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F. RUGET (1), J.-C. MOREAU (2), M. FERRAND (2), S. POISSON (2), P. GATE (3), B. LACROIX (3), J. LORGEOU (3), E. CLOPPET (4), AND F. SOUVERAIN (4) (1) UMR.

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Presentation on theme: "F. RUGET (1), J.-C. MOREAU (2), M. FERRAND (2), S. POISSON (2), P. GATE (3), B. LACROIX (3), J. LORGEOU (3), E. CLOPPET (4), AND F. SOUVERAIN (4) (1) UMR."— Presentation transcript:

1 F. RUGET (1), J.-C. MOREAU (2), M. FERRAND (2), S. POISSON (2), P. GATE (3), B. LACROIX (3), J. LORGEOU (3), E. CLOPPET (4), AND F. SOUVERAIN (4) (1) UMR 1114 EMMAH INRA 84914 AVIGNON CEDEX 9 (RUGET@AVIGNON.INRA.FR), (2) INSTITUT DE L’ELEVAGE, AUZEVILLE 31326 CASTANET -TOLOSAN ET 149 RUE DE BERCY 75011 PARIS, (3) ARVALIS INSTITUT DU VÉGÉTAL, LA MINIÈRE 78210 GUYANCOURT/ 31450 BAZIÈGE/91170 BOIGNEVILLE, (4) 42 AV G CORIOLIS 31000 TOULOUSE Effect of climate change in herbivorous livestock systems, in the French area. 9th EMS Annual Meeting & 9th ECAM in Toulouse 28 sept. 2 oct. 2009

2 Content Climatic date, and their use Climate analysis, with spatialized MFA Use of climatic indicators Use of a phenological model Use of a crop model (STICS): adaptations of the model, several results, adaptations of the crops 9th EMS Annual Meeting & 9th ECAM in Toulouse 28 sept. 2 oct. 2009

3 9th EMS Annual Meeting & 9th ECAM in Toulouse 28 sept. 2 oct. 2009 Climatic data : origin and use Série«Réf»Sé «Ré» Sé Se A2 Série B1L 2070 2099 SrieA2L 19801960 2006 Srie Sé A2 Srie B1p 2020 2049 SérieA2p Série«Ré» Ref series Série S A2 Série B1L 2070 2099 SriesA2L 19801960 2006 S e rie Sé A2 Sries B1p 2020 2049 SérieA2p Gross data for the studies of climate features and (agro)-climatic indicators Use of the STICS crop model for grass, alfalfa and corn 2070 2096 19801960 2006 2020 2046 Série Sé Obs B1Lano A2Lano B1pano A2pano 2070 2096 19801960 2006 2020 2046 Série Series Obs B1Lano A2Lano B1pano A2pano B1Lano A2Lano B1pano A2pano Obs+ (x) anomaliesObs+ (x) anomaliesObs+ (x) anomalies 717 ppm462 ppm 532 ppm 360 ppm 441 ppm Data from the ARPEGE model (Déqué, CNRM) 1. Use of climatic data

4 New climates, appearing at the end of the century (40 % of the French area) Multiple factor analysis, including spatial variables Actual climate (1970-2006) in the future classes 9th EMS Annual Meeting & 9th ECAM in Toulouse 28 sept. 2 oct. 2009 2. Climate analysis How will change the climate ?

5 Indicators dates of practices defined according to the zones (MFA) criteria defined for each season  first grazing date: several days without rain (favourable) or high rain (saturated soil, un favourable)  production : too high temperatures, low or very high rainfall  hay harvest: several consecutive days without rain for drying criteria calculation and mapping 9th EMS Annual Meeting & 9th ECAM in Toulouse 28 sept. 2 oct. 2009 3. Climatic indicators

6 Favourable and unfavourable events Far future (2070-2099), scenario A2 Number of years (/10 years) as function of the present conditions Unfavourable conditions for first grazing date : high rain 5 days with more than 60 mm more frequent less frequent a 9th EMS Annual Meeting & 9th ECAM in Toulouse 28 sept. 2 oct. 2009 3. Climatic indicators

7 Wheat: more elevated temperature during grain filling shrivelling worse grain filling Wheat : increase of shrivelling Loss of yield in the next future (red) in the far future (green) 2071-2096 2021-2046 bissectrice line % of decrease of the 1000 kernel weight (KW) of the reference period % of decrease of KWt as function of the reference period 9th EMS Annual Meeting & 9th ECAM in Toulouse 28 sept. 2 oct. 2009 4. Phenological models

8 How was the model STICS adapted and used? Effect of temperature –introduction or reestimation of high thresholds (developement, leaf growth, grain filling) Effect of CO 2 : –crop production : CO 2 fixation –crop transpiration : decrease of stomatal conductance –not any change on morphogenesis Soil types: high or low water reserves Agricultural practices: –Grassland and alfalfa harvests starting at a heat sum (adapted to changes),early and frequent use (grazing) or late cuts (hay) –for corn, present or adapted (earlier sowings, later cultivars) practices 9th EMS Annual Meeting & 9th ECAM in Toulouse 28 sept. 2 oct. 2009 5. Crop models

9 Grassland: first cut dates, number of uses (grazing) Number of uses (grazing each 500°C.day) (soil with low available water) Number of days of advance for first grazing, at 500 °C.day after the beginning of growth 9th EMS Annual Meeting & 9th ECAM in Toulouse 28 sept. 2 oct. 2009 5. Crop models

10 Grassland: annual production Low available water 9th EMS Annual Meeting & 9th ECAM in Toulouse 28 sept. 2 oct. 2009 5. Crop models High available water Grazing with livestock each 500 °C day Variability of production as function of zone, period and soil available water

11 Alfalfa production High soil available water Annual yield increased in all the conditions : no problem of water (deep roots) no problem of nitrogen (symbiotic fixation) 9th EMS Annual Meeting & 9th ECAM in Toulouse 28 sept. 2 oct. 2009 5. Crop models

12 During the last 30 years In the future decrease of length of the life cycle in the next past increase in yield, especially with CO2 effect on transpiration Maize 9th EMS Annual Meeting & 9th ECAM in Toulouse 28 sept. 2 oct. 2009 5. Crop models grain yield, without CO2 effect grain yield, with CO2 effect present near future (B1) far future (B1) far future (A2)

13 Conclusion Methods Different uses of present (actual) and estimated (present and future) data Different types of models : climatic indicators, agro-climatic and phenological models, crop models Main results : for grass production, in the next future, increase, in the far future increase depending on water (soil abilities, transpiration effect of CO2) and nitrogen (legumes) availability, sometimes more risks for harvests for grain crops, more risks of grain shrivelling, the yield increase depends on the CO2 effect (uncertainty on photosynthesis and mainly on transpiration and on phenology and morphogenesis processes) 9th EMS Annual Meeting & 9th ECAM in Toulouse 28 sept. 2 oct. 2009 6. Conclusion


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