Impacts of climate change on the production of crops used in French livestock systems - SHMU
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Impacts of climate change
on the production of crops used
in French livestock systems
Ruget F.(1), Moreau J.-C., Ferrand M., Poisson S.(2), Gate P.,
Lacroix B., Lorgeou J.(3), Cloppet E. and Souverain F. (4).
(1) UMR 1114 EMMAH INRA 84914 AVIGNON cedex 9
(2) Institut de l’Elevage, Auzeville
31326 CASTANET -TOLOSAN and 149 Rue de Bercy 75011 PARIS,
(3) Arvalis Institut du végétal, La Minière 78210 Guyancourt/
31450 Baziège/91170 Boigneville,
(4) Météo-France, 42 Av G Coriolis 31000 Toulouse
Introduction
Aim of the project : assess the possible effects of climate change on the main
livestock systems in France
Method : using climate projections of GCM to calculate agroclimatic indices or
as inputs of a crop model
Aim of this talk : present some of the results of this project
temporal and spatial distribution of main climate changes in France,
some agroclimatic indices,
effects of climate change mainly on forage crops,
show some examples of system adaptation.
Climate COST 734 Zamok Topol'cianky 1. Climate 4 May 2011
Climate Temperatures and rain changes
Scenario A2 , distant futur (2070-2099)
Distant A2 - Reference T °C Distant A2 - Reference T °C
Spring Summer
++ ++++
+ ++
Distant A2 / Reference Rain Distant A2 / Reference Rain
Spring Summer
+
Data from CNRM
Météo-France - (0,4 = - 60%)
ACTA CC
COST Project
734 Zamok Topol'cianky 4 May 2011
1. Climate
Climatic indicators COST 734 Zamok Topol'cianky 2. Climatic indicators 4 May 2011
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
COST 734 Zamok Topol'cianky 2. Climatic indicators 4 May 2011
Soil trafficability for early grazing
more
less
Number of years among ten when more or less
unfavourable conditions will occur in the distant
A2 scenario
Agro-climatic indicator for the soil trafficability for early grazing is the occurrence
of a period of 5 days with rainfall higher than 60 mm occurs at the beginning of
spring (500 °C. d after 1st feb.)
We compare the number of years with this occurrence in each temporal period
COST 734 Zamok Topol'cianky 2. Climatic indicators 4 May 2011
Wheat : increase of shrivelling
Arpège 2007- Scenario A2
% of decrease of KW as function of the reference period
Trémie semé le 20 octobre
30
84
25 5
3147 3446
33
pertes de PMG s imulées
Loss of yield 20 11
78 64
45
37 3 54 2163 12
69
67
(model Panoramix) 3585 51 71
1589
25 2071-2096
2071 à 2096
15 2 40 87
2021-2046
2021 à 2046
56 6
in the near future (red) bisecting line
Bissectrice
80 14
in the distant future 10
(green) 29
5
0
0 5 10 15 20 25 30
% of decrease ofperte
thede PMG
1000de la pèriode
kernel de référence
weight (KW) of the reference period
More days with high temperatures during grain filling shrivelling worse grain filling
COST 734 Zamok Topol'cianky 4. Phenological models
2. Climatic indicators 4 May 2011Crops: grass, alfalfa, maize COST 734 Zamok Topol'cianky 3. Crop model results 4 May 2011
Short or long term and CO2 effects
near A2 – OB near A2 – OB
with CO2 without CO2
distant A2 – OB distant A2 – OB
with CO2 without CO2
Ratio between the difference future-present and the present yield of grass
OB= observed=reference, soil with low water reserve (66 mm), mowing (spaced out cuttings)
COST 734 Zamok Topol'cianky 3. Crop model results 4 May 2011Annual production for alfalfa and grass
near A2, green
distant A2 red
distant B1 orange
Alfalfa Grass
Ratio between the difference future - present and the present
production for 34 actual and ficitve stations
COST 734 Zamok Topol'cianky 3.soil
Cropwith highresults
model water reserve (208 mm).
4 May 2011Changes of seasonal daily production
60
d_A2
50
n_A2
d_B1
40
obs
30
20
10
0
1 16 31 46 61 76 91 106 121 136 151 166 181 196 211 226 241 256 271 286 301 316 331 346 361
-10
Aurillac (Lon 02° 26', lat 44° 55', altitude 639 m, Massif Central)
Daily dry matter production (kg.ha-1.day1), in the western slope of Massif Central
COST 734 Zamok Topol'cianky 3. Crop model results 4 May 2011Livestock systems COST 734 Zamok Topol'cianky 4. Livestock systems adaptation 4 May 2011
Some french dairy and meat systems
intensive and economical dairy system meat and milk, maximum grazing
ingestion en kgMS par jour légende ingestion en kgMS par jour légende
18 Ens Herbe Ens Herbe
18
16 16
14 Ens Maïs Ens Maïs
14
12
Foin 12
10 Foin
10
8
eurubannage 8
6 eurubannage
4
6
2 pature 4
2 pature
0 1-janv 15-févr 30-avr 30-juin 1-sept 15-nov 1-janv
0 1-janv 15-avr 1-juin 1-août 15-oct 1-janv
Bretagne, Rennes Lorraine, Nancy
meat, grazing
maize
hay
semi-intensive mixed dairy system
Limousin
grazing grass
ingestion en kgMS par jour légende
18
16
14
12
Ens Herbe
Ens Maïs
silage
10 Foin
8
6 eurubannage
4
2 pature
0 1-janv 15-mars 15-avr 20-juin 15-sept 1-nov 1-janv
Ségalas, Sud-Ouest
Massif-Central, Aurillac
maize and zero grazing dairy system
ingestion en kgMS par jour légende
18 Ens Herbe
16
14 Ens Maïs
12
10 Foin
8
6 eurubannage
4
2 pature
0 1-janv 1-mars 15-mars 15-juin 1-sept 20-oct 1-nov 1-janv
Bassin Adour, Pau
COST 734 Zamok Topol'cianky 4. Livestock systems adaptation 4 May 2011Dairy cows in Lorraine (NE)
Nancy : present (and recent past) 1980-2006
ingestion en kgMS par jour légende
18 Ens Herbe
16
14 Ens Maïs
12
10 Foin
8
6 eurubannage
4
2 pature
0 1-janv 15-avr 1-juin 1-août 15-oct 1-janv
Near future : 2020-2050
ingestion en kgMS par jour légende
18 Ens Herbe
16
14 Ens Maïs
12
10 Foin
8
6 eurubannage
4
2 pature
0 1-janv 13-avr 1-juin 1-août 25-sept 1-janv
Distant future 2070-2099
ingestion en kgMS par jour légende
18 Ens Herbe
16
14 Ens Maïs
12
10 Foin
8
6 eurubannage
4
2 pature
0 1-janv 1-avr 1-juin 1-août 7-oct 1-janv
COST 734 Zamok Topol'cianky 4. Livestock systems adaptation 4 May 2011Conclusion
Most important results :
changes of dates : all is earlier (more sure because processes involved
are well known)
changes in production seem to be low in the near future and high in the
distant future, especially in the "pessimistic" scenario, which seems to be
near from reality. In the distant future, they depend more on the effect of CO2
which is in debate.
Moreover, the importance of the processes involved in stresses will take more
importance : as the crops will take place in non optimal conditions, some
processes like setting of roots and the volume where they can extract water
or nutrients become more and more important, and the ability to understand
and predict it will have more influence than now.Thank you for your attention
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