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.