etude de la dissolution de la silice biogénique des agrégats. utilisation dans la reconstruction...

Etude de la dissolution de la silice biogénique des agrégats.

Utilisation dans la reconstruction des flux de sédimentation de la silice

biogénique et du carbone dans la colonne d’eau.

Brivaëla MORICEAU

Supervised by Olivier RAGUENEAU

Introduction

Carbon cycleIntroduction

Deforestation

Combustion

Before the industrial era

The carbon cycle was balanced

Then: intense human activity

Increase of C in the

atmosphere (Berner and Berner 1996, Kump et al. 1999)www.ggl.ulaval.ca/personnel/bourque/s3/cycles.biogeochimiques.html

Atmosphere

Lithosphere

Photosynthesis Respiration

AbsorptionRespiration

Limestone and silicate alteration

Precipitation

Volcanicity

Buried

Biosphere

Hydrosphere

770 GtC

610 GtC

39 000 GtC

55 000 000 GtC

Introduction

Role of the ocean in the carbon cycle

SourcesSinks

Carbon exchanges

TSurface exchange

Physical

pHalcalinity

Chemical

Photosynthesis

Respiration

Biological

The global ocean retards the increase of carbon in the atmosphere

"Les Humeurs de l'Océan" magazine Pour la Science, 1998

Diatoms

Introduction

Biological pump of carbon

40-45% of the PP (Mann 1999)

aggregates and fecal pellets (Turner, 2002; Thornton 2002)

Basis of an efficient food web (Silver et al., 1978)

Important role of diatoms in the biological

pump of carbon

Diatoms

awi-potsdam.de/Carbon/calcif-d.html

Si + C

Influence of Influence of aggregation on aggregation on biogenic silica biogenic silica

(BSiO(BSiO22) ) dissolution? dissolution?

DSi

Si + C

Preservation

Mesopelagic zone

50%

DSi?

Depth of BSiODepth of BSiO22 recycling?recycling? Deep ocean

Euphotic zone

0 m

100 m

1000 m

several months

several years

10-100 years

Geological time scale

Organic carbon fluxes

ORFOIS

Dissolution parameters of

BSiO2

Parameterisation of global models

+ sedimentation rates of the sinking particles

Reconstruction of BSiO2 fluxes

Theoretical water column


In situ

Laboratory experiments

Mechanistic model

Impact of aggregation on

BSiO2 dissolution?

Impact of aggregation on the depth of the

BSiO2 recycling?

Role of diatoms in the Biological pump?

(Si/C)z = (Si/C)0 z0.41

Aggregate

Data base sediment trap

Framework of the PhD

Ragueneau et al. 2002

Which processes are

involved?

Validity of the experimental

measurements?

Semi-mechanistic model

Mechanistic model

AWI Bremerhaven Uta Passow and Michael Garvey



the BSiO2


Reconstruction of the BSiO2 fluxes

Theoritical water column

Reconstruction of the BSiO2 fluxes

In situ


Mecanistic model

Impact of aggregation on BSiO2

dissolution?

Impact of aggregation on the depth of the BSiO2 recycling?


(Si/C)z = (Si/C)0 z0.41

Aggregate



Which processes are involved?

Validity of the experimental measurements?

Impact of aggregation on

BSiO2 dissolution?

2- Cohesion- TEP (Transparent Exopolymer Particles)

1- Collision- High cell density

- Differential sinking velocity

GLUE

How to make aggregates?

Measurement of the BSiO2 dissolution rate in aggregate: methods

Shanks and Edmondson 1989

12

Skeletonema costatum

3

Chaetoceros decipiens

Talassiosira weissflogii

Settling during 24-48 h

Step 2

4ℓ 1ℓ

Aggregate treatment

Free cell treatment

Step 1

Dissolution

13°C Dark

13°C Dark

roller table

Incubation without

aggregation

13°C Dark

shaker table

Manual transfer of aggregates into artificial seawater (no nutrients)

11

Cell poor medium

artificial seawater (no nutrients)

13°C Dark

shaker table

22

Experiments Measurement of the BSiO2 dissolution rate in aggregate: methods

aggregation

Dissolution Experiment

• BSiO2 • TEP

100 Aggregates

Free cells

Parallel measurements

Parameters that could possibly influence the BSiO2 dissolution

BSiO2 dissolution rate :

Si(OH)4 = f(t) Initial dissolution rate (Greenwood 2001)

