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Abstract

Background Wind strongly impacts plant growth, leaf traits, biomass allocation, and stem mechanical properties. However, whether there are common whole-plant wind responses among different plant species is still unclear. We tested this null hypothesis by exposing four eudicot steppe species to three different wind treatments in a field experiment: reduced wind velocity using windbreaks, ambient wind velocity, and enhanced wind velocity through a novel methodology using wind-funneling baffles. Results Across the four species, wind generally decreased plant height, projected crown area, and stepwise bifurcation ratio, and increased root length and stem base diameter. In contrast, the response patterns of shoot traits, especially mechanical properties, to wind velocity were idiosyncratic among species. There was no significant difference in total biomass among different treatments; this might be because the negative effects on heat dissipation and photosynthesis of low wind speed during hot periods, could counteract positive effects during favorable cooler periods. Conclusions There are common wind response patterns in plant-size-related traits across different steppe species, while the response patterns in shoot traits vary among species. This indicates the species-specific ways by which plants balance growth and mechanical support facing wind stress. Our new field wind manipulation methodology was effective in altering wind speed with the intended magnitude. Especially, our field wind-funneling baffle system showed a great potential for use in future field wind velocity enhancement. Further experiments are needed to reveal how negative and positive effects play out on whole-plant performance in response to different wind regimes, which is important as ongoing global climatic changes involve big changes in wind regimes.
Zhangetal. Plant Methods (2021) 17:5
https://doi.org/10.1186/s13007-020-00705-2
RESEARCH
New eld wind manipulation methodology
reveals adaptive responses ofsteppe plants
toincreased andreduced wind speed
Shudong Zhang1,2,3, Guofang Liu1, Qingguo Cui1, Zhenying Huang1*, Xuehua Ye1*
and Johannes H. C. Cornelissen3
Abstract
Background: Wind strongly impacts plant growth, leaf traits, biomass allocation, and stem mechanical properties.
However, whether there are common whole-plant wind responses among different plant species is still unclear.
We tested this null hypothesis by exposing four eudicot steppe species to three different wind treatments in a field
experiment: reduced wind velocity using windbreaks, ambient wind velocity, and enhanced wind velocity through a
novel methodology using wind-funneling baffles.
Results: Across the four species, wind generally decreased plant height, projected crown area, and stepwise bifurca-
tion ratio, and increased root length and stem base diameter. In contrast, the response patterns of shoot traits, espe-
cially mechanical properties, to wind velocity were idiosyncratic among species. There was no significant difference in
total biomass among different treatments; this might be because the negative effects on heat dissipation and photo-
synthesis of low wind speed during hot periods, could counteract positive effects during favorable cooler periods.
Conclusions: There are common wind response patterns in plant-size-related traits across different steppe species,
while the response patterns in shoot traits vary among species. This indicates the species-specific ways by which
plants balance growth and mechanical support facing wind stress. Our new field wind manipulation methodology
was effective in altering wind speed with the intended magnitude. Especially, our field wind-funneling baffle system
showed a great potential for use in future field wind velocity enhancement. Further experiments are needed to reveal
how negative and positive effects play out on whole-plant performance in response to different wind regimes, which
is important as ongoing global climatic changes involve big changes in wind regimes.
Keywords: Biomass and allocations, Ecological method, Mechanical properties, Mu Us Sandland, Plant size, Wind
funneling
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Background
Almost all terrestrial plants face wind stress, especially
in mountain and coastal ecosystems, plateaus and other
inland ecosystems where wind has sufficient open space
or natural funneling to gain in force [14]. Wind is a
major source of mechanical loading and leaf tempera-
ture regime on plants, by which it has a major impact
on plant growth, morphology, physiology, dispersal and
ecology [3, 57]. Almost all plants have to balance five
major requirements throughout their lifetime: photo-
synthesis, water transport, growth, reproduction, and
mechanical support [8]. Wind may affect all these five
requirements. First, in the natural environment, wind
is the main source of mechanical perturbation. e
mechanical signals that plants perceive imposed by wind
Open Access
Plant Methods
*Correspondence: zhenying@ibcas.ac.cn; yexuehua@ibcas.ac.cn
1 State Key Laboratory of Vegetation and Environmental Change, Institute
of Botany, Chinese Academy of Sciences, Beijing 100093, People’s
Republic of China
Full list of author information is available at the end of the article
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Page 2 of 16
Zhangetal. Plant Methods (2021) 17:5
can induce thigmomorphogenesis, which may alter plant
growth patterns and cause lower stature, thicker stem,
and smaller shoots [5, 913]. Additionally, mechanical
stress can reduce plant growth [14, 15], increase the root/
shoot ratio [13, 16], and change leaf properties including
a reduction in the number of leaves, individual leaf area
or dry mass and petiole length, and increase leaf thick-
ness and flexibility [5, 7, 1719]. Second, besides creating
stressful drag force, wind also influences photosynthesis
and transpiration of plants in different ways depending
on plant traits, wind intensities and ambient tempera-
tures. Photosynthetic rates will decrease at (very) low
wind speed due to the increase in the leaf boundary layer
and the consequent reduction in the diffusive resistance
for carbon dioxide; at high ambient air temperatures a
thick boundary layer may also cause excessive leaf tem-
peratures that inhibit photosynthesis. At (very) high wind
speed and low ambient air temperature, photosynthesis
may be reduced due to below-optimal leaf temperatures
and stomatal conductance, and to leaves rolling up [5,
16, 18]. ird, in some specific areas (e.g. coastal dunes,
inland arid and semi-arid dunes), sand movement caused
by strong wind is a common environmental agent affect-
ing plants [2024]. In these habitats, plants may face
stress caused by soil losses or sand burial under wind
erosion. In extreme cases, wind denudation may cause
soil water loss, reduction in nutrient content or greater
exposure of the upper roots of plants to high temperature
[2428]. In contrast, moderate sand burial may improve
soil water and nutrient conditions and moderate the tem-
perature fluctuation around plant roots, which may ben-
efit plant growth [29].
Plants have developed various adaptations to cope with
strong wind exposure, e.g. through trait variation in their
branches [30] and leaves [31], biomass allocation [32],
root structure [33], and/or stem mechanical properties
[18, 34]. However, these traits of different plant organs
are subject to trade-offs (e.g. carbon distribution) or
coordination (e.g. allometric relationships). erefore, it
is hard from most previous studies focusing on particu-
lar plant organs and particular structural, morphological,
and/or physiological traits, to infer whole-plant strate-
gies in terms of adaptive response to wind. Few previous
studies have compared wind responses among several
species, even though plant species are known to vary in
their capacity to resist wind, and to recover from or off-
set the effects of wind damage [35]. In addition, research
fields study different aspects of plant response to wind.
