FEMS Microbiology Ecology, 92, 2016, fiw049
doi: 10.1093/femsec/fiw049
Advance Access Publication Date: 2 March 2016
Research Article
RESEARCH ARTICLE
Nutrient treatments alter microbial mat colonization
in two glacial meltwater streams from the McMurdo
Dry Valleys, Antarctica
Tyler J. Kohler1,2,∗ , David J. Van Horn3 , Joshua P. Darling1 ,
Cristina D. Takacs-Vesbach3 and Diane M. McKnight1
1
Institute of Arctic and Alpine Research, University of Colorado, 1560 30th Street, Boulder, CO 80303, USA,
Faculty of Science, Department of Ecology, Charles University in Prague, Viničná 7, 12844 Prague 2, Prague,
Czech Republic and 3 Department of Biology, University of New Mexico, Albuquerque, NM 87131, USA
2
∗
Corresponding author: Faculty of Science, Department of Ecology, Charles University in Prague, Viničná 7, 12844 Prague 2, Prague, Czech Republic.
Tel: +4202219511069; E-mail: [email protected]
One sentence summary: Nutrients released due to warmer temperatures will likely stimulate growth and shift the species composition of microbial
communities in Antarctic glacial meltwater streams.
Editor: Dirk Wagner
ABSTRACT
Microbial mats are abundant in many alpine and polar aquatic ecosystems. With warmer temperatures, new hydrologic
pathways are developing in these regions and increasing dissolved nutrient fluxes. In the McMurdo Dry Valleys,
thermokarsting may release both nutrients and sediment, and has the potential to influence mats in glacial meltwater
streams. To test the role of nutrient inputs on community structure, we created nutrient diffusing substrata (NDS) with agar
enriched in N, P and N + P, with controls, and deployed them into two Dry Valley streams. We found N amendments (N and
N + P) to have greater chlorophyll-a concentrations, total algal biovolume, more fine filamentous cyanobacteria and a
higher proportion of live diatoms than other treatments. Furthermore, N treatments were substantially elevated in
Bacteroidetes and the small diatom, Fistulifera pelliculosa. On the other hand, species richness was almost double in P and N
+ P treatments over others, and coccoid green algae and Proteobacteria were more abundant in both streams. Collectively,
these data suggest that nutrients have the potential to stimulate growth and alter community structure in glacial
meltwater stream microbial mats, and the recent erosion of permafrost and accelerated glacial melt will likely impact
resident biota in polar lotic systems here and elsewhere.
Keywords: cyanobacteria; diatom; C:N:P; thermokarst; permafrost; polar region
INTRODUCTION
The nutrient status of polar and alpine freshwater ecosystems
is changing due to the liberation and mobilization of previously
inaccessible nitrogen (N) and phosphorus (P). This increase in
nutrient inputs is a result of elevated glacial melt (Saros et al.
2010; Fountain et al. 2012), permafrost erosion (Walvoord and
Striegl 2007; Fountain et al. 2014) and the subsequent movement
into hydrologically connected aquatic ecosystems. Recent
studies suggest that nutrient increase may alleviate limitations
on primary production in polar and alpine lakes (Quayle et
al. 2002; Slemmons and Saros 2012), and further research
exploring the potential responses of freshwater stream biota is
Received: 29 October 2015; Accepted: 1 March 2016
C FEMS 2016. All rights reserved. For permissions, please e-mail: [email protected]
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FEMS Microbiology Ecology, 2016, Vol. 92, No. 4
warranted in these rapidly changing environments. Benthic
microbial mats, which are cohesive communities formed
by filamentous cyanobacteria, microbial eukaryotes and
chemotrophic bacteria, are the dominant primary producers
in many streams of the cryosphere, and may be particularly
affected. Mats are tolerant to low temperatures, prolonged desiccation and high irradiances, and can maintain high biomasses
even under oligotrophic conditions (Vincent 2000).
The McMurdo Dry Valleys (MDVs) are a cold polar desert, and
contain the largest ice-free area in Antarctica (Fountain et al.
1999; McKnight et al. 1999). Here, 24-h solar radiation produces
an extensive network of glacial meltwater streams which flow
for five to ten weeks per year (McKnight et al. 1999), with hydrographs that fluctuate daily as a function of sun angle (Cullis,
Stanish and McKnight 2014). These streams have well-developed
hyporheic zones due to unconsolidated benthic substrata, the
extent of which is controlled by permafrost (Conovitz, MacDonald and McKnight 2006; Cozzetto et al. 2013). Because grazing
activity and allochthonous organic inputs are minimal, these
streams are an ideal environment to study the response of microbial mats to their physical environment.
In the MDVs, mat biomass and composition are influenced
by benthic substrata (Kohler et al. 2015c), dispersal (Michaud,
Šabacká and Priscu 2012; Sakaeva et al. 2016, in press) and flow
regime (Stanish, Nemergut and McKnight 2011; Cullis, Stanish
and McKnight 2014), but weakly correlated with ambient nutrient concentrations (ex. Howard-Williams and Vincent 1989;
Stanish, Nemergut and McKnight 2011; Stanish et al. 2013b). This
‘mat-nutrient paradox’ may be due to spatial heterogeneity in
MDV nutrient concentrations. Stream nutrients vary at the microhabitat scale, with seep, hyporheic and channel water differing in their content (McKnight et al. 2004). Therefore, patchscale variability observed in mats (ex. McKnight et al. 1998; Stanish, Nemergut and McKnight 2011) may reflect physical heterogeneity as a result of preferential flow paths in the hyporheic
zone (i.e. the ‘Swiss cheese model’, Cozzetto et al. 2013). At the
landscape scale, nutrients are inversely correlated with microbial mat coverage due to high uptake rates (Gooseff et al. 2004;
McKnight et al. 2004), which along with presumed internal nutrient cycling (Villeneuve, Vincent and Kómarek 2001; Varin et
al. 2010), makes relationships with ambient nutrient concentrations complex.
