Distinct Biogeographic Patterns for Archaea, Bacteria, and Fungi along the Vegetation Gradient at

14 Pages·2017·2.58 MB·English

RESEARCH ARTICLE
EcologicalandEvolutionaryScience
crossm
Distinct Biogeographic Patterns for
Archaea, Bacteria, and Fungi along the
Vegetation Gradient at the Continental
Scale in Eastern China
D
o
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BinMa,a,bZhongminDai,a,bHaizhenWang,a,bMelissaDsouza,c,fXingmeiLiu,a,b n
YanHe,a,bJianjunWu,a,b JorgeL.M.Rodrigues,dJackA.Gilbert,c,e,f lo
a
PhilipC.Brookes,a,bJianmingXua,b
d
e
InstituteofSoilandWaterResourcesandEnvironmentalScience,CollegeofEnvironmentalandResource
d
Sciences,ZhejiangUniversity,Hangzhou,Chinaa;ZhejiangProvincialKeyLaboratoryofAgriculturalResources f
r
andEnvironment,Hangzhou,Chinab;DepartmentofEcologyandEvolutionandDepartmentofSurgery, o
m
UniversityofChicago,Chicago,Illinois,USAc;DepartmentofLand,AirandWaterResources,Universityof

California,Davis,Davis,California,USAd;BioscienceDivision,ArgonneNationalLaboratory,Lemont,Illinois, h
t
USAe;TheMarineBiologicalLaboratory,WoodsHole,Massachusetts,USAf tp
:
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ABSTRACT The natural forest ecosystem in Eastern China, from tropical forest to m
boreal forest, has declined due to cropland development during the last 300 years, Received19November2016 Accepted5 sy
January2017 Published7February2017 s
yet little is known about the historical biogeographic patterns and driving processes CitationMaB,DaiZ,WangH,DsouzaM,LiuX, te
for the major domains of microorganisms along this continental-scale natural vege- HeY,WuJ,RodriguesJLM,GilbertJA,Brookes m
tation gradient. We predicted the biogeographic patterns of soil archaeal, bacterial, PC,XuJ.2017.Distinctbiogeographicpatterns s
.
forarchaea,bacteria,andfungialongthe a
and fungal communities across 110 natural forest sites along a transect across four vegetationgradientatthecontinentalscalein s
m
vegetation zones in Eastern China. The distance decay relationships demonstrated EasternChina.mSystems2:e00174-16.https://
.
the distinct biogeographic patterns of archaeal, bacterial, and fungal communities. doi.org/10.1128/mSystems.00174-16. o
r
EditorKarenG.Lloyd,UniversityofTennessee g
While historical processes mainly influenced bacterial community variations, spatially /
Copyright©2017Maetal.Thisisanopen- o
autocorrelated environmental variables mainly influenced the fungal community. Ar- accessarticledistributedunderthetermsof n
chaea did not display a distance decay pattern along the vegetation gradient. Bacte- theCreativeCommonsAttribution4.0 A
rial community diversity and structure were correlated with the ratio of acid oxalate- Internationallicense. p
r
soluble Fe to free Fe oxides (Feo/Fed ratio). Fungal community diversity and AddresscorrespondencetoJianmingXu, il
[email protected]. 3
structure were influenced by dissolved organic carbon (DOC) and free aluminum ,
Morereliablesoilmicrobial 2
(Ald), respectively. The role of these environmental variables was confirmed by the 0
biogeographicpatternsreconstructedfrom 1
correlations between dominant operational taxonomic units (OTUs) and edaphic thenaturalforestinEasternChina 9