Forestry researchers tend to observe storm-damaged for-
est and often focus on the growth versus shade-tolerance
trade-off of tree species [17, 36]. Agricultural research
has focused on lodging resistance and yield-related traits
[8, 15]. us, the scientific community is dispersed in the
specific variables they measure in response to wind [6].
Research methods applied for wind manipulation also
vary greatly, from field observation to field experiment to
glasshouse controlled-environment experiment.
Two main experimental approaches have so far been
used to impose wind disturbance effects on plants. One
is artificially creating mechanical perturbation by shak-
ing and brushing plants [5, 12, 19, 3741], which has
focused on the mechanical perturbation caused by wind
and has been conducted mostly in controlled environ-
ments in glasshouses in the absence of wind. Another has
been the use of wind tunnels or electric fans to enhance
wind force [5, 16, 18, 32, 42, 43]. ese methods depend
on power supply and indoor facilities, which makes them
hard to be widely applied under field conditions. Because
of these limitations, we still understand poorly whether
there are general syndromes of whole-plant response to
wind exposure across organs, i.e. wind-coping strategies,
or whether responses to wind are idiosyncratic among
species without consistent responses among organs and
their various traits.
Here we aimed to overcome the above limitations in a
unique field experiment in order to test the null hypoth-
esis that there are common whole-plant wind responses
among different plant species. We assigned four contrast-
ing vascular species to three treatments (reducing wind
velocity, ambient wind velocity, enhancing wind velocity)
in the steppe area of north China. To increase wind veloc-
ity we employed a novel methodology using connectivity
modifiers (baffles) to converge wind. Connectivity modi-
fiers, a patch-scale manipulation, can effectively change
the size of connected pathways for wind or water under
field conditions without directly affecting other abiotic
and biotic factors. is methodology was previously used
in some studies to collect foliar litter and seeds [44, 45],
but has, to our knowledge, not been used to study wind
effects on living plants. is methodology allows the
wind regimes in this study to reflect the real environmen-
tal conditions that plants may encounter outdoors, where
wind stress or disturbance may vary with weather condi-
tions and the local properties of the terrain.
Material andmethods
Study site
e experiment was carried out at the Ordos Sandland
Ecological Station of the Chinese Academy of Science
(OSES, 39° 29 N, 110° 11 E, 1296m a.s.l.), located in the
northeastern Mu Us Sandland in Inner Mongolia, China.
Mean annual precipitation is 350mm, with inter-annual
fluctuations from 161 to 664 mm. Mean annual tem-
peratures range from 5.0 to 8.5°C, and mean potential
evaporation is 2300 mm (OSES weather station, 2005–
2015). On average 140 days per year have maximum
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Zhangetal. Plant Methods (2021) 17:5
wind speed > 6bft (> 10.8m/s), and the wind predomi-
nantly comes from the north-west (Additional file1: Fig.
S1). During the study year (2017), the total precipitation
was 312.6 mm, most of which (280.4 mm) fell during
the experimental period in the growing season (May to
October; Additional file1: Fig. S2A). Monthly mean wind
velocities ranged from 1.6 to 2.31 m/s and maximum
wind velocity (14.4m/s) were reached in May (Additional
file1: Fig. S2B, C; all the wind data were collected from
the OSES weather station at the standard 10m height).
e distribution of wind direction of maximum wind
speed was consistent with these data (Additional file 1:
Fig. S2D). e landscape in this area is characterized by
mobile, semi-fixed and fixed sand dunes. As water avail-
ability is low, the area is dominated by steppe or desert
vegetation with low height and sparse cover.
Plant materials
Two predominant shrubs, i.e. Artemisia ordosica Krasch
(Asteraceae), Caragana intermedia Kuang (Fabaceae)
and two locally common herbs, i.e. Agriophyllum squar-
rosum (L.) Moq. (Chenopodiaceae) and Salsola ruthenica
Iljin (Chenopodiaceae), were selected for the experiment.
A. ordosica is a dominant shrub in (semi-)fixed sand
dunes, approximately 0.5–1.0m tall with plumose, lin-
early lobate leaves. Its lateral roots are mainly distributed
in the upper 30cm of the sand soil profile, while its pri-
mary roots may reach 1–3m deep [27]. C. intermedia is
a deciduous pinnate-leaved shrub approximately 1.5–2m
tall, widely used to mitigate desertification in north
China [46]. A. squarrosum and S. ruthenica are annual
herbs, up to 1 m tall, with erect stems and basal side-
shoots. A. squarrosum is an important pioneer on mov-
ing and semi-fixed sand dunes, widely distributed in arid
and semiarid regions of central Asia [47, 48] and widely
naturalized in many other parts of the world.
Seeds of the four species were collected near OSES in
2015. On 16 September 2016, A. ordosica and C. inter-
media seeds were germinated on wet filter paper; on 23
September 2016 the seedlings were transplanted into
fabric bags (10cm diameter, 15cm height) and grown in
the greenhouse of OSES through the winter. On 18 May
2017, 18 seedlings of each species with similar height
(28.5 ± 4.07cm for C. intermedia and 10.74 ± 0.89cm for
A. ordosica) and stem base diameter (1.91 ± 0.42mm for
C. intermedia and 4.00 ± 0.86 cm for A. ordosica,) were
chosen and randomly transplanted into a 50 L (0.4m
diameter, 0.4m high) pot filled with sand without drain-
age holes in the bottom. On 15 May 2017, A. squarro-
sum and S. ruthenica seeds were germinated on wet filter
paper. After 16days, 18 seedlings per species were trans-
planted into the pots (see above). All pots were buried in
the quadrats of the three different treatments on 19 May,
2017. During the experimental period, all plants received
2L of water once a week and 1L of 1g/L nutrient solu-
tion (Peters Professional 20-20-20 General Purpose, the
Scotts Company, Ohio, USA; N:P:K = 1:0.83:0.44, plus
microelements) once a month.
Experimental design
We imposed three different wind treatments on the four
plant species: decreased wind velocity (D), ambient wind
velocity (CK), and increased wind velocity (I); see Fig.1
for methodological details. In brief, treatment D was
implemented through a wind shield (Fig.1a). e design
of using transparent plastic sheets was intended to mini-
mize the influence of the wind shield on the light regime.
Treatment I was implemented through artificial air baf-
fles that funneled the ambient wind towards the target
plant (Fig.1c). To the best of our knowledge, this repre-
sents a new method for wind enhancement with minimal
experimental artefact (see under “Results”). e wind
velocity increasing method was based on an ideal model
(Fig.2a) coming from the fluid continuity equation:
where ρ was a constant representing the density of air
flow. A1 was the interface area of the wind flow coming
in and A2 was the interface area of the wind flow going
out. V1 was the initial wind velocity when air flow came
in and V2 was the wind velocity when air flow went out.
