Ehime University Institutional Repository

Ehime University (愛媛大学)博士（理学）doctoral thesi

神田, 宗欣

KANDA, Kazuki

 
 
（第３号様式）(Form No. 3) 
学 位 論 文 要 旨 
Dissertation Summary 
氏    名 (Name) 神田 宗欣 
論 文 名： Effects of exposure to tris (2-chloroethyl) phosphate (TCEP) on ex ovo chicken 
embryos 
(Dissertation Title) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Tris (2-chloroethyl) phosphate (TCEP) is one of the pervasive organophosphorus flame 
retardants (OPFRs) that has been commercially used in polyurethane foam, textiles, and furniture to 
delay the spread of fire after ignition. TCEP has been detected in the atmosphere, dust, river water, 
and tissues and eggs of wild birds. However, there are few studies regarding the toxic effects of 
TCEP on avian embryos. In in ovo exposure test of avian embryogenesis, in situ observation has 
been difficult because avian embryos develop within non-transparent eggshells. A novel shell-less 
incubation system for chicken embryos that enables visualization in situ of the development of 
chicken embryos was developed in 2014. This study thus aimed to investigate the phenotypes and 
transcriptome effects of TCEP exposure in ex ovo chicken. 
Fertilized chicken (Gallus gallus domesticus) eggs were treated with 50, 250, and 500 nmol/g 
egg of TCEP (TCEP-L, -M, -H, respectively) or DMSO (vehicle control) at the beginning of 
incubation.  
Survival rates started to be greatly reduced from day 3 of incubation and were significantly 
decreased until day 9 in TCEP-M and TCEP-H groups. Morphological biometrics, the heart rate, and 
total extraembryonic blood vessel length were significantly decreased from days 3 to 9 in TCEP-
exposed groups. These results suggested that TCEP exposure induced developmental delay and 
cardiovascular dysfunction in chicken embryos. In transcriptome analysis, the cardiac development 
transcription factor NKX2-5 and the cardiac conduction-related gene CACNA1G were 
downregulated in the day five heart. Gene expression of MYLs, a cardiac contraction-related gene, 
and RYR2, a calcium transport-related gene, was decreased in the day nine heart. It was suggested 
that the downregulation of these genes induced a decrease in heart rate. In vitelline membranes with 
reduced vessel length, genes associated with VEGF signaling were downregulated, which may 
 
 
trigger vasculogenesis and angiogenesis inhibition. SNAI2, a transcription factor for epithelial-
mesenchymal transition, and TBXT, a mesoderm marker gene, were downregulated during the 
gastrulation of chicken embryos by TCEP exposure. Therefore, it was suggested that TCEP inhibits 
mesoderm differentiation and causes cardiovascular failure in chicken embryos. 
 
 
 
F
ig
. 
P
ro
p
o
se
d
 c
h
ro
n
o
lo
g
ic
al
 a
d
v
er
se
 o
u
tc
o
m
e 
p
at
h
w
ay
s 
(A
O
P
s)
 f
o
r 
th
e 
to
x
ic
it
y
 o
f 
T
C
E
P
 i
n
 1
8
 h
, 
d
ay
 5
, 
an
d
 d
ay
 9
 c
h
ic
k
en
 e
m
b
ry
o
s.
 
