session 5.1 strong spatial variability of lue in coffee agroforestry systems

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STRONG SPATIAL VARIABILITY OF LIGHT USE EFFICIENCY IN A COFFEE AFS, HIGHLIGHTED BY 3D LIGHT AND GAS EXCHANGE MODEL Fabien Charbonnier 1 ,2,3,4,* , Olivier Roupsard 1,4 , Fernando Casanoves 4 , Louise Audebert 5 , Elsa Defresnet 6 , Aurélie Cambou 7 , Clémentine Alline 8 , Bruno Rapidel 8 , Jacques Avelino 9,4 , Karel Van den Meersche 1,4 , Jean-Michel Harmand 1 , Christophe Jourdan 1 , Philippe Vaast 1,10 , Alejandra Barquero 11 , Patricia Leandro 4 & Erwin Dreyer 2,3 1 CIRAD, UMR Eco&Sols (Ecologie Fonctionnelle & Biogéochimie des Sols et des Agro-écosystèmes), 34060 Montpellier Cedex 2, France; 2 Université de Lorraine, UMR 1137 “Ecologie et Ecophysiologie Forestières, F 54500 Vandoeuvre, France; 3 INRA, UMR 1137 “Ecologie et Ecophysiologie Forestières”, F54280 Champenoux, France; 4 CATIE (Centro Agronómico Tropical de Investigación y Enseñanza), 7170 Turrialba, Costa Rica; 5 Faculté des Sciences, Université de Lorraine, F 54500 Vandoeuvre, France; 6 AGROCAMPUS OUEST, Centre de Rennes, 35042, Rennes Cedex, France; 7 ENSAIA, Ecole Nationale Supérieure d’Agronomie et des Industries Alimentaires, Nancy, France; 8 CIRAD, UMR System, 34060 Montpellier, France; 9 CIRAD, UPR Bioagresseurs, F-34398 Montpellier, France; 10 ICRAF, United Nations, Avenue Gigiri, PO Box 30677- 00100, Nairobi, Kenya; 11 Cafetalera Aquiares S.A., PO Box 362-7150 Turrialba, Costa Rica

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Page 1: Session 5.1 strong spatial variability of LUE  in coffee agroforestry systems

STRONG SPATIAL VARIABILITY OF LIGHT USE EFFICIENCY IN A COFFEE AFS, HIGHLIGHTED BY 3D LIGHT AND GAS

EXCHANGE MODELFabien Charbonnier1,2,3,4,*, Olivier Roupsard1,4, Fernando Casanoves4, Louise Audebert5,

Elsa Defresnet6, Aurélie Cambou7, Clémentine Alline8, Bruno Rapidel8, Jacques Avelino9,4, Karel Van den Meersche1,4, Jean-Michel Harmand1, Christophe Jourdan1, Philippe Vaast1,10,

Alejandra Barquero11, Patricia Leandro4 & Erwin Dreyer2,3

1CIRAD, UMR Eco&Sols (Ecologie Fonctionnelle & Biogéochimie des Sols et des Agro-écosystèmes), 34060 Montpellier Cedex 2, France; 2Université de Lorraine, UMR 1137 “Ecologie et Ecophysiologie Forestières, F 54500 Vandoeuvre, France; 3INRA, UMR 1137 “Ecologie et Ecophysiologie Forestières”, F54280 Champenoux, France; 4CATIE (Centro Agronómico Tropical de Investigación y Enseñanza), 7170 Turrialba, Costa Rica; 5Faculté des Sciences, Université de Lorraine, F 54500 Vandoeuvre, France; 6AGROCAMPUS OUEST, Centre de Rennes, 35042, Rennes Cedex, France; 7ENSAIA, Ecole Nationale Supérieure d’Agronomie et des Industries Alimentaires, Nancy, France; 8CIRAD, UMR System, 34060 Montpellier, France; 9CIRAD, UPR Bioagresseurs, F-34398 Montpellier, France; 10ICRAF, United Nations, Avenue Gigiri, PO Box 30677-00100, Nairobi, Kenya; 11Cafetalera Aquiares S.A., PO Box 362-7150 Turrialba, Costa Rica

Page 2: Session 5.1 strong spatial variability of LUE  in coffee agroforestry systems

RessourcesCO2

H20Nutrients

Net Primary ProductionConversion

efficiency

By-productsRespiration

Tree/Crop interactions in AFS

ENERGY

SHADE TREES

COMPETITIONCOMPLEMENTARITY/FACILITATION

NON LIMITING

???

