YOKOZAWA, Masayuki
Professor
(School of Human Sciences)
https://sites.google.com/site/yokozawalab/my-homepage
http://www.researcherid.com/rid/O-2829-2014(Researcher ID)
https://scholar.google.co.jp/citations?hl=ja&user=FE6tAFcAAAAJ(Google Scholar Citation)
Faculty of Human Sciences(e-School (Internet Degree Program), School of Human Sciences)
Faculty of Human Sciences(Graduate School of Human Sciences)
-1985 | BS, Tokyo Institute of Technology, Physics |
-1987 | MS, Tokyo Institute of Technology, Physics |
Ph.D Thesis The University of Tokyo Ecology/Environment
1987/04-2013/09 | National Institute for Agro-Environmental Science |
2013/10-2017/03 | Shizuoka UniveristyDepartment of EngineeringProfessor |
American Geophysical Union
Nakagawa Y, Yokozawa M, Ito A, Hara T.
Ecological Modelling 361p.95 - 1122017-
Sakurai G, Yamaji N, Mitani-Ueno N, Yokozawa M, Ono K, Ma J.
Frontiers in Plant Science 8p.11872017-
Y. Kunimitsu R. Kudo T. Iizumi M. Yokozawa
Paddy and Water Environment 14p.131 - 1442016-
Y. Nakagawa M. Yokozawa T. Hara
Nonlinear Theory and Its Applications 7p.126 - 1452016-
Y. Nakagawa M. Yokozawa T. Hara
Ecological Complexity 26p.95 - 1162016-
Y. Nakagawa M. Yokozawa T. Hara
Ecological Modelling 301p.41 - 532015-
G. Sakurai S. Yonemura A.W. Kishimoto S. Murayama T. Ohtsuka M. Yokozawa
PLOS ONE 10p. e01190012015-
G. Sakurai A. Satake N. Yamaji N. Mitani-Ueno M. Yokozawa F.G. Feugier J. Ma
Plant and Cell Physiology 56p.631 - 6392015-
M. Okada T. Iizumi G. Sakurai N. Hanasaki T. Sakai K. Okamoto M. Yokozawa
Journal of Advances in Modeling Earth Systems 7p.1409 - 14242015-
J.M. Tubay K. Suzuki T. Uehara S. Kakishima H. Ito A. Ishida K. Yoshida S. Mori J. Rabajante S. Morita M. Yokozawa J. Yoshimura
Scientific Reports 5p.153762015-
T. Iizumi M. Okada M. Yokozawa
Journal of Geophysical Research - Atmospheres 119p.363 - 3842014-
M. Okada T. Iizumi M. Yokozawa
Journal of Agricultural Meteorology 70p.13 - 232014-
G. Sakurai T. Iizumi M. Nishimori M. Yokozawa
Scientific Reports 4p.49782014-
T. Iizumi J.J. Luo A.J. Challinor G. Sakurai M. Yokozawa H. Sakuma M.E. Brown T. Yamagata
Nature Communications 2014-
T. Iizumi G. Sakurai M. Yokozawa
Journal of Agricultural Meteorology 70p.73 - 902014-
Y. Kunimitsu T. Iizumi M. Yokozawa
Paddy and Water Environment 12p.213 - 2252014-
A. Kotera N.D. Nguyen T. Sakamoto T. Iizumi M. Yokozawa
Paddy and Water Environment 12p.343 - 3542014-
T. Iizumi Y. Tanaka G. Sakurai Y. Ishigooka M. Yokozawa
Journal of Advances in Modeling Earth Systems 6p.527 - 5402014-
S. Yonemura M. Yokozawa G. Sakurai W.A. Kishimoto-Mo N. Lee S. Murayama K. Ishijima Y. Shirato H. Koizumi
Journal of Forest Research 18p.49 - 592013-
T. Iizumi H. Sakuma M. Yokozawa J.J. Luo A.J. Challinor M.E. Brown G. Sakurai T. Yamagata
Nature Climate Change 3p.904 - 9082013-
T. Iizumi M. Yokozawa G. Sakurai M.I. Travasso V. Romanernkov P. Oettli T. Newby Y. Ishigooka J. Furuya
Global Ecology and Biogeography 23p.346 - 3572013-
T. Iizumi G. Sakurai M. Yokozawa