In the ideal model, air should flow through a closed tun-
nel. e basic continuity equation, states that the amount
of air flowing in on one side must equal the air flowing
out on the other side. In this case, we could change the
velocity of air flow by changing the ratio of A1 and A2. In
our design, we used air baffles to create an air tunnel that
had a larger area where the wind flow entered than the
area where the wind flow exited. According to the conti-
nuity equation,
where Vout represents the wind velocity at the exit point
of the wind funnel, and Vin is the initial wind velocity
before treatment. s is the length of the short side of the
wind funnel, l the length of the wind baffle. However, the
above formula assumes a closed funnel at the top. As our
wind funnel was open at the top, the actual wind veloc-
ity at the exit point of the wind funnel should be smaller
than Vout. Increasing the baffle height would make the
funnel closer to the sealed status, i.e. it could make the
final wind velocity closer to Vout.
Both treatments CK (Fig.1b) and I had a large-mesh
fence around the plant to protect it from herbivory. In
total, there were 72 plants: 4 species × 3 treatments × 6
(1)
ρA1V1=ρA2V2.
(2)
Vout =(s+2l)Vin/s
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Zhangetal. Plant Methods (2021) 17:5
Fig. 1 Experimental design and images of wind treatments. a The Decreased wind velocity treatment was implemented through a wind shield,
which was 1 m × 1 m × 0.75 m (0.75 m high) and built with four steel tubes and transparent plastic sheets. The plastic chambers did not have
a roof, so that ambient air could mix with that in the cubicles freely. b There was no additional treatment for the ambient treatment, apart from
a large-mesh, 0.6 m high fence to avoid herbivory by wild rabbits (In a pilot test, the fence had a negligible influence on wind velocity). c The
Increased wind velocity treatment was implemented through experimental wind baffles. We placed 1.5 m long and 1 m high iron sheets at each
side directed towards the North-East, North-West, South-East and South-West, respectively from each pot, to converge and increase wind velocity.
These baffles were at 0.7 m distance from the plant pot to avoid a shading effect
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Page 5 of 16
Zhangetal. Plant Methods (2021) 17:5
replicates (Fig. 1). e experimental site was very flat,
and treatments were far away from each other and taller
surrounding vegetation. For avoiding obstruction of the
air flow to other treatments, the D section was laid out
at the south-west, the CK section was set out at the east
and I section at the west of the experimental site. Dur-
ing the experiment period, sand burial happened due to
the increased wind velocity in treatment I despite the
protection of the plastic pot. Extra sand was periodically
removed from the pots using a brush when burials hap-
pened to minimize the influences of the sand burial on
plants.
Environment parameters measurements
Wind speed, air temperature and relative humidity
were measured at 0.8m above the ground (i.e. close to
maximum plant height), using AZ9671 Anemometer
Loggers (Shenzhen frank electronics co. LTD., China).
e loggers recorded data with 90-s intervals. Because
the AZ9671 Anemometer Loggers can only quantify air
movement in one direction, we chose westerly as our
main direction (due to prevailing strong wind coming
from this direction; see Additional file1: Fig. S1) and
all the loggers were positioned toward the west dur-
ing the whole experiment period. Soil volumetric water
content and temperature were measured 10cm below
the soil surface in the middle of the buckets by Em50
series data loggers (Decagon Devices, Inc., USA). e
loggers collected data at 2-min intervals. In each treat-
ment section, three AZ9671 and Em50 loggers were
installed in random positions. We collected data from
1 June to 7 September 2017. Due to the limited of the
power supplies and data storage of AZ9671 loggers, we
had to retrieve the loggers from the field for replacing
batteries and download data regularly. Additionally, the
anemometer had a high rate of malfunction in the rain.
us we also avoid the continuously rainy days. In this
case, the data set of wind speed, air temperature and
relative humidity had some breaks in time during the
whole experimental period, but we tried our best to
make sure that the measurements covered most of the
available time. e specifications of all the instruments
used in this study can be found in Additional file 1:
TableS1.
Fig. 2 Diagrammatic sketch of wind velocity increasing methodology and effects of wind treatments. a Wind velocity increasing method. Ain is
the interface area of the wind flow coming in and Aout is the interface area of the wind flow going out. Vin is the initial in-coming wind velocity and
Vout is the wind velocity of air flowing out. s is the length of the short side of the wind funnel, and l is the length of the wind baffle. b Diurnal mean
wind velocity pattern (mean ± SE) over 24 h under wind treatments throughout the experimental period. c Diurnal maximum wind velocity pattern
(mean ± SE) over 24 h under wind treatments throughout the experimental period. d Effects of wind treatments. The black dashed line with the
equation (
y=
(s
+
2l)
sx
) represents the ideal wind velocity that could be reached by acceleration. The black dashed line with the equation (y = x)
represents the wind velocity in the ambient treatment (CK). Red dots and line represent the relationship between the temporally matched hourly
maximum wind velocity in I and CK. Blue dots and line represent the relationship between the temporally matched hourly maximum wind velocity
in D and CK. Regression equations and R2 are given. D means decreased wind velocity treatment, CK means ambient wind velocity treatment, and I
means increased wind velocity treatment
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Zhangetal. Plant Methods (2021) 17:5
Plant trait measurements
All plants were harvested within nine days from 7 Sep-
tember 2017.
Plant height, stem base diameter (SBD), crown traits,
leaf traits and branching pattern were measured before
harvest. Plant crown length (L) and width (W) were
measured, and projected crown area (PCA) was calcu-
lated as
For each plant, 15 fresh leaves were scanned and leaf
length (LL) and leaf area (LA) were measured. e leaves
were dried at 80°C for 48h, then weighed. Specific leaf
area (SLA) was calculated as fresh leaf area per unit leaf
dry mass.
e branching pattern was measured following Strahler
method [49]. Numbers of first to third degree branches
were counted, then overall bifurcation ratio (OBR) and
stepwise bifurcation ratio (SBR) were calculated as
where numbers of branches are represented by Nt for all
segments, Ns for the highest-order branches, N1 for the
first-degree branches, while Ni the branch number of i
degree.
After harvest, each plant was divided into root and
shoot. We measured root length (RL) of the longest root.
For shoots, 15cm long primary stem sections were sepa-
rated from the bottom of the plant shoot for determina-
tion of mechanical properties.
Young’s modulus (E) of the main stems was measured
with an electromechanical device (Type 5540; Instron,
Norwood, MA, USA), applying the three-point bending
technique [50]. E is a measure of stiffness of a material
[7]. Vertically applied forces (F; N) and resulting deflec-
tions (
δ
; m) were recorded. E was calculated as
where L is the length between the supports (m) and I the
second moment of area (m4). I was calculated as
where r = stem radius in m. is index is a measure of the
geometric contribution to rigidity [7]. Flexural stiffness of
stems is a measure of the rigidity of a material, calculated
as the product of E and I (EI, N/m2; [7]).
Mechanical measurements of each plant were com-
pleted within 15min after cutting. After these tests, all
parts of the plants were dried at 80°C for at least 72h.
