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Spatially correlated forest stand structures: A simulation approach using copulas

机译:与空间相关的林分结构:使用copulas的模拟方法

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Spatial structure of forest stands is one of the main drivers of forest growth and yield, and is an important indicator of wildlife habitat, aesthetics, and other non-timber forest uses. Because spatial structure is costly to measure, a number of approaches for simulating spatial structures have been proposed. In this paper, we propose a simple approach that is capable of generating multispecies stand structures. Based on the method of copulas (Genest and MacKay, 1986, Am. Stat. 40:280-283), we utilize a normal copula to simulate spatially correlated stand structures. Species composition, diameter, height, and crown ratio distributions of each species, and their correlation with underlying spatial patterns are all controlled by user inputs. Example data sets are used to demonstrate how to estimate required parameters and compare simulated spatial structures with observed spatial structures. Except at the smallest scales (<10 m in the longleaf pine dataset and <2 m in the mixed Acadian Forest dataset), the simulated stand structures adequately captured the observed spatial patterns. Based on these comparisons, we conclude that the system is capable of simulating a range of forest stand spatial structures
机译:林分的空间结构是森林生长和产量的主要驱动力之一,并且是野生动植物栖息地,美学和其他非木材森林用途的重要指标。由于空间结构的测量成本很高,因此提出了许多模拟空间结构的方法。在本文中,我们提出了一种能够生成多种树种结构的简单方法。基于系法(Genest和MacKay,1986,美国国家统计局40:280-283),我们利用普通系法模拟空间相关林分结构。每个物种的物种组成,直径,高度和冠比分布及其与基础空间格局的相关性均由用户输入控制。示例数据集用于演示如何估计所需的参数以及将模拟的空间结构与观察到的空间结构进行比较。除了最小尺度(在长叶松树数据集中小于10 m,在Acadian Forest混合数据集中小于2 m)之外,模拟的林分结构足以捕获观测到的空间格局。基于这些比较,我们得出结论,该系统能够模拟一定范围的林分空间结构

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