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Longitudinal variation of microbial communities
in benthic biofilms and association with hydrological
and physicochemical conditions in glacier-fed streams
Ze Ren
1,3
, Hongkai Gao
2,4
, and James J. Elser
1,5
1
Flathead Lake Biological Station, University of Montana, Polson, Montana 59860 USA
2
School of Life Sciences, Arizona State University, Tempe, Arizona 85281 USA
Abstract: Glacier-fed streams are highly dynamic environments that integrate upstream catchment processes and
are prominent geomorphological and ecological components of alpine landscapes. In these systems, hydrological
and physicochemical factors change significantly with location downstream of the glacier. Variation in microbial
communities in benthic biofilms along such gradients are not well studied, nor do we understand how hydrological
and physicochemical factors drive those changes. We characterized microbial community structure in 2 glacier-fed
streams in the Tianshan Mountains, central Asia, by sequencing 16S ribosomal (r)RNA genes in benthic biofilms
and documented abiotic environmental conditions. Alpha diversity indices of microbes in benthic biofilms (num-
ber of operational taxonomic units, evenness, phylogenetic diversity) were significantly related to hydrological fac-
tors, including distance to glacier (G
D
), glacier area proportion (G
A
), and glacier source proportion (G
S
), and phys-
icochemical factors, including water temperature, pH, dissolved organic C (DOC), total N (TN), and NO
3
. The
dominant phyla were Proteobacteria (46% of operational taxonomic units [OTUs]), Cyanobacteria (16%), Bac-
teroidetes (12%), Actinobacteria (9%), and Acidobacteria (6%). Microbial communities differed longitudinally
along the stream at the OTU level and even at the phylum level. Correlation, canonical correlation, and network
analyses showed that the microbes had significant associations with hydrological (G
A
,G
S
, and G
D
), biogeochemical
(TN, NO
3
, DOC, total P, and soluble reactive P), and physicochemical (pH) factors. These results add to our
knowledge of microbial community structure and potential drivers of that structure in glacier-fed stream ecosys-
tems and provide potentially valuable data for assessing future dynamics as these systems experience further dis-
ruption caused by the influences of climate change.
Key words: benthic biofilm, glacier-fed streams, hydrology, microbial diversity, microbial community, physico-
chemical factors
Glaciers cover ~10% of the Earth’s surface and store ~75%
of the world’s freshwater (Barnett et al. 2005, Gardner et al.
2013, Zemp et al. 2015), thereby providing an important
water resource. Glaciers harbor complex microbial com-
munities including viruses, bacteria, protozoa, and algae
(Schuette et al. 2010, Anesio and Laybourn-Parry 2012,
Liu et al. 2015) that are active in various biogeochemical
processes and that can be released downstream upon ice
melt (Simon et al. 2009, Singer et al. 2012). On glacier fore-
lands, glacier-fed (periglacial) streams integrate upstream
catchment processes and can constitute a prominent geo-
morphological and ecological component in the alpine land-
scape (Wilhelm et al. 2013, Robinson et al. 2016). In partic-
ular, microorganisms can attach to stones or sediments to
form benthic biofilms, building hot spots of microbial diver-
sity and activity in glacier-fed streams (Wilhelm et al. 2014).
However, little is known about patterns of microbial com-
munity structure in periglacial streams or about how these
patterns are related to environmental conditions (Wilhelm
et al. 2013, 2014).
Glacier-fed streams are highly dynamic environments
originating with unstable channels, low temperature, and
low nutrient concentrations (Jacobsen et al. 2014). How-
ever, with increasing distance from the glacier, the contri-
butions of ice melt and snow melt to stream flow decrease
(Brown et al. 2007, Milner et al. 2009, Gao et al. 2016),
E-mail addresses:
3
ze.ren@umontana.edu;
4
To whom correspondence should be addressed, hongkai.gao@asu.edu;
5
jim.elser@flbs.umt.edu
DOI: 10.1086/693133. Received 23 January 2017; Accepted 16 May 2017; Published online 16 June 2017.
Freshwater Science. 2017. 36(3):479–490. © 2017 by The Society for Freshwater Science. 479
thereby influencing stream water temperature, channel
stability, conductivity, and solute chemistry, with major
implications for benthic biota (Milner et al. 2001, 2009,
Hannah et al. 2007, Kuhn et al. 2011). Thus, stream com-
munities are linked to the dynamics of water source contri-
bution (Milner et al. 2009). Any changes in glacier runoff
are likely to affect aquatic community structure and biodi-
versity (Brown et al. 2007, Cauvy-Fraunié et al. 2015). In-
vestigators have begun to document microbial diversity
and activity in glacier ice (Simon et al. 2009, Xiang et al.
2009, Liu et al. 2015) and glacier-fed streams (Wilhelm
et al. 2013, 2014, Kohler et al. 2016) and to evaluate factors
driving variation in microbial biomass and diversity. For
example, Kohler et al. (2016) suggested that nutrient avail-
ability can stimulate growth and alter community struc-
ture of microorganisms in glacier-fed streams. Microbial
diversity in biofilms was higher than in ice but lower than
in the stream water itself and decreased with elevation
(Wilhelm et al. 2013). However, longitudinal patterns of
benthic biofilms in glacier-fed streams are relatively un-
studied, and we lack a good understanding of how longitu-
dinal variations in microbial communities correspond to
various hydrological and physicochemical factors.
Understanding these patterns and processes is especially
importantwith ongoing global climate change because most
glaciers onEarth are receding rapidlyand many are expected
to disappear by 2050 (Zemp et al. 2006, IPCC 2014). Ongo-
ing glacier retreat could lengthen stream channels (Milner
et al. 2009, Robinson et al. 2014), shift water sources (the rel-
ative contributions ofice melt, snowmelt, and ground water)
to streams (Brown et al. 2003), and change their biogeo-
chemistry (Hood and Scott 2008). Previous studies have in-
dicated that glacier retreat has facilitated displacement of
cold-adapted invertebrate species by less cryophilic species
(Brown et al.2007, Finn et al. 2010) and that the regional bio-
diversity of benthic biofilms in glacier-fed streams decreases
with glacier retreat (Wilhelm et al. 2013). Our goal was to
assess longitudinal variations ofmicrobial community struc-
ture and biodiversity in glacier-fed streams in terms of envi-
ronmental change, including the influence of physicochem-
ical and hydrological factors. The results have potential to
increase our knowledge of microbial ecology in glacier-fed
stream ecosystems and document baseline conditions as
these streams increasingly fall under the influence of cli-
mate change.