Journal of Agricultural Meteorology 69p.243 - 2542013-
G. Sakurai M. Jomura S. Yonemura T. Iizumi Y. Shirato M. Yokozawa
Soil Biology and Biochemistry 46p.191 - 1992012-
Y. Masutomi T. Iizumi K. Takahashi M. Yokozawa
Environmental Research Letters 7p.140202012-
S. Suzuki M. Yokozawa K. Inubushi T. Hara M. Kimura S. Tsuga Y. Tako Y. Nakamura
Journal of Hydrometeorology 13p.966 - 9802012-
R. Yoshida T. Iizumi M. Nishimori M. Yokozawa
Geophysical Research Letters 39p.L224012012-
F. Tao Z. Zhang M. Yokozawa
Regional Environmental Change 11p.41 - 482011-
T. Iizumi M. Yokozawa M. Nishimori
Climatic Change 107p.391 - 4152011-
M. Okada T. Iizumi Y. Hayashi M. Yokozawa
Environmental Research Letters 6p.340312011-
T. Iizumi M. Nishimori K. Dairaku S. Adachi M. Yokozawa
Journal of Geophysical Research 116p.D011112011-
G. Sakurai T. Iizumi M. Yokozawa
Climate Research 49p.143 - 1542011-
M. Okada T. Iizumi Y. Hayashi M. Yokozawa
Journal of Agricultural Meteorology 67p.283 - 2932011-
W. Kim J. Cho D. Komori M. Aoki M. Yokozawa S. Kanae T. Oki
Hydrological Research Letters 5p.73 - 772011-
T. Iizumi M. Nishimori M. Yokozawa A. Kotera N.D. Khang
International Journal of Climatology 32p.464 - 4802011-
M. Yokozawa Y. Shirato T. Sakamoto S. Yonemura M. Nakai T. Ohkura
Soil Science and Plant Nutrition 56p.168 - 1762010-
N.D. Khang A. Kotera T. Iizumi T. Sakamoto M. Yokozawa
Journal of Agricultural Meteorology 66p.11 - 212010-
T. Iizumi K. Ishida M. Yokozawa M. Nishimori
Agricultural Information Research 19p.36 - 422010-
T. Iizumi M. Nishimori M. Yokozawa
Journal of Applied Meteorology and Climatology 49p.574 - 5912010-
M. Toda M. Yokozawa S. Emori T. Hara
Ecological Modelling 221p.2887 - 28982010-
T. Iizumi M. Yokozawa M. Nishimori
Agricultural and Forest Meteorology 149p.333 - 3482009-
F. Tao M. Yokozawa J. Liu Z. Zhang
Climatic Change 93p.433 - 4452009-
F. Tao M. Yokozawa Z. Zhang
Agricultural and Forest Meteorology 149p.831 - 8502009-
M. Okada T. Iizumi M. Nishimori M. Yokozawa
Journal of Agricultural Meteorology 65p.97 - 1092009-
S. Yonemura M. Yokozawa Y. Shirato S. Nishimura I. Nouchi
Journal of Agricultural Meteorology 65p.141 - 1492009-
F. Tao Z. Zhang J. Liu M. Yokozawa
Agricultural and Forest Meteorology 149p.1266 - 12782009-
T. Iizumi M. Yokozawa M. Nishimori
Journal of Agricultural Meteorology 65p.179 - 1902009-
T. Sakamoto V.P. Cao A. Kotera N.D. Khang M. Yokozawa
Landscape and Urban Planning 92p.34 - 462009-
T. Sakamoto V.P.Cao A. Kotera N.D. Khang M. Yokozawa
JARQ 43p.173 - 1852009-
M. Toda M. Yokozawa A. Sumida T. Watanabe T. Hara
Ecological Modelling 220p.2272 - 22802009-
M. Okada T. Iizumi Y. Hayashi M. Yokozawa
Journal of Agricultural Meteorology 65p.327 - 3372009-
F. Tao Y. Hayashi Z. Zhang T. Sakamoto M. Yokozawa
Agricultural and Forest Meteorology 148p.94 - 1102008-
T. Iizumi M. Nishimori M. Yokozawa
Journal of Agricultural Meteorology 64p.9 - 232008-
F. Tao M. Yokozawa Y. Hayashi Z. Zhang Y. Ishigooka, 1982-2000
International Journal of Remote Sensing 29p.5461 - 54782008-
T. Iizumi M. Yokozawa Y. Hayashi F. Kimura