Measurement of the BSiO2 dissolution rate in aggregate: methods

• number of bacteria • diatom viability

0

5

10

15

20

25

30

35

40

45

50

0 50 100 150 200 250 300time h

DS

i µM

aggregates 7a

aggregates 7b

Free cells

Moriceau et al. in revision

0

0.02

0.04

0.06

0.08

0.1

0.12

Thalassiosiraweissflogii

Chaetocerosdecipiens

Skeletonemacostatum

Average

BS

iO2

initi

al d

isso

lutio

n ra

te d

-1

freely suspended cells

aggregates

5

1

3

2 2

5

513

13 experiments on aggregates

5 experiments on freely suspended

diatoms3 diatom species

Statistical t-testSignificant decrease of the BSiO2 dissolution

rate

x 20.054 d-1

0.026 d-1

Measurement of the BSiO2 dissolution rate in aggregate: results and discussion

From Moriceau et al., in revision

0

10

20

30

40

50

0 200 400 600

time (hours)

% v

iab

ility

(1) The viability of the cells

Free cells

aggregates

Which parameters could provoke a decrease of the BSiO2 dissolution rate?


Nelson et co-workers (1976)

Evolution of the diatoms viability

coupled0%

10%20%30%40%50%60%70%80%90%

100%

0 200 400 600

time h

% o

f dis

solv

ed

BS

iO2

µM

dissolution experiment on T.

weissflogii

aggregates

Free cells

Number of cells alive Total number of cells

RBSiO2 for cells alive ~ 0Viability could explain the decrease of the BSiO2

dissolution rate in aggregates

Moriceau et al., in revision

From Moriceau et al. in revision

Organic coating

BSiO2

Internal organic matter

(2) Bacteria number

Patrick and Holding (1985)

Bidle and Azam (1999)

Role of bacteria in the BSiO2 dissolution

Measurement of the bacterial number / diatom cell

No possible differentiation between attached and free bacteria

BUT

Bacteria/diatom

0

20

40

60

80

100

120

140

Aggregate free cellsThe number of bacteria per diatom could explain

the decrease of the BSiO2 dissolution rate in

aggregates


(3) DSi concentration

outside aggregates: 5 to 40 µM

inside aggregates: 80 to 250 µM

Van Cappellen and Qiu, 1997b

Solubility of BSiO2 between 4°C and 25°C: 500 - 1800µM (Hurd

and Teyer 1975, Kamatani and Riley 1979, Van Cappellen and Qiu 1997a,b)

Brzezinski and co-workers 1997

DSi inside natural aggregates: 300 µM

DSi inside aggregates could explain the

decrease of the BSiO2 dissolution rate in

aggregates

DSi concentrations in the ocean = 0-200µM and average 70µM (NODC, www.nodc.noaa.gov/OC5/WOA01F) (Tréguer et al., 1995)


http://www.nodc.noaa.gov/OC5/WOA01F

DSi

time

BSiO2 or DSi Concentration

Solubility (1200µM at 13°C)

Dissolution rate measured = Dissolution Diffusion+

DSi

Aggregate

3 phases

Free cell

2 phases

Decrease Decrease

0

0.02

0.04

0.06

0.08

0.1

Average

BS

iO2

dis

solu

tion

ra

te d

-1

free cells

aggregates

MODEL

Experimental measurement of the BSiO2 dissolution rate


University of Utrecht Philippe Van Cappellen and Goulven Laruelle



BSiO2





In situ


Mecanistic model


dissolution?



(Si/C)z = (Si/C)0 z0.41

Aggregate Data base

sediment trap




Modelling the BSiO2 dissolution in an

aggregate

RBSiO2 = Kdis f(viability,DSiagg)

2²²

1BSiO

aggeff

agg Rr

DSiDr

rrt

DSi

reteff fDD

Modelling an aggregateAggregate = sphere

Modelling an aggregate: model description

r

DSi

Decrease of the DSi diffusion solely

Decrease of the DSi diffusion + BSiO2 dissolution

DissolutionDiffusion

Viability = 0 no cell alive

RBSiO2 DSiagg = DSiext

Decrease of the BSiO2 dissolution solely

?

