iLEAPS-Japan 研究集会 2021
⼤気−陸⾯プロセスの研究の進展：観測とモデルによる統合的理解

要旨集*

開催⽇ ：2021 年 12 ⽉ 9 ⽇(⽊)・10 ⽇(⾦)
場所

：名古屋⼤学研究所共同館Ⅱ・409 室 （地球⽔循環共⽤室）
および、オンライン会場

主催：名古屋⼤学宇宙地球環境研究所・⽇本学術会議 iLEAPS ⼩委員会※

(兼)名古屋⼤学宇宙地球環境研究所
令和 2 年度共同利⽤・共同研究（研究集会）
報告書

開催趣旨

iLEAPS（Integrated Land Ecosystem‒ Atmosphere Process Study：統合
陸域⽣態系―⼤気プロセス研究計画）は、⼤気−陸域境界で⽣じる物理的・化学的・⽣物学的な諸過程についての理解の促進を⽬的とした国際研究計画です。iLEAPS は、持続可能な⼈間社会の構築を⽬的とした国際的な研究プラットフォームである Future Earth の、GRPs (Global Research
Projects) の⼀つとして位置づけられています。我が国においては、⽇本学
術会議 環境学委員会・地球惑星科学委員会合同 FE・WCRP 合同分科会の下部組織として iLEAPS ⼩委員会が設けられています。⼤気−陸域プロセスに関わる研究としては、これまで野外観測、広域モニタリングデータ解
析、数値モデル開発が⾏われ、個葉の環境応答からグローバルな変動まで様々な時間・空間スケールにおける研究が⾏われてきました。iLEAPS は、
このような多岐にわたる⼿段から得られた様々な知⾒の統合的理解を⽬指しています。本研究集会では、⼤気−陸域プロセスに関⼼のある研究者にお集まりいただき、各⾃の最新の研究成果を報告し、その統合的理解に向けた情報共有と議論を⾏います。特に、観測とモデルによる統合的理解について議論し、⼤気−陸域プロセスをベースとした気候変動予測研究の推進において、今後何が必要であるかについて議論します。

⽂責：佐藤永（海洋研究開発 機構・⽇本学術会議 iLEAPS ⼩委員会委員⻑）iLEAPS-Japan2021 研究集会 プログラム
12 ⽉ 9 ⽇（⽊）
座⻑：伊勢武史（京都⼤学）
13:00〜13:05 主催者挨拶と主旨説明（佐藤永・iLEAPS-Japan ⼩委員会 委員⻑）
13:05〜13:10 ロジ説明（檜⼭哲哉・iLEAPS-Japan ⼩委員会 前委員⻑）
13:10〜13:35 阿部隼⼈（九州⼤）ほか 5 名
Effects of differences in aboveground dead organic matter types on the stand-scalecarbon dynamics in a subtropical forest in Okinawa Island, Japan
13:35〜14:00 伊勢武史（京都⼤）Toward high-throughput forest inventory with deep learning
14:00〜14:25 岡村沙南（⼤阪府⼤）ほか２名
Eddy covariance measurements of NO2 flux at an urban center
14:25〜14:50 川嶋しほり（⼤阪府⼤）ほか 4 名
Factors for geographical distribution of spring onsets of vegetation in interior
Alaska14:50〜15:15 近藤雅征（名古屋⼤）ほか 4 名
Enhanced net CO2 uptake induced by autumn cooling in central Siberia
15:15〜15:30 休憩
座⻑：佐藤永（海洋研究開発機構）
15:30〜15:55 久⽶朋宣（九州⼤）Online 発表
Characteristics of carbon cycling in Moso bamboo forests
15:55〜16:20 ⼤久保晋治郎（北海道⼤）ほか 2 名 Online 発表の可能性有り
Changes in the CO2 and energy balances of a degraded tropical peat swamp forest
by fires16:20〜16:45 ⾼屋浩介（京都⼤）ほか 1 名
Automatic detection of thermokarst in satellite images using deep learning
16:45〜17:10 中⽥裕太（名古屋⼤）ほか 2 名
Global simulation of atmospheric methane by coupling the terrestrial ecosystemmodel VISIT and the global chemistry model CHASER
17:10〜17:25 第⼀⽇⽬・総括
18:00〜20:00 懇親会（12 ⽉上旬のコロナの状況により開催するか否かを決定します）

12 ⽉ 10 ⽇（⾦）
座⻑：持⽥陸宏（名古屋⼤学）

09:00〜09:25 ⼆宮秀輝（北海道⼤）ほか 2 名Simulating the effect of carbon starvation on the terrestrial ecosystem by using
individual-based vegetation model SEIB-DGVM
09:25〜09:50 持⽥陸宏（名古屋⼤）ほか 9 名
Atmospheric organic aerosol from terrestrial ecosystems: A field study in Australia
and a plan to develop a field station in Hokkaido
09:50〜10:15 両⾓友喜（北海道⼤）ほか 18 名
Ground based observation of solar induced chlorophyll fluorescence using a fineresolution spectrometer across multiple sites in cool temperate to sub-tropicalecosystems, Japan
10:15〜10:25 休憩
10:25〜10:50 籾⼭寛樹（東京⼤）ほか 2 名 Online 発表
Model analysis of forest thinning impacts on the water resources duringhydrological drought periods
10:50〜11:15 ⼭根⽔⽉（静岡県⽴⼤）ほか 1 名 Online 発表
Development of VOC uptake model by plant
11:15〜11:30 第⼆⽇⽬・総括、閉会の挨拶
11:40〜12:30 第 25 期・第 2 回 iLEAPS ⼩委員会（⼩委員会メンバーのみ参加・⾮公開）※発表は、プレゼンテーション 15 分+質疑応答 10 分
オンサイト会場のご案内
名古屋⼤学東⼭キャンパス 宇宙地球環境研究所 研究所共同館 II・409 号室(地球⽔循環共⽤室)
https://www.nagoya-u.ac.jp/upload_images/campus_map_jp.pdf ←この地図の右端 F3⑧です

