Spatial Distribution Pattern of the Populations of Camellia japonica in Busan

Journal of Life Science.
2014.
Aug,
24(8):
813-819

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

- Received : May 09, 2014
- Accepted : July 13, 2014
- Published : August 30, 2014

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The spatial distribution of geographical distances at five natural populations of
Camellia japonica
in Busan, Korea was studied. The four plots (Mollundae, Gadeok-do, Du-do, and Jwiseum) of
C. japonica
were uniformly distributed in the forest community and only one plot (Amnam-dong) was aggregately distributed in the forest community. Morisita index is related to the patchiness index showed that the plot 20m×50m had an overly steep slope when the area was larger than 20m×20m, which indicated that the degree of aggregation increased significantly with increasing quadrat sizes, while the patchiness indices did not change from the plot 5m×10m to 10m×10m. The spatial structure was quantified by Moran’s
I
, a coefficient of spatial autocorrelation. Ten of the significant values (76.9％) were positive, indicating similarity among individuals in the first 4 distance classes (80 m), i.e., pairs of individuals with dissimilarity characteristics can separate by more than 100 m.
Camellia japonica
in Busan.
In theory, genetic differentiation over short distances may occur either as a result of spatially variable selection or localized genetic drift, provided that gene flow is sufficiently restricted
[14]
. Indirect evidence for genetic correlations between neighboring plants has been obtained from data on mating systems
[5]
. Localized seed and pollen dispersals produce family clusters within these populations
[7]
. Several studies have revealed decreased seed set and seed survivorship from mating between genetically similar near-neighbors, which has been interpreted as inbreeding depression
[10]
.
In the wild,
C. japonica
is found in mainland China (Shandong, east Zhejiang), Taiwan, southern Korea and southern Japan.
C. japonica
is sometimes called the rose of winter, it belongs to the Theaceae family. An edible oil is obtained from the seeds of this species. The leaves are a tea substitute. The dried flowers used as a vegetable or mixed with gelatinous-rice to make a Japanese food called ‘mochi’.
Saha-gu and Gangseo-gu locate in south of the Korean, and at the western part of the North Pacific Ocean. A sample of a large (more than 300 individuals) natural population of wild species
C. japonica
collected at Saha-gu and Gangseogu in Korea was used in this study.
The purpose of this paper was to describe a statistical analysis for detecting a species association, which is valid even when the assumption of within- species spatial randomness is violated. The purpose of this study is to find if there a spatial structure within four populations of
C. japonica
and 2) if so, what is the spatial pattern and if it is the same for all populations?
Camellia japonica
at Saha-gu and Gangseo-gu in Busan-si (
Fig. 1
). This area is on the southern margin of Busan. It has a temperate climate with a little hot and long summer. In this region the mean annual temperature is 14.7℃ with the maximum temperature being 29.4℃ in August and the minimum −0.6℃ in January. Mean annual precipitation is about 1519.1 mm with most rain falling period between June and August.
The five studied populations of Camellia japonica in Busan, Korea . ANM: Amnam-dong, DUD: Du=do, JWI: Jwiseum, GAD: Gadeok-do
C. japonica
was analyzed according to the Neatest Neighbor Rule
[3
,
11]
with Microsoft Excel 2010.
Average viewing distance (
r_{A}
) was calculated as follows:
Where
r_{i}
is the distance from the individual to its nearest neighbor.
N
is the total number of individuals within the quadrat.
The expectation value of mean distance of individuals within a quadrat (
r_{B}
) was calculated as follows:
Where
D
is population density and
D
is the number of individuals per plot size.
R = r_{A} / r_{B}
When
R
>1, it is a uniform distribution,
R
=1, it is a random distribution,
R
<1, it is an aggregated distribution.
The significance index of the deviation of
R
that departs from the number of “1” is calculated from the following formula
[11]
.
When
C_{R}
>1.96, the level of the significance index of the deviation of R is 5％, and when
C_{R}
>2.58, the level is 1％.
We calculated the degree of population aggregation under different sizes of plots by dispersion indices: index of clumping or the index of dispersion (
C
), aggregation index (
CI
), mean crowding (
M
*), patchiness index (
PAI
), negative binominal distribution index K, Ca indicators (Ca is the name of one index)
