Assessing Atmospheric Pollen Dispersion and
Gene Flow from Herbicide-resistant Horseweed
Meilan Qi1§, Haiyan Huang2§, Rongjian Ye3§, Xiangzhen Li 4, David R. Miller 5, ,
David W. DuBois 6, Junming Wang2*, and C. Neal Stewart 3
1
School of Science, Wuhan University of Technology, Wuhan, Hubei, P. R. China
2
Illinois State Water Survey, Prairie Research Institute, University of Illinois at Urbana-
Champaign, Champaign, IL, USA
3
Department of Plant Sciences, University of Tennessee, 2431 Joe Johnson Dr., Knoxville,
TN, USA
4
Chengdu Institute of Biology, Chengdu, Sichuan, P. R. China
5
Department of Natural Resources and Environment, University of Connecticut, Storrs,
CT, USA
6
Department of Plant and Environmental Sciences, New Mexico State University, Las
Cruces, NM, USA
§
*
These authors contributed to the work equally.
Corresponding author: Illinois State Water Survey, Prairie Research
Institute,University of Illinois at Urbana-Champaign, 2204 Griffith Dr., Champaign, IL
61820-7463, wangjim@illinois.edu, Voice: (217) 300-2529, FAX: (217) 244-0220
1
Summary
1. Horseweed (Conyza canadensis) with evolved herbicide resistance has become an
especially problematic weed in crop production across the United States. The
resistant horseweed can pollinate regular horseweed and spread herbicide
resistance through gene flow.
2. Although horseweed pollen dispersal is wind-borne, there is little knowledge,
preventive guidelines, and mechanism modeling in regards to gene flow (dynamic
pollen dispersion, deposition, and final outcrossing), especially on the relationship
of pollen dispersion, deposition, and outcrossing with different atmospheric
conditions, herbicide-resistant horseweed patch size, pollen size, buffer crop type,
height, and field size.
3. A pollen dispersion and deposition model was calibrated and validated using 2013
field experimental data. Regression slope and correlation coefficient of the
measured vs simulated pollen concentration were 0.99 and 0.6, respectively; the
slope and coefficient of determination of measured vs. simulated pollen
deposition were 1.29 and 0.4, respectively.
4. The validated model was run for various combinations of atmospheric conditions,
horseweed characteristics, and different buffer plants and sizes. Pollen dispersion,
deposition, and the potential outcrossing ratio with distance were obtained under
the different conditions.
2
5. Although the horseweed characteristics and atmospheric conditions cannot be
controlled in field conditions, crop fields with high leaf area densities, tall heights,
and a large field sizes can effectively prevent pollen dispersion.
6.
Synthesis: This study provided information on the pollen gene flow and
invasion from herbicide-resistant horseweeds under different environmental and
cropping conditions. The information will help provide guidelines for preventing
herbicide-resistance spread/gene flow from herbicide-resistant weeds and
genetically modified plants in general.
Keywords: Gene flow, herbicide resistance, horseweed, modeling, pollen dispersion
Introduction
The evolution of glyphosate resistance (GR) in weedy species places an
environmentally benign herbicide in peril. Horseweed (Conyza canadensis) with evolved
GR has become an especially problematic weed in crop production across the United
States. This plant is considered a significant agricultural weed because it can reduce
agricultural yields by 90% at high densities and becomes problematic under low-tillage
agriculture (Bruce & Kells, 1990; Shields et al., 2006). The spread of GR horseweed has
been rapid, with resistant populations covering millions of acres in corn (Zeamays L.),
soybean, and cotton (Gossypium hirsutum L.) fields in the US (Heap, 2014).
Horseweed gene flow studies have been conducted (e.g., Bruce & Kells, 1990; Dauer
et al., 2006, 2007, and 2009; Henry et al., 2008; Regehr & Bazzaz, 1979; Shields et al.,
3
2006; Weaver, 2001). Horseweed is self-compatible (Shields et al., 2006), and Smisek
(1995) found that 96% of florets were self-pollinated and the outcrossing rate averaged
only about 4% . Therefore, horseweed gene flow studies have been focused on seed
spread (Dauer et al., 2006, and 2007; Shields et al., 2006) instead of pollen transport,
pollination, and outcrossing.