variables. However, most of the dominant OTUs were not correlated with the major b
y
driving variables for the entire communities. These results demonstrate that soil ar- g
u
chaea, bacteria, and fungi have different biogeographic patterns and driving pro- e
cesses along this continental-scale natural vegetation gradient, implying different s
t
community assembly mechanisms and ecological functions for archaea, bacteria, and
fungiinsoilecosystems.
IMPORTANCE Understanding biogeographic patterns is a precursor to improving
our knowledge of the function of microbiomes and to predicting ecosystem re-
sponses to environmental change. Using natural forest soil samples from 110 loca-
tions, this study is one of the largest attempts to comprehensively understand the
different patterns of soil archaeal, bacterial, and fungal biogeography at the conti-
nental scale in eastern China. These patterns in natural forest sites could ascertain
reliable soil microbial biogeographic patterns by eliminating anthropogenic influ-
ences. This information provides guidelines for monitoring the belowground ecosy-
stem’s decline and restoration. Meanwhile, the deviations in the soil microbial com-
munities from corresponding natural forest states indicate the extent of degradation
of the soil ecosystem. Moreover, given the association between vegetation type and
January/February2017 Volume2 Issue1 e00174-16 msystems.asm.org 1
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the microbial community, this information could be used to predict the long-term
response of the underground ecosystem to the vegetation distribution caused by
globalclimatechange.
KEYWORDS EasternChina,edaphicfactors,forestsoil,historicalprocesses,microbial
diversity,vegetationzone
Eastern China experiences a continual natural vegetation gradient from tropical
forest to boreal forest. There is growing awareness of the importance of soil
microbiomes,includingbacteria,archaea,andfungi,forregulatingecosystemservices
(1).Soilmicrobiomesperformthemajorityofsoilcarbonandnutrientbiogeochemical
transformations (2), control plant and animal population growth as decomposers,
D
mutualists,orpathogens(3),andinfluenceglobalclimatechangethroughgreenhouse o
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gas emissions (4). Soil microbiomes are extremely complex and diverse, with a large
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number of archaeal, bacterial, and fungal taxa being typically found in 1 g ofsoil (5). lo
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Numerous studies have established that microorganisms display spatial geographic
d
patterns (6–8). Our recent study also confirmed clear biogeographic patterns for a e
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cooccurrence relationship at the continental scale across Eastern China (9). However, f
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while biogeographic patterns have been observed, little is known regarding the o
m
influence of the naturally occurring vegetation gradient on these patterns. Although
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thesenaturalforestecosystemshavebeenextensivelyreducedbyexpandingcropland t
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and urban area in the last 300 years (10), the ecosystem relicts preserved in nature :
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reserves allow the reconstruction of historically widespread microbiomes (11). Given m
therelativelylowanthropogenicinfluenceonpreservednaturalforestecosystems,we s
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arguethatitispossibletoidentifynaturalbiogeographicpatternsfrommicrobiomesin s
t
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forestreserves(12). m
Thebiogeographicpatternsofarchaea,bacteria,andfungihavebeeninvestigated s
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from local to global scales, but the exact mechanisms governing their distribution a
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remain poorly understood (13). Microbial communities have been found to display m
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different biogeographic patterns than plants and animals (14). Some studies showed o
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thatsoilbacterialbiogeographicpatternsarecontrolledbysoilpHatbothregionaland g
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globalscales(2,12,15).Otherstudies,however,suggestthatbacterialspatialdistribu- o
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tion patterns are associated with differences in carbon dynamics; e.g., the dominant
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Verrucomicrobia in prairie soils specialize in the degradation of recalcitrant carbon p
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compounds(11).Globally,soilC/Nratiosinfluencearchaealrelativeabundances,which il
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are higher in soils with lower C/N ratios (16). Additionally, soil salinity, rather than ,

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temperature, is one of the principal driving forces responsible for the creation and
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maintenance of uncultured-Archaea distribution patterns at the global scale (17). A 1
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regionalstudyalongasteepprecipitationgradientsuggeststhatthecompositionsof b
archaeal and bacterial communities differ profoundly according to ecosystem type, y

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whichcanbeexplainedlargelybytheprecipitationgradientcombinedwithvegetation u
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cover (18). Fungal richness is strongly and positively associated with soil pH and Ca s
t
concentration(2).However,processesoperatingatlargespatialscales,suchasdispersal
limitation, were identified as first-order determinants of both regional species pools
andthecommunitycompositionofsoilfungiatlandscapescalesacrossNorthAmer-
ican soil microbiomes (19). These apparently contradictory conclusions may arise
throughthedifferencesinscaleofthestudies,sincecertainecologicalprocessesmight
only be dominant at a particular scale (20). For example, dispersal barriers determine
speciespoolsatalargespatialscale,environmentalconditionsdeterminecommunity
compositioninparticularhabitatsatanintermediatespatialscale,andcoexistenceat
a small spatial scale is determined by niche differences (19). Moreover, differences in
methodologicalandtheoreticalframeworksmakecomparisonsacrossstudiesdifficult
(14). Therefore, it is essential that consistent sampling and analytical methods should
be applied to compare the biogeographic patterns of archaea, bacteria, and fungi
under the same sampling regimes. Recent advances in DNA sequencing technology
have permitted a more robust characterization of microbial biogeographic patterns
January/February2017 Volume2 Issue1 e00174-16 msystems.asm.org 2
BiogeographyofArchaea,Bacteria,andFungi
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FIG1 Locationsandvegetationtypesof110samplingsitesinChina. s
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(14).Despitethis,todate,processesthatdeterminethebiogeographicpatternsofsoil s
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archaea,bacteria,andfungihavenotbeeninvestigatedsimultaneously. a
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Inthisstudy,weusedlarge-scale,systematicsamplingandsoilanalyticalmethods m
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to investigate soil archaeal, bacterial, and fungal communities along a latitudinal o
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gradient range from 18.9 to 48.7°N (over 3,000 km) across four continual vegetation g
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typesinEasternChina.Thesevegetationtypesincludedtropicalseasonalforests(TSF), o
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subtropicalbroad-leavedevergreenforests(SBEF),temperatedeciduousbroad-leaved
A
forests(TDBF),andtemperatemixedconiferous-broadleafforests(TMCF)(seeTableS1 p
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inthesupplementalmaterial).Previousmicrobialbiogeographystudiesinthisregion il
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were largely carried out at local scales or on arable soils (21–23). To minimize the ,

