Сибирское отделение РАН 
Институт цитологии и генетики

Первое международное рабочее совещание "Биоразнообразие и динамика экосистем Северной Евразии: информационные технологии и моделирование" (WITA-2001)

9-14 июля 2001 года, Новосибирск, Россия

Тезисы докладов

Эволюция видов и экосистем: теоретический анализ и моделирование

Analysis of microbial interactions in forest soil.

Krivtsov V.1*, K. Liddell1, R. Salmond1, A. Garside1, J. Thompson1, T. Bezginova1, B. Griffiths2, H.J Staines1, R. Watling3 and J.W. Palfreyman1.

School of Science & Engineering,
University of Abertay Dundee,

Mutivariate interactions between microorganisms and their interrelations with other ecosystem components are highly complex (Griffiths & Bardgett, 1998). However, the understanding of these relationships is indispensable for sustainable environmental management. To enhance this understanding, detailed monitoring programmes should be combined with advanced numerical analysis (e.g. ANOVA, ANCOVA, factor analysis, and mathematical modelling). Here we report on the progress of an ongoing research programme (including monitoring fungi, bacteria, protozoa, total microbial biomass & nutrient content, nematodes, soil pH, moisture and organic content, forest litter production & decomposition, etc.) designed to study the ecosystem dynamics in a Scottish woodland. Statistical analysis of the monitoring data set showed that in winter 2000/2001 the dynamics of all the microbiota was affected by physical factors, particularly by seasonal changes in temperature and moisture content. Superimposed on these effects, however, was variability due to microbial interactions and habitat characteristics. The importance of the latter factors was especially evident in stepwise regression models. For example, ergosterol (a proxy for total fungal biomass) was shown to be significantly related to soil organic content, bacteria, and soil pH (with the total variance explained increasing as follows: 38.79, 45.63, and 51.81 %), while the biomass of arbuscular mycorrhizal fungi (measured as glomalin) was shown to be significantly related only to soil organic content (R2=65.6). Amoebae were shown to be significantly related to microbial feeding nematodes, pH and protozoan flagellates (with the total variance explained increasing as follows: 75.12, 79.58 and 81.5%). The model for flagellates, however, returned only one weak predictor - bacteria (R2=18.49). The highest number of predictors were revealed for bacteria abundance, which was shown to be related to the total fungal biomass, plant feeding nematodes, soil organic content, pH and amoebae (with the total variance explained increasing as follows: 30.86, 50.57, 56.44, 63.78 and 68.99%). These results highlighted interdependency of the dynamics of different microbial groups, as well as their interrelations with abiotic ecosystem components. The data are now being modelled using a system of differential equations, with the most important ecosystem components represented as separate compartments. It is expected that this dynamic simulation model together with the results of statistical analysis will allow further insight into complex interactions among ecosystem components (sensu Krivtsov et al., 2000). The latter will be useful for management of the site, and may have profound implications for ecological theory in general. References:

Griffiths, B.S. and Bardgett, R.D. 1998 Interactions Between Microbe-Feeding Invertebrates and Soil Microorganisms. In Modern soil microbiology (van Elsas J.D, Trevors, J.T. & Wellington, E.M.H eds.). Marcel Dekker, New York, pp. 165-182.

Krivtsov, V., Corliss,J., Bellinger, E., Sigee, D. (2000). Indirect Regulation Rule for Consecutive Stages of Ecological Succession. Ecological Modelling 133/1-2, 73-81.

Примечание. Тезисы докладов публикуются в авторской редакции

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