(3)
(4)
OBR =(NtNs)/(NtN1)
(5)
SBR(i:i+1)=Ni/(Ni+1)
(6)
E=
FL3
/48δ
I
(7)
I=r4)/4
en, root and shoot biomass were weighed and root/
shoot ratio was calculated. After weighing, the main
stems used for mechanical measurements were ground
by ball mill; stem lignin content (SLC) was determined
as acid insoluble (Klason) lignin. Stem cellulose con-
tent (SCC) was determined colorimetrically with the
anthrone reagent [51].
Data analysis
Because the data set of wind speed, air temperature and
relative humidity had breaks in time, only days with the
completed data were chosen for the analysis. In total
there were 31 completed days that covered the whole
experimental period. en, the average hour-by-hour val-
ues of each parameter in each treatment throughout this
period were calculated. Based on the hourly maximum
wind velocities in consecutive days, the hour-by-hour
mean hourly maximum wind velocity was calculated. To
evaluate the results of wind velocity changes, the hourly
maximum wind velocity in the treatment CK and I, and
Treatment CK and D were temporally matched, then
the linear regression lines were generated by the for-
mula (
y=ax
) in R software (v3.3.0, R core team, 2015).
Because of the limitation of the AZ9671 Anemometer
Logger, wind velocity data were collected from only one
direction (west). e wind velocity data collected from
the directions perpendicular to the logger were expected
to be underestimates. For checking the accuracy of our
wind velocity data, we used the wind data collected from
OSES weather station as a reference. e OSES weather
station recorded the hourly average wind direction dur-
ing the whole experimental period. We first extracted the
time intervals during which the wind came from the west
(from 225° to 315°) during the experimental period. en,
we paired these time points with the data collected from
the AZ9671 Anemometer Logger, extracting the time
intervals each day when the wind was mainly coming
from the west during our experimental period. By com-
paring the average hour-by-hour wind velocities between
the westerly wind data set with those in the whole data
set, we could evaluate the accuracy of our whole wind
velocity data set collected from AZ9671 Anemometer
Logger, and especially the robustness of the differences
found among wind treatments. Two-way ANOVAs
were used to analyze the (interactive) effects of different
species and wind treatments on each plant trait. One-
way ANOVA was used to test differences in plant traits
among the three wind treatments for each species sepa-
rately, followed by Tukey’s HSD tests for multiple com-
parisons. Data were log10(x + 1)-transformed if necessary
to improve the equality of variance distributions among
treatments. Statistical analyses were performed using
SPSS18 (SPSS Inc., USA2009). A redundancy analysis
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Page 7 of 16
Zhangetal. Plant Methods (2021) 17:5
was carried out in R software (v3.3.0, R core team, 2015)
using the package Vegan to explore the covariance struc-
ture of the different trait responses to the wind treat-
ments across the species comprehensively. e plant
traits were used as the respective response variables.
en, the response matrix was standardized by a scale
function. e explanatory matrix was defined by the
plant species and wind treatments. For testing the sig-
nificance of the variation in response matrix explained
by explanatory variables, a Monte Carlo permutation
test was used (Anova function with permutation options,
permutations = 999). e adjusted R2 was computed,
after the permutation test.
Results
Environmental variables indierent wind treatments
e wind shields (treatment D) reduced daily ambient
wind velocity by 71% and maximum wind velocity by 67%
on average (Fig.2b, c). It increased ambient air tempera-
ture on average by 2.1°C, and reduced ambient relative
humidity by 3%, ambient soil temperature by 0.4°C and
ambient soil volumetric water content by 14% on average
(Additional file1: Fig. S3). e experimental wind baf-
fles (treatment I) increased daily ambient wind velocity
by 56% and maximum wind velocity by 114%, decreased
ambient air temperature by 0.6°C and ambient soil tem-
perature by 1.7°C on average, while they increased ambi-
ent relative humidity and soil volumetric water content
each by 2% (Fig.2b, c, Additional file1: Fig. S3). e aver-
age hour-by-hour wind velocity between the westerly
wind data set and the whole data set (Additional file1:
Fig. S4) showed similar patterns when comparing the
mean wind velocities among different wind treatments.
is means that, although the limitation of the AZ9671
Anemometer Logger caused some inaccuracy in absolute
wind velocity values, the whole data set still reflected the
real wind patterns in the different treatments during our
experimental period.
e temporally matched relationship between the
hourly maximum wind velocity in the CK and I showed
that our wind funnel design had potential to accelerate
wind flow reaching the velocity calculated by the ideal
model (Fig. 2d). According to the regression equation
y = 1.51x, the actual accelerated hourly maximum wind
velocity of our design can be predicted by the hourly
maximum wind velocity in the ambient condition. e
temporally matched relationship between the hourly
maximum wind velocity in the CK and D also reflected
the effect of the wind breaks on decreasing wind veloc-
ity. Another regression equation y = 0.307x was gener-
ated which could be used to estimate the maximum wind
velocity in the treatment D.
Commonalities inresponses amongthespecies towind
treatments
All plant traits showed significant differences among
species, while 10 out of 19 traits showed significant
wind effects and nine out of 19 traits significant inter-
actions of species and wind treatment (Table1). Across
species, wind velocity significantly affected plant
height, PCA, SBD, RL, SBR(1:2), LL, total and shoot
biomass, root/shoot ratio, and E. ere were signifi-
cant species by treatment effects on PCA, SBD, OBR,
SBR(1:2), root/shoot ratio, SCC, I and E (Table1).
Among species, common responses mainly showed as
decreases in size-related traits and increases in wind-
resistance abilities. Plants tended to be shorter, have
smaller PCA, SBR(1:2), and lower biomass in response to
increasing wind velocity (Table2, Figs.3, 4). Height of
C. intermedia and S. ruthenica decreased with increas-
ing wind velocity (Fig.3a). PCA of A. ordosica, C. inter-
media, and S. ruthenica decreased with increasing wind
velocity (Fig.3b). OBR and SBR(1:2) of A. ordosica and
C. intermedia were markedly influenced by the wind
treatments (Table2), being lower in CK and I than in
D (Fig.3d, Additional file1: Fig. S5E). Increased wind
velocity decreased total biomass of C. intermedia,
and shoot biomass of C. intermedia and A. squarro-
sum (Table2, Fig.4). RL, SBD and I tended to increase
with increased wind velocity (Table2, Figs. 3, 5, and
Additional file1: Fig. S5). RL of A. squarrosum and S.
ruthenica increased steadily from D via CK to I while A.
ordosica only showed an increase from CK to I and C.
intermedia showed no response at all (Table2, Fig.3c).
I of A. ordosica and S. ruthenica was higher in treat-
ments CK and I than in D (Table2, Fig.5c). Stem base
diameter of A. ordosica and A. squarrosum increased in
CK and I compared to treatment D (Table2, Additional
file1: Fig. S5F).