However, the transfer of GR via pollen as a mechanism of gene flow, in addition to
long-distance seed movement, is troubling because it could aid in the evolution of
multiple resistance (Henry et al., 2008). Even a single outcrossed plant can produce more
than 200,000 seeds (Bhowmik & Bekech 1993; Weaver 2001).
Although horseweed pollen dispersal is described as wind-borne, there is no
knowledge, preventive guidelines, and mechanism modeling in regards to gene flow
(dynamic pollen dispersion, deposition, and final outcrossing) for GR horseweed. In
particular, little information is available on the relationship of gene flow with
atmospheric conditions (wind speed, direction, wind variability, and atmospheric
stability), buffer plant type, height, and size, pollen size, and GR horseweed patch size.
Spatial and temporal extrapolation of gene flow measurements are most efficient
using numerical models. The most useful models for gene flow will be those that can be
used to dynamically predict pollen transport, deposition, and final outcrossing from
individual locations and then scale up to landscape and regional scales.
Various descriptive models have been used to depict pollen dispersal in horizontal or
vertical planes (Fitt et al., 1987; Haldane, 1948; Levin & Kerster, 1974; Kareiva et al.,
1994; McCartney, 1994; Wright, 1943). Yet these descriptive models do not have the
power to analyze the effects of controlling factors, should not be extrapolated outside the
4
observation range, and cannot simulate or predict the dynamics of the dispersal process
(Emberlin et al., 1999).
Some comprehensive models of atmospheric transport are quite well developed
for simulating transport processes in and above vegetation canopies (Aylor, 1982; Aylor
& Ferrendino, 1989; Aylor & Flesch, 2001; Klein et al., 2003; Okubo & Levin, 1989;
Raupach, 1993; Raupach et al., 1998; Tufto et al., 1997; Wang & Yang, 2010; Yang et al.,
1991). Transport models can be broadly classified as Lagrangian or Eulerian based on the
type of reference frame used for formulation (Shirolkar, et al., 1996). The application of
Eulerian models for estimating scalar transfer by turbulence within and above plant
canopies has been limited by the inability to treat the dispersion of material from nearby
sources well. Lagrangian models do not suffer from this deficiency since they consider
the diffusion of materials from both nearby and far away sources explicitly (Van den
Hurk & Baldocchi, 1990).
The objectives of this paper were to calibrate and validate a Lagrangian model for GR
horseweed pollen gene flow simulation, and then run the model to find the gene flow
with different atmospheric conditions, buffer plant type, height, and size, pollen size, and
GR horseweed patch size.
Materials and Methods
Lagrangian model
The Lagrangian model in Wang & Yang (2010) was used to simulate horseweed
pollen dispersion. The random flight of each pollen particle is simulated in a sequence of
short time steps, during each of which the particle moves:
5
dx  [u  u ]dt , dy  vdt , dz  ( w  v s )dt (1)
where u is the mean alongwind velocity at the present height of the particle; u , v , and
w are the alongwind, crosswind, and vertical turbulent velocities; and v s is the settling
velocity of the pollen grain (0.02 m/s for horseweed pollen, settling speed was calculated
based on Stoks law (2014) and pollen density in van Hout et al., 2008). The velocity
fluctuations have been formulated in a Markov chain approach based on inputs of u*
(the friction velocity, m/s), wind direction (degree), and L (the Monin Obokov length, m).
The pollen release height was from 0.5 m to 1.3 m. The instantaneous concentration
(grains/m3) at a location is calculated as the number of pollen grains in a unit volume at
that location and time. The average concentration during an averaging time period is the
average of the instant concentrations.
Pollen grains intercepted by plants were determined by the probability that a pollen
grain was intercepted during a time step based on the canopy horizontal and vertical
projection of element area density and pollen grain speed, as described in Wang & Yang
(2010). Table 1 listed the plant characteristics used in this paper.