Moriceau et al. to be submitted a

Model Output

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

0 100 200 300time h

DS

i ex

t µ

M

S.costatum aggregates 7a

S.costatum aggregates 7b

Internal DSi concenration External DSi concentration

Modelling an aggregate: model description

DSiagg(r = ragg) = DSiext

RBSiO2 viability = 0 ; DSiagg = DSiext

0 0.1

0.20.3

0.4

0

100

200

3000

50

100

150

distance x (cm)time t (hours)

DS

iag

g µ

mo

l L-1

0.4

Freely suspended cells :10 nmol g-1BSiO2 s-1

Decrease of the dissolution rate Decrease of the DSi

diffusion

Moriceau et al. to be submitted a

kdis = 4 nmol g-1BSiO2 s-1 and fret = 150

kdis = 5 nmol g-1BSiO2 s-1 and fret = 125

WHY?

Modelling an aggregate: Diffusion

R2 = 0.7758

0

5000

10000

15000

20000

25000

0 5 10 15Kdis nmolSi s

-1 g-1BSiO2

TE

P µ

g X

eq l-1TEP

Complex composition

Chemical binding

Geometry of the aggregate Dachs and Bayona 1998

Decrease of the diffusion of O2 from

the outside to the inside of the aggregate

DSi

fret = 150 realistic ??

Brzezinski et al. 1997 fret = 20-200Calculation using Fick’s Law fret = 33-600

YES

Moriceau et al. in revision

n

eq

aggviableBSiOdisBSiO DSi

DSifMWBSiOkR

1110

1 622

2

BSiO2 dissolution rate inside an aggregate

Dissolution coefficient

Solubility of the BSiO2

Porosity of an aggregate

Molecular weight of the BSiO2

Number of living cells Total number of cells

BSiO2 concentration

DSi concentration

Modelling an aggregate: decrease of the BSiO2 dissolution

2- RBSiO2 varies with the DSi concentration inside the aggregate

3- RBSiO2 varies with the DSi concentration inside the aggregate and depends on the viability of the aggregated cells

Impact of the high DSiagg and

of the high viability of the aggregated cells

fviable = 0

n

eq

aggviableBSiOdisBSiO DSi

DSifMWBSiOkR

1110

1 622

2

variable

m = 0.5-2

variablefviable = 0.4

0

2

4

6

8

10

12

aggregate free cell

Kd

is n

mo

l g-1

BS

iO2 s

-1

undersaturationdegree

apparent rate

0

2

4

6

8

10

12

aggregate free cell

kd

is n

mo

l g-1

BS

iO2 s

-1

viability

undersaturationdegree

apparent rate

1- DSi concentration inside the aggregate

Kdis = 6 nmol g-1BSiO2 s-1

and fret = 150

2- viability of the cells inside the aggregate

Kdis = 8-10 nmol g-1BSiO2 s-1

and fret = 200-150

Modelling an aggregate: decrease of the BSiO2 dissolution rate

33-66 % of the decrease of the BSiO2 dissolution rate is explained by the viability

16-33 % of the decrease of the BSiO2 dissolution rate is explained by

the high DSi concentration inside the aggregate

From Moriceau et al. to be submitted a




BSiO2





In situ


Mecanistic model


dissolution?



(Si/C)z = (Si/C)0 z0.41

Aggregate





Return to the LEMAR Olivier RAGUENEAU


0

1000

2000

3000

4000

5000

6000

0% 50% 100%%BSiO2

de

pth

mImpact of the decrease of the

BSiO2 dissolution rate in aggregates

Aggregates s = 100 m d-1

R = 0.026 d-1

Freely suspended cells s = 1 m d-1 Smayda 1970 R = 0.054 d-1 Measured in this study for FC

Aggregates s = 100 m d-1 Alldredge and Gotschalk 1988

R = 0.054 d-1 Measured in this study for FC

25% 50%

BSiO2 flux in the water column: methods

Implication for paleoceanography

Implication for primary productionAggregates form the majority of

the sedimentation flux s

Important impact of the decrease of the BSiO2

dissolution rate in aggregates

Alldredge and Gotschalk 1988

Measured in this study for aggregate

From Turner 2002

Composition of the sedimentation flux


0

100

200

300

400

500

600

700

800

900

1000

0% 20% 40% 60% 80% 100%

%BSiO2d

epth

m

free cells

aggregates

feaces

Large free cells

total flux

Ragueneau et al., to be submitted

2 groups of particles to reconstruct the BSiO2 fluxes:

Large particles (LP)

Free cells (FC)

