of 20
Impact of River Channel Lateral Migration on Microbial
Communities across a Discontinuous Permafrost Floodplain
Madison M. Douglas
,
a
Usha F. Lingappa
,
a
Michael P. Lamb
,
a
Joel C. Rowland
,
b
A. Joshua West
,
c
Gen Li
,
a
Preston C. Kemeny
,
a
Austin J. Chadwick
,
a
Anastasia Piliouras
,
b
Jon Schwenk
,
b
Woodward W. Fischer
a
a
Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California, USA
b
Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, New Mexico, USA
c
Department of Earth Sciences, University of Southern California, Los Angeles, California, USA
ABSTRACT
Permafrost soils store approximately twice the amount of carbon cur-
rently present in Earth
s atmosphere and are acutely impacted by climate change
due to the polar ampli
fi
cation of increasing global temperature. Many organic-rich
permafrost sediments are located on large river
fl
oodplains, where river channel
migration periodically erodes and redeposits the upper tens of meters of sediment.
Channel migration exerts a
fi
rst-order control on the geographic distribution of per-
mafrost and
fl
oodplain stratigraphy and thus may affect microbial habitats. To exam-
ine how river channel migration in discontinuous permafrost environments affects
microbial community composition, we used amplicon sequencing of the 16S rRNA
gene on sediment samples from
fl
oodplain cores and exposed riverbanks along the
Koyukuk River, a large tributary of the Yukon River in west-central Alaska. Microbial
communities are sensitive to permafrost thaw: communities found in deep samples
thawed by the river closely resembled near-surface active-layer communities in non-
metric multidimensional scaling analyses but did not resemble
fl
oodplain permafrost
communities at the same depth. Microbial communities also displayed lower diver-
sity and evenness in permafrost than in both the active layer and permafrost-free
point bars recently deposited by river channel migration. Taxonomic assignments
based on 16S and quantitative PCR for the methyl coenzyme M reductase functional
gene demonstrated that methanogens and methanotrophs are abundant in older
permafrost-bearing deposits but not in younger, nonpermafrost point bar deposits.
The results suggested that river migration, which regulates the distribution of per-
mafrost, also modulates the distribution of microbes potentially capable of produc-
ing and consuming methane on the Koyukuk River
fl
oodplain.
IMPORTANCE
Arctic lowlands contain large quantities of soil organic carbon that is
currently sequestered in permafrost. With rising temperatures, permafrost thaw may
allow this carbon to be consumed by microbial communities and released to the
atmosphere as carbon dioxide or methane. We used gene sequencing to determine
the microbial communities present in the
fl
oodplain of a river running through dis-
continuous permafrost. We found that the river
s lateral movement across its
fl
ood-
plain in
fl
uences the occurrence of certain microbial communities
in particular,
methane-cycling microbes were present on the older, permafrost-bearing eroding
riverbank but absent on the newly deposited river bars. Riverbank sediment had mi-
crobial communities more similar to those of the
fl
oodplain active-layer samples
than permafrost samples from the same depth. Therefore, spatial patterns of river
migration in
fl
uence the distribution of microbial taxa relevant to the warming Arctic
climate.
KEYWORDS
permafrost, active layer, methanogenesis, methanotrophy, Koyukuk,
Alaska
Citation
Douglas MM, Lingappa UF, Lamb MP,
Rowland JC, West AJ, Li G, Kemeny PC,
Chadwick AJ, Piliouras A, Schwenk J, Fischer
WW. 2021. Impact of river channel lateral
migration on microbial communities across a
discontinuous permafrost
fl
oodplain. Appl
Environ Microbiol 87:e01339-21.
https://doi
.org/10.1128/AEM.01339-21
.
Editor
Isaac Cann, University of Illinois at
Urbana-Champaign
Copyright
© 2021 American Society for
Microbiology.
All Rights Reserved
.
Address correspondence to Madison M.
Douglas, mmdougla@caltech.edu.