Pollen deposition flux density (grains/m2/s) at the height of 0.5 m (lowest flower
height of horseweed) was calculated as the concentration at 0.8 m at the corresponding
horizontal location multiplied by deposition velocity (0.26 m/s). The deposition velocity
was obtained from experimental data (Fig. 1). Details of the experimental method will be
explained in the following experiments section.
Outcrossing
6
Henry et al. (2008) found that adjacent GR to Glyphosate susceptible (GS)
horseweeds had an outcrossing ratio of 4%. If the pollen outcrossing ratio was linearly
related to a total pollen vertical flux (grains/m2) like corn (Wang et al., 2006), the
outcrossing ratio of source GR horseweeds to a GS horseweed was estimated as 0.04 (4%)
multiplied by the ratio of deposition of the GS horseweed to source strength. The
outcrossed seed number at a location (seed grains/plant) was estimated as 200,000
grains/plant multiplied by the corresponding outcrossing ratio.
Experiments
Experiments of GR horseweed pollen emission and dispersion were conducted at the
Research Farm, University of Tennessee at Knoxville (Latitude: 35º 53 46.57 N;
Longitude:83 º 57 35.99 W; Elevation:250 m). The sampling time period was during
horseweed pollination season from August 5th, 2013 to September 27th, 2013 (Fig. 1).
Source plants were GR horseweeds with a field diameter of 6 m. The density was 4
plants/ m2. The plant height was 1.3 m. The atmospheric conditions for model inputs
were measured using an anemometer at the height of 2.6 m in the center of the field
(CSAT3, Campbell Sci, Utah, IL). The average u* was 0.15±0.05 m/s (ranged from 0.04
to 0.44 m/s); mean wind direction was 223±55º (ranged from 1 to 346 º); and mean L was
-0.1±15 m (ranged from -55 to 317 m).
Pollen concentration sampling
In pollen dispersal experiments, pollen concentration (grains/m3) was measured
using columns of Rotorod samplers (Model 20, Sampling Technologies, Inc., MN, USA)
in the downwind sampling line. One column of Rotorod samplers was located in the
center of the source to measure the horizontal flux (grains/m2/s) profiles of source
7
production and release (Fig. 2). Other columns of Rotorod samplers were set up in the
prevailing wind direction.
Pollen deposition sampling
Microscope slides (2.5 cm  7.5 cm) covered with silicon grease (Sampling
Technologies, Inc., MN, USA) were used to measure the deposition flux density
(grains/m2/s) at 0.5 m heights along the sampling lines. Details of the experimental setup
are provided in Fig. 2.
Pollen concentration and deposition sampling were conducted throughout the
pollination season. The sampling period for the collectors was 2 hr to 3 hr during the
daytime (7:00-19:30). Timers on the Rotorod samplers were used to provide different
intermittent samplings, as determined by the capacity of the Rotorod samplers to avoid
being overloaded. New fresh sampling rods and slides were placed for each new
sampling period.
Pollen concentration, deposition, source strength, and atmospheric parameters
during each experimental period were obtained following Wang & Yang (2010).
There were a total of 34 sampling periods with greater than 0 pollen grains/plant/s
source strength. The data of concentration at 0.8 m height and deposition flux density at
0.5 m height at the Rotorod pole locations during the first 17 periods were used to
calibrate the deposition velocity (Fig. 1). The remaining data were used to validate the
model.
Model application
8
After validation, the model was applied to predict effects of source strength,
horseweed patch size, buffer plant type and size, pollen settling speed, and the
atmospheric parameters on pollen dispersion and outcrossing from GR horseweeds.
The default parameters are listed in Table 2. Typical noon time atmospheric
parameters (u* and L) were used for atmospheric inputs. Measured average source
strength was used as the default source strength. The default patch size of the horseweed
was 1 m radius circle area that contained 13 horseweed plants (4 plants/m2). The default
buffer (surrounding crop field) was grass ground.