influenceoflanduseonsoilmicrobialcommunities(24),allsoilsamplesinthisstudy 2
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were collected from natural forest reserves, where the changes in soil microbial 1
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communities can represent unperturbed biogeographic patterns without obvious an-
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thropogenic influence. The aim of this study was to determine and compare biogeo- y

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graphic patterns and drivers for archaeal, bacterial, and fungal communities at a u
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continentalscale.Ourresearchquestionswereasfollows.(i)Dobiogeographicpatterns
s
differforsoilarchaeal,bacterial,andfungalcommunitiesalongthiscontinualvegeta- t
tion gradient? (ii) What are the determinant drivers for soil archaeal, bacterial, and
fungalbiogeographicpatterns?
RESULTS
Changesinforestsoilmicrobiotaacrossthevegetationgradient.Wesequenced
variable regions 3 to 5 (the V3–V5 region) of the archaeal 16S rRNA gene, the V1–V3
region of the bacterial 16S rRNA gene, and the V1–V3 region of the fungal 18S rRNA
gene. After quality filtering, we obtained 144,706 archaeal sequences (1,316 (cid:2) 815
reads[mean(cid:2)standarddeviation]persample),504,359bacterialsequences(4,585(cid:2)
1,354 reads per sample), and 470,872 fungal sequences (4,280 (cid:2) 2,133 reads per
sample) from 110 distinct sampling sites (Fig. 1). At 97% sequence identity, a total of
3,366operationaltaxonomicunits(OTUs)weredetectedforthearchaealcommunity,
57,561forthebacterialcommunity,and12,862forthefungalcommunity.Ninesamples
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FIG 2 Composition profiles of archaeal, bacterial, and fungal communities in metacommunities (pie
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charts)anddifferentvegetationtypes(barcharts). t
with less than 300 archaeal sequences were removed from the archaeal community
analysis.AmajorityofthearchaealsequencesbelongedtotheordersNitrososphaerales
(59.7%), Cenarchaeales (22.5%), and NRP-J (5.6%) of the phylum Thaumarchaeota
(92.3%)andsubgroupE2(5.8%)ofthephylumEuryarchaeota(7.1%)(Fig.2a).Members
ofthebacterialtaxaAlphaproteobacteria(16.4%),Gammaproteobacteria(12.7),EC1113
(11.2%), Actinobacteria (9.4%), Thermoleophilia (9.2%), Acidobacteria (6.0%), and Beta-
proteobacteria(5.0%)comprisedthelargestproportionofsequences(Fig.2b).Themost
abundantfungalclassesbelongedtotheclassesEurotiomycetes(20.2%),Sordariomy-
cetes (19.6%), Dothideomycetes (12.1%), and Leotiomycetes (8.1%) of the phylum
Ascomycota (73.7%), class Mucoromycotina (10.3%) of the phylum Mucoromycota
(10.3%),andclassAgaricomycetes(8.5%)ofthephylumBasidiomycota(8.5%)(Fig.2c).
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BiogeographyofArchaea,Bacteria,andFungi
Overall,ourOTU-levelclassificationrevealedthat128(3.8%)archaealOTUsand6,021
(10.5%) bacterial OTUs exhibited (cid:3)97% identity to 16S rRNA gene sequences in the
Greengenes database (13_8 release). Likewise, 2,762 (21.5%) fungal OTUs exhibited
(cid:3)97%identityto18SrRNAgenesequencesintheSILVAdatabase(version111).
Thedominantarchaeal,bacterial,andfungalphylogeneticgroupswerepresentin
soils supporting all vegetation types, but their relative proportions varied across the
vegetationgradient.Forarchaealtaxa(Fig.2d),therelativeabundanceofNitrososphae-
rales was highest in TDBF (64.3%) and lowest in TSF (55.3%). Conversely, the relative
abundances of Cenarchaeales and NRP-J were highest in TSF (26.4% and 10.7%) and
lowestinTDBF(20.4%and8.3%).MembersofE2weremostabundantinSBEF(6.7%).
Forbacterialtaxa(Fig.2e),therelativeabundancesofAlphaproteobacteriawerehighest
inTSF(31.3%)andlowestinTMCF(23.8%).TherelativeabundancesofThermoleophilia D
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rangedfrom10%inTSFto14.4%inTMCF.Acidobacteria,Ktedonobacteria,andABS-6 w
wereabundantinTDBF(8.3,2.7,and1.4%relativeabundances,respectively),SBEF(7.9, n
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3.5, and 4%, relative abundances, respectively), and TSF (7.8, 2, and 1.7% relative a
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abundances, respectively). For fungal taxa (Fig. 2f), members of Eurotiomycetes were
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themostabundantinTSF(36.8%).TherelativeabundancesofSordariomycetes(27.5%), d