Idiosyncratic responses amongspecies towind treatments
In contrast to the common responses to wind treatments
for size-related traits, the plants showed idiosyncratic
responses among species for some traits (Additional
file 1: Fig. S6). Responses of mechanical properties
showed large diversity. Wind decreased E in A. ordosica
and S. ruthenica. E of A. ordosica decreased markedly in
CK and I as compared to D, which resulted in an increase
of EI. In S. ruthenica, E decreased in CK. However, the
wind treatments had no significant influence on E of A.
squarrosum and increased E of C. intermedia. Except for
A. ordosica, EI of the other three species was not signifi-
cantly influenced by the wind treatments. Moreover, SCC
of A. ordosica was higher in CK than in D, while in A.
squarrosum it was lower in CK and I than in D (Fig.5).
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Page 8 of 16
Zhangetal. Plant Methods (2021) 17:5
Leaf traits also responded in a species-specific manner
to the wind treatments. Leaf length of C. intermedia and
S. ruthenica and leaf area of C. intermedia and A. squar-
rosum were influenced by wind treatments (Table2). e
leaves of S. ruthenica were shorter in CK and I as com-
pared to D (Additional file1: Fig. S5A). Leaf area of C.
intermedia was markedly reduced in CK as compared to
D, and leaf area of A. squarrosum was lower in CK and I
than in D (Additional file1: Fig. S5C).
Discussion
To our knowledge, this is the first experimental study to
simultaneously compare effects of both decreased and
increased wind speed on plant performance with ambient
wind speed under field conditions. Our wind funneling
treatment has added a new experimental method to
increase wind speed under field conditions without some
of the experimental artefacts on other environmental fac-
tors associated with treatments using wind tunnels and
fans. In particular, our field wind-funneling baffles con-
tinuously increased wind speed proportionally (increased
daily ambient wind velocity by 56% and maximum wind
velocity by 114%, Fig.2) to ambient wind speed. ese
treatments were effective in altering wind speed with the
intended magnitude of reduction or increase through-
out the day across the growing season (Fig.2). is new
experimental design has been able to reveal how four
morphologically different steppe plant species, includ-
ing two shrubs and two forbs, responded in apparently
adaptive ways to both reduced and increased wind speed.
Overall, these responses showed both common patterns
among these species, especially for traits related to plant
and organ size, and idiosyncratic patterns, which were
seen mostly for traits related to shoot and leaf properties.
Correspondingly, we will first discuss the commonalities
in trait response among the species, followed by a focus
on the traits that showed idiosyncratic responses among
species. We will also discuss the possible confound-
ing influences of the treatments on plant performance
via microclimate effects on leaf boundary layer and gas
exchange, which we did not measure. Finally we will dis-
cuss the effects of our wind treatments and their future
application.
Common response patterns ofplant size related traits
amongspecies
In general, plants can adapt to wind stress at the whole-
plant level (i.e. besides possible effects via photosynthesis
Table 1 Eects ofspecies andwind velocity treatments, andtheir interactions onplant traits
Italic type indicates signicant dierences at p < 0.05
Plant traits Species (S) Wind treatments (T) S × T
F P F P F P
Morphology
Height 43.16 < 0.001 20.06 < 0.001 1.31 0.268
Projected crown area 146.12 < 0.001 32.33 < 0.001 3.09 0.012
Stem base diameter 204.97 < 0.001 10.51 < 0.001 3.00 0.013
Root length 71.48 < 0.001 10.35 < 0.001 1.59 0.167
Overall bifurcation ratio 10.52 < 0.001 2.26 0.113 3.35 0.007
Stepwise bifurcation ratio(1:2) 13.18 < 0.001 3.29 0.044 3.47 0.005
Leaf length 359.76 < 0.001 4.81 0.012 1.03 0.413
Leaf area 51.88 < 0.001 0.73 0.485 0.29 0.939
Specific leaf area 248.26 < 0.001 0.08 0.921 0.30 0.937
Biomass and allocation
Total biomass 171.96 < 0.001 9.60 < 0.001 0.35 0.908
Shoot biomass 246.47 < 0.001 10.67 < 0.001 0.17 0.846
Root biomass 19.01 < 0.001 2.63 0.080 0.77 0.599
Root/shoot ratio 61.17 < 0.001 10.82 < 0.001 7.40 < 0.001
Mechanical properties
Stem lignin content 11.71 < 0.001 0.38 0.687 0.72 0.637
Stem cellulose content 5.41 0.002 1.67 0.196 7.90 < 0.001
Lignin/cellulose ratio 11.16 < 0.001 0.7 0.500 3.11 0.010
Second moment of area (I) 16.57 < 0.001 1.51 0.231 3.79 0.003
Young’s modulus (E) 10.93 < 0.001 10.63 < 0.001 4.52 0.001
Flexural stiffness (EI) 14.68 < 0.001 3.09 0.054 0.69 0.660
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Page 9 of 16
Zhangetal. Plant Methods (2021) 17:5
and transpiration) either by reducing the mechanical
stress through lower height and smaller crown; and/or
by increasing the resistance abilities via increasing stem
base diameter, root length, and/or changing mechani-
cal properties. Our results showed that across species,
wind velocity significantly affected plant shoot biomass
and morphology traits at the whole-plant level, particu-
larly plant height, projected crown area, stepwise bifur-
cation ratio, root length and stem diameter. Increased
wind velocity had negative effects on plant height, PCA
and total biomass across all species. In the two shrub spe-
cies (A. ordosica and C. intermedia), SBR(1:2) also showed
a negative trend with the increase in wind velocity. In
contrast, there were positive trends with root length in all
species. SBR(1:2) indicates directly branching conditions
in the current year [52], and decreased of SBR(1:2) means
that plants reduce the numbers and densities of branches.
Together with a decrease of PCA, lower SBR(1:2) will
reduce the wind drag to whole plants. ese results are
consistent with most previous studies on single plant
species, where plant height usually decreased and stem
base diameter increased at high wind velocity [12, 14,
15], plant biomass and PCA decreased [4, 10] and root/
shoot ratio increased [9, 16]. In summary, across species,
plants will reduce the mechanical stress caused by wind
through smaller stature and increase the physical resist-
ance against wind through deeper and coarser roots.
