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What drives carbon allocation to stem and fine roots in a mature coppice of <em>Quercus ilex</em> in the Mediterranean? A data model analysis

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HAL Id: hal-02747216

https://hal.inrae.fr/hal-02747216

Submitted on 3 Jun 2020

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What drives carbon allocation to stem and fine roots in a mature coppice of Quercus ilex in the Mediterranean?

A data model analysis

Nicolas Martin-Stpaul, Morine Lempereur, Nicolas Delpierre, Jean-Marc Ourcival, Hendrik Davi, Christophe François, Paul Leadley, Eric Dufrene,

Serge Rambal

To cite this version:

Nicolas Martin-Stpaul, Morine Lempereur, Nicolas Delpierre, Jean-Marc Ourcival, Hendrik Davi, et al.. What drives carbon allocation to stem and fine roots in a mature coppice of Quercus ilex in the Mediterranean? A data model analysis. 7th international conference on funtional structural plant models, Jun 2013, Saariselska, Finland. �hal-02747216�

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WHAT DRIVEs CARBON ALLOCATION TO STEM

AND FINE ROOTS IN A Quercus ilex FOREST?

A DATA-MODEL ANALYSIS

MARTIN-STPAUL NK.; LEMPEREUR M., DELPIERRE N., OURCIVAL JM, DAVI H., FRANCOIS C.,

(3)

 Increase drought prone area world wide

Recent climate change:

Dryer climate in the future!

Gao & Gio rg i 2008 GP C

Improving process based models

 Decrease productivity

 Increase mortality

Increase vulnerability of forests:

CONTEXT

Anticipating the future of forests:

Finding out

the most influencial

processes that drives

growth & C allocation

Summer rainfall anomaly (%)

[1961 2000] – [2070 2100]

(Choat et al. 2012 Nature)

(Ciais et al. 2005 Nature)

(Allen et al. 2010 FEM; Carnicer et al. 2012 PNAS) (Dai 2012 Nature Climate Change)

(4)

0 5 10 15 20 25 0 50 100 150 200 250 T e m p ( °C ) o u VP D (h Pa )

MOTIVATIONS: THE EXPERIMENTAL SITE OF PUECHABON

Puechabon experimental site

http://puechabon.cefe.cnrs.fr/

 Mediterranean climate

 Evergreen Quercus ilex (~65 years old)

 Long term records (1998)

 Fluxes:

ecosystem (Eddy Covariance, litterfall) ; tree (sap flow); organ (Chamber)

 C stocks:

forest inventory, litter fall

 Phenology, growth, cavitation

curves, storage

E.C. Fluxes Organ level Gas exch. Phenology Band dendrometer Litter fall Ra in fal l Rainfall VPD Temp Ψ

(5)

0 100 200 300 -4 -3 -2 -1 0 0 100 200 300 0.0 0.2 0.4 0.6 0.8 1.0 0 100 200 300 0 2 4 6 8 10 Gross Photosynthesis (gC m-² day) Relative Stem Growth Day of year Pla nt Ψ p red aw n

MOTIVATIONS: SEASONAL PATTERN OF GROWTH & C FLUXES

Day of year

Lempereur et al in prep

(6)

0 100 200 300 -4 -3 -2 -1 0 0 100 200 300 0.0 0.2 0.4 0.6 0.8 1.0 0 100 200 300 0 2 4 6 8 10 Relative Stem Growth Pla nt Ψ p red aw n

MOTIVATIONS: SEASONAL PATTERN OF GROWTH & C FLUXES

Gross Photosynthesis (gC m-² day)

Day of year

IS GROWTH LIMITED

BY THE SOURCE? due to the decrease in carbon availability

BY THE SINK? Due to the decrease in the water potential

Lempereur et al in prep

(7)

Relative Stem Growth

NEE (gC m-2 j-1)

MOTIVATIONS: SEASONAL PATTERN OF GROWTH & C FLUXES

Gross Photosynthesis (gC m-² day) Day of year 0 100 200 300 0.0 0.2 0.4 0.6 0.8 1.0 0 100 200 300 -3 -2 -1 0 1 2 0 100 200 300 0 100 200 300 0 2 4 6 8 10 C Source C Sink

(8)

Relative Stem Growth

MOTIVATIONS: SEASONAL PATTERN OF GROWTH & C FLUXES

Gross Photosynthesis (gC m-² day) Day of year 0 100 200 300 0.0 0.2 0.4 0.6 0.8 1.0 0 100 200 300 -3 -2 -1 0 1 2 0 100 200 300 0 100 200 300 0 2 4 6 8 10

Where the C sequestered during the summer period is allocated to ?

