Supplementary Information
45.0
40.0
35.0
Temperature, C
30.0
25.0
20.0
15.0
10.0
5.0
0.0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Thermocouple position on temperature gradient plate
Supplementary Figure S1. Temperatures on the temperature gradient plate, measured
with thermocouples placed directly on the surface of the plate (- -) underneath the Petri
dishes containing pollen germination medium or in the pollen media itself (). The
plate was run twice for each pollen type; once with a 5.6-27.4 °C gradient and once with a
24.6-45.4 °C gradient. Linear regressions for these two gradients were y=-1.67x + 29.68
(R2=0.98) and y=-1.58x+46.04 (R2=0.99) on the plate surface and y=-1.65x + 30.21
(R2=0.98) and y=-1.30x+43.75 (R2=0.96) in the pollen media, respectively.
(a)
Air temperature ( C)
32
30
28
26
24
22
0:00
6:00
12:00
18:00
0:00
6:00
12:00
18:00
0:00
6:00
Time of day (h:mm)
12:00
18:00
0:00
(b)
Relative humidity (%)
100
95
90
85
80
0:00
6:00
12:00
18:00
0:00
Supplementary Figure S2. Diurnal air temperature (a) and relative humidity (b) of
field environment from two days before anthesis to anthesis for rice cultivar, N22
(dotted line; on 2-3 August 2011), and for cultivars CG14 and IR64 (solid line; on
15-16 August 2011).
Supplementary Table S1.
In vitro germination of pollen of rice cultivar IR64 at different concentrations of
Ca(NO3)2.4H2O in pollen germination medium. Values are means of four replicates. (SED
= 12.5%, 15 degrees of freedom)
Ca(NO3)2.4H2O, g l-1 0.030
Germination, %
37.5
(standard error)
(10.8)
0.040
39.5
(10.6)
0.050
46.8
(9.9)
0.055
73
(4.2)
0.060
78.2
(5.4)
0.070
52.2
(9.2)
Supplementary Table S2.
Comparisons of models of pollen germination of three rice cultivars at temperatures
between 5.6 and 45.4 °C. Models compared are multiplicative (Mult.) or subtractive
(Subt.) probability models with either a linear (Lin.) or an exponential (Exp.) effect of
temperature (T) on the variation in maximum temperature limits (sx). The value of the
parameter, r, is shown for exponential models. Increases in residual deviances (RD) are
shown relative to model (1).
Model Effect
of T
r for Source of variation
d.f.
Exp.
Deviance
Deviance
Prob-
Ad-
or sum of
or F ratio
ability
justed
squares*
R2
4
338437
6958 <0.001 0.9969
77
936.6
…
on sx
a) CG14
1 Mult. Exp.
1.164 Regression
Residual deviance
2 Mult. Lin.
…
Increase in RD (2-1)
1
60.93
5.01
<0.01 0.9968
3 Subt.
Exp.
1.072 Increase in RD (3-1)
1
89.14
7.33
<0.01 0.9967
4 Subt.
Lin.
…
2
175.4
8.95
<0.01 0.9965
4
399215
70
881.1
…
-2.77
Increase in RD (4-1)
b) IR64
1 Mult. Exp.
1.045 Regression
Residual deviance
7927 <0.001 0.9975
2 Mult. Lin.
…
Increase in RD (2-1)
1
-34.89
3 Subt.
Exp.
1.118 Increase in RD (3-1)
1
171.5
13.6 <0.001 0.9971
4 Subt.
Lin.
…
2
163.0
6.47
4
1699157
73
3532
…
Increase in RD (4-1)
ns 0.9977
<0.01 0.9972
c) N22
1 Mult. Exp.
1.164 Regression
Residual deviance
8778 <0.001 0.9977
2 Mult. Lin.
…
Increase in RD (2-1)
1
328.6
6.79
<0.05 0.9975
3 Subt.
Exp.
1.067 Increase in RD (3-1)
1
3.11
0.06
ns 0.9977
4 Subt.
Lin.
…
2
672.0
6.58
<0.05 0.9974
Increase in RD (4-1)
ns = not significant (P > 0.05); d.f. = degrees of freedom