V
a
s
c
u
lo
g
e
n
e
s
is
A
n
g
io
g
e
n
e
s
is
M
o
le
c
u
la
r
le
v
e
l
C
e
ll
u
la
r 
le
v
e
l
O
rg
a
n
 l
e
v
e
l
B
lo
o
d
 v
e
s
s
e
l 
le
n
g
th
K
e
y
 e
v
e
n
ts
A
d
v
e
rs
e
 o
u
tc
o
m
e
P
IK
3
C
A
F
G
F
2
V
E
G
F
R
2
V
E
G
F
R
3
V
E
G
F
C
A
K
T
1
R
A
C
1
H
IF
1
A
M
o
le
c
u
la
r
le
v
e
l
C
e
ll
u
la
r 
le
v
e
l
O
rg
a
n
 l
e
v
e
l
K
e
y
 e
v
e
n
ts
A
d
v
e
rs
e
 o
u
tc
o
m
e
s
M
Y
L
2
M
Y
L
3
M
Y
L
4
M
u
s
c
le
 f
ila
m
e
n
t
M
y
o
c
a
rd
ia
l 
c
o
n
tr
a
c
ti
o
n
C
a
2
+
tr
a
n
s
p
o
rt
H
e
a
rt
 f
a
ilu
re
C
a
rd
ia
c
a
rr
e
s
t
C
a
rd
ia
c
 h
y
p
e
rt
ro
p
h
y
R
Y
R
2
N
F
K
B
1
S
P
1
S
P
3
S
M
A
D
4
G
L
I1
C
T
N
N
B
1
A
K
T
1
C
a
rd
ia
c
 c
o
n
d
u
c
ti
o
n
M
o
le
c
u
la
r
le
v
e
l
C
e
ll
u
la
r 
le
v
e
l
O
rg
a
n
 l
e
v
e
l
F
Z
D
6
R
A
C
1
N
K
X
2
-5
C
A
C
N
A
1
G
B
IN
1
M
ic
ro
tu
b
u
le
 
d
e
p
o
ly
m
e
ri
z
a
ti
o
n
A
c
ti
n
 c
y
to
s
k
e
le
to
n
 
re
g
u
la
ti
o
n
H
e
a
t 
ra
te
A
b
n
o
rm
a
l 
c
a
rd
ia
c
 
m
o
rp
h
o
g
e
n
e
s
is
K
e
y
 e
v
e
n
ts
A
d
v
e
rs
e
 o
u
tc
o
m
e
s
W
n
t2
B
W
n
t1
0
A
K
C
N
E
5
K
C
N
J
2
IN
S
F
G
F
2
0
P
IK
3
C
A
P
IK
3
R
3
IT
G
B
5
IT
G
A
7
W
A
S
F
N
C
K
A
P
T
B
X
6
W
N
T
3
A
M
e
s
o
d
e
rm
 
d
if
fe
re
n
ti
a
ti
o
n
M
o
le
c
u
la
r
le
v
e
l
C
e
ll
u
la
r 
le
v
e
l
F
G
F
4
S
N
A
I2
T
B
X
T
E
p
it
h
e
lia
l-
m
e
s
e
n
c
h
y
m
a
l 
tr
a
n
s
it
io
n
 (
E
M
T
)
K
e
y
 e
v
e
n
ts
E
-c
a
d
h
e
ri
n
N
-c
a
d
h
e
ri
n
O
rg
a
n
 l
e
v
e
l
C
a
rd
ia
c
 d
e
v
e
lo
p
m
e
n
t
V
a
s
c
u
lo
g
e
n
e
s
is
A
d
v
e
rs
e
 o
u
tc
o
m
e
s
E
m
b
ry
o
g
e
n
e
s
is
1
8
 h
(H
H
4
)
D
a
y
 5
(H
H
2
7
)
D
a
y
 9
(H
H
3
5
)
B
la
s
to
d
e
rm
H
e
a
rt
H
e
a
rt
V
it
e
lli
n
e
 m
e
m
b
ra
n
e


English

Ex ovo　ニワトリ胚に対するリン酸トリス（2-クロロエチル）（TCEP）曝露の影響

Ehime University (愛媛大学)博士(農学)thesi

宮澤, 譲治

1487

MIYAZAWA, Jozi

Development of temporal and spatial sowing methods for increasing soil moisture and yield of upland rice under rainfed conditions in Benin, West Africa

Ehime University (愛媛大学)博士(医学)doctoral thesi

久門, 啓志

KUMON, Hiroshi

（第３号様式） 
 
 
学 位 論 文 要 旨 
 
 
 
            氏   名 久門 啓志 
 
 
 
            論 文 名 AGXT2遺伝子の機能性多型である rs37369が糖尿病のリスク因
子となる 
 
 
 