オンライン（Zoom）会場のご案内
2021 年 12 ⽉ 9 ⽇（⽊） 13:00〜18:00
https://shorturl.at/hzCG8 ←短縮 URL
https://us02web.zoom.us/j/84018697612?pwd=UXR3M3RUUjkvaHZ2em5CaDN3S0NUQT09
2021 年 12 ⽉ 10 ⽇（⾦） 09:00〜11:30
https://shorturl.at/yzLT1 ←短縮 URL
https://us02web.zoom.us/j/84712034935?pwd=MHZpVXVMNGFFemdFUEtWM0VzdzdQZz09
パスワードは配信しません。待機室を設けて、実⾏委員会で⼊室管理いたします。
オンライン参加される⽅は、事前に Zoom のインストールをお願いいたします。

発表要旨

Day 1, 13:10~13:35

Effects of differences in aboveground dead organic matter types on thestand-scale carbon dynamics in a subtropical forest in Okinawa Island,
Japan
Hayato ABE1*, Ayumi Katayama2, Shingo Taniguchi3, Atsushi Takashima4,
Tomonori Kume2, Kazuho Matsumoto3
1

Graduate School of Bioresource and Bioenvironmental Sciences, Kyushu University, Fukuoka 819-0395, Japan.
2
Shiiba Research Forest, Kyushu University, Shiiba-village, Miyazaki 883-0402, Japan
3
Faculty of Agriculture, University of the Ryukyus, Okinawa 903-0213, Japan
4
Yona Field, Subtropical Field Science Center, Faculty of Agriculture, University of the Ryukyus, Okinawa
905-1427, Japan*
Corresponding author (e-mail: abe.hayato.360@s.kyushu-u.ac.jp)

Background
Dead organic matter (DOM) plays a crucial role in forest carbon (C) cycling. DOM consists of leaf
litter, fine woody debris (FWD; < 3 cm diameter), downed coarse woody debris (CWDlog), and standing or
suspended coarse woody debris (CWDsnag). Although the generation and decomposition processes of each DOM
type have been studied separately, C stock (necromass) and C efflux (Rstand) of each above-ground DOM and its
contribution on those in stand-scale have not been well evaluated. Additionally, there is little knowledge of theeffect of each DOM type on the accuracy of stand-scale estimates of total necromass and Rstand.
Objective
This study aimed to understand the characteristics of necromass and Rstand of each DOM type in thesubtropical forest in the Okinawa island. We also aimed to develop an optimal sampling strategy to estimate
necromass and Rstand.
Methodological descriptions
This study was conducted in a subtropical evergreen broad-leaved forest owned by the University of the
Ryukyus, in the northern part of Okinawa Island (2500 m2). We sampled leaf litter, FWD, CWDlog, and CWDsnag
separately within the study site in 2019 for necromass estimation. CO2 efflux rate from each DOM type wasmeasured 6 times during 2019 and examined relationships with environmental factors such as soil temperatureand moisture. Annual CO2 efflux from each DOM type was estimated using the relationships. The Rstand was
calculated by necromass and estimated annual CO2 efflux rate. Spatial distribution pattern of necromass of each
DOM type was examined and the optimal sampling plots area and arrangement for the accurate estimates were
calculated. We calculated the potential error induced by the spatial variability using the law of propagation.
Results and Discussions
The CWDsnag accounted for the highest proportion (54%) of total necromass (1499.7 g C m–2), followed
by CWDlog (24%), FWD (11%), and leaf litter (11%). Leaf litter accounted for the highest proportion (37%) of
total Rstand (340.6 g C m–2 yr–1), followed by CWDsnag (25%), CWDlog (20%), and FWD (17%). The CWDsnag
was distributed locally with 173% of the coefficient of variation for necromass, which was approximately twotimes higher than those of leaf litter and FWD (72–73%). Our spatial analysis revealed, for accurate estimates of
CWDsnag and CWDlog necromass, sampling areas of ≥ 28750 m2 and ≥ 2058‒42875 m2 were required,respectively, under the condition of 95% confidence level and 0.1 of accepted error. In summary, CWD
considerably contributed to stand-scale carbon storage and efflux in this subtropical forest, resulting in a major
source of errors in the stand-scale estimates.
Future perspectives
In forests where frequent tree death is likely to occur, necromass and Rstand of CWD are not negligible inconsidering the carbon cycling as in this study, and therefore need to be estimated accurately.

Day 1, 13:35~13:40

Toward high-throughput forest inventory with deep learning
Takeshi ISE1*
1

Field Science Education and Research Center, Kyoto University*
Corresponding author (e-mail: ise.takeshi.5e@kyoto-u.ac.jp)

Recently, a study suggested that the estimation of forest biomass in Japan has been overly underestimated, andthe actual amount can be more than two times higher than that previously thought. This implies that the forest
observation should be improved. The need should particularly be important to achieve carbon-neutral tominimize global climate change. In this study, commercially available UAVs are used to obtain the forest visual
data, and the data are analyzed by deep learning to obtain tree type, size, and density (Figure 1). The
performance of this approach is reasonable. Monotonous conifer forests for silviculture are particularly good
examples of this approach. The performance for broadleaf forests with high tree diversity is slightly lower thanthat for conifer forests, indicating this approach requires more training data for precise estimation. Because thisapproach can estimate the tree biomass efficiently with reasonable accuracy, it would be possible to be used to
update the forest inventory for a large area.

Figure 1. An example of forest observation using UAV and deep learning.

Day 1, 14:00~14:25

Eddy covariance measurements of NO2 flux in an urban center
Sana Okamura1*, Masahito Ueyama1, Kenshi Takahashi2
1

