[Succession caused by beaver (Castor fiber L.) life activity: II. A refined Markov model].

Pub Date : 2015-03-01
Logofet, O I Evstigneev, A A Aleinikov, A O Morozova
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引用次数: 0

Abstract

The refined Markov model of cyclic zoogenic successions caused by beaver (Castor fiber L.) life activity represents a discrete chain of the following six states: flooded forest, swamped forest, pond, grassy swamp, shrubby swamp, and wet forest, which correspond to certain stages of succession. Those stages are defined, and a conceptual scheme of probable transitions between them for one time step is constructed from the knowledge of beaver behaviour in small river floodplains of "Bryanskii Les" Reserve. We calibrated the corresponding matrix of transition probabilities according to the optimization principle: minimizing differences between the model outcome and reality; the model generates a distribution of relative areas corresponding to the stages of succession, that has to be compared to those gained from case studies in the Reserve during 2002-2006. The time step is chosen to equal 2 years, and the first-step data in the sum of differences are given various weights, w (between 0 and 1). The value of w = 0.2 is selected due to its optimality and for some additional reasons. By the formulae of finite homogeneous Markov chain theory, we obtained the main results of the calibrated model, namely, a steady-state distribution of stage areas, indexes of cyclicity, and the mean durations (M(j)) of succession stages. The results of calibration give an objective quantitative nature to the expert knowledge of the course of succession and get a proper interpretation. The 2010 data, which are not involved in the calibration procedure, enabled assessing the quality of prediction by the homogeneous model in short-term (from the 2006 situation): the error of model area distribution relative to the distribution observed in 2010 falls into the range of 9-17%, the best prognosis being given by the least optimal matrices (rejected values of w). This indicates a formally heterogeneous nature of succession processes in time. Thus, the refined version of the homogeneous Markov chain has not eliminated all the contradictions between the model results and expert knowledge, which suggests a further model development towards a "logically inhomogeneous" version or/and refusal to postulate the Markov property in the conceptual scheme of succession.

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[2]海狸(Castor fiber L.)生命活动引起的演替:一个改进的马尔可夫模型]。
由海狸(Castor fiber L.)生命活动引起的循环动物演替的精细马尔可夫模型表现为洪水林、沼泽林、池塘、草地沼泽、灌木沼泽和潮湿森林6种状态的离散链,它们对应于演替的特定阶段。对这些阶段进行了定义,并根据对“Bryanskii Les”保护区小河漫滩海狸行为的了解,构建了一个时间步之间可能过渡的概念方案。我们根据优化原则校准了相应的转移概率矩阵:最小化模型结果与现实之间的差异;该模型生成了与演替阶段相对应的相对区域分布,必须将其与2002-2006年在保护区进行的案例研究所得的分布进行比较。选择时间步长为2年,并将差值和中的第一步数据赋予不同的权重w(0到1之间)。选择w = 0.2的值是由于其最优性和一些其他原因。利用有限齐次马尔可夫链理论公式,得到了校正模型的主要结果,即演替阶段面积、循环度指数和演替阶段平均持续时间(M(j))的稳态分布。校正结果使演替过程的专家知识具有了客观的定量性质,并得到了合理的解释。2010年的数据没有参与校准过程,可以在短期内(从2006年的情况来看)评估同质模型的预测质量:模型面积分布相对于2010年观测到的分布的误差在9-17%之间,最佳预测是由最小的最优矩阵(w的拒绝值)给出的,这表明演替过程在时间上具有正式的异质性。因此,齐次马尔可夫链的精炼版本并没有消除模型结果和专家知识之间的所有矛盾,这表明模型进一步发展到“逻辑非齐次”版本或/和拒绝在继承的概念方案中假设马尔可夫性质。
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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