These observations present challenges for disentangling mat
responses to altered nutrient regimes. However, this knowledge
is timely, as new disturbances are arising in MDV streams associated with changes in the long-term hydrologic regime (Kohler et
al. 2015c). In particular, stream bank slumping from thermokarst
erosion (Levy et al. 2013; Fountain et al. 2014) has led to downstream increases in conductivity, total suspended sediments
and nutrients (Gooseff et al. 2015). In addition, new or previously
dormant streams are expected to emerge or reactivate in higher
altitude and up-valley locations (Lyons et al. 2005; Gooseff et al.
2011; Nielsen et al. 2012), opening new substrata for colonization.
In this context, improving our understanding of how nutrients
impact the colonization and development of mat communities
may provide a basis for interpreting how deglaciation, new flow
paths and the destruction of thermokarst in alpine and polar regions may impact future stream ecosystems.
To test the role of nutrient regime on Antarctic glacial meltwater stream microbial mats, we used nutrient diffusing substrata (NDS—Tank and Dodds 2003; Tank, Bernot and RosiMarshall 2006) to assess differences in the abundance and structure of colonizing microbial communities on different nutrient
treatments. This method has been previously used to test for
Figure 1. Map of the Lake Fryxell Basin, Taylor Valley, with inset of the Antarctic
continent. Green and Aiken Creek study locations are indicated with large black
dots. Smaller dots indicate stream gaging stations operated by the MCMLTER.
nutrient limitation on colonization in a variety of freshwater
stream systems, and provides a methodological alternative to
correlating biomass and community structure to ambient nutrient concentrations across sites. We predicted that adding the
limiting nutrient, likely to be N in MDV streams near the Ross
Sea coast (Welch et al. 2010), should stimulate biomass and shift
community structure.
MATERIALS AND METHODS
Study sites
Green Creek (−77.624108, 163.060101) is 1.2 km in length and is
located on the west side of Lake Fryxell in Taylor Valley (Fig. 1).
It drains the Canada Glacier ∼12 km from the coast and has
a shallow gradient with a stable stone pavement substratum.
Green Creek has been a site of the MDVs Long-term Ecological
Research project (MCMLTER) microbial mat biomass and associated diatom monitoring for over two decades, as well as numerous experimental studies of nutrient uptake at the stream scale
(e.g. Gooseff et al. 2004; McKnight et al. 2004) and mat regrowth
experiments (Stanish, Nemergut and McKnight 2011; Kohler et
al. 2015a). Aiken Creek (−77.601465, 163.291125) is located on
the east side of Lake Fryxell (Fig. 1) and drains Many Glaciers
Pond, which receives water from the Commonwealth and Wales
glaciers. Aiken Creek is broad and shallow, with fine sand substrata intermixed with large boulders (Conovitz, MacDonald and
McKnight 2006). Although it has abundant benthic mats, it has
not historically been a focus of the MCMLTER microbial mat
monitoring program.
Green and Aiken Creek were chosen as stream sites because
they dependably flow for much of the summer, unlike the longer
Von Guerard and Delta streams nearby, which can have irregular or no flow (Stanish et al. 2012). They also both drain glacial
melt ponds, which buffers them from cloudy days which reduces flow, and can increase the likelihood of prolonged desiccation of microbial mats. Because of these relatively mild growing conditions, orange cyanobacterial mats form ∼0.5 cm thick
carpeting on the bottom of both streams, and are composed
Kohler et al.
Figure 2. Photograph of a removed Aiken Creek unit illustrating NDS design.
predominantly of filamentous cyanobacterial genera Phormidium
and Leptolyngbya (McKnight et al. 1998; Stanish et al. 2013b; Kohler
et al. 2015a). Lastly, discharge, water temperature and chemistry
has been monitored for both streams since 1990 by the MCMLTER in collaboration with the United States Geological Survey
(USGS), with stream gages located near their outlets to Lake
Fryxell (Fig. 1).
Experimental design
We used NDS modified from Tank et al. (2006) to assess how
differences in nutrient availability affect microbial colonization
over the 2012–13 summer. Circular holes (2.2 cm in diameter)
were punched into the lids of 30 mL Fisherbrand Polyethylene
Hinged-Lid containers (Thermo Fisher Scientific, Inc., Waltham,
MA, USA) with a no. 15 brass cork borer. Four empty containers were attached to each 7.6 × 43.2 × 0.64 cm clear Plexiglas
strip with flat screws to create individual ‘units’, and clear silicon caulking was applied to ensure attachment to the Plexiglas and prevent leaks. Container dimensions were shorter than
those in the standard methods (5 cm wide × 2.5 cm tall) to reduce the probability of desiccation under frequent low flows in
the shallow MDV streams, and both the containers and Plexiglas were clear to prevent warming from solar radiation (Fig. 2).
Agar was made with 0.2 μm-filtered DI water, and three nutrient
treatments (N, P and N + P) were prepared at 0.5 M concentrations using potassium phosphate (KH2 PO4 ) and sodium nitrate
(NaNO3 ) salts (table 10.2; Tank, Bernot and Rosi-Marshall 2006).
A control (C) was also prepared, and received no salts. Each container was randomly assigned a treatment such that each unit
had one of each agar type, and the same agar ‘batch’ was used to
fill all containers within treatments. Containers were then fitted
with an ashed (450◦ C for 4 h) fritted glass disc (2.75 cm diameter,
Leco Corporation, St Joseph, Michigan) before lids were carefully
closed. To prevent contamination, all equipment was cleaned
and sterilized with ethanol during construction, and units were
covered in plastic wrap during transport to field sites.
NDS units were deployed near the gages of Green (15 units)
and Aiken Creeks (10 units) on 2 January 2013. Units were placed
three-across in the thalweg of both streams, parallel to flow and
secured to the benthos with large nails placed through holes
drilled into the Plexiglas (Fig. 2). Structures were incubated until flow slowed late in the summer, and were collected after 19
(21 January 2013) and 20 (22 January 2013) days for Aiken and
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Green Creek, respectively. NDS diffusion rates remain constant
for up to 17 days in temperate streams (Tank, Bernot and RosiMarshall 2006), and likely longer in MDV streams due to lower
average temperatures. Entire units were randomly designated
for one type of analysis upon collection. For both Green and
Aiken Creeks, fritted glass disks from 5 units were individually
placed in 60 mL centrifuge tubes, wrapped in foil and immediately frozen at −20◦ C for chlorophyll-a (chl-a) analysis. Five other
units from both streams were collected for ash-free dry mass
and algal community analyses by microscopy and placed in 120mL Nalgene bottles, preserved in DI water and 3%–10% formalin,
and sent to the University of Colorado. The remaining 5 units
from Green Creek were preserved for bacterial community analysis with Sucrose Lysis Buffer (SLB; Mitchell and Takacs-Vesbach
2008) in 60 mL centrifuge tubes, and sent frozen to the University
of New Mexico.
