• Aucun résultat trouvé

en fr

N/A
N/A
Protected

Academic year: 2022

Partager "en fr "

Copied!
2
0
0

Texte intégral

(1)

HAL Id: hal-02819370

https://hal.inrae.fr/hal-02819370

Submitted on 6 Jun 2020

HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci- entific research documents, whether they are pub- lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Impacts of future climate scenario and summer extreme events on perennial grassland

Marine Zwicke, Giorgio Alessio, Jean-François Soussana, Catherine Picon-Cochard, Robert Falcimagne

To cite this version:

Marine Zwicke, Giorgio Alessio, Jean-François Soussana, Catherine Picon-Cochard, Robert Falci-

magne. Impacts of future climate scenario and summer extreme events on perennial grassland. Col-

loque Ecologie 2010, Sep 2010, Montpellier, France. 2010. �hal-02819370�

(2)

A L I M E N T A T I O N A G R I C U L T U R E

E N V I R O N N E M E N T

INRA – Centre de Clermont-Ferrand - Theix UR874 Ecosystème Prairial

63100• Clermont Ferrand • France www.clermont.inra.fr/urep

Impacts of future climate scenario and summer extreme events on perennial grassland

Marine Zwicke, Giorgio Alessio, Lionel Thierry, Robert Falcimagne, Catherine Picon-Cochard, Jean François Soussana marine.zwicke@clermont.inra.fr

At the end of the century, climate scenarii predict increases of air temperature as well as a decrease of summer precipitations (IPCC 2007). These mean changes will probably be associated with the occurrence of extreme event such as 2003 heat wave. In this context, ecosystems processes could change punctually, irreversibly as well as progressively. So services of permanent grassland, such as forage supply for ruminants in quantity and quality, high level of biodiversity and high quantity of soil C storage, could be affected. We want to study in situ how these main services are modified by climatic changes and how grassland ecosystem is resilient after summer extreme.

Four regionalised climatic scenarii (CN: Control without extreme; CX: Control with extreme; TN:

2050 without extreme; TX: 2050 with extreme) are applied in field conditions for 2 years in an upland permanent grassland (Auvergne, France, 900m a.s.l., 8.7°C and 856mm mean annual temperature and rainfall). Two cutting frequencies are applied to mimic grassland management and to observe how climate changes interact with anthropic factors. Frequent cut (F) represents an intensive management with 6 cuts per year, infrequent (I) cut represents extensive management with only 3 cuts per year. All treatments are established in 4 replicates (3 x 3 m).

Microclimate is modified with curtains that are opened at night and during rainfall events. This allows increasing night–time air temperature and controlling precipitations (Beier et al 2004).

This system is able to increase significantly night-time soil and leaf temperature (+0.8°C; +2°C respectively) and daily soil and night-time air temperatures (+0.5°C) under optimal environmental conditions. From March to October 2009, this experimental system was used at 75% due to environmental constraints. Due to snow fall in winter 2009, the system was stopped and start again in march 2010.

Extreme treatments (CX; TX) were characterised by a progressive decrease of precipitations in June 2009 and a prolonged drought (-70mm) until august 31th combined with 2 weeks of heat waves (+6°C of daily mean temperature) in July. Heat waves was controlled by active warming system using infrared heaters (Kimball, 2003).

INTRODUCTION INTRODUCTION

METHODS METHODS

FORAGE PRODUCTION AND FUNCTIONAL GROUP COMPOSITION FORAGE PRODUCTION AND FUNCTIONAL GROUP COMPOSITION

ECOSYSTEM SOIL RESPIRATION ECOSYSTEM SOIL RESPIRATION

CONCLUSIONS & PERSPECTIVES CONCLUSIONS & PERSPECTIVES

During extreme event, soil respiration of CX and TX treatments rapidly declined. This effect was maintained until October for the scenario treatment (TX) while for the actual climate treatment (CX) resilience of soil respiration occurred 9 days after the end of extreme event. Under future scenario without extreme (TN) lower soil respiration is observed at the end of July due to lower rainfall amount (lower soil water content; SWC), despite higher soil temperature due to night- time warming treatment. In November, lower soil respiration was observed on CN scenario compared to TN, as SWC was not limiting (>20%). In spring 2010, soil respiration of CX and TX were equal but higher in TN treatment. In conclusion, increase of soil respiration in response to 2050 scenario without extreme event is highly related to SWC. Soil respiration of our grassland ecosystem was resilient to the applied extreme event but was slower in 2050 scenario.

The summer extreme event (precipitation reduction and air warming) had pronounced effects on above-ground biomass production, functional group composition and soil respiration of grassland ecosystem. Management by cutting influenced the grassland resistance to the summer extreme event. However, these effects were reversible one year after, both under actual and future climate.

More data on forage composition (carbohydrates, digestibility, cell walls) are needed to assess the total resilience of this ecosystem. How the species responded to the applied treatment is necessary in order to adapt permanent grassland in a future climate.