Osaka Prefecture University
2
Kyoto University*
Corresponding author (e-mail: scc03008@edu.osakafu-u.ac.jp)
Objectives: Urban NO2 emissions are important as an air pollutant and climatic forcing through aerosol
formulations. Despite of the importance, continuous measurements of NO2 flux are limited in urban areas. In thisstudy, we directly measured NO2 flux by the eddy covariance method in an urban center of Sakai, Osaka forclarifying its environmental drivers, such as wind direction, air temperature, and traffic counts.
Materials and methods: The measurements were conducted at the urban center, Sakai, Osaka (34°34’ N,
135°29’ E). The west of the flux footprint consists of highly urbanized areas including heavy traffic roads,
highways, and the coastal industrial region, and the east consists mostly of residential areas. The measurements
were conducted from February to July, 2021. The eddy covariance system simultaneously measured energy, CO2,
and CH4 fluxes at 111.7 m above the ground (Takano and Ueyama, 2021). We installed a closed path NO2
analyzer (CAPS NO2 Monitor, Aerodyne Research Inc, USA), where an air inlet was set close to the threedimensional ultrasonic anemometer (CSAT3A, Campbell Scientific Inc, USA). We applied relevant corrections
including a high-frequency loss correction. We used the traffic counts for Hanshin Expressway No. 15 Sakai
Line, which was approximately 300 m to the west of the site.
Results and discussion: NO2 flux was 2.8~3.3 times
higher in the west than in the east on average (Fig. 1).
The mean NO2 flux was 13.8 nmol m-2 s-1 in the west,
and 4.3 nmol m-2 s-1 in the east. This suggests that thehigh emission sources existed mainly in the west. In
winter, winds often came from north when the mean
NO2 flux was 8.8 nmol m-2 s-1 (Fig. 1a).
NO2 fluxes were 1.7 times higher in weekdays than inweekends (Fig. 2a). The ratio of weekday to weekend in
NO2 flux was higher than those in the traffic counts. The
traffic counts were 1.4 times higher in weekdays than inweekends (Fig. 2b). This might be caused by mobile
sources, such as heavy tracks, were higher in theweekdays than in the weekends.
NO2 flux showed a clear diurnal variation with a peakin the morning in weekdays. NO2 flux showed a peak of
20.8 nmol m-2 s-1 at 9:30. After the peak, NO2 flux
ranged between 16~18 nmol m-2 s-1 until 16:00. The
traffic counts showed a diurnal variation with two peaksin the morning and afternoon in weekdays. The traffic
counts showed a first peak of 702 Veh h-1 at 7:30, and asecond peak of 638 Veh h-1 at 17:00. After the peak at
7:30, the traffic counts decreased to 506 Veh h-1 at 13:00,
and then increased again. The difference in the diurnal
variations may be due to the fact that the traffic counts
does not fully represent dynamics for diesel vehicles
emitted NOx within the flux footprint. Emission sources
other than traffic may contribute to NO2 flux.

Fig 1. Windrose of daytime NO2 flux for the
winter (a) and summer (b). Winter is fromFebruary to March, and Summer is from May to

Fig 2. Diurnal pattern of NO2 flux (a), and traffic
counts (b) for weekdays and weekends. The solidline represents the 3-hour moving average, andthe shaded area represents the standard deviation.

References
Takano, T., Ueyama, M., 2021. Spatial variations in daytime methane and carbon dioxide emissions in two
urban landscapes, Sakai, Japan. Urban Climate, 36, 100798.
Acknowledgements
The traffic counts from the highway were provided by the Hanshin Expressway Company.

Day 1, 14:25~14:50

Factors for geographical distribution of spring onsets of vegetation ininterior Alaska
Shihori Kawashima1*, Masahito Ueyama1, Yoshinobu Harazono1, Hiroki Iwata2, Hideki
Kobayashi3
1

Osaka Prefecture University
2
Shinshu University
3
Japan Agency for Marine-Earth Science and Technology (JAMSTEC)*
Corresponding author (e-mail: sac03010@edu.osakafu-u.ac.jp)
Objectives: The spring onset of vegetation is essential in modeling carbon balance of high-latitude ecosystems.
The spring onsets in boreal ecosystems are highly variable at spatiotemporal scales due to the heterogeneous
topography and vegetation. However, models having a coarse spatial resolution, such as earth system model,
possibly cannot consider such variabilities. In this study, we clarify controlling factors for explaining the
spatiotemporal variabilities in the spring onset in interior Alaska. For explaining the variabilities, we used terrain
slope orientation, elevation, vegetation type, snow disappearance, and land surface temperature (LST) in spring.
Materials and methods: The area surrounding Fairbanks, Alaska (64°8′~65°4′N, 147°3′~147°9′W; 65 km x 65km) was evaluated from 2000 to 2021. We estimated the spring onset of each grid (250 m x 250 m) and thenestimated the spatial distribution of the thermal forcing requirement (TFR) for the spring onset in the growing
degree-day (GDD) model. The spring onset was estimated with the extended vegetation index (EVI)(MOD13Q1) from the Moderate Resolution Imaging Spectroradiometer (MODIS). In the GDD model, thedaytime LST (MOD11A1) was used as an input. We set the degree-day base temperature to 0°C, and set the dayon which GDD accumulation started as the snow disappearance date (MOD10A1) (Kawashima et al., 2021; J.
Agric. Meteorol.). We evaluated the spatial variations of the 2000-2021 mean spring onsets, the mean snow
disappearance dates, and the TFR using terrain slope orientation and elevation from the ASTER Global
Elevation Model and vegetation map from the National Land Cover Database 2011.
Results and discussion: Regional
spring onsets based on mean ofindividual grids were two to four days
later (interquartile range) than those
based on the aggregated EVI for theFig 1. Composition of vegetation
target area from 2000 to 2021. This
type for the south-facing (a), andindicates that the spring onsets withnorth-facing (b) slopes. ‘n’ is thethe coarse spatial resolution were
number of grids.
estimated earlier due to a lack ofconsidering spatial variabilities, such as topography and vegetation.
The mean spring onsets was, on average, DOY 132.2±4.0, the meansnow disappearance date was DOY 125.5±4.9, and the TFR was
65.9±29.9 °C day; ± denotes spatial variability. The median of the TRF in
the south-facing slope was 12 °C day higher than that in the north-facing
slope. The differences could be explained by vegetation compositions
between the slopes (Fig 1). Deciduous forests consisted on the southfacing slopes; bud bursts of deciduous trees were further lagged aftersnow disappearance, compared with spruce trees dominated in northfacing slope. Since the available data number was limited for north-facing
slopes (Fig 1), we focused further data analyses on the south-facing slopes. Fig 2. The relationship between
The spring onset was earlier in lower elevations (17 days km-1), and each spatial variation and elevation
earlier in deciduous forests than that in evergreen forests (p < 0.05). These in the south-facing slopes. Colors invariations had strong positive correlations to the variations in the snow scatter plots represent the mean
disappearance date (Fig 2a, b). This means the snow disappearance date is LST in the spring (DOY 105-135)
the potentially important for controlling the spring onset. The TFR was or May. White plots represent thelower in vegetation at higher elevations (Fig 2c; -52 °C day km-1). Thus, binned mean for each vegetation,
vegetation at higher elevations became active with a shorter period after and error bars represent thethe snow disappearance (-7.1 day km-1). This might be explained by standard deviations.
different vegetation types depending on the elevation.

