Download Seasonal changes in vertical canopy structure in a

Ecol Res (2015) 30: 821–831
DOI 10.1007/s11284-015-1281-3
O R I GI N A L A R T IC L E
Youngkeun Song • Youngryel Ryu
Seasonal changes in vertical canopy structure in a temperate
broadleaved forest in Korea
Received: 26 December 2014 / Accepted: 13 May 2015 / Published online: 21 May 2015
The Ecological Society of Japan 2015
Abstract Field measurements of vertical canopy structure have been challenging for decades and still important for understanding forest ecosystems. We measured
the vertical canopy structure and its seasonal changes in
a temperate deciduous forest canopy in Gwangneung,
Korea. Time-series measurements of leaf area index
(LAI) were collected in 2013 from a five story (4-m
vertical intervals) tower. We evaluated crown depth and
species composition by height from a vegetation survey.
The vertical distribution of leaf and woody area density
was described from measurements taken during the leafon and leaf-off seasons, and averaged 0.18 and
0.04 m2 m 3, respectively. Three strata were characterized: (1) the dense upper crowns with large trees (>16m) of Quercus serrata, in which 29.3 % of the plant
materials were distributed; (2) abundant foliage
dominated by Carpinus laxiflora at about 16-m
(40.8 %); and (3) a diverse and well-developed understory vegetation at about 4-m (15.5 %), consisting of C.
laxiflora, Carnipus cordata, and Styrax japonica communities. Per-layer phenology of each species was successfully illustrated by the drastic increase in LAI during
the leaf-out season [days of the year (DOY) 110–140],
the full-leaved stage LAI of 3.4 ± 0.9 m2 m 2
(mean ±1 standard deviation), and a decrease during
the leaf-fall season (DOY 280–320). The seasonal variation in gap fractions reflected different light conditions
varying with canopy height. This type of vertical profile
Y. Song Æ Y. Ryu
Brain Korea 21 Plus Team, Seoul National University,
Seoul, Republic of Korea
Y. Ryu (&)
Department of Landscape Architecture and Rural Systems
Engineering, Seoul National University, Seoul 151-921,
Republic of Korea
E-mail: [email protected]
Tel.: 82-2-880-4871
Y. Ryu
Interdisciplinary Program in Agricultural and Forest Meteorology,
Seoul National University, Seoul, Republic of Korea
archive is valuable not only for comparing the structure
of various forests but also for monitoring changes in this
ecosystem in the future.
Keywords Foliage-height profile Æ Gwangneung Æ Leaf
area density Æ Leaf area index Æ Phenology
Introduction
Canopy structure, defined as the spatial arrangement of
the above-ground organs of plants (Campbell and
Norman 1989), provides key information to understand
the microclimate, ecological processes, succession, and
evolutionary history of a forest ecosystem (Lowman and
Rinker 2004). In particular, a number of studies have
highlighted the influence of canopy structure on forest
turbulence characteristics (Pereira and Shaw 1980, 1982;
Queck and Bernhofer 2010), forest hydrological cycles
(Crockford and Richardson 2000; Link et al. 2004; Song
et al. 2014), or radiation regimes and photosynthesis in
canopies (Ross 1981; Ellsworth and Reich 1993; Baldocchi et al. 2002). Thus, canopy structure should be
surveyed in the field, particularly to describe the nonuniform spatial distribution of plant materials, such as
leaves, stems, twigs, and branches. However, the difficulties of quantitatively describing canopy features and
their heterogeneity at various spatial and temporal scales
(Norman and Campbell 1989) remain challenging. Additionally, the limited number of data measurement
methods (Ishii et al. 2004) and the inaccessibility to the
height of upper canopies are further difficulties (Parker
et al. 1992).
Vertical canopy structure was formerly measured by
destructive sampling of plant materials based on the
stratified clip technique (Monsi and Saeki 1953, 2005).
This method quantifies the vertical distribution of the
total plant area by harvesting all plant materials in appropriate horizontal layers and separately measuring the
plant area in each layer. Although this required a
tremendous amount of fieldwork and could not be used
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to monitor temporal changes in the canopy, this method
was useful to describe less-studied forest ecosystems,
such as savanna and tropical forests of Thailand (Ogawa
et al. 1961), a mature dipterocarp forest in Borneo
(Yamakura et al. 1986), a Japanese larch plantation
(Satoo 1970), and representative forest types across Japan (Kira et al. 1969). Hutchison et al. (1986) measured
the vertical distribution of plant area and leaf inclination
angles directly within sampled volumes of a forest canopy instead of complete harvesting; however, this
method still required a large amount of detailed fieldwork on a hydraulic lift with a 20-m vertical extension.
In contrast, the point-quadrat method (Wilson 1960,
1965) was proposed to estimate foliage-height profiles.
This method involves non-destructive sampling because
the canopy structure is retrieved from a number of lineintercept samples (the position of leaf contact) taken
through the canopy in several predetermined directions.
This method has been used to vertically profile aspen
and oak stands in North America (Miller 1969) and a
chestnut coppice woodland in England (Ford and
Newbould 1971). However, this method is laborious and
involves the danger of working at heights, particularly
when conducted in mature stands in taller canopy layers.