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Dothideomycetes(13.6%),Leotiomycetes(11.3%),Cryptomycotina(3.8%),andChytrid- ro
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iomycetes(1.8%)werehighestinTMCF.Likewise,therelativeabundancesofMucoro-

mycotina,Agaricomycetes,andGlomeromyceteswerehighestinTMCF(17.5,7.4,and h
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1.6%,respectively). p
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Geographic patterns of microbial community diversity. We used the Shannon /m
indextomeasuremicrobialalpha-diversityineachofthesoilsamples(101samplesfor s
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archaea and 110 for bacteria and fungi). The differences between the Shannon index s
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values for the different vegetation types were not significant for archaea (F (cid:4) 0.98, em
df(cid:4)3,P(cid:4)0.41)andfungi(F(cid:4)1.29,df(cid:4)3,P(cid:4)0.28).However,significantdifferences s
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inthebacterialShannonindexvalueswereobservedforthedifferentvegetationtypes a
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(F(cid:4)5.32,df(cid:4)3,P(cid:4)0.002)(Fig.3a).ThemeanbacterialShannonindexvaluesinthe m
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SBEF were significantly lower than those observed in the TMCF (P (cid:5) 0.001, Tukey o
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honestlysignificantdifference[HSD],95%confidence).
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We performed multiple regression modeling (MRM) and structural equation mod- o
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eling (SEM) to test for the effects of environmental variables, including edaphic and A
climaticfactors,ontheShannonindexvalues.ThearchaealShannonindexvalueswere p
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not significantly affected by any of the environmental variables. However, total nitro- il
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gen (TN) explained 16% of the archaeal Shannon index variation (F (cid:4) 3.36, df (cid:4) 99, ,
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P (cid:4) 0.07 for MRM; P (cid:4) 0.02 in SEM) (Fig. 3b; see also Fig. S1a in the supplemental 0
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material).Theratioofacidoxalate-solubleFetofreeFeoxides(Feo/Fedratio)wasthe 9