The model was also used to simulate potential gene flow with different horseweed patch
sizes (0.2 to 100 m), different source strengths (0.2 to 83.3 grains/plant/s), buffer plants,
buffer sizes (0 to 200 m), wind strengths (u* from 0.05 to 1.5 m/s), atmospheric
stabilities (L from -1,000 to 1,000 m), and pollen settling speeds (0.05 to 0.34 m/s).
The domain of the simulations was set by the distance where the deposition flux density
was reduced to 0.1% of source strength. The total simulation period was from 15 min to 2
h corresponding to the distance.
The model outputs 3-D concentration (grains/m3), 2-D deposition flux density
(grains/m2/s) at 0.5 m height, and 2-D outcrossing ratio from the source plant. The
deposition output was accumulated over time for the whole pollination season. The 1%
and 0.1% distances (at which the predicted pollen deposition flux density was 1% and 0.1%
of the source strength, respectively) were determined along the prevailing wind direction.
9
For all simulations except for different source sizes, the total deposition flux
(TDF, grains/m2) during the pollen viable period (2 h, Aylor et al., 2003) was estimated
at each prediction location by multiplying the deposition flux density by 2 h.
In simulations for different source sizes, the grand total pollen deposition flux for the
whole pollination season was estimated by multiplying the deposition flux density by the
daily shedding time of 12.5 h (7:00-19:30) and the pollination season.
The 1% and 0.1% distances for total deposition flux in the prevailing wind direction were
used as the distance where the deposition flux density was 1% and 0.1% of the source
strength. Similarly, the 1% and 0.1% distances in the prevailing wind direction for
outcrossing ratio are the distances where the outcrossing ratio was 1% and 0.1%.
Results
Model validation
The model simulated pollen plumes reasonably. Figure 3 shows a sample output
from the model with u*=0.1 m/s and L=-1 m. As expected, concentration plume height
increased with distance and concentration decreased with height and distance; deposition
decreased with downwind and cross wind distances.
Compared with experimental data, the ratio of simulated to the measured
concentration was 0.99 and the correlation coefficient was 0.6 (Fig. 4). The ratio of
10
simulated to the measured deposition flux density was 1.29 and the correlation coefficient
was 0.4.
Model application
The model was run to simulate pollen dispersion under different environmental
conditions. With increased horseweed amounts, the 1% and 0.1% distances increased
(Table 3). If there is one horseweed plant in a field, it may have 1% and 0.1% deposition
distances at 1 and 7 m, respectively, which can potentially produce 80 seed grains/plant at
7 m. That means that even though there may only be several GR horseweeds in a field,
the GR gene flow potential is large.
The total deposition flux during a period is linearly related to source strength as
shown in Table 4. Even though the release rate of pollen is the average source strength
from 13 plants (radius of 1 m area, 2 grains/plant/s), the total deposition flux at the 1%
and 0.1% distances can be high (187,200 and 18,720 grains/m2).
With increased wind speed, the average pollen flight time and travel distance
increased (Table 5), while the 1% and 0.1% distance decreased. This implies that,
although large wind speed can disperse pollen to further distances, it can dilute pollen
concentration and then decrease deposition density.
The 1% and 0.1% distances of pollen transport reached a maximum under neutral
atmospheric stability conditions and generally decreased with distance from neutral,
either from neutral to very unstable or from neutral to very stable condition (Table 6).
This can be explained as follows. Under unstable conditions, strong turbulence may
11
dilute the pollen concentration and then the deposition by increasing the spread. Under a
stable condition, the pollen can be transported further with little downward mixing in the
more laminar air than under a neutral condition (with vertical mixing air) and therefore, it
diluted the pollen concentration and deposition.
Because there was not much vegetation to intercept the pollen on the grass land the 1%
and 0.1% distances were highest on the grass land buffer among all the buffer plants
(grass, soybean, sweet and grain corn) (Table 7). Although soybean is shorter than corn,
its leaf area density was much larger than corn (Table 1). Therefore, the 1% and 0.1%
distances were smaller in the soybean buffer field than in the corn field. Although grain
corn (2.83 m) was taller than sweet corn (1.71 m), the 1% and 0.1% distances were
similar in the two buffer fields. The reason may be that although taller plants can
intercept more pollen, they can decrease the wind speed more than shorter ones, resulting
in less dilution of the pollen concentration and deposition.