Based on theories from these direct sampling methods, researchers have developed indirect and more efficient methods for estimating vertical canopy structure,
e.g., by measuring leaf-contact heights using a camera
with a telephoto lens fixed on a tripod (MacArthur and
Horn 1969; Aber 1979; Parker et al. 1989), or a laser
range finder (Radtke and Bolstad 2001), by measuring
canopy gap fractions using quantum sensors (Norman
and Jarvis 1975), or light-emitting diode (LED) sensors
(Ryu et al. 2010a) mounted at multiple canopy depths
(Ryu et al. 2014). All of these efforts attempted to
quantify vertical canopy profile, and focused on how to
describe canopy stratification (Parker and Brown 2000).
More technically, it was how to estimate leaf area density (LAD) or leaf area index (LAI) (Weiss et al. 2004) at
different canopy heights. A number of indirect methods
of estimating LAI have been developed, as reviewed in
Jonckheere et al. (2004) and evaluated [e.g. Ryu et al.
(2010c)] for widely used instruments such as hemispheric
photographs using a fisheye lens (Bonhomme and
Chartier 1972; Neumann and Den Hartog 1989; Zhang
et al. 2005) or a Plant Canopy Analyzer (LICOR Inc.,
Lincoln, NE, USA) (Chason et al. 1991; Welles and
Norman 1991; Cutini et al. 1998). However, the use of
these to estimate vertical structure has not been investigated extensively. Light detection and ranging (LiDAR) remote sensing has been developed as an efficient
means of estimating the spatial distribution of LAD
(Lovell et al. 2003; Hosoi and Omasa 2006, Hosoi and
Omasa 2009; Song et al. 2011). However, the method is
controversial due to its inconsistent results (Bater et al.
2011), which depend on the sensor configuration, site
characteristics, and the LiDAR data processing method.
Accessibility to the upper forest canopy is a critical
issue for surveying canopy structure. Traditional forest
scientists used a rope system (Perry 1978; Perry and
Williams 1981), ladder and aerial walkways (Muul and
Liat 1970), hydraulic lifts (Hutchison et al. 1986), canopy rafts (Sterck et al. 1992), or cranes (Parker et al.
1992) to approach higher canopy layers. Micrometeorological observation towers established by the
FLUXNET community (Baldocchi et al. 2001) have
enabled direct access to the entire vertical structure from
the forest floor to the above-canopy area and allow the
observation of forest phenology at multiple canopy
layers (Ryu et al. 2014). Currently, more than 630 flux
towers have been established within representative
ecosystems worldwide (http://fluxnet.ornl.gov/), and
may provide the opportunity to extend our observations
of those diverse ecosystems.
The Gwangneung experiment forest, an old natural
forest located in the west-central part of the Korean
Peninsula (Fig. 1), is a valuable ecosystem with a typical
climax community of local deciduous-broadleaved species dominated by Quercus spp. and Carpinus spp. (Lim
et al. 2003; Kang et al. 2009). This site has been designated as a national conservation area for research since
1929 and as a UNESCO Biosphere Reserve since 2010,
and continues to provide valuable study areas for researchers as a long-term intensive monitoring site.
About 300 studies on this ecosystem have been published in Korea, and a number of biometeorological
studies (Hong et al. 2008; Ryu et al. 2008; Kwon et al.
2010) using the tall flux towers (20 and 40 m heights) in
the forest have been reported. Previous studies attempted to estimate seasonal changes in on-ground LAI
of the deciduous forest district at this site using upward
hemispherical photographs (Lim et al. 2003) or Plant
Canopy Analyzer instrument (Kwon et al. 2010). However, these have limitations in terms of quantifying the
vertical structure of this forest. Ryu et al. (2014) successfully conducted tower-based observations of the
multi-canopy-layer phenology during the green-up season. However, further understanding would be achieved
by conducting observations of the vertical species composition throughout the year.
This study aimed to identify vertical canopy structure
and its seasonal changes in the Gwangneung temperate
deciduous forest in Korea, based on seasonal measurements of LAD (and LAI) at multiple canopy heights.
Specifically, we present the vertical structure in terms of
the (1) distribution of leafy and woody materials, (2) the
number of individuals and species composition, and (3)
seasonal variations in the total LAI, species-specific
LAD, and the light environment with height.
Materials and methods
Study site
The study site is located in a complex, hilly deciduous
forest catchment (220 ha) of Gwangneung, Pocheon-
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Fig. 1 Location of study site and sampling design
si, Gyeonggi-do, Republic of Korea (37.748717N,
27.148176E, elevation: 260 m; Fig. 1). The mean annual air temperature at the site is 11.5 C, and the mean
annual precipitation is 1332 mm. The local climate is a
typical temperate climate, with hot, wet summers under
the effect of the East Asian monsoon and a dry winter
with snow. A walkable 20-m-high tower was built in the
forest to measure ecological variables in the canopy
layers. We studied vertical canopy structure using this
tower. The topography around this tower slopes downward at about 10 in an easterly direction. More detailed
information about this site has been published previously (Lim et al. 2003; Kim et al. 2006; Kang et al. 2009).