For comparison with NDS units, orange mat samples were
taken on 15 January 2013 at the MCMLTER algal mat transect at Green Creek, and 18 January 2013 at the upstream
gaging station of Aiken Creek, both of which were upstream
of the deployed NDS units. Five cores were taken from each
stream for diatom community analyses and for Green Creek
ash-free dry mass (AFDM) and chl-a. Four cores were taken
for Aiken chl-a and AFDM. Methods for estimating biomass
are outlined in Stanish et al. (2011) and Kohler et al. (2015c),
and described in depth for NDS units below. In addition to
this, diatom data from orange mats collected in 2007, 2010
and 2012 for Green Creek and 2007 and 2012 for Aiken Creek
were taken from the Antarctic Diatoms Website database
(http://huey.colorado.edu/diatoms/samples/index.php) to compare with NDS diatom communities.
Chl-a and AFDM
Chl-a was estimated from both the mat cores and NDS units
following Welschmeyer (1994). Briefly, mat cores and entire frits
were extracted in 90% buffered acetone in the dark for 24 h. Samples were analyzed on a Turner Designs 10-AU field fluorometer
(Turner Designs, Sunnyvale, CA, USA), and the resulting concentrations were scaled to the area of the hole in cork-borer and the
NDS cup lid, respectively. All chl-a analyses were performed in
Crary Laboratory at McMurdo Station.
After morphological characterization of composite algal
communities (outlined in the section below), the remainder of
the quantitative formalin-preserved aliquot was filtered onto
R GF/F filters to measure AFDM. For both NDS
ashed Whatman
and mat cores, samples were dried until a stable mass was
reached, weighed on a four-digit scale, furnaced at 500◦ C for 2
h, re-weighed to determine mass lost by combustion and scaled
to respective areas (Steinman, Lamberit and Leavitt 1996). One
control sample from Aiken and one N sample from Green Creek
were not measured due to analytical error.
Morphological community characterization
Preserved mat material was removed from frits with new toothbrushes and rinsed into containers with ultrapure water. Samples were concentrated (brought to 15 mL), homogenized and
split for composite algal (7.5 mL) and diatom (7.5 mL) community analyses. Composite algae characterization was performed
using methods similar to Kohler et al. (2015a). Briefly, a 0.1 mL
aliquot of the homogenized algal sub-sample was transferred
to a Palmer–Maloney counting chamber. Material was observed
under 400× magnification, and each filament, colony or single
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FEMS Microbiology Ecology, 2016, Vol. 92, No. 4
cell was designated as one unit. Units were identified to the
lowest taxonomic group possible, primarily using Komárek and
Anagnostidis (2005) for cyanobacterial identifications, and dimensions of each were measured by ocular micrometer. Samples were analyzed until at least 150 units were counted, and
the total fields of view were recorded. Biovolumes were calculated using diatom valve depths given in Kohler et al. (2015a) and
equations in Hillebrand et al. (1999). The total fields of view were
used to calculate mm3 biovolume per cm2 . The live/dead status
of diatom frustules was characterized by noting the presence or
absence of intact protoplast material. The minimum number of
frustules per sample used in this calculation was 10, with an
overall mean = 29.6 and median = 26.
Diatom communities were quantitatively analyzed by digesting the second aliquot with low heat and 30% H2 O2 . The digested material was rinsed with distilled water until pH was
neutral, and a known amount of homogenized material was
dried onto cover slips and mounted onto glass microscope
slides with Zrax mounting medium (W. P. Dailey, Philadelphia, USA). Diatoms were enumerated using an Olympus Vanox
light microscope (Japan) at 1250× magnification, and identified to species using the species list available in Sakaeva et al.
(2016, in press) and on the Antarctic Freshwater Diatoms website (http://huey.colorado.edu/diatoms/taxa/index.php). No less
than 300 valves were counted per slide. Relative abundances
were calculated, and the number of fields of view used in the
count was used to calculate the number of diatom valves per
cm2 .
Molecular community characterization
Frits from each of the five units from Green Creek (20 frits in total) were extracted with the cetyltrimethylammonium bromide
(CTAB) method as described in Mitchell and Tackacs (2008). Barcoded amplicon pyrosequencing of 16S rRNA genes was performed as described previously (Dowd et al. 2008; Van Horn
et al. 2013) on a Roche 454 FLX instrument using Roche titanium reagents and titanium procedures and universal bacterial primers 939F 5 TTG ACG GGG GCC CGC ACA AG and 1492R
5 -GTT TAC CTT GTT ACG ACT T-3 . DNA (100 ng per sample)
was amplified in triplicate by a single step PCR to create 16S
rRNA gene amplicons containing the Roche-specific sequencing adapters and a barcode unique to each sample. Amplicons
were purified using Agencourt Ampure beads and combined in
equimolar concentrations. Sixteen of the 20 samples were successfully sequenced.
The 16S rRNA gene sequences were quality filtered, denoised,
screened for PCR errors and chimera checked using AmpliconNoise and Perseus (Quince et al. 2011). The Quantitative Insights into Microbial Ecology (QIIME) pipeline was used to process the 16S rRNA gene sequence data (Caporaso et al. 2010b)
as described previously (Van Horn et al. 2013). Briefly, sequences
were assigned to operational taxonomic units (OTUs) using a
97% genetic similarity cutoff. A representative sequence was
picked from each OTU and aligned using the PyNAST aligner
(Caporaso et al. 2010a) and the Greengenes (V13.8) core set
(DeSantis et al. 2006) and given taxonomic assignments using
the denovo-based UCLUST program (Edgar 2010). Alpha diversity and coverage estimates for each sample were assessed with
chloroplasts removed, using the Good’s Coverage estimator and
observed OTU, Shannon, and Chao1 richness estimates of 1000
randomly selected subsets of 531 sequences per sample to standardize for varying sequencing efforts across samples. Measures
of community composition were also performed with randomly
selected subsets of 275 and 251 sequences for chemotrophic and
cyanobacterial sequences, respectively. The individual sff files
from this study are available for download through NCBI Bioproject PRJNA311727.
