ICOS Science Conference, Session 8

1. Short-term impacts
of the summer 2019 heatwave
on ecosystem functioning
inferred from ICOS Ecosystem stations in France
P. Buysse1, G. Simioni2, S. Lafont3, N. Martin-St Paul2, J. Ruffault2, N. Delpierre4, B. Loubet1, D.
Berveiller, D. Bonal, F. Bornet, A. Brut, B. Burban, J-C Calvet, E. Ceschia, J. Chave, C. Chipeaux,
M. Corbin, M. Cuntz, O. Darsonville, E. Dufrêne, C. Flechard, C. Galy, F. Gastal, S. Gogo, A.
Jacotot, K. Klumpp, J. Leonard, J-B Lily, J-M Limousin, D. Loustau, O. Marloie, V. Moreaux, J-M
Ourcival, T. Tallec, D. Voisin, B. Zawilski.
1INRAE, ECOSYS, Université Paris Saclay, Thiverval-Grignon, France
2INRAE, URFM, Avignon, France
3INRAE, ISPA, Bordeaux, France
4CNRS, ESE, Orsay, France
ICOS Science Conference, Online 15-17 september 2020

2. Context of the study
• Heat waves will be more and more frequent in the future (e. g. extreme
event like summer 2003 expected at least once in 30-year period, Russo et
al., 2015)
• Mechanisms at work in terrestrial ecosystems are still debated (e.g.
Gourlez de la Motte et al. 2019)
 Why a particular focus on 2019 in France?
• Two short summer heat wave episodes in Europe and in France in particular
• Absolute temperature record broken in France: 46°C in Verargues, Southern
France, on 28 June (previous french record was 44.1°C).
• Local temperature records broken as well, e.g. 42.6°C in Paris on 25 July.
• Notably, not all regions were affected in the same way at the same time!!
https://earthobservatory.nasa.gov/images/145377/a-
second-scorching-heatwave-in-europe
2

3. Observation sites and data
•Along a gradient of climates, soil types, management pressure
•14 ICOS ecosystem sites located in metropolitan France:
• 6 forest sites (FR-Hes, FR-Fon, FR-Bil, FR-Pue, FR-FBn)
• 5 crop sites (FR-Gri, FR-Aur, FR-Lam, FR-EM2, FR-Mej)
• 4 grassland sites (FR-Lq2, FR-Tou, FR-Clt)
• 1 peatland site (FR-LGt)
•Class 2, Class 1 and associated sites
•Consistent monitoring of carbon and water budgets, growth, and
meteorological data.
•Eddy Flux data measured using ICOS instructions and processed
homogeneously.
→ great infrastructure to assess heat wave effects
3
FR-Mej FR-Fon
FR-Gri FR-EM2
FR-Bil
FR-Aur
FR-Lam
FR-Tou
FR-Pue
FR-FBn
FR-Clt
FR-Lq2
FR-LGt
FR-Hes
https://www.icos-cp.eu/observations/ecosystem/stations

4. 4
Science questions and hypotheses
•How did the 2019 heat waves impact the ecosystem fluxes?
• (Net Ecosystem Exchange, Photosynthesis, Respiration, Water fluxes, Stomatal conductance)
•What are the links between carbon and water fluxes?
•What are the roles of temperature, air humidity and soil water stress in the responses to heat waves?
HYPOTHESES
•Heat waves  Reductions of net CO2 exchange (NEE)
•NEE reductions may be caused by:
•Increase of temperature  Increased respiration
•Increase of water stress and vapor pressure deficit (VPD)  Stomatal closure  reduction of GPP
and λE
•Damage in photosynthetic enzymes  reduction of GPP

5. 5
Methods
1. Definition of heat waves:
• A number of definitions exist throughout the world.
• The most consistent ones are based on local temperature anomalies

6. 6
Methods
1. Definition of heat waves:
• A number of definitions exist throughout the world.
• The most consistent ones are based on local temperature anomalies
• The definition we used:
• Heatwave = period ≥ 3 consecutive days with maximum temperature (Tmax) above the daily threshold
• for the reference period 1981–2010.
• The threshold is defined as the 90th percentile of daily maximum temperature, centered on a 31 day
window.
• We used the SAFRAN (Meteo France product) dataset.
• Heat wave intensity index is computed based on temperature anomaly and heat wave duration.
References:
Stefanon et al. 2012,Heatwave classification over Europe and the Mediterranean region ERL doi:10.1088/1748-
9326/7/1/014023
Russo et al. 2015, Top ten European heatwaves since 1950 and their occurrence in the coming decades. Environmental
Research Letters 10(12), http://doi.org/10.1088/1748-9326/10/12/124003

7. 7
Heat wave
occurrences
•Two main heat wave events
(HW) were detected at almost
all sites:
• end of June, South of France
• end of July, North of France

8. 8
Methods
2. Data processing:
• Carbon and water fluxes:
• Collection of EC and meteo data from all sites
• Calculations and data analyses performed with R software
• Data gap-filling and flux partitioning (night-time and day-time approaches used with REddyProc package)
• Water stress:
• Reconstruction of water holding capacity and temporal dynamics of available water from evapotranspiration
and precipitation measurements.
• Water stress increased linearly with decreasing available water when below 40 % of water holding capacity.
• Canopy conductance (Gc):
• inversion of the Penman Monteith equation

9. 9
Overview of net C fluxes
at all sites
(not gap-filled, May-August 2019)
NEE(µmolm-2s-1)
DOY
• Shows the diversity of situations
• Two main HWs: around DOYs 178 and 206
• Possible impact of HW on NEE (reduction of
C sequestration) is clearly visible on many
sites, at different times
• BUT this is not observed so clearly at all sites:
• Crop sites, particularly when in the
growing phase (maize crops, June HW)
• GrasslandsBarley crops
Maize crops
Forests
Grasslands/ Fallow
Peatland
https://puechabon.cefe.cnrs.fr/

10. Changes in NEE during heat waves
Crops
Forests
Grasslands
Peatland
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Carbon sequestration decreased for most sites and heat waves, to various extents,
but there were some exceptions.

11. A typical expected response under no or little water stress:
Example of the Font-Blanche forest (FR-FBn) in june
a mixed Mediterranean forest (Aleppo pine and holm oak)
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 (1) Higher VPD (air dryness) caused a stomatal regulation and a decrease in canopy conductance (Gc)
 (2) Decreased Gc caused a decrease in photosynthesis (GPP)
 (3) Higher temperature caused an increase in respiration (Reco)
 (4) Combined trends in GPP and Reco caused a decrease in carbon sequestration (higher NEE), the forest switched from
sink to source of carbon
 (5) Soil water stress was moderate and did not affect a lot those trends
C fluxes (µmol m-2 s-1)
Hours
NEE
Hours
GPP
Hours
Reco
Gc
(mol m-2 s-1)
0.2
0.4
0.6
0.8
1
100 200 300
DOY
Water stress
begins
Hours
Water stress
(no stress = 1)

12. A typical expected response under no or little water stress:
Example of the Grignon rainfed maize crop site (FR-Gri) in July
12
Gc
(mol m-2 s-1)
 (1) Similar response to that of FR-FBn
 (2) very clear reduction in canopy conductance (Gc) at the warmest hours
 (3) Corresponding decrease in photosynthesis (GPP) in the middle of the day
 (4) Strong increase in respiration (Reco)
 (5) All resulting in a strong decrease in C sequestration (NEE)
Hours
Hours
NEE
Hours
GPP Reco
C fluxes (µmol m-2 s-1)
Hours
Water stress
(no stress = 1)
Little
Water
stress0.2
0.4
0.6
0.8
100 200 300
DOY
1

13. 13
Example of a site possibly showing a “benefit” from a heat wave:
The maize crop field of Lamasquère (FR-Lam) in July
NEEGPP
Hours Hours
(1) High (higher?) canopy conductance (Gc) during heat wave (light increase of VPD), probably due to rain at
the beginning of the heat wave. Increase in Gc is hypothetical since no data before the heat wave.
(2) This allowed high photosynthesis (GPP).
(2) Also an increase in respiration (Reco) due to higher temperatures.
(3) Net result was an increase in C sequestration (lower NEE).
0.2
0.4
0.6
0.8
1
Water stress
(no stress = 1)
100 200 300
DOY
No water
stress during
HW
Gc
(mol m-2 s-1)
C fluxes (µmol m-2 s-1) Water stress
(no stress = 1)
Reco

14. Work in progress…
 Large dataset with many variables to handle
 A lot of particular cases due to multiple, sometimes
antagonistic environmental events (changes in water
stress, rain during the heat wave, cloudy days, leaf
damage…) that need to be disentangled
 Important concerns about flux partitioning
methods during extreme events (e.g. different
results with day-time and night-time methods)
 Flux recovery after heat wave also needs to be
investigated
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NT method
FR-Gri
Reco
FR-Fon
DT method

15. Conclusion
•The 2019 summer heat waves affected the carbon and water fluxes
of the sites present in this study.
•Most of the studied sites showed a reduction in NEE during heat
waves.
•Soil water stress and decreasing stomatal conductance during the
extreme events may explain a reduction in GPP though this was not
observed at all sites.
•The actual mechanisms behind the observed NEE reductions are yet
to be understood and more work is necessary on this dataset.
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16. Thank you for your attention!
16
Thank you for your attention!
And thank to all the technical teams