METHODS
Study area and sampling points
The Tianshan Mountains in central Asia harbor mainly
cirque, hanging, and cirque–hanging glaciers (Han and Liu
1993). Based on data from the 2
nd
Chinese glacier inventory
(Guo et al. 2015), 7934 glaciers are distributed in China’s
Tianshan Mountains with a total area of 7179.77 km
2
and
an ice volume of 707.95 km
3
that account for 16.33, 13.87,
and 15.75% of the total number, total area, and total volume
of glaciers inChina, respectively (Liuet al. 2015). Glaciers are
one of the most important water resources in the Tianshan
Mountain area (Unger-Shayesteh et al. 2013). The total con-
tribution ofsnow and ice melt water to river flows was ~10%
at the outlets of Tianshan Mountain valleys (Aizen et al.
1997). These glaciers have been shrinking rapidly with global
warming (Aizen et al. 2007, He et al. 2015, Liu and Liu 2016,
Wang et al. 2016). For example, Urumqi Glacier No. 1 (GN1,
lat 437060N, long 867490E), situated at the headwater of the
Urumqi River in the eastern Tianshan Mountains, has been
investigated since 1959. GN1 had an area of 1.95 km
2
and a
terminus altitude of 3730 m based on the 1962 glacier inven-
tory. According to data from 2010, the area has shrunk to
1.65 km
2
and the terminus had retreated to an altitude of
3743 m (Zhang et al. 2014). The average ice thickness was
44.50 m in 2012 with a thinning rate of 0.34 m/y during
1981–2012 (Wang et al. 2016).
To investigate longitudinal variations of microbial as-
semblages in glacier-fed streams, 11 sampling points were
distributed along 2 glacier-fed streams at the southern and
northern slopes of the Tianshan Mountains (Fig. 1). Water
chemistry and benthic biofilm samples were collected from
these sampling points in June 2016. Glacier distribution
data were obtained from the 2
nd
Chinese glacier inventory
dataset (Guo et al. 2015). The river channel network and
the catchment boundaries were generated from the Digital
Elevation Model (DEM) with a resolution of 90 m (https://
earthexplorer.usgs.gov/).
Benthic biofilm sampling
At each sampling point, 6 to 9 submerged rocks were
randomly chosen along the river cross section. The benthic
biofilm was removed by vigorously brushing a 4.5-cm-
diameter area from the upper surface of each stone with
a sterilized nylon brush (changed between samples) and
rinsing the slurry with sterile water. Approximately 10 mL
of the mixed slurry was filtered through 0.2-lmmembrane
filters, which were immediately frozen in liquid N in the
field and transported to the laboratory when sampling was
complete. Benthic biofilm samples were stored in the labo-
ratory at 2807C until DNA extraction.
Physicochemical variables
Water temperature, dissolved O
2
(DO), pH, and con-
ductivity were measured in situ at each point with a hand-
held meter (model 80; Yellow Springs Instruments, Yellow
Springs, Ohio). Elevation was measured with a Magellan
(Santa Clara, California) Triton 500 global positioning sys-
tem (GPS) unit. Water samples were collected for nutrient
and dissolved organic C (DOC) analyses. Total N (TN) was
analyzed by the persulfate/ultraviolet oxidation method
(Cai 2007) and NO
3
was measured by ion chromatography
(Cai 2007). Total P (TP) was analyzed with the ammonium
480 | Microbial communities in glacier-fed streams Z. Ren et al.
molybdatemethod after oxidation (Murphy and Riley 1962),
and soluble reactive P (SRP) was analyzed with the ammo-
nium molybdate method (Murphy and Riley 1962). DOC
was analyzed on a TOC analyzer (TOC-VCPH; Shimadzu
Scientific Instruments, Columbia, Maryland).
Hydrological modeling
The contributions of different water sources to stream
flow can significantly affect biotic and abiotic components
of glacier-fed streams (Milner et al. 2001, 2009, Hannah et al.
2007, Kuhn et al. 2011), so quantifying the hydrological con-
tributions of glacier melt to streamflow is useful (Schaner et al.
2012). The discharge hydrograph in our study region was
segregated into different components based on a landscape-
based hydrological model by Gao et al. (2016), who found
that the glaciated area generated 4 to 5more runoff per
unit area than the nonglaciated area. Based on this conclu-
sion, the catchments associated with the 11 sampling
points in our study were classified into 2 landscape types,
glaciated and nonglaciated, and the proportion of glaciated
area (G
A
) in the catchment of each sampling point was cal-
culated (Table 1). The proportion of streamflow from glacier
sources (G
S
) was calculated with the landscape-based hydro-
logical model of Gao et al. (2016). The distance to glacier
(G
D
; Table 1) of each sampling point was measured based
on a map of the river channel network (Fig. 1).
DNA extraction, polymerase chain reaction
(PCR), and sequencing
Bacterial 16S ribosomal (r)RNA genes were analyzed to
assess benthic biofilm community structure and diversity.
Genomic DNA was extracted using the PowerSoil DNA Iso-
lation Kit (MoBio, Carlsbad, California) following manufac-
turer’sprotocols.TheV3–V4 regions of the 16S rRNA gene
were amplified using 338F-ACTCCTACGGGAGGCAGCA
and 806R-GGACTACHVGGGTWTCTAAT(Invitrogen, Vi-
enna, Austria). PCR was performed with an ABI Model
2720 thermal cycler (Applied Biosystems, Foster City, Cal-
ifornia) with the following program:1-min hot start at 807C,
947C for 5 min followed by 30 cycles of denaturation at
947C for 30 s, followed by annealing at 527C for 30 s, exten-
sion at 727C for 90 s, with a final extension step at 727C
for 10 min. Amplified DNA was verified by electrophore-
sis of PCR mixtures in 1.0% agarose in 1X TAE buffer and
purified using the Qiagen gel extraction kit (Qiagen, Hilden,
Germany). Samples were sent for sequencing on a MiSeq
sequencing platform (Illumina, San Diego, California). Se-
quencing data were cleaned with the software package
QIIME (Caporaso et al. 2010) and clustered to operational
taxonomic units (OTUs) with a complete linkage algorithm
on a 97% sequence identity level.
Analysis
The relationships between adiversity indices and hy-
drological factors (G
D
,G
A
, and G
S
) were tested with non-
linear regression to evaluate longitudinal variations of mi-
crobial diversity (SPSS, version 20.0; IBM, Armonk, New
York). The adiversity indices include the number of OTUs,
evenness, and phylogenetic diversity (PD). Correlation anal-
ysis was conducted to assess the relationships between
physicochemical factors and microbial diversity and the re-
lationships between abiotic factors (both hydrological and
Figure 1. Study area and sampling points. Eleven samples were collected from 2 glacier-fed streams in June 2016 in the Tianshan
Mountains, central Asia.
