THEME – 2 Identifying climate patterns during the crop growing cycle from 30 years of CIMMYT elite...
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Identifying climate patterns during the crop growing cycle from 30 years of CIMMYT elite spring Wheat international yield trials Zakaria KEHEL, Jose CROSSA and Matthew REYNOLDS Rabat-Morocco. 24-27 June 2014
Transcript of THEME – 2 Identifying climate patterns during the crop growing cycle from 30 years of CIMMYT elite...
Identifying climate patterns during the crop growing cycle from 30 years of CIMMYT elite spring Wheat
international yield trials
Zakaria KEHEL, Jose CROSSA and Matthew REYNOLDS Rabat-Morocco. 24-27 June 2014
Climate change for wheat development
Reduced yields. High temperatures and drought-related stress.
Increased irrigation.
Planting and harvesting changes. Shifting seasonal rainfall patterns delay planting and harvesting.
More pests. Lower-latitude pests may move to higher latitudes.
Climatic variable Intercept Slope P(Intercept) P(Slope) R2
tmin_veg 13.61 -0.003 0.52 0.78 0.32
tmin_rep -13.40 0.012 0.57 0.31 4.23
tmin_gf -33.92 0.024 0.12 0.03 18.04
tmin_seas -35.12 0.023 0.05 0.01 23.76
tmax_veg -39.25 0.030 0.09 0.01 22.55
tmax_rep -41.28 0.032 0.19 0.04 15.96
tmax_gf -64.12 0.046 0.04 0.00 29.31
tmax_seas -80.13 0.052 0.00 0.00 56.44
dtr_veg -52.87 0.033 0.02 0.00 29.12
dtr_rep -27.88 0.020 0.25 0.09 11.18
dtr_gf -30.19 0.022 0.04 0.00 28.88
dtr_seas -45.01 0.029 0.00 0.00 43.37
tavg_veg -12.82 0.013 0.50 0.17 7.73
tavg_rep -27.34 0.022 0.27 0.08 12.18
tavg_gf -49.02 0.035 0.06 0.01 25.58
tavg_seas -57.62 0.037 0.00 0.00 46.55
srad_veg 0.76 0.007 0.98 0.59 1.22
srad_rep 68.20 -0.025 0.15 0.28 4.80
srad_gf -13.45 0.018 0.62 0.20 6.61
srad_seas -26.33 0.022 0.22 0.05 15.63
vpd_veg -7254.53 4.018 0.03 0.02 20.31
vpd_rep -6303.50 3.687 0.26 0.20 6.89
vpd_gf -15138.76 8.380 0.04 0.02 19.47
vpd_seas -11316.95 6.195 0.01 0.00 29.15
dl_veg 24.28 -0.007 0.00 0.00 30.62
dl_rep 39.87 -0.014 0.00 0.00 65.58
dl_gf 24.37 -0.006 0.00 0.00 54.54
dl_seas 15.95 -0.002 0.00 0.20 6.88
rhum_veg 499.79 -0.221 0.01 0.01 22.73
rhum_rep 90.47 -0.020 0.66 0.85 0.15
rhum_gf 143.06 -0.049 0.35 0.52 1.71
rhum_seas 344.06 -0.146 0.04 0.07 13.02
gdd_veg 2619.92 -0.859 0.14 0.33 3.98
gdd_rep 644.12 -0.124 0.00 0.08 12.32
gdd_gf -12196.80 6.717 0.01 0.00 32.38
gdd_seas -8765.28 5.667 0.07 0.02 19.98
dth_mean 531.85 -0.221 0.00 0.01 24.27
veg_days 485.83 -0.208 0.01 0.02 20.19
rep_days 82.27 -0.028 0.13 0.29 4.66
gf_days -576.07 0.1201 0.02 0.01 24.61
What does it mean? Constraints
Year tmin_gf tmax_gf tmin_rep tmax_rep tmin_veg tmax_veg
p-value cluster p-value cluster p-value cluster p-value cluster p-value cluster p-value cluster
1995 0.0000 High 0.0001 High 0.3658 Random 0.1679 Random NaN NaN 0.3392 Random
1996 0.0003 High 0.0000 High 0.4336 Random 0.0815 High 0.5036 Random 0.0501 High
1997 0.0320 High 0.0097 High 0.3213 Random 0.8897 Random NaN NaN 0.1084 Random
1998 0.0003 High 0.0000 High NaN NaN 0.8988 Random NaN NaN 0.4388 Random
1999 0.0000 High 0.0000 High 0.0968 High 0.0103 High NaN NaN 0.0101 High
2000 0.0021 High 0.0000 High 0.9595 Random 0.0859 High 0.1365 Random 0.0028 High
2001 0.0000 High 0.0000 High 0.0033 High 0.0021 High NaN NaN 0.1795 Random
2002 0.0010 High 0.0000 High 0.8590 Random 0.9247 Random 0.6714 Random 0.4215 Random
2003 0.1010 Random 0.1348 Random 0.1327 Random 0.0818 High NaN NaN 0.2048 Random
2004 0.0000 High 0.0000 High 0.5892 Random 0.9132 Random NaN NaN 0.1121 Random
2005 0.0514 High 0.0032 High 0.0253 High 0.0008 High 0.4310 Random 0.0037 High
2006 0.0001 High 0.0000 High 0.6581 Random 0.4251 Random NaN NaN 0.4108 Random
2007 0.0004 High 0.0000 High 0.2256 Random 0.1020 Random NaN NaN 0.5464 Random
2008 0.0001 High 0.0000 High 0.4245 Random 0.0955 High NaN NaN 0.1207 Random
2009 0.0000 High 0.0000 High 0.0148 High 0.0011 High 0.9666 Random 0.2163 Random
Any pattern?
Where hot and where cold? VEG
Where hot and where cold? REP
Where hot and where cold? GF
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
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ays
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vg_v
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tavg
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tmax
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PC1
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vpd
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vg_s
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tmax
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tmax
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R5
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R5
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rep
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CL
R1
0m
mC
L
PC2
PCA analysis to understand
But patterns are lost!
Self-Organized Maps SOM
SOM for Tmin
SOM for Tmax
SOM for stages length
Clusters
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%C
lust
er1
Clu
ster
2
Clu
ster
3
Clu
ster
4
Clu
ster
5
Clu
ster
6
Clu
ster
7
Clu
ster
8
Clu
ster
9
Clu
ster
10
Y2009
Y2008
Y2007
Y2006
Y2005
Y2004
Y2003
Y2002
Y2001
Y2000
Y1999
Y1998
Y1997
Y1996
Y1995
Y1993
Y1992
Y1991
Y1990
Y1989
Y1988
Y1987
Y1986
Clusters and years
red for VEG,
green for REP
and blue for GF
Relevance of all climatic variables for the SOM-
map grids
Clustering all locations now
Conclusions
• The wheat cycle is facing a significant rise in temperature, especially tmax • Humidity and precipitations were reduced over years for most ESWYT
locations • Neighboring locations had similar climatic profile except for Middle East and
Central Europe • PC analysis was not able to identify any of the spatial or temporal patterns
present in the data and hence cannot be used to investigate any climate change
• The SOM approach was able to identify regional and temporal change Non
linearity • Patterns of change in climatic profiles + genotypic sensitivities Breeding
strategies
