Prediction of Field Germination
Using
Wet Thermal Accumulation
Jennifer Coleman, Bruce Roundy, Brad Jessop, and April Hulet
Brigham Young University
Department of Plant and Wildlife Sciences
Provo, Utah
Study Methods
Created model
Tested model
Tested model
Constant
temperatures
Fluctuating
temperatures
Field seedbag
retrievals
Related model
Emergence & Survival
WetDevelopment
Thermal Accumulation
Model
¾ Germination requirements
1) Water
¾ Above soil moisture threshold (Wb)
2) Temperature
¾ Above threshold base temperature (Tb)
¾ Thermal time requirement (degree days)
WetDevelopment
Thermal Accumulation
Model
Germination requirements
¾ Agropyron cristatum
1) Soil moisture threshold
¾ Wb = -1.5 MPa
¾
W = -1.0 MPa
2) Base temperature threshold ¾ Tb = 0°C
¾
3) Thermal time requirement
T = 20°C
¾ 5 days at 20°C = 50%
(20°C -- 0°C)*(5
0°C)*(5 days)
days)==100
100wet
degree
days
degree
days
Model Development
¾Crested wheatgrass requires 100 wet degree days for 50%
germination
¾Days to 50% germination:
35
¾ 50 at 2° C
30
Temperature C
¾100 at 1° C
25
20
15
10
5
¾ 5 at 20° C
0
0
500
1000
Hour of the day
1500
2000
Species
Common Name
Cultivar
Source
Year
Collected
Achillea millefolium
eagle yarrow
N/A
Eastern Washington
2003
Achillea millefolium
white yarrow
N/A
Eastern Washington
2003
Enceliopsis nudicaulis
nakedstem sunray
Linum lewisii
Lewis flax
Linum perenne
blue flax
Lupinus arbustus
longspur lupine
Agropyron cristatum
crested wheatgrass
Hycrest
Agropyron desertorum
crested wheatgrass
Nordan
MT
2003
Psuedoroegneria spicata
bluebunch
wheatgrass
Secar
Eastern Washington
2003
Psuedoroegneria spicata
bluebunch
wheatgrass
Anatone
UDWR-commercially
grown
2003
Elymus elymoides
squirreltail
Sanpete
Sanpete Co., UT
2003
Bromus tectorum
cheatgrass
N/A
Lookout Pass, UT
2005
Bromus tectorum
cheatgrass
N/A
Spanish Fork, UT
2005
Bromus tectorum
cheatgrass
N/A
Skull Valley, UT
2005
2003
Provo, UT
Appar
UDWR-commercially
grown
2001
2003
2003
Study Methods
Created model
Tested model
Tested model
Constant
temperatures
Fluctuating
temperatures
Field seedbag
retrievals
Related model
Small plot emergence & survival
Model Development:
Thermal time requirement
• Constant Temperatures:
– 5-35 °C
• What we measured:
– Time required for germination
• 10%
• 25%
• 50%
• What we needed to know:
– Germination rate (1/days to % germination)
Model Development:
Curve fitting
Elymus elymoides
0.25
0.2
80
1/days to germination
days to 50% germination
90
70
60
50
40
30
20
0.15
0.1
0.05
10
supraoptimal
suboptimal
optimal
0
0
5
10
15
20
25
30
Temperature (°C)
35
40
45
0
0
10
20
30
Te mpe rature (°C)
40
50
Study Methods
Created model
Tested model
Tested model
Constant
temperatures
Fluctuating
temperatures
Field seedbag
retrievals
Related model
Small plot emergence & survival
Lab verification:
mid-late May
Spring temperature simulations
early-mid March
mid-late April
35
Temperature C
30
25
20
15
10
5
0
0
500
1000
Hour of the day
1500
2000
Lab verification:
Spring simulation
Predicted
Actual
18
days to 10% germination
16
14
12
10
8
6
4
2
0
Agcr
Elel SVBrte Lipe
Warm
Agcr
Elel SVBrte Lipe
Cool
Lab verification:
Conclusions
• Models can be used to predict