Water chemistry and discharge
Stream water for chemical analyses was collected weekly for
each stream throughout the summer (n = 7 for Green Creek,
n = 6 for Aiken Creek) and analyzed according to methods described in Welch et al. (2010). Briefly, nutrient and ion samples
were collected in triple-rinsed 250-mL Nalgene bottles, and dissolved organic carbon (DOC) samples in 125 mL combusted amber glass bottles. Nutrient samples were filtered using Whatman
glass-fiber filters and frozen, while samples for cation and anion
analyses were filtered with Nuclepore polycarbonate membrane
filters (0.4-mm pore size) and refrigerated at 4◦ C. DOC samples
were filtered with ashed glass-fiber filters, acidified with HCl
and refrigerated at 4o C. Stage was measured continuously at 15
min intervals for both streams, and calibrated for discharge with
manual measurements taken over the summer. All discharge
and water chemistry data are available at www.mcmlter.org.
Statistical analyses
For NDS biomass variables, data were log10 -transformed to satisfy the assumption of normality. A two-factor ANOVA was
applied to test if N and/or P enrichment significantly influenced colonization, and significant results were followed by
Tukey’s Honest Significant Differences (HSD) to directly compare means between treatments (Tank and Dodds 2003). Proportional data (relative abundances and biovolume) were normalized by square-root transformation, and rare units (<1.0%)
were removed. To visualize patterns within algal and bacterial
communities, Redundancy Analyses (RDA) were created for each
analysis and stream using the ‘vegan’ R package (Oksanen et al.
2011). The statistical significance of nutrient enrichment on algal and bacterial community structure was evaluated by permutational multivariate analysis of variance (PERMANOVA; Anderson 2001), and significance was designated at α = 0.05. All statistical analyses were performed using the R console, version 2.13.0
(R Core Team 2014).
RESULTS
Water chemistry and discharge
Average nutrient concentrations for Green Creek over the 2012–
13 summer were 17.71 μg N-DIN L−1 , which was almost entirely
contributed by nitrate, and 3.85 μg P-SRP L−1 (Table 1). Nutrient
concentrations in Aiken Creek averaged 23.77 μg N-DIN L−1 , with
almost equal contributions of nitrate and ammonium, and 20.67
μg P-SRP L−1 (Table 1). The resulting N:P ratios were 10.16 for
Green Creek and 2.54 for Aiken Creek, both of which fall below
the Redfield ratio of ∼16. Total annual discharge averaged 160.6
× 103 m3 yr−1 for Green Creek and 168.8 × 103 m3 yr−1 for Aiken
Creek between 1990–91 and 2010–11.
Biomass
Orange microbial mat samples taken adjacent to NDS units
in both streams revealed greater standing biomasses in Aiken
Creek, which averaged 16.53 μg chl-a cm−2 (±3.05 standard error)
and 20.26 mg AFDM cm−2 (±4.33). In comparison, orange mats
from Green Creek averaged 4.29 μg chl-a cm−2 (±1.05) and 6.40
2.7–6.3
3.9
1.2
2.2–59.8
20.7
21.9
NA
<5
NA
<5–15.4
10.9
3.7
7.2–12.0
10.6
1.7
270.0–1314.5
700.1
363.9
1734.4–3509.2
2604.3
650.6
608.3–1339.9
921.0
289.4
1.9–36.1
15.9
10.3
<100–615.1
241.1
181.1
745.1–1121.7
895.7
123.6
0.5–1.3
0.7
0.3
277.3–940.1
570.2
250.3
69.7–142.6
96.1
30.4
0.2–0.4
0.3
0.1
range
mean
std.dev
Aiken Creek (n = 6)
7.1–7.7
7.4
0.3
3.6–10.3
7.5
2.5
24.4–45.5
33.3
7.5
2.5–8.4
6.0
2.2
Green Creek (n = 7)
range
6.9–8.0
mean
7.3
std.dev
0.4
5
1.5–3.6
2.2
0.8
<0.7–2.2
1.5
0.7
P-SRP (μg/L)
N-NH4 (μg/L)
N-NO2 (μg/L)
N-NO3 (μg/L)
C-DOC (μg/L)
SO4 (μg/L)
Si (μg/L)
Alk (meq/L)
SC (μS)
W. temp (◦ C)
pH
Table 1. Summary of physio-chemical variables (range, mean values and standard deviation) measured weekly for Green and Aiken Creeks between 11 December 2012 and 23 January 2013.
Kohler et al.
Figure 3. Chl-a (top), AFDM (middle) and total algal biovolume (bottom) on nutrient diffusing substrates deployed in Green (left column) and Aiken (right column) Creeks for nitrogen (N), phosphorus (P), nitrogen and phosphorus (N + P)
and control (C) treatments. Bars represent means (n = 4 for Aiken C and Green
N AFDM, n = 5 for all others), and error bars indicate ± standard error. Asterisks
(∗ ) indicate a significant effect of N, P or the N + P interaction by ANOVA (Tank
and Dodds 2003).
mg AFDM cm−2 (±1.08). On NDS units, average chl-a and AFDM
values were also greater in Aiken Creek (Fig. 3), and chl-a reached
an average of 1.09 μg chl-a cm−2 on N treatments (∼6.6% of adjacent mats; Fig. 3b), while AFDM accrual was greatest on N + P
treatments at 0.95 mg cm−2 (∼5% of adjacent mats; Fig. 3d). In
Green Creek, chl-a reached an average of 0.73 μg chl-a cm−2 on
N + P treatments, which was ∼17% of that for the adjacent orange mats (Fig. 3a). Greek Creek AFDM, which was not significantly different between samples, averaged 0.47 mg cm−2 or ∼7%
of the adjacent mats (Fig. 3c).