[12
] and Morisita index (IM) were calculated with Microsoft Excel 2010. The formulae are as follows:
Index of dispersion: C = S ^{2}/m
Aggregation index
Mean crowding = m +CI =m +C −1−1
Patchiness index
Aggregation intensity
Ca indicators Ca = 1/k
IM =
Where
S
^{2}
is variance and
m
is mean density of
C. japonica.
When
C, M*, PAI
>1, it means aggregately distributed, when
C, M*, PAI
<1, it means uniformly distributed, when
CI, PA
, Ca >0, it means aggregately distributed, and when
CI, PA
, Ca <0 it means uniformly distributed.
We used the mean aggregation number to find the reason for the aggregation of
C. japonica
[1]
.
δ = mr /2k
Where r is the value of chi-square when the degree of freedom is 2k and k is the aggregation intensity.
I
, and a significant population structure was revealed beyond 20.0-m. Thus, the distance classes are 0-20.0 m (class I), 20.0-40.0 m (class II), 40.0-60.0 m (class III), 60.0-80.0 m (class IV), 80.0-100.0 m (class V), 100.0-120.0 m (class VI), 120.0-140.0 m (class VII), and 140.0-160.0 m (class VIII). The codes of classes are the same as in the distance classes and are listed
Table 1
.
R and C_{R} were shown in text.
The spatial structure was quantified by Moran's
I
, a coefficient of spatial autocorrelation (SA)
[15
,
16]
. As applied in this study, Moran's
I
quantifies the similarity of pairs of spatially adjacent individuals relative to the population sample as a whole. The value of
I
ranges between +1(completely positive autocorrelation, i.e., paired individuals have identical values) and −1(completely negative autocorrelation). Each plant was assigned a value depending on the presence or absence of a specific individual. If the
i
th plant was a homozygote for the individual of interest, the assigned pi value was 1, while if the individual was absent, the value 0 was assigned.
Pairs of sampled individuals were classified according to the Euclidian distance, dij, so that class k included dij satisfying k − 1 < dij < k + 1, where k ranges from 1 to 7. The interval for each distance class was 20 m. Moran's
I
statistic for class k was calculated as follows:
where Zi is
pi
− p (p is the average of
pi
); Wij is 1 if the distance between the
i
th and
j
th plants is classified into class k; otherwise, Wij is 0; n is the number of all samples and S is the sum of
in class k. Under the randomization hypothesis,
I
(k) has the expected value u1 = −1/(n − 1) for all k. Its variance, u2, has been given, for example, in Sokal and Oden (1978a). Thus, if an individual is randomly distributed for class k, the normalized
I
(k) for the standard normal deviation (SND) for the plant genotype, g(k) = {
I
(k) − u1}/u2
^{1/2}
, asymptotically has a standard normal distribution
[3]
. Hence, SND g(k) values exceeding 1.96, 2.58, and 3.27 are significant at the probability levels of 0.05, 0.01, and 0.001, respectively.
D
) varied from 0.097 to 0.190, with a mean of 0.130 (
Table 1
). The values of spatial distance (the rete of observed distance-to-expected distance) among the nearest individuals were higher than 1 but Amnam-dong was lower than 1. The four plots (Mollundae, Gadeok-do, Du-do, and Jwiseum) of
C. japonica
were uniformly distributed in the forest community and only one plot (Amnam-dong) was aggregately distributed in the forest community (
Table 1
).
C
) were higher than 1 except for three quadrats (5 m × 5 m, 5 m × 10 m, and 10 m × 10 m) of Amnam-dong (
Table 2
). As the sizes of quadrat were greater, the values of
C. japonica
were high. Thus aggregation indices were positive except for plots which indicate a clumped distribution. The values of
PI
and
Ca
were shown greater than zero. The values of
PAI
except three quadrats of Anman-dong were greater than 1 (
Table 2
). Thus, the most individuals of
C. japonica
were clustered and the distribution pattern of the
C. japonica
was quadrat-sampling dependent. When the sampling quadrat in Amnam-dong was smaller than 10 m × 10 m,
C
. japonica were aggregately distributed, and when the sampling quadrat was greater than 10 m x 10 m, the aggregation index showed the trend of being uniformly distributed for
C. japonica
. The mean crowding (
M
*) and aggregation intensity (
Ca
) indicator were higher with a big quadrat.
Aggregation indices were shown in text.
Morisita index (
IM
) related to the patchiness index (
PAI
) showed that the plot 20 m × 50 m had an overly steep slope when the area was larger than 20 m × 20 m, which indicated that the degree of aggregation increased significantly with increasing quadrat sizes, while the patchiness indices did not change from the plot 5 m × 10 m to 10 m × 10 m (
Fig. 2
).