Volume 36 September 2017 | 481
physicochemical factors) and the relative abundance of
phyla (SPSS). The significance values of correlation analy-
sis were adjusted by Bonferroni correction. Canonical cor-
respondence analysis (CCA) was conducted to character-
ize the relationships between microbial communities and
abiotic factors (R, version 3.3.2 and vegan package, ver-
sion 2.4; R Project for Statistical Computing, Vienna, Austria).
Network analysis was conducted to explore the influences
of abiotic factors on each OTU. Spearman correlation coef-
ficients (r)andp-values were calculated for OTUs with rel-
ative abundance >0.01% and physicochemical variables
(hmisc package, version 4.0-1) in R. Only strong (r>0.60)
and significant ( p<0.05) correlations were considered.
These correlations were visualized using Cytoscape (ver-
sion 3.4.0; Shannon et al. 2003). We also calculated several
topological metrics for these physicochemical variables in
the network, including betweenness centrality (an indicator
of a node’s location relative to other nodes that measures
the number of shortest paths through a given node) and de-
gree (an index related to the number of ties from a node to
others).
RESULTS
Longitudinal variation in microbial diversity
in glacier-fed streams
Hydrological and physicochemical characteristics var-
ied longitudinally along streams (Table 1). This variability
probably affected microbial diversity and community struc-
ture in benthic biofilms. The 16S rRNA data set consisted of
127,146 sequences clustered in 7545 OTUs. Number of
OTUs/sampling point varied from 729 (N1; Fig. 1) to 3241
(S4), and OTU accumulation curves at each sampling point
indicated that most bacteria taxa had been covered (Fig. 2).
Diversity indices (number of OTUs, evenness, and phyloge-
netic diversity) had significant increasing power relation-
ships with G
D
(Fig. 3A–C) and decreasing relationships with
G
A
(Fig. 3D–F) and G
S
(Fig. 3G–I). Microbial diversity was
positively associated with temperature, pH, and DOC but
negatively associated with TN and NO
3
(Table 2).
Microbial communities
The dominant phyla (phyla with relative abundances
>5%) were Proteobacteria (46% of OTUs), Cyanobacteria
(16%), Bacteroidetes (12%), Actinobacteria (9%), and Acido-
bacteria (6%). However, relative abundances of microorgan-
isms at the phylum level differed among sampling points
(Fig. 4). At the sampling point closest to the glacier (N1),
the microbial community was dominated by Proteobacteria
(82%). The relative abundances of phyla were associated with
several abiotic factors (Table 3). Proteobacteria were posi-
tively correlated with G
A
and G
S
, whereas Acidobacteria
Figure 2. Rarefaction curves of operational taxonomic units
(OTUs) for each sampling point. No. 5number.
Table 1. Basic hydrological and physicochemical characteristics of the sampling points in 2 glacier-fed streams in the Tianshan Moun-
tains. G
D
5distance to glacier, G
A
5glacier area proportion, G
S
5glacier source proportion, Temp 5temperature, DO 5dissolved O
2
,
Cond 5conductivity, TN 5total N, TP 5total P, SRP 5soluble reactive P, DOC 5dissolved organic C.
Sampling
point
Altitude
(m)
G
D
(km)
G
A
(%)
G
S
(%)
Temp
(7C)
DO
(mg/L) pH
Cond
(lS/cm)
TN
(mg/L)
NO
3
(mg/L)
TP
(mg/L)
SRP
(mg/L)
DOC
(mg/L)
N1 3828 0.01 73.79 76.85 0.6 10.08 7.58 20.9 0.923 0.755 0.014 0.014 0.94
N2 3505 3.86 23.48 51.37 2.7 10.24 7.82 18.6 0.891 0.729 0.009 0.008 0.94
N3 3209 10.95 10.49 32.07 4.1 10.87 7.97 72.4 0.924 0.773 0.020 0.018 1.54
N4 3135 13.31 9.55 30.06 5.8 10.96 7.95 77.5 0.922 0.760 0.009 0.009 1.71
N5 3112 14.51 9.13 29.11 6.4 10.93 7.99 75.9 0.948 0.784 0.010 0.010 1.37
N6 2646 23.83 5.79 20.67 7.5 11.21 7.95 96.4 1.070 0.906 0.021 0.010 1.60
S1 3548 3.28 3.93 15.03 5.3 10.32 8.01 61.5 1.078 0.841 0.012 0.012 1.69
S2 3412 6.51 4.84 17.87 9.4 10.59 8.07 62.2 0.575 0.461 0.011 0.009 3.31
S3 3339 7.98 4.01 15.29 6.4 10.55 8.09 60.5 0.336 0.301 0.011 0.010 3.09
S4 2934 25.84 2.47 10.02 9.0 10.74 8.08 82.1 0.592 0.443 0.012 0.010 2.38
S5 2840 28.83 1.94 8.04 9.5 10.76 8.22 90.6 0.442 0.407 0.013 0.013 3.18
482 | Microbial communities in glacier-fed streams Z. Ren et al.
were negatively correlated with G
A
and G
S
. Actinobacteria,
Chloroflexi, Firmicutes, Gemmatimonadetes, OD1, and
TM7 were negatively correlated with TN and NO
3
, whereas
Cyanobacteria were positively correlated with TN and NO
3
.
Acidobacteria and Gemmatimonadetes were positively cor-
related with pH. Chloroflexi, OD1, and TM7 were positively
correlated with DOC.
CCA analysis was applied to depict spatial differences in
community composition among sampling points in rela-
tion to the effects of physicochemical and hydrological fac-
tors (Fig. 5). N1 and S1 microbial communities (the 2 sam-
pling points closest to the glacier) differed from other
sampling points. The first 2 axes accounted for 32.26% of
the variance (axis 1: 18.50%; axis 2: 13.76%). G
S
,TN,DOC,
temperature, and pH were the most significant abiotic fac-
tors associated with the distribution of microorganisms
(Monte Carlo test, p<0.05; Fig. 5). Axis 1 was mainly de-
fined by TN (negatively), temperature (positively), and DOC
(positively). Axis 2 was mainly defined by G
S
(positively) and
pH (negatively). In general, sampling points except S1 and
N1 were distributed along Axis 1. Furthermore, sampling
points in the northern stream were distributed mainly in
Figure 3. Power relationships between number of operational taxonomic units (OTUs) (A, D, G), evenness (B, E, H), and phyloge-
netic diversity (C, F, I) with distance to glacier (A–C), % glacier area (D–F), and % glacier source (G–I) in benthic biofilm communi-
ties along 2 glacier-fed streams in the Tianshan Mountains.