LAI measurements and data processing
LAI at a particular canopy height was determined from
the gap fractions measured using an LAI-2200 Plant
Canopy Analyzer. This optical sensor records hemispheric radiation at five rings (centered at 7, 23, 38,
53, and 68) for light below 490 nm; these wavelengths
were used to reduce errors from light transmitted and
reflected by the canopy. Below-canopy light intensity
was measured in five tower layers (every 4 m), towards
the north, west, and south directions per layer and three
times (right-side, center, and left-side) per direction. We
used a 90 viewing cap on the LAI-2200 lens for the
directional measurements. We excluded the east-directed
observations because of large canopy openness induced
by the topography and fallen trees. Cho (1992) reported
that a large gap size >200 m2 is abnormal (<8 % of all
gaps) in Gwangneung Forest and that most of the gaps
in this forest are small and made by only a few fallen
trees. Therefore, our survey did not include this ‘‘abnormal’’ quarter in the easterly direction of the circular
plot (Fig. 1). Above-canopy light intensity was measured at the top of the 20-m tower before and after the
below-canopy measurements. We also collected paired
sunlit and shaded measurements with a diffuser cap to
compute the beam proportion of incoming light to remove scattered light caused by the canopy, which causes
underestimation of the LAI; we used a 270 viewing cap
to compute directional variation in the sky radiation,
according to Kobayashi et al. (2013), which enabled us
to use this instrument during daytime. Measurements
based on this protocol were conducted through days of
the year (DOY) 105 (April 15) to 317 (November 13),
which was sufficient to observe the phenology of this
forest.
The measured time-series LAI data were corrected
for the pattern of seasonal change in the gap fractions.
The ideal shape of a seasonal change in the gap fraction
would be close to a u-shaped curve because it decreases
as the canopy closes during leaf-out and increases as the
canopy opens during leaf-fall. We occasionally encountered unexpected outliers in a series of measurements.
Plant materials that were not viewed in other observations seemed to be included on some specific dates. We
may have had some inconsistent measurement positions,
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although we attempted to measure at the same positions
as much as possible. We replaced these erroneous measurements with values linearly interpolated from the
corresponding gap fractions measured before and after
the current observations. This correction process was
applied to all observations at the same positions and
rings of the LAI-2200. We averaged the logarithm of gap
fractions instead of the logarithm over the mean of gap
fractions to account for foliar clumping effects in computing LAI (Ryu et al. 2010b).
Evaluation
LAI measurements were evaluated using the results of
Ryu et al. (2014), who estimated seasonal changes in
LAI at the same study site using upward-pointing digital
cameras and LED sensors. The LED sensors, which
were used as spectrally-selective light detectors (Ryu
et al. 2010a), enabled us to estimate LAI through Beer’s
Law by measuring incoming irradiance at different canopy depths (Ryu et al. 2014). Our measurements were
compared with the average LAI for 5 days (i.e., 2 days
before and after the corresponding day), so we could
match the LAIs even though the observations of Ryu
et al. (2014) may not have been performed on the same
day. Seasonal measurements of the whole canopy LAI in
this study (i.e., LAIs measured in the bottom layer in
Fig. 1) were compared to the observations in Ryu et al.
(2014), using upward digital-cameras installed on the
ground at breast height and LED sensors mounted at
2 m height of the tower in Ryu et al. (2014). LAI values
of the overstory (12–20 m) and understory (2–12 m)
canopy layers in Ryu et al. (2014) corresponded to the
sum of the per-layer LAIs at the top to the second and
the third to the bottom in Fig. 1, respectively.
Vegetation survey
A tree survey was conducted within a 20-m radius of the
tower to identify species structural characteristics (Fig. 1).
A quarter in the east direction of our circular plot was
excluded from this tree survey, because the LAI measurements did not cover that area (see ‘‘LAI measurements and
data processing’’). Tree species, diameter at breast height
(DBH), crown top height, and crown base height were
measured for all trees in the plot with DBH >3 cm.
Analysis
The vertical distribution of leafy and woody parts in the
forest was quantified using the LAI measurements during the leaf-on and leaf-off seasons, respectively. All LAI
measurements were converted to LAD by taking the
difference in the LAI values of the neighboring two canopy layers and dividing this difference by the vertical
interval of observations (i.e., 4 m in this study). The
maximum LAD value at each measured height during
the full-leaf season [from DOY 138 (May 20) to DOY
249 (September 6)] was regarded as the total magnitude
of plant materials, including both leafy and woody
parts. The woody parts were quantified using the woody
area density (WAD), which was measured during the
leaf-off season [DOY 105 (April 15)] as the LAD.
We derived a crown depth diagram from the vertical
distribution of tree heights collected during the field
survey. According to Ogawa et al. (1961), cumulative
curves for crown top and base heights could be determined based on the relative frequency of the number of
trees. Then, crown depth was calculated from the difference between the two curves. A crown depth diagram
was obtained for each dominant species and was used to
discuss species composition at different canopy heights.
The phenology of each layer was described based on
the time-series LAI measurements at different canopy
heights, and specified into the phases of selected dominant species. The contribution of selected species to the
LAD and WAD values in each layer was determined by
the ratio of the number of individuals of the selected
species to the total number of individuals in the layer.
We also used the weighted average values of gap fractions in the five rings of LAI-2200 to show the light
condition inside the canopy. The weighting factor for
each ring was determined by multiplying the sine of the
mean zenith angle by the corresponding ring-width (radians), and normalized to sum to 1.0, according to LICOR (2009).
Results
Evaluation of LAI measurements
The LAI measurements agreed well with the LAI estimates of Ryu et al. (2014) (Fig. 2). LAI values measured
on the forest floor (i.e., total LAI estimates in all canopy
layers) throughout the year using the LAI-2200 instrument in this study presented a linear relationship with
the digital camera [r2 = 0.91, root mean square error
(RMSE) = 0.39, bias = 0.01] and LED sensor estimates (r2 = 0.90, RMSE = 0.33, bias = 0.10) of
Ryu et al. (2014) (Fig. 2a). Seasonal measurements of
the canopy stories (Fig. 2b) also exhibited good agreement between our study and that of Ryu et al. (2014),
showing r2 = 0.91 (RMSE = 0.23, bias = 0.05) for
the over-story and r2 = 0.56 (RMSE = 0.25, bias = 0.06) for the understory. These measurements
suggested that the subsequent analysis based on our LAI
measurements was acceptable.
