Species-Area Relationships
The positive relationship between species richness (S) and the surveyed
area (A) is one of the clearest, least disputed macroecological patterns
and is fundamental to understanding the inherent heterogeneity of global
biodiversity (Arrhenius 1921). The power-law
S=cAz has been used to compare the relationship
between species number and area, where c is the intercept and the
exponent z measures the rate of community turnover across a
standardized spatial scale. This phenomenon has been explored across a
myriad of taxa, including birds (Jetz & Rahbek 2001), mammals (Lomolino
1982), plants (Honnay et al. 1999), terrestrial microbial
eukaryotes (Green et al. 2004), soil bacteria (Horner-Devineet al. 2004), aquatic bacteria (Reche et al. 2005; Martinyet al. 2011), ectomycorrhizal fungi (Peay et al. 2007),
and vertebrate gut bacteria (Godon et al. 2016). Yet, the
power-law often fails to predict species richness for many organisms
(McCoy & Connor 1976; Connor & McCoy 1979) indicating that this
relationship may only apply to a subset of spatial scales (i.e. local or
regional), habitat types, or taxonomic groups.
Among microbial studies that investigate species-area or taxa-area
relationships, microbial diversity often increases with spatial scale
but to a much lower extent (slope z = 0.02 - 0.1) than observed
for macroorganisms (slope z = 0.3 – 0.6, see Green & Bohannan
(2006) and references therein). Moreover, the shape of this relationship
is often monotonic and does not follow the proposed power-law for larger
organisms. Spatial scaling of microbial diversity may vary from that of
macroorganisms for many reasons including the higher diversity of
microorganisms versus macroorganisms, loose species definitions for
microorganisms, dormancy of microbial taxa (Jones & Lennon 2010), or
extracellular DNA confounding species richness estimates (Cariniet al. 2016).
In addition to methodological concerns, many variables other than
spatial extent affect the distribution of free-living and
host-associated microorganisms. For example, microbes associated with
marshland habitat respond to both geographic distance and sediment
moisture (Horner-Devine et al . 2004). While species-area
relationships are beginning to be explored across microbial systems,
many confounding factors exist among comparative studies, such as
differences in spatial extent or environmental heterogeneity.
Illustrating this point is the finding that the rate of community
turnover depends on whether microbial species richness is measured
within or across habitats (Martiny et al . 2011). In addition,
determining patterns of species richness over space is even more
intractable for host-associated microbial taxa, such as ectomycorrhizal
fungi, where host effects and dispersal limitation might conflate the
relative importance of various factors in prediction of species richness
(Tanesaka 2012). Nevertheless, despite the shape of the relationship of
species richness and area, taxa within most microbial guilds and
lifestyles increase in diversity across space.
Latitudinal Diversity
Gradient
The Latitudinal Diversity
Gradient (LDG), whereby biodiversity increases from the poles to the
equator, is a common large-scale pattern in ecology (Jablonski et
al. 2006). Many invertebrate and vertebrate species manifest this
gradient, as do vascular plants and some fungi and marine bacteria
(Hillebrand 2004). However, many macro- and microorganisms do not
exhibit a latitudinal diversity gradient (Fuhrman et al. 2008;
Gillman et al. 2015), owing to legacies of environmental
disturbance, dependence on environmental factors that do not trend with
latitude, or dependence on biotic interactions with other organisms
whose diversity also does not scale linearly with latitude.
Early reports on microbial
diversity suggested that some fungi and marine bacteria may follow the
classic LDG pattern much as plants and animals do (Hillebrand 2004).
Further studies confirmed this pattern in stream diatoms, marine
bacterioplankton, marine tintinnids, Streptomyces bacteria,
freshwater fungi, and most fungal taxonomic groups (Fuhrman et
al. 2008; Tedersoo et al. 2014; Hyde et al. 2016; Andamet al. 2016). The main drivers of this pattern were mean annual
precipitation, temperature, carbon availability, and substrate pH.