strongestpredictorofbacterialShannonindexvalues(F(cid:4)12.85,df(cid:4)108,P(cid:5)0.001 b
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forMRM)(Fig.3c)andexplained12%ofthebacterialShannonindexvariation(P(cid:4)0.05 g
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inSEM)(seeFig.S1b).ThefungalShannonindexvaluesweresignificantlyinfluencedby e
dissolved organic carbon (DOC) (F (cid:4) 5.88, df (cid:4) 108, P (cid:4) 0.017) (Fig. 3d). This st
observationwasalsoreflectedinourSEMresults(P(cid:4)0.05),where21%ofthevariation
inthefungalShannonindexvalueswasexplainedbyDOC(seeFig.S1c).
Toextendourresultsbeyondthe110soilsamplesdirectlyassayed,weconstructed
spatialmapsofthealpha-diversitiesofsoilmicrobialcommunitiesforwholesampling
regionsusingakriginginterpolationapproach(Fig.4).Thepredictedmapsshowedthat
soilsfromthecentralregionofChinahadlowerarchaealdiversitiesbuthigherbacterial
andfungaldiversities.Soilsfromthenorthernregionhadhigherbacterialandfungal
diversities than those in the southern regions. In addition, bacterial and fungal diver-
sities displayed different spatial patterns in the northern regions. All of the predicted
diversity distributions for archaea, bacteria, and fungi exhibited nonrandom spatial
patterns. However, geographic distance had no significant effect on Shannon index
values(theMantelrvalueswere0.02forarchaea[P(cid:4)0.26],0.01forbacteria[P(cid:4)0.47],
and0.02forfungi[P(cid:4)0.26]).
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FIG3 Shannondiversityindexvaluesforarchaeal,bacterial,andfungalcommunities.(a)Distributionsofarchaea, tp
bacteria,andfungiintropicalseasonalforests(TSF),subtropicalbroad-leavedevergreenforests(SBEF),temperate :
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deciduousbroad-leavedforests(TDBF),andtemperatemixedconiferous-broadleafforests(TMCF)andrelationships /m
between(b)Shannonindexvaluesofarchaealcommunityandtotalnitrogen(TN),(c)bacterialcommunityand s
amorphousiron/freeironratio(Feo/Fedratio),and(d)fungalcommunityanddissolvedorganiccarbon(DOC).The y
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boxesshowthedistributionofvalues.Thelowerandupperhingescorrespondtothefirstandthirdquartiles.The t
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upperandlowerwhiskersextendfromthehingetothelargestvaluenofurtherthan1.5timesoftheinterquartile
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range from the upper and lower hinges, respectively. The outlier points are the data beyond the end of the
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whiskers. .
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Toevaluatechangesinmicrobialcompositionacrossthefourvegetationtypes,we o
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used principal coordinate analysis (PCoA) to represent pairwise Bray-Curtis dissimilar- /

ities across soil microbial community profiles (Fig. 5). We also used permutational o
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multivariate analysis of variance (PERMANOVA) to assess significant differences in A
microbial community compositions across the vegetation types. While the archaeal p
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communitieswerenotsignificantlydifferent(R2(cid:4)0.03,P(cid:4)0.68)acrossthedifferent il
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vegetationtypes,thebacterial(R2(cid:4)0.055,P(cid:4)0.001)andfungalcommunities(R2(cid:4) ,

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0.054,P(cid:5)0.001)showedsignificantdifferencesaccordingtovegetationtype.Wethen 0
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utilizedlinearfittingtorevealtheeffectsofenvironmentalvariablesoncompositional 9
variations. The archaeal community composition was significantly affected by mean b
annual air temperature (MAAT) (R2 (cid:4) 0.074, P (cid:4) 0.024) (see Table S2 in the supple- y
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mentalmaterial).Thebacterialcommunitycompositionwasdominantlyaffectedbythe u
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FIG4 SpatialmappingofShannonindexvaluesforarchaeal(a),bacterial(b),andfungalcommunities(c)acrosssamplingregionsusingkriginginterpolation.
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BiogeographyofArchaea,Bacteria,andFungi
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FIG5 Ordinationofmicrobialcommunities.TheBray-CurtisdissimilaritydistancesarerepresentedusingPCoAordinationforarchaeal,bacterial,andfungal e
communities in tropical seasonal forests (TSF), subtropical broad-leaved evergreen forests (SBEF), temperate deciduous broad-leaved forests (TDBF), and d

temperatemixedconiferous-broadleafforests(TMCF). fr
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Feo/Fedratio(R2(cid:4)0.13,P(cid:4)0.002),Fed(R2(cid:4)0.08,P(cid:4)0.01),totaldissolvednitrogen t
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(R2(cid:4)0.07,P(cid:4)0.02),humicacid(R2(cid:4)0.06,P(cid:4)0.04),andavailablepotassium(R2(cid:4) p:
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0.06, P (cid:4) 0.04) (see Table S3). The fungal community composition was dominantly /m
affected by free aluminum (Ald) (R2 (cid:4) 0.142, P (cid:4) 0.001), mean annual precipitation s
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(MAP)(R2(cid:4)0.15,P(cid:4)0.002),MAAT(R2(cid:4)0.14,P(cid:4)0.002),andsoilpH(R2(cid:4)0.11,P(cid:4) s
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0.01) (see Table S4). These observations were confirmed by constrained correspon- m
dence analysis (CCA), where the Feo/Fed ratio and Ald were the most important s
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variables associated with changes in bacterial and fungal communities, respectively a
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(seeFig.S2toS4). m
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Toidentifyadditionalspatialsourcesofvariationinthemicrobialcommunities,we o
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examinedthecorrelationsbetweencommunitysimilarityandspatialdistancematrices. g
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When examining entire data sets, we found that geographic distance correlated o
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positively with bacterial (R2 (cid:4) 0.06, P (cid:5) 0.001) and fungal (R2 (cid:4) 0.09, P (cid:5) 0.001)
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community dissimilarities. In contrast, archaeal community dissimilarities were not p
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correlatedwithgeographicdistance(R2(cid:4)(cid:6)0.02,P(cid:4)0.105)(Fig.6).TheManteltest il
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resultsshowedthatdissimilaritiesinbacterialcommunitiesweresignificantlycorrelated ,