Journal of Applied Meteorology and Climatology 47p.2265 - 22782008-
N.D. Khang A. Kotera T. Sakamoto M. Yokozawa
Journal of Agricultural Meteorology 64p.167 - 1762008-
A. Kotera T. Sakamoto N.D. Khang M. Yokozawa
JARQ 42p.267 - 2742008-
F. Tao M. Yokozawa J. Liu Z. Zhang
Climate Research 38p.83 - 942008-
M. Toda M. Yokozawa A. Sumida T. Watanabe T. Hara
Carbon Balance and Management 2(6) 2007-
T. Sakamoto N.D. Khang A. Kotera H. Ohno N. Ishitsuka M. Yokozawa
Remote Sensing of Environment 109p.295 - 3132007-
A. Kotera T. Sakamoto M. Yokozawa
International Journal of Geoinformatics 3p.1 - 82007-
T. Sakamoto N. Van Nhan H. Ohno N. Ishitsuka M. Yokozawa
Remote Sensing of Environment 100p.1 - 162006-
K. Yamamura M. Yokozawa M. Nishimori Y. Ueda T. Yokosuka
Population Ecology 48p.31 - 482006-
Y. Shirato M. Yokozawa
Soil Biology and Biochemistry 38p.812 - 8162006-
S. Suh Y. Chun N. Chae J. Kim J. Lim M. Yokozawa M. Lee J. Lee
Ecological Research 21p.405 - 4142006-
F. Tao M. Yokozawa Y. Xu Y. Hayashi Z. Zhang
Agricultural and Forest Meteorology 138p.82 - 922006-
T. Iizumi ME. Hori M. Yokozawa H. Nakagawa Y. Hayashi F. Kimura
SOLA 2p.156 - 1592006-
F. Yao Y. Xu E. Lin M. Yokozawa
Climatic Change 80p.395 - 4092006-
Y. Shirato K. Paisancharoen P. Sangtong C. Nakviro M. Yokozawa N. Matsumoto
European Journal of Soil Science 56p.179 - 1882005-
F. Tao M. Yokozawa Y. Hayashi E. Lin
Climatic Change 68p.169 - 1972005-
F. Tao M. Yokozawa
Journal of Agricultural Meteorology 60p.885 - 8872005-
F. Tao M. Yokozawa Z. Zhang Y. Xu Y. Hayashi
Ecological Modelling 183p.385 - 3962005-
T. Sakamoto M. Yokozawa H. Toritani M. Shibayama N. Ishizuka H. Ohno
Remote Sensing of Environment 96p.366 - 3742005-
Y. Shirato M. Yokozawa
Soil Science and Plant Nutrition 51p.405 - 4152005-
F. Tao M. Yokozawa
Journal of Agricultural Meteorology 60p.1169 - 11742005-
M. Yokozawa F. Tao T. Sakamoto
Chinese Journal of Agricultural Meteorology 26p.1 - 62005-
T. Watanabe M. Yokozawa S. Emori K. Takata A. Sumida T. Hara
Global Change Biology 10p.963 - 9822004-
M. Yokozawa F. Tao T. Sakamoto
Crop, Environment and Bioinformatics 1p.264 - 2712004-
F. Tao M. Yokozawa Z. Zhang Y. Hayashi H. Grassl H. Fu
Climate Research 28p.23 - 302004-
F. Tao M. Yokozawa Y. Hayashi E. Lin
Agriculture Ecosystems and Environment 95p.203 - 2152003-
M. Yokozawa S. Goto Y. Hayashi H. Seino
Journal of Agricultural Meteorology 59p.117 - 1302003-
F. Tao M. Yokozawa Y. Hayashi E. Lin
Ambio 32p.295 - 3012003-
E. Ranatunge B.A. Malmgren Y. Hayashi T. Mikami W. Morishima M. Yokozawa M. Nishimori
Palaeogeography, Paleoclimatology, Paleoecology 197p.1 - 142003-
F. Tao M. Yokozawa Y. Hayashi E. Lin
Agricultural and Forest Meteorology 118p.251 - 2612003-
T. Nakadai M. Yokozawa H. Ikeda H. Koizumi
Applied Soil Ecology 19p.161 - 1712002-
K. Yamamura M. Yokozawa
Applied Entomology and Zoology 37p.181 - 1902002-
S. Sekikawa H. Koizumi T. Kibe M. Yokozawa T. Nakano S. Mariko
Journal of the Japanese Agricultural Systems Society 18p.44 - 542002-