Which sites? Our reconstruction implies a known BSiO2 production


Weight % BSiO2 in sediments : 8000 data pointsAnnual BSiO2 and Corg fluxes in the water column: 200 data points

PAP

SACCAPFPNACC POOZ

APFA

BATS

OSP

EqPac

Reasonable estimates of annual BSiO2 production : 9 data points

SINOPS www.Pangaea.de

Moriceau et al., to be submitted b

0

500

1000

1500

2000

2500

3000

3500

4000

4500

0% 50% 100%%BSiO2

De

pth

m

model % BSiO2

APFP BSiO2 0

1000

2000

3000

4000

5000

6000

0% 50% 100%

%BSiO2 D

epth

m

model % BSiO2

SACC

0

1000

2000

3000

4000

5000

6000

0% 50% 100%%BSiO2

De

pth

m model %BSiO2

OSP

Model output

Kdis fixed

BSiO2 flux in the water column: results and discussion

18%700large

particles

82%5free cell

% BSiO2

S m d-1

36%60large

particles

64%2free cell

% BSiO2

S m d-1

41%700large

particles

59%0.5free cell

% BSiO2

S m d-1

s consistent with the literature

Kdis can be used in models

Repartition can be obtained from the model not from in situ

measurements

Moriceau et al., to be submitted bMoriceau et al., to be submitted b

PAP

SACCAPFP

NACC POOZAPFA

BATSOSP

EqPac

0

1000

2000

3000

4000

5000

0% 50% 100%

%BSiO2

De

pth

m POOZSFC=5SFC=2SFC=1SFC=0.5SFC=0.1

FC sinking rate

Moriceau et al., to be submitted

LP sinking rate

0

1000

2000

3000

4000

5000

0% 50% 100%

%BSiO2

De

pth

m

POOZ

SLP=45

SLP=65

SLP=100

SLP=200

SLP=500

repartition of the BSiO2

0

1000

2000

3000

4000

5000

0% 50% 100%% BSiO2

De

pth

m

POOZ75%FC 25%LP72%FC 28%LP65%FC 35%LP55%FC 45%LP60%FC 40%LP


Sensibility tests

Robustness of the model

BSiO2 flux in the water column: results


PAP

SACCAPFP

NACC POOZAPFA

BATSOSP

EqPac

With the same BSiO2 Production rate

Different ratios of BSiO2 preserved in sediments

Importance of particle dynamics

POOZNACC

APFA

EqPac

OSP

BATSAPFP

SACC

PAP

0%

10%

20%

30%

40%

50%

0 200 400 600 800

WML

% B

SiO

2 in

teg

rate

d t

o L

P

y = 0.7091x + 0.0099

R2 = 0.7106

0%

10%

20%

30%

40%

50%

0% 10% 20% 30% 40% 50%

%of the BSiO2 production integrated to LP

%B

SiO

2 a

t th

e s

ea

floo

r

• Sedimentation flux intensity depends on the ability of cells to enter into large particles

• Recycling or DSi availability depends on the amount of cells that can stay freely suspended

Sedimentation flux

Particle dynamics

winter mixed layer = 200 m

maximum amount of BSiO2 integrated into large

particles

BSiO2 flux in the water column: results

Moriceau et al., to be submitted bMoriceau et al., to be submitted b

Role of the diatoms in the biological pump?

Still in the LEMAR Still working with Olivier RAGUENEAU



BSiO2





In situ


Mecanistic model


dissolution?



(Si/C)z = (Si/C)0 z0.41

Aggregate





Antia et al. (2001)

Suess (1980)Betzer et al. (1984)Pace et al. (1987)Berger et al. (1987)Antia et al. (2001)

Antia and co-workers, 2001

Different methods used to determine the carbon flux

High variability between methods

From BSiO2 fluxes to C fluxes in the water column

How to evaluate the ratio of carbon that could reach the maximum depth of the Wind Mixed Layer (WML)?

Is it possible to reconstruct the carbon flux from the BSiO2 fluxes?