Received
7 July 2021
Accepted
26 July 2021
Accepted manuscript posted online
4 August 2021
Published
October 2021 Volume 87 Issue 20 e01339-21
Applied and Environmental Microbiology
aem.asm.org
1
ENVIRONMENTAL MICROBIOLOGY
28
September
2021
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P
ermafrost environments cover 24% of land area in the Northern Hemisphere and
contain signi
fi
cant amounts of organic carbon in soil and sedimentary deposits (1,
2). This organic carbon (OC) has been largely isolated from microbial consumption, in
some cases for thousands of years, due to low subsurface temperatures and ice-
cemented sediment pore spaces (3). Currently, polar ampli
fi
cation of increases in
global air temperature is causing rapid permafrost thaw that exposes previously se-
questered organic carbon stores to greater rates of microbial degradation (4). The
upper
active layer
of Arctic soils thaws each summer, in contrast to underlying per-
mafrost, i.e., ground that has remained below 0°C for at least 2 years. As the active layer
deepens interannually across the Arctic due to higher temperatures, labile OC becomes
available for respiration by permafrost microbial communities, and active-layer
microbes may penetrate deeper soil horizons. This soil carbon reservoir can be released
to the atmosphere as methane (CH
4
) or carbon dioxide (CO
2
) or remain sequestered in
Arctic sediments, depending on the af
fi
nities and activities of microbes present in per-
mafrost environments (5).
Predicting microbial responses to permafrost thaw requires understanding changes
in soil microbiomes with warming over decadal timescales within heterogeneous land-
scapes. Most understanding of permafrost microbial activity comes from laboratory
incubation studies simulating deepening of the active layer. Previous work docu-
mented an initial spike in CO
2
emissions in the days following permafrost thaw, with
peak CH
4
emissions occurring years after thaw (5
7). However, incubation studies
range widely in their predictions of CO
2
-C equivalent emissions, primarily due to chal-
lenges in mapping results from laboratory incubations to the three-dimensional struc-
ture of landscapes (6, 8). Furthermore, understanding the vertical structure of perma-
frost microbiomes requires time-integrated tracking of the depths of the active layer,
water table, and seasonal frost, all of which may generate vertical discontinuities in mi-
crobial community composition (9, 10).
In addition to vertical variations in soil structure and microbial community, perma-
frost landscapes are laterally heterogeneous (11). Previous work correlating micro-
biome and landform heterogeneity focused on variations in soil saturation of ice
wedge polygons near Barrow, AK (12), and in Stordalen Mire, Sweden (13
16).
However, many organic-matter-rich permafrost deposits are located in the
fl
oodplains
of large rivers, where
fl
uvial processes control the transport of carbon and sediment
and the resulting architecture of the deposits (17
19). In particular, river channel
migration may introduce additional variability to the permafrost soil microbiome by
eroding the active layer and upper tens of meters of underlying permafrost and by
building new deposits elsewhere on the
fl
oodplain (20).
Arctic rivers can migrate laterally by meters per year (21), and river migration con-
trols spatial patterns of grain size, surface water in lakes, and deposit age across
fl
ood-
plains (22). Meandering streams erode previous river channel deposits on the outside
of bends in their sinuous channel paths, forming a steep cutbank (Fig. 1E). In locations
with permafrost, the river must
fi
rst thaw its cutbanks before being able to erode the
thawed sediment (23). Most bank thaw and erosion occur during the spring snowmelt
fl
ood following ice breakup, which removes unconsolidated sediment and exposes
permafrost to thawing by the river (24). At the same time that cutbanks are eroding,
the river deposits sediment on the inside of bends, forming shallowly sloping point
bars and maintaining a roughly constant channel width (Fig. 1C to E). These erosion
and depositional processes gradually increase curvature until the channel eventually
cuts itself off and subsequently begins the process anew. Point bar deposits display
systematic, predictable trends in grain size: coarser sand or gravel occurs at depth,
re
fl
ecting the size of sediment transported along the bed of the river, while deposits
closer to the surface of the
fl
oodplain contain
fi
ne sand, silt and clay transported in the
upper portion of the river water column (25).