Treatment D had stronger effects on size-related traits
than treatment I, such as on PCA in A. ordosica and C.
intermedia, height of C. intermedia and S. ruthenica, and
shoot biomass of C. intermedia and A. squarrosum. How
can we explain this? Firstly, on an evolutionary time scale,
windy conditions have probably been more common than
still conditions [5355]. e monthly mean wind speeds
during our experimental period were below 2.5m/s, i.e.
were lower than those in most other parts of the Inner
Mongolian Plateau region. Regional ecotypes may thus
be adapted to higher wind exposure. Secondly, there was
a 71% reduction and a 56% increase of daily wind velocity
and a 67% reduction and a 114% increase of daily maxi-
mum wind velocity compared to the control treatment.
is difference in treatment effect may have led to differ-
ent effect sizes of response. By adjusting the height and
length of the artificial air baffles in treatment I, we should
be able to adjust the wind speed increase. Longer baffles
will be needed to obtain stronger wind forces to cover the
Table 2 Eects ofwind velocity treatments onplant traits ofA. ordosica, C. intermedia, A. squarrosum, andS. ruthenica
based onone-way ANOVAs
Italic type indicates signicant eects at p < 0.05
Plant traits A. ordosica C. intermedia A. squarrosum S. ruthenica
F P F P F P F P
Morphology
Height 1.82 0.201 15.55 < 0.001 2.51 0.131 6.40 0.010
Projected crown area 10.97 < 0.001 10.57 0.003 1.64 0.238 25.24 < 0.001
Stem base diameter 5.50 0.016 0.59 0.567 4.11 0.038 2.13 0.155
Root length 8.57 < 0.001 0.50 0.617 5.48 0.017 3.00 0.085
Overall bifurcation ratio 6.03 0.012 4.71 0.026 1.29 0.304 16.36 < 0.001
Stepwise bifurcation ratio(1:2) 6.51 < 0.001 4.23 0.035 0.91 0.423 3.38 0.062
Leaf length 2.97 0.082 5.51 0.016 0.30 0.747 4.40 0.031
Leaf area 0.06 0.942 4.52 0.029 3.79 0.047 0.04 0.966
Specific leaf area 1.15 0.342 0.51 0.610 0.01 0.992 0.19 0.826
Biomass and allocation
Total biomass 3.04 0.078 6.94 0.007 0.93 0.415 1.85 0.192
Shoot biomass 1.22 0.323 9.22 0.002 4.45 0.030 1.99 0.171
Root biomass 1.39 0.279 2.53 0.113 0.85 0.448 0.60 0.561
Root/shoot ratio 2.50 0.121 4.52 0.049 5.06 0.021 0.10 0.907
Mechanical properties
Stem lignin content 0.59 0.566 0.01 0.993 0.14 0.870 1.51 0.252
Stem cellulose content 13.72 < 0.001 0.12 0.885 25.94 < 0.001 2.68 0.101
Lignin/cellulose ratio 4.74 0.025 0.02 0.984 4.52 0.029 0.68 0.522
Second moment of area (I) 8.80 < 0.001 2.54 0.124 1.56 0.243 6.43 0.014
Young’s modulus (E) 11.83 < 0.001 5.57 0.021 0.70 0.513 6.93 0.011
Flexural stiffness (EI) 3.70 0.049 0.27 0.770 1.10 0.359 1.86 0.201
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Page 10 of 16
Zhangetal. Plant Methods (2021) 17:5
full range of wind velocities different plants may experi-
ence not only in steppe but also in other ecosystems.
Idiosyncratic shoot trait response patterns amongspecies
Mechanical perturbation caused by wind in nature has
long been examined [12, 16], and is known to change the
flexibility and rigidity of plant stems or petioles [9, 19,
56]. Plants may either develop flexible stems for reduc-
ing the stress imposed by wind drag force; or stiff stems
to resist wind [19, 57, 58]; and there may be trade-offs
between these two aspects. erefore, the response pat-
terns of shoot traits, especially mechanical properties,
to wind velocity is expected to be idiosyncratic among
species.
In this experiment, wind significantly increased the
second moment of area (I) of A. ordosica and decreased
Young’s modulus (E) of stem of A. ordosica and S. ruthen-
ica, resulting in a significant increase of Flexural stiffness
(EI); while wind did not significantly affect EI in the other
three species. is is consistent with previous studies
[59, 60], in which EI remained constant or increased. Yet,
a constant EI value does not mean that the mechanical
properties do not change, because EI depends on both E
and I. Actually, wind significantly increased E in C. inter-
media, and I in S. ruthenica in our experiment; while
wind did not change E, I or EI in A. squarrosum. us,
both A. ordosica and S. ruthenica tended to become more
flexible under strong wind stress while C. intermedia
shoots tended to increase their rigidity.
e change in EI in this experiment is likely a result of
the change in stem base diameter, change in symmetry
and/or amounts of chemical compounds such as plant
stem cellulose content, all of which may have influenced
the flexibility of the stem [60]. SBD is tightly correlated
with I, the rigidity index [7]. In A. ordosica, the increase
of SBD in treatment I corresponded with the increase of
I, and thereby increased EI. But the increase of SBD in A.
squarrosum did not coincide with changes in mechanical
properties, which may be attributed to the cancellation
effect of a reduction of cellulose content.
Fig. 3 Plant size and shape traits of four plant species under different wind treatments. Plant height (a), projected crown area (b), root length (c)
and STEPWISE bifurcation ratio(1:2) (d). Decrease, CK (ambient) and Increase refer to wind velocity treatments. Different lowercase letters indicate
significant differences among treatments at p < 0.05. The error bars are plotted by means ± SE
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Page 11 of 16
Zhangetal. Plant Methods (2021) 17:5
Most of the time, the effects of wind on plants are mod-
ified by other environmental factors. e responses to
wind are specifically modified by shading, the nutritional
status of plants, by soil water and inherent plant traits,
such as clonality [16, 19, 32, 61]. ese factors may also
enhance the idiosyncrasy of shoot trait response patterns
to wind among species. Additionally, in the Mu Us Sand-
land, Aeolian sand displacement is an important environ-
mental factor. Wind denudation and sand burial are the
two main sand mobility processes that will also modify
the effects of wind on plants (see “Background”). For
example, the root to shoot ratio of A. ordosica seedlings
was found to increase while the height and stem diam-
eter decreased under wind denudation of the soil surface
[27, 62]. e E, I and EI of C. intermedia were found to
decrease with sand burial [23]. ese traits were also
influenced by our experimental wind perturbation. us,
plant responses to sand movement may also modify plant
wind resistance traits. Although the influences of wind-
blown sand on plants were minimized in our experi-
ment, it is still a very interesting question to address in
further studies. In-depth studies are needed to focus on
the effects of confounded factors related to climate, soil
properties, Aaeolian sediment and inherent plant traits
on response patterns to wind.
Indirect wind eects onspecies’ performance
throughchanging microclimate
Under field conditions, besides affecting plant perfor-
mance through changing their leaf traits, wind can also
influence photosynthesis and transpiration through
changing the microclimate. Different from branches and
trunks, leaves are highly flexible, and only very strong
wind gusts could cause significant damage, such as being
torn, shredded or pulled off the branches [63]. Under less
extreme wind condition, many previous studies on single
species found that wind reduced the number of leaves,
leaf area and leaf dry mass, with an increase of leaf thick-
ness [5, 7, 1719, 27]. Our results showed that, across
plant species, wind significantly affected leaf length only,
but had no significant effects on leaf area or SLA. e leaf
traits measured also showed very different response pat-
terns to wind.
