Succession Caused by Beaver (Castor fiber L.) Activity: I. What Is Learnt from the Calibration of a Simple Markov Model

Logofet, D.O.; Evstigneev, O.I.; Aleinikov, A.A.; Morozova, A.O.

Статья опубликована в журнале из списка RSCI Web of Science

Информация о цитировании статьи получена из Web of Science
Статья опубликована в журнале из перечня ВАК
Статья опубликована в журнале из списка Web of Science и/или Scopus
Дата последнего поиска статьи во внешних источниках: 4 сентября 2019 г.

Авторы: Logofet D.O., Evstigneev O.I., Aleinikov A.A., Morozova A.O.
Журнал: ЖУРНАЛ ОБЩЕЙ БИОЛОГИИ
Том: 5
Номер: 1
Год издания: 2015
Издательство: ФГБУ "Издательство "Наука"
Местоположение издательства: Москва
Первая страница: 28
Последняя страница: 35
DOI: 10.1134/S2079086415010053
Аннотация: A homogeneous Markov chain of three aggregated states, “pond–swamp—forest,” is proposed as a model of cyclic zoogenic successions caused by beaver (Castor fiber L.) activity in a forest biogeocoenosis. The data obtained from field studies undertaken in the “Bryanskii Les” Reserve in 2002–2008 proved to be sufficient for calibrating the chain transition matrix. With the use of the formulas of finite homogeneous Markov chain theory, the main results for calibration of a model were obtained: the stationary probability distribution of chain states, the matrix (T) of mean first passage times, and the mean durations (Mj) of successional stages. The former illustrates the distribution of relative areas under succession stages if the current trends and transition rates of succession are conserved in the long term—it appeared to be close to the observed distribution. Matrix T provides the quantitative characteristics of the cyclical process by specifying the ranges proposed by the experts for the duration of stages in the conceptual scheme of succession. The calculated values of Mj detect potential discrepancies between empirical data, the expert knowledge that summarizes the data, and the postulates accepted in the mathematical model. The calculated M2 value falls out side the expert range, which gives a reason to doubt the validity of the proposed expert estimation, the aggregation mode chosen for chain states, and/or the accuracy of data available, that is, to draw certain “lessons” from partially successful calibration. Disaggregation of aggregated vegetation states, refusal to postulate the time homogeneity, and refusal of the Markov property of the chain are also discussed among possible ways to improve the model.
Добавил в систему: Евстигнеев Олег Иванович

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Succession Caused by Beaver (Castor fiber L.) Activity: I. What Is Learnt from the Calibration of a Simple Markov Modelстатья

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