Spatial Statistics in Landscape Ecology
Spatial Statistics in Landscape Ecology
复制标题
景观生态学中的空间统计
DOI：
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发表时间：
1999
期刊：
影响因子：
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通讯作者：
M. Fortin
中科院分区：
文献类型：
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作者：
M. Fortin
在生态学中，特别是在植物生态学中，识别和量化空间格局是司空见惯的（Greig-Smith 1952，1964; Kershaw 1964）。事实上，大多数生态数据本质上是由几个层次的空间结构组成的：大尺度趋势（物种对气候条件、迁移过程等的反应），小规模模式，斑块（天气条件，物理条件，扩散机制，捕食，竞争等），和局部随机噪声。因此，空间自相关的概念意味着"任何事物都与其他事物相关，但近处的事物比远处的事物更相关"（Tobler 1970），"利用空间数据，人们可以从给定的面积单元中预测属性值，而不是随机的机会."（海宁1980）。Griffith（1992）提供了空间自相关的其他几个定义，其中包括"空间模型错误说明的诊断工具;未观察到的地理变量的替代品;将传统统计方法应用于空间数据系列的麻烦;面积单位划分的适当性和可能人为因素的指标"。
In ecology, especially in plant ecology, it is commonplace to identify and quantify spatial patterns (Greig-Smith 1952, 1964; Kershaw 1964). In fact, most ecological data are inherently composed of several levels of spatial structure: large-scale trends (species responses to climate conditions, to migration process, etc.), small scale patterns, patchiness (weather conditions, physical conditions, dispersal mechanisms, predation, competition, etc.), and local random noise. Therefore, the notion of spatial autocorrelation implies that “Everything is related to everything else, but near things are more related than distant things” (Tobler 1970) and “with spatial data, there is a better than random chance that one can predict attribute values from a given areal unit from those taken on by its juxtaposed areal units …” (Haining 1980). Griffith (1992) provides several other definitions of spatial autocorrelation, which include “a diagnostic tool for spatial model misspecification; a surrogate for unobserved geographical variables; a nuisance in applying conventional statistical methodology to spatial data series; an indicator of the appropriateness of, and possible artifact of, areal unit demarcation.”