measurements and models of primary productivity
TRANSCRIPT
Cullen C-MORE 2014
1Provided by the SeaWiFS Project, NASA/Goddard Space Flight Center and ORBIMAGE
Measurements and Models of Primary Productivity
Supported by NSERC including OTN
John J. Cullen !
Department of Oceanography, Dalhousie University Halifax, Nova Scotia, Canada B3H 4R2
!2014 C-MORE Summer Training Course
“Microbial Oceanography: Genomes to Biomes”
John Cullen: C-MORE 2013
Source of some reading
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http://www.ceotr.ca/publications/
for reading lists, [email protected]
MacIntyre and Cullen 2005
Parkhill et al. 2001
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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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More to it than that, of course
Doney, S. C.,et al. (2004), Frontiers in Ecology and the Environment, 2(9), 457-466.
John Cullen: C-MORE 2013
Biological oceanography and phytoplankton ecologyDescribe the causes and consequences of variations in
primary productivity (and food web structure)
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Ecological prediction!
Biogeochemical models!
Climate change scenarios
Why measure and model primary productivity?
Behrenfeld et al. Nature 2006
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Oxygenic Photosynthesis
This process can be quantified directly by measuring the increase of oxygen, the decrease of CO2, or the increase of organic carbon. Incubations can be conducted with 14C, 13C or H218O added as tracers.!!The process has many chemical consequences that can be traced with measurements of the concentrations of oxygen and carbon, and their isotopic signatures !!
Cullen C-MORE 2014Annual Review of Marine Science 2013
There are measurements and there are measurements…
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in vitro vs in situ
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In situ estimates need calibration
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Cullen, J.J., 2001. Plankton: Primary production methods. In J. Steele, S. Thorpe, K. Turekian (Eds.), Encyclopedia of Ocean Sciences (pp. 2277-2284): Academic Press.
Biological Oceanography (4): John Cullen
Effects of Light on PhotosynthesisNet Photosynthesis = Gross Photosynthesis - Respiration
Respiration is measured directly only in the dark. The light-dependent component is much harder to measure (18O-tracer can be used for that). 12
Biological Oceanography (4): John Cullen
Effects of Light on PhotosynthesisNet Photosynthesis = Gross Photosynthesis - Respiration
Net photosynthesis is negative when irradiance is below the compensation irradiance.13
Biological Oceanography (4): John Cullen
Relating oxygen evolution to carbon assimilation with the photosynthetic quotient
Note that more photosynthesis is required for growth on nitrate because the nitrate must be reduced.
1.0 NO3- + 5.7CO2 + 5.4H 2O! → ! (C5.7H9.8O2.3N) + 8.5 O2 +1.0 OH-
P.Q. = 1.49 (O2 evolved /CO2 consumed)
1.0 NH4+ + 5.7CO2 + 3.4H2O ! → ! (C5.7H9.8O2.3N) + 6.25 O2 +1.0 H+
P.Q. = 1.10
Generalized reactions for growth on nitrate and ammonium
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Inevitable comparisons with satellite-based estimates (models)
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What is behind this?
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Still a benchmark: The 14C method for measuring primary productivity
HOT website
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epth
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Productivity (mgC m-3 d-1)
± s.e.
The 14C method for measuring primary productivity
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An incredibly useful tool for time series and process studies
HOT website
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Ideally, the 14C method measures net primary productivity
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Productivity (mgC m-3 d-1)
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12 - 24 h incubations
Sometimes, it does
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The measurement is subject toartifacts and biases
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Dep
th (m
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Productivity (mgC m-3 d-1)
± s.e.
12 - 24 h incubations
Hypothesis: uncertainties inherent in the 14C method are being forgotten with important consequences for the estimation of primary productivity using other methods.
Cullen, J.J., 2001. Plankton: Primary production methods. In J. Steele, S. Thorpe, K. Turekian (Eds.), Encyclopedia of Ocean Sciences (pp. 2277-2284): Academic Press.
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The measurement is subject toartifacts and biases
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Dep
th (m
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Productivity (mgC m-3 d-1)
± s.e.
12 - 24 h incubations
Overestimation due to exclusion of UV-B
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The measurement is subject toartifacts and biases
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0 1 2 3 4 5
Dep
th (m
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Productivity (mgC m-3 d-1)
± s.e.
12 - 24 h incubations
Underestimation due to static incubation at excessive irradiance
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The measurement is subject toartifacts and biases
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0 1 2 3 4 5
Dep
th (m
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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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The measurement is subject toartifacts and biases
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Dep
th (m
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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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The measurement is subject toartifacts and biases
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Dep
th (m
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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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The measurement is subject toartifacts and biases
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Dep
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Productivity (mgC m-3 d-1)
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Overestimation due to inadequate time for respiration to be measured
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…and that’s not all:
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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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Productivity normalized to Chl is biased by:
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Dep
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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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and in general…
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Irradiance is not controlled!
Respiration is not accurately measured
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The measurement has its limitations
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Net production?
!Gross production?
!Overestimate?
!Underestimate?
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A less skeptical view
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But we use it routinely
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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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Regardless, it has served us very well
Time Series
Karl et al. in Williams et al. 2002
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Process studies
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Solving mysteries
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Equatorial Pacific – 140°W, 0° ± 2° – PBopt
Measurements vs Behrenfeld et al. Models"Mystery Solved"
PB opt (g
C gC
hl-1
h-1
)
Temperature (°C)
VGPM Exponential Model
Revised according to insightsfrom Behrenfeld et al. Nature 2006
Real measurementsfrom JGOFS EqPac
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Direct Measurements will Never Provide Synoptic Estimates of
Productivity
marine.rutgers.edu/opp/
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Continuous measures of optics reveal rates
see
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Ocean chemistry tells the tale — even in the most oligotrophic waters
3 years of O2 at POT: Ken Johnson
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Models are required for many applications
Productivity from ocean color!