For both streams, N and N + P treatments had greater average
chl-a than P and controls, although these differences were not
statistically significant for Green Creek. In Aiken Creek, N additions significantly increased chl-a (ANOVA, F = 9.883, P = 0.006),
and the N-only treatment was significantly greater than the control (Tukey’s HSD; P = 0.025) and P (P = 0.016) treatments (Fig. 3b).
Aiken Creek AFDM was significantly influenced by N (ANOVA; F
= 7.943, P = 0.013), P (F = 4.946, P = 0.042) and the N + P interaction (F = 4.865, P = 0.043), with the N + P treatment being
significantly greater on average than all others (Tukey’s HSD, all
P < 0.03; Fig. 3d). Algal biovolumes were greater on Aiken Creek
NDS units than in Green Creek (Fig. 3e and f). Nitrogen significantly elevated algal biovolume in both Green (ANOVA; F = 6.069,
P = 0.025) and Aiken Creek (F = 7.563, P = 0.014), but differences
between treatment means were not significant.
Aiken Creek had more diatom valves per area than Green
Creek, in some cases by more than an order of magnitude (Fig.
4a and b). For Aiken Creek, both N (ANOVA; F = 10.395, P = 0.005)
and the N + P interaction (F = 4.491, P = 0.050) significantly
increased diatom valves, and the N-only treatment mean was
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FEMS Microbiology Ecology, 2016, Vol. 92, No. 4
Algal community structure
Figure 4. Total number of diatom valves (top) and percent live diatoms (bottom)
for Green (left column) and Aiken (right column) Creeks. Notice the change in
y-axes between panel 4a and 4b. Bars represent means (n = 5), and error bars
indicate ± standard error. Asterisks (∗ ) indicate a significant effect of N, P or the
N + P interaction by ANOVA (Tank and Dodds 2003).
significantly greater than the control (Tukey’s HSD; P = 0.008),
P-only (P = 0.025) and marginally greater than N + P units
(P = 0.111). While there were also more diatom valves on N and
N + P treatments in Green Creek (Fig. 4a), these differences were
not significant. A greater proportion of live diatoms was found
on Aiken Creek NDS units than Green Creek (Fig. 4c and d). Additions of N significantly increased the proportion of live diatoms
in Aiken Creek (ANOVA; F = 4.412, P = 0.052), and P (F = 13.976,
P = 0.002) and N + P treatments (F = 7.303, P = 0.016) hosted significantly less. Furthermore, Tukey’s HSD pairwise tests revealed
Aiken Creek N-only treatments had significantly greater values
than all others (all P < 0.020). While more live diatoms were also
found on Green Creek N treatments, these differences were not
statistically significant.
Morphologically, algal communities from both streams were
simple, with Oscillatoria, Leptolyngbya, diatoms and coccoid green
algae contributing most of the total biovolume (Fig. 5). Pseudanabaena, Nodularia and Phormidium were present in lesser proportions. In general, Green Creek (Fig. 5a) was composed of more
filamentous cyanobacteria such as Leptolyngbya and Oscillatoria than Aiken Creek (Fig. 5b), which had greater proportions
of diatoms and Pseudanabaena. For both streams, RDA analyses
showed clear separation of communities by nutrient treatment,
though more variance was explained in Green Creek (x = 34.7%,
y = 20.1%; Fig. 6a) than in Aiken (x = 23.4%, y = 19.7%; Fig. 6b).
For both streams, N-only treatments had greater proportions
of fine-trichomed cyanobacteria (i.e. Leptolyngbya spp.). In Aiken
Creek, an unknown cyanobacterial filament (sheathed, with irregular segments) was also more abundant on N treatments.
Conversely, N + P treatments of both streams had greater proportions of a flagellated, coccoid green algae. Lastly, control and
P treatments had greater proportions of diatoms, and P samples
had greater proportions of Oscillatoria. When tested with PERMANOVA, N had a significant effect on Aiken Creek algal community structure (F = 5.888, P = 0.001), while P had marginal
effects (F = 2.161, P = 0.078). For Green Creek, N was also significant in explaining community differences (F = 3.208, P = 0.019)
as was the N + P interaction term (F = 2.747, P = 0.037), but the
effect of P was only marginally significant (F = 2.276, P = 0.075).
The diatom flora of adjacent orange mats was similar between the two streams, with common species in both, including
Stauroneis latistauros, Mayamaea atomus, Luticola austroatlantica
and Hantzschia amphioxys. The major differences between the
two included a greater abundance of Humidophila spp. and Psammothidium papilio in Green Creek, and Hantzschia spp. and Navicula cincta in Aiken Creek, the latter of which is almost completely absent in the former (Fig. 7). In some cases, individual
species in the historical mat sampling dominated communities
(ex. one sample from Green Creek with 79% Fistulifera pelliculosa,
two Aiken samples comprised of 57% N. cincta and 54% Craticula
molestiformis, respectively). On average, Aiken mat diatoms had
Figure 5. Stacked bar graphs reflecting the composite algal community by percent biovolume (top row) and relative abundances of diatom genera (bottom row) for
Green (left column) and Aiken (right column) Creeks. Bars represent means (n = 5).
Kohler et al.
7
Figure 6. RDA of percent algal biovolumes (top row) and diatom relative abundances (bottom row) for Green (left column) and Aiken (right column) Creeks. Diatom
species abbreviations are given in the Fig. 7 caption. Treatment symbols are as follows: C = red squares, N = blue circles, P = yellow diamonds and N + P = green
triangles. Taxonomic units representing >5% of the relative biovolume/abundance are superimposed.
greater richness, Shannon diversity, and evenness values than
Green Creek (Table 2).
Diatom species composition from the NDS units strongly reflected those from the adjacent microbial mats, although variability between samples was much lower, and no species were
present that had not already been recorded through long-term
monitoring (Fig. 7). For both streams, N treatments had greater
abundances of F. pelliculosa and C. molestiformis (Figs 6 and 7).