CROP

Light Use Efficiency

Species, phenology, microclimate, plant

architecture, leaf traits…

Page 3: Session 5.1 strong spatial variability of LUE  in coffee agroforestry systems

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LUE, NPP and aPAR

gC MJaPAR-1

MJaPAR resprout-1 year-1

Poorter et al. (2002), Hunt et al. (2001)

3

NPPNPPLUEaPAR

gC resprout-1 year-1

NPP = Net Primary Productivity; G = Growth; L = Litter production; Ex = Exportation

MAESPA model (Duursma & Medlyn , 2013; Charbonnier et al., 2013)

Page 4: Session 5.1 strong spatial variability of LUE  in coffee agroforestry systems

M&M: experimental design

•60 coffee resprouts / 6 age classes / 2 light environments / 5 blocks•Design of branch, leaf and fruit level allometric relationships•One biometric measurement every 2 months• Litter harvest every 15 days• Coffee fruit harvesting every year• Monitored during 2 years• Analyzed with Linear Mixed Models

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Modeled light environment in MAESPA (transmittance+aPAR)Charbonnier et al., Agric. For. Meteorol. (2013)

3 m

5 YO

5 YO

5 YO

4 YO

4 YO

3 YO

Page 5: Session 5.1 strong spatial variability of LUE  in coffee agroforestry systems

NPP of coffee resprouts

• Strong age effect on resprout NPP

• Surprisingly, no effect of shade on resprout NPP

5

0 0 1 1 2 2 3 3 4 4 5 5Sun Shade Sun Shade Sun Shade Sun Shade Sun Shade Sun Shade

0

200

400

600

42 34 83 82 101 108 123 151 155 178 179 17941 29

77 119 109165 162

215 230 203264 213

2425 65

15157

51

197148

208

162

NPP - 2 years average

NPP

(gC

resp

rout

-1 Y

-1)

Fruit NPP On a 2 year basis:

On a year to year basis• Strong biennial bearing under sun• No biennial bearing under shade• Shade tree transmittance not

explanatory

Branch NPPLeaf NPP

Page 6: Session 5.1 strong spatial variability of LUE  in coffee agroforestry systems

NPPLA & LUENPP of resproutsCoefficients df F-value p-value

NPPLA ( R22=0.24)Resprout age 109 5.16 0.0003Shade tree transmittance NS

LUENPP (R22=0.37)Resprout age 90 6.43 0.0001Shade tree transmittance -0.72 90 8.80 <0.0039

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Example for resprouts of 4 years old:

Page 7: Session 5.1 strong spatial variability of LUE  in coffee agroforestry systems

RessourcesCO2

H20Nutrients

Net Primary Production

By-productsRespiration

What happened under Shade Trees?

ENERGY

SHADE TREES

NON LIMITING

+57%

CROP

Light Use Efficiency

Specie, microclimates, phenology, plant

architecture, leaf traits…

-40% aPAR

No significant change

+30% diffuse radiation

EXPLAINS 20% of the LUE increaseSource: Photosynthesis model in MAESPA

Below-ground NPP

Above-ground NPP

Not significantSource:Sequential Coring

• Leaf traits change? Not significant• Change in microclimate? Shade trees

buffer highest temperaturesi.e: -3°C under large Inga densiflora (Siles et al. 2010) -25% ???

Page 8: Session 5.1 strong spatial variability of LUE  in coffee agroforestry systems

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What does the litterature say?

- Increased LUE is an important phenomenon in AFS- Few studies on LUE because of the difficulty in characterizing aPAR- The nearly total compensation was rarely observed in the litterature:

+26% for groundnut with a decrease of transmitted light of 50% (Monteith et al., 1991);

+27% for millet with a decrease of transmitted light of 50% (Monteith et al., 1991);

+ 20% for lettuce with a decrease of transmitted light of 33% (Dapoigny et al., 2000)

+57% in our study for a 41% decrease of irradiance

- Our study on LUE is one of the first working with large shade trees prone to affect significantly local temperatures

- May be coffee plants are more prone to such behavior because it is a shade tolerant specie: more efficient photosynthesis at low incident light (Ong et al., 1991).

Page 9: Session 5.1 strong spatial variability of LUE  in coffee agroforestry systems

THANK YOU !THIS EXPERIMENT WAS CONDUCTED WITHIN FLUXNET/COFFEE-FLUX OBSERVATORY

[email protected]