学位論文要旨 
 
この実験は愛媛大学医学部附属病院臨床研究倫理審査委員会で承認されている。 
（2015 年 4 月 27 日、承認番号 1504012） 
 
 一酸化窒素は内皮細胞のアポトーシスを抑制し、増殖と遊走を促進する。非対称型
NG,NG-ジメチル-L-アルギニン(ADMA)は一酸化窒素合成酵素を阻害する内因性阻害物質
であり、これにより ADMAは血管内皮細胞の増殖と血管新生を阻害することが知られてい
る。ADMA は様々な疾患において心血管イベント及び死亡の予測因子としても注目されて
おり、2型糖尿病の患者だけでなく糖尿病予備軍の患者でも、健常者と比較して血中 ADMA
濃度が有意に高いことが示されている。 
 アラニン-グリオキシル酸アミノトランスフェラーゼ 2（AGXT2）は ADMAなどのメチル
アルギニンの代謝を制御する重要な酵素であり、AGXT2 遺伝子の一塩基多型(SNP)は冠動
脈疾患や動脈硬化、慢性心不全、血糖値、血圧などとの関連が示されている。また AGXT2
の SNP の一つである rs37369 は AGXT2 の機能低下と関連することが報告されている。さ
らに AGXT2 遺伝子の機能欠損はヨーロッパの人では 10%程度であるのに対して、日本人
では 30～40%と高い割合であることも報告されている。 
 そのため本研究では愛大コホート研究のデータベースを用いて AGXT2 遺伝子の SNP と
糖尿病のリスクの関連を調べることを目的とした。 
 2015年から開始された前向きコホート研究(愛大コホート研究)の参加者 2,390人を対
象に、症例群 190 人、非症例群 2,290 人として症例対象研究を行った。本研究では空腹
時血糖＞126 mg/dL、HbA1C＞6.5%、糖尿病の既往歴のいずれかを満たすものを症例群と
して割り付けた。対象者の末梢血から DNAを抽出し、AGXT2遺伝子の SNPである rs37370、 
氏名   久門 啓志   
 
rs37369、rs180749、rs16899974 の遺伝子型を特定し、Stata/SE ソフトウェアを用いて
アレル頻度やハプロタイプの推定を行った。 
 非症例群と比較して症例群では BMI が高く、高血圧や脂質異常症の割合が多かった。
また非症例群において、AGXT2遺伝子の SNPである rs16899974はハーディワインベルグ
平衡から外れており、本研究の解析対象から除外した。解析の結果、AGXT2遺伝子の SNP 
rs37369 では、CC 遺伝子型は TT 遺伝子型と比較して、オッズ比 1.83 倍で有意に糖尿病
のリスクが高いことが分かった(95%信頼区間, 1.04～3.47)。また rs37370 および
rs180749では、糖尿病リスクと有意な関連は認めなかった。さらに rs37370、rs37369、
rs180749の CTAハプロタイプでは、糖尿病リスクと正の相関(粗オッズ比, 1.25; 95%信
頼区間、1.01～1.56)を認め、CCAハプロタイプでは逆相関(粗オッズ比, 0.53; 95%信頼
区間、0.27～0.956)を認めた。これまでの研究から AGXT2遺伝子の SNP rs37369の Tア
レルは、AGXT2の機能低下に関連し、また冠動脈疾患と有意な正の相関も報告されており
本研究の結果と部分的に一致すると考えられる。一方で AGXT2遺伝子の SNP rs37369の
CC遺伝子型が慢性心不全のリスク増加と関連しているという報告もある。また AGXT2遺
伝子のプロモーター領域に結合し、AGXT2 遺伝子の発現を制御する転写因子として
Hepatocyte nuclear factor 4α (HNF4α)が知られており、これは若年発症柄糖尿病の
原因遺伝子として考えられていることから、AGXT2 遺伝子と糖尿病との関連については
さらなる研究が必要と考えらえる。本研究は，AGXT2遺伝子の SNP rs37369や CTAハプロ
タイプ、CCAハプロタイプと糖尿病の間に有意な関連を示した初めての研究である。 
 
