C-MORE Schofield Lecture 3

7/31/2019 C-MORE Schofield Lecture 3

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C-MORE 2012: Measuring phytoplankton productivity &biomass

Oscar Schofield


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Photosynthesis = PAR * * f

aph =

a(l )*Eo(l )dl400nm

700nm

Eo(l)d

l400nm

700nm

Spectrally averaged absorption

Energy that is into the cellVaries with cell pigmentation,

light history, and size

~ 1%

)()()(

dd

d EKdz

dE

0.00 0.20 0.40 0.60 0.80 1.00

Irradiance

0.00

20.00

40.00

60.00

80.00

100.00

Dep

th

(m

)

Scalar visible irradiance

Energy into the oceanVaries with depth according to the IOPsIOPs with radiative transfer eqns describe the AOPS

Efficiency of converting energy intoEnd product (electrons, oxygen, carVaries with end product and physiolo

Quantum efficiency of ..

High

Low

Absorption

Fluorescenceor chargeseparation

oxygen

carbonfixation

growth


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Enough energy make something new(rearrange a molecule)

Enough energy to excite(vibrate a molecule) Enough energy move electrons

Phytoplankton growth and nutrient assimilation is tied to ambient light levels.


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Every day, the ocean changes colour or rather, it passes though a varietyof hues between the morning, noon

and night of a single day. The subtleshapes of clouds, the glittering light

of the sun, and the shifts in

atmospheric pressure tint the seawith deep tones, cheerful tomes,

plaintive tones that would cause anypainter to pause in wonder.

from The Samurai by Shusaku Endo(1980)


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Eyeball Optics

The Secchi Disk:

First systematic usage reported in 1866, but

observed and remarked upon much earlier.

Early experiments carried out by Commander

Cialdi, head of the Papal Navy, and Professor

Secchi onboard the SS LImmacolata

Concezione (Cialdi, 1866).

Used operationally for establishing aids to

navigation over shallow water.Thanks to Marlon Lewis


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Eyeballs Watch Harmful Algal Blooms

HABs


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The underwater light field is not a collimated beam.

So we define another term(s), the diffuse attenuationcoefficient(s), K, to describe the penetration of light in

the sea. It is closely related to absorption.

~ 1%

Optical Properties of the Sea

)()()(

dd

d EKdz

dE

0.00 0.20 0.40 0.60 0.80 1.00

Irradiance

0.00

20.00

40.00

60.00

80.00

100.00

Dep

th(m

)


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From John T. O. Kirks billabongs

Measuring the light into the system


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Reflectance() = G* bb()/{bb() +a()}


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primary productivity

or export productivity

(Behrenfeld and Falkowski, 1997)

(Muller-Karger et al., 2005)

Wh t f th l i l DIMS?


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What are some of the classical DIMS?

laustre et al.

Diatoms Y 0.114 + 0.051Cryptophytes Y 0.053 + 0.011

Y* = P/(Qpar(0+))

Localweather

seasonal

Morel and Platt show Y* variabilityOf 50% around a value of at specific

chl values


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Penetration of light is determined by the material in the waterwhich is determined by the overall inherent optical properties (IOPs)

Absorption (a) color

Photos by S. Etheridge


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Scattering (b) clarity

a + b = c

c = attenuation

From Collin Roesler


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detector detector

Absorption (a)Attenuation (b)

WetLabs


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Scattering Case I waterscp(660) bp(660)

Loisel and Morel 1998Bp ChlAc )660(

Positively correlated Non-linear, B 0.7 High unexplainedvariance


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Particle backscattering

Cannizzaro et al. 2002

West Florida Shelf

Karenia brevisbloom

POC S i (C I )


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POC Scattering (Case I waters)

Loisel and Morel 1998

Bp POCAc )660(

B 1

Subtropical Pacific, North Atlantic

Contrast with non-linear

dependence on Chl

POC-Chl variationsare important


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E.m. radiation propagating as plane waves;g

geometric cross

section (its shadow )

EFFICIENCY FACTORS

Energy absorbed withinEnergy scattered out by..

Divided by

Energy impinging on g

Qa and Qb, respectively

From beautiful work of Morel, Bricaud, and Kirk


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(Finkel 2001)


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Durand et al. 2002


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Positivelycorrelated

Chl: 0.02 25mg m-3

(eutrophic,mesotrophic, and

oligotrophic

waters) Bricaud et al. 1995 Non-linear dependence

Thanks to Heidi Sosik


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Chl-specific phytoplankton

absorption Second-ordervariability in aph()

)(* )()( Bph ChlAa

Chl

aa

ph

ph

)()(*

A() and B()

statistically determined

This reflects effects of changing growth conditions andcommunity structure with trophic status

Note: unexplained variability

Negatively correlated


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Low light

High light


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Low light

High light

Photosyntheticpigments

Photo-protectivepigments

chlorophyte alga Haematococcus pluvialis


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0

5

10

15

20

400 450 500 550 600 650 700

Wavelength (nm)