Wind speed plays an important role in the micro-
climate around a leaf attached to the plant. Increased
wind velocity could result in lower leaf boundary layer
Fig. 4 Plant biomass and its allocation in four plant species under different wind treatments. Decrease, CK (ambient) and increase refer to wind
velocity treatments. Different uppercase and lowercase letters indicate significant differences among treatments at p < 0.05. The error bars are
plotted by means ± SE
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Page 12 of 16
Zhangetal. Plant Methods (2021) 17:5
conductance which can cool the leaves and improve gas
exchange at higher temperatures [64, 65]. At low ambient
air temperature, photosynthesis may be reduced due to
below-optimal leaf temperatures and stomatal conduct-
ance [5, 16, 18].
In contrast, at low wind speed, a thicker leaf boundary
layer may cause high leaf temperatures and inhibit pho-
tosynthesis. In treatment D, the peak wind velocity at
noon was on average less than 0.5m/s (Fig. 2b). Under
such conditions the already high air temperatures (Addi-
tional file1: Fig. S3) will be amplified by the boundary
layer potentially risking acute heat damage [63]. e neg-
ative effects of low wind treatments on leaf performance
through excessive leaf temperatures may explain why
total biomass did not increase in three species out of four
(i.e. except C. intermedia) under our low wind treatment.
Smaller or narrower leaves are more suited to withstand
high air temperature due to better convective dissipation
[63]. is could explain why the leaf area of A. ordosica
and S. ruthenica did not increase significantly under low
wind treatment, even though leaf area tended to increase
at low wind condition overall. At the same ambient air
temperature, pinnate leaves dissipate heat more effec-
tively than simple ones [63]. C. intermedia has pinnate
leaves, which should help it to cope with high air tem-
perature. Trichomes can also help leaves to substantial
reduce sunlight absorption, which can reduce the dam-
age due to low wind and high temperature [63]. ere
were 10–50 trichomes/mm2 on the leaves of A. squar-
rosum and more than 50 trichomes/mm2 on the leaves
of C. intermedia [66]. is may explain why leaf area of
C. intermedia and A. squarrosum could increase signifi-
cantly under low wind velocity.
Eects ofthewind treatments andits future application
Our new field wind-funneling design (I) showed high
potential in synchronously increasing the wind velocity
in the treatment area roughly in proportion to the ambi-
ent wind velocity. rough the four funnel entrances in
four different directions, the wind can be accelerated in
Fig. 5 Shoot property traits linked to wind resistance in four plant species under different wind treatments: a Stem cellulose content, b Young’s
modulus (E), c Second moment of area (I), and d Flexural stiffness (EI). Decrease, CK (ambient) and Increase refer to wind velocity treatments.
Different lowercase letters indicate significant differences among treatments at p < 0.05. The error bars are plotted by means ± SE
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Page 13 of 16
Zhangetal. Plant Methods (2021) 17:5
different directions, which ensures that with the change
of wind direction, the wind flowing through the fun-
nel can be continuously accelerated in an effective way.
According to formula Vout = (s+
2
l)Vin/s, it is possible to
adjust the wind speed increase by adjusting the length of
the artificial air baffles. Wind acceleration effects can be
estimated according to the quadrat length and the length
of baffles. In another ongoing experiment of ours, we are
also attempting to use this design at community scale
to detect the response of A. ordosica community to the
increased wind speed (Additional file1: Fig. S7A). In that
experiment, 4m × 4 m quadrats were set out and four
5m long and 1.2m high baffles were used to increase the
wind velocity. e results showed that the wind funnel
design also had potential to be used at community scale
(Additional file1: Fig. S7B–D). e experimental wind
baffles (treatment I) increased daily ambient wind veloc-
ity by 47% and maximum wind velocity by 130%, while
decreasing ambient air temperature by 0.7°C on average.
e height of the baffle would not affect wind velocity
increase in our ideal model, while increasing the baffle
height would make the funnel closer to the sealed sta-
tus, which should make the results for the wind increase
treatment closer to those calculated by the model. us,
we suggest that the height of the baffle should also be
considered when building new wind funnels for getting
better acceleration results. Additionally, according to
the fluid continuity equation, the border of the exit side
of the wind funnel has the shortest width, which means
that the wind velocity peak appears at this point. Because
the quadrat was set at 1m × 1m in our experiment, i.e. a
small area, the wind velocity may not vary much within
the quadrat. In larger quadrats wind might decline
through the quadrat in the wind flow direction. Such a
gradient in the wind velocity should also be considered in
future studies.
Our wind shield design (D), like many other wind
reduction designs, was effective in decreasing wind
velocity. However, the use of wind shields could cause
two main confounding effects: light shielding and heat
trapping. e choice of using transparent plastic sheets
was based on the intention to minimize the influence
of the wind shield on the light regime. However, we
are aware that the plastic sheets used in treatment D
could alter light quality somewhat by intercepting or
reflecting certain wavelength bands more than oth-
ers. Especially the red: far-red ratio could have been
affected, which is known to affect several plant perfor-
mance parameters [67, 68]. Also, the reflection of the
red and far-red part of the light spectrum might have
caused a minor increase of air temperature. In future
experiments of this kind, a material should be used that
causes minor and evenly distributed interception and
reflection of the whole range of plant-relevant wave-
lengths and the actual interception should be meas-
ured. Our wind decreasing treatment increase the air
temperature (especially around noon) by, on average,
1.7°C; even though the rationale of this treatment was
to decrease wind velocity simultaneously with wind
velocity enhancing methods under field conditions in
a way that had minimal influences on the other envi-
ronmental factors. is drawback may be overcome
by adjusting the fencing method. For example, we also
tried a slightly different design with a larger fencing
area and distance between quadrat and fences (Addi-
tional file1: Fig. S7A); this design seemed to have less
influence on the air temperature (increase by 0.03°C
on average; from our unpublished data). us, we sug-
gest that, with such improvements, this wind reduction
method can still be effective and economical for use in
field wind manipulating experiments.
Finally, we did not focus on the influence of the wind
on the reproductive traits of plants, as the early harvest
(needed for accurate measurement of E) did not allow
for enough flowering or fruiting. However, it would be
interesting to test whether the influence of wind could
carry over to the next generation via the phenotypes of
the seeds (e.g. through amount of reserves). Also, future
experiments could test if the wind treatments could favor
the survival and reproductive output of certain geno-
types within a population of a species, thereby potentially
also affecting the performance of future generations.
us we suggest that our wind design could be the per-
fect candidate for further experiments to address this
issue by collecting the seeds from plants from different
wind treatments and then sow them to study subsequent
generations.
