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A new family of standardized and symmetric indices for measuring the intensity and importance of plant neighbour effects

机译:一种新的标准化和对称指标,用于测量植物邻居效应的强度和重要性

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摘要

Measurements of competition and facilitation between plants often rely upon intensity and importance indices that quantify the net effect of neighbours on the performance of a target plant. A systematic analysis of the mathematical behaviour of the indices is lacking and leads to structural pitfalls, e.g. statistical problems detected in importance indices. We summarize and analyse the mathematical properties that the indices should display. We review the properties of the commonly used indices focusing on standardization and symmetry, which are necessary to avoid compromising data interpretation. We introduce a new family of indices Neighbour-effect Indices' that meetall the proposed properties. Considering the commonly used indices, none of the importance indices are standardized, and only RII (Relative Interaction Index) displays all the required mathematical properties. The existing indices show two types of symmetries, namely, additive or commutative, which are currently confounded, potentially resulting in misleading interpretations. Our Neighbour-effect Indices encompass two intensity and two importance indices that are standardized and have different and defined symmetries. Our new additive intensity index, NInt(A), is the first of its kind, and it is generally more suitable for assessing competition and facilitation intensity than the widely used RII, which may underestimate facilitation. Our new standardized importance indices solve the main statistical problems that are known to affect C-imp and I-imp. Intensity and importance with the same symmetry should be used within the same study. The Neighbour-effect Indices, sharing the same formulation, will allow for unbiased comparisons between intensity and importance, and between types of symmetry.
机译:植物之间的竞争和促进的测量通常依靠强度和重要指标,这些指标量化邻居对目标植物性能的净效应。缺乏对索引的数学行为的系统分析,导致结构缺陷,例如,重要性指数中检测到的统计问题。我们总结并分析了指数应显示的数学属性。我们审查了专注于标准化和对称性的常用指数的属性,这是避免损害数据解释所必需的。我们介绍了一系列新的指数邻居效应索引',符合所提出的属性。考虑到常用的指数,都没有重要的指标是标准化的,并且只有RII(相对交互索引)显示所有所需的数学属性。现有索引显示两种类型的对称性,即附加或换向,当前被混淆,可能导致误导性解释。我们的邻居效应指数包括两个强度和两个重要性指标,标准化并具有不同和定义的对称性。我们的新添加剂强度指数,nint(a)是其第一种,而且通常更适合评估比广泛使用的rii的竞争和促进强度,这可能低估了便利。我们的新标准化重要指标解决了已知影响C-IMP和I-IMP的主要统计问题。应在同一研究中使用相同对称性的强度和重要性。共享相同的配方的邻效索引将允许强度和重要性之间的无偏见和对称类型之间的比较。

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