Actual calculation of carbon fluxes problems

YES

Ragueneau et al., 2002

(Si/C)z = (Si/C)0 . z0.41


0

1000

2000

3000

4000

5000

0% 50% 100%C

De

pth

m

model %C

pooz C

0

1000

2000

3000

4000

5000

6000

0% 50% 100%BSiO2

Dep

th m

model % BSiO2

pooz BSiO2

ZOOM

BSiO2 fluxes different types of particles

Good reconstruction of the C fluxes

Reconstruction of the carbon sedimentation fluxes

0500

10001500200025003000350040004500

0% 50% 100%%BSiO2 %C

De

pth

m

model % BSiO2

APFP BSiO2

model %C

APFP C

0100200300400500600700800900

1000

0% 50% 100% C

De

pth

m

model %C

APFP C



(Si/C)z = (Si/C)0 z0.41

Moriceau et al., to be submitted b


PAP

SACCAPFP

NACC POOZAPFA

BATSOSP

EqPac

c. POOZ site

0

200

400

600

800

1000

1200

1400

0 0.5 1 1.5 2 2.5 3

POC flux (mol m -2 yr -1)

Dep

th (

m) Traps

Betzer

Suess

Moriceau

Schlitzer

d. SACC site

0

200

400

600

800

1000

1200

1400

0 0.5 1 1.5 2 2.5 3 3.5 4

POC flux (mol m-2 yr-1)

De

pth

(m

)

Traps

Betzer

Suess

Moriceau

Schlitzer

e. OSP site

0

200

400

600

800

1000

1200

1400

0 0.5 1 1.5 2 2.5 3 3.5 4

POC flux (mol m-2 yr-1)

De

pth

(m

) Traps

Betzer

Suess

Moriceau

Schlitzer

f. PAP site

0

200

400

600

800

1000

1200

1400

0 0.5 1 1.5 2 2.5 3 3.5 4

POC flux (mol m -2 yr -1)

Dep

th (

m) Traps

Betzer

Suess

Moriceau

IM (Schlitzer)

Comparison with other methods of

calculation

Our method:

Lower estimation of the carbon flux



PAP

SACCAPFP

NACC POOZAPFA

BATSOSP

EqPac

(a)

0

0.1

0.2

0.3

0.4

0.5

0 100 200 300 400

PP (g C m-2 yr-1)

e at

100

m

(b)

0

0.1

0.2

0.3

0.4

0.5

0 100 200 300 400

PP (g C m-2 yr-1)

e a

t W

WM

L

0.00

0.05

0.10

0.15

0 1 2 3 4

Suess 1980This study

Betzer et al., 1984Schlitzer et al., 2002 calculated at 133 m

e100m decreases with PP e100m increases with PP

e100m is constant

A trend between eWWML and PP still exists in our study



Importance of the seasonality

SI = 6 – number of months necessary to reach half of the anual PP

Berger and Wefer, 1990

1 2 3 4 5 6

PP

months

Constant PP SI ~0

Pulsed PP SI ~ 5

Pulsed PP export more than constant PP

50% of annual PP


0

0.1

0.2

0.3

0.4

0.5

0 100 200 300 400

(c)

y = 0,0289x + 0,0100R2 = 0,75 p = 0,0025

0.00

0.05

0.10

0.15

0 1 2 3 4

SI/(WWML*PP)

e a

t W

WM

L

0

50

100

150

200

0 100 200 300 400 500 600

Export ratio depends on the seasonality index

Aggregation is a seasonal process

Need to study the sedimentation flux in a seasonal time scale




Conclusions et perspectives



Impact of aggregation

on BSiO2 dissolution?

Impact of aggregation on the depth of the BSiO2

recycling?

Role of diatoms in the Biological

pump?

Dissolution parameters of BSiO2 in the

Aggregate

Which processes are

involved?


measurements?



Impact of aggregation on BSiO2 dissolution?


recycling?


Dissolution parameters of BSiO2 in the

Aggregate



measurements?

The BSiO2 dissolution rate is decreased by a factor of 2 for aggregated

diatoms

The decrease of the DSi diffusion coefficient by a factor of 150

The high viability of aggregated cells

The high DSi concentration inside aggregates

The low number of bacteria per diatom



aggregation decrease the BSiO2

dissolution by a factor of 2


recycling?


Dissolution of BSiO2 in the

Aggregate


measurements?