SpectralIrr

adiance(

mW

cm-2nm-1)

chl a chl achl b

chl c

chl bcarotenoids

phycobilins

0

0.25

0.50

0.75

1.0

1.25

RelativeAbsorption

chl a-chl c-carotenoidschl a-chl b-carotenoids

chl a-phycobilins


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2 0 22 0 42 0 62 0 82 1 02 1 22 1 4

0

2

4

6

8

0

2

e

p

t

h

(

m

2 0 22 0 42 0 62 0 82 1 02 1 22 1 4

0

2

4

6

8

0

2

e

p

t

h

(

m

mo

lpho

tons

(m-2

s-1)

Dep

th(m)

Calendar DayB

mol photons m-2 s-1

C

Calendar Day

D

(m-1)pha

Dep

th(m)

0 22 0 42 0 62 0 82 1 02 1 22 1 4

500

1000

1500

2000

0400 450 500 550 600 650 700

0

0.3

0.6

0.9

1.2

surface

1m

2m

5m13m

Wavelength (nm)Calendar Day

A

. . . .

Oliver et al. 2004


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0.0

0.02

0.04

0.06

0.08

400 450 500 550 600 650 700

chl achl b

chl c

PSC

PPC

wavelength (nm)

absorptioncoefficient(m2m

g-1)

From Bidigare

Individual pigments can be measured on discrete samples biochemically


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0

20

40

60

80

1000 1 2 3

D

epth(m)

Relative pigment-specific

spectrally weighted absorption

B)

Decreasing efficiency Increasing efficiency

Chl a

Chl bPSCChl c

Wavelength (nm)

0.00001

0.0001

0.001

0.01

0.1

1

10

400 500 600 700Spectralirradiance(mWcm-2s-1)

1

25

90

Sun stimulated

fluorescence

A)


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Absorbed photon Charge stabilization &

photosynthesis

Heat

Fluorescence


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Chlorophyll a -Fate of photonsabsorbed by an isolated molecule

Diagram of energy states in chlorophyll and possible

transitions


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Alexander Graham Belldeveloped spectrophone,

essentially an ordinaryspectroscope equipped with

a hearing tube instead of aneyepiece listening to lightinduced changes in the

thermal sound.

Light Absorption

Heating

Thermal Expansion

PressureWave

Photoacousticsignal


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Weak light flash

Strong light flash


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photosynthesis

Heat

Fluorescence


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Fluorescence

Use of sun-induced chlorophyll


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Use of sun induced chlorophyllfluorescence to estimate the rate of

carbon fixation -Example

Stegmann et al. (1992)

JGR

Pacific


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Chloroph

yll

fluorescence

Chlorophyll concentration

Stress(light, nutrients)


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8:00 12:00 18:00 22:00

5

10

15

20

Local DaylightTime

0

Depth(m)

CDOM

8:00 12:00 18:00 22:00

5

10

15

20

0

D

epth(m)

Chl a

mixed

chromophyte

community

m

onospecific

G.breve

c

ommunity

Local DaylightTime


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0.00

0.25

0.50

0.75

5:00 9:00 13:00 17:00 21:00

0

400

800

1200

1600

PAR

molm-2

s-1)

Fv/Fm

EPS

Local Daylight Time

0

0.2

0.4

0.6

6:00 10:00 18:0014:00

Local Daylight Time

Fv/F

m

0

200

400

600

800Visible light downregulation

UVB

damage

PAR(

molm-2

s-1)

UVB + UVA + PAR

UVA + PAR

PAR

Ik>PARIk>PAR

Physiological response Environmental Stress

Falkowski et al. (1991) Nature


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Falkowski et al. (1991) Nature


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Fluorescence: The Basics

F0 = aph PARkf

kp +kf+kd

Fm = aph PARkf

kf+kd

Fv = aph PARkf

kp(Q)+kf+kd

Fm - F0

Fm=

kp

kp +kf+kd= f IIeo

time

Fluorescence

intens

ity

F0

Fm

Ft

Saturating flash

Fm

Other useful indices


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Time

Fluorescencerise

Integrated area isreflection of the absorption

cross-section

Flash is on RC2

Highlightcells

Lowlightcells

Photo-acclimation

Photons

Ot e use u d cesFLUORESCENCE INDUCTION

O


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0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800

Fluorescence

decaycons

tan

ts

Local time of day

Time

Other useful indicesFLOURESCENCE DECAY CONSTANTS

LightFlash

TurnedOff

Fluorescenc

e

RC

Pheo

Qa

Qb

PQ

D1

D2


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photosynthesis

Heat

Fluorescence


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Light Reactions produce ATP, NADPH2

Light

Transmission& light absorption

Light Reactions Dark Reactions

ATP& NADPH

CO2 sugars& carbos

Cellular Growth

Nitrogen,

Phosphorus,Metals

BiomassIncrease


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0

2

4

6

8

10

0.1 1 10 100 1000

0.4

0.5

0.6

0.7

0.8

Irradiance (mmol photons m-2 s-1)Prod

uctivity(mg

CmgChla-2h

-1)

0

0.02

0.04

0.06

0.08

0.1

CarbonQ

uantumYield

(molCmolphotonsabsorbed-1)

Fv/Fm

a

Pmax

Ik

fmax

Environmentalstress


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Production = Pmax. tanh(PAR/Ik)

Pmax

a

Ik = Pmax/a

PAR (mmol photons m-2 s-1)

oxygen

evo

lution

0

1

2

3

4

0 50 100 150 200 250 300


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fluorescence-based predictions of oxygen evolution

measuredoxyge

nevolution

0

1

2

3

4

5

6

0 1 2 3 4 5 6

R2=0.92, P


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From Jassby and Platt 1976

Is a cell a puddle or lake?


