SYNTHESIS OF RESULTS
Across all macroecological rules the majority of macroecological
microbial studies (78%) have been conducted on free-living
microorganisms, mainly in aquatic ecosystems (Figure 2 ). In
contrast, few studies have examined similar patterns in host-associated
microorganisms with the notable exceptions of studies of latitudinal
diversity and island biogeographic patterns focused on plant-associated
fungi (e.g., mycorrhizal fungi and endophytes; Figure 2 ).
Furthermore, the bulk of these studies examined community-level trends
in microbial macroecology, with less than 35% of studies occurring at
the organismal level (Figure 2 ). For community-based
macroecological rules, latitudinal diversity gradients were more
commonly studied, but patterns of microbial diversity did not
consistently decrease from the equator to the poles, with reverse,
hump-shaped, and indistinct diversity patterns prevalent across
latitudes (Figure 3 ). In contrast, rules predicted by the
dynamic equilibrium theory of island biogeography, which was the second
most-studied community-based macroecological rule, were largely upheld
in many systems (e.g. terrestrial host-associated mycorrhizal fungi,
aquatic bacteria and protists) with increasing diversity on larger
islands (but see notable exceptions, e.g., leaf endophytic fungi;Figure 3 ). Similarly, diversity was often negatively correlated
with island distance from the source population, especially for
plant-host associated microorganisms. For organism-based macroecological
rules, microorganisms often followed the same patterns as macroorganisms
(e.g., Bergmann’s Rule, Rapoport’s Rule), though evidence was sparse.
Notably, Gloger’s Rule of increasing pigmentation at lower latitudes was
reversed for fungi in the only two published studies, which suggested
that melanization was associated with thermal adaptation to colder, more
polar latitudes. Finally, for functional-based macroecological rules,
evidence for metabolic scaling of microbial function confirmed expected
positive temperature-dependence but was examined in only 14 studies and
never in host-associated microbial communities.
When macroecological rules were upheld in microorganisms, drivers of
these patterns were mostly similar to those hypothesized for the
macroorganisms studied to date (Table 1 ). For example, patterns
consistent with the rules predicted by the dynamic equilibrium theory of
island biogeography were often correlated with island patch size and
dispersal, whereas latitudinal diversity gradients and metabolic scaling
followed temperature gradients. Surprisingly, substrate pH was only
related to species-area relationships and island size in island
biogeography, despite its pivotal role in determining patterns of
microbial beta-diversity at large spatial scales (Fierer & Jackson
2006). Instead, other environmental factors related to climate and
resources (carbon, nutrients) often were correlated with many microbial
macroecological patterns. In addition, dispersal limitation and patch
size were among the main correlates of microbial distributions,
regardless of habitat or host-associated versus free-living status.
While data were scarce, the distributions of host-associated
microorganisms tended to be structured more heavily by biotic factors
(e.g., host identity, microbial interactions) than were free-living
taxa. Similarly, when comparisons were possible (e.g., Latitudinal
Diversity Gradient, Species Area Relationship, Theory of Island
Biogeography) there were no clear differences in drivers of terrestrial
and aquatic microorganisms or among microbial kingdoms (Table
1 ). Clearly more investigation into several macroecological rules such
as Gloger’s Rule, Foster’s Rule and Bergmann’s Rule is warranted, as is
more in-depth inquiry of the processes driving macroecological patterns,
since over 30 studies found support for microbial congruence with
macroecological rules but did not test or describe an underlying process
to create these patterns.
Many factors should be considered when one compares these
microorganismal trends to those of macroorganisms. Many microbial
studies did not explicitly test a macroecological rule and were not
searchable in Web of Science or Google Scholar. In addition, null
results are less likely to be published. These factors could have biased
our findings towards rule confirmation rather than exception.
Biologically, patterns of microbial distributions obtained from
sequencing may sample a different subset of organisms than those derived
from observational studies of plants and animals. DNA-based sampling
encompasses both dormant and active states, which may increase estimates
of microbial diversity as compared to plants and animals. An analog
would be to sample all plant and animal gametes, which clearly is not
feasible. Microorganisms that undergo horizontal gene transfer or have
higher DNA substitution rates may also evolve faster than
macroorganisms, allowing greater ability to respond to microclimates and
shifts in environments than plants and animals. This could be why
microbial distributions seem to track local nutrients or niches more
than would be predicted by theories mentioned above for macroorganisms.