Population Dynamics of Nitrifying Bacteria in an Aquatic Ecosystem.

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  • Kubo Yoshiko
    Department of Information and Computer Sciences, Nara Women's University, Kita-Uoya Nishimachi, Nara 630-8506, Japan
  • Takasu Fugo
    Department of Information and Computer Sciences, Nara Women's University, Kita-Uoya Nishimachi, Nara 630-8506, Japan
  • Shimura Ryuji
    Advanced Engineering Services Co., Ltd., Takezono, Tsukuba, Ibaraki 305-0032,Japan
  • Nagaoka Shunji
    Department of Physiology , Fujita Health UniversitySchool of Health Sciences, Toyoake, Aichi 470-1192, Japan
  • Shigesada Nanako
    Department of Information and Computer Sciences, Nara Women's University, Kita-Uoya Nishimachi, Nara 630-8506, Japan

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In a space environment such as Space Shuttle or Space Station, animal experiments with aquatic species in a closed system pose a crucial problem in maintaining their water quality for a long term. In nature, ammonia as an animal wastes is converted by nitrifying bacteria to nitrite or nitrate compounds, which usually become nitrogen sources for plants. Thus an application of the biological reactor with such bacteria attached on some filters has been suggested and experimentally studied for efficient waste managements of ammonia. Although some successful results were reported (Kozu et al. 1995, Nagaoka et al. 1998, Nakamura et al. 1997, 1998) in the space applications, purely empirical approaches have so far been taken to develop a biological filter having a stable nitrifying activity. In this study, we constructed a mathematical model to deal with the dynamics of the ammonia nitrifying processes in a biological reactor. The model describes population dynamics of the ammonia-oxidizing bacteria and the nitrite-oxidizing bacteria cultivated on the same filter. We estimated parameters involved in the model using the experimental data. The result shows that these estimated parameters could be applied to general cases and that the two bacteria are in a symbiotic relationship; they can better perform when both coexist, as has been empirically recognized. Based on the model analysis, we discuss how to prepare a high performance biological filter.

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