 
 
キーワード（３～５） 
 
 
 
AGXT2 
糖尿病 
一塩基多型 
 
 
 


AGXT2遺伝子の機能性多型であるrs37369が糖尿病のリスク因子となる

入江, 賀子

IRIE, Noriko

竹島, 久美子

TAKESHIMA, Kumiko

川原, 尚子

KAWAHARA, Naoko

－ 13 －
『愛媛大学社会共創学部紀要』第７巻第２号　2023年　p.13-19
Abstract
     Information on forest growth is important for the sustainable use of forests and maximising their value, 
such as by increasing carbon fixation. This study aims to tentatively estimate a growth model for forests 
using data on Japanese cedar forests in Ehime Prefecture by reviewing previous studies on how to estimate 
and use a growth model for forests.
要旨
　森林の持続的な活用や炭素固定量を増やすなど、森林の価値を最大限発揮させるような利用のために重要とな
るのは、森林の成長量に関する情報である。本研究では、愛媛県のスギの林分データから、林分の成長モデルを
いかに推定するのか、当該モデルをいかに利用するのかについて先行研究をレビューしつつ、林分の成長モデル
を仮推定することを目的とする。
論　説
Growth model of forests as a basis for climate change mitigation and 
nature-based solutions: Tentative estimation of a Japanese cider forest’s 
growth model in Ehime
Noriko IRIE（Environmental Design）
Kumiko TAKESHIMA（Regional Resource Management）
Naoko KAWAHARA（Kindai University）
入　江　賀　子（環境デザイン学科）
竹　島　久美子（地域資源マネジメント学科）
川　原　尚　子（近畿大学経営学部）
Keywords: forest, Ehime ciders, sustainable usage, growth model, parameter estimation
キーワード：森林、愛媛のスギ、持続的利用、成長モデル、パラメータ推定
【原稿受付︰2023 年 7 月 25 日　受理・採録決定︰2023 年 8 月 4 日】
1.	 Importance	 of	 estimating	 forest	 growth	
models
     In recent years, forest management plans have 
been developed to increase the overall value of 
forests. This value is not limited to only the wood 
supply for housing and wood products but also 
includes the use of forest biomass as an energy 
source and a sink for carbon dioxide (CO2) to aid in 
decarbonisation. Moreover, the importance of forest 
ecosystem conservation measures as ‘nature-based 
solutions’ (IUCN, 2023) to so-called environmental 
and social challenges such as disaster resilience 
is also emphasised. For the sustainable and 
environmentally sound use of forests, it is necessary 
to know the exact rate of forest growth in terms age. 
This is because, for example, differences in thinning 
timing, thinning location, and thinning intensity 
may result in different growth rates, which are 
related to carbon fixation, degree of ecosystem 
conservation, and other factors. Therefore, a 
model that can predict forest growth is required to 
optimise forest use.
－ 14 －
『愛媛大学社会共創学部紀要』第７巻第２号　2023
     However, in numerous cases, the forest growth 
models have not yet been updated. This study aims 
to tentatively estimate a growth model for the forest 
based on Japanese cedar forest data in the Ehime 
Prefecture, referring to Yoshimoto et al. (2012), 
while reviewing the literature on how to update the 
growth model and use it for forest management.
2.	 Forest	growth	data	and	existing	models
     Data on forest growth have traditionally included forest 
registers, forest yield tables, and stand density management 
diagrams, which were prepared for each prefecture and 
other entities. A stand density management diagram is a 
model used to describe forest growth (Ando, 1966). This 
model is based on height (tree height), average volume 
(volume), and the decreasing curve of the number of trees 
that die because of natural decay over time (Ando, 1966; 
Yoshimoto et al., 2012).
     This study estimates a forest growth model by adding 
the concept of time to the model (Yoshimoto et al., 2012). 
This study uses data from Toyota’s (2013) real forest yield 
table for Japanese cedar previously measured and estimated 
in Ehime Prefecture forests (Table 1) and parameters from 
the stand density management diagram at Shikoku (Table 2). 
Because the parameters of the stand density management 
diagram were studied from 1978 to 1988, this study updated 
the information on these parameters.
     The structure of the stand density management diagram 