The BSiO2 dissolution depth depends on the capacity of the cells to aggregate or to stay freeAggregation influences the depth of the BSiO2 recycling due to aggregate sinking and dissolution rates

YESThe experimental measurements are accurate and can be used in a global

model

Importance of particle dynamics



Experimental measurement are accurate

Role of diatoms in the Biological

Pump?Capacity of diatoms to transport carbon

Capacity of diatoms to Protect their carbon

aggregation decrease the BSiO2

dissolution by a factor of 2

Dissolution of BSiO2 in the

Aggregate

Aggregation influences the depth of the BSiO2 recycling due to the

sinking and dissolution rates


Post Doc CARBALIS

Construction of a semi-mechanistic

model

Construction of a mechanistic model

Post Doc CARBALISCarbon and Ballasts Interactions during Sinking:

an Experimental and Modelling Approach

The overall objective of CARBALIS is to improve our understanding of POC and ballasts

interactions during sinking throughout the mesopelagic and deep layers of the ocean

Experimental phase

Modelling phase

A 3 years Marie Curie Fellowship

Supervised by O. Ragueneau

At Stony Brook University (New York)

At Stony Brook University (New York)

+ At the IUEM

The role of bacteria in the recycling of BSiO2 during sedimentation

Collaboration with C. Tamburini

Coupled experiments: BSiO2 dissolution + C degradationCollaboration with C. Lee, M. Goutx, U. Passow

CARBALIS

Construction of a mechanistic model

Collaboration with R. Armstrong

Use of the mechanistic model in 1D model

Collaboration with P. Pondaven, K. Soetaert

External carbon – BSiO2

Internal carbon – BSiO2

Modelling

Thank You!!Olivier Ragueneau

Uta Passow

Karline Soetaert

Madeleine Goutx

Catherine Jeandel

Marion

Laurent Memery

Morgane gallinari

Michael

Sorcha

Joëlle

Jonathan

Pierro

Pierre U

Matthieu

Aude Leynaert

Sophie

Sabine

Gwen

Géraldine

Eva

Marie

Tristan

Le LEMAR

L’AWI

Gerald

Anja (les 2)

Ma mère

Ma sœur

Béatrice

Ma famille

Loïc

Danielle, Alain et Suzanne

L’IFREMER d’Argenton

L’équipe de BIOZAIR

Christian Tamburini

Cathy

L’équipe de marseille

Philippe Van Cappellen

Goulven Laruelle

Jim greenwood

L’équipe de Si-Web

Les microbios et les poissons

Monique

Bob

Raoul

Julien

Ben

Jacques

Mathieu

Hélène

Anne

Annick

Rudolph

Pascal Morin

Pierre Lecorre

Sandrine

Stephane

Martial

Philippe

Christophe

Aurore

Schumina

Michaela

Et bien d’autres…

Diatoms aggregates

• The dissolution rate of the BSiO2 is 2 times

lower in aggregates

• The diffusion coefficient of the DSi is decreased by 150 in aggregates

• Validity of the experimental measurements

Conclusion

How does aggregation influence the BSiO2

dissolution?


The depth of the BSiO2 recycling depends on the amount of diatoms that aggregate or stay free

In a model:

Importance of the particle dynamics

Importance of the particle dissolution kinetic

In aggregate BSiO2 dissolution is 2 times lower

Optimum wind mixed layer maximum depth for the formation of large particles: 200 m

Conclusion

Reconstruction of the C fluxes from BSiO2 fluxes

Construction of a semi-mechanistic model

We are able to evaluate the C flux at each depths

We are able to evaluate the export efficiency down to the mixing zone

Conclusion

C-Si interactions during degradation

Intracellular carbon degrades after BSi dissolution?? or with the BSi??

Marker Lipids

Extracellular C-BSi interaction: NSF-CNRS collaboration MedFlux

Organic coating

BSi

Internal organic matter

y = -0,092x + 5,0516

3

4

4

5

5

6

6

0 2 4 6time days

lipid

s µ

M

y = 0,0185x + 4,33373

4

5

6

0 2 4 6time days

lipid

s µM

02468

1012

0 50 100 150time h

Si(

OH

)4

0

5

10

15

20

0 50 100 150time

Si(O

H)4

Particular lipids

DSi

Collect during 16h Collect during 48h

Madeleine GOUTX

Catherine GUIGUE

Plan

• Introduction• Etude de la dissolution de la BSiO2

dans les agrégats de diatomées– Expérimentations– Modèle

• Impact sur les flux de silice• Impact sur les flux de carbone• Conclusion et Perspectives