In this study, we examined microbial community variation throughout various
fl
ood-
plain deposits of the Koyukuk River
a major tributary of the Yukon River that runs
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FIG 1
(A) Map of Alaska, with the study location near the village of Huslia on the Koyukuk River, a
major tributary of the Yukon River. Base map generated in QGIS 3.4 using USGS GTOPO30 30 arc-
second digital elevation model (68) and the HydroSHEDS 15 arc-second Arctic regional river
shape
fi
le (69) projected in WGS 84/NSIDC Sea Ice Polar Stereographic North. (B) Satellite imagery of
the Koyukuk Flats
fl
oodplain marked with sampling locations and contacts between scroll bar
complexes that illustrate cross-cutting relationships indicating their relative age. Core 1 was
sampled approximately 10 m from the river cutbank, while bank 1 was sampled at the cutbank.
Note the abundant scroll bar complexes that trace out past locations of the river channel as it
migrated across the
fl
oodplain. (C) Oblique UAV photograph taken at 243 m above ground level of
a meander bend on the Koyukuk River, with the boat circled for scale and water
fl
owing away from
the viewer. Unfrozen sediment is deposited on the sandy point bar and then becomes vegetated in
alternating grass lake troughs and elevated, forested scrolls. (D) Field photo of permafrost river
cutbank at sampling location bank 9, with undercut peat deposits over permafrost and a thick
apron of thawed sediment containing slump blocks armoring the bank. (E) Schematic of river
channel migration, with the river eroding an outer cutbank composed of former point bar deposits
while depositing new sediment on the point bar on the right. The river
fl
ows out of the page (
fl
ow
direction shown by black arrow), constructing cross-bedded strata in the point bar deposits that are
coarser at the base of the channel and
fi
ne upwards. The river is migrating to the left (white
arrow), eroding permafrost deposits (with permafrost shaded in blue and the active layer near the
surface on the
fl
oodplain and the channel bank) with peat and black spruce vegetation, while the
point bar consists of scrolls with ridges containing white spruce and deciduous trees alternating
with troughs containing grasses.
River Migration Impacts Permafrost Microbial Community
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through a
fl
oodplain underlain by discontinuous permafrost (Fig. 1A). The river is thaw-
ing and eroding permafrost along cutbanks exposed at the outside of its bends and
depositing sediment on its inner bends without permafrost, generating a juxtaposition
of permafrost, active-layer (including laterally thawed sediment on the riverbanks), and
nonpermafrost environments with the same local climate (Fig. 1E, with scroll bars high-
lighted and direction of river migration indicated). Here, we compared the microbial
community compositions of sediments from different landforms across the river
fl
ood-
plain to see if newly built, unfrozen point bar deposits contained a microbial community
similar to that of their opposing, eroding permafrost cutbanks (Fig. 1B).
RESULTS
Microbial community diversity.
Comparison of amplicon sequences to reference
taxa indicated that members of the
Acidobacteria
,
Actinobacteria
, and
Proteobacteria
(mainly
Alphaproteobacteria
and
Betaproteobacteria
) were the most dominant phyla,
followed by
Bacteriodetes
,
Chloro
fl
exi
, and
Firmicutes
(Fig. 2). This is taxonomically con-
sistent with previous studies of permafrost microbial communities (3, 12, 32).
A distinction between permafrost versus active-layer and nonpermafrost deposits
was re
fl
ected in certain taxonomic groups. The families
Caldisericaceae
, vadinHA17
(
Bacteroidetes
), and
Clostridiaceae 1
are relatively abundant in our permafrost samples,
while few representatives are present in nonpermafrost or active-layer samples (Fig. 3).
Other groups, such as
Rhizobiales
,
Planctomycetaceae
, and
Gemmatimonadaceae
, dis-
played the opposite trend and were more abundant in nonpermafrost deposits (Fig. 3).