is as follows (Yoshimoto et al., 2012). The coefficients are 
determined based on region and tree species; p1–p12 are the 
parameters. Given the number of timber trees per hectare 
(number of standing trees) N and the height H, the average 
volume per tree v (N, H ) is given by Equation (1.1):
     By multiplying (1.1) by N, the number of standing trees 
yields Equation (1.2) for the lumber volume per hectare.
     The number of standing trees and the height of the trees 
are used to calculate the value in Equation (1.3), which is 
the forest-shaped height.
     Assuming a cylinder with this forest-shaped height as 
its height and considering the lumber volume per hectare 
as the volume of the cylinder, the cross- sectional area per 
hectare can be calculated using Equation (1.4).
    Furthermore, using Equation (1.4) and N, the average 
diameter of the cross-sectional area per tree can be obtained 
as in Equation (1.5).
     The average diameter of the cross-sectional area is then 
adjusted by N and H to obtain the average breast height 
diameter per tree as in Equation (1.6).
     Although not estimated in the present study, the 
relationship between N and the number of trees N  0 at the 
time of planting is calculated using the natural mortality 
line as in Equation (1.7).
3.	 Methodologies
     The estimation methodology in this study followed that of 
Yoshimoto et al. (2012). The estimation flow is as follows: 
first, a height growth model was estimated; then, based on 
the estimated height and number of trees, the estimated 
values using the stand density management diagram were 
compared with the values in the forest yield table, and the 
parameters of the height growth model and stand density 
management diagram were re-estimated to best fit the 
measured data. The tree height growth model was estimated 
using the Chapman–Richards Equation (1.8) as a trial. All 
the parameters were exponentially transformed such that 
they were expected to be positive.
     First, the parameters (α, β, γ) of the height growth curve 
－ 15 －
Growth model of forests as a basis for climate change mitigation and nature-based solutions
in Equation (1.8) were estimated by minimising the sum 
of residual squares. Using the estimated parameters and 
the parameters of the stand density management diagram 
as initial values, a tentative parameter  that minimises the 
sum of residual squares as shown in (1.9) was obtained. 
From this, the covariance matrix of the residuals was 
estimated using (1.10), and the generalised least square 
estimator (GLSE)   that minimises the weighted residual 
sum of squares was estimated as shown in (1.11).
4.	 Estimation	results	and	discussion
     Figure 1 shows graphs of the fitted and original data 
(in the forest yield table) of the estimated growth model. 
The thin circles represent the original data, and the dotted 
lines represent the estimated values. The latter reflects the 
original data very well.
     This study tentatively estimated the parameters of the 
growth model and the stand density management diagrams 
of the ‘Shikoku National Forest Cedar’ created in the years 
1978–1988, based on the data of the forest yield table of 
ciders with the site as type ‘1/5’ in Ehime Prefecture by 
Toyota (2013). The parameters can be estimated with the 
data of ciders with the site as type ‘2/5’ to ‘5/5’ in the same 
way. Although the tentatively estimated parameter values 
must be confirmed in the future, this method enabled us to 
re-estimate the parameters of the growth model and stand 
density management diagrams.
     The real forest yield table in Toyota (2013) was created 
based on 334 stand structures of Japanese cedar forests 
in Ehime Prefecture, rejecting outliers. Because the data 
in question are for Ehime Prefecture as a whole, if data 