0.00

0.05

0.10

0.15

0.20

0.25

0.30

-90 -40 10 60

Latitude

TE wi

th EP f

rom La

ws

0.00

0.05

0.10

0.15

0.20

0.25

0.30

-90 -40 10 60

LatitudeTE

with E

P from

Schli

tzer

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

-90 -70 -50 -30 -10 10 30 50 70 90

Latitude

CaCO

3 flu

x

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75

2.00

-90 -70 -50 -30 -10 10 30 50 70 90

Latitude

BSiO

2 flu

x

TE

with

EP

from

Laws

TE

with

EP

from

Schlitz

er

CaCO

3flux

BSiO

2flux

Latitude

LatitudeLatitude

Latitude

0.00

0.05

0.10

0.15

0.20

0.25

0.30

-90 -40 10 60

Latitude

TE wi

th EP f

rom La

ws

0.00

0.05

0.10

0.15

0.20

0.25

0.30

-90 -40 10 60

LatitudeTE

with E

P from

Schli

tzer

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

-90 -70 -50 -30 -10 10 30 50 70 90

Latitude

CaCO

3 flu

x

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75

2.00

-90 -70 -50 -30 -10 10 30 50 70 90

Latitude

BSiO

2 flu

x

0.00

0.05

0.10

0.15

0.20

0.25

0.30

-90 -40 10 60

Latitude

TE wi

th EP f

rom La

ws

0.00

0.05

0.10

0.15

0.20

0.25

0.30

-90 -40 10 60

LatitudeTE

with E

P from

Schli

tzer

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

-90 -70 -50 -30 -10 10 30 50 70 90

Latitude

CaCO

3 flu

x

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75

2.00

-90 -70 -50 -30 -10 10 30 50 70 90

Latitude

BSiO

2 flu

x

0.00

0.05

0.10

0.15

0.20

0.25

0.30

-90 -40 10 60

Latitude

TE wi

th EP f

rom La

ws

0.00

0.05

0.10

0.15

0.20

0.25

0.30

-90 -40 10 60

LatitudeTE

with E

P from

Schli

tzer

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

-90 -70 -50 -30 -10 10 30 50 70 90

Latitude

CaCO

3 flu

x

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75

2.00

-90 -70 -50 -30 -10 10 30 50 70 90

Latitude

BSiO

2 flu

x

0.00

0.05

0.10

0.15

0.20

0.25

0.30

-90 -40 10 60

Latitude

TE wi

th EP f

rom La

ws

0.00

0.05

0.10

0.15

0.20

0.25

0.30

-90 -40 10 60

LatitudeTE

with E

P from

Schli

tzer

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

-90 -70 -50 -30 -10 10 30 50 70 90

Latitude

CaCO

3 flu

x

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75

2.00

-90 -70 -50 -30 -10 10 30 50 70 90

Latitude

BSiO

2 flu

x

TE

with

EP

from

Laws

TE

with

EP

from

Schlitz

er

CaCO

3flux

BSiO

2flux

Latitude

LatitudeLatitude

Latitude

Recent studies using a consequent data base demonstrated the better

efficiency of coccoliths to transport carbon to the deep sea

Coccolithophorids are more efficient

The carbon attached to diatoms could be more labile

Ragueneau et al, 2002

0.00

0.05

0.10

0.15

0.20

0.25

0.30

-90 -40 10 60

Latitude

TE

wit

h E

P fr

om L

aws

0.00

0.05

0.10

0.15

0.20

0.25

0.30

-90 -40 10 60

Latitude

TE

wit

h E

P fr

om S

chli

tzer

0.000.05

0.100.150.20

0.25

0.30

0.350.400.450.50

-90 -70 -50 -30 -10 10 30 50 70 90

Latitude

CaC

O3 fl

ux

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75

2.00

-90 -70 -50 -30 -10 10 30 50 70 90

Latitude

BSi

O2 fl

ux

TE

wit

h E

P f

rom

Law

s

TE

wit

h E

P f

rom

Sch

litz

er

CaC

O3 f

lux

BS

iO2

flux

Latitude

LatitudeLatitude

LatitudeCoccolithophorids are more

efficientDiatoms are more efficient

The respective role of diatoms and coccolithophorids in the transfer efficiency depend on how the export production is estimated

DSi

Shaking

DSi + number of cells

Aggregates and cell size

etude de la dissolution de la silice biogénique des agrégats. utilisation dans la reconstruction...

Documents

dissolution bsio

dissolution experiment

depth of bsio

dissolution measurement

dissolution rate x

biogenic silica bsio

introduction slide

gtc slide