germination response to fluctuating
temperatures
™Thermal accumulation requirement determined
by constant temperature trials tends to
overestimate time to germination
Study Methods
Created model
Tested model
Tested model
Constant
temperatures
Fluctuating
temperatures
Field seedbag
retrievals
Related model
Small plot emergence & survival
Field verification:
Skull Valley
Lookout Pass
Study Sites
Seedbed Monitoring
• Temperature
– Depths:
• 1-3 cm
• 13-15 cm
• 28-30 cm
• Moisture
– Depths:
• 1-3 cm
• 13-15 cm
• 28-30 cm
Study Sites
Block Year
Small Plots
1 retrievals
Year 1
• 19 seedbag
Seedbags
1
Skull Valley
BlockSmall
1 Plots
2
–
–
–
–
Year 2
Seedbags
Small Plots
Fall
1 Year 1
Seedbags
2
BlockSmall
2 Plots
2
Year
2
Winter
Seedbags
Small Plots
Early Spring
1 Year 1
Seedbags
3
BlockSmall
3 Plots
Late Spring
2 Year 2
Seedbags
Small Plots
Year 1
Seedbags
BlockSmall
4 Plots
2 Year 2
Seedbags
1
4
Lookout Pass
Thermal accumulation: 2 methods
Warm
1) Thermal
accumulation
resumes
= Σ wet periods
Seeds
begin
to germinate
Thermal
accumulation
stops
2) Thermal accumulation
begins
again = wet period
Germination
stops
Unimbibed
Germination
Wet
Dry
Field verification:
Seedbag Retrievals
1) 2 methods
•
•
Thermal accumulation = each wet period
Thermal accumulation = Σ wet periods
Model Accuracy:
method = ∑ wet periods
wet period
Σ wet periods
1
0.9
0.8
% correct
0.7
0.6
0.5
0.4
0.3
A
B
A
B
A
B
0.2
0.1
0
d10
d25
d50
Field verification:
Seedbag Retrievals
1) 2 methods
•
•
Thermal accumulation = each wet period
Thermal accumulation = Σ wet periods
2) 3 soil moisture thresholds
•
-0.5, -1.0, -1.5 MPa
Model Accuracy:
moisture threshold = -1.5 MPa
-0.5
-1
-1.5
1
0.9
0.8
% correct
0.7
0.6
0.5
0.4
0.3
B
C
A
C
B
A
B
A
0.2
0.1
0
d10
d25
d50
A
Field verification
1) 2 methods
•
•
Thermal accumulation = each wet period
Thermal accumulation = Σ wet periods
2) 3 soil moisture thresholds
•
-0.5, -1.0, -1.5 MPa
3) 3 germination predictions
•
10%, 25%, 50%
Model Accuracy:
Lookout Pass
method = ∑ wet periods
moisture threshold = -1.5 MPa
d10
d25
d50
1
0.9
0.8
% correct
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Agcr
Brte
Elel
Pssp
Lipe
Model Accuracy:
Skull Valley
method = ∑ wet periods
moisture threshold = -1.5 MPa
d10
d25
d50
1
0.9
0.8
% correct
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Agcr
Brte
Elel
Pssp
Lipe
Model Accuracy:
method = ∑ wet periods
wet base = -1.5
LP
SV
1
0.9
0.8
% correct
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Agcr
Brte
Elel
Pssp
Lipe
Field verification
1) 2 methods
•
•
Thermal accumulation = each wet period
Thermal accumulation = Σ wet periods
2) 3 soil moisture thresholds
•
-0.5, -1.0, -1.5 MPa
3) 3 germination predictions
•
10%= 87% 25%= 90% 50%= 77%
Model Accuracy:
Season
d10
d25
d50
1
0.9
0.8
% accurate
0.7
0.6
0.5
A
0.4
B
0.3
0.2
A
A
B
C
C
C
B
A
A
C
0.1
0
Fall
Winter
early Spring
late Spring
Field verification:
Conclusions
1) 2 methods
•
•
Thermal accumulation = each wet period
Thermal accumulation = Σ wet periods
2) 3 soil moisture thresholds
•
-0.5, -1.0, -1.5
3) 3 germination predictions
•
10%= 87% 25%= 90% 50%= 77%
4) Overestimates germination time with
highly fluctuating temperatures
