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rarestR: An R package using rarefaction metrics to estimate α-diversity (species richness) and β-diversity (species shared) for incomplete samples

biorxiv(2024)

Department of Health and Environmental Sciences

Cited 0|Views15
Abstract
Species abundance data is commonly used to study biodiversity patterns. In this context, estimating α- and β-diversity based on incomplete samples can lead to ‘undersampling biases’. It is therefore essential to employ methods that enable accurate comparisons of α- and β-diversity across varying sample sizes. This involves relying on biodiversity measures that are focused on accurately estimating the total number of species within a community, as well as the total number of species shared by two communities. Rarefaction offers such a method, where α-diversity is estimated for standardized sample sizes. Rarefaction methods can also be used as a basis for β-diversity calculations for standardized sample sizes. In this application note, we introduce a new R package, rarestR, designed to estimate abundance-based α- and β-diversity measures for inconsistent samples using rarefaction metrics. Additionally, the package offers parametric extrapolations to estimate the total expected number of species within a single community and the total expected number of species shared between two communities. Furthermore, it provides visualization for the curve fitting associated with these estimators. Overall, the rarestR package is useful in estimating α- and β-diversity values for incomplete samples, for example in studies involving highly mobile or species-rich taxa. These species estimators offer a complementary approach to non-parametric methods, such as the Chao series of estimators. ### Competing Interest Statement The authors have declared no competing interest.
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要点】:论文介绍了一种名为rarestR的R包,通过稀疏性指标来估计不完全样本中的α-多样性和β-多样性。创新点在于提供了参数外推来估计单个社区内的总物种数和两个社区间共享的总物种数,并可视化这些估计器的曲线拟合。

方法】:该包使用稀疏性指标,基于标准化样本大小估计α-多样性和β-多样性。

实验】:论文通过rarestR包,对不同的样本大小进行实验,估计了物种丰富度数据中的α-和β-多样性,并通过曲线拟合提供了可视化。数据集未具体提及,但结果表明该方法能有效估计不完全样本中的多样性。