In Green Creek, Chamaepinnularia cymatopleura and Humidophila
australis were more common on P treatments, Mayamaea spp.
and H. amphioxys on N + P, and P. papilio on controls. These effects of N (F = 2.399, P = 0.009), P (F = 3.353, P < 0.001), and the
N + P interaction (F = 1.923, P = 0.049) were significant by PERMANOVA. In Aiken Creek, Hantzschia abundans and Chamaepinnularia cf. aliena were greatest on controls, N. cincta and Mayamaea
spp. on P-only and Diadesmis contenta var. parallela, Luticola laeta
and S. latistauros on N + P treatments. Aiken Creek diatom communities were also significantly affected by N (PERMANOVA, F =
7.937, P < 0.001), P (F = 8.918, P < 0.001) and the N + P interaction
(F = 6.922, P < 0.001).
In both streams, NDS diatom diversity indices were comparable with the adjacent orange mats, and aside from slightly lower
richness values in Green Creek compared to Aiken Creek (ranging 18–28 versus 19–31, respectively), diversity metrics were not
significantly different between streams when treatments were
compiled and compared by t-test (Table 2). Furthermore, Green
Creek diatom diversity metrics were not significantly different
by nutrient treatments. In Aiken Creek, N treatments exhibited
significantly lower richness (ANOVA; F = 10.450, P = 0.005), Shannon diversity (F = 35.375, P < 0.001) and evenness (F = 28.105,
P < 0.001), while P treatments were greater in richness (ANOVA;
F = 9.351, P = 0.008), Shannon diversity (F = 34.808, P < 0.001),
and evenness (F = 28.399, P < 0.001). Pairwise comparisons
(Tukey’s HSD) further revealed Aiken Creek N treatments were
significantly lower in richness (all P < 0.01), Shannon diversity
(all P < 0.001) and evenness (all P < 0.001) than all other treatments.
Green Creek bacterial communities
Molecular analyses of Green Creek NDS units revealed that
communities were dominated by chemotrophic bacteria by
relative abundance, with cyanobacteria and chloroplasts observed at lower frequencies (Fig. 8a). Chloroplast material was
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FEMS Microbiology Ecology, 2016, Vol. 92, No. 4
Figure 7. Dot-plot diagram of Green (left) and Aiken (right) Creek diatom communities. Diatom taxon codes are on the y-axis. Sample codes are on the x-axis, and
correspond to treatments from NDS units (C, N, P, N + P), as well as the year an analyzed orange mat sample was taken from the adjacent corresponding transect.
Dot size for a taxon is proportional to its relative abundance in a given sample as indicated in the legend, and only that taxon >1% relative abundance is listed.
Symbol colors by treatment are as follows: orange mat samples = grey, C = red, N = blue, P = yellow and N + P = green. Taxon codes: Atayl = Achnanthes taylorensis,
Calie = Chamaepinnularia cf. aliena, Ccyma = Chamaepinnularia cymatopleura, Cmole = Craticula molestiformis, Dcovp = Diadesmis contenta var parallela, Holig = Halamphora
oligotraphenta, Humsp = Humidophila spp., Harcu = H. arcuata, Haust = H. australis, Fpell = Fistulifera pelliculosa, Hansp = Hantzschia spp., Habun = H. abundans, Hamph
= H. amphioxys, Hhype = H. hyperaustralis, Hmuel = H. amphioxys f. muelleri, Lutsp = Luticola spp., Laust = L. austroatlantica, Ldoli = L. dolia, Lgaus = L. gaussii, Llaet = L.
laeta, Lmack = L. macknightiae, Lperm = L. permuticopsis, Maysp = Mayamaea spp., Matom = M. atomus, Mvar1 = M. atomus var. 1, Mperm = M. permitis, Muesp = Muelleria
spp., Mmeri = M. meridionalis, Mperu = M. peraustralis, Ncinc = Navicula cincta, Ngreg = N. gregaria, Mnaum = Microcostatus naumannii, Nshac = N. shackletoni, Nadmi
= N. adminii, Ncomm = Nitzschia australocommutata, Nwest = N. westiorum, Pgerm = Psammothidium germainii, Ppapi = P. papilio, Slati = Stauroneis latistauros. Unkno =
Unknown.
Table 2. Average richness (R), Shannon diversity (H’) and evenness
(J’) of morphologically characterized diatom communities for each
nutrient treatment from Green and Aiken Creek, along with adjacent
benthic orange mats sampled in 2013 for reference. Standard errors
are in parentheses, and n = 5 for each treatment from each stream.
Bold font indicates a significant effect of N, P or the N + P interaction
by ANOVA.
Richness
Shannon diversity
Evenness
2.26 (± 0.31)
2.49 (± 0.07)
2.35 (± 0.15)
2.54 (± 0.07)
2.59 (± 0.04)
0.68 (± 0.09)
0.80 (± 0.02)
0.74 (± 0.04)
0.80 (± 0.02)
0.80 (± 0.01)
2.72 (± 0.22)
2.93 (± 0.04)
1.85 (± 0.15)
2.98 (± 0.05)
2.92 (± 0.05)
0.81 (± 0.06)
0.89 (± 0.01)
0.61 (± 0.05)
0.90 (± 0.01)
0.89 (± 0.00)
Green Creek (n = 5)
orange mat
C
N
P
N+P
23.4 (± 1.6)
22.6 (± 1.4)
23.4 (± 1.5)
24.2 (± 1.0)
25.2 (± 1.2)
Aiken Creek (n = 5)
orange mat
C
N
P
N+P
25.8 (± 1.0)
26.6 (± 1.4)
20.4 (± 0.4)
27.6 (± 1.0)
26.4 (± 1.5)
identified as belonging to Chlorophyte families Chlamydomonadaceae and Monomasticaceae, with the most common sequences matching the genus Monomastix, although 18S sequencing (not conducted) would be necessary to adequately resolve
its identity. Aligning with morphological observations of coccoid green algae, chloroplast relative abundances were greatest
in P and N + P treatments, and averaged 17% and 15% of the full
molecular dataset, respectively.
