INTRODUCTION
Understanding the factors that determine the abundance, distribution, and diversity of organisms across spatial and temporal scales is a fundamental challenge in ecology. For plants and animals, manymacroecological rules (also known as ”ecogeographic rules”) have been theorized to explain the physiological and ecological processes that underlie these patterns. Microorganisms also exhibit patterns in abundance, distribution, and diversity over space and time (Martiny et al. 2006, 2011; Hanson et al. 2012; Talbot et al. 2014; Kivlin 2020). Yet it is unclear whether macroecological rules developed for plants and animals apply to microorganisms and if they could be used to encourage best practices and improve predictions for abundance, distribution, and diversity of microorganisms. (Prosser et al. 2007; Soininen 2012; Shadeet al. 2018; Kivlin et al. 2020). Defining which macroecological rules are universal across the tree of life will allow for ecosystem-wide development of theory of common mechanisms affecting community assembly, response to global change, and recovery from human-induced disturbance.
Some macroecological rules should apply across the spectrum of life. For example, those that describe patterns of abundance or biodiversity of plants and animals (e.g., latitudinal/altitudinal clines in biodiversity, species-area relationships, species-abundance distributions, island biogeographic patterns) easily translate to microorganisms since these rules share a common theoretical underpinning of expanding the drivers of local-based community assembly to larger scales. Community assembly of all organisms, including microscopic ones, is driven by deterministic and stochastic processes (Vellend 2010; Nemergut et al. 2013). Deterministic processes include environmental selection or filtering, and biotic interactions such as competition and facilitation (Funk et al. 2008; Goldford et al. 2018). Stochastic processes that affect community assembly include dispersal limitation, neutral processes of ecological and evolutionary drift (Hubbell 2001; Martiny et al. 2011), priority effects of colonization (Fukami et al. 2010), legacy effects of previous environmental conditions (Hawkes et al.2017), and historical vicariance of geographic position of land masses (Matheny et al. 2009) or suitable habitat (Takacs‐Vesbachet al. 2008). Because these explanatory drivers of community assembly apply regardless of the focal organism, community-level macroecological patterns driven by these processes should hold across the tree of life (Horner-Devine et al. 2004; Shade et al.2018).
In contrast, other organismal and functional macroecological rules, such as the Metabolic Theory of Ecology (Brown et al. 2004), Bergmann’s Rule (Bergmann 1847), Foster’s Rule (Foster 1964), and Rapoport’s Rule (Stevens 1989) may lack direct analogs to microbial consortia because the mechanisms posited to underlie these rules relate to traits (e.g., body size, thermoregulation, or homeostasis) that may not exist in microorganisms or that are difficult to measure. This is particularly true of macroecological rules that assume sexual dimorphism of two sexes (Rensch’s Rule; Rensch 1950), which apply well to many animals but break down in organisms with simpler (e.g., asexual bacteria) or much more complex mating systems (e.g., fungal species with hundreds of mating types). Moreover, macroecological rules based on body size lack direct analogs for most microorganisms where body size could be thought of as cell size, colony size or sporocarp size. Even if a consensus could be reached, DNA-based inference of microbial abundance is unlikely to represent cell size or abundance when ribosomal copy number varies 100-fold among microbial taxa and lacks clear phylogenetic signal (Lofgren et al. 2019).
In addition to whether or not macroecological rules apply to microorganisms, microbial groups may also vary in their ability to conform to macroecological rules of plants and animals due to differences in habitat. For example, dispersal limitation of soil-borne and plant-associated microorganisms should be much higher compared to air-borne, water-borne, or animal-associated microorganisms that are actively transported as animals explore surrounding landscapes. This could limit range sizes of terrestrial and plant-associated microorganisms relative to aquatic or animal-associated microorganisms. In addition, climate fluctuations of terrestrial ecosystems may be more pronounced than those in aquatic ecosystems, which could affect organism range sizes (Sorte et al. 2013). Finally, biotic interactions may be more tightly linked in confined terrestrial spaces (e.g., soil pores) compared to large or more well mixed aquatic and marine ecosystems.