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Chl-specific alpha

0

20

40

60

80

100

0.02 0.03 0.04 0.05 0.06 0.07 0.08

aw a

light-limited

(mg C mg chl a-1 h-1[ mol photons m-2 s-1]-1)

depth(m

)

light-saturated


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Photosynthesis a chain of cascading reactions:

Each step sets the upper limit efficiency for each following step down the line

Fmpsii (0.65) > fm02 (on the order 0.125)>fmco2 (on the order 0.07)

For each use of energy go to one process, it is the expense of

another reaction, this impacts the overall efficiency

Nutrient source fmco2Ammonium 0.09Nitrate 0.07

Simplest expression for photosynthesis is

P = f * aph * PAR


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From Behrenfeld et al.

The conversion efficiency can varies between end products


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0

2

4

6

8

10

12

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5

Absorbed Quanta by phytoplankton

Light-saturated photosynthesis

Light-limitedphotosynthesis

Ra

tioo

fOxygen

toCar

bon

Quan

tum

Y

ields

The conversion efficiency can varies between end products

While chlorophyll specific absorption varies 3-4 foldt i ld b d f it d


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From Babin et al.

quantum yields vary by an order of magnitude

Even in 1980s was treated as a constant

NUTRIENT LIMITATIONS


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U O S

Iron-Ex

)Roug

h seas


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50 100 150 200 250 300 3500.005

0.025

0.045

0.065

0.085

0.105

0.125

1

2

3

45

6

7

8 9

10

11

12

13

14

1516

171819

20

21

22

23

New Jersey Coastal Region22 Southern California Bight21

NW Atlantic Continental Shelf (Spring)

20 Gulf Stream (Spring)19 NW Atlantic Subtropical Gyre (Spring)18 NE Atlantic Subtropical Gyre (Spring)17 Canary Islands (Spring)16 NW Atlantic Continental Shelf (Fall)15 Gulf Stream (Fall)14 NW Atlantic Subtropical Gyre (Fall)13 NE Atlantic Subtropical Gyre (Fall)12 Canary Islands (Fall)11 Antarctic (Palmer Station)10 Antarctic (Transitional Weddell Water)9 Antarctic (Bellingshausen Warm water)

8 Antarctic (Bellingshausen Cold water)7

Arabian Sea (NE Monsoon)

6

Arabian Sea (Inter Monsoon)

5

Arabian Sea (SW Monsoon)

4321

Antarctic (Bransfield-Bellingshausen water)Antarctic (Bransfield-Weddell water)Antarctic (Ice-Edge water)Antarctic (Weddell-Scotia Confluence waters)

23

Ek(PAR) (mol photons m-2 s-1)

max

(molCm

olphotonsabsorbed-1)

Oligotrohicseas

Types of satellite models


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Empirical: Purely a statistical fit. Earliest ones were simple regressionmodels of measured primary production against satellite derivedchlorophyll concentration. These models can explain a lot of the observed

variance; however assume that the fraction of productivity perphytoplankton cell is essentially fixed.

Early models were derived by Smith et al. (1982) and Eppley (1985) atScripps Visibility Labs and Food Chain Working Group


Ck = surface chlorophyll concentration, II or Pt = depth-integrated production

Smith & Baker 1978

Eppley et al. 1978



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Empirical: It works because, the amount of chlorophyll in a volume ofwater is proportional to the number of phytoplankton cells and the numberof photosynthetic reaction centers. In many ways it provides a goodOckams razor for the sophisticated productivity models.

Problems:

l These relationships assume that the conversion of light energy is constant (nottrue), that the light harvested for within and between phytoplankton is constant (nottrue).

l Chlorophyll is a concentration, productivity is a rate which has a time dependentvariable.

l Scales in which to apply the model?

Applying the razor: Back in early 1990s, many sophisticated bio-opticalproductivity were being developed. A global comparison of the models at thetime indicated that simple correlation models did as well or even sometimesbetter than more sophisticated and biologically realistic models. This did notsit well with some in the community.

Complexity can add uncertainty

The overcome the errors associated with the depth-dependent variabilityY t li t l i d id li d fil


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Platt and Sathyendranath, Science

You generate climatalogies and idealized profiles.

Ignoring the vertical behaviorcan lead to a 30% error

Remember the majority of

phytoplankton biomass is likelylight limited, so the importance

of the upper water column wherelight levels are high dominate

the integrated productivityestimates.


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Relative cloud cover Biogeographic provinces

Monthly weighted chl productivity

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