouron 2007

Conventional 14C:Near-surface inhibition is overestimated

Error at the surface: big

Error for integral: 8%

0

20

40

60

80

100

0 10 20 30 40

Dep

th (

m)

PB (mg C mg Chl-1 d-1)

Artifact

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Cullen Agouron 2007

Parameterizationof an Artifact?

Consequences for a model: minor except for irradiance dependence of P at higher daily irradiance

Behrenfeld and Falkowski Consumer’s Guide: L&O 1997

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Cullen Agouron 2007

But remember…Near-surface inhibition is also underestimated

Polycarbonate bottles exclude UV-B

(this refers to 14C incubations of 12 - 24 hours)

Dep

th (

m)

0

10

20

30

40

50

0 1 2 3 4 5

Productivity (gC gChl-1 h-1)

UV-BTransparent

That’s a different talk…

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Cullen Agouron 2007

Many models calculate P from measured relationships

FromPB vs E

and E vs depth

and Chl

todaily water column net

primary productivity

0

20

40

60

80

100

0 0.2 0.4 0.6 0.8 1

P (mg C m-3 d-1)

Dep

th (

m)

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Cullen Agouron 2007

Results can be generalized

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

PB / PBopt

Z /

Z1%

(PA

R)

€

PZ =Popt

B ⋅B

KPAR

⋅ f (EPAR (0)Ek

)

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Cullen Agouron 2007

Maximum PB is still a key parameter for most models

0

20

40

60

80

100

0 2 4 6 8 10

PB (g C g Chl-1 h-1) Z

(m

)

Even the spectral ones — even the quantum-yield models

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Cullen Agouron 2007

Compared to other measures, PBopt is

relatively insensitive to artifact

0

20

40

60

80

100

0 10 20 30 40D

epth

(m

)

PB (mg C mg Chl-1 d-1)

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Cullen Agouron 2007

Global assessment of primary productivity requires global assessment of maximum PB

Behrenfeld and Falkowski 1997b L&O

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Cullen Agouron 2007

PBopt modelled as a function of

temperature

Behrenfeld and Falkowski 1997b L&O

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Cullen Agouron 2007

Two commonly used functionsTwo commonly used functions

Behrenfeld and Falkowski 1997b L&O

0

2

4

6

8

10

0 5 10 15 20 25 30

Temperature (°C)

B & F VGPM

Eppley - type(e.g., Antoine et al 1996)

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Cullen Agouron 2007

You may have seen the figure

Behrenfeld and Falkowski 1997b L&O

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Cullen Agouron 2007

Here are the measurements

Rutgers OPP Study Data Base

0

5

10

15

20

25

30

35

40

0 5 10 15 20 25 30

Temperature (°C)

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Cullen Agouron 2007

Compared with more measurements

Texas Shelf

0

5

10

15

20

25

30

35

40

0 5 10 15 20 25 30

Temperature (•C)

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Cullen Agouron 2007

and more measurements!

0

5

10

15

20

25

30

35

40

0 5 10 15 20 25 30

Eppley Type ModelVGPMRutgers OPP DataTexas Shelf & SlopeHOTBATSEqPacArabian Sea JGOFSRoss Sea JGOFSAntarctic PFZ JGOFSPBmax Texas (SL)

Temperature (•C)

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Cullen Agouron 2007

General functions of T cannot capture major General functions of T cannot capture major causes of variability in water column productivitycauses of variability in water column productivity

± 2x error

-3

-2

-1

0

1

2

3

-5 0 5 10 15 20 25 30 35

Temperature (°C)

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Cullen Agouron 2007

Conclusion: General functions of T cannot capture major Conclusion: General functions of T cannot capture major causes of variability in water column productivitycauses of variability in water column productivity

Relative Error

QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

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Cullen Agouron 2007

We must appreciate the implicationsWe must appreciate the implicationsof this unexplained variabilityof this unexplained variability

QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

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Cullen Agouron 2007

Estimates like these (NPP) do not yetEstimates like these (NPP) do not yetaccount for variable physiologyaccount for variable physiology

beyond central tendenciesbeyond central tendencies

marine.rutgers.edu/opp/

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Cullen Agouron 2007

The need to compare models The need to compare models with measurementswith measurements

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Cullen Agouron 2007

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Cullen Agouron 2007

HOT data

Model

Measurements

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Cullen Agouron 2007

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Cullen Agouron 2007

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Cullen Agouron 2007

0

2

4

6

8

10

10 15 20 25 30

Equatorial Pacific – 140°W, 0° ± 2° – PB

opt

Measurements vs Behrenfeld et al. Models

PB

opt (gC gChl

-1 h

-1)

Temperature (°C)

VGPM Exponential Model

Revised according to insightsfrom Behrenfeld et al. Nature 2006

Real measurementsfrom JGOFS EqPac

Comparison with measurements is instructive

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Cullen Agouron 2007

It is also useful to remember the distinctionbetween models and observations

Follows et al. ModelVGPM model

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Cullen Agouron 2007

Many models cannot be directly verified

0

20

40

60

80

100

1200.4 0.5 0.6 0.7 0.8 0.9 1.0

Mixing Depth (m)

PT / P

Tpot

20, 40, 60min

Nomixing

8 h

4 h2 h

b

No one is immune!

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Cullen Agouron 2007

Conclusions• Models of primary productivity are a fundamental

requirement for describing and explaining ecosystem dynamics and biogeochemical cycling in the sea

• The models are based on measurements:– The measurements are not perfect– The models are not perfect

• Capabilities and limitations of models should always be considered when they are applied

• Effects of underlying assumptions• Comparison with real measurements when available

• Know your model!