Institute for Agro-Environmental Sciences, NARO

Statistical Modeling Unit

Accurate prediction and decision making based on the analysis of statistical data and mathematical modeling are necessary at each stage of agricultural production, experimental research, and policy making. Remarkable results have been produced in the agricultural research field by using various statistical and mathematical methods over the years. In recent years, the need to develop new theories and methods based on large and complex data is increasing, hence it is necessary to promote fundamental research that can meet the expectation. At the same time, to address specific issues utilizing various data related to the agro-environmental change is also crucial.
The work of Statistical Modeling Unit covers a wide range of research areas from basic theories to practical applications. For instance, we develop statistical methods to estimate and visualize potential distribution of certain species by weighting based on the relative value of each data and integrally using various kinds of geographical information, such as data of location where the species were found and meteorological data of the place. We also develop methods for presuming and predicting the agricultural productivity index while ensuring the validity of estimates obtained from biophysical models by using various types of data such as Agricultural census data, weather data, and data from soil and biophysics in an integrated manner. In addition, we aim to provide the research results to a wide range of end users in communities of researchers, the sites of agricultural experiment, and the administrative organs through statistics training and consulting at national and prefectural research institutes where many long-term researches have been carried out.

Unit Leader

Research Topics :Population ecology, Statistics

Unit Members

Research Topics
Kunio TAKEZAWA Principal Researcher Statistical inference
Takehiko YAMANAKA Principal Researcher Population ecology, Conservation biology
Gen SAKURAI Researcher Ecological theory and Bayesian modeling
Nobuhiro MINAKA Re-employed Staff Systematic biology, Phylogenetic theory

Research Publications

  • Iizumi, T., Luo, J., Challinor, A.J., Sakurai, G., Yokozawa, M., Sakuma, H., Brown, M.E. and Yamagata, T. 2014. Impacts of El Nino Southern Oscillation on the global yields of major crops. Nature Communications 5: 3712. doi:10.1038/ncomms4712
  • Liebhold, A. M., Berec, L., Brockerhoff, E. G., Epanchin-Niell, R. S., Hastings, A., Herms, D. A., Kean, J. M., McCullough, D. G., Suckling, D. M., Tobin, P. C. and Yamanaka, T.2016. Eradication of invading insect populations: from concepts to applications. Annual Review of Entomology, 61: 335-352. doi:10.1146/annurev-ento-010715-023809
  • Nobuhiro Minaka 2016. Chain, Tree, and Network: The Development of Phylogenetic Systematics in the Context of Genealogical Visualization and Information Graphics. Pp. 410-430 in: David M. Williams, Michael Schmitt, and Quentin D. Wheeler (eds.), The Future of Phylogenetic Systematics -The Legacy of Willi Hennig. Cambridge University Press, Cambridge. ISBN:978-1-107-11764-8
  • Yuki Mitsui, Michihiko Shimomura, Kenji Komatsu, Nobukazu Namiki, Mari Shibata-Hatta, Misaki Imai, Yuichi Katayose, Yoshiyuki Mukai, Hiroyuki Kanamori, Kanako Kurita, Tsutomu Kagami, Akihito Wakatsuki, Hajime Ohyanagi, Hiroshi Ikawa, Nobuhiro Minaka, Kunihiro Nakagawa, Yu Shiwa and Takuji Sasaki 2015. The radish genome and comprehensive gene expression profile of tuberous root formation and development. Scientific Reports, 5: 10835; doi:10.1038/srep10835
  • Nelson, W. A., Bjornstad, O. N. and Yamanaka, T. 2013. Recurrent insect outbreaks caused by temperature-driven changes in system stability. Science, 341: 796-799. doi:10.1126/science.1238477
  • Sakurai, G., Iizumi, T., Nishimori, M., and Yokozawa, M. 2014. How much has the increase in atmospheric CO2 directly affected past soybean production.Scientific Reports, 4: 4978. doi:10.1038/srep04978
  • Kunio Takezawa2014. Learning Regression Analysis by Simulation. Springer-Verlag, Tokyo. ISBN:978-4-431-54321-3
  • Kohji Yamamura2016. Bayes estimates as an approximation to maximum likelihood estimates. Population Ecology, 58: 45-52. doi:10.1007/s10144-015-0526-x
  • Kohji Yamamura2016. Estimation of the predictive ability of ecological models. Communications in Statistics-Simulation and Computation, 45: 2122-2144. doi:10.1080/03610918.2014.889161
  • Kohji Yamamura, Hajime Katsumata, Junji Yoshioka, Tatsuya Yuda and Kenji Kasugai 2016. Sampling inspection to prevent the invasion of alien pests: Statistical theory of import plant quarantine systems in Japan. Population Ecology, 58: 63-80. doi:10.1007/s10144-015-0521-2
  • Yamaji, N., Sakurai, G., Mitani-Uenoa, N., and Ma, J.F. 2015. Orchestration of three transporters and distinct vascular structures in node for intervascular transfer of silicon in rice. Proceedings of the National Academy of Sciences, U. S. A., 112(36) 11401-11406. doi:10.1073/pnas.1508987112
  • Yamanaka, T., Morimoto, N., Nishida, G. M., Kiritani, K., Moriya, S. and Liebhold, A. M. 2015. Comparison of Insect Invasions in North America, Japan and their Islands. Biological Invasions, 17: 3049-3061. doi:10.1007/s10530-015-0935-y