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.