Table 2. Relationships between microbial diversity indices (number of operational taxonomic units [OTUs], evenness, and phyloge-
netic diversity [PD]) and various physicochemical factors. See Table 1 for abbreviations and units for physicochemical variables.
*5p<0.05, ** 5p<0.01.
Diversity Altitude Temp DO pH Cond TN NO
3
TP SRP DOC
Number of OTUs 20.537 0.810** 0.310 0.757** 0.488 20.717* 20.741** 20.357 20.399 0.705*
Evenness 20.427 0.695* 0.260 0.812** 0.409 20.716* 20.714* 20.421 20.238 0.662*
PD 20.427 0.727* 0.22 0.741** 0.388 20.796** 20.805** 20.421 20.287 0.708*
Volume 36 September 2017 | 483
the negative direction along Axis 1 and the sampling points
in the southern stream were distributed mainly in the pos-
itive direction along that axis (Fig. 5).
Network analysis
Connections among OTUs and abiotic factors also were
explored by network analysis (Fig. 6). The network com-
prised 531 nodes (including 13 abiotic factors and 518 OTUs)
and 1245 edges (Fig. 6). TN and NO
3
were associated with
the maximum number of OTU nodes, followed by DOC,
temperature, G
D
,pH,G
S
,G
A
, TP, DO, SRP, altitude, and
conductivity (Fig. 6, Table 4). TN and NO
3
were associated
with a wide range of nodes with mainly negative relation-
ships, whereas DOC was positively associated with a wide
range of nodes. pH was mostly associated with nodes be-
longing to Proteobacteria with both negative and positive
relationships. Hydrological factors (G
D
,G
S
, and G
A
)were
mainly positively associated with nodes, most of which be-
longed to Proteobacteria. TP had positive relationships with
nodes belonging to Cyanobacteria. SRP had positive rela-
tionships with nodes belonging to Bacteroidetes and nega-
tive relationships with others. These results were consistent
with the results of correlation analysis and CCA.
DISCUSSION
Glaciers are in retreat worldwide, making a better un-
derstanding of the ecological status of glacier-fed streams
necessary. These streams probably are among the most vul-
nerable environments as climate change continues to un-
fold (Smith et al. 2001, Cauvy-Fraunié et al. 2015). Glacier-
fed streams are dynamic environments and have heteroge-
neous habitats (Milner et al. 2001, Hannah et al. 2007) in
which hydrological and physicochemical factors drive shifts
in benthic microbial communities. These physicochem-
ical traits in concert with biological traits and physiological
tolerances of different microorganisms act as environmen-
tal filters in benthic biofilms (Fig. 6). In the 2 glacier-fed
streams studied in the Tianshan Mountains, the dominant
microbial phyla were Proteobacteria, Cyanobacteria, Bac-
teroidetes, Actinobacteria, and Acidobacteria (Fig. 4), which
are typical of freshwater ecosystems in general (Tamames
et al. 2010, Wilhelm et al. 2013) and are common in ice eco-
systems (Xiang et al. 2009, Liu et al. 2015). Both microbial
community composition and diversity differed along the
stream and were correlated with hydrological and physico-
chemical factors.
In glacier-fed streams, the contribution of different wa-
ter sources shifts with increasing distance from the glacier
(Milner et al. 2009, Gao et al. 2016), thereby influencing
the abiotic habitat template, including water temperature,
channel stability, conductivity, and nutrients (Milner et al.
2001). Downstream increases in channel stability and wa-
ter temperature were associated with increases in aquatic
biodiversity in previous studies of glacier-fed streams (Mil-
ner et al. 2001, Jacobsen et al. 2010). Such patterns are sup-
ported by our data from the Tianshan Mountains. Various
diversity indices (number of OTUs, evenness, and phyloge-
netic diversity) had positive power relationships with G
D
and negative power relationships with G
A
and G
S
(Fig. 3A–I),
Figure 4. The relative abundance of bacterial phyla at each sampling point. Only phyla with relative abundance >1% are shown.
Unclassified, unidentified, and taxa that have a relative abundance <1% are grouped as “Others”.
484 | Microbial communities in glacier-fed streams Z. Ren et al.
Table 3. Relationships between hydrological factors and the relative abundance of dominant phyla (p-values were adjusted by Bonferroni correction). See Table 1 for
abbreviations and units for physicochemical variables. * 5p<0.05, ** 5p<0.01.
Taxon G
A
G
S
G
D
Altitude DO pH Cond Temp TN NO
3
TP SRP DOC
Acidobacteria 20.655* 20.661* 0.117 20.098 20.007 0.665* 0.207 0.462 20.487 20.533 20.592 20.433 0.494
Actinobacteria 20.206 20.349 0.411 20.213 0.065 0.397 0.216 0.547 20.680* 20.731* 20.452 20.330 0.560
Bacteroidetes 20.502 20.422 0.108 20.162 0.148 0.459 0.304 0.068 0.108 0.128 0.174 0.437 0.059
Chloroflexi 20.385 20.484 0.351 20.25 0.113 0.571 0.245 0.492 20.850** 20.850** 20.439 20.321 0.659*
Cyanobacteria 20.221 20.051 0.016 20.251 0.283 20.106 0.151 20.158 0.694* 0.716* 0.517 0.015 20.475
Firmicutes 20.272 20.426 0.681* 20.445 0.191 0.508 0.394 0.575 20.600 20.622* 20.318 20.150 0.462
GN02 0.809** 0.576 20.162 0.406 20.511 20.543 20.435 20.371 20.151 20.168 20.04 0.233 20.137
Gemmatimonadetes 20.423 20.513 0.617* 20.414 0.210 0.630* 0.403 0.679* 20.578 20.606* 20.365 20.157 0.538
OD1 20.344 20.446 0.259 20.132 0.002 0.466 0.145 0.612* 20.690* 20.755** 20.385 20.396 0.643*
Proteobacteria 0.794** 0.669* 20.36 0.499 20.389 20.579 20.46 20.364 20.058 20.051 20.107 0.172 20.106
TM7 20.377 20.460 0.033 20.020 0.007 0.506 0.105 0.546 20.820** 20.840** 20.317 20.364 0.811**
Verrucomicrobia 20.483 20.413 0.550 20.610* 0.529 0.491 0.430 0.568 20.425 20.367 20.315 20.636* 0.423
Thermi 20.003 0.230 20.449 0.289 20.171 20.268 20.308 20.554 0.575 0.571 0.236 0.317 20.555
indicating a strong rolefor hydrological factors in influencing
microbial diversity in these periglacial streams. These results
are in line with a study of glacier-fed streams in the Austrian
Alps in which microbial diversity decreased with elevation
(Wilhelm et al. 2013) and with studies of macroinverte-
brates in which species richness increased with increasing
distance from the glacier (Milner et al. 2001, Jacobsen and
Dangles 2012).
pH, temperature, DOC, TN, and NO
3
had close rela-
tionships with microbial diversity and community compo-
sition in our study. Streamwater pH has been proposed as
a variable that effectively integrates a number of stream at-
tributes that could predict much of the variability in mi-
crobial communities (Fierer et al. 2007). Indeed, significant
correlations between pH and microbial communities have
been observed in both aquatic and terrestrial ecosystems
(Hörnström 2002, Fierer and Jackson 2006, Fierer et al.
