[海狸(Castor fiber L.)生命活动引起的演替:1 .从一个简单马尔可夫模型的校准中学到的东西]。

Pub Date : 2014-03-01
D O Logofet, O I Evstigneev, A A Aleĭnikov, A O Morozova
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引用次数: 0

摘要

提出了一个由“池塘-沼泽-森林”三种聚集状态组成的均匀马尔可夫链作为森林生物地群落中海狸(Castor fiber L.)生命活动引起的动物演替循环模型。为了校准链过渡矩阵,从2002-2008年在“Bryanskii Les”保护区进行的实地研究中获得的数据似乎已经足够。校准模型的主要结果来自有限齐次马尔可夫链理论的公式:状态的平稳概率分布,平均首次通过时间的矩阵(T)和演替阶段的平均持续时间(M(j))。前者描述了在长期保持当前演替趋势和演替过渡速率的情况下,演替阶段下相对面积的分布,与观测分布较为接近。矩阵T提供了循环过程的定量特征,指定了专家在演替概念方案中提出的阶段持续时间的范围。M(j)的计算值检测经验数据、总结数据的专家知识和数学模型中接受的假设之间的潜在差异。计算出的M2值落在专家范围之外,这使得人们有理由怀疑所提出的专家估计的有效性,对链状态选择的聚合模式,或/和可用数据的准确性,即从部分成功的校准中吸取某些“教训”。本文还讨论了拒绝假设链的时间同质性或马尔可夫性质的可能改进方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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[Succession caused by beaver (Castor fiber L.) life activity: I. What is learnt from the calibration of a simple Markov model].

A homogeneous Markov chain of three aggregated states "pond--swamp--wood" is proposed as a model of cyclic zoogenic successions caused by beaver (Castor fiber L.) life activity in a forest biogeocoenosis. To calibrate the chain transition matrix, the data have appeared sufficient that were gained from field studies undertaken in "Bryanskii Les" Reserve in the years of 2002-2008. Major outcomes of the calibrated model ensue from the formulae of finite homogeneous Markov chain theory: the stationary probability distribution of states, thematrix (T) of mean first passage times, and the mean durations (M(j)) of succession 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 has appeared close to the observed distribution. Matrix T provides for quantitative characteristics of the cyclic process, specifying the ranges the experts proposed for the duration of stages in the conceptual scheme of succession. The calculated values of M(j) 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 outside the expert range, which gives a reason to doubt the validity of expert estimation proposed, the aggregation mode chosen for chain states, or/and the accuracy-of data available, i.e., to draw certain "lessons" from partially successful calibration. Refusal to postulate the time homogeneity or the Markov property of the chain is also discussed among possible ways to improve the model.

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