Vertical structure of leafy and woody parts
Figure 3 describes vertical canopy structure by the LAD
profile. Vertically averaged LAD during the full-leaf
825
the uppermost canopy layer (0.27 m2 m 3 in LAD), although the amount of woody materials were almost
identical to each other (0.06 m2 m 3 in WAD of both
layers). Therefore, seasonality in terms of leaf-out and
leaf-fall was most remarkable in this layer. On the other
hand, little seasonal change was observed in the layers at
heights of 4–8 and 8–12 m because of the small amount
of leaves present at those heights; those LAD records
mostly resulted from woody materials, not from leaves,
because there was little difference between the values of
LAD and WAD (0.02 and 0.05 m2 m 3, respectively).
Species composition at different heights
Fig. 2 Cross validation of the leaf area index (LAI) measurements
in this study with those of Ryu et al. (2014), depending on a the
instruments used and b the heights measured
Fig. 3 Vertical distribution of the leafy (right-hand section) and
woody (left-hand section) parts of trees. Open dots with error bars
are plotted from the gap fraction statistics at the measured height
and represent the average gap fraction value and range, respectively
season was 0.18 ± 0.13 m2 m 3 (mean ± 1 SD). LAD
during the leaf-off season (i.e., WAD) less varied vertically than LAD of the full-leaf season, with
0.04 ± 0.02 m2 m 3 at the vertical average.
The structural details were assessed by comparing the
WAD with the LAD at the same height. The canopy at
heights of 12–16-m (0.37 m2 m 3 in LAD) had the most
abundant foliage in vertical distribution, even more than
Ninety-six individuals of 14 species (DBH >3 cm)
were identified in the study area. The species composition was characterized by large-sized Quercus serrata
(50.6 ± 11.7-cm DBH) and C. laxiflora (29.9 ± 11.6cm DBH), and large numbers of Carpinus cordata and S.
japonica (Table 1).
The cumulative curves in Fig. 4 show the vertical
distribution of the number of trees at the study site. The
slight increases in the cumulative crown top and base
height curves at heights >16 and >12 m, respectively,
reflect the small number of trees in the over-story
(Fig. 4a). A drastic increase in both curves, particularly
from 8 to 4 m, represents the large number of understory trees at those heights. The crown depth curve,
which was derived from the difference between both
curves, effectively described the vertical profile of leafy
parts and its stratified structure, based on the number of
individuals. According to this crown depth curve, canopy structure was stratified with the following three
layers: (1) top layer >16 m, with a small number of
trees; (2) intermediate layer from 16 to 8 m, with a small
number of trees; and (3) bottom layer from 8 to 2 m,
with a large number of trees.
The crown depth curves for selected species (Fig. 4b)
illustrate the species composition according to height.
The top layer was occupied only by large oak trees (Q.
serrata). The upper crown of the intermediate layer was
dominated by Carpinus laxiflora, but the species composition of the lower part of this layer was diverse. The
under-story trees in the bottom layer consisted of C.
laxiflora, C. cordata, and S. japonica communities.
Phenology with height
Figure 5 clearly shows the phenological characteristics
of the deciduous forest; the drastic increase in LAI
during the leaf-out season (DOY 110–140), a relatively
stable phase during full-leaf period (DOY 140–280), and
a decrease during the leaf-fall season (DOY 280–320).
The spatial variation in LAI of all canopy layers during
the full-leaf season was 3.36 ± 0.88 (mean ± 1 SD;
range 1.81–4.90). LAI values for DOY 317 were greater
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Table 1 Trees within the footprint of the leaf area index (LAI) measurements
Species
Quercus serrata
Carpinus laxiflora
Carpinus cordata
Styrax japonica
Acer pseudosieboldianum
Rhus trichocarpa
Sorbus alnifolia
Fraxinus rhynchophylla
Cornus kousa
The others
No. of trees
15
9
17
16
9
5
5
3
3
6
Stem density (trees ha 1)
159.2
95.5
180.5
169.9
95.5
53.1
53.1
31.8
31.8
63.7
DBH (cm)
Crown top
height (m)
Crown base
height (m)
Mean
SD
Mean
SD
Mean
SD
50.6
29.9
10.1
6.7
5.2
4.3
4.2
7.9
7.2
6.0
11.7
11.6
4.2
2.1
2.0
0.5
0.8
6.2
4.7
4.2
20.5
13.3
7.4
6.2
4.8
5.3
5.2
4.2
7.1
5.5
7.3
3.1
1.8
1.6
1.3
0.9
2.2
2.4
3.4
3.9
10.6
6.9
2.2
2.9
2.4
3.4
1.8
2.3
2.9
2.1
3.9
2.2
0.6
1.5
0.5
0.6
0.4
1.2
1.0
1.3
Only individuals with a diameter at breast height (DBH) >3 cm were surveyed
Fig. 4 Crown depth diagram based on the
distribution of crown heights and the
number of individuals. The crown depth
curve was derived from the difference in
cumulative curves between the crown top
and base heights (a), and was partitioned by
species (b)
than those for DOY 105 because some senescent leaves
remained attached to branches.
Species-specific phenology in vertical structure (Fig. 6)
reveals that how the dominant species are changing the
amount of leaves at each layer through the seasons.
Seasonal change of LAD values in Q. serrata ranged from
0.07 to 0.27 m2 m 3 over 16-m height throughout the
year, while the other species had no foliage at this height.