Few groups exhibited consistent trends with depth, likely due to discontinuities in soil
conditions at the base of the active layer (for permafrost samples) or at the depth of
annual frost formation in nonpermafrost samples (12). Both permafrost and nonperma-
frost samples contained
Anaerolineaceae
, while
Syntrophaceae
were more abundant in
active-layer and permafrost deposits (Fig. 3) (33, 34). These taxa were classi
fi
ed into
families associated with anaerobic taxa, including obligate anaerobes, suggesting that
while anoxic conditions were common across the
fl
oodplain, there were potentially
more reducing conditions in permafrost. Archaea typically accounted for
,
1% of
sequence reads in nonpermafrost deposits (Fig. 2). In permafrost, several of our subsur-
face samples from below the active layer contained more than 10% of reads belonging
to the
Archaea
. Archaeal abundance was driven by members of the
Euryarchaeota
,
which made up a mean of 85% of archaeal reads in permafrost, 88% in the active layer,
and 68% in nonpermafrost deposits. The remaining archaeal operational taxonomic
units (OTUs) consisted of unclassi
fi
ed
Thaumarchaeota
, particularly
Candidatus
Nitrosoarchaeum.
Previous studies of ice wedge polygons found that autotrophic am-
monia oxidizers from the
Nitrososphaerales
dominate the
Thaumarchaeota
found in
permafrost, implying that
Archaea
may play an important role in nitrogen cycling in
permafrost environments (35). Fewer than 1% of archaeal reads consisted of
Crenarchaeota
or other phyla (e.g., Asgard taxa).
Replicate sample splits analyzed from Core9-44-46 and Core9-109-115 generated
highly similar relative OTU abundances (Fig. 4), which we quanti
fi
ed as the standard
deviation of relative abundance for the most abundant listed taxa at the phylum and
family level. In comparison to Core9-44-46-R1 and -R3, Core9-44-46-R2 displayed
slightly higher
Acidobacteria
and
Chloro
fl
exi
relative abundances and smaller amounts
of
Euryarchaeota
,
Actinobacteria
, and
Alphaproteobacteria
. The differences in relative
abundance contributed to the higher uncertainty in reads for Core9-44-46 (2.0% at the
phylum level and 1.4% at the family level) versus Core9-109-115 (0.50% at the phylum
level and 0.44% at the family level). However, the similar and consistent OTU occur-
rence and relative abundance between replicates indicates relatively low uncertainty
due to potential sample contamination as well as DNA extraction, ampli
fi
cation, and
sequencing.
We observed lower microbial diversity in permafrost than in active-layer samples and
the highest diversity and evenness in nonpermafrost samples (Table 1; Fig. 5). We rare
fi
ed
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the data to 4,500 reads and did not conduct diversity analyses on samples with fewer
reads out of concern that low reads were due to an error in sequencing and the data are
not representative of the sample. However, we note that rarefying to 1,000 reads did not
signi
fi
cantly change our results. The number of observed OTUs and the Shannon diversity
index, Chao 1, Fisher
salpha,Simpson
s evenness, and Simpson
s index all indicated
decreased diversity when transitioning from nonpermafrost to active-layer and perma-
frost samples. Active-layer samples from the
fl
oodplain cores and cutbanks showed simi-
lar diversity and evenness:
fl
oodplain active-layer samples had a Fisher
salphaof
1,272
6
703 (mean
6
1 standard deviation) and a Simpson
sevennessof0.1254
6
0.0830,
while cutbank active-layer samples had a Fisher
salphaof1,552
6
1,106 and a Simpson
s
evenness of 0.1423
6
0.1912 (Table 1). The
fl
oodplain and cutbank active-layer samples
differed by
,
3% of the mean value of all other diversity metrics and had intermediate di-
versity between permafrost and nonpermafrost samples. Therefore, we inferred that the
regions of the Koyukuk River
fl
oodplain that contain no permafrost hosted a greater vari-
ety of taxa. In contrast, permafrost and active-layer sediment contained microbial com-
munities dominated by fewer taxa (Table 1; Fig. 5).