The curves of patchiness in four populations of Camellia japonica using values of Green index.
The mean aggregation number analysis showed that the reasons for aggregation of
C. japonica
differed in quadrats with different plot sizes (
Table 3
). The cluster at 5 m × 5 m quadrat was determined by environmental factors. When the sizes were greater than 10 m × 10 m quadrat, the clusters were determined by both species characteristics and environmental factors.
* p <0.05, ** p <0.01, *** p <0.001.
The changes in the mean aggregation numbers for five populations.
I
is presented in
Table 3
. Separate counts for each type of joined individuals and for each distance class of separation were tested for significant deviation from random expectations by calculating the SND. Moran's
I
of
C. japonica
significantly differed from the expected value in only 13 of 35 cases (37.1％). Thirteen of these values (37.1％) were negative, indicating a partial dissimilarity among pairs of individuals in the seven distance classes. Ten of the significant values (76.9％) were positive, indicating similarity among individuals in the first four distance classes, i.e., pairs of individuals can separate by more than 100 m. Namely, significant aggregations were partially observed within IV classes. As a matter of course, the negative SND values at classes IV, V, and VI. Thus, dissimilarity among pairs of individuals could be found by more than 100 m.
The comparison of Moran’s
I
values to a logistic regression indicated that a highly significant percentage of individual dispersion in
C. cammelia
populations of the Saha-gu and Gangseo-gu could be explained by isolation by distance.
C. japonica
included primarily their life history, artificial disturbance, and population density. Life history theory seeks to understand the variation in traits such as growth rate, number and size of offsprings and life span observed in nature, and to explain them as evolutionary adaptations to environmental conditions
[17]
. The cluster was determined by environmental factors when the sampling quadrat was smaller than 10 m × 10 m (<2). Artificial disturbance such as constitutional roads is an important environmental factor affecting
C. japonica
in Amnam-dong. At the plots which had fewer
C. japonica
, the cluster was mainly determined by
C. japonica
themselves; the mean value of the aggregation index changed irregularly with the variation in plot sizes.
A significant positive value of Moran's
I
indicated that pairs of individuals separated by distances that fell within distance class IV had similar individuals, whereas a significant negative value indicated that they had dissimilar individuals. The overall significance of individual correlograms was tested using Bonferroni's criteria. The results revealed that patchiness similarity was shared among individuals within up to a scale of an 80 m distance. Thus it was looked for the presence of dispersion correlations between neighbors at this scale.
The results from this study are consistent with the supposition that a plant population is subdivided into local demes, or neighborhoods of related individuals
[4
,
7]
. Previous reports on the local distribution of genetic variability suggested that microenvironmental selection and limited gene flow are the main factors causing substructuring of alleles within a population
[5]
.
The community of
C. japonica
at Gadeok-do is the Busan Natural Monument No. 38. There are some communities of the Korean Natural Monuments of
C. japonica
: No. 66 (Daecheon-do, Ungjin-gun, Gyeonggi-do). No. 161 (Baekryeonsa, Gangjin-gun, Jeon-nam), No. 169 (Marhang-ri, Seocheon-gun, Chung-nam), No. 184 (Seonsa, Gochang-gun, Jeon-buk), No. 489 (Okrhongsa, Gwangyang-ci, Jeon-nam).
C. japonica
is one of very important resource of East Asia. The camellia in Europe was brought details of over 30 varieties back from Asia. Camellias were introduced into Europe during the 18th century and had already been cultivated in the Orient for thousands of years.
In conclusion,
C. japonica
populations within the Saha-gu and Gangseo-gu were observed a strong spatial structure. Neighboring patches of
C. japonica
were predominantly 80 to 100 m apart on average. The present study demonstrates that a spatial structure of
C. japonica
in the Saha-gu and Gangseo-gu populations could be explained by isolation by distance, limited gene flow, and topography. The results of this study were used as systematic conservation planning which is an effective way to seek and identify efficient and effective types of reserve design to capture or sustain the highest priority biodiversity values and to work with communities in support of local ecosystems.