S. Kamara T. Kuruppuarachchi E.R. Ranatunge Y. Hayashi M. Yokozawa M. Nishimori T. Mikami
Journal of Agricultural Meteorology 58p.171 - 1832002-
T. Kuruppuarachchi E.R. Ranatunge Y. Hayashi M. Yokozawa M. Nishimori
Newsletter of Climate Impacts and Application 19p.39 - 462001-
B. Li T. Shibuya Y. Yogo T. Hara M. Yokozawa
Plant Species Biology 16p.193 - 2072001-
S. Yonemura M. Yokozawa S. Kawashima H. Tsuruta
Tellus B52p.919 - 9332000-
S. Yonemura M. Yokozawa
World Resources Review 12p.149 - 1702000-
S. Mariko N. Nishimura W. Mo Y. Matsui M. Yokozawa S. Sekikawa H. Koizumi
Environmental Science 13p.69 - 742000-
S. Yonemura A. Miyata M. Yokozawa
Atmospheric Environment 34p.5007 - 50142000-
M. Yokozawa T. Hara
Ecological Modelling 118p.61 - 721999-
M. Yokozawa Y. Kubota T. Hara
Ecological Modelling 118p.73 - 861999-
M. Yokozawa
Bulletin of Mathematical Biology 61p.949 - 9611999-
M. Yokozawa Y. Kubota T. Hara
Ecological Modelling 106p.1 - 161998-
Y. Hayashi M. Yokozawa S. Yamakawa H. Toritani
Journal of Agricultural Meteorology 52p.745 - 7481997-
M. Yokozawa Y. Kubota T. Hara
Annals of Botany 78p.437 - 4471996-
M. Yokozawa T. Hara
Annals of Botany 76p.271 - 2851995-
T. Hara M. Yokozawa
Annals of Botany 73p.39 - 511994-
M. Yokozawa T. Hara
Journal of Agricultural Meteorology 48p.827 - 8301993-
M. Yokozawa T. Hara
Annals of Botany 70p.305 - 3161992-
H. Nishimori K. Okamoto M. Yokozawa
Journal of the Physical Society of Japan 56p.4126 - 41331987-
Yonemura S, Kaneda S, Kodama N, Sakurai G, Yokozawa M.
Journal of Agricultural Meteorology Peer Review Yes 2018/12-2018/12
Sakurai, Gen; Yamaji, Naoki; Mitani-Ueno, Namiki; Yokozawa, Masayuki; Ono, Keisuke; Ma, Jian Feng
Frontiers in Plant Science 82017/07-2017/07
Outline:© 2017 Sakurai, Yamaji, Mitani-Ueno, Yokozawa, Ono and Ma. Silicon is the second most abundant element in soils and is beneficial for plant growth. Although, the localizations and polarities of rice Si transporters have been elucidated, the mechanisms that control the expression of Si transporter genes and the functional reasons for controlling expression are not well-understood. We developed a new model that simulates the dynamics of Si in the whole plant in rice by considering Si transport in the roots, distribution at the nodes, and signaling substances controlling transporter gene expression. To investigate the functional reason for the diurnal variation of the expression level, we compared investment efficiencies (the amount of Si accumulated in the upper leaf divided by the total expression level of Si transporter genes) at different model settings. The model reproduced the gradual decrease and diurnal variation of the expression level of the transporter genes observed by previous experimental studies. The results of simulation experiments showed that a considerable reduction in the expression of Si transporter genes during the night increases investment efficiency. Our study suggests that rice has a system that maximizes the investment efficiency of Si uptake.
