Rarefaction and extrapolation with beta diversity under a framework of H ill numbers: The iNEXT . beta3D standardization
Rarefaction and extrapolation with beta diversity under a framework of H ill numbers: The iNEXT . beta3D standardization
复制标题
希尔数框架下的β多样性稀疏和外推：iNEXT。
DOI：
10.1002/ecm.1588
复制
发表时间：
2023
影响因子：
6.1
通讯作者：
Chao A
中科院分区：
文献类型：
--
作者：
Chao A
基于采样数据，我们提出了一种严格的标准化方法来衡量和比较数据集之间的Beta多样性。这里，量化群落间分化程度的贝塔多样性依赖于惠特克最初的乘法分解方案，但我们使用希尔数来表示任何多样性阶q ≥0。基于丰富度的贝塔多样性(Q= 0)量化了物种同一性转变的程度，而基于丰度的(Q>； 0)贝塔多样性也量化了群落间物种丰度的差异程度。我们采用并定义了统计抽样模型的假设作为我们方法的基础，将抽样数据视为从集合中提取的代表性样本。该方法明确区分了理论集合级别(集合的未知属性/参数)和采样数据级别(根据数据计算的经验/观察统计数据)。在群落水平上，N集合体的β多样性反映了群落中物种丰度分布和个体的时空聚集的相互作用。在独立采样下，观测到的β(=γ/α)多样性不仅取决于组合间的差异，而且还取决于采样努力/完整性，这反过来又导致β对α和伽马多样性的依赖。如何消除基于丰富度的贝塔多样性对其伽马成分(种子库)的依赖已经引起了激烈的争论。我们的方法是根据样本覆盖率(样本完整性的客观衡量标准)对伽马和阿尔法进行标准化。对于单个组合，发展了INEXT方法，通过内插(稀疏化)和希尔数外推，通过采样努力/完整性对样本进行标准化。在这里，我们将inext标准化适应于阿尔法和伽马多样性，即在相同的样本覆盖水平上评估阿尔法和伽马多样性，以制定标准化的、基于覆盖的贝塔多样性。将inext扩展到beta多样性需要开发新的概念和理论，包括正式证明和基于模拟的演示，证明由此产生的标准化beta多样性消除了beta多样性对伽马值和alpha值的依赖，从而反映了纯粹的组合间差异。建议的标准化是以空间、时间和时空数据集为例，而免费软件iNEXT.beta3D方便了所有的计算和图形。
Based on sampling data, we propose a rigorous standardization method to measure and compare beta diversity across datasets. Here beta diversity, which quantifies the extent of among‐assemblage differentiation, relies on Whittaker's original multiplicative decomposition scheme, but we use Hill numbers for any diversity orderq ≥0. Richness‐based beta diversity (q= 0) quantifies the extent of species identity shift, whereas abundance‐based (q> 0) beta diversity also quantifies the extent of difference among assemblages in species abundance. We adopt and define the assumptions of a statistical sampling model as the foundation for our approach, treating sampling data as a representative sample taken from an assemblage. The approach makes a clear distinction between the theoretical assemblage level (unknown properties/parameters of the assemblage) and the sampling data level (empirical/observed statistics computed from data). At the assemblage level, beta diversity forNassemblages reflects the interacting effect of the species abundance distribution and spatial/temporal aggregation of individuals in the assemblage. Under independent sampling, observed beta (= gamma/alpha) diversity depends not only on among‐assemblage differentiation but also on sampling effort/completeness, which in turn induces dependence of beta on alpha and gamma diversity. How to remove the dependence of richness‐based beta diversity on its gamma component (species pool) has been intensely debated. Our approach is to standardize gamma and alpha based on sample coverage (an objective measure of sample completeness). For a single assemblage, the iNEXT method was developed, through interpolation (rarefaction) and extrapolation with Hill numbers, to standardize samples by sampling effort/completeness. Here we adapt the iNEXT standardization to alpha and gamma diversity, that is, alpha and gamma diversity are both assessed at the same level of sample coverage, to formulate standardized, coverage‐based beta diversity. This extension of iNEXT to beta diversity required the development of novel concepts and theories, including a formal proof and simulation‐based demonstration that the resulting standardized beta diversity removes the dependence of beta diversity on both gamma and alpha values, and thus reflects the pure among‐assemblage differentiation. The proposed standardization is illustrated with spatial, temporal, and spatiotemporal datasets, while the freeware iNEXT.beta3D facilitates all computations and graphics.