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首页> 外文期刊>Landscape Ecology >An ecological classification of forest landscape simulation models: tools and strategies for understanding broad-scale forested ecosystems
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An ecological classification of forest landscape simulation models: tools and strategies for understanding broad-scale forested ecosystems

机译:森林景观模拟模型的生态分类:了解大规模森林生态系统的工具和策略

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摘要

Computer models are increasingly being used by forest ecologists and managers to simulate long-term forest landscape change. We review models of forest landscape change from an ecological rather than methodological perspective. We developed a classification based on the representation of three ecological criteria: spatial interactions, tree species community dynamics, and ecosystem processes. Spatial interactions are processes that spread across a landscape and depend upon spatial context and landscape configuration. Communities of tree species may change over time or can be defined a priori. Ecosystem process representation may range from no representation to a highly mechanistic, detailed representation. Our classification highlights the implicit assumptions of each model group and helps define the problem set for which each model group is most appropriate. We also provide a brief history of forest landscape simulation models, summarize the current trends in methods, and consider how forest landscape models may evolve and continue to contribute to forest ecology and management. Our classification and review can provide novice modelers with the ecological context for understanding or choosing an appropriate model for their specific hypotheses. In addition, our review clarifies the challenges and opportunities that confront practicing model users and model developers..
机译:森林生态学家和管理者越来越多地使用计算机模型来模拟森林的长期景观变化。我们从生态学而不是方法论的角度审视森林景观变化模型。我们基于三种生态标准的表示制定了分类:空间相互作用,树种群落动态和生态系统过程。空间交互是分布在整个景观中并依赖于空间上下文和景观配置的过程。树种的社区可能会随时间变化或可以先验地定义。生态系统过程的表示形式可以从无表示形式到高度机械化的详细表示形式。我们的分类突出了每个模型组的隐式假设,并有助于定义每个模型组最适合的问题集。我们还提供了森林景观模拟模型的简要历史,概述了方法的当前趋势,并考虑了森林景观模型如何演变并继续为森林生态和管理做出贡献。我们的分类和审查可以为新手建模者提供生态环境,以帮助他们理解或为他们的特定假设选择合适的模型。此外,我们的审查阐明了练习模型用户和模型开发人员所面临的挑战和机遇。

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