2007). However, the mechanisms underpinning these rela-
tionships are still unclear (Fierer et al. 2007). In glacier-fed
streams, terrestrial sources of DOC can be significant parts
of ecosystem C budgets. This DOC is carried by multiple
flow pathways from the surrounding watershed, including
shallow pathways through organic-C-rich soil horizons
(Gremm and Kaplan 1998, Ågren et al. 2010, McLaughlin
and Kaplan 2013). The input of terrestrial DOC can pro-
mote the growth of heterotrophic biofilm bacteria in stream
ecosystems (Battin et al. 1999, Risse-Buhl et al. 2012). Sup-
plies of potentially limiting nutrients, such as N and P, prob-
ably also play a role in shaping microbial biofilms in glacier-
fed streams. N in glacier-fed streams probably comes mainly
from allochthonous inputs derived from the melting gla-
ciers themselves, with some originating from N-fixation by
cyanobacteria (Howard-Williams et al. 1989). Glaciers accu-
mulate a range of chemicals from the atmosphere, so alpine
glacier meltwater contains variable amounts of NO
3
(May-
ewski et al. 1986, Blais et al. 2001) from atmospheric deposi-
tion. Other processes, such as sublimation and evaporation
on glaciers, appear to concentrate NO
3
and then deliver
high-NO
3
meltwater to downstream aquatic ecosystems (Sa-
ros et al. 2010). However, P is mainly associated with poorly
weathering calcite/apatite-rich mineral phases (Hodson et al.
2004), suggesting that total P and SRP concentrations would
be low in the glacier-fed streams (Hood and Scott 2008). This
N-rich but P-poor environment would result in high N∶P
ratios, which suggests that microbial growth in glacier-fed
streamsshould beP-limited, affecting the structure and func-
tion of microbial assemblages in these streams. This possibil-
ity remains to be tested experimentally.
Microbial taxa in the Tianshan Mountain glacier-fed
streams showed various relationships with abiotic factors,
especially with pH, nutrients (TN, NO
3
, and DOC), and hy-
drological factors (G
D
,G
S
, and G
A
). Species-sorting by local
environmental conditions could be one of the mechanisms
for observed variations in the microbial communities. We
hypothesize that microbes in glacier-fed streams have spe-
cialized physiological and functional adaptations to the
particular hydrological and physicochemical environments
of these harsh systems. These adaptations would contrib-
ute to strong longitudinal shifts in microbial community
structure and correlation with physicochemical conditions.
In future studies, we will attempt to document these physi-
ological and functional adaptations via metagenomic se-
quencing.
Some differences in community composition along the
glacier-fed stream can be attributed to influences of the meta-
community, which is the set of local communities linked by
dispersal (Leibold et al. 2004, Wilhelm et al. 2013). In the
framework of metacommunity theory (Leibold et al. 2004),
the numerous sources of microorganisms from the larger
metacommunity also could be a mechanism for variation of
benthic biofilm assemblages in the glacier-fed streams that
we studied. In glacier-fed streams, microorganisms can come
from various sources, such as cryoconite holes (Edwards
et al. 2011), glacial ice (Miteva 2008), groundwater (Brunke
and Gonser 1997, Griebler and Lueders 2009), and the ad-
jacent terrestrial environment (Hullar et al. 2006, Schuette
et al. 2010). Cryoconite holes are extensively distributed on
glacier ice surfaces and bathed with meltwater to some ex-
tent (Fountain et al. 2004). Both glacier ice and cryoconite
holes harbor diverse bacterial communities (Sawstrom et al.
2002, Miteva 2008), members of which can be delivered
downstream by supraglacial meltwater over the glacier sur-
face (Edwards et al. 2011). Headwater streams also are inti-
mately associated with terrestrial ecosystems. Bacteria and
Archaea in a headwater stream are similar to communities
Figure 5. Canonical correspondence analysis (CCA) biplot
of microbial community composition at the operational taxo-
nomic unit (OTU). Lines show significant (Monte Carlo test, p<
0.05) correlations of physicochemical and hydrological factors
with stream microbial communities. CCA1 and CCA2 have
eigenvalues equal to 0.394 and 0.293 with 18.50 and 13.76% of
variance explained, respectively. See Fig. 1 and Table 1 for sam-
pling point names and variable abbreviations.
486 | Microbial communities in glacier-fed streams Z. Ren et al.
in soil water (Crump et al. 2012). Thus, soil bacteria also
could influence bacterial communities in headwater streams
through immigration or advection (Crump et al. 2012, Ruiz-
González et al. 2015).
Conclusion
Rapid shrinking of glaciers caused by climate change is
one of the most serious threats to glacier-fed stream eco-
systems because it disrupts runoff amount and timing, water
source contributions, and physicochemical habitats. Al-
tered water-source contributions and physiochemical con-
ditions drive significant shifts in microbial diversity and
community composition in benthic biofilms and poten-
tially have widespread implications for ecosystem structure
and function in alpine catchments. In a study substi-
tuting space for time, Wilhelm et al. (2013) found that lon-
gitudinal patterns in microbial communities in benthic bio-
films in glacier-fed streams may act as sentinels of climate
change, indicating the shifts in microbial diversity and
Figure 6. Network analysis showing connectedness between operational taxonomic units (OTUs) with relative abundance >0.01% and
abiotic factors. Only strong (Spearman’s correlation, r>F0.60F) and statistically significant (p<0.05) correlations are shown. Blue solid
curves indicate positive associations and brown dashed lines indicate negative associations. See Table 1 for variable abbreviations.
Table 4. Topological metrics for physicochemical parameters in the network analysis. See Table 1 for abbreviations and units for
physicochemical variables. * 5p<0.05, ** 5p<0.01.