The 12–16 m layer was the most competitive heights for
seasonal development of foliage, and was dominated by
C. laxiflora (0.04 to 0.20 m2 m 3 of LAD), followed by
Q. serrata (0.02 to 0.08 m2 m 3) and the other species
(0.02 to 0.10 m2 m 3). Carpinus cordata and S. japonica
showed similar seasonal variations of LAD at heights
under 12-m. The variation in seasonal LAD values was
larger at lower heights because more trees in these species
were found at the height closer to the forest floor.
Variation in relative light intensity at different heights
Figure 7 shows the spatial and temporal variations in
gap fractions in terms of measured height. Gap fractions
in the highest canopy layer were 20–100 % (Fig. 7a; see
vertical error bars), particularly during the full-leaf
season of DOY 224–302. In contrast, the light environment on the ground (Fig. 7e) was more homogenous, as
the range of variation in gap fractions (i.e., vertical error
bars) was <20 % throughout the year. These changes in
vertical light conditions occurred gradually in the intermediate canopy layers (Fig. 7b–d); a larger variation
in the upper canopy and a smaller variation in the lower
canopy were observed in the year-round measurements.
In addition, this tendency in light conditions to vary
with height depended on the vertical distribution of
plant materials. The dots in Fig. 3 indicate that the re-
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lative light intensity (i.e., gap fraction) on the forest floor
averaged 11.5 % under a full-leaf canopy (the right-side
block) but 54.5 % without foliage (left block). The range
in the gap fractions was larger during the full-leaf season
than that during the leaf-off season, particularly in the
upper canopy.
Discussion
Quantification of vertical structure using leaf area
density
Fig. 5 Seasonal changes in cumulative leaf area index (LAI) values
measured at different canopy heights
Canopy structure was well-illustrated by using the vertical distribution of LAD (Fig. 3) and it was better than
using a single LAI value. As LAI, by definition, describes only a vertically ‘‘stacked’’ structure, limitations
remain for retrieving the vertical structure. Kira et al.
(1969) clarified the difference in vertical structures between two Castanopsis cuspidata stands, despite their
similar LAI values. Accordingly, the vertical profile beyond the LAI value was determined only by measuring
LAD at different heights. Using the LAD values, the
structural characteristics could be compared to those of
other forests. Vertically averaged full-leaved LAD (see
Fig. 6 Seasonal changes in the vertical distribution of leaf (bars in green color) and woody (bars in brown color) area density depending on
the selected dominant species
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Fig. 7 Time-series variations in the gap
fractions measured at canopy heights of
0–4 m (a), 4–8 m (b), 8–12 m (c), 12–16 m
(d), and >16 m (e). In these box and
whisker plots, the ends of the whisker are set
at 1.5 · IQR (interquartile range) above the
third quartile (Q3) and 1.5 · IQR below the
first quartile (Q1), where the IQR is Q3–Q1
‘‘Vertical structure of leafy and woody parts’’) was similar to that determined for other temperate deciduous
forests (0.1–0.3) (Tadaki 1966; Parker 1995). A Fagus
crenata community, a typical climax deciduous-broadleaved-forest in Japan, showed a similar vertical structure in terms of LAD values at corresponding heights
and strata (Kira et al. 1969). Compared to an oak forest
in Tennessee, USA (Hutchison et al. 1986), Gwangneung had a less closed canopy (i.e., lower LAD) in the
upper part, but a denser understory (i.e., higher LAD)
near the forest floor, and more noticeable multiple layers
with height.
Integrated interpretation of vertical leaf area density
and species distribution
The vertical canopy structure was clearly understood
based on information regarding the amount of plant
materials distributed (Fig. 3) and the number of individuals or species diversity at different heights (Fig. 4).
The upper crown (>16-m), in which 29.3 % of the
vertical LAD was distributed (Fig. 3), consisted of a few
large-sized Q. serrata (Fig. 4). Similarly, a small number
of large-sized C. laxiflora dominated the canopy from 16
to 12 m, which was the most-dense layer, comprising
40.8 % of the vertical LAD. However, large numbers of
understory trees of diverse species at about 4-m height
(Fig. 4) provided only a small canopy cover, which was
5.3 % at 8 to 4-m and 15.5 % at <4-m height.
Although this forest was dominated by old Q. serrata
(80–200 years old, Kang et al. 2009), a number of other
shade-tolerant tree species were present under the canopy besides Q. serrata saplings. Quercus spp. is less
competitive on the forest floor because it is a shadeintolerant species. Even in the improved light environment in gaps, Quercus spp. was suppressed because it
grows slowly; most of the gaps in this forest are small
and will close rapidly (Cho 1992). In contrast, Carpinus
spp. (C. laxiflora and C. cordata) was present at different
heights from the forest floor to the sub-canopy layer
because they are shade-tolerant and grow rapidly. Longlived Q. serrata is expected to dominate this forest, but a
drastic change in species composition may occur if a
large number of Quercus spp. die suddenly, e.g., due to
oak wilt disease, which is at present spreading in Korea.
Implication of phenology observations
The intervals among the phenology curves at different
canopy heights (Fig. 5) indicate per-layer seasonal
changes from WAD to LAD (Fig. 3), which has not been
reported previously. Ryu et al. (2014) quantified leaf-out
dates for over- and under-story canopy layers at the
current study site. Bi-weekly measurements by LAI-2200
829
at different canopy heights were useful in describing
vertical structure, but inadequate for estimating the leafout date because of low observation frequency. The LED
sensors and upward-pointing digital cameras yielded less
uncertainty in leaf-out estimates because those sensors
provided daily LAI values. However, the LED sensors
and upward-pointing digital cameras did not monitor
canopy structure in different directions per layer. Thus,
integrating the LAI-2200 and LED sensor/digital camera
could facilitate spatially and temporally continuous observations of multiple layers of the canopy structure.
