Coverage-based rarefaction and extrapolation: standardizing samples by completeness rather than size
Coverage-based rarefaction and extrapolation: standardizing samples by completeness rather than size
复制标题
DOI：
10.1890/11-1952.1
复制
发表时间：
2012-12-01
期刊：
影响因子：
4.8
通讯作者：
Jost, Lou
中科院分区：
文献类型：
--
作者：
Chao, Anne;Jost, Lou
我们提出了一个综合的采样，稀疏，外推方法来比较物种丰富度的一组社区的基础上的样本的完整性（如测量样本覆盖率），而不是相等的大小。传统的稀疏化或外推到相等大小的样本可能会错误地表示被比较的社区的丰富度之间的关系，因为给定大小的样本可能足以充分表征较低多样性的社区，但不足以表征较丰富的社区。因此，传统的方法系统地偏向于社区丰富度之间的差异程度。我们推导了一种新的基于无缝覆盖的稀疏化和外推的解析方法。我们表明，这种方法产生的社区之间的丰富度偏差较小的比较，并管理这与较少的总采样工作。当这种方法在采样期间与自适应的基于覆盖的停止规则集成时，可以直接比较样本而无需稀疏化，因此不需要额外的数据，也不会丢弃任何数据。即使在数据收集过程中不使用此停止规则，基于覆盖率的稀疏化也比传统的基于大小的稀疏化丢弃更少的数据，并且更有效地根据社区的真实丰富度找到正确的社区排名。几个假设的和真实的例子证明了这些优点。
We propose an integrated sampling, rarefaction, and extrapolation methodology to compare species richness of a set of communities based on samples of equal completeness (as measured by sample coverage) instead of equal size. Traditional rarefaction or extrapolation to equal-sized samples can misrepresent the relationships between the richnesses of the communities being compared because a sample of a given size may be sufficient to fully characterize the lower diversity community, but insufficient to characterize the richer community. Thus, the traditional method systematically biases the degree of differences between community richnesses. We derived a new analytic method for seamless coverage-based rarefaction and extrapolation. We show that this method yields less biased comparisons of richness between communities, and manages this with less total sampling effort. When this approach is integrated with an adaptive coverage-based stopping rule during sampling, samples may be compared directly without rarefaction, so no extra data is taken and none is thrown away. Even if this stopping rule is not used during data collection, coverage-based rarefaction throws away less data than traditional size-based rarefaction, and more efficiently finds the correct ranking of communities according to their true richnesses. Several hypothetical and real examples demonstrate these advantages.