However, a number of studies show that microbes tend to follow a
hump-shaped diversity pattern within a hemisphere such that the greatest
diversity is found in temperate areas. This trend was demonstrated in
planktonic bacteria (Milici et al. 2016), ectomycorrhizal fungi
(Tedersoo et al . 2014), aquatic hyphomycete fungi (Jabiolet al. 2013; Duarte et al. 2016), and saprotrophic stream
fungi (Seena et al. 2019). Potential drivers of this type of
distribution include sea water temperature, thermoclines, day length,
and phosphorus levels for aquatic species, dispersal limitation in
terrestrial microbes, and plant host-related diversity and distribution
in ectomycorrhizal fungi.
Other patterns of diversity
have also been found across latitude. A study of stream diatoms found
that richness showed a U-shaped pattern. However, the study ranged only
from subtropical to temperate latitudes in the northern hemisphere
(Passy 2010). Thus, a different pattern might have been observed had a
larger latitudinal gradient been examined. In addition, for both the
hump-shaped and U-shaped diversity distributions, sampling bias toward
temperate areas may have influenced these results. Overall, a majority
of studies found no pattern in microbial diversity across latitude.
These include microbes in the Pacific ocean (Baldwin et al.2005), marine free-living ciliates (Azovsky & Mazei 2013), freshwater
diatoms (Soininen & Teittinen 2019), heterotrophic bacterioplankton
(Schiaffino et al. 2013), autotrophic eukaryotes (Schiaffinoet al. 2016), soil bacteria (Fierer & Jackson 2006; Hendershotet al. 2017), and soil fungi (Hendershot et al. 2017).
Instead, soil pH was an important driver of distributions for
terrestrial microorganisms in these studies, but localized climatic
factors, nutrient availability, dispersal limitations, and scale of
study may also play a role. Species richness of some ecto- and
endoparasites also does not vary with latitude, since they are insulated
from environmental conditions by their hosts (Rohde 1978, 1999).
FUNCTIONAL
MACROECOLOGICAL RULES
Metabolic Theory of
Ecology
The Metabolic Theory of
Ecology (MTE) predicts that the metabolism of individual organisms
increases with environmental temperature, often with a
3/4th scaling to body size (Brown et al. 2004).
Corollary predictions suggest that metabolic rates of all organisms are
a combination of the allometric scaling of their body mass and
biochemical kinetics (West et al. 1997) which leads to a negative
association between population carrying capacity and temperature (Brownet al . 2004). While supported in some plant and animal systems,
considerable controversy surrounds the universality of metabolic theory.
For example, many underlying assumptions of metabolic theory, such as
the actual scaling of surface area to volume ratio across organisms and
enzymatic activation energies, remain untested or unproven across the
tree of life (Duncan et al. 2007; Price et al. 2012).
In microbial systems, this theory has been extended to extracellular
enzyme activities (Elias et al. 2014), which are assumed to
reflect intracellular metabolic rates. Many studies across environmental
temperature gradients find positive relationships between temperature
and soil enzyme activities and respiration (Xu et al. 2017) as
well as between temperature and microbial diversity (Okie et al.2015; Zhou et al. 2016; Wu et al. 2018). Similarly,
meta-analyses confirm that metabolic efficiency (i.e. the quantity of
resources incorporated into biomass relative to uptake) scales with body
size among microorganisms in terrestrial and aquatic ecosystems
(Sinsabaugh et al. 2015). However, metabolic scaling in
microorganisms rarely follows the 3/4th power to body
size (DeLong et al. 2010) and studies are often confounded by
other abiotic and biotic factors that also shift with temperature, such
as variation in water, nutrient availability, plant diversity, or
productivity (Zhou et al . 2016). Furthermore, thermal acclimation
(Bradford et al. 2008) and adaptation (Alster et al. 2020)
can alter microbial temperature responses in less than a decade. Thus,
while evidence in support of metabolic scaling of microbial processes
seems confirmatory, the rule should be examined more carefully across
gradients that decouple temperature from other environmental drivers
over evolutionary time. In addition, cell size is not linearly related
to metabolic rates in marine phytoplankton communities (Marañón 2015),
suggesting that the relationship between organismal size and metabolism
may apply to aggregates of microorganisms but break down at the
smallest, cellular scales.