Day 1, 14:50~15:15

Enhanced net CO2 uptake induced by autumn cooling in central Siberia
Masayuki Kondo1, Motoki Sasakawa2, Mizuki Takeuchi3, Kaho Suganuma3, Tetsuya
Hiyama1,1

Institute for Space-Earth Environmental Research, Nagoya University, Nagoya, Furocho, Chikusa Ward,
Nagoya, Aichi 464-8601 Japan
2
National Institute for Environmental Studies, Tsukuba, Ibaraki 305-8506, Japan
3
Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, Furocho, Chikusa Ward, Nagoya,
Aichi 464-8601 Japan*
Corresponding author: Masayuki Kondo (e-mail: redmk92@gmail.com)
For the past 60 years, climate change has enhanced the productivity of ecosystems in Siberia. The warming
climate has elongated the growing period of vegetation and enhanced the peak productivity during summer.
Correspondingly, CO2 uptake in Siberia has continuously increased since the 1960s, playing a significant
contributor to the increased amplitude of the atmospheric CO2 seasonal cycle in the Northern Hemisphere.
As the temperature increased over decades, however, the impact of a warming climate has shown different
aspects among regions of Siberia. Permafrost thaw could facilitate the release of CO2 through microbial
decomposition of carbon stored in frozen soils and through root rot that causes forest dieback. This negative
impact of a warming climate on vegetation productivity has begun to be seen in Eastern Siberia and may widely
spread over ecosystems standing on permafrost in the future. In central Siberia, where permafrost is absent, awarming climate is expected to further increase CO2 uptake during spring and summer. However, continued
warming in autumn may facilitate CO2 release from ecosystem respiration, weakening net CO2 uptake duringthat period.
While the negative impact of a warming climate is becoming a reality in Siberia, a recent study reported
that an abrupt and persistent autumn cooling influenced by Pacific Decadal Oscillation (PDO) and Siberian highoccurred from 2004 to 2018 around central Siberia. This result suggests a possibility that for 2004-2018 CO2
release was suppressed by autumn cooling while having increasing CO2 uptake in warming spring and summer,
which leads to a hypothesis that net CO2 uptake in central Siberia was the largest ever for 2004-2018.
This study investigates the validity of the hypothesis about recent net CO2 uptake in central Siberia. Using
atmospheric CO2 measurements in central Siberia and upscaled eddy flux observations, we demonstrate how
seasonal atmospheric CO2 and net CO2 uptake changed before and after 2004, focusing on autumn.

Day 1, 15:30~15:55

Characteristics of Carbon Cycling in Moso Bamboo forests
Tomonori Kume1*
1*

Shiiba Research Forest, Kyushu University (10 p)
Corresponding author (e-mail: kumett@gmail.com) (10 p)

Introduction
Forest plantations that exhibit fast-growing characteristics, such as bamboo forests, have been assumed toshow a high carbon sequestration ability. Moso bamboo (Phyllostachys pubescens), one of the dominant bamboo
species in East Asia, is a monopodial species distributed over an elevation range of 600–1500 m in central
Taiwan. The aggressive expansion of Moso bamboo forest into adjacent ecosystems which might alter the
carbon balance replacement, has been noted recently in East Asian countries such as Taiwan. Moso bamboo hasa biennial growth cycle that can causes significant inter-annual variations in net primary productivity (NPP) andnet ecosystem productivity (NEP). On the other hand, to our knowledge, only one study has investigated NPP
covering biennial cycles in a Moso bamboo forest. Therefore, the aim of the present study was to clarify the NPP
and NEP in a Moso bamboo forest in Taiwan by considering above- and below-ground processes over a 4-year
experimental period.
Materials and methods
A 20 x 25 m study plot was established in a pure Moso bamboo (P. pubescens) forest in the Experiment
Forest of National Taiwan University (23°40′, 120°48′), located in Nantou County, central Taiwan. The study
plot is located at 1120 m above sea level, and it experiences a subtropical monsoon montane climate.
Meteorological data, such as air temperature and precipitation, were recorded by a weather station located 0.2
km northeast of the experimental site. The mean annual air temperature (MAT) over the study period (April
2012–March 2016) was 18.6 °C. The mean annual precipitation was 2407 mm. NPP and NEP were quantified
biometric measurements including above- and below-ground biomass measurements and soil respirationconsisting of autotrophic and heterotrophic respirations.
Results and discussion
The estimated NPP and NEP showed considerable inter-annual variations (coefficient of variation of 39 and79%, respectively). Averaged over the 4 years, the NPP and NEP were 8.86 ± 3.46 and 4.32 ± 3.35 Mg C ha-1
year-1, respectively, which were within the ranges (6.53–14.36 and 3.59–7.98 Mg C ha-1year-1, respectively)
reported for Moso bamboo forests in East Asian countries. A global comparison of NPP and NEP among forest
ecosystems using data from published literature indicated that the estimated NPP and NEP in the present study,
as well as those in Moso bamboo forests from East Asian countries, were within the upper range of the values
reported for other forest ecosystem. The results indicate that Moso bamboo forests may have high potential as acarbon sink among forests ecosystems. On the other hand, this study has some weakness. For example, it ispossible that 4-year period is still not sufficient to acquire robust NPP and NEP measurements. The Student’s ttest analysis showed that the minimum numbers of sample years required to estimate the mean NPP and NEP are
greater than 38 and 159 years, respectively, with a significance level of 0.05 and a 20% error of the mean. Thisfinding implies that additional long-term monitoring is needed to acquire robust NPP and NEP estimations withhigh temporal representatively.