Metric G
A
G
S
G
D
Altitude DO pH Cond Temp TN NO
3
TP SRP DOC
Betweenness 0.039 0.038 0.238 0.020 0.058 0.085 0.001 0.135 0.266 0.363 0.115 0.068 0.171
Degree 44 49 106 18 23 86 11 119 263 282 36 22 186
Volume 36 September 2017 | 487
community composition in alpine streams that can be ex-
pected as glaciers disappear from the landscape in coming
decades.
ACKNOWLEDGEMENTS
Author contributions: ZR contributed to the main work of
study design, sample collection, data analyses, and manuscript
preparation. HG contributed to the sample collection, hydrolog-
ical model analysis, and manuscript preparation. JJE contributed
to manuscript preparation and revision.
We are grateful to E. K. Moody for suggestions on writing and
analysis, Q. D. Zhao, T. D. Han, and Y. Ren for assistance in the
field. This work was supported by the State Key Laboratory of
Cryospheric Sciences, Cold and Arid Regions Environment and
Engineering Research Institute, Chinese Academy of Sciences
(SKLCS-OP-2016-04).
LITERATURE CITED
Ågren, A., M. Haei, S. J. Köhler, K. Bishop, and H. Laudon. 2010.
Regulation of stream water dissolved organic carbon (DOC)
concentrations during snowmelt; the role of discharge, winter
climate and memory effects. Biogeosciences 7:2901–2913.
Aizen, V. B., E. M. Aizen, and V. A. Kuzmichonok. 2007. Glaciers
and hydrological changes in the Tien Shan: simulation and
prediction. Environmental Research Letters 2:45019.
Aizen, V. B., E. M. Aizen, J. M. Melack, and J. Dozier. 1997. Cli-
matic and hydrologic changes in the Tien Shan, Central Asia.
Journal of Climate 10:1393–1404.
Anesio, A. M., and J.Laybourn-Parry. 2012. Glaciers and ice sheets
as a biome. Trends in Ecology and Evolution 27:219–225.
Barnett, T. P., J. C. Adam, and D. P. Lettenmaier. 2005. Potential
impacts of a warming climate on water availability in snow-
dominated regions. Nature 438:303–309.
Battin, T. J., A. Butturini, and F. Sabater. 1999. Immobilization
and metabolism of dissolved organic carbon by natural sedi-
ment biofilms in a Mediterranean and temperate stream. Aquatic
Microbial Ecology 19:297–305.
Blais,J.M.,D.W.Schindler,D.C.Muir,M.Sharp,D.Donald,M.
Lafrenière,E.Braekevelt,andW.M.Strachan.2001.Meltinggla-
ciers: a major source of persistent organochlorines to subalpine
Bow Lake in Banff National Park, Canada. Ambio 30:410–415.
Brown, L. E., D. M. Hannah, and A. M. Milner. 2003. Alpine stream
habitat classification: an alternative approach incorporating the
role of dynamic water source contributions. Arctic, Antarctic,
and Alpine Research 35:313–322.
Brown, L. E., D. M. Hannah, and A. M. Milner. 2007. Vulnerability
of alpine stream biodiversity to shrinking glaciers and snow-
packs. Global Change Biology 13:958–966.
Brunke, M., and T. Gonser. 1997. The ecological significance of
exchange processes between rivers and groundwater. Fresh-
water Biology 37:1–33.
Cai, Q. H. 2007. Protocols for standard observation and measure-
ment in aquatic ecosystems. China Environmental Science
Press, Beijing, China.
Caporaso, J. G., J. Kuczynski, J. Stombaugh, K. Bittinger, F. D.
Bushman, E. K. Costello, N. Fierer, A. G. Peña, J. K. Goodrich,
J. I. Gordon, G. A. Huttley, S. T. Kelley, D. Knights, J. E. Koenig,
R. E. Ley, C. A. Lozupone, D. McDonald, B. D. Muegge, M.
Pirrung, J. Reeder, J. R. Sevinsky, P. J. Turnbaugh, W. A. Wal-
ters, J. Widmann, T. Yatsunenko, J. Zaneveld, and R. Knight.
2010. QIIME allows analysis of high-throughput community
sequencing data. Nature Methods 7:335–336.
Cauvy-Fraunié, S., R. Espinosa, P. Andino, D. Jacobsen, and O.
Dangles. 2015. Invertebrate metacommunity structure and
dynamics in an Andean glacial stream network facing climate
change. PLoS ONE 10:e1367938.
Crump, B. C., L. A. Amaral-Zettler, and G. W. Kling. 2012. Mi-
crobial diversity in arctic freshwaters is structured by inocula-
tion of microbes from soils. ISME Journal 6:1629–1639.
Edwards, A., A. M. Anesio, S. M. Rassner, B. Sattler, B. Hubbard,
W. T. Perkins, M. Young, and G. W. Griffith. 2011. Possible
interactions between bacterial diversity, microbial activity and
supraglacial hydrology of cryoconite holes in Svalbard. ISME
Journal 5:150–160.
Fierer, N., and R. B. Jackson. 2006. The diversity and biogeogra-
phy of soil bacterial communities. Proceedings of the National
Academy of Sciences of the United States of America 103:
626–631.
Fierer, N., J. L. Morse, S. T. Berthrong, E. S. Bernhardt, and R. B.
Jackson. 2007. Environmental controls on the landscape-scale
biogeography of stream bacterial communities. Ecology 88:
2162–2173.
Finn, D. S., K. Raesaenen, and C. T. Robinson. 2010. Physical and
biological changes to a lengthening stream gradient following
a decade of rapid glacial recession. Global Change Biology 16:
3314–3326.
Fountain, A. G., M. Tranter, T. H. Nylen, K. J. Lewis, and D. R.
Mueller. 2004. Evolution of cryoconite holes and their contri-
bution to meltwater runoff from glaciers in the McMurdo Dry
Valleys, Antarctica. Journal of Glaciology 50:35–45.
Gao, H., T. Han, Y. Liu, and Q. Zhao. 2016. Use of auxiliary data
of topography, snow and ice to improve model performance
in a glacier-dominated catchment in Central Asia. Hydrology
Research 48:nh2016242.
Gardner, A. S., G. Moholdt, J. G. Cogley, B. Wouters, A. A.
Arendt, J. Wahr, E. Berthier, R. Hock, W. T. Pfeffer, G. Kaser,
S. R. Ligtenberg, T. Bolch, M. J. Sharp, J. O. Hagen, M. R. van
den Broeke, and F. Paul. 2013. A reconciled estimate of glacier
contributions to sea level rise: 2003 to 2009. Science 340:852–
857.