with geographic distance (P (cid:4) 0.012) and dissimilarities in fungal communities were 2
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significantlycorrelatedwithenvironmentalvariables(P(cid:4)0.010)andmarginallysignif- 1
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icantlycorrelatedwithgeographicdistance(P(cid:4)0.051).ThepartialManteltestresults
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FIG6 RelationshipsbetweentheBray-Curtissimilaritiesofarchaeal,bacterial,andfungalcommunitiesandgeographicdistance.Thelines
representthelinearregressionresults.Theshadedareasshowthe95%confidenceinterval.
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TABLE1 MantelandpartialManteltestresultsforthecorrelationbetweencommunity
similarityandenvironmentalandgeographicdistance
Mantelstatisticr(Pvalue)fora:
Effectof Controllingfor Archaea Bacteria Fungi
Geographicdistance (cid:6)0.015(0.657) 0.059(0.012*) 0.055(0.051)
Environmentalvariables (cid:6)0.044(0.738) 0.010(0.398) 0.109(0.010**)
Geographicdistance Environmentalvariables 0.012(0.370) 0.054(0.011*) 0.056(0.016*)
Environmentalvariables Geographicdistance (cid:6)0.043(0.738) 0.026(0.234) 0.012(0.314)
aStatisticalsignificancewastestedbasedon9,999permutations.*,P(cid:5)0.05;**,P(cid:5)0.01.
indicated that bacterial and fungal communities were primarily governed by spatial
distancewhenthevariationassociatedwithenvironmentalvariableswasremoved(P(cid:4) D
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0.011forbacteria,andP(cid:4)0.016forfungi)(Table1). w
Associations between dominant OTUs and environmental factors. The re- n
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sponsesofthedifferenttaxatodifferentenvironmentalvariablesmayvary.Therefore, a
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wecalculatedtheSpearmancorrelationcoefficientsbetweenenvironmentalvariables e
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and dominant OTUs in archaeal, bacterial, and fungal communities (Fig. 7; see also