Day 1, 15:55~16:20

Changes in the CO2 and energy balances of a degraded tropical peat swamp
forest by fires
Shinjiro Ohkubo1*, Takashi Hirano1, Kitso Kusin2
1
2

Research Faculty of Agriculture, Hokkaido University, Sapporo, Japan.
CIMTROP, University of Palangkaraya, Palangkaraya 73112, Indonesia*
Corresponding author (e-mail: sohkubo@env.agr.hokudai.ac.jp)

Tropical peatland is widely distributed in Southeast Asia, and it is well known as a giant carbon pool.
However, it had been disturbed by deforestation and drainage mainly for agricultural land use. Moreover,aridification caused by these disturbances increase the risk of fire. Such disturbances increase CO2 emission to
the atmosphere by accelerated peat decomposition and biomass burning. Many studies estimated carbon balanceon peatland and revealed the relationship with environmental changes. In particular, negative correlation
between groundwater level (GWL) and net ecosystem CO2 exchange (NEE) was observed in many peatland sites(e.g., Hirano et al., 2012; Deshmukh et al., 2021). On the other hand, these land cover changes have a significant
impact also on water and heat exchanges between land and the atmosphere. In this study, we mainly evaluatedthe influence of disturbances (especially, fire) on NEE and evapotranspiration (ET) with sensible and latent heat
fluxes (H and E) in degraded peat ecosystems.
Observation had been conducted in an ex-peat swamp forest, Central Kalimantan, Indonesia. The site wasforested until 1997, when a fire destroyed the forest and left the site in ruins. Since then, the site had been burned
at least three times in 2002, 2009 and 2014. NEE and ET were measured by the eddy flux technique.
Observation had been conducted from April 2004 to December 2016. In 2009, the study site experienced
moderate fire, and some aboveground herbaceous plants were burned. At this time measurement was suspended
due to the fire damage.
Monthly NEE had been positive (i.e., the ecosystem released CO2 in total) until the fire in 2009. On thecontrary, the NEE turned to be negative after the fire. There are some possible causes: 1) Coarse woody debris
which was major CO2 source, was destroyed by the fire, 2) Peat decomposition was suppressed with waterlogged
condition in subsequent La Niña years, 3) Gross primary production promptly returned to its original level underfavorable (moist soil and high solar radiation) conditions for plant growth. However, this does not necessarilymean the peatland ecosystem turned to be a carbon sink by the fire. This is because the site had emitted large
amount of CO2 during past fires, far more than it absorbed CO2 after fire in 2009. Moreover, temporary CO2
release by the biomass burning could not be observed during suspended observation period.
The ET was relatively stable irrespective of precipitation. However, ET decreased with extremely deepened
GWL (GWL<-0.5 m). This would be due to disconnected capillary force and ceased root water uptake, althoughrainwater shortage was usually compensated by soil water. Decreased ET was seen regardless of whether there
was fire damage to vegetation or not. On the other hand, both H and E decreased when there was a significant
drop in net radiation due to fire-induced haze. At that time, Bowen ratio (H/E) temporarily increased.
Meanwhile, apparent albedo increased because of dense haze layer above canopy.
As further analysis, partitioning ET into evaporation and transpiration is important to understand thebiological and physical mechanisms deeply. Evaluation excluding the effect of post-fire weather conditions
would also be needed to assess the impact of fire alone.
Much of this presentation is described in Ohkubo et al. (2021a; 2021b; 2021c).
References:
Deshmukh et al. (2021). Conservation slows down emission increase from a tropical peatland inIndonesia. Nature Geoscience, 1-7.
Hirano et al. (2012). Effects of disturbances on the carbon balance of tropical peat swamp forests. Global
Change Biology, 18(11), 3410-3422.
Ohkubo et.al. (2021a). Influence of disturbances and environmental changes on albedo in tropical peat
ecosystems. Agricultural and Forest Meteorology, 301, 108348.
Ohkubo et al. (2021b). Assessing the carbon dioxide balance of a degraded tropical peat swamp forest following
multiple fire events of different intensities. Agricultural and Forest Meteorology, 306, 108448.
Ohkubo et al. (2021c). Influence of fire and drainage on evapotranspiration in a degraded peat swamp forest inCentral Kalimantan, Indonesia. Journal of Hydrology, 603, 126906.

Day 1, 16:20~16:45

Automatic detection of thermokarst in satellite images using deep learning
Kosuke TAKAYA1*, Takeshi ISE2
1

Graduate School of Agriculture, Kyoto University
Field Science Education and Research Center, Kyoto University*
Corresponding author (e-mail: takaya.kosuke.25a@st.kyoto-u.ac.jp)
2

Climate change is causing rapid changes in the permafrost of the Arctic. The permafrost contributes to soil
temperature and moisture content and the stability of Arctic ecosystems and infrastructure. Thermokarst, causedby the thawing of the frozen soil, promotes ecosystem change by creating landscape-level changes, which affecthuman society, such as the subsidence of housing. It also has the potential to release carbon stored in the frozen
soil. In order to understand the dynamics of thermokarst, extensive and long-term monitoring is essential.
Satellite imagery can reveal the distribution of thermokarst over a wide area, but manual methods are laborintensive. We may monitor a more expansive area to identify thermokarst using image recognition technology
based on deep learning. Therefore, the purpose of this study is to clarify whether it is possible to detect
thermokarst from satellite images by deep learning. As a result of creating a thermokarst identification modelusing the chopped picture method, it became clear that thermokarst can be detected by deep learning. However,some thermokarst could not be detected due to their image conditions. In the case of thermokarst, which has asimilar appearance, we created a more robust model that can be used in multiple regions. In this presentation, we
will discuss the potential and future challenges of environmental monitoring in the Arctic region using a
combination of satellite imagery and artificial intelligence.

Figure 1. Classification results of thermokarst: (a)original images and (b) results. Red
squares indicate thermokarst, green indicates others.

Day 1, 16:45~17:10

Global simulation of atmospheric methane by coupling the terrestrial
ecosystem model VISIT and the global chemistry model CHASER
Yuta Nakata1*, Akihiko Ito2,3, Kengo Sudo1,3
1