Seasonal variation of total LAI (Fig. 5) was largely
driven by the two species, Q. serrate and C. laxiflora,
which formed the overstory canopy layer (Fig. 6). Seasonal variation of LAD in the other species appeared
relatively marginal, presumably because of the limitation
of the light environment. Our measurements can detect
this kind of unique phases of niche occupation and the
dynamics of forest vertical structure, depending on the
seasons, species, and canopy heights. Therefore, longterm and periodic campaigns to obtain these measurements could aid in gaining a better understanding of the
relationship among forest species composition and the
structure in relation to changing climatic factors.
The characteristics of the vertical light conditions
(Fig. 7) seemed closely related to sunfleck, which drives
a highly dynamic light environment with brief and often
unpredictable periods of direct solar irradiance (Chazdon and Pearcy 1991). The sunfleck in this forest more
appeared during the leaf-on season and in the upper
canopy layers. The sunfleck was ‘‘blurred’’ on the forest
floor because incoming solar irradiance was often intercepted or scattered by upper-layer plant materials.
Conclusion
We quantitatively evaluated the vertical canopy structure of a deciduous forest in Gwangneung, Korea using
a time-series of LAI measurements taken from multiple
stories of a tower located in the forest and a vegetation
survey. A small number of large and old Q. serrata trees
covered the uppermost canopy with dense leafy and
woody materials, and 30 % of the plant materials
were vertically distributed. The sub-canopy layer was
occupied mostly (40 %) by foliage rather than woody
materials, as it included large C. laxiflora. Despite the
few trees in the intermediate layer, diverse shade-tolerant tree species occurred near the forest floor (20 %).
Per-layer phenology of each species was described
successfully. However, more frequent measurements
would be required to identify days on which the characteristics of different canopy heights would be evident.
Measurements during the leaf-on and leaf-off periods
facilitated separate quantification of the spatial distribution of leafy and woody parts. The integrated interpretation of the vertical LAD distribution with crown
depth and species composition deepened our under-
standing of canopy strata characteristics. The gap fraction records used here for the estimation of LAI have the
potential to allow evaluation of light conditions inside
the canopy. These canopy structural data are valuable
and should be extended to diverse global ecosystems.
Acknowledgments This work was funded by the Korea Meteorological Administration Research and Development Program under
the Grant Weather Information Service Engine (WISE) project
(KMA-2012-0001-A). The authors were supported by BK21 Plus
Project in 2014 (Seoul National University Interdisciplinary Program in Landscape Architecture, Global Leadership Program Towards Innovative Green Infrastructure). English editing was
supported by the Research Institute for Agriculture and Life Sciences, Seoul National University.
References
Aber JD (1979) A method for estimating foliage-height profiles in
broad-leaved forests. J Ecol 67:1979
Baldocchi D, Falge E, Gu L, Olson R, Hollinger D, Running S,
Anthoni P, Bernhofer C, Davis K, Evans R, Fuentes J, Goldstein A, Katul G, Law B, Lee X, Malhi Y, Meyers T, Munger
W, Oechel W, KTP U, Pilegaard K, Schmid HP, Valentini R,
Verma S, Vesala T, Wilson K, Wofsyn S (2001) FLUXNET: a
new tool to study the temporal and spatial variability of
ecosystem-scale carbon dioxide, water vapor, and energy flux
densities. Bull Am Meteorol Soc 82:2415–2434
Baldocchi DD, Wilson KB, Gui L (2002) How the environment,
canopy structure and canopy physiological functioning influence carbon, water and energy fluxes of a temperate broadleaved deciduous forest—an assessment with the biophysical
model CANOAK. Tree Physiol 22:1065–1077
Bater C, Wulder MA, Coops NC, Nelson RF, Hiker T (2011)
Stability of sample-based scanning-LiDAR-derived vegetation
metrics for forest monitoring. IEEE Trans Geosci Remote Sens
49:2385–2392
Bonhomme R, Chartier P (1972) The interpretation and automatic
measurement of hemispherical photographs to obtain sunlit
foliage area and gap frequency. Isr J Agric Res 22:53–61
Campbell GS, Norman JM (1989) The description and measurement of plant canopy structure. In: Russell G, Marchall B,
Jarvis PG (eds) Plant canopies: their growth, form and function. Cambridge University Press, Cambridge, pp 1–19
Chason JW, Baldocchi DD, Huston MA (1991) A comparison of
direct and indirect methods for estimating forest canopy leaf
area. Agric For Meteorol 57:107–128
Chazdon RL, Pearcy RW (1991) The importance of sunflecks for
forest understory plants. Bioscience 41:760–766
Cho D-S (1992) Disturbance regime and tree regeneration in
Kwangnung Natural Forest (in Korean). Korean J Ecol
15:395–410
Crockford RH, Richardson DP (2000) Partitioning of rainfall into
throughfall, stemfow and interception: effect of forest type,
ground cover and climate. Hydrol Process 14:2903–2920
Cutini A, Matteucci G, Mugnozza GS (1998) Estimation of leaf
area index with the Li-Cor LAI 2000 in deciduous forests. For
Ecol Manage 105:55–65
Ellsworth DS, Reich PB (1993) Canopy structure and vertical
patterns of photosynthesis and related leaf traits in a deciduous
forest. Oecologia 96:169–178
Ford ED, Newbould PJ (1971) The leaf canopy of a coppiced deciduous woodland: I. Development and structure. J Ecol
59:843–862
Hong J, Kim J, Lee D, Lim J-H (2008) Estimation of the storage
and advection effects on H2O and CO2 exchanges in a hilly
KoFlux forest catchment. Water Resour Res. doi:10.1029/
2007wr006408
830
Hosoi F, Omasa K (2006) Voxel-based 3-D modeling of individual
trees for estimating leaf area density using high-resolution
portable scanning lidar. IEEE Trans Geosci Remote Sens
44:3610–3618
Hosoi F, Omasa K (2009) Estimating vertical plant area density
profile and growth parameters of a wheat canopy at different
growth stages using three-dimensional portable lidar imaging.