Gremm, T. J., and L. A. Kaplan. 1998. Dissolved carbohydrate
concentration, composition, and bioavailability to microbial
heterotrophs in stream water. Acta Hydrochimica et Hydro-
biologica 26:167–171.
Griebler, C., and T. Lueders. 2009. Microbial biodiversity in
groundwater ecosystems. Freshwater Biology 54:649–677.
Guo, W. Q., S. Y. Liu, J. L. Xu, L. Z. Wu, D. H. ShangGuan, X. J.
Yao, J. F. Wei, W. J. Bao, P. C. Yun, Q. Liu, and Z. L. Jiang.
2015. The second Chinese glacier inventory: data, methods
and results. Journal of Glaciology 61:357–372.
Han, T. D. and C. H. Liu. 1993. Resource and distribution pattern
of glaciers in the Tianshan Mountains, China. Arid Land Ge-
ography 16:11–18.
Hannah, D. M., L. E. Brown, A. M. Milner, A. M. Gurnell, G. R.
McGregor, G. E. Petts, B. P. G. Smith, and D. L. Snook. 2007.
Integrating climate–hydrology–ecology for alpine river systems.
488 | Microbial communities in glacier-fed streams Z. Ren et al.
Aquatic Conservation: Marine and Freshwater Ecosystems 17:
636–656.
He, Y., T. Yang, Q. Ji, J. Chen, G. Zhao, and W. Shao. 2015. Gla-
cier variation in response to climate change in Chinese
Tianshan Mountains from 1989 to 2012. Journal of Mountain
Science 12:1189–1202.
Hodson, A., P. Mumford, and D. Lister. 2004. Suspended sedi-
ment and phosphorus in proglacial rivers: bioavailability and
potential impacts upon the P status of ice-marginal receiving
waters. Hydrological Processes 18:2409–2422.
Hood, E., and D. Scott. 2008. Riverine organic matter and nutri-
ents in southeast Alaska affected by glacial coverage. Nature
Geoscience 1:583–587.
Hörnström, E. 2002. Phytoplankton in 63 limed lakes in compar-
ison with the distribution in 500 untreated lakes with varying
pH. Hydrobiologia 470:115–126.
Howard-Williams, C., J. C. Priscu, and W. F. Vincent. 1989. Ni-
trogen dynamics in two Antarctic streams. Hydrobiologia
172:51–61.
Hullar, M., L. A. Kaplan, and D. A. Stahl. 2006. Recurring sea-
sonal dynamics of microbial communities in stream habitats.
Applied and Environmental Microbiology 72:713–722.
IPCC (Intergovernmental Panel on Climate Change). 2014. Cli-
mate Change 2014: Synthesis Report. Contribution of Work-
ing Groups I, II and III to the 5
th
Assessment Report of the
Intergovernmental Panel on Climate Change. Intergovern-
mental Panel on Climate Change, Geneva, Switzerland.
Jacobsen, D., S. Cauvy-Fraunié, P. Andino, R. Espinosa, D. Cueva,
and O. Dangles. 2014. Runoff and the longitudinal distribu-
tion of macroinvertebrates in a glacier-fed stream: implica-
tions for the effects of global warming. Freshwater Biology
59:2038–2050.
Jacobsen, D., and O. Dangles. 2012. Environmental harshness and
global richness patterns in glacier-fed streams. Global Ecology
and Biogeography 21:647–656.
Jacobsen, D., O. Dangles, P. Andino, R. Espinosa, L. Hamerlik,
and E. Cadier. 2010. Longitudinal zonation of macroinverte-
brates in an Ecuadorian glacier-fed stream: do tropical glacial
systems fit the temperate model? Freshwater Biology 55:1234–
1248.
Kohler, T. J., D. J. Van Horn, J. P. Darling, C. D. Takacs-Vesbach,
and D. M. McKnight. 2016. Nutrient treatments alter micro-
bial mat colonization in two glacial meltwater streams from
the McMurdo Dry Valleys, Antarctica. FEMS Microbiology
Ecology 92:w49.
Kuhn, J., P. Andino, R. Calvez, R. Espinosa, L. Hamerlik, S. Vie, O.
Dangles, and D. Jacobsen. 2011. Spatial variability in macro-
invertebrate assemblages along and among neighbouring equa-
torial glacier-fed streams. Freshwater Biology 56:2226–2244.
Leibold, M. A., M. Holyoak, N. Mouquet, P. Amarasekare, J. M.
Chase, M. F. Hoopes, R. D. Holt, J. B. Shurin, R. Law, D. Tilman,
M. Loreau, and A. Gonzalez. 2004. The metacommunity con-
cept: a framework for multi-scale community ecology. Ecology
Letters 7:601–613.
Liu, Q., and S. Liu. 2016. Response of glacier mass balance to cli-
mate change in the Tianshan Mountains during the second
half of the twentieth century. Climate Dynamics 46:303–316.
Liu, Q., Y. Zhou, and Y. Xin. 2015. High diversity and distinctive
community structure of bacteria on glaciers in China revealed
by 454 pyrosequencing. Systematic and Applied Microbiology
38:578–585.
Liu, S. Y., X. J. Yao, W. Q. Guo, J. L. Xu, D. H. Shangguan, J. F.
Wei, W. J. Bao, and L. Z. Wu. 2015. The contemporary gla-
ciers in China based on the Second Chinese Glacier Inventory.
Acta Geographica Sinica 70:3–16.
Mayewski, P. A., W. B. Lyons, M. J. Spencer, M. Twickler, W.
Dansgaard, B. Koci, C. I. Davidson, and R. E. Honrath. 1986.
Sulfate and nitrate concentrations from a south Greenland
ice core. Science 232:975–977.
McLaughlin, C., and L. A. Kaplan. 2013. Biological lability of dis-
solved organic carbon in stream water and contributing ter-
restrial sources. Freshwater Science 32:1219–1230.
Milner, A. M., J. E. Brittain, E. Castella, and G. E. Petts. 2001.
Trends of macroinvertebrate community structure in glacier-
fed rivers in relation to environmental conditions: a synthesis.
Freshwater Biology 46:1833–1847.
Milner, A. M., L. E. Brown, and D. M. Hannah. 2009. Hydroeco-
logical response of riversystems to shrinkingglaciers. Hydrolog-
ical Processes 23:62–77.
Miteva, V. 2008. Bacteria in snow and glacier ice. Pages 31–50 in
R. Margesin, F. Schinner, J. C. Marx, and C. Gerday (editors).
Psychrophiles: from biodiversity to biotechnology. Springer,
Berlin, Germany.