in specific municipalities are collected in the same way 
and parameters are estimated, the tailor-made parameters 
in those specific areas can be estimated. For example, it 
is possible to use Bayesian statistics to re-estimate the 
posterior distribution of parameters by adding new data, 
using currently estimated parameters as prior information 
(Yoshimoto et al., 2012).
     Such growth model updates could lead to uses that 
increase the overall forest value. For example, by updating 
the growth model for a given forest area in a given region, 
the amount of carbon that can be fixed from the forests in 
that area can be estimated more accurately. If the growth 
models of different forest areas can be compared, it will 
be possible to explore the factors that influence the growth 
of forest areas, such as thinning practices and other socio-
environmental factors, which will be useful in formulating 
future management policies. Furthermore, dynamic 
planning models can be created based on growth models 
(Yoshimoto, 2003).
     Although this study examined a useful model for forest 
unit management, future studies should examine optimal 
management methods for forest parcels or multiple forest 
units with additional constraints, such as conservation sites 
(Konoshima and Yoshimoto, 2013). Forest management 
for nature-based solutions is also an interesting topic. For 
example, it would be meaningful to study the optimisation 
of forest conditions (number of trees, height, breast 
height, diameter, etc.) as well as forest-level optimisation 
by considering spatial information such as adjacency 
and slope for disaster management (Yohimoto, personal 
communication, 1 July 2023).
Acknowledgement
     The authors would like to express their great 
appreciation to Professor Atsushi Yoshimoto, The 
Institute of Statistical Mathematics, for his valuable 
and constructive suggestions during the planning 
and development of this research. His willingness to 
generously give his time is greatly appreciated.
References
Ando, T. (1966) Forest Density Management Diagram), Tokyo, 
Japan: Norin syuppan. (In Japanese)
Forest Research and Management Organization (2023) Yield 
Ratio Number Ry Calculation Program (shuryo hisu Ry 
keisan puroguramu), https://www.ffpri.affrc.go.jp/database/
yieldindex/ index.html (accessed on 2 July 2023). (In 
Japanese)
International Union for Conservation of Nature and Natural 
Resources (IUCN) (2023) Nature-based Solutions, https://
－ 16 －
『愛媛大学社会共創学部紀要』第７巻第２号　2023
www.iucn.org/our-work/nature-based-solutions (accessed 
on 2 July 2023).
Konoshima, M., Yoshimoto, A. (2013) Optimization model for 
forest resource management and its application - harvest 
scheduling problems, Proceedings of the Institute of 
Statistical Mathematics, 61 (1), 97-109. (In Japanese)
Toyota, N. (2013) On the preparation of forest yield tables for 
plantation and real forests of Japanese cedar and Japanese 
cypress in Ehime prefecture (Ehime-ken sugi・hinoki 
jinkorin genjitsu rimbunshukakuhyo no sakusei ni tsuite), 
Research Report of the Forestry Research Center, Ehime 
Prefectural Institute of Agriculture, Forestry and Fisheries 
(Ehime-ken norin-suisan-kenkyujo ringyo-kenkyu-senta 
kenkyu hokoku, 30, 17-34. (In Japanese)
Yohimoto, A. (2003) A dynamic programming model for forest 
stand management using MSPATH algorithm, Proceedings 
of the Institute of Statistical Mathematics, 51 (1), 73-94. (In 
Japanese)
Yoshimoto, A., Kamo, K., Yanagihara, H. (2012) Statistical 
analysis of environmental data by R (R ni yoru kankyo data 
no tokei bunseki～Shinrin bunya de no oyo～ ), Tokyo, 
Japan: Asakura syoten. (In Japanese)
－ 17 －
Growth model of forests as a basis for climate change mitigation and nature-based solutions
Tables and Figures 
 