Nonmetric multidimensional scaling (NMDS) analyses of the microbial community data
found distinct differences between the microbial communities of permafrost, active-layer,
and nonpermafrost deposits, with active-layer samples spanning the space between iso-
lated clusters of permafrost and nonpermafrost samples (Fig. 6A). Plotting the vectors of
the most signi
fi
cant
de novo
taxa showed that most were from
Gemmatimonadaceae
,
Xanthobacteraceae
,
Syntrophaceae
(genus
Smithella
), and
Acidobacteria
subgroup 6. Some
taxa commonly associated with nitrogen cycling, in particular
Bradyrhizobiaceae
and
Nitrosomonadaceae
, were highly signi
fi
cant and preferentially associated with nonperma-
frost and active-layer deposits. We focused further analyses on the differences between
permafrost, active-layer and nonpermafrost deposits in sequences assigned to families of
biogeochemical interest but noted that large contributions to these differences come
from sequences assigned to uncultured families and
Acidobacteria
subgroup 6.
FIG 2
Mean relative taxon abundances for permafrost, active-layer, and nonpermafrost samples, with
error bars showing the standard deviations of relative abundance within each grouping. The
permafrost samples contained ice cement (
n
= 8: Core1-105-111 and core 9 samples
.
58-cm depth),
active-layer samples overlay ice cement (
n
= 6: core 1 and core 9 samples
.
58-cm depth) or located
on riverbanks with ice cement (
n
= 8: banks 1, 2, and 9), and nonpermafrost scroll bars were unfrozen
(
n
= 9: core 7, pit 1, pit 2, pit 5, pit 6, and pit 8).
River Migration Impacts Permafrost Microbial Community
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Taxa involved in methane biogeochemistry.
Community analyses revealed that
relative abundances of both methanogens and methanotrophs decrease upon per-
mafrost thaw over seasonal timescales (Fig. 3). The main methanogenic taxa in our
data belong to Rice Cluster II, which contains
Candidatus
Methano
fl
orens stordalen-
mirensis
(100% similarity to IonTorrent metagenome
SRA096214
using BLASTn)
a
hydrogenotrophic methanogen whose abundance strongly correlated with soil
methane concentrations in Stordalen Mire, Sweden (14
, 16). OTUs assigned to Rice
Cluster II were abundant in permafrost samples in this study, including those from
core 1, bank 1, and core 9, accounting for up to 28.0% of reads (Fig. 3). We also
observed less abundant taxa from the hydrogenotrophic genus
Methanobacterium
(up to 13.7% of reads) and the acetoclastic methanogenic genera
Methanosaeta
(up
to 0.5% of reads) and
Methanosarcina
(up to 0.3% of reads) in core 9, core 1, bank 1,
bank 9, and pits 1 to 8. In cutbanks that had been thawed by river migration, metha-
nogen abundance was near or below the limit of detection (Fig. 7). Previous studies
found similar trends with the hydrogenotrophic methanogens
Methanobacterium
and
Methanocellales
as well as the acetoclastic methanogens
Methanosarcina
and
Methanosaeta
(10, 15).
The main methanotrophic taxa in our data belong to GoM Arc I, which contains
Candidatus
Methanoperedens nitroreducens,
a species of ANME 2d. These are anaer-
obic methanotrophic (ANME) archaea that in cultured strains have a metabolism cou-
pling methane oxidation to nitrate/nitrite reduction (37). OTUs assigned to GoM Arc I
were abundant in one sample, Bank1-120, where they made up 10.9% of reads. ANME
2d archaea have been previously detected in permafrost microbial communities (38),
often located in soil horizons slightly above horizons rich in methanogens (39).
However, locations with abundant methanogens often contained few ANME archaea
(e.g., core 9,
,
0.2% ANME relative abundance), while bank 1 contained a high relative
abundance of ANME archaea but a low relative abundance of methanogens.
