• Aucun résultat trouvé

CROSTVOC : an integrated project for studying the impact of abiotic stresses on BVOC production of field crops and grasslands

N/A
N/A
Protected

Academic year: 2021

Partager "CROSTVOC : an integrated project for studying the impact of abiotic stresses on BVOC production of field crops and grasslands"

Copied!
1
0
0

Texte intégral

(1)

CROSTVOC : AN INTEGRATED PROJECT FOR STUDYING THE IMPACT OF ABIOTIC

STRESSES ON BVOC PRODUCTION OF FIELD CROPS AND GRASSLANDS

B. H

EINESCH1*

, C. A

MELYNCK2

, M. A

UBINET1

, A. B

ACHY1

, A. D

IGRADO3

, P. D

ELAPLACE3

, P.

DU

J

ARDIN3

,

M-L. F

AUCONNIER4

, A. M

OZAFFAR1-2

, N. S

CHOON2

1 Exchanges Ecosystems - Atmosphere, Biosystem Engineering, Gembloux Agro-Bio Tech, University of Liege, Gembloux, Belgium 2 Belgian Institute for Space Aeronomy, Brussels, Belgium

3Unit of Plant Biology, Gembloux Agro-Bio Tech, University of Liege, Gembloux, Belgium 4Agro-Bio systems Chemistry, Gembloux Agro-Bio Tech, University of Liege, Gembloux, Belgium

*Corresponding author, bernard.heinesch@ulg.ac.be

CROSTVOC ?

In addition to a lack of data on biogenic volatile organic compound (BVOC) emissions from important agricultural lands, large uncertainties in BVOC emission inventories are attributed to stress, which can drastically alter the emission capacities of plants and change their BVOC emission patterns. With “CROSTVOC” (for CROp STress VOC, 2013-2017), we will study the effects of abiotic stress (heat, drought, ozone and

grazing) on BVOC emissions, both at the ecosystem and plant scale, for three specific

model systems (maize/wheat/grassland) representing together about 75% of the agricultural land-use in Wallonia (Belgium).

Parallel investigations under field natural conditions and growth-chamber controlled conditions will help to understand to which extent knowledge coming from laboratory measurements can be extrapolated to real conditions.

SCIENTIFIC QUESTIONS TO BE INVESTIGATED

Which BVOCs are emitted by these under-studied agricultural crops in non-stressed conditions, in which amount and when? Which environmental (light, temperature, humidity,…) or phenological conditions are driving these exchanges?

How frequently and when are these ecosystems subjected to (a)biotic stress? What is the quantitative and qualitative (compound speciation) impact of those stress events on BVOC emissions?

What is the relative impact of phenology, plant type and stress level on BVOC stress-induced emissions?

What is the impact of combined stress on BVOC emissions and biosynthesis pathways?

Keywords : GC-MS, PTR-MS, eddy covariance, BVOC, field crop, grassland, abiotic stress, chlorophyll fluorescence,

chlorophyll content, stomatal conductance

- Environmental data collection

- ecophysiological measurements

- BVOC measurements in field

enclosures and at the ecosystem level

Link between

ecophysiological dataset

and altered BVOC

emissions

Simulation of the environmental

constraints linked to altered BVOC

emissions in growth chamber and

measure of the resulting BVOC emissions

Equipment for environmental and BVOC eddy-covariance data collection at

Lonzée (top) and Dorinne (bottom) sites Field cuvette for PTR-MS and GC-MS measurements

Chamber cuvette (whole plant on the left and hanging leaf cuvette on the right) for PTR-MS and GC-MS measurements

Field campaigns

Hypothesis

Laboratory validation

Acknowledgments : the CROSTVOC research project is fully funded by the Fonds de la Recherche Scientifique (FNRS)

Experimental sites

Lonzée (crop, ICOS site) and Dorinne (grazed grassland) terrestrial observatories Growth chamber at the Belgian Institute for Space Aeronomy: 18 m3, temperature

(15-35 °C) and PAR (0-600 µmol m-2s-1) control, realistic soil substrate

Six automated field cuvettes and several 22-44 L growth-chamber cuvettes with RH control and O3fumigation capacities

Environmental data (field/lab)

Meteorological data (precipitation, radiation, air temperature, air humidity, O3conc)

Soil humidity, soil temperature

Field CO2, H2O, O3and sensible heat fluxes by eddy-covariance Phenology (field/lab)

Biomass growth follow-up using destructive samplings and LAI measurements Crop management activities follow-up (fertilizer, pesticides, grazing intensity for the grassland)

Stress markers (field/lab)

Chlorophyll content and chlorophyll fluorescence kinetics Stomatal conductance

Destructive sampling for antioxidant measurement

Monitoring of biotic stresses (controlled to avoid them to settle in the field and mask abiotic stresses)

BVOC measurements (field/lab)

Ecosystem scale BVOC fluxes measurements by eddy-covariance using proton transfer reaction-mass spectrometry (PTR-MS)

Plant scale BVOC fluxes measurements by PTR-MS in field cuvettes (Sampling Duration , SD : 10 min/h) and in growth chamber cuvettes

BVOC identification by gas chromatography-mass spectrometry (GC-MS) with dynamic headspace sampling in all types of cuvettes ( SD : 4 h/week)

TO

O

LS

S

TR

A

TE

G

Y

C

O

N

TE

X

T

Références

Documents relatifs

The absence of a single well-defined peak, but a generally increasing trend in ozone, with individual profiles characterized by the presence of multiple laminae of the order of

Direct Detection Differential Absorption LIDAR for Multi-Species Atmospheric Sensing in the 2-µm Range Erwan Cadiou, Jean-Baptiste Dherbecourt, Dominique Mammez, GuillaumeE.

To examine the winter 2004–2005 hydrographic characteristics of the western basin, we first review successive profiles of θ, S and σθ for ARGO float 6900279, which ulti- mately

calculated traits (aboveground leaf mass fraction, plant-scale speci fic leaf area, aboveground leaf area ratio), aboveground absolute and relative growth rates on a biomass basis and

The purpose of this paper is therefore to propose a model for analysing the overlapping processes between internationalization, national adaptation, regionalization

Il y avait une corrélation significative entre le niveau d’éducation et l’adhérence du patient (r=0.176, p=0.048) Les corrélations entre les items du questionnaire de

1) Time-to-Collision based: One of the most intuitive approaches to detect the driver unawareness is to use the time-to-collision (T T C). This type of temporal property is usually

Après trois ans d’observations et de mesures du bagage de connaissances et de compétences des étudiants qui s’inscrivent en première année aux FUNDP, l’équipe du projet