Nakagawa, Yoshiaki; Yokozawa, Masayuki; Ito, Akihiko; Hara, Toshihiko
Ecological Modelling 361p.95 - 1122017/10-2017/10
ISSN:03043800
Outline:© 2017 Elsevier B.V. Forest gap models (non-spatial, patch- and individual-based models) and size structure models (non-spatial stand models) rely on two assumptions: the mean field assumption (A-I) and the assumption that plants in one patch do not compete with plants in other patches (A-II). These assumptions lead to differences in plant size dynamics between these models and spatially explicit models (or observations of real forests). Therefore, to more accurately replicate dynamics, these models require model tuning by (1) adjusting model parameter values or (2) introducing a correction term into models. However, these model tuning methods have not been systematically and statistically investigated in models using different patch sizes. We used a simple spatially explicit model that simulated growth and competition processes, and rewrote it as patch models. The patch sizes of the patch models were set between 4 and 1500 m 2 . First, we estimated the parameter values (the intrinsic growth rate, metabolic loss, competition coefficient, and competitive asymmetry) of these models that best reproduce plant size growth under competition using field data from a Sakhalin fir stand, and compared the parameter values among the models. Second, we introduced correction terms into the patch models and estimated the optimal correction term for reproducing plant size growth under competition using the field data. The estimated parameter values of the patch models for all patch sizes differed greatly from those of the spatially explicit models. Therefore, parameter values should not be shared between spatially explicit models and patch models. In addition, the parameter value sets for the models with small patches differed from those with large patches. This is because parameter values for small patches mainly improve biases of A-II, while those for large patches mainly improve biases of A-I. Therefore, parameter values should not be shared between patch models with small patches and with large patches. The estimated correction term in the patch models with large patches excluded the competitive effects of small and medium-sized plants on their neighbors, even though these effects exist in real stands. This exclusion can be ascribed to the discrepancy between their competition in real plant populations and A-I. Therefore, the competitive effects of small and medium-sized plants should not be included in patch models with large patches. Finally, the reproducibility of the models tuned with correction terms was higher than those with adjusted parameters.
Yonemura, Seiichiro; Yokozawa, Masayuki; Sakurai, Gen; Kishimoto-Mo, Ayaka W.; Lee, Nayeon; Lee, Nayeon; Murayama, Shohei; Ishijima, Kentaro; Shirato, Yasuhito; Koizumi, Hiroshi; Koizumi, Hiroshi
Journal of Forest Research 18(1) p.49 - 592013/01-2013/01
ISSN:13416979
Outline:At the Takayama deciduous broadleaved forest Asiaflux site in Japan, the ecosystem carbon dynamics have been studied for more than two decades. In 2005, we installed non-dispersive infrared CO 2 sensors in the soil below the site's flux tower to systematically study vertical soil-air CO 2 dynamics and explain the behavior of soil surface CO 2 efflux. Soil-air CO 2 concentrations measured from June 2005 through May 2006 showed sinusoidal variation, with maxima in July and minima in winter, similar to the soil CO 2 effluxes measured simultaneously using open-flow chambers. Soil-air CO 2 concentrations increased with soil depth from 5 to 50 cm: from 2,000 to 8,000 ppm in the summer and from 2,000 to 3,000 ppm in the winter under snow. Summer soil-air CO 2 concentrations were positively correlated with soil moisture on daily and weekly scales, indicating that the Oi, Oe, and A horizons, where decomposition is accelerated by high-moisture conditions, contributed substantially to CO 2 emissions. This result is consistent with the short residence time (about 2 h) of CO 2 in the soil and larger emissions in shallow soil layers based on our diffusion model. We revealed for the first time that soil-air CO 2 concentrations in winter were correlated with both snow depth and wind speed. CO 2 transfer through the snow was hundreds of times the gas diffusion rates in the soil. Our estimate of the CO 2 efflux during the snow-cover season was larger than previous estimates at TKY, and confirmed the important contribution of the snow-cover season to the site's carbon dynamics. © 2012 The Japanese Forest Society and Springer Japan.