FIG 3
Heat map of dominant families in each sample. Note that members of the methanogenic Rice Cluster II (outlined in
red) were abundant in permafrost and rare in nonpermafrost deposits. Sample core, pit, or bank number and depth in
centimeters are indicated in sample names, and replicates are indicated as R1, R2 and R3. Nonpermafrost samples come
from all depths in locations without observed permafrost, active-layer samples come from the zone of seasonal thaw on
river banks or sediment overlying permafrost, and permafrost samples contained ice cement. Samples moving from left to
right trend from more recent (nonpermafrost) river deposits to the oldest permafrost
fl
oodplain, and the samples at each
location are listed moving from shallow to deep.
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We observed rare reads of potential aerobic methanotrophs in both permafrost and
nonpermafrost deposits, classi
fi
ed as members of the alphaproteobacterial families
Methylocystaceae
and
Methylobacteriaceae
, the betaproteobacterial family
Methylophilaceae
,
and the gammaproteobacterial families
Crenotrichaceae and Methylococcaceae
(see Table
S1 in the supplemental material). However, these taxa were very low in abundance (taken
together, 2.5% of reads in Core1-105-111 and
,
1% of reads in other samples) and therefore
are likely to be minor contributors to methane consumption.
As a complementary approach to corroborate the presence of methanogenic and an-
aerobic methanotrophic taxa, we conducted qPCR analyses to examine the abundance of
the methyl-coenzyme M reductase a-subunit functional gene (
mcrA
). Samples with abun-
dant
Methanomicrobia
16S amplicons (largely Rice Cluster II with minor contributions from
other methanogenic taxa and GoM Arc I) also contained high abundances of the
mcrA
functional gene by qPCR (Fig. 8A), with the relative abundance of
mcrA
following trends
with depth similar to those of the relative abundance of
Methanomicrobia
OTUs (Fig. 8B).
Some samples (Core9-0, Core9-33-38, and Core9-44-46-R3) showed delayed ampli
fi
cation
of
mcrA
(indicating the rare presence of the gene) but contained few or no amplicons
attributed to known methanogenic or anaerobic methanotrophic taxa. We interpreted this
to mean that these samples contained a very low abundance of such taxa (
,
0.001 relative
abundance) whose presence was revealed by qPCR ampli
fi
cation. The samples with the
highest
mcrA
gene abundances of samples with low or no methane-cycling taxa identi
fi
ed
by 16S overlay sediment that both
mcrA
and 16S analyses indicated contains abundant
Methanomicrobia
, with the exception of Core7-85-95. Therefore, while qPCR results sug-
gested that microbes carrying the
mcrA
gene may in fact be present in these samples at
very low abundance, overall
mcrA
qPCR results lend support to metabolic inferences based
on taxonomic classi
fi
cation of methanogen prevalence between sampling sites across the
landscape (Fig. 8B).
We note that complete characterization of methane cycling on the Koyukuk
fl
ood-
plain requires constraining the activity, and not just the presence, of methanogens and
methanotrophs (40). Previous work found that methanogenesis pathways inferred
from 16S sequencing correlated with methane
fl
uxes and
d
13
C measurements made in
FIG 4
Comparison of replicate samples analyzed from (A) Core9-44-46 and (B) Core9-109-115 at the
phylum and family taxonomic levels, displaying the 10 most abundant families for each sample.
River Migration Impacts Permafrost Microbial Community
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permafrost at Stordalen Mire (14). Our
fi
ndings indicated that concentrations of metha-
nogen and methanotroph DNA detectable via 16S sequencing and correlated abun-
dance of the
mcrA
functional gene
a minimum constraint for methane production
and consumption
were found only in permafrost terrain far from the river channel.
Improved understanding of covariance of landscapes with microbial communities can
guide further analysis
such as
fi
eld- and laboratory-based measurements and incuba-
tions to measure methane
fl
ux
required to further characterize and quantify metha-
nogen and methanotroph activity (41).
Soil geochemistry.