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FIG7 CorrelationsbetweendominantmicrobialOTUsandedaphicvariables.ColorsindicatetheSpearman’scorrelationcoefficients,asshowninthekey.
DominantOTUsuncorrelatedwithanyedaphicvariablesarenotdisplayed.Theorder,family,andgenusnamesforthecorrespondingOTUsareshowntothe
leftofthegrids;“NA”indicatesunclearclassificationatthecorrespondingtaxonomiclevel.pH,soilpH;HA,humicacid;FA,fulvicacid;HA/FAratio,humic
acid/fulvicacidratio;TN,totalnitrogen;TDN,totaldissolvednitrogen;OC,organiccarbon;DOCdissolvedorganicmatter;C/Nratio,carbon/nitrogenratio;AK,
availablepotassium;Clay,proportionofclay;Silt,proportionofsilt;Sand,proportionofsand;Ald,freealuminum;Alo,amorphousaluminum;Feo,amorphous
iron;Fed,freeiron;Feo/Fedratio,amorphousiron/freeironratio.
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Fig. S5 in the supplemental material). Dominant OTUs were defined as those with
relativeabundancesabove0.1%.Theseincluded42archaealOTUs,85bacterialOTUs,
and108fungalOTUs.MostofthedominantmicrobialOTUswerenotassociatedwith
anyoftheenvironmentalvariablesmeasured(seeFig.S5).Fifty-fourdominantbacterial
OTUs(63.5%ofthedominantbacterialOTUs)mainlycorrelatedwiththeFeo/Fedratio,
Fed, amorphous aluminum (Alo), and pH. Clay content, DOC, and Ald were the most
crucial environmental variables for 43 fungal OTUs (39.8% of the dominant fungal
OTUs). Soil Ald was the major edaphic variable closely correlated with 9 dominant
archaeal OTUs (21.4% of the dominant fungal OTUs). The dominant microbial OTUs
fromthesametaxonomicgrouphadsimilarresponsestoenvironmentalvariables.Ald
wasnegativelycorrelatedwitharchaealOTUsbelongingtothegeneraNitrososphaera
but positively correlated with the archaeal OTUs belonging to the NRP-J group. One
D
archaeal OTU belonging to the SAGMA-X group correlated positively with available o
w
potassium. The soil Fed concentrations were positively correlated with the bacterial
n
OTUsbelongingtotheordersAcidobacteriales,Actinomycetales,andSolirubrobacterales lo
a
but negatively correlated with the OTUs belonging to the order Rhizobiales. The
d
bacterial OTUs belonging to the order Gaiellales were not correlated with soil Fed e
d
concentrations but were either positively correlated with soil pH or negatively corre- f
r
lated with soil Ald concentrations. The soil Ald concentrations were negatively corre- o
m
lated with the fungal OTUs belonging to the Dothideomycetes and Sordariomycetes.
h
ThefungalOTUsbelongingtotheArchaeorhizomycesandMucoromycotina,however, t
t
p
werecorrelatedwitheithersoilfulvicacid(FA)concentrationsorsoilpHratherthansoil :
/
/
Aldconcentrations.ThefungalOTUsbelongingtotheEurotiomyceteswerenegatively m
correlatedwithsoilDOCconcentrationsratherthansoilAldconcentrations. s
y
s
t
e
DISCUSSION m
Understanding biogeographic patterns requires characterization of the contribu- s
.
tions of contemporary environmental factors versus those made by historical events. a
s
Giventhatdistancedecayofcommunitysimilarityindicatestheinfluenceofhistorical m
.
factors (5), the different influences of geographic distance on archaeal, bacterial, and o
r
fungal community dissimilarities (Fig. 6) imply a discrepancy in the historical effects g
/

uponthedifferenttaxa.Thedistancedecaypatternofbacterialcommunitydissimilarity o
n
isconsistentwithpreviousobservationsbasedonhigh-throughputsequencing(25)but
A
not with those using relatively low-resolution community profiling tools, such as p
r
terminal restriction fragment length polymorphism (T-RFLP) (9). Likewise, the correla- il
3
tion between geographic distance and fungal community dissimilarity agrees with ,

2
previousobservationsoftheglobaldistributionofsoilfungi(2)andprotists(26).Wedid
0
notobserveadistancedecaypatternforarchaea,aspreviouslyreportedfortrophiclake 1
9
sediments (27), or for ammonium-oxidizing archaea, as previously reported for the b
agricultural soils of Eastern China (28). However, spatial distance was also not a y

