Introduction
Biogeographic patterns and the underlying mechanisms are essential in
biodiversity research. The understanding of biogeographic patterns is
crucial for predicting how global change affects biodiversity, designing
effective conservation strategies, and achieving sustainable development
(Gaston 2000). Studies on biogeographic patterns can be challenging due
to the interactions among multiple biotic and abiotic factors, and to
complex interrelationships among animals, plants, and microorganisms
(Dolan 2006; Delavaux et al., 2019). Previous research focusing
solely on macrobiota biodiversity may therefore be inadequate to clarify
the full view of biogeography (Mascarenhas et al. , 2020). Despite
microbes being the most important biotic driver of global material and
energy flows, biogeographic research on microbiota has long lagged
behind that of macrobiota, and there are debates on whether
heterogeneous biogeographic patterns
exists in microbes (Martiny et al. , 2006; Meyer et al.,2018). The followings may be the main obstacles of microbial
biogeography.
The primary obstacle for the lagged research on microbial biogeography
is evaluating microbial diversity accurately. Microbial communities
contain extremely high microbial biodiversities and nonculturable taxa.
So, the traditional pure culture methods cannot deal with the obstacle.
Recent advances in metagenomics have finally made fast evaluations of
microbial diversity possible (Hanson et al. 2012), while concerns
about the new methodologies remain. First, metagenomic approaches use
operational taxonomic units (OTU)
clustered based on arbitrary identity thresholds (usually 97%), which
reduces the resolution of the taxonomic data set and generates confusing
patterns (Storch et al. 2008). Second, metagenomic approaches are
not concern on the strain level and unable to match OTUs with actual
taxa or identify dormant microorganisms (Dolan 2006; Land et al.,2015; Locey et al., 2020). Third, metagenomic approaches
controversially neglect the rare taxa which are often more important
than common taxa in analyses of microbial diversity (Gobet et
al., 2012). Although current reaserch have begun to use amplicon
sequence variants (ASV) with higher resolution to replace OTU, ASV is
still an operational taxonomic unit in essence, which has not been
completely solved those problems.
At last, the core obstable is the choice of research units. Many studies
about microbial biodiversity lack systematic sampling designs, clear
research boundaries, and appropriate research scales (Ladau &
Eloe-Fadrosh 2019). The worse is that biogeographic patterns are
particularly sensitive to above factors (Bay et al., 2020). Those
caused confused results, and the confusions make it impossible for
researchers to distinguish variation in microbial biodiversity caused by
contemporary or historical factors (Castle et al., 2019).
We propose three solutions to overcoming above obstacles and clarify the
confusions. First, microbial biogeographic studies should depend on
natural units with clear boundaries. Current studies on microbial
biodiversity use either an arbitrary grid as unit of analysis or
nothing, which may result in mixing up the effects of various factors.
Natural units with clear boundaries should also be the fundamental need
for the study about biodiversity, because coupling animal, plant and
microbial biodiversity distributions is inevitable for future
biogeographic research (Peters et al., 2016). While biogeographic
units for animals and plants have long been defined (e.g., ecoregions,
biota, biogeographic provinces) (Hausdorf 2002; Smith et al.,2018), they do not match well with each other; great differences were
among different regions and taxa (Smith et al., 2020). We propose
that natural watersheds are ideal units for biodiversity research,
because they are relatively independent or “close” units of material
and energy flow, and their boundaries can be natural barriers of
transmission (Timur 2013). In addition, the contemporary and historical
effects driving species distribution should change gradiently in
different scales of watersheds, and watershed units could help us
distinguish contemporary and historical effects.
Second, a framework that considers the importance of rare species and
removing the coverup of widespread species should be established.
Because rare species comprise a large part of the microbial community
and contribute greatly to the microbial geographical patterns (Lynch &
Neufeld 2015), their narrow distribution cannot be ignored. However,
most of the existing research focuses on common species which widely
distributed. The widespread species with large biomass are likely to
masked the heterogeneous biogeographic patterns of microbial community.
This may be due in part to the overconfidence in technology and resource
limitations, so inadequate sampling efforts are engaged in current
metagenomic approaches. Limitations on the resolution of metagenomic
approaches often results in the removal of rare taxa data during data
processing (Bay et al., 2020). While the pure culture methods may
be more effective at detecting rare species, its high workload makes it
difficult to achieve comprehensive monitoring for huge microbial
communities. To better account for the issue, we suggest 1) selecting a
cultivatable and relatively small microbial taxon as the research
object, 2) sampling adequately with stratified sampling strategy, 3)
removing the coverup of widespread
species at species level, and 4) analysing the widespread species
biogeographic patterns at genetic level. These strategies will avoid the
common problems plaguing the existing research system and should
therefore set the standard for comprehensively understanding the
biogeographic patterns of microorganisms.
Third, we suggest that studies about microbial biodiversity should be
conducted in highly heterogenous environments. Microorganism dispersal
is largely driven by both abiotic and biotic factors, and microbes are
readily able to adapt and survive in a variety of environments. Indeed,
studies conducted in homogeneous environments and within small spatial
scales often reveal that either microorganisms are randomly distributed,
or the weakness of environmental effects and dispersal limitations fail
to indicate any non-random patterns in these region (Meyer et
al., 2018; Liu et al., 2020). We believe it is easier to observe
the spatial distribution pattern of microorganisms on large scales with
high environmental heterogeneity.
Consequently, we conducted this research in Yunnan Province, China,
which holds six major international rivers belonging to the Pacific and
Indian Ocean systems. The watersheds were largely shaped by the
collision of the Indian Ocean and Eurasian plates, with the formation of
the Qinghai-Tibet Plateau. The spatial heterogeneity in Yunnan is very
high, given that mountainous areas occupy 88.6% of the province.. Using
the stratified sampling method, we collected 2,250 specimens from 228
sites in Yunnan Province (Figure 1, 2). We combined pure culture and
molecular methods to investigate how common and rare Nematode-Trapping
Fungi (NTF, a cultivable microbial group consisting of 99 known species
) taxa are spatially distributed across Yunnan. By doing so, we aim to
verify our three proposed recommendations regarding 1) using watersheds
as the research units, 2) removing the coverup of widespread species,
and 3) stratified sampling from heterogenous environments, to overcome
the challenges of microbial biodiversity research and to test our
hypothesis that the microbial biogeographic patterns could be found in
the perspective of watersheds.