To evaluate how sediment properties might in
fl
uence microbial
diversity, we conducted scaled principal-component analysis (sPCA) on our diversity
metrics and metadata, including OC content, stable isotope ratios, sample depth, and
median grain size (Tables 2 and 3). The
fi
rst two sPCA components accounted for 47%
and 19% of the variance in community composition, respectively. Our results show
that the
fi
rst component depended primarily on diversity indices (observed OTUs,
Chao 1, Simpson
s evenness, Fisher
s alpha, Shannon index, and Simpson
s index) and
sample classi
fi
cation as permafrost, active layer, or nonpermafrost (Fig. 5). The second
component is mainly dependent on total organic carbon (TOC), total nitrogen (TN),
and the TOC/TN ratio, with secondary contributions for sample depth and median
grain size (Fig. 6B). Many of these variables are highly correlated; we observed higher
TOC and TN contents in
fi
ner-grained sediment, similar to previous studies on sedi-
ments from other Arctic rivers (42, 43). In turn, point bar deposits tended to be
fi
ner
grained closer to the
fl
oodplain surface (25), so TOC content was also weakly anticorre-
lated with sample depth. However, sample classi
fi
cation as permafrost, active layer, or
nonpermafrost appeared to dominate variations in sediment geochemistry in deter-
mining taxa presence and diversity (Fig. 5). We also noted that in our study area, vege-
tation varies with permafrost occurrence (26), so the changes in microbial community
between frozen and unfrozen sediment may also be a result of different ecological
niches available in the permafrost and nonpermafrost rhizospheres (44).
TABLE 1
Diversity metrics for the 16S ampli
fi
cation data, rare
fi
ed to 4,500 reads
Sample
No. of observed OTUs Shannon diversity index Chao 1 Fisher's alpha Simpson's index Simpson's evenness
Nonpermafrost
Pit2-10
2,686
11.129
3,579
2,808
0.9992
0.4874
Pit5-20
2,720
11.006
4,894
2,910
0.9991
0.4050
Pit6-60
2,552
10.599
5,820
2,444
0.9964
0.1093
Pit8-40
2,777
11.018
6,275
3,090
0.9991
0.4158
Core7-0-5
2,099
10.239
3,102
1,531
0.9973
0.1739
Core7-85-95
1,573
8.960
3,178
859
0.9795
0.0310
Core7-390-400
1,032
8.505
1,848
419
0.9932
0.1421
Active layer
Bank2-10
2,977
11.260
5,887
3,835
0.9994
0.5849
Bank2-230
2,157
9.989
4,619
1,626
0.9900
0.0461
Bank9-Peat
877
6.225
1,901
325
0.9122
0.0130
Bank9-220
1,656
9.662
3,646
946
0.9939
0.0989
Bank9-350
2,215
9.141
4,477
1,727
0.9569
0.0105
Bank9-510
1,010
7.469
1,955
405
0.9686
0.0316
Bank1-Peat
2,171
10.277
3,422
1,650
0.9973
0.1683
Bank1-120
2,308
10.209
7,344
1,901
0.9977
0.1850
Core1-22-28
2,352
10.529
3,894
1,989
0.9981
0.2201
Core9-33-38
1,759
9.055
5,969
1,063
0.9938
0.0913
Core9-44-46-R1
1,474
8.807
2,965
763
0.9895
0.0648
Permafrost
Core1-105-111
678
5.606
1,674
222
0.9016
0.0150
Core9-58-67
1,099
7.470
1,722
464
0.9410
0.0154
Core9-90-97
2,059
9.466
5,570
1,468
0.9915
0.0573
Core9-109-115-R2 1,268
7.596
3,417
587
0.9631
0.0214
Core9-169-174
1,364
7.786
3,892
666
0.9724
0.0265
Douglas et al.