Introduction

In recent decades, there was much increase in the statistical tools used in spatial ecology
[13]
. Botanists, ecologists, geographers and plant evolutionary biologists have long recognized that plants are not distributed at random within communities but are rather clustered in distinct patches
[8
,
20]
. Environmental heterogeneity is usually cited as playing a critical role in determining the spatial structure, but colonization patterns and stochastic events affecting establishment and mortality are also important
[18]
. More recently, plant evolutionary biologists have demonstrated that genetic variations in plant populations are also nonrandomly distributed
[6]
. This nonrandom distribution of genetic variation is often referred to as the genetic structure of a population
[9]
. The genetic structure is an integral part of the process of population genetics
[5]
. Population structure interacts with a number of factors: microenvironmental heterogeneity, mortality due to stochastic events
[19]
, and mating systems that feature limited dispersal of seed or pollen
[5]
.
Of the several methods of describing the spatial distribution of plant community the simplest way is percentage distribution of individuals over the geographical areas. Another methodology usually adopted is to list the geographical areas of a given class into rank order which enables comparison of ranking from individual to individual. In this report, the several statistical tools of percentage distribution and population structure of the geographical areas are used to study the spatial distribution of
Materials and Methods

- Study area

We conducted the spatial analysis in the communities of
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- Sampling procedure

We established nine plots with an area of 20 m × 160 m each around four populations at Saha-gu and one population at Gangseo-gu in Busan, 2014. We randomly located quadrates in each plot which we established populations. The quadrat sizes were 5 m × 5 m, 5 m × 10 m, 10 m × 10 m, 10 m × 20 m, 20 m × 20 m, and 20 m × 50 m. We mapped all plants to estimate population density.
- Index calculation and data analysis

The spatial pattern of
- Spatial structure

Numerical simulations of previous analyses were performed to investigate the significant differences at various distance scales, i.e., 10.0, 20.0 m, and so on. However, no significant population structure was found within the 20.0 m distance classes by means of Moran's
Spatial patterns ofCamelliajaponica individuals at five populations in Busan

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Results

- The spatial pattern of individuals

Population densities (
- The degree of population aggregation

Dispersion index (
Changes in gathering strength ofCamellia japonicaat different sampling quadrat sizes

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Spatial autocorrelation coefficients (Moran'sI) among five populations ofCamellia japonicafor seven distance classes

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- Analysis of spatial autocorrelation

The spatial autocoefficient, Moran's
Discussion

When the value of δ is less than 2, the aggregation is mainly caused by the environmental factors
[11]
. When δ is higher than 2, the aggregation is mainly caused by both species characteristics and environmental factors
[11]
. We recognized that the important environmental factors might be considered competition, growth rate, little decomposition, light, and below-ground resources. The characteristics of the
Acknowledgements

This work was supported by Dong-eui University Grant (2014AA474).

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Citing 'Spatial Distribution Pattern of the Populations of Camellia japonica in Busan
'

@article{ SMGHBM_2014_v24n8_813}
,title={Spatial Distribution Pattern of the Populations of Camellia japonica in Busan}
,volume={8}
, url={http://dx.doi.org/10.5352/JLS.2014.24.8.813}, DOI={10.5352/JLS.2014.24.8.813}
, number= {8}
, journal={Journal of Life Science}
, publisher={Korean Society of Life Science}
, author={강, 만기
and
허, 만규}
, year={2014}
, month={Aug}