g
significantpredictorofarchaealcommunitycompositioninsubpolarandarcticwaters u
e
(29).Thedistancedecaypatternofmicrobialcommunitydissimilarityisgeneratedby s
t
selection effects and drift, counteracted by dispersal, and modified by mutation (14).
The effects of mutation cannot be considered in this data set, due to the highly
conserved nature of the 16S and 18S rRNA marker genes (30). We found that the
archaealcommunitydidnotshowdistancedecayatthecontinentalscaleandwasnot
significantly influenced by the selection effects of local environmental variables. Ar-
chaealspeciesrepresentalowproportionoftotalmicrobialcommunitiesandcanbe
grouped into the rare biosphere (31). When relative abundance is low, selection is
ineffective,andneutralforcesshaperarebiosphereassemblies(32).Theseassemblies
may persist in the environment for a long time and exhibit different biogeographic
patterns than groups that are more abundant. However, the lack of a distance decay
patternforarchaeamightonlybeduetotheircosmopolitanabilitytothriveinavariety
ofhabitsordomain-levelresolutionswhichobscuredmeaningfulcorrelationsatlower
taxonomiclevels.Thespatialstructuresofbacteriaandfungimayhaveresultedfrom
autocorrelated environmental variables or from dispersal limitation. In our study,
January/February2017 Volume2 Issue1 e00174-16 msystems.asm.org 9
Maetal.
bacterial community similarities were not correlated with environmental variables
regardless of whether the test was controlled by the geographic distance or not,
indicatingthatthedistancedecaypatternforbacterialcommunitiesrelatedtohistor-
ical dispersal limitation. The Mantel test results suggested a selection effect of envi-
ronmental variables on fungal communities (Table 1). However, this correlation of
environmentalvariablesdisappearedwhenthegeographicdistancewascontrolledin
the partial Mantel test. Accordingly, the distance decay patterns of fungi can be
predominantlyattributedtotheautocorrelatedenvironmentalvariables.Thecontribu-
tionofhistoricalprocessesrepresentedbythedistanceeffectmaybeoverestimated,as
a spurious distance effect will be found if some spatial autocorrelated environmental
variables are not measured, such as climatic conditions, countless edaphic variables,
and the disregarded interactions within microbial communities. The correlation be-
D
tween different compositions in a community influences microbial distributions and o
w
alsodisplaysbiogeographicpatterns(33).
n
Evidence for distinct biogeographic patterns of the three microbial taxa was also lo
a
witnessedthroughthedifferentiationofcommunitydiversityacrossvegetationtypes
d
(Fig. 3a). Consistent changes in the composition of the dominant taxa may result in e
d
differencesinthediversityofmicrobiomesacrossenvironmentalgradients.Ourresults f
r
suggested that the diversity of archaeal, bacterial, and fungal communities was con- o
m
trolledbydifferentenvironmentalvariables(Fig.3btod).Thestrongpositiveinfluence
h
of the Feo/Fed ratio on bacterial community diversity and structure is related to its t
t
p
influenceonbacterialsuccessionduringsoildevelopment(34).TheFeo/Fedratiohas :
/
/
been used for characterizing Fe oxide crystallinity and measuring the proportion of m
amorphousFeintotalFeoxides(35).Inglobalandregionalsoils,pHwasidentifiedas s
y
a major environmental variable that explained bacterial community diversity and s
t
e
composition (1, 15, 36). Fierer and Jackson (1) reported that pH is probably masking m
another environmental variable driving community assembly. The close association s
.
between the Feo/Fed ratio and soil pH (35) suggests that the effects of soil pH on a
s
bacterialcommunitydiversityandcompositionmayberelatedtothesoilFeo/Fedratio. m
.
The direct influence of DOC on fungal diversity agrees with the observed positive o
r
correlation between ectomycorrhizal fungal (EMF) diversity and DOC (37). The global g
/

fungal diversity is strongly affected by soil pH and Ca concentration (2). Notably, the o
n
effectofCaonfungalcommunitydiversitywasattributedtothepositiveinfluenceof
A
exchangeableCaontheturnoverrateofsoilorganicmatter(38).Thelargeinfluenceof p
r
soilAldonfungalcommunitydiversitysuggeststhatthecommunitydiversitymaybe il
3
controlledbyavailablealuminum,whichincreasesassoilpHdeclines(39).Theprevi- ,

2
ouslyreportedinfluenceofsoilpHonfungalcommunitystructuremaybeattributed
0
toaluminumtoxicity.Thetoleranceoffungiforaluminumtoxicityvarieswithdifferent 1
9
phylogenetic groups (40). The marginally significant influence of TN on archaeal b
diversitymaybeassociatedwiththedominanceofNitrososphaerales,whichcandrive y

g
nitrificationinsoils(41). u
e
The nonrandom spatial variation of community composition (Fig. 2) and diversity s
t
(Fig. 3) provides further evidence that archaea, bacteria, and fungi display different
biogeographicpatterns.Thiswasclearlyobservedthroughtheinfluenceofvegetation
type on the relative abundance of dominant taxa. The variation in the relative abun-
dances of Nitrososphaerales indicated that ammonium oxidation activity is higher in
temperateregions(TDBFandTMCF)thanintropicalregions(TSFandSBEF).Members
ofNitrososphaeralesplayacrucialroleinammonia-oxidizingprocessesinsoil(42).The
tendencies of Cenarchaeales and NRP-J suggest that those archaeal groups may re-
spond negatively to ammonium oxidation activities. The members of Cenarchaeales
haveyettobecultured(43),butdenitrificationgeneswerefoundinthegenomesof
Cenarchaeales based on metagenomic approaches (44). The uncultured NRP-J in Cre-
narchaeota were identified from soils, but their functions were unknown (45). The
dominant bacterial taxa identified as part of this study were previously reported as
dominanttaxainsoilsglobally(46).Inadditiontothis,wefounddifferentdistribution
patternsforseveralofthesedominantbacterialtaxabetweentropical(TSFandSBEF)
January/February2017 Volume2 Issue1 e00174-16 msystems.asm.org 10