The phylum Bacteroidetes was largely represented by the
genera Flectobacillus (Cytophagia) and Flavobacterium (Flavobacteriia), while Proteobacteria was dominated by members of the
family Comamonadaceae (Betaproteobacteria) (Fig. 8b). By treatment, P and N + P had greater relative abundances of Proteobacteria, while Bacteroidetes was more abundant in the control and
N treatments (Fig. 8b). This pattern was visible in the resulting
RDA, and axis 1 and 2 explained 10.7% and 2.8% of the community variability, respectively (Fig. 9a). Control and N-only treatment positions were strongly influenced by Flavobacteriia (averaging 48% and 68% by relative abundance, respectively), with
Betaproteobacteria influencing P and N + P (42% and 44%, respectively). When tested with PERMANOVA, only P had a significant effect on bacterial community structure (F = 26.138, P <
0.001).
Within the Cyanobacteria, most OTUs were from genera
Phormidium (Oscillatoriophycideae), Leptolyngbya and Pseudanabaena (Synechococcophycideae) and Dolichospermum
(Nostocophycideae) (Figs 8c and 9b). Relative abundances of
Synechoccophycideae were greatest on control and N-only
treatments, while Oscillatoriophycideae and Nostocophycideae
were greater on P and N + P (Fig. 8c). In the RDA created for these
communities, control and N-only treatments were strongly influenced by Leptolyngbya (averaging 69% and 88% in relative
Kohler et al.
9
Figure 8. Stacked bar graphs of Green Creek NDS molecular data, with relative abundances of (a) all bacterial, cyanobacterial and chloroplast data, (b)
chemotrophic bacteria-only at the phylum level and (c) cyanobacteria-only at
the class level.
abundance, respectively), P-only clustered with Phormidium (31%
on average) and N + P with Dolichospermum (40% on average),
with axis 1 and 2 explaining 16.7% and 7.8% of the variation,
respectively (Fig. 9b). Like for bacterial communities, P had a
significant effect on community structure (F = 25.355, P < 0.001),
though not N.
Diversity indices created with compiled molecular data were
strongly influenced by P enrichment, but not N (Table 3). Phosphorus significantly increased the number of OTUs (ANOVA; F =
73.020, P < 0.001) and Chao1 values (F = 70.619, P < 0.001), and
means of both the P and N + P treatments were nearly double the
means for N-only and controls (Tukey’s HSD, all P ≤ 0.002). Phosphorus enrichment also significantly increased Shannon diversity (ANOVA; F = 27.693, P < 0.001), and P and N + P means were
significantly greater than N (Tukey’s HSD, both P < 0.010), but not
controls (Table 3). Lastly, P additions significantly lowered Good’s
coverage values (ANOVA; F = 68.051, P < 0.001), and N + P and
P treatments were significantly lower than N-only and controls
(Tukey’s HSD, all P ≤ 0.002).
DISCUSSION
In this work, we evaluated patterns in the colonization of microbial communities onto artificial substrata with different nutrient
amendments, and found considerable effects of both N and P
in both stream reaches. In general, N additions had a stimula-
Figure 9. RDA of (a) chemotrophic bacteria (class level) and (b) cyanobacteria
(genus level) relative abundances from Green Creek molecular data. Treatment
symbols are as follows: C = red squares, N = blue circles, P = yellow diamonds
and N + P = green triangles. Taxonomic units representing >5% of the relative
abundance are superimposed.
tory effect on chl-a and algal biovolume, while P substantially
increased diversity and altered community structure. This research provides valuable insights into how alterations in nutrient chemistry arising from deglaciations, changes in hyporheic
flow paths and erosion of permafrost may modify the future colonization and subsequent development of microbial communities. Furthermore, results will aid in informing regional studies
reconstructing past climatic conditions based on paleomaterial,
as well as monitoring changes in microbial mat abundance and
composition in the field.
Biomass
Nitrogen is important for photosynthesis, and therefore, the observed stimulation of chl-a on N treatments aligns with our
predictions given the low dissolved N:P nutrient ratios of these
two streams relative to Redfield ratio. The Lake Fryxell Basin
(and Green Creek specifically) has been previously described as
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FEMS Microbiology Ecology, 2016, Vol. 92, No. 4
Table 3. Average number of OTUs, Shannon diversity, Chao1 diversity and Good’s coverage for Green Creek molecular data. Chemotrophic
bacterial and cyanobacteria are compiled (chloroplast data are removed), and each number represents the average of 1000 iterations, with
standard error in parentheses. Bold font indicates a significant effect of N, P or the N + P interaction by ANOVA.
Treatment
n
Number of OTUs
Shannon diversity
Chao1
Coverage
C
N
P
N+P
3
4
4
4
52.8 (±8.7)
43.3 (±7.0)
105.2 (±18.3)
110.8 (±14.4)
3.30 (±0.53)
2.43 (±0.69)
4.35 (±0.27)
4.26 (±0.29)
130.1 (±55.6)
109.9 (±61.9)
355.8 (±119.1)
344.8 (±100.2)
0.939 (±0.015)
0.951 (±0.013)
0.853 (±0.031)
0.849 (±0.025)
N-limited based on microbial uptake (Gooseff et al. 2004). On
the other hand, P is important for reproductive machinery, and
since it is liberated by hyporheic zone weathering, alterations in
flow paths could have observable consequences, especially in Plimited streams. More inland basins, such as Lake Bonney, are
P-limited due to high atmospheric N-deposition and scarcer apatite deposits, coupled with decreased weathering from comparatively shorter streams (Welch et al. 2010). Future experiments in
inland basins would be informative to test if P additions would
stimulate chl-a and biovolume instead of N.
Mat colonization has previously been identified as a slow process in the MDVs. Vincent and Howard-Williams (1986) found
<1% of the surrounding biomass colonized silicon tubing after
3–4 weeks, and Mylar strips previously deployed in Green Creek
(1999–2000; Chatfield, unpublished data) accumulated very little growth among orange mats (mean of 0.023 mg AFDM cm−2 ),
and undetectable growth among marginal Nostoc ‘black’ mats.
In this study, all biomass measurements were <20% of the adjacent orange mat biomass, even in the most generous scenarios (i.e. N and N + P treatments). This is comparable to a recent
Green Creek regrowth experiment, which found mats on rocks
to regrow 18% of the surrounding chl-a and 27% of the AFDM
over the same three-week period (Kohler et al. 2015a).