Graduate School of Environmental Studies, Nagoya University
National Institute for Environmental Studies (NIES), Tsukuba
3Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama
2Methane (CH4) is one of the most important greenhouse gases in the atmosphere. Methane has both naturaland anthropogenic sources, such as wetlands, termites, coal mining, livestock, and rice paddies. Although mostsources and sinks of CH4 have been identified, their relative contributions to the atmospheric CH4 levels arehighly uncertain (Kirschke et al, 2013). This study focuses on wetland CH4 emission which is the largest natural
source of atmospheric CH4, amounting to roughly 20-40 % of global CH4 emissions. In this study, wetland
emissions, off-line calculated by the terrestrial ecosystem model, VISIT (Ito and Inatomi, 2012), were given as
an input to the global chemistry model, CHASER (Sudo et al., 2002) to simulate the global chemical fields forthe years from 2001 to 2018. By comparing the global CH4 simulations with satellite and ground-based
observation data, we evaluated the reproducibility of the spatiotemporal distributions of methane withinvestigating the impacts of wetland emissions on atmospheric methane.
For the VISIT calculation, two distinct schemes of emission estimate are tested for checking the sensitivityof CHASER simulation. One is the Cao Scheme (Cao et al., 1996) in which the total exchange of CH4 isevaluated as the difference between CH4 production and oxidation rates, while the other (Walter-Heimann
scheme) (Walter and Heimann 2000) explicitly considers various CH4 production and transport processes byexpressing belowground processes using a one-dimensional multilayer system in which the soil from the surface
to a depth of 1 m was divided into 50 layers (each 2 cm).
The CHASER model in this study is based on MIROC (ver.5). For this study, we adopted a horizontal
spectral resolution of T42 (approximately, 2.8° × 2.8°) with 36 vertical layers from the surface up to about 55km
altitude. The anthropogenic CH4 emissions are taken from the EDGAR (Emissions Database for Global
Atmospheric Research) v4.2 inventory with the GEIA (Global Emission Initiative) used for other naturalemissions. The methane distributions and time evolution calculated by CHASER were evaluated with thesatellite observations by GOSAT (Greenhouse Gases Observing Satellite) and ground-based observations inNorth America, Asia, Europe, Africa, Oceania, Antarctica, and Hawaii.
The global methane simulations using the VISIT wetland emissions generally well reproduced the
distribution of CH4 as observed by the ground and satellite observations, largely reducing the overestimates in
the mid to high latitudes in NH. It is found that the simulations using the VISIT wetland emissions tend to
reduce the magnitude of seasonal cycles in the global mean methane time series. In addition, the results ofsensitivity experiments also show that the seasonality of wetland emissions can be an important factor in theseasonal cycle of methane. Comparing the results that using each scheme, reproducibility was better when the
Cao scheme was used. This is because the annual emissions from wetlands calculated by the Walter-Heimann
scheme were on average 11 Tg smaller. In terms of seasonal cycles, Walter-Heimann scheme slightly better
simulates seasonal pattern of CH4 than the Cao scheme does. However, the difference in reproducibility of eachscheme was small, and their reproducibility was better at least than the standard experiment.
Acknowledgements: The calculations were performed by using the supercomputer system (NEC SX-Aurora
TSUBASA) of the National Institute for Environmental Studies (NIES).
References:
Cao et al., : Global carbon exchange and methane emissions from natural wetlands: Application of a processbased model, J. Geophys. Res., 110, 14399-14414,1996.
Ito and Inatomi : Use of process-based model for assessing the methane budgets of global terrestrial ecosystems
and evaluation uncertainty, Biogeosciences, 9(2), 759-773.
Kirschke et al., : Three decades of global methane sources and sinks, Nature Geoscience., 6, 813-823,
https://doi.org/10.1038/ngeo1955,2013.
Sudo, K., M. Takahashi, J. Kurokawa, and H. Akimoto (2002), CHASER: A global chemical model of thetroposphere: 1. Model description, J. Geophys. Res., 107(D17), 4339, doi:10.1029/2001JD001113.
Walter, B. P. and Heimann, M.: A process-based, climate-sensitive model to derive methane emissions fromnatural wetlands : Application to five wetlands sites, sensitivity to model parameters, and climate,
Global Biogeochem. Cy., 14 745-765, 2000.

Day 2, 9:00~9:25

Simulating the effect of carbon starvation on the terrestrial ecosystem byindividual-based vegetation model SEIB-DGVM
Hideki Ninomiya1*, Tomomichi Kato2,3, Hisashi Sato4
1. Graduate School of Global Food Resources, Hokkaido University
2. Research Faculty of Agriculture, Hokkaido University
3. Global Center for food, Land, and Water Resources, Research Faculty of Agriculture, Hokkaido University
4. Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology (JAMSTEC)*Corresponding author (email: hideki.ninomiya0302@gmail.com)
Pervasive shifts in forest vegetation dynamics are already happening and are expected to accelerate
under future global changes (McDowell et al., 2020). Forest dynamics are changing due to anthropogenic-driven
drivers, such as rising temperature and CO2, and affected by transient disturbances. Tree recruitment and growthdepend on the changing drivers in a spatially and temporally way, potentially leading to an increase of treemortality rates. Then, tree mortality results in a negative impact on the earth (Adams et al, 2013). However, it ischallenging to estimate the negative impact due to the unsolved carbon flow in trees. Trees have grown tocontrol their carbon resources to extend lives and strategically allocate them to growth, respiration, storage,
reproduction, and defense (Hoch et al, 2003; Henrik et al, 2018). Among carbon resources, non-structural carbon(NSC) is commonly considered a repository depending on the balance between the supply of assimilated carbon
and carbon demand. Hence, the size of stored C pools can be considered an indicator of the carbon balance of theplant. Additionally, NSC could be the threshold of the conceptual “carbon starvation” as one of the mechanisms
after drought (Hoch et al, 2003; McDowell et al., 2008). The objectives of the research are to apply the processrepresenting NSC dynamics to the ecological model and expect the potential effect of carbon starvation in the
future.
The process-based Spatially Explicit Individual-Based Dynamic Global Vegetation Model (SEIBDGVM; Sato et al., 2007), representing three-dimensional tree structure and individual tree growth, was used inthis study. In a 30m×30m grid, each plant competes with the other for incoming solar photons. Then, we newly
created a process of accumulating NSC in tree bodies for SEIB-DGVM. When the photosynthesis rate declines,
NSC compensates for maintenance respiration and is gradually close to zero. We validated the new function at apoint and global scale, and analyzed how the model outputs from new model is different from them from original
SEIB-DGVM. In addition, we set conditions that could represent carbon starvation using NSC dynamics, thenresearch how carbon starvation will affect the vegetation distribution, gross primary production (GPP), net
primary production (NPP) in the future.

