Plenary talks

Wednesday, Sep. 7

Time 14:00 - 15:00, Sep. 7
Room D

Professor Mark Rees

Department of Animal and Plant Sciences, Sheffield University, England

Evolutionary Demography an Integral Projection Approach

Integral projection models (IPMs) project a continuously structured population, where say individuals are characterized by their size, in discrete time. An overview of the application of IPMs to field populations will be given covering 1) model parameterization in both constant and stochastic environments, 2) populations where multiple traits influence an individual’s fate (e.g. size and age), and 3) density dependence. The use IPMs to understand the evolution of traits in natural populations will then be explored. In these IPMs individuals are characterized by traits that vary over the organism’s life, such as size and age, and invariant traits, such as genotype or breeding value. Methods of approximating the dynamics of both the mean and variance of the genotype/breeding value distribution will be presented. Methods for embedding quantitative genetics models into IPMs will be presented and used to explore the timing of reproduction in two plant populations. These models will be used to explore the maintenance of genetic variability in natural populations.

Time 15:00 - 16:00, Sep. 7
Room D

Professor Miles Davenport

Centre for Vascular Research, University of New South Wales, Sydney, Australia

Modeling “latent” Infection

When we think of infection, we usually think of active replication of a virus or parasite, causing illness. However, some infections can lie sleeping (latent) for many years before they re-activate to cause a new active infection. Understanding how infections become latent, and how they reactivate from latency, is important to controlling infection. Because it is not easy to measure the latent (sleeping) infection, modeling is needed to study how infection reactivates. This talk will discuss modeling applied to experimental data from patient and animal studies to better understand the dynamics of latency in HIV infection.


  1. Pinkevych M, Cromer D, Tolstrup M, Grimm AJ, Cooper DA, Lewin SR, Søgaard OS, Rasmussen TA, Kent SJ, Kelleher AD, Davenport MP.HIV Reactivation from Latency after Treatment Interruption Occurs on Average Every 5-8 Days--Implications for HIV Remission.PLoS Pathog. 2015 Jul 2;11(7):e1005000.
  2. Reece J, Petravic J, Balamurali M, Loh L, Gooneratne S, De Rose R, Kent SJ, Davenport MP.An "escape clock" for estimating the turnover of SIV DNA in resting CD4 T cells.PLoS Pathog. 2012;8(4):e1002615.

Award lectures

Thursday, Sep. 8

Time 15:45 - 17:15, Sep.8
Room D

Dr. Takeshi Kano

Research Institute of Electrical Communication

Toward Understanding of the Decentralized Control Mechanism Underlying Adaptive Locomotion of Animals

In this presentation, I talk about my research activities up to now, mainly focusing on the decentralized control mechanism underlying animal locomotion.

Animals exhibit adaptive, versatile, and resilient locomotion under unpredictable and unstructured real- world constraints. They achieve such movements by successfully coordinating many points along their bodies, each of which has some degrees of freedom, even though their computational resources are limited. A key mechanism for the coordination of many body points is an autonomous decentralized control, whereby the non-trivial macroscopic behavior or functionality of an entire system emerges through the coordination of simple individual components. In fact, several biological findings indicate that animal locomotion depends on autonomous decentralized control mechanisms such as biochemical oscillators in true slime molds [1] and central pattern generators (CPGs) found in many animals [2].

We are trying to understand the decentralized control mechanism of various animals by using a synthetic approach: we propose a mathematical model based on the observation of real animals, and then we implement the propose mechanism in a robot to reproduce the locomotion of real animals. I introduce our recent results based on this approach, particularly focusing on the locomotion of snakes and ophiuroids [3,4].


  1. Takamatsu, A., Tanaka, R., Yamada, H., Nakagaki, T., Fujii, T., and Endo, I., 2001. Spatio-temporal Symmetry in Rings of Coupled Biological Oscillators of Physarum Plasmodium, Phys. Rev. Lett., 87: 078102.
  2. Ijspeert, A.J., 2008. Central Pattern Generators for Locomotion Control in Animals and Robots: A Review, Neural Networks, 21: 642–653.
  3. Kano, T., Sato, T., Kobayashi, R., and Ishiguro, A., 2012. Local Reflexive Mechanisms Essential for Snakes' Scaffold-based Locomotion, Bioinsp. Biomim., 7: 046008.
  4. Kano, T., Sato, E., Aonuma, H., Matsuzaka, Y., and Ishiguro, A., 2014. Mathematical Model of Inter-arm Coordination Mechanism of Ophiuroids, JSMB/SMB 2014.