Ecological prediction!
Biogeochemical models!
Climate change scenarios
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Photosynthesis normalized to chlorophyll is the foundation of productivity modeling
Pmaxchl ⋅ (1− exp −(α chl ⋅E)
Pmaxchl
$%&
'())
Pchl vs. E relationship! "##### $#####
Behrenfeld and Falkowski L&O 1997
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One approach: model the measurements
Behrenfeld and Falkowski 1997a L&O
! Opt
ical
Dep
th
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Simplified functions describe major patterns
Behrenfeld and Falkowski 1997a L&O
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Is the measured/modeled pattern real?
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Dep
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PB (mg C mg Chl-1 d-1)
Measured near-surface inhibition
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Is the measured/modeled pattern real?
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Dep
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PB (mg C mg Chl-1 d-1)
or an artifact of fixed-depth incubation?
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Measurements must be made on a shorter time scale
Photosynthetron: Controlled laboratory incubation (Lewis and Smith 1983)
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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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Chlorophyll a (mg m-3)
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Dep
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Short-term measurements can detect near surface inhibition
0630 h: Chlorophyll and Pmax are nearly uniform in the 50-m mixed layer
MORNING
PBm . Chl (mg C m-3 h-1)
Principles described by Marra, Harris, Yentsch -- all prior to 1980
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PBm . Chl (mg C m-3 h-1)
1215 h: Chlorophyll and Potential Productivity are 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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Surface incubation led to artifact
1530 h: Fixed-depth incubations at the surface are “fried” — an artifact of sustained exposure 35% underestimation of ML productivity
INCUBATED
PBm . Chl (mg C m-3 h-1)
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Conventional 14C: Near-surface inhibition is overestimated
Error at the surface: big
Error for integral: 8%
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Dep
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PB (mg C mg Chl-1 d-1)
Artifact
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Parameterization of an Artifact?
Consequences for a model: minor except for irradiance dependence of ΣP at higher daily irradiance
Behrenfeld and Falkowski Consumer’s Guide: L&O 1997
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Many models calculate P from measured relationships
From! ! PB vs E!
and ! E vs depth!
and ! ! Chl!
to! daily water column net primary productivity
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P (mg C m-3 d-1)
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Results can be generalized
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PB / PBopt
Z /
Z 1%(P
AR)
€
PZ =PoptB ⋅BKPAR
⋅ f (EPAR (0)Ek)
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Maximum PB is still a key parameter for most models
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0 2 4 6 8 10PB (g C g Chl-1 h-1)
Z (m
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Even the spectral ones — even the quantum-yield models
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Compared to other measures, PBopt is
relatively insensitive to artifact
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0 10 20 30 40D
epth
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PB (mg C mg Chl-1 d-1)
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Global assessment of primary productivity requires global assessment of maximum PB
Behrenfeld and Falkowski 1997b L&O
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PBopt modelled as a function of
temperature
Behrenfeld and Falkowski 1997b L&O
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Two commonly used functions
Behrenfeld and Falkowski 1997b L&O
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Max
imum
PB (g
C g
Chl-1
h-1
)
Temperature (°C)
B & F VGPM
Eppley - type(e.g., Antoine et al 1996)
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You may have seen the figure
Behrenfeld and Falkowski 1997b L&O
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Here are the measurements
Rutgers OPP Study Data Base
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Max
imum
PB (g
C g
Chl-1
h-1
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Temperature (°C)
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Compared with more measurements
Texas Shelf
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Max
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PB (g
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and more measurements!
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Eppley Type ModelVGPMRutgers OPP DataTexas Shelf & SlopeHOTBATSEqPacArabian Sea JGOFSRoss Sea JGOFSAntarctic PFZ JGOFSPBmax Texas (SL)
Max
imum
PB (g
C g
Chl-1
h-1
)
Temperature (•C)
The foundations of VGPM
Behrenfeld and Falkowski 1997 L&O Underlying data + a few more data sets
Published Statistical Fit Measurements (note scale)
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General functions of T cannot capture major causes of variability in water column productivity
± 2x error
-3
-2
-1
0
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-5 0 5 10 15 20 25 30 35
ln(m
easu
red/
mod
eled
)
Temperature (°C)
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Conclusion: General functions of T cannot capture major causes of variability in water column productivity
Relative Error
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We must appreciate the implicationsof this unexplained variability
Carbon cancels out!
…and implications of a carbon-based model that isn’t
!Times Cited: 353 (from Google Scholar, May 2014)
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How much confidence should we have?
Juranek and Quay 2013 Ann Rev Mar Sci
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Estimates like these (NPP) do not yet account for variable physiology beyond central tendencies
Behrenfeld et al. Nature 2006
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The need to compare models with measurements
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Validation is important
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Model
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Headline
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Published model result
Measurements!show the !
opposite trend
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Time Frame
& Statistics
Matter
Measurements
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Measurements !
(no headlines)
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It is also useful to remember the distinction between models and observations
Follows et al. ModelVGPM model
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Many models cannot be directly verified
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Mix
ing
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th (m
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PT / PTpot
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Nomixing
8 h4 h
2 h
b
No one is immune!
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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!