C Source

C Sink

NEE (gC m-2 j-1)

(9)

Solar radiation temperature Water vapour Interception Photosynthesis Precipitations Canopy interception Throughfall Stem flow Litter Surface Root zone Soil evaporation Carbon Allocation C Root C F.Root C surface CO2 Canopy Evaporation drainage Stomatal Cond. GPP C Stem C Stor. Transpiration C litter C deep C leaves Reco ETR Heterotrophic Respiration Autotrophic Respiration

Davi et al., 2005; Dufrêne et al., 2005 Ecological Modelling

THE MODEL CASTANEA

2D Stand-scale model Half Hourly time step

Average Tree (Monospecific) Water budget

Carbon Budget Carbon allocation

(10)

Photosynthesis

Maintenance

Respiration

Carbon available

for growth

(11)

Photosynthesis

Maintenance

Respiration

Carbon available

for growth

ALLOCATION IN CASTANEA & HYPOTHESIS TESTING

Storage (NSC) Leaves Above and below ground Woody tissue Fine Roots Repro.

(12)

Photosynthesis

Maintenance

Respiration

Carbon available

for growth

ALLOCATION IN CASTANEA & HYPOTHESIS TESTING

Storage (NSC) Leaves Above and below ground Woody tissue Fine Roots Repro. Extensive calibration (Rodriguez-Calcerrada et al 2012) (Rodriguez-Calcerrada et al sub) Data assimilation (MCMC )

(13)

Photosynthesis

Maintenance

Respiration

Carbon available

for growth

ALLOCATION IN CASTANEA & HYPOTHESIS TESTING

Storage (NSC) Leaves Above and below ground Woody tissue Fine Roots Repro.

Simulated

by testing 3 different

hypothesis

Prescribed

(in situ measurements litterfall & phenology)

Data assimilation (MCMC )

Eddy Covariance, sapflow

Extensive calibration

(Rodriguez-Calcerrada et al 2012) (Rodriguez-Calcerrada et al sub)

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ALLOCATION IN CASTANEA & HYPOTHESIS TESTING

Growth depends on available carbon only

0 100 200 300 0.0 0.2 0.4 0.6 0.8 1.0 0 100 200 300 0 2 4 6 8 10 Relative growth GPP

H1: Source Limitation

(15)

ALLOCATION IN CASTANEA & HYPOTHESIS TESTING

Growth depends on available carbon only

H1: Source Limitation

H2: Sink-FineRoots

H1: Sink-Storage

Growth is Limited by water

potential  Available Carbon

is allocated to Fine Roots

Growth is Limited by water

potential  Available Carbon

is allocated to Storage 0 100 200 300 -4 -3 -2 -1 0 0 100 200 300 0.0 0.2 0.4 0.6 0.8 1.0 0 100 200 300 0 2 4 6 8 10

~-1 MPa

Relative growth GPP

(16)

0 100 200 300 -4 -3 -2 -1 0 0 100 200 300 0.0 0.2 0.4 0.6 0.8 1.0 0 100 200 300 0 2 4 6 8 10

ALLOCATION IN CASTANEA & HYPOTHESIS TESTING

Growth depends on available carbon only

Growth is Limited by water

potential  Available Carbon

is allocated to Fine Roots

Growth is Limited by water

potential  Available Carbon

is allocated to Storage

VALIDATION:

Yearly wood increment (forest inventory + allometric relationship): 2000 2010 Temporal dynamic of Storage concentration

Temporal dynamic & Level of 𝐹𝑖𝑛𝑒𝑅𝑜𝑜𝑡𝐿𝑒𝑎𝑓 biomass

~-1 MPa

Relative growth

GPP

(17)

RESULTS: STEM GROWTH MEASURED vs. SIMULATED

0 20 40 60 80 100 120 0 20 40 60 80 100 120 0 20 40 60 80 100 120 0 20 40 60 80 100 120

Source Limitation

R²=0.4

Slope=0.45

R²=0.6

Slope=0.8

R²=0.6

Slope=0.8

An

nu

al

gr

o

wth

si

mul

at

ed

Annual growth measured (gC m² year

-1

)

H3: Sink-Storage

H2: Sink-FineRoots

(18)

BEST GUESSES

0 20 40 60 80 100 120 0 20 40 60 80 100 120 0 20 40 60 80 100 120 0 20 40 60 80 100 120

Source Limitation

R²=0.4

Slope=0.45

R²=0.6

Slope=0.8

R²=0.6

Slope=0.8

An

nu

al

gr

o

wth

si

mul

at

ed

Annual growth measured (gC m² year

-1

)

RESULTS: STEM GROWTH MEASURED vs. SIMULATED

H3: Sink-Storage

H2: Sink-FineRoots

(19)

RESULTS: STORAGE & FINE ROOT/LEAF BIOMASS

Fine Roots/Leaves

Storage

H3: Sink-Storage

H2: Sink-FineRoots

Challenge:

 𝑭𝒊𝒏𝒆 𝑹𝒐𝒐𝒕𝑳𝒆𝒂𝒇 is far from published value (~0.6, Lopez et al. 1998 Plant & Soil)

 Fine roots are sensitive to Ψplant (Growth: Lockhart 1965 ; Mortality: Anderegg et al., 2012)

2000 2002 2004 2006 2008 2010 0.0 0.5 1.0 1.5 2.0 2.5 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 2000 2002 2004 2006 2008 2010 𝐹𝑖𝑛𝑒𝑅𝑜𝑜𝑡𝑠 𝐿𝑒𝑎𝑣𝑒𝑠 𝑆𝑡𝑜𝑟𝑎𝑔𝑒 𝐶𝑜𝑛𝑐𝑒𝑛𝑡𝑟𝑎𝑡𝑖𝑜𝑛

Years

~0.6 Lopez et al. 1998

(20)

Lim ousin et al . 20 10 T ree P h ys |Ψ | (Mpa)

RESULTS: STORAGE & FINE ROOT/LEAF BIOMASS

Challenge:

 𝑭𝒊𝒏𝒆 𝑹𝒐𝒐𝒕𝑳𝒆𝒂𝒇 is far from published value (~0.6, Lopez et al. 1998 Plant & Soil)

 Fine roots are sensitive to Ψplant (Growth: Lockhart 1965 ; Mortality: Anderegg et al., 2012)

Ψpredawn

at Puechabon % CAVITATION

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NEW HYPOTHESIS

𝑭𝒊𝒏𝒆 𝒓𝒐𝒐𝒕 𝒎𝒐𝒓𝒕𝒂𝒍𝒊𝒕𝒚=(𝟏+𝐞𝐱𝐩 𝟎.𝟕𝟕×𝜳𝟏 𝑷𝒓𝒆𝒅𝒂𝒘𝒏+𝟐.𝟒 ) 𝒊𝒇 𝜳𝒅𝒂𝒘𝒏 < −𝟏𝐌𝐏𝐚 {𝑨𝒍𝒍 𝒈𝒓𝒐𝒘𝒕𝒉= 0 ; Storage=1 } 𝑭𝒊𝒏𝒆 𝒓𝒐𝒐𝒕 𝒈𝒓𝒐𝒘𝒕𝒉 = 𝒇(𝑺𝒕𝒐𝒓𝒂𝒈𝒆, 𝑭𝑹𝒐𝒐𝒕𝑻𝒉) Lim ousin et al . 20 10 T ree P h ys |Ψ | (Mpa) Ψpredawn at Puechabon % CAVITATION OF ROOTS

(22)

NEW HYPOTHESIS

𝑆𝑡𝑜𝑟𝑎𝑔𝑒 𝐹𝑖𝑛𝑒𝑅𝑜𝑜𝑡 𝐿𝑒𝑎𝑓 0.1 0.2 0.3 0.4 0.5 0.6 0.7 2000 2003 2006 2009 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.0 0.5 1.0 1.5 2.0 2.5 2000 2002 2004 2006 2008 2010 0.0 0.5 1.0 1.5 2.0 2.5 Sink-FineRoots Sink-Storage ~0.6 Lopez et al. 1998 NEW MODEL

(23)

𝑆𝑡𝑜𝑟𝑎𝑔𝑒 (%) 0.1 0.2 0.3 0.4 0.5 0.6 0.7 2000 2003 2006 2009 0.1 0.2 0.3 0.4 0.5 0.6 0.7

NEW HYPOTHESIS

0 100 200 300 0.10 0.12 0.14 0.16 0.18 -4 -3 -2 -1 𝑆𝑡𝑜𝑟𝑎𝑔𝑒 Ψ (𝑀𝑃𝑎)

Rodriguez-Calcerrada et al. submitted Storage in the sapwood

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SUMMARY

 Stem growth is likely not C-limited and can be accurately model

assuming a direct effect of water potential

 The carbon sequestered during the drought period might be used for

fine root production or reconstruction

 A model accouting for fine roots mortality and reconstruction was

consistent with the observations of increasing storage concentration

during the seasonal drought

(25)

SUMMARY

& CONCLUSION

 Stem growth is likely not C-limited and can be accurately model

assuming a direct effect of water potential

 The carbon sequestered during the drought period might be used for

fine root production or reconstruction

 A model accouting for fine roots mortality and reconstruction was

consistent with the observations of increasing storage concentration

during the seasonal drought

 The process simulated by the improved model are believed to be

involved in tree vulnerability to drought

(McDowell et al. 2011 Trends. Ecol.

Evolution)

 This model might be a step in assessing tree’ outcomes under

(26)

Thank you for

your attention

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