Day 2, 9:25~ 9:50

Atmospheric organic aerosol from terrestrial ecosystems: a field study inAustralia and a plan to develop a field station in Hokkaido
Michihiro Mochida1*, Sho Ohata1, Yoko Yokoyama2, Motomi Igarashi2, Dhananjay K.
Deshkukh3, Bhagawati Kunwar3, Kimitaka Kawamura3, Sonia Afsana1, Quang Dang4, andClare Palton-Walsh4
1

Nagoya University
Murata Keisokuki Service Co., Ltd.
3
Chubu University
4
University of Wollongong*
Corresponding author (e-mail: mochida@isee.nagoya-u.ac.jp)
2

Terrestrial ecosystems are an important source of organic aerosol in the atmosphere. Atmospheric reactionsof biogenic volatile organic compounds (BVOCs) from the ecosystems include formation processes of so-calledbiogenic secondary organic aerosol (BSOA) (Hallquist et al., 2009). Further, terrestrial ecosystems also
contribute to the burden of organic aerosol through the release of primary biological aerosol particles (PBAP)(Després et al., 2012). Wildfire is also considered as a pathway to provide atmospheric organic aerosol, whichcontain unique organic compounds as a result of the pyrolysis of the biomass. Previous discussions on theseorganic aerosols include the contribution of BSOA to the abundance of cloud condensation nuclei (CCN) and thepossible role of PBAP as ice nuclei. Our current knowledge of the roles of these organic aerosol on climate isstill limited, and observational evidence to better constrain the atmospheric loadings and also to characterize
their properties are strongly required. In this presentation, two research topics related to organic aerosols
originated from terrestrial ecosystems will be discussed.
The first topic is about a recent field study of atmospheric organic aerosol based on aerosol sampling in
New South Wales, Australia, as part of COALA-2020 field campaign. The aerosol sampling during the
campaign was performed using a high-volume air sampler coupled with a cascade impactor, from January to
March, 2020, at Cataract Scout Park. Sub-micrometer aerosol particles were collected on quartz fiber filters, andinorganic ions, organic carbon, elemental carbon, water-soluble organic carbon, and individual organic
compounds including the tracers of BSOA and biomass burning aerosol were analyzed. The tracer analysis
suggests the strong variations of the contributions of biomass burning and BSOA during the study period,
encouraging a study about the contrast between these two types of organic aerosols and the resulting variationsof aerosol properties such as light absorption property. During the campaign, total suspended particulate matter
was also collected on polycarbonate filters using a low-volume air sampler. Water-insoluble particles on thefilters are going to be analyzed using single-particle extinction and scattering (SPES) method.
The second topic is about the development of an observatory in Hokkaido for the measurements ofatmospheric aerosols and gases, in particular for the studies of organic aerosols from biogenic VOCs and forest
fires. A plan to develop a ground-based field station utilizing Moshiri Observatory, Institute for Space-EarthEnvironmental Research, Nagoya University, will be explained. Whereas the formation and transport of organic
aerosols from vegetation, including those from biomass burning, needs to be further explored, their roles should
also be explored in view of their climatic effects and further to the feedback to vegetation (Sporre et al., 2019).
Suggestions and comments on the plan from the audience are appreciated.
References
Després, V. R. et al.: Primary biological aerosol particles in the atmosphere: a review, Tellus B, 64, 15598, 2012.
Hallquist, M. et al.: The formation, properties and impact of secondary organic aerosol: current and emerging
issues, Atmos. Chem. Phys., 9, 5155–5236, 2009.
Sporre, M. K., Blichner, S. M., Karset, I. H. H., Makkonen, R., and Berntsen, T. K.: BVOC–aerosol–climate
feedbacks investigated using NorESM, Atmos. Chem. Phys., 19, 4763–4782, 2019.

Day 2, 9:50~10:15

Ground based observation of solar induced chlorophyll fluorescence
using a fine resolution spectrometer
across multiple sites in cool temperate to sub-tropical ecosystems, Japan
Tomoki Morozumi1*, Tomomichi Kato1,2, Naohisa Nakashima1,3, Buareal Kanokrat2,
Kitpanuwat Tanatarakeree4, Hideki Kobayashi5, Yuma Sakai5, Katsuto Tsujimoto6,
Hibiki M. Noda7, Yoshiyuki Takahashi7, Kentaro Takagi8, Takashi Hirano1,
Masahito Ueyama9, Keisuke Ono10, Kazuho Matsumoto11, Tomoko Kawaguchi
Akitsu12, Kenlo Nishida Nasahara12, Shohei Murayama13, Hiroyuki Muraoka14
1

Research Faculty of Agriculture, Hokkaido University
Graduate School of Global Food Resources, Hokkaido University
3
Department of Agro-environmental Science, Obihiro University of Agriculture and Veterinary Medicine
4
Graduate School of Agriculture, Hokkaido University
5
Institute of Arctic Climate and Environmental Research, Japan Agency for Marine-Earth Science andTechnology
6
Graduate School of Life Sciences, Tohoku University
7
Earth System Division, National Institute for Environmental Studies
8
Field Science Center for Northern Biosphere, Hokkaido University
9
Graduate School of Life and Environmental Sciences, Osaka Prefecture University
10
Institute for Agro-Environmental Sciences, NARO
11
Faculty of Agriculture, University of the Ryukyus
12
Faculty of Life and Environmental Sciences, University of Tsukuba,
13
Environmental Management Research Institute, National Institute of Advanced Industrial
Science and Technology
14River Basin Research Center, Gifu University*
Corresponding author (e-mail: morozumit@cen.agr.hokudai.ac.jp)
2