Table 1. Real forest yield: Japanese cedar site as type ‘1/5’  
Adjustment in October 2009 
          
Site 
index 
forest 
age 
Height of 
upper tier 
trees 
Average 
tree 
height 
Average 
diameter 
Number 
of trees 
Total 
cross-
sectional 
area  
Total 
trunk 
volume 
 
Current 
annual 
increment 
Average 
increment 
24.60 5 12.1 10.2 12.1 2,863 34.27 215.6  43.1 
24.60 10 14.3 12.5 15.5 1,946 38.09 267.0 10.3 26.7 
24.60 15 16.3 14.5 18.8 1,437 41.39 315.8 9.8 21.1 
24.60 20 18.2 16.5 21.9 1,124 44.27 361.9 9.2 18.1 
24.60 25 20.0 18.3 25.0 916 46.82 405.3 8.7 16.2 
24.60 30 21.6 19.9 27.9 770 49.10 446.2 8.2 14.9 
24.60 35 23.2 21.5 30.7 663 51.14 484.7 7.7 13.8 
24.60 40 24.6 23.0 33.3 582 52.99 520.8 7.2 13.0 
24.60 45 25.9 24.3 35.9 520 54.67 554.7 6.8 12.3 
24.60 50 27.2 25.6 38.2 470 56.20 586.5 6.4 11.7 
24.60 55 28.4 26.8 40.5 430 57.59 616.3 6.0 11.2 
24.60 60 29.5 27.9 42.6 397 58.87 644.2 5.6 10.7 
24.60 65 30.5 29.0 44.6 369 60.04 670.4 5.2 10.3 
24.60 70 31.4 29.9 46.5 346 61.11 694.9 4.9 9.9 
24.60 75 32.3 30.8 48.2 326 62.10 717.8 4.6 9.6 
24.60 80 33.1 31.7 49.9 309 63.01 739.2 4.3 9.2 
24.60 85 33.9 32.5 51.4 295 63.85 759.3 4.0 8.9 
24.60 90 34.6 33.2 52.9 282 64.62 778.0 3.8 8.6 
24.60 95 35.3 33.9 54.3 271 65.34 795.6 3.5 8.4 
24.60 100 35.9 34.5 55.6 261 66.00 812.0 3.3 8.1 
          
Reference Toyota (2013:31). Appendix 9. Yield table for a real forest area (Japanese cedar 1). 
  
－ 18 －
『愛媛大学社会共創学部紀要』第７巻第２号　2023
 
Table 2. Parameters of the stand density management diagram of ciders in national forests in Shikoku.       
Formula Parameter 
Parameter 
Value 
Formula Parameter 
Parameter 
Value 
Trunk lumber 
volume per tree 
1 0.0805 Average diameter 
of chest height 
8 0.2529 
2 1.4295 9 0.0000 
Formula (1.1) 3 5644.2 Formula (1.6) 10 0.9813 
 4 2.9858    
Shape height of a 
forest division 
5 2.1726    
6 0.1453    
Formula (1.3) 7 0.3004    
      
      
Forest Research and Management Organization (2023); Yoshimoto et al. (2012). 
Note: Parameter values of the national cider forests in Shikoku from the Forest Research and Management 
Organization (2023) were used.  
 
 
 
Age (year) 
 
Average height (m) 
－ 19 －
Growth model of forests as a basis for climate change mitigation and nature-based solutions
 
 
Figure 1. Graphs of fitted and original data (tree height, diameter at breast height, and lumber volume). 
Circles indicate original data and dotted lines indicate estimated values. 
Age (year) 
 
Age (year) 
 
Average breast height diameter (cm)
Average lumber volume (m3)


Growth model of forests as a basis for climate change mitigation and nature-based solutions:Tentative estimation of a Japanese cider forest’s growth model in Ehime

石川, 慶一郎

ISHIKAWA, Keiichiro

Japanese

バブル経済崩壊後の東京都中央区における居住者特性の空間パターン変化－国勢調査・調査票情報により作成した調査区別集計の地図化－

佐藤, 大規

SATO, Taiki

福山城伏見櫓に関する考察

田中, 尚子

TANAKA, Naoko

北条泰時と『御成敗式目』: 『式目』注にみるその評価の変化

神野, 遥奈

JINNO, Haruna

徳田秋聲「軀」における軍隊と社会的階層の連鎖

諸田, 龍美

MOROTA, Tasumi

「山の詩人」白居易（3） :「奏状」・京兆府戸曹参軍・藍田山悟真寺・太子左賛善大夫

渡邉, 敬逸

日本における「隠れ過疎地域」の特定に関する探索的研究

Not a member yet