Modelling the Impact of Human Population and Its Associated Pressure on Forest Biomass and Forest-Dependent Wildlife Population

Ibrahim M. Fanuel, Damian Kajunguri, F. Moyo
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引用次数: 3

Abstract

Mathematical models have been widely used to explain the system originating from human-nature interaction, investigate the impacts of various components, and forecast system behaviour. This paper provides a profound reference to the current state of the art regarding the application of mathematical models to study the impact of human population and population pressure on forest biomass and forest-dependent wildlife. The review focused on two aspects, namely, model formulation and model analysis. In model formulation, the review revealed that socioeconomic status influences forest resource consumption patterns, thus, stratification of the human population based on economic status is a critical phenomenon in modelling human-nature interactions; however, this component has not been featured in the reviewed models. Regarding model analysis, in most of the reviewed work, single parameter approach was utilized to perform uncertainty quantification of the model parameter; this approach has been proven to be inadequate in measuring the uncertainty and sensitivity of the parameter. Thus, the use of correlation or variance based methods, which are multidimensional parameter space methods are of significant importance. Generally, despite the limitations of many assumptions in mathematical modelling, it is revealed that mathematical models demonstrate the ability to handle complex systems originating from interactions between humans and nature.
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模拟人口及其相关压力对森林生物量和依赖森林的野生动物种群的影响
数学模型已被广泛用于解释源于人与自然相互作用的系统,研究各组成部分的影响,并预测系统行为。本文对利用数学模型研究人口和人口压力对森林生物量和依赖森林的野生动物的影响的现状提供了深刻的借鉴。本文主要从模型制定和模型分析两个方面进行综述。在模型制定方面,综述表明,社会经济地位影响森林资源消费模式,因此,基于经济地位的人口分层是模拟人与自然相互作用的关键现象;然而,这个组件并没有在审查的模型中出现。在模型分析方面,在大多数综述工作中,采用单参数方法对模型参数进行不确定性量化;这种方法已被证明在测量参数的不确定度和灵敏度方面是不够的。因此,使用基于相关或方差的多维参数空间方法具有重要意义。一般来说,尽管数学建模中的许多假设存在局限性,但数学模型显示出处理源自人与自然相互作用的复杂系统的能力。
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