ISPRS J Photogramm Remote Sens 64:151–158. doi:
10.1016/j.isprsjprs.2008.09.003
Hutchison BA, Matt DR, McMillen RT, Gross LJ, Tajchman SJ,
Norman JM (1986) the architecture of a deciduous forest canopy in Eastern Tennessee, USA. J Ecol 74:635–646
Ishii HT, Pelt RV, Parker GG, Nadkarni NM (2004) Age-related
development of canopy structure and its ecological functions.
In: Lowman M, Rinker HB (eds) Forest canopies. Elsevier
Academic Press, Massachusetts, pp 102–117
Jonckheere I, Fleck S, Nackaerts K, Muys B, Coppin P, Weiss M,
Baret F (2004) Review of methods for in situ leaf area index
determination. Agric For Meteorol 121:19–35. doi:
10.1016/j.agrformet.2003.08.027
Kang M, Park S, Kwon H, Choi HT, Choi YJ, Kim J (2009)
Evapotranspiration from a deciduous forest in a complex terrain and a heterogeneous farmland under monsoon climate.
Asia-Pacific J Atmos Sci 45:175–191
Kim J, Lee D, Hong J, Kang S, Kim S-J, Moon S-K, Lim J-H, Son
Y, Lee J, Kim S, Woo N, Kim K, Lee B, Lee B-L, Kim S (2006)
HydroKorea and CarboKorea: cross-scale studies of ecohydrology and biogeochemistry in a heterogeneous and complex
forest catchment of Korea. Ecol Res 21:881–889. doi:
10.1007/s11284-006-0055-3
Kira T, Shinozaki K, Hozumi K (1969) Structure of forest canopies
as related to their primary productivity. Plant Cell Physiol
10:129–142
Kobayashi H, Ryu Y, Baldocchi DD, Welles JM, Norman JM
(2013) On the correct estimation of gap fraction: how to remove
scattered radiation in gap fraction measurements? Agric For
Meteorol 174–175:170–183. doi:10.1016/j.agrformet.2013.02.013
Kwon H, Kim J, Hong J, Lim JH (2010) Influence of the Asian
monsoon on net ecosystem carbon exchange in two major
ecosystems in Korea. Biogeosciences 7:1493–1504. doi:
10.5194/bg-7-1493-2010
Li-Cor I (2009) LAI-2200 plant canopy analyzer instruction manual. Lincoln, NE, USA
Lim JH, Shin JH, Jin GZ, Chun JH, Oh JS (2003) Forest stand
structure, site characteristics and carbon budget of the
kwangneung natural forest in Korea. Korean J Agric For
Meteorol 5:101–109
Link TE, Unsworth M, Marks D (2004) The dynamics of rainfall
interception by a seasonal temperate rainforest. Agric For
Meteorol 124:171–191. doi:10.1016/j.agrformet.2004.01.010
Lovell JL, Jupp DLB, Culvenor DS, Coops NC (2003) Using airborne and ground-based ranging lidar to measure canopy
structure in Australian forests. Can J Rem Sens 29:607–622
Lowman M, Rinker HB (2004) Forest canopies. Elsevier Academic
Press, Massachusetts
MacArthur RH, Horn HS (1969) Foliage profile by vertical measurements. Ecology 50:802–804
Miller PC (1969) Tests of solar radiation models in three forest
canopies. Ecology 50:878–885
Monsi M, Saeki T (1953) Über den Lichtfaktor in den
Pflanzengesellschaften und seine Bedeutung für die Stoffproduktion. Jpn J Bot 14:22–52
Monsi M, Saeki T (2005) On the factor light in plant communities
and its importance for matter production, 1953. Ann Bot
95:549–567. doi:10.1093/aob/mci052
Muul I, Liat LB (1970) vertical zonation in a tropical rain forest in
Malaysia: method of study. Science 169:788–789
Neumann HH, Den Hartog G (1989) Leaf area measurements
based on hemispheric photographs and leaf-litter collection in a
deciduous forest during autumn leaf-fall. Agric For Meteorol
45:325–345
Norman JM, Campbell GS (1989) Canopy structure. In: Pearcy
RW, Ehleringer JR, Mooney HA, Rundel PW (eds) Plant
physiological ecology. Chapman & Hall, London, pp 301–325
Norman JM, Jarvis PG (1975) Photosynthesis in sitka spruce [Picea sitchensis (Bong.) Carr.]: V. Radiation penetration theoryand a test case. J Appl Ecol 12:839–878
Ogawa H, Yoda K, Kira T, Ogino K, Shidei T, Ratanawongse D,
Apasutaya C (1961) Comparative ecological studies on three
main types of forest vegetation in Thailand. I. Structure and
floristic composition. In: Kira T, Iwata K (eds) Nature and life
in Southeast Asia. Fauna and Flora Research Society, Kyoto,
pp 13–48
Parker GG (1995) Structure and microclimate of forest canopies.