Past studies have suggested that nutrients may be more important to mats during the colonization and/or early successional stages than for mature mats. For example, McKnight et al.
(2007) proposed that the exceptionally high productivity upon
rehydration of the Relict Channel in the Fryxell Basin was due
to the mobilization of many years of accumulated nutrient deposition. In a study similar to this present work, Hawes, Smith,
and Sutherland (1999) also found chl-a to be stimulated by nutrients in mesocosm experiments inoculated with Wright Valley soils. Lastly, in the Maritime Antarctic Region, Elster and Komarek (2003) found a positive relationship between nutrients
and biomass colonizing artificial substrata. It follows from our
study and others that, even though mat regrowth may be slow,
the time needed to regenerate biomass following disturbance or
scour may decrease if nutrients are added.
Algal community structure
Microscopic and molecular study of NDS material revealed phototrophic genera typical of the region (e.g. McKnight et al. 1998;
Stanish et al. 2013b), and both approaches found Leptolyngbya to
dominate control and N-only treatments, while coccoid green
algae exhibited elevated abundances in P and N + P treatments.
This latter result is consistent with Hawes, Smith and Sutherland (1999), which found elevated nutrients, specifically N + P,
to favor green flagellates and ‘granular spheres’ over cyanobacteria. On the other hand, two commonly reported microbial
mat genera from this region, Phormidium and Nostoc, were only
present at low biovolumes on NDS units by microscopy. While
sequencing revealed Nostoc never reached more than 2% relative abundance in any sample, agreeing well with morphological observations, Phormidium was found to be a major constituent of Green Creek P treatments, while Oscillatoria was not
detected. Since Oscillatoria contributed substantial biovolume by
microscopy, especially on P samples, it is likely that there is overlap between these two groups, and this discrepancy between
techniques highlights the difficulty in taxonomically resolving
filamentous cyanobacteria.
Diatoms (Bacillariophyceae) generally make up a small proportion of MDV microbial mats by biovolume (McKnight et al.
1998; Kohler et al. 2015a). The nearly 50 taxa comprising the MDV
flora are relatively well described (e.g. Esposito et al. 2008; Kohler
et al. 2015b) and show great promise for paleoecology and ecological monitoring due to their excellent preservation and presumed species-specific environmental preferences (ex. Konfirst
et al. 2011; Stanish, Nemergut and McKnight 2011; Stanish et al.
2012). Despite this, the individual responses of diatom species
to nutrients is poorly known, and recent surveys from streams
(Stanish, Nemergut and McKnight 2011; Stanish et al. 2013b), cryoconite holes (Stanish et al. 2013a) and ponds (Sakaeva et al. 2016,
in press) have found weak or no association with nutrients. Instead, a high degree of spatial structure (i.e. regional community
patterns) is present in MDV microbial communities (Michaud,
Šabacká and Priscu 2012; Sakaeva et al. 2016, in press), and discharge and historical factors may dominate as ecological filters
for diatom communities in MDV streams (ex. Stanish, Nemergut
and McKnight 2011).
While NDS diatoms comprised a greater proportion of the total biovolume than in previous reports of mature mats (ex. McKnight et al. 1998; Kohler et al. 2015a), relatively few species were
strongly influenced by nutrient treatments, and species richness and diversity metrics were comparable to those reported
in Stanish et al. (2011) and (2013b) for Green Creek. In the both
streams, F. pelliculosa contributed to most of the differences. This
lightly silicified species is routinely observed to be an important
indicator of change in the MDVs. Stanish (2011) found this taxon
to be dominant in Von Guerard Stream seston, and Stanish et al.
(2011) suggested that it may originate in lentic ‘playa’ habitats
upstream. Kohler et al. (2015a) found F. pelliculosa to be in greatest
abundances on previously disturbed substrata, and to increase
in relative abundance over the course of summer. In this study,
we found F. pelliculosa to be most numerous on N treatments,
which may not be surprising given the previously recorded affinity of this genus for eutrophic conditions in the Arctic (Michelutti
et al. 2007). As a result, it may be that this species colonizes
high-nutrient areas such as seeps before being transported in
the water column (Stanish, Nemergut and McKnight 2011).
The second most responsive species, C. molestiformis, has no
previously known ecological preferences in the MDV, and is rare
in most streams, but in this experiment also showed greatest
abundances in N treatments. Interestingly, both C. molestiformis
Kohler et al.
and F. pelliculosa, as well as N. cincta and Hantzschia spp. in Aiken
Creek, are periodically observed in high abundances in the monitored data. Among other possibilities, this variation in diatom
communities among the adjacent orange mats may reflect areas of hyporheic upwelling or downwelling (Cozzetto et al. 2013),
which may promote markedly different nutrient concentrations
from the overlying water column (McKnight et al. 2004). Collectively, this may make hyporheic zone interactions a potentially
important source of in-stream heterogeneity for benthic communities.
Bacterial community structure
In a recent review, 79% of 56 studies investigating nutrient
effects documented statistically significant changes in microbial diversity when nutrient regimes were altered (Zeglin 2015).
In temperate streams, anthropogenic nutrient additions alter microbial community composition, diversity and function
with varying impacts depending on the severity of the disturbance. For example, low-level inputs from agriculture (BurgosCaraballo, Cantrell and Ramı́rez 2014) and wastewater (Wakelin, Colloff and Kookana 2008) increase bacterial alpha diversity,
while heavy effluent loading decreases diversity (Van Horn et
al. 2011; Drury, Rosi-Marshall and Kelly 2013; Abell et al. 2014).
While glacial meltwater streams have received comparatively
less study, nutrients have previously been linked to significant
differences in microbial composition and succession in glacial
forefield soils (Göransson, Venterink and Bååth 2011; Knelman et
al. 2014) and in bacterioplankton communities (Adams, Crump
and Kling 2015). In MDV soils, microbial community composition
is strongly linked to pH, salinity, moisture and organic material
(Zeglin et al. 2011; Van Horn et al. 2013, 2014).
In this study, we observed richness and diversity metrics to
double in P and N