Animal Gut Microbiome (AGM) Data from 91 Published Studies for 224 Animal Species

Diversity and heterogeneity often are conflated but are fundamentally different. An aphorism proposed by Shavit and Ellison (2021; J. Phil. 118: 525–548) for distinguishing them is that “a zoo is diverse whereas an ecosystem is heterogeneous.” That is, a zookeeper measuring diversity simply enumerates the different types of animals; interactions are not expected to occur between animals separated by fences or other barriers. In contrast, measures of heterogeneity ought to include both interspecific interactions and relationships between species and their heterogeneous habitats. Here, we use cross-scale, dual scaling-law analyses of heterogeneity and diversity of animal gut microbiomes (AGMs) to address three objectives: (i) estimate the spatial heterogeneity and diversity of animal-gut microbiomes; (ii) analyze influences of phylogeny and diets on scaling of diversity and heterogeneity; (iii) explore mechanistic differences between diversity and heterogeneity in AGMs. From 4903 AGM samples collected from 318 animal species covering all six classes of vertebrates and four major classes of invertebrates, we estimated that ≈640,000 operational taxonomic units (OTUs or “species”) make up the pool of microbial species that could inhabit animal guts, among which ≈8000 are relatively common and ≈800 are dominant. The gut of any single animal, however, includes only 0.01–0.5% of the total species pool. We extended Ma’s diversity-area relationship for scaling diversity and extend Taylor’s Power Law and Luna et al.’s (2020; Diversity 12: 86) interaction diversity for scaling heterogeneity. At the community scale, phylogeny significantly influenced heterogeneity, but diets did not. Phylogeny and diets had limited influence on diversity at both community and landscape scales. Although two common measures of diversity—beta diversity and unevenness—commonly are synonymized with heterogeneity, our data lead us to conclude that diversity and heterogeneity measure two very different properties. Further, differences in scaling of diversity and heterogeneity are a result of heterogeneity being primarily the result of evolved dispersal behavior and interspecific interactions, whereas diversity results from abundances controlled on ecological time scales.多样性（diversity）与异质性（heterogeneity）常被混淆，但二者本质迥异。夏维特与埃利森（Shavit & Ellison, 2021; J. Phil. 118: 525–548）提出了一则用以区分二者的箴言："动物园体现的是多样性，而生态系统体现的则是异质性"。换言之，动物园管理员衡量多样性时，仅需枚举不同种类的动物即可；被围栏或其他障碍物分隔开的动物之间，无需考虑物种间的相互作用。与之相对，异质性的测度则应同时涵盖物种间相互作用，以及物种与其异质生境之间的关联。 在此研究中，我们采用跨尺度双重标度律分析方法，对动物肠道微生物组（animal gut microbiomes, AGMs）的异质性与多样性展开研究，旨在达成三个目标：（i）估算动物肠道微生物组的空间异质性与多样性；（ii）分析系统发育与饮食对多样性和异质性标度关系的影响；（iii）探究动物肠道微生物组中多样性与异质性的机制性差异。 我们从涵盖脊椎动物全部6纲、无脊椎动物4个主要纲的318个动物物种中，采集了4903份动物肠道微生物组样本，据此估算出：可定植于动物肠道的微生物物种库约包含64万个操作分类单元（operational taxonomic units, OTUs，或称"物种"），其中约8000个为常见类群，约800个为优势类群。然而，单只动物的肠道内仅包含总物种库0.01%~0.5%的物种。 我们拓展了用于多样性标度分析的马氏种-面积关系（Ma’s diversity-area relationship），同时拓展了用于异质性标度分析的泰勒幂法则（Taylor’s Power Law）与卢纳等人（Luna et al., 2020; Diversity 12: 86）提出的相互作用多样性模型。在群落尺度上，系统发育对异质性具有显著影响，而饮食则无此作用；无论在群落尺度还是景观尺度上，系统发育与饮食对多样性的影响均较为有限。 尽管两种常见的多样性测度指标——β多样性（beta diversity）与不均匀性（unevenness）——常被视作异质性的同义词，但我们的研究数据表明，多样性与异质性所表征的是两种截然不同的属性。进一步而言，多样性与异质性的标度关系存在差异，其根源在于：异质性主要源于演化形成的扩散行为与物种间相互作用，而多样性则由生态时间尺度上的物种丰度调控所决定。