In: Lowman M, Nadkarni N (eds) forest canopies. Academic
Press, San Diego, pp 73–106
Parker GG, Brown MJ (2000) Forest canopy stratification—is it
useful? Am Nat 155:473–484
Parker GG, O’Neill JP, Higman D (1989) Vertical profile and canopy organization in a mixed deciduous forest. Vegetatio
85:1–11
Parker GG, Smith AP, Hogan KP (1992) Access to the upper forest
canopy with a large tower crane. Bioscience 42:664–670
Pereira AR, Shaw RH (1980) A numerical experiment on the mean
wind structure inside canopies of vegetation. Agric Meteorol
22:303–318
Perry DR (1978) A method of access into the crowns of emergent
and canopy trees. Biotropica 10:155–157
Perry DR, Williams J (1981) The tropical rain forest canopy: a
method providing total access. Biotropica 13:283–285
Queck R, Bernhofer C (2010) Constructing wind profiles in forests
from limited measurements of wind and vegetation structure.
Agric For Meteorol 150:724–735. doi:10.1016/j.agrformet.
2010.01.012
Radtke PJ, Bolstad PV (2001) Laser point-quadrat sampling for
estimating foliage-height profiles in broad-leaved forests. Can J
For Res 31:410–418. doi:10.1139/cjfr-31-3-410
Ross J (1981) The radiation regime and architecture of plant
stands. Junk Publishers, The Hague
Ryu Y, Kang S, Moon S-K, Kim J (2008) Evaluation of land
surface radiation balance derived from moderate resolution
imaging spectroradiometer (MODIS) over complex terrain and
heterogeneous landscape on clear sky days. Agric For Meteorol
148:1538–1552. doi:10.1016/j.agrformet.2008.05.008
Ryu Y, Baldocchi DD, Verfaillie J, Ma S, Falk M, Ruiz-Mercado
I, Hehn T, Sonnentag O (2010a) Testing the performance of a
novel spectral reflectance sensor, built with light emitting diodes
(LEDs), to monitor ecosystem metabolism, structure and
function. Agric For Meteorol 150:1597–1606. doi:10.1016/
j.agrformet.2010.08.009
Ryu Y, Nilson T, Kobayashi H, Sonnentag O, Law BE, Baldocchi
DD (2010b) On the correct estimation of effective leaf area
index: does it reveal information on clumping effects? Agric For
Meteorol 150:463–472. doi:10.1016/j.agrformet.2010.01.009
Ryu Y, Sonnentag O, Nilson T, Vargas R, Kobayashi H, Wenk R,
Baldocchi DD (2010c) How to quantify tree leaf area index in
an open savanna ecosystem: a multi-instrument and multimodel approach. Agric For Meteorol 150:63–76. doi:
10.1016/j.agrformet.2009.08.007
Ryu Y, Lee G, Jeon S, Song Y, Kimm H (2014) Monitoring multilayer canopy spring phenology of temperate deciduous and
evergreen forests using low-cost spectral sensors. Remote Sens
Environ 149:227–238. doi:10.1016/j.rse.2014.04.015
Satoo T (1970) Primary production in a plantation of Japanese
Larch, Larix leptolepis: a summarized report of JPTF-66
KOIWAI. J Jpn For Soc 52:154–158
Shaw RH, Pereira AR (1982) Aerodynamic roughness of a plant
canopy: a numerical experiment. Agric Meteorol 26:51–65
Song Y, Maki M, Imanishi J, Morimoto Y (2011) Voxel-based
estimation of plant area density from airborne laser scanner data.
Int Arch Photogramm Remote Sens Spat Inf Sci XXXVIII-5/
W12:209–212. doi:10.5194/isprsarchives-XXXVIII-5-W12-209-2011
831
Song Y, Ryu Y, Jeon S (2014) Interannual variability of regional
evapotranspiration under precipitation extremes: a case study
of the Youngsan River basin in Korea. J Hydrol
519:3531–3540. doi:10.1016/j.jhydrol.2014.10.048
Sterck F, Pvd Meer, Bongers F (1992) herbivory in two rain forest
canopies in French Guyana. Biotropica 24:97–99
Tadaki Y (1966) Some discussion on the leaf biomass of forest
stands and trees. Bull Gov For Exp Stn Tokyo 184:135–162
Weiss M, Baret F, Smith GJ, Jonckheere I, Coppin P (2004) Review of methods for in situ leaf area index (LAI) determination.
Agric For Meteorol 121:37–53. doi:10.1016/j.agrformet.
2003.08.001
Welles JM, Norman JM (1991) instrument for indirect measurement of canopy architecture. Agron J 83:818–825
Wilson JW (1960) Inclined point quadrats. New Phytol 59:1–8
Wilson JW (1965) Point quadrat analysis of foliage distribution for
plants growing singly or in rows. Aust J Bot 13:405–409
Yamakura T, Hagihara A, Sukardjo S, Ogawa H (1986) tree size in
a mature dipterocarp forest stand in Sebulu, East Kalimantan,
Indonesia. Southeast Asian Stud 23:452–478
Zhang Y, Chen JM, Miller JR (2005) Determining digital hemispherical photograph exposure for leaf area index estimation.
Agric For Meteorol 133:166–181. doi:10.1016/j.agrformet.
2005.09.009