As expected, if the buffer field size increased, it decreased the 1% and 0.1% distances
(Table 8). If the buffer size increased to 50 m (grain corn), all the pollen can be blocked
by the buffer and there were no pollen grains deposited after the buffer.
If the pollen settling speed increased (pollen size increased with different plant
species), the pollen transport distance decreased (Table 9). Corn pollen is the largest
pollen in nature and has a settling speed of 0.34 m/s. The 1% and 0.1% distances were
estimated at only 5 m and 13 m, respectively, while the distances of horseweed pollen
were 13 and 55 m, respectively, because of its lighter settling speed of 0.02 m/s.
Discussion
12
Model validation
The model performance is comparable to the literature. For example, in the dispersion
model review paper (Weil. et al., 1992), one Gaussian dispersion model gave a
correlation coefficient of r=0.14 between measured and simulated gas pollutant
concentrations from a power plant stack (regression slope of simulated vs measured
concentration was 1). After the model was improved with a better buoyancy component,
the r=0.58 (slope =1). The model in this study had r=0.6 for pollen concentration
simulation (slope=0.99) and had r=0.4 for pollen deposition simulation (slope=1.29).
Gene flow prevention
Pollen dispersion is affected by wind speed, atmospheric stability, horseweed patch
size, source strength, pollen settling speed, and buffer plant type and size. While the
atmospheric factors and horseweed characteristics cannot be controlled, buffer crop type
and field size can be chosen to better prevent pollen dispersion. In this study, the buffer
plants with a higher leaf area density and larger field size can better prevent pollen
dispersion.
Acknowledgements
The authors gratefully acknowledge financial support for this research from USDANIFA-AFRI- Controlling Weedy and Invasive Plants Grant (2012-67013-19687), and the
support from the Illinois State Water Survey at the University of Illinois at UrbanaChampaign. We thank the excellent programming work by Ms. Xiufen Cui. Opinions
expressed are those of the authors and not necessarily those of the Illinois State Water
13
Survey, the Prairie Research Institute, the University of Illinois, or the University of
Tennessee.
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Table 1. Canopy characteristics of horseweed, corn, and soybean. LAD: leaf area
density; Fx: the proportion of leaf area projection on horizontal ground; Fz: the
proportion of leaf area projection in the vertical direction; Lv: the stem average diameter.
Corn data was from Wang and Yang, 2010. Horseweed and soybean data were measured
in this study by sampling 4 plants.
Level
Height
(cm)
8
7
6
5
4
3
2
1
114-130
98-114
81-98
65-81
49-65
33-49
16-33
0-16
Level
Height
(cm)
8
7
6
79-90
68-79
56-68
Horseweed
LAD
(m3/m2)
0.000
0.000
0.044
0.044
0.044
0.044
0.032
0.032
Fx
Fz
0.59
0.59
0.59
0.59
0.59
0.00
0.00
0.00
0.51
0.51
0.51
0.51
0.51
1.00
1.00
1.00
Lv
(m)
0.003
0.003
0.005
0.005
0.004
0.004
0.002
0.002
Soybean
LAD
(m3/m2)
0.14
7.11
7.11
Fx
Fz
0.91
0.91
0.91
0.42
0.42
0.42
LAD
(m3/m2)
0.000
0.000
0.000
17
5
4
3
2
1
45-56
34-45
23-34
11-23
0-11
Level
Height
(cm)
8
7
6
5
4
3
2
1
150-171
128-150
107-128
86-107
64 -86
43-64
21.-43
0-21
Level
Height
(cm)
8
7
6
5
4
3
2
1
248-283
212-248
177-212
142-177
106-142
71-106
35-71
0-35
7.11
5.9
5.9
5.9
1.13
0.71
0.71
0.71
0.50
0.50
0.71
0.71
0.71
0.87
0.87
0.003
0.003
0.003
0.003
0.003
Sweet Corn
LAD
(m3/m2)
0.10
0.82
1.42
1.47
1.30
1.56
1.20
0.35
Fx
Fz
0.04
0.60
0.68
0.78
0.76
0.71
0.63
0.59
0.99
0.75
0.70
0.55
0.56
0.65
0.66
0.69
LAD
(m3/m2)
0.038
0.075
0.087
0.065
0.073
0.051
0.046
0.042
Grain Corn
LAD
(m3/m2)
0.18
1.15
2.30
2.40
2.74
1.87
1.38
0.30
Fx
Fz
0.14
0.68
0.55
0.75
0.60
0.52
0.58
0.58
0.98
0.60
0.69
0.59
0.65
0.76
0.69
0.52
LAD
(m3/m2)
0.011
0.038
0.055
0.046
0.054
0.052
0.047
0.037
Table 2. Default conditions used for simulations of different source field sizes,
source strengths, buffer heights, buffer field sizes, atmospheric conditions, and pollen
sizes.