Murphy, J., and J. P. Riley. 1962. A modified single solution method
for the determination of phosphate in natural waters. Analytica
Chimica Acta 26:31–36.
Risse-Buhl, U., N. Trefzger, A. Seifert, W. Schoenborn, G. Gleixner,
and K. Kuesel. 2012. Tracking the autochthonous carbon trans-
fer in stream biofilm food webs. FEMS Microbiology Ecology 79:
118–131.
Robinson, C. T., C. Thompson, and M. Freestone. 2014. Eco-
system development of streams lengthened by rapid glacial
recession. Fundamental and Applied Limnology 185:235–
246.
Robinson, C. T., D. Tonolla, B. Imhof, R.Vukelic, and U.Uehlinger.
2016. Flow intermittency, physico-chemistry and function of
headwater streams in an Alpine glacial catchment. Aquatic Sci-
ences 78:327–341.
Ruiz-González, C., J. P. Niño-García, and P. A. Del Giorgio. 2015.
Terrestrial origin of bacterial communities in complex boreal
freshwater networks. Ecology Letters 18:1198–1206.
Saros, J. E., K. C. Rose, D. W. Clow, V. C. Stephens, A. B. Nurse,
H. A. Arnett, J. R. Stone, C. E. Williamson, and A. P. Wolfe.
2010. Melting alpine glaciers enrich high-elevation lakes with
reactive nitrogen. Environmental Science and Technology 44:
4891–4896.
Sawstrom, C., P. Mumford, W. Marshall, A. Hodson, and J.
Laybourn-Parry. 2002. The microbial communities and pri-
mary productivity of cryoconite holes in an Arctic glacier (Sval-
bard 79 degrees N). Polar Biology 25:591–596.
Schaner, N., N. Voisin, B. Nijssen, and D. P. Lettenmaier. 2012.
The contribution of glacier melt to streamflow. Environmen-
tal Research Letters 7:034029.
Schuette, U. M. E., Z. Abdo, J. Foster, J. Ravel, J. Bunge, B. Solheim,
and L. J. Forney. 2010. Bacterial diversity in a glacier foreland of
the high Arctic. Molecular Ecology 191:54–66.
Shannon, P., A. Markiel, O. Ozier, N. S. Baliga, J. T. Wang, D.
Ramage, N. Amin, B. Schwikowski, and T. Ideker. 2003. Cyto-
Volume 36 September 2017 | 489
scape: a software environment for integrated models of biomo-
lecular interaction networks. Genome Research 13:2498–2504.
Simon, C., A. Wiezer, A. W. Strittmatter, and R. Daniel. 2009.
Phylogenetic diversity and metabolic potential revealed in a
glacier ice metagenome. Applied and Environmental Microbi-
ology 75:7519–7526.
Singer, G. A., C. Fasching, L. Wilhelm, J. Niggemann, P. Steier, T.
Dittmar, and T. J. Battin. 2012. Biogeochemically diverse or-
ganic matter in Alpine glaciers and its downstream fate. Na-
ture Geoscience 5:710–714.
Smith, B. P., D. M. Hannah, A. M. Gurnell, and G. E. Petts. 2001.
A hydrogeomorphological framework for the ecology of al-
pine proglacial rivers. Freshwater Biology 46:1579–1596.
Tamames, J., J. Jose Abellán, M. Pignatelli, A. Camacho, and A.
Moya. 2010. Environmental distribution of prokaryotic taxa.
BMC Microbiology 10:85.
Unger-Shayesteh, K., S. Vorogushyn, D. Farinotti, A. Gafurov, D.
Duethmann, A. Mandychev, and B. Merz. 2013. What do we
know about past changes in the water cycle of central Asian
headwaters? A review. Global and Planetary Change 110:4–25.
Wang, P., Z. Li, H. Li, H. Yao,C. Xu, P. Zhou, S. Jin, and W. Wang.
2016. Analyses of recent observations of Urumqi Glacier No. 1,
Chinese Tianshan Mountains. Environmental Earth Sciences
75:1–11.
Wang,P.,Z.Li,W.Wang,H.Li,L.Wu,B.Huai,P.Zhou,S.Jin,andL.
Wang. 2016. Comparison of changes in glacier area and thickness
on the northern and southern slopes of Mt. Bogda, eastern Tian-
shan Mountains. Journal of Applied Geophysics 132:164–173.
Wilhelm, L., K. Besemer, C. Fasching, T. Urich, G. A. Singer, C.
Quince, and T. J. Battin. 2014. Rare but active taxa contribute
to community dynamics of benthic biofilms in glacier-fed
streams. Environmental Microbiology 16:2514–2524.
Wilhelm, L., G. A. Singer, C. Fasching, T. J. Battin, and K. Besemer.
2013. Microbial biodiversity in glacier-fed streams. ISME Jour-
nal 7:1651–1660.
Xiang, S., T. Shang, Y. Chen, Z. Jing, and T. Yao. 2009. Dominant
bacteria and biomass in the Kuytun 51 Glacier. Applied and
Environmental Microbiology 75:7287–7290.
Zemp, M., H. Frey, I. Gärtner-Roer, S. U. Nussbaumer, M.
Hoelzle, F. Paul, W. Haeberli, F. Denzinger, A. P. Ahlstrøm,
B. Anderson, S. Bajracharya, C. Baroni, L. N. Braun, B. E. Cá-
ceres, G. Casassa, G. Cobos, L. R. Dávila, H. Delgado Grana-
dos, M. N. Demuth, L. Espizua, A. Fischer, K. Fujita, B. Gadek,
A. Ghazanfar, J. O. Hagen, P. Holmlund, N. Karimi, Z. Li, M.
Pelto, P. Pitte, V. V. Popovnin, C. A. Portocarrero,R. Prinz, C. V.
Sangewar, I. Severskiy, O. Sigurðsson, A. Soruco, R. Usubaliev,
and C. Vincent. 2015. Historically unprecedented global glacier
decline in the early 21
st
century. 2015. Journal of Glaciology
61:745–762.
Zemp, M., W. Haeberli, M. Hoelzle, and F. Paul. 2006. Alpine gla-
ciers to disappear within decades? Geophysical Research Let-
ters 33:L1350413.
Zhang, G., Z. Li, W. Wang, and W. Wang. 2014. Rapid decrease
of observed mass balance in the Urumqi Glacier No. 1, Tian-
shan Mountains, central Asia. Quaternary International 349:
135–141.
490 | Microbial communities in glacier-fed streams Z. Ren et al.