Study Methods
Created model
Tested model
Tested model
Constant
temperatures
Fluctuating
temperatures
Field seedbag
retrievals
Related model
Small plot emergence & survival
Small Plots
Block Year
1
1
2
1
2
2
1
3
2
1
4
2
Small Plots
Seedbags
Small Plots
Seedbags
Small Plots
Seedbags
Small Plots
Seedbags
Small Plots
Seedbags
Small Plots
Seedbags
Small Plots
Seedbags
Small Plots
Seedbags
Seedling Emergence:
Year 1 plots
# seedlings/m row
Lookout Pass
Agcr
Brte
7/2
10/10
Elel
Lipe
Pssp
100
90
80
70
60
50
40
30
20
10
0
3/24
Season 1
1/18
4/28
Season 2
8/6
Seedling Emergence:
Year 2 plots
Lookout Pass
# seedlings/m row
Agcr
Brte
Elel
Lipe
Pssp
100
90
80
70
60
50
40
30
20
10
0
4/18
5/8
5/28
6/17
Season 2
7/7
7/27
Seedling Emergence:
Reduced yr 2 emergence
Lookout Pass Precipitation Data
Season 1
Season 2
Ap
ri l
M
ay
Ju
ne
Ju
l
Au y
Se g us
t
pt
em
b
O er
ct
ob
N
ov e r
em
b
D
ec er
em
be
r
80
70
60
50
40
30
20
10
0
Ja
nu
Fe ary
br
ua
ry
M
ar
ch
precipitation (mm))
2005
• Low temperatures for 2 weeks in Feb
• less germination = less emergence in Year 2 plots
Seedling Survival:
Reduced season 2 survival
Lookout Pass Precipitation Data
Season 2
Ap
ri l
M
ay
Ju
ne
Ju
l
Au y
Se g us
t
pt
em
b
O er
ct
ob
N
ov e r
em
b
D
ec er
em
be
r
Future Work:
•
•
Season 1
80
70
60
50
40
30
20
10
0
Ja
nu
Fe ary
br
ua
ry
M
ar
ch
precipitation (mm)
2005
• High
germination
&
Deeper
sensor
analysis
Root growth/survival modelling
emergence ≠ high survival
Seedling Emergence:
Year 1 plots
Lookout Pass
100
90
80
% of seeds sown
70
60
% germinated
% emerged 2006
50
% survived 2006
% survived 2007
40
30
20
10
0
Agcr
Brte
Elel
Lipe
Pssp
Seedling Emergence:
Year 1 plots
Skull Valley
100
90
80
% of seeds sown
70
60
% germinated
% emerged 2006
50
% survived 2006
% survived 2007
40
30
20
10
0
Agcr
Brte
Elel
Lipe
Pssp
Conclusions
• Can a wet thermal accumulation model be
used to predict germination?
– Yes, with about 80% accuracy
• Exception: species with special requirements
• Seedbag ≠ Seedbed conditions?
• Precautions:
– Dry conditions
– High temperature and moisture fluctuations
Management Implications:
• So what?
– Better selection of species
– Specific herbicide application
– Timed mechanical control
– Weed vs. seeded emergence
Questions?
Seedling Emergence:
Year 2 plots
Skull Valley
Agcr
Brte
Elel
Lipe
Pssp
# seedlings/m row
60
50
40
30
20
10
0
4/18
5/8
5/28
6/17
Season 2
7/7
7/27
Seedling Survival:
Season 2
Lookout Pass
Skull Valley
Agcr
1
6.7
2
6.7
1
2
2
1.8
Elel
2.7
2.6
1.3
1.3
Lipe
1.3
1
0.1
0.7
Pssp
6.9
5.4
1.2
1.4
Year seeded
Seedling Emergence:
Year 1 plots
Skull Valley
Agcr
Brte
Elel
Lipe
Pssp
# seedlings/m row
60
50
40
30
20
10
0
3/24
7/2
Season 1
10/10
1/18
4/28
Season 2
8/6
Skull Valley Precipitation Data
2006
2007
M
ay
Ju
ne
Ju
l
Au y
Se g us
t
pt
em
b
O er
ct
ob
N
ov e r
em
b
D
ec er
em
be
r
Less emerged at Skull Valley
Yr 1: 2 wk in Feb, low temp and no
precip
Ap
ri l
80
70
60
50
40
30
20
10
0
Ja
nu
Fe ary
br
ua
ry
M
ar
ch
precipitation (mm)
2005
Model Accuracy:
Retrievals 4-7
20
0
0.2
0.4
10
0.6
0.8
5
1
0
27-Feb
1.2
2-Mar
6-Mar
10-Mar
14-Mar
18-Mar
22-Mar
26-Mar
1.4
-5
Temperature
Soil Moisture
Soil Moisture (-MPa)
Soil Temperature (C)
15