Indo-Pacific Climate Variability and Predictability. (eds., Behera K. Yamagata T.)(Sharing writing)
World Scientific Publishing2016-
Responsible Number of Pages:281-304
Morphogenesis and Pattern Formation in Biological Systems. (eds., Sekimura, T., Noji, S., Ueno, N. and Maini, P.K.)(Sharing writing)
Springer-Verlag2003-
Responsible Number of Pages:237-246
Research Classification:
Modeling forest ecosystem responses to environmental change implementing spatial heterogeneity of trees2018/-0-2021/-0
Allocation Class:¥4290000
Research Classification:
Systemic Risk in the World Food Market and Trade Liberalization under Climate Change: Evaluation by the Multi-regional DSGE Model2016/-0-2020/-0
Allocation Class:¥16120000
Research Classification:
Forest determinant factors and the effects of precipitation shift under global climate changeo in Thailand2016/-0-2021/-0
Allocation Class:¥40950000
Research Classification:
Elucidating the impacts of variations in major cereal crop productions due to abnormal weather condition on world food supply, demand and population under malnutrition2014/-0-2018/-0
Allocation Class:¥15600000
Research Classification:
Dynamic study of soil gas exchange2011/-0-2014/-0
Allocation Class:¥20020000
Research Classification:
Vulnerability evaluation on rice production in response to sea-level rise in Vietnam Mekong DeltaAllocation Class:¥10790000
Research Classification:
Long-term durability of carbon sequestration in terrestrial ecosystemsAllocation Class:¥38090000
Research Classification:
Evaluation of soil carbon sequestration in a small basin ecosystemAllocation Class:¥13400000
Research Classification:
Systemic regulation of whole-plant metabolic scaling including roots2015/-0-2018/-0
Allocation Class:¥3900000
2018
Research Results Outline: 流域スケールの作物生産性変動をナウキャスト(作物の生産性を収穫の数ヶ月前に予測)するシステムに組み込むモデルのプロトタイプ開発を行った。対象であるサ 流域スケールの作物生産性変動をナウキャスト(作物の生産性を収穫の数ヶ月前に予測)するシステムに組み込むモデルのプロトタイプ開発を行った。対象であるサトウキビなど糖料作物はバイオマス量よりも植物体に含まれる糖度量の推定が経済的側面から重要であること... 流域スケールの作物生産性変動をナウキャスト(作物の生産性を収穫の数ヶ月前に予測)するシステムに組み込むモデルのプロトタイプ開発を行った。対象であるサトウキビなど糖料作物はバイオマス量よりも植物体に含まれる糖度量の推定が経済的側面から重要であることから、作物の生育環境に応じた糖度特性決定に関するモデル化を行うとともに、JAMSTEC/APLから出力される気象環境データの時間空間分解能の観点からモデルに取り込む素過程の簡略化または高度化を行った。登熟過程に焦点をあてて、環境条件とスクロース貯蔵過程との関係の経験的モデルとして定式化した。そのモデルについて、貯蔵スクロース収量の環境応答を調べた。
Course Title | School | Year | Term |
---|---|---|---|
Basic Seminar I | School of Human Sciences | 2020 | spring semester |
Basic Seminar I | School of Human Sciences | 2020 | spring semester |
Introduction to Human Sciences | School of Human Sciences | 2020 | fall quarter |
Introduction to Human Sciences | School of Human Sciences | 2020 | fall quarter |
Basic Ecology | School of Human Sciences | 2020 | fall semester |
Agricultural Meteorology | School of Human Sciences | 2020 | spring semester |
Eco-Informatics | School of Human Sciences | 2020 | an intensive course(spring) |
Seminar I(Arable Land environment) | School of Human Sciences | 2020 | spring semester |
Seminar II (Arable Land environment) | School of Human Sciences | 2020 | fall semester |
Introduction to Human Sciences | School of Human Sciences (Online Degree Program) | 2020 | summer quarter |
Agricultural Meteorology | School of Human Sciences (Online Degree Program) | 2020 | fall semester |
Arable Land Environment | Graduate School of Human Sciences | 2020 | spring semester |
Arable Land Environment | Graduate School of Human Sciences | 2020 | fall semester |
Arable Land Environment(1) | Graduate School of Human Sciences | 2020 | spring semester |
Arable Land Environment(1) | Graduate School of Human Sciences | 2020 | fall semester |
Arable Land Environment(2) | Graduate School of Human Sciences | 2020 | spring semester |
Arable Land Environment(2) | Graduate School of Human Sciences | 2020 | fall semester |
Ecological Modelling | Graduate School of Human Sciences | 2020 | summer quarter |
Agri-Informatics | Graduate School of Human Sciences | 2020 | an intensive course(spring) |
Arable Land Environment(D) A | Graduate School of Human Sciences | 2020 | spring semester |
Arable Land Environment(D) B | Graduate School of Human Sciences | 2020 | fall semester |