Pollen
Horseweed
u* L Source strength
settling
patch size:
Buffer
(m/s) (m) (Grains/plant/s)
speed
radius (m)
(m/s)
Grass
0.2 -15
2
1
0.02
land
18
Table 3. 1% and 0.1% deposition flux distances simulated from different size source
fields (where the grand total deposition fluxes were 200,000 and 20,000 grains/m2,
outcrossing ratios were 0.004 and 0.0004 and outcrossed seed numbers were 800 and 80
seeds/plant, respectively). (See Table 2 for the default atmospheric and plant conditions.)
Source Radius
Plant
1% Distance
0.1% Distance
/m
number
/m
/m
0.28
1
1
7
1
13
13
55
5
314
89
255
10
1256
167
481
20
5024
300
756
56
39388
627
1609
100
125600
891
2057
Table 4. Predicted total deposition flux (TDF, grains/m2) during 2-h period at 1% and
0.1% distances from 3.14 m2 (1 m radius, 13plants) herbicide-resistant horseweed plants
for different source strengths under normal atmospheric conditions (see Table 2 for the
default weather and plant conditions)
TDF at 1% distance TDF at 1% distance of
Source Strength
of 13 m
55 m
(grains/plant/s)
2
(grains/m )
(grains/m2)
0.2
18,720
1,872
2
187,200
18,720
8.3
776,880
77,688
16.7
1,563,120
156,312
33.3
3,116,880
311,688
83.3
7,796,880
779,688
Table 5. Predicted 1% and 0.1% distances and pollen average flight time (not deposited
or intercepted) and flight distances during two-hour simulation period from 3.14 m2 (1 m
radius) herbicide-resistant horseweed plants for different u* (see Table 2 for the default
weather and plant conditions)
Average
Wind speed at
Average
1% Distance
0.1% Distance
Horizontal
u* one meter above
Flight
(TDF = 187,200) (TDF = 18,720)
Flight
(m/s)
canopy
time
(m)
(m)
Distance
(m /s)
(s)
(m)
0.05
0.32
30
90
3,288
2,687
0.1
0.63
22
75
4,036
6,628
19
0.2
1.27
13
57
2,538
8,264
0.3
1.90
9
49
1,800
8,821
0.8
5.07
3
27
725
9,467
1.5
9.51
2
16
393
9,638
Table 6. Predicted 1% and 0.1% distances with total deposition flux (TDF, grains/m2)
during two-hour period from 3.14 m2 (1 m radius) herbicide-resistant horseweed plants
for different atmospheric stabilities (see Table 2 for the default weather and plant
conditions)
1% Distance
0.1% Distance
L
Atmospheric state
(TDF =187,200 )
(TDF = 18,720)
(m)
(m)
(m)
-5
Very unstable
9
39
-15
Moderate unstable
13
59
-50
Unstable
17
72
-1000
Neutral
24
87
1000
Slightly stable
18
56
50
Stable
17
61
Table 7. Predicted 1% and 0.1% distances with total deposition flux (TDF, grains/m2)
during a two-hour simulation period from 3.14 m2 (1 m radius) herbicide-resistant plants
for different buffer plants under normal atmospheric condition (see Table 2 for the
default weather and plant conditions).