Applied and Environmental Microbiology
October 2021 Volume 87 Issue 20 e01339-21
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We compared soil geochemistry to examine differences between permafrost, active-
layer, and nonpermafrost sediments (Table 2). On average, organic matter in permafrost
samples had a slightly lower
d
13
Cvalueof
2
28.13
6
1.29
%
(measurement mean with
uncertainty reported as one standard deviation) compared to
2
26.89
6
1.21
%
for active-
layer samples and
2
26.96
6
0.49
%
for nonpermafrost samples. TOC was more strongly
correlated with grain size than permafrost presence, with nonpermafrost, active-layer, and
permafrost samples having mean TOC values of 2.61
6
2.49%, 14.22
6
19.44%, and
9.42
6
9.80%, respectively. TN exhibited similar variation within classes; nonpermafrost sam-
pleshadameanTNvalueof0.21
6
0.12%, while active-layer and permafrost samples had
values of 0.46
6
0.40% and 0.58
6
0.45%, respectively. However, permafrost samples dis-
played TOC/TN ratios slightly higher than those of nonpermafrost samples and with less
variability than in the active layer. Mean TOC/TN ratios for permafrost samples were
11.8
6
5.3, while TOC/TN ratios were 21.1
6
19.8foractive-layersamplesand17.1
6
6.1 for
nonpermafrost samples. Therefore, permafrost, active-layer, and nonpermafrost samples
show a similar N content, potentially indicating that N bioavailability is insensitive to perma-
frost thaw by either deepening of the active layer or bank erosion in the Koyukuk
fl
oodplain.
Effects of river migration.
The differences in microbial communities between per-
mafrost, active-layer, and nonpermafrost samples were greater than the variability
within river deposits grouped into coeval scroll bar complexes. Samples from pits 1 to
6 were taken in a transect moving away from the river shoreline within a single scroll
bar complex; these exhibited similar relative abundances of taxa at the family level
(Fig. 3). Similarly, bank 1 and core 1 samples were also taken from the same scroll bar
complex that is currently being eroded by the river; again, samples taken from similar
depths (Bank1-Peat and Core1-22-28; Bank1-120 and Core1-111-115) displayed similar
microbial community compositions at the family level. In contrast, permafrost, active-
FIG 5
Box-and-whisker plots indicating the median and the 25th and 75th percentiles of diversity
index distributions. Samples are grouped as nonpermafrost (no ice cement, only seasonal frost;
n
= 7),
active layer (permafrost cutbanks or samples overlying permafrost;
n
= 11), and permafrost (ground
containing ice cement;
n
= 5), rare
fi
ed to 4,500 OTU reads.
River Migration Impacts Permafrost Microbial Community
Applied and Environmental Microbiology
October 2021 Volume 87 Issue 20 e01339-21
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layer, and nonpermafrost samples contained distinct communities, re
fl
ecting how var-
iations in permafrost occurrence between scroll bar complexes govern microbial com-
munity, more so than variability within a scroll bar complex. Since scroll bar complex
age and permafrost presence were strongly correlated, we were not able to decon-
volve changes in microbial community due to deposit age from the presence or ab-
sence of permafrost.
To understand how river channel migration in
fl
uences the geographic distribution
of microbial communities, we compared samples from a permafrost section of
fl
ood-
plain and eroding riverbank to a nonpermafrost point bar (Fig. 7). As the Koyukuk River
migrated, it eroded permafrost bank 9 while migrating toward core 9 (located on a dis-
tal permafrost
fl
oodplain approximately 5.5 km from the modern river channel) and
depositing new sediment on the nonpermafrost opposing point bar at core 7 (Fig. 7).
FIG 6
(A) NMDS analysis of microbial communities, color coded by sample classi
fi
cation as
permafrost, active layer, or nonpermafrost, demonstrating that microbial communities vary
depending on permafrost presence. The samples are plotted for MDS vectors from a Bray matrix
calculated to maximize the difference between samples based on the rank order of the square root
of taxon abundance for each sample. The vectors for OTUs with
P
values of
,
10
2
5
are displayed,
with the family-level taxonomic classi
fi
cation for each vector in the legend and the number of
vectors for each family shown in parentheses. (B) Results of scaled principal-component analysis
(sPCA), with diversity metrics for samples rare
fi
ed to 4,500 OTU reads, geochemical analyses, and
metadata vectors plotted against the
fi
rst and second principal components (accounting for 47% and
19% of sample variability, respectively).
Douglas et al.
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October 2021 Volume 87 Issue 20 e01339-21
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