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1
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 +
11
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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Cullen Agouron 2007
Typical Structure of Chl and PP
Sikes - MS 320 - Rutgers
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Cullen Agouron 2007
Starting Point: The 14C method for measuring primary productivity
HOT website
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Cullen Agouron 2007
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!