We have been conducting ground-based measurement of solar induced chlorophyll fluorescence (SIF) as aremote sensing variable to capture the photosynthetic activity in terrestrial ecosystems. When illuminated bysolar radiation, chlorophyll pigment emits red and far-red fluorescence at 650-850 nm wavelength. SIF ismeasurable fraction of the fluorescence at the atmospheric absorption band so-called Fraunhofer lines in O2-A
and O2-B bands with fine resolution (< 0.5 nm) of upward and downward radiation. Canopy-scale SIF arethought to be a proxy of ecosystem level CO2 fixation, i.e., gross primary production (GPP), although previous
research pointed out species/ecosystem-type and scale dependent relationship between SIF and GPP. Satellite
SIF product (e.g. GOSAT-2, OCO-2, TROPOMI, FLEX, GeoCarb etc.) is expected to contribute to those tasks.
However, there is lack of ground-based dataset covering various ecosystem types. The purpose of the study is tounderstand site-scale SIF:GPP relationship in various ecosystem, Japan, to improve our understanding of landatmosphere interaction processes.
We installed spectrometers with fine wavelength resolution, QE pro (Ocean Insight, FL, USA) with full
width half maximum (FWHM) = 0.24 nm. The locations were selected from the collaborated field sites inremote sensing network PEN (http://pen.envr.tsukuba.ac.jp). The study sites are including cool-temperate
deciduous broadleaf forest dominated by birch and oak (TKY: 36°N, 137°E, Gifu, Japan), deciduous needleleaf
larch forest (FHK: 35°N, 139°E, Yamanashi; TSE: 45°N, 142°E, Hokkaido), cool-temperate wetland (BBY:
43°N, 141°E, Hokkaido), temperate rice paddy field (MSE: 36°N ,140°E, Ibaraki), subtropical evergreen
broadleaf forest (YNF: 27°N, 128°E, Okinawa). Targeting optical receivers (cosine collector for field of view:
FOV = 180° or bare fiber for FOV = 25°) are mounted on flux towers. Observations started in 2019 at TKY,
MSE, YNF, BBY and in 2021 at FHK and TSE. The seasonal variation of SIF varied approximately 0-1.5 mW
m-2 nm-1 sr-1 from relatively flat peak at an evergreen forest (YNA) to short sharp peak at a rice paddy (MSE). In
this presentation, we will also show recent progress on SIF:GPP study on MSE paddy field, BBY wetland, TKY
deciduous forest, and also introduce a crop canopy SIF radiative transfer modelling (Morozumi et al, submitted)
and a practical approach of SIF retrieval in low resolution spectra based on a fine resolution spectral observation
in TKY (Nakashima et al 2021).
Nakashima, N., Kato, T., et al (2021). Area-ratio Fraunhofer Line Depth (aFLD) method approach toestimate solar-induced chlorophyll fluorescence in low spectral resolution spectra in a cool-temperate deciduous
broadleaf forest. Journal of Plant Research, 134, p.p. 713–728.

Day 2, 10:25~10:50

Model analysis of forest thinning impacts on the water resources duringhydrological drought periods
Hiroki Momiyama1*, Tomo'omi Kumagai1, 2, 3, Tomohiro Egusa1, 4
1

Graduate School of Agricultural and Life Sciences, The University of Tokyo
2
Institute for Space-Earth Environmental Research, Nagoya University
3
Water Resources Research Center, University of Hawaiʻi at Mānoa
4Faculty of Agriculture, Shizuoka University*
Corresponding author (e-mail: momiyama@g.ecc.u-tokyo.ac.jp)

In Japan, there has recently been an increasing call for forest thinning to conserve water resources fromforested mountain catchments in terms of runoff during prolonged drought periods of the year. However, it has
not been fully explained how forest thinning effects on increasing both minimum seasonal streamflow rateduring the drought periods of the year and extremely low streamflow rate during the prolonged drought periods.
To investigate how their water balance and the resultant runoff are altered by forest thinning, we conducted amodel analysis using a combination of 8-year hydrological observations, 100-year meteorological data output
that is generated using a stochastic model, and a semi-process-based rainfall-runoff model.
In this study, the hydrological, meteorological, and geographical data of Oborasawa Experimental
Watershed (Kanagawa, 35°28´N, 139°28´E, altitude 439–872 m, 49.5 ha) is used. The rainfall-runoff model isdeveloped based on TOPMODEL[1]. 100-year meteorological data were constructed using random numbers
generated from probability distributions representing current precipitation characteristics at the site to consider
the most severe drought conditions. We validated those models against runoff observations at Oborasawa. After
that, we conducted the simulation of thinning, assuming that forest thinning has an impact on runoff primarily
through an alteration in canopy interception and that interception can be determined by an interception model [2]using stem density.
The model reproduced temporal variations in runoff and evapotranspiration at inter- and intra-annual timescales, and the flow duration curves were well reproduced. On the basis of projected flow duration curves for the
100-year, despite the increase in an annual total runoff with thinning, low flow rates (the flows within the rangeof >70% time exceedance) in both dry and normal years (the years in which low flow are the lowest and 50th thelowest) were impacted by the forest thinning to a lesser extent (Figure 1). Simulations also showed that low
flows would increase more with higher catchment water retention capacity, and higher catchment water retention
capacity would enhance the forest thinning effect on increasing available water resources (Figure 1).
The model developed in this study is expected to be useful for examining the effects of forest management
on various forested catchments by giving the water retention capacity of the watershed in advance. How todetermine the water retention capacity in the model and how and to what extent the water retention capacity of awatershed can be changed by forest management will require further study, but the application of this study
would be helpful in planning for better forest management considering runoff from forested catchments.

Figure 1
Relationships between m (the parameter that
represents catchment water retention
capacity) and increases in runoff afterthinning. Changes in the values due toalterations of stand density from 2229 to1132 trees ha−1 is shown. The relationships
are compared between intermediate flows
and low flows situations and between thenormal year and the dry year.
[References][1] Beven and Kirkby (1979): Hydrol. Sci. Bull., 24(1), 43–69.
[2] Komatsu et al. (2007): J. Hydrol., 336(3–4), 361–375.

Day 2, 10:50~11:15

Development of VOC uptake model by plant
Mizuki, Yamane, Akira TANI*
Department of Environmental Sciences, School of Food and Nutritional Sciences, University of Shizuoka*
Corresponding author (e-mail: atani@u-shizuoka-ken.ac.jp)

Large amount of volatile organic compounds (VOCs) are emitted into the atmosphere from biogenic andanthropogenic sources. Many kinds of VOCs are directly harmful to human and some of them are carcinogenic.
VOCs promote creation of photochemical oxidants including ozone in the troposphere, and it may cause
respiratory diseases. VOCs also promote productions of secondary organic aerosol (SOA), which affects humanhealth and climate. SOA absorbs and scatters shortwave radiation and affects cloud properties by acting as cloud
condensation nuclei (CCN) or ice nuclei. It has been reported that plants can remove inorganic gases such asozone and NOx from the atmosphere. Recent study revealed that some species of VOCs, in particularoxygenated VOCs, are also taken up by plants. The removal of VOCs by plants from the atmosphere cancontribute not only to reducing direct negative effect of harmful VOCs but also to suppressing its indirect effects
on the creations of ozone and SOAs. The process of VOC uptake by plant leaves seems to be composed ofseveral steps: VOC diffusion via stomata, air-liquid partitioning governed by Henry’s law constant, andmetabolic conversion in plant cells. To explain this process, we have developed a plant VOC uptake model basedon the diffusion theory analogous to CO2 assimilation by plants.