Patterns of Land Degradation in Drylands
Patterns of Land Degradation in Drylands
复制标题
旱地土地退化模式
DOI：
10.1007/978-94-007-5727-1_10
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Brazier R
中科院分区：
文献类型：
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作者：
Brazier R
一些传统的关注以及对科学理解的外部压力导致了对不确定性的低估。土地退化研究绝不是唯一一个假定不确定性问题如果被忽视，它就会消失的研究。我们证明，这种“一头扎进沙子”的方法是错误的，因为不确定性支撑着我们所有的科学活动。实地测量和经验观察不亚于复杂的数值模型。不确定性可以被区分为偶然的，或由于固有的可变性，或认识的，作为不确定知识的结果，尽管在现实中这两种类型是密切相关的。模型参数反映了学科中的基础概念模型，当这些概念模型发生变化时，参数测量也可能需要变化。然而，考虑到测量中的所有可变性来源是至关重要的，以确保我们不会因为错误的原因而拒绝模型。提出了一种结构，用于解决模型中的不确定性传播，使用区间，模糊隶属函数和概率分布与随机模拟。模型结构的不确定性的影响被认为是在各种贝叶斯框架内，其相对优势和弱点解决。如果我们要建立一个把生态地貌反馈和人类活动结合起来的健全的土地退化模型，就必须考虑到不确定性的所有方面。
A number of traditional concerns as well as outside pressures on scientific understanding have led to the underplaying of uncertainty. Land-degradation studies are by no means alone in assuming that if the problem of uncertainty is ignored, it will go away. We demonstrate that such a head-in-the-sand approach is fallacious, as uncertainty underpins all our scientific activity. Field measurements and empirical observations are no less exempt than complicated numerical models. Uncertainty can be distinguished as being aleatory, or due to inherent variability, or epistemic, as a result of uncertain knowledge, although in reality both types are intimately related. Model parameters reflect the underpinning conceptual models in a discipline, and as those conceptual models change, parameter measurements may also need to change. Taking account of all of the sources of variability in measurement is critical, though, in ensuring that we do not reject models for the wrong reasons. A structure is presented for addressing uncertainty propagation in models using intervals, fuzzy membership functions and probability distributions in conjunction with stochastic simulation. The effects of model structural uncertainty are considered within a variety of Bayesian frameworks, and their relative strengths and weaknesses addressed. All aspects of uncertainty must be considered if we are to develop robust models of land degradation that incorporate ecogeomorphic feedbacks and human activity.