Conclusions
Our new experimental method to continuously increase
wind speed, using wind-funneling baffles, enabled us to
partially validate our null hypothesis that there are com-
mon whole-plant responses to wind stress across dif-
ferent plant species; strong wind significantly affected
plant-size-related traits in our experiment. However, the
response patterns of shoot traits, especially mechanical
properties, to wind velocity were idiosyncratic among
species. Furthermore, the wind effects on plant perfor-
mance through changing leaf microclimate could be
negative or positive depending on confounding factors
including plant properties and local weather. In-depth
experiments are needed to disentangle these effects of
increasing wind on plant performance under different
wind speeds achieved through different dimensions of
wind-funneling baffles under field conditions.
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Page 14 of 16
Zhangetal. Plant Methods (2021) 17:5
Supplementary Information
The online version contains supplementary material available at https ://doi.
org/10.1186/s1300 7-020-00705 -2.
Additional le1: TableS1. The specifications of all the instruments used
in the experiment. Fig. S1. The distribution of wind direction of maximum
wind speed from 2005 to 2015 at the meteorological station at Ordos
ecological station. Fig. S2. Background environmental conditions during
experimental period at Ordos ecological station. (A) Rainfall and tempera-
ture pattern within 2017. (B) Monthly mean and maximum wind velocity
within the experimental period (April to October of 2017). (C) Daily mean
and maximum wind velocity within the experimental period (April to
October of 2017). (D) The distribution of wind direction of maximum wind
speed from April to October of 2017. Fig. S3. Dynamics of air tempera-
ture (A), soil temperature (B), relative humidity (C) and volumetric water
content (D) (mean ± SE) under different wind treatment over 24 h during
the experiment period. D in the legend means decreased wind velocity
treatment, CK means ambient wind velocity treatment, and I means
increased wind velocity treatment. Fig. S4. Comparison of the wind
treatment effects between the whole data set and the westerly-wind data
subset extracted from the whole data set. D means decreased wind veloc-
ity treatment, CK means ambient wind velocity treatment, and I means
increased wind velocity treatment. D-W, CK-W and I-W, respectively, are
the westerly subsets of the data for the decreased, ambient and increased
wind velocity treatments. Fig. S5. Response of various traits to different
wind velocity treatments in four plant species: Leaf length (A), leaf width
(B), leaf area (C), SLA (D), overall bifurcation ratio (E), Stem base diameter
(F), and stem lignin content (G). Decrease means decreased wind velocity
treatment, CK means ambient wind velocity treatment, and Increase
means increased wind velocity treatment. Different lowercase letters indi-
cate significant differences among the three treatments at P < 0.05. The
error bars are plotted by means ± SE. Fig. S6. Results of the redundancy
analysis (RDA) for the four plant species: distribution of each treatment of
4 plant species on the RDA1 × RDA2 plane. The relationship is significant
(p < 0.01) based on 999 permutations. The adjusted R2 is 0.61. Suffix D of
plant species name in the legend represents decrease wind velocity treat-
ment, CK represented ambient wind velocity treatment, and I represented
increase wind velocity treatment. The first dimension (RDA1), which
describes 34.81% of the total variability, is positively correlated with stem
cellulose content, root/shoot ratio and I, and negatively correlated with
total biomass, shoot biomass, root biomass, plant height, leaf length, stem
base diameter, leaf area, SLA, projected crown area, stem lignin content, E,
EI, OBR and SBR(1:2). The second dimension (RDA2), which explains 16.86%
of the total variability, is positively correlated with EI, I, stem base diameter,
leaf area, OBR and SBR(1:2), while it is negatively correlated with root
length, stem cellulose content, E, projected crown area and SLA. For trait
abbreviations see the main text. Fig. S7. Application of wind manipulation
design at community scale (4 m × 4 m quadrat, A. ordosica community)
from our ongoing experiment. (A) Picture of the experiment set and detail
of treatments. The Decreased wind velocity treatment (D) was imple-
mented through a wind shield. The plastic chambers did not have a roof,
so that ambient air could mix with that in the cubicles freely. Distances
were kept between the wind shield and quadrat to avoid shading effect.
There was no manipulation for the ambient treatment (CK). The Increased
wind velocity treatment (I) was implemented through experimental wind
baffles. We placed sheets at each side directed towards the North-East,
North-West, South-East and South-West, respectively from each quadrat
with plants, to converge and increase wind velocity. (B) Diurnal mean
wind velocity pattern (mean ± SE) over 24 h under wind treatments. (C)
Diurnal maximum wind velocity pattern (mean ± SE) over 24 h under
wind treatments. (D) Effects of wind treatments. The black dashed line
with the equation (
y=
(s+
2l)
sx
) represents the ideal wind velocity
that could be reached by acceleration. The black dashed line with the
equation (y = x) represents the wind velocity in the treatment CK. Red
dots and line represent the relationship between the temporally matched
hourly maximum wind velocity in I and CK. Blue dots and line represent
the relationship between the temporally matched hourly maximum wind
velocity in D and CK. Regression equations and R2 are given.
Acknowledgements
Special thanks to Mr. Qiang Zhang for the great support during the
experiment.
Authors’ contributions
SZ, GL, XY and ZH conceived the ideas and designed methodology; SZ and
QC collected the data; SZ, GL, JHC and XY analysed the data; SZ, XY, ZH and
JHC led the writing of the manuscript. All authors contributed critically to the
drafts. All authors read and approved the final manuscript.
Funding
This research was supported by the Strategic Priority Research Program of the
Chinese Academy of Sciences (XDA23080302), National Natural Science Foun-
dation of China (31470032), and the CAS President’s International Fellowship
Initiative (PIFI, 2018VCA0014) for JHCC.
Availability of data and materials
All data generated or analysed during this study are included in this published
article [and its additional information files].
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1 State Key Laboratory of Vegetation and Environmental Change, Institute
of Botany, Chinese Academy of Sciences, Beijing 100093, People’s Republic
of China. 2 University of Chinese Academy of Sciences, Beijing 100049, People’s
Republic of China. 3 Systems Ecology, Department of Ecological Science, Vrije
Universiteit, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands.
Received: 1 March 2020 Accepted: 24 December 2020
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Little is known about how the effects of mechanical perturbation (MP) on clonal semishrubs vary with soil water in inland dune ecosystems. To investigate this, a greenhouse experiment was conducted in which the seedlings of the clonal semishrub Hedysarum laeve were subjected to two levels of MP (non-MP vs. MP 60 s d-1) and two levels of water supply (200 vs. 400 mL d -1). MP induced plants to yield shorter stems with less rigidity, fewer leaves, thinner basal diameters, and less biomass; increased soil water allowed plants to produce taller stems, more leaves, thicker basal diameters, and more biomass. However, significant MP by water interactions on the growth and mechanical properties of H. laeve were not detected. These findings suggest that the effects of MP on the growth and mechanical properties of semishrubs may be independent of soil water.
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