Perhaps one of the most crucial distinctions among microbial lifestyles is that of free-living versus host-associated microorganisms (Figure 1 ). Some microorganisms are free-living in the environment in soil and water substrates. Distributions of these taxa may be mostly affected by dispersal limitation and subsequent environmental filtering, where contingencies such as dormancy (Lennon & Jones 2011) or reduced metabolic rates (Wisnoski et al. 2020) allow some microorganisms to cope with unfavorable environmental conditions. However, a large portion of microbial diversity lives in symbiosis inside (endophytic ) or on (epiphytic ) animal and plant tissues. For many vertically transmitted host-associated microorganisms in animals and some plants, dispersal of the microorganism often depends on dispersal of the host (Salerno et al. 2016; Shade et al. 2017), eventually leading to co-cladogenesis in each group (Takiya et al. 2006; Schardlet al. 2008) and a strong signal of biotic filtering on the microbiome among hosts. This is especially true when host-associated microbes are more buffered from environmental conditions compared to free-living microorganisms. Multiple lines of evidence suggest that host-associated microorganisms (especially vertically transmitted microorganisms) often have narrower thermal tolerances (Dunbar et al. 2007; Kikuchi et al. 2016) and reduced genome sizes and functions (Moran et al. 2008). However, for other plant-associated microorganisms (e.g., mycorrhizal fungi), independent dispersal of plants and microorganisms allows dispersal limitation and environmental filtering (Hazard et al. 2013) to influence host-associated microbial communities.
In this review, we synthesize macroecological trends of free-living and host-associated microorganisms from terrestrial and aquatic ecosystems to understand the extent to which microorganisms follow the same large-scale macroecological patterns as animals and plants. The objectives of this review are to (1) Determine to what extent macroecological rules explain the distribution of host-associated and free-living microorganisms, and (2) understand which environmental factors most affect the distributions of host-associated versus free-living microorganisms among microbial clades and habitats. We focus on six macroecological rules at the organismal level (Gloger’s Rule, Rapoport’s Rule, Abundance/Occupancy Relationships, Bergmann’s Rule, Foster’s Rule, Rensch’s Rule), three rules that describe/explain community assembly and biodiversity (Theory of Island Biogeography, Species-Area Relationships, Latitudinal Diversity Gradient), and one functional rule (Metabolic Theory of Ecology).
For each rule we collected studies by querying Web of Science or Google Scholar with the search terms “rule name” AND “micro*” or “fung*” or “bacteri*” or “protist*” or “archaea” (query completed 06.15.2020). Because many studies report trends consistent with these rules without studying them directly, we also surveyed all papers that were cited by or cited the papers in our query. We did not include human-associated microorganisms in our survey. This search resulted in 175 studies with 218 records across all continents. For each study, we classified which macroecological rule(s) were surveyed and each study organism (archaea, bacteria, fungi, or protist), habitat (terrestrial or aquatic/marine), and niche (free-living or host-associated). We considered species-area relationships only for contiguous habitats and included species-area relationships among island-like habitats (e.g., lakes, tree holes, plant rhizosphere, animals) with other island biogeography studies. When the data were available, we classified which deterministic (e.g., resources and climate) and stochastic (e.g., dispersal limitation, priority effects) drivers were correlated with each observed macroecological pattern. Despite collecting 218 records for this synthesis, data limitation precluded a quantitative meta-analytical approach to addressing both adherence of microorganisms to macroecological rules and the environmental drivers influencing these distributions. Instead, we use vote counting (Hedges & Olkin 1980) to define which macroecological rules were supported among microbial guilds and lifestyles and which environmental factors may have influenced these distributional patterns. While vote counting techniques are sensitive to sample size within studies, this analysis clearly demonstrates both when microbial distributions conform to macroecological rules and more importantly when gaps in scientific inquiry do not allow us to make this conclusion.