Time 16:15 - 16:45, Sep.8
Room D

Dr. Yukihiko Nakata

Department of Mathematics, Shimane University

Analysis and applications of delay equations in mathematical epidemiology

Mathematical description of disease transmission dynamics often yields a nonlinear infinite- dimensional dynamical system ([1]). Many important mathematical theories for infectious diseases dynamics have been developed [2]. However, the waning immunity is a major challenge for mathematical modeling and analysis. We present our recent studies for epidemiological models with waning immunity [3]. Here we also discuss delay equation formulation in the spirit of Lotka’s renewal equation. We then introduce an application of delay differential equations for modeling periodical outbreak of a childhood disease [4].


  1. W.O. Kermack, A.G. McKendrick, A contribution to the mathematical theory of epidemics. Proc. R. Soc. Lond. B Biol. Sci. 115 (1927) 700-721
  2. O. Diekmann, H. Heesterbeek, and T. Britton, Mathematical tools for understanding infectious disease dynamics. Princeton University Press, (2012)
  3. Y. Nakata, Y. Enatsu, H. Inaba, T. Kuniya, Y. Muroya, Y. Takeuchi, Stability of epidemic models with waning immunity. SUT J. Math. Vol. 50, No. 2 (2014), 205–245
  4. R. Omori, Y. Nakata, H. L. Tessmer, S. Suzuki, K. Shibayama, The determinant of periodicity in Mycoplasma pneumoniae incidence: an insight from mathematical modelling. Scientific Reports 5, 14473 (2015)

Time 16:45 - 17:15, Sep.8
Room D

Dr. Takeshi Miki

Institute of Oceanography, National Taiwan University. Research Center for Environmental Changes, Academia Sinica

Multiple modeling approaches for better understanding the roles of microbial diversity in community and ecosystem dynamics.

Microbial diversity in natural environments had been not observable for long time but microbial ecology and environmental microbiology have identified microbial diversity in the last two decades. General ecology also has just started investigating in-situ roles of microbial diversity, not only for using microbial community as model system. Major research interests include the roles of microbial community and diversity as the determinant of fitness of other organisms and their diversity through interactions, e.g, those between microbes and plants, their impacts on ecosystem functions (i.e. biogeochemical processes such as carbon and nutrient cycling), and community and ecoststem stability. In this presentation, after briefly summarizing my past studies on the roles of microbial community (bacteria and fungi) in plant-soil feedback in terrestrial ecosystems, I’m going to talk on recent achievements and developing ideas for better understanding the roles of bacterial diversity in ecosystem functions and their stability.

With a series of mathematical models, we have investigated the roles of microbes in the plant-soil feedback system where plant community alters soil abiotic and biotic environment that in turn affects plant growth, competition, and thus community and ecosystem dynamics. A model of two plant-two microbe species coupled with nutrient cycling demonstrated the roles of microbial diversity in buffering species- specific plant control on soil environments, and thus maintaining plant coexistence [1]. The buffering effect was later supported by the microcosm experiment. A model of the stage-structured plant population coupled with two distinct microbial functional groups (parasitic and mutualistic ones) demonstrated that different plant traits are the key determinants of plant fitness under the dominance of parasitic or mutualistic microbes, which could also explain the empirical pattern [2]. We have also reviewed the past achievement in the field of plant-soil feedback from the point of mathematical modeling [3].

For better understanding the roles of bacterial diversity in the maintenance of ecosystem functioning in aquatic ecosystems, we are developing an integrated framework that combines comparative genomic analysis, microcosm experiments, and model simulations [4]. The key index to predict the decline of ecosystem functionality due to species loss is called ‘functional redundancy’, i.e., how many functions are shared by coexisting species within a community. Our new approach succeeded in evaluating the functional redundancy through species loss simulation using whole genome information of bacteria, which can quantitatively explain the results from microcosm experiments. On-going study extends this framework for developing new indices to predict functional stability of ecosystem, as well as the magnitude of ecosystem functions. Finally, I will briefly address the importance of developing new statistical methods to quantify microbial functions, which will be the main topic in my presentation at the mini symposium “Mathematical and statistical modeling to bridge the gap between empirical and theoretical research in ecology” on Sep. 9.


  1. T. Miki*, Masayuki Ushio, Shin Fukui, Michio Kondoh. (2010) Functional diversity of microbial decomposers facilitates plant coexistence in a plant-microbe-soil feedback model. Proceedings of the National Academy of Sciences, USA 107:14251-14256
  2. Po-Ju Ke, Takeshi Miki*, Tzung-Su Ding (2015) The soil microbial community predicts the importance of plant traits in plant- soil feedback. New Phytologist DOI: 10.1111/nph.13215
  3. Po-Ju Ke*, Takeshi Miki (2015) Incorporating the soil environment and microbial community into plant competition theory. frontiers in Microbiology
  4. Takeshi Miki, Taichi Yokokawa, Kazuaki Matsui* (2014) Biodiversity and multifunctionality in a microbial community: a novel theoretical approach to quantify functional redundancy. Proceedings of The Royal Society B vol.281 no.1776 20132498