0.1% Distance
Buffer
1% Distance
(TDF =
height
Buffer plant
(TDF = 187,200 )
18,720)
/m
(m)
(m)
0.2
Grass ground
13
59
0.9
Soybean
8
20
1.71
Sweet corn
11
26
2.83
Grain corn
13
23
Table 8. Predicted 1% and 0.1% distances with total deposition flux (TDF, grains/m2)
during two-hour simulation period from 3.14 m2 herbicide-resistant plants for different
buffer sizes (buffer plant characteristics used grain corn data; see Table 2 for the default
weather and plant conditions).
20
Buffer
Size
(m)
1% Distance
(TDF = 187,200 )
(m)
0.1% Distance
(TDF = 18,720)
(m)
% deposition
at buffer
downwind
boundary
0
12
54
29
5
2
32
7
10
1
16
2
20
0
1
0.2
30
0
0
0.01
50
0
0
0
100
0
0
0
200
0
0
0
Table 9. Predicted 1% and 0.1% distances during two-hour period from 3.14 m2
herbicide-resistant plants for different pollen settling speeds under normal atmospheric
conditions (see Table 2 for the default weather and plant conditions; TDF = total
deposition flux, grains/m2).The settling speed was calculated following Stoke’s law (2014)
and pollen density (van Hout et al., 2008).
Species
Pollen
1% Distance
0.1% Distance
Settling speed
diameter
(TDF = 187,200)
(TDF = 18,720)
(m / s)
(µm)
(m)
(m)
Horseweed (Ye, R. et al.,
21
0.02
13
55
2014,unpublished)
Sunflower (Baghali et al.,
27.5
0.03
13
53
2011)
Rice (Dai et al., 2006)
42
0.07
13
45
Switchgrass (Ge et al.,
54
0.10
11
43
2011)
Corn (Wang and Yang,
100
0.34
5
13
2010)
21
Deposition (grains/m2/s)
60
50
40
y = 0.26x
r= 0.8
30
20
10
0
0
50
100
150
200
250
Concentration (grains/m3)
Figure 1. Deposition velocity calibration (ratio of deposition divided by concentration)
using half of the experimental data (first 17 sets of 34 experimental periods). r is the
correlation coefficient of the simulated and the measured data (P<0.001).
22
N
E
W
S
24m
12m
6m
3m
1.5m
0.5m
1m
6m
3m
3m
0.75m
0.75m
1.0m
0.75m
0.75m
2.6m
0.5m
0.5m
0.8m
0.8m
Rotorod pole
(3.55m)
1.3m
Rotorod pole
(3.05m)
0.5m
Slide pole
Anemometer
Horseweed
plant
Figure 2. Schematic sketch of experimental setup. Locations of the sampling poles in the
field (top) and vertical positions of the samplers on the poles (bottom).
23
Figure 3. One sample output from the model during a noon time 15 min simulation
period, when u* = 0.1 m/s, wind direction = 0, L = -1 m. The source had a radius of 6 m.
The arrow in the deposition graph shows the wind direction. Top: concentration with
height and downwind distance; bottom: deposition flux density with distance.
24
Model concentration
(grains/m3)
1000
y = 0.99x
r =0.6
100
10
1
0.1
1
10
100
1000
0.1
Measured concentration (grains/m3)
Figure 4. Simulated vs. measured pollen concentration. r is the correlation
coefficient of the simulated and the measured data (P<0.001).
Simulated deposition
(grains/m2/s)
100
y = 1.29x
r=0.4
10
1
0.1
1
10
100
0.1
Measured deposition (grains/m2/s)
Figure 5. Simulated vs measured pollen deposition flux. r is the correlation
coefficient of the simulated and the measured data (P<0.001).
25