Microbial communities contain unparalleled complexity, making them difficult to describe and compare. Characterizing this complexity will contribute to understanding the ecological processes that drive microbe-host interactions, bioremediation, and biogeochemistry. Moreover, an estimate of species richness will provide an indication of the completeness of a community profile. Such estimates are difficult, however, because community structure rarely fits a well-defined distribution. We present a model based on the word usage in books to illustrate the power of statistical tools in describing microbial communities and suggesting biological hypotheses. The model also generates data to test these methods when there are insufficient data in the literature. For example, by simulating the word distribution in books, we can predict the number of words that must be read to estimate the size of the vocabulary used to write the book. Combined with other models that have been used to make inaccessible problems tractable, our book model offers a unique approach to the complex problem of describing microbial diversity.

中文翻译：

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最后一句话：书籍是微生物群落的统计隐喻。

微生物群落具有无与伦比的复杂性，使其难以描述和比较。表征这种复杂性将有助于理解驱动微生物与宿主相互作用，生物修复和生物地球化学的生态过程。此外，对物种丰富度的估计将提供群落概况完整性的指示。但是，这样的估计很困难，因为社区结构很少适合定义明确的分布。我们在书中提供了一个基于单词用法的模型，以说明统计工具在描述微生物群落和提出生物学假设方面的作用。当文献中的数据不足时，该模型还会生成数据以测试这些方法。例如，通过模拟书籍中的单词分布，我们可以预测必须阅读的单词数，以估计用于编写本书的词汇量。结合用于使难以解决的问题变得易于处理的其他模型，我们的书本模型为描述微生物多样性的复杂问题提供了独特的方法。