Active warming by infrared heaters

In June 2009, infrequent cut management was more productive than frequent management and mainly composed of grasses (94%). Competition for light, higher in infrequent cut, explains legumes and forbs decline. After heating in July 2009, there was no biomass production on both CX and TX treatments, all the vegetation was senescent except two species (T. officinalis, D.

glomerata). In August, actual climate scenario (CX) allowed better ecosystem resistance than the future one (TX) where biomass production was very low. Forbs became dominant on all treatments, legumes disappeared on TX treatment due to Trifolium repensmortality. Dominance of T. officinalis (forb) after extreme was probably due to its deeper roots and higher carbohydrates storage ability. In November, only vegetation under actual climate (CN, CX) and infrequent cut produced above-ground biomass, with dominance of grasses and disappearance of legumes. In 2010, above-ground biomass and functional group composition reach values of Spring 2009, meaning that resilience of grassland to scenario and summer extreme event was reached in frequent and infrequent cut.

Difference of air and soil temperatures between scenario (T) and control (C) treatments

during night-time

(°C)

Time (h)

20:00 22:00 00:00 02:00 04:00 06:00

-0.5 0.0 0.5 1.0 1.5 2.0

dT sol (T-C) dT air (T-C) June 11th 2009

Nocturnal passive warming under curtains

April 6th 2009

Daily infrared leaf temperature of grassland during the extreme event

Dates

08/07 10/07 12/07 14/07 16/07 18/07 20/07 22/07

(°C)

0 5 10 15 20 25 30 35 40

45 External control

TX CX 2009

Percentage of functional groups (grasses, legumes, forbs) before, during and after extreme event

10/04 30/0519/07 7/09 27/10

Soil respiration (µmol m-2s-1)

Dates 0

2 4 6 8 10 12

CN CX TN TX

2009 2010

HEATING DROUGHT

16/12 26/03 15/05 4/07 23/08

Dates 01/01 01/03 01/05 01/07 01/09 01/11 -8

-4 0 4 8 12 16 20 24

2009

Air, soil temperature (°C)

-8 -4 0 4 8 12 16 20 24

T soil CN T soil CX T soil TN T soil TX T air 2010

01/0330/04 29/0628/0827/10 2009

Dates 01/01 01/03 01/05 01/07 01/09 01/11

0 4 8 12 16 20 24 28 32

CN CX TN TX

Soil volumic water content (%) (line: 0-30cm; symbol: 0-15cm)

0 4 8 12 16 20 24 28 32 36

2009

2010 April 29th

Grasses Legumes Forbs

frequentinfrequent June 16th

CN

CX

TN

TX

frequentinfrequent August 24th

frequentinfrequent November 16th

frequentinfrequent May 10th

54

2122 2323

96

63 94

39 90

45 97

57 1621

25

36 10

24 31 2

1 4 2 2 3

43 12

45 55

2 43

7 39

54 2 46

52

37 33

7

56 6

61

29

71 71

29 60 39 1

60

2 38

63

1819 63

11 26

62

1622 63

1423

59

2120 60

1624

63

1522 66

925 ns

a b c

a c b b b a c a abbc

c a abb

a b

a

DROUGHT HEATING a

a a

infrequent cut

0 200 400 600 800

frequent cut Standing biomass (g m-2)

0 200 400 600

800 CN

CX TN TX

june june augoctober april august

2009 2010

april

ns ns

ns

113,5 106 176,5 174,5 17/08/2010

45,5 47 62 62,5 07/06/2010

263 266,5 232,5 232 11/05/2010

47 47 95 95 16/11/2009

53,6 59,6 77,6 79,6 01/10/2009

22 43 76 50 24/08/2009

43,0 84,0 85,0 183,0 27/07/2009

34,5 36 40,8 44 16/06/2009

215 215 200 200 12/05/2009

TX TN CX CN

Precipitations between cuts (mm)

Références

Documents relatifs

La multiplicité des méthodes d’estimation peut conduire à des résultats parfois très différents dans l’estimation des valeurs extrêmes (figure ), avec les approches purement

Specifically, we aimed at (i) quantifying the respective impacts of extreme spring frosts and droughts on the resistance, recovery and resilience of radial growth of three

We hypothesized a strong relationship between above- ground (herbaceous species) and below-ground (Collem- bola) compartments along a riparian flooding gradient and tested whether

During recovery from extreme events, root growth rate shows a significant increase in elevated CO2 compared to ambient CO2 (consequent to higher above-ground biomass production)

Marquis RJ, Lill JT, Forkner RE, Le Corff J, Landosky JM and Whitfield JB (2019) Declines and Resilience of Communities of Leaf Chewing Insects on Missouri Oaks Following Spring

This study therefore tested (i) whether or not there was a close relationship between biomass production and the community-weighted mean trait values (CWM), as expected from

Study of new rare event simulation schemes and their application to extreme scenario generation.. Ankush Agarwal, Stefano de Marco, Emmanuel Gobet,

GLM (type I sum of squares) table of F-values for effects of block, plot, fertilization (FERT), log-transformed plant species richness(logSR), plant functional group richness