Rarefaction and extrapolation with Hill numbers: a framework for sampling and estimation in species diversity studies
Rarefaction and extrapolation with Hill numbers: a framework for sampling and estimation in species diversity studies
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DOI：
10.1890/13-0133.1
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发表时间：
2014-02-01
影响因子：
6.1
通讯作者：
Ellison, Aaron M.
中科院分区：
文献类型：
--
作者：
Chao, Anne;Gotelli, Nicholas J.;Ellison, Aaron M.
量化和评估生物多样性的变化是许多生态研究的核心方面，但从采样数据估计生物多样性的准确方法一直难以捉摸。希尔数，或有效的物种数，越来越多地用于表征一个组合的分类，系统发育或功能多样性。然而，希尔数，包括物种丰富度的经验估计，往往是一个越来越多的功能的采样努力，因此，往往会增加与样本的完整性。根据采样理论绘制的综合曲线将稀疏（内插）和预测（外推）平滑地联系起来，根据样本大小或样本完整性使样本标准化，并便利生物多样性数据的比较。在这里，我们扩展了以前的稀疏和外推模型的物种丰富度（希尔数D-q，其中q = 0）的措施，分类多样性纳入相对丰度（即，对于任意Hill数D-q，q> 0），并给出了基于个体（丰度）数据和基于样本（发生率）数据的统一方法。使用这个统一的抽样框架，我们得到的理论公式和分析估计的无缝稀疏和外推的基础上希尔数。前三个希尔数提供了详细的例子：q = 0（物种丰富度），q = 1（香农熵指数的指数），q = 2（辛普森浓度指数的倒数）。我们开发了一种自助方法，用于构建希尔数周围的置信区间，便于比较稀薄和外推样品的多个组合。所提出的估计是精确的稀疏和短程外推。对于长程外推，估计器的性能取决于q的值和外推范围。我们测试了我们的方法模拟数据产生的物种丰度模型和大型物种库存的数据。我们还说明了公式和估计使用经验数据集的温带森林蜘蛛和热带蚂蚁的生物多样性调查。
Quantifying and assessing changes in biological diversity are central aspects of many ecological studies, yet accurate methods of estimating biological diversity from sampling data have been elusive. Hill numbers, or the effective number of species, are increasingly used to characterize the taxonomic, phylogenetic, or functional diversity of an assemblage. However, empirical estimates of Hill numbers, including species richness, tend to be an increasing function of sampling effort and, thus, tend to increase with sample completeness. Integrated curves based on sampling theory that smoothly link rarefaction (interpolation) and prediction (extrapolation) standardize samples on the basis of sample size or sample completeness and facilitate the comparison of biodiversity data. Here we extended previous rarefaction and extrapolation models for species richness (Hill number D-q, where q = 0) to measures of taxon diversity incorporating relative abundance (i.e., for any Hill number D-q, q > 0) and present a unified approach for both individual-based (abundance) data and sample-based (incidence) data. Using this unified sampling framework, we derive both theoretical formulas and analytic estimators for seamless rarefaction and extrapolation based on Hill numbers. Detailed examples are provided for the first three Hill numbers: q = 0 (species richness), q = 1 (the exponential of Shannon's entropy index), and q = 2 (the inverse of Simpson's concentration index). We developed a bootstrap method for constructing confidence intervals around Hill numbers, facilitating the comparison of multiple assemblages of both rarefied and extrapolated samples. The proposed estimators are accurate for both rarefaction and short-range extrapolation. For long-range extrapolation, the performance of the estimators depends on both the value of q and on the extrapolation range. We tested our methods on simulated data generated from species abundance models and on data from large species inventories. We also illustrate the formulas and estimators using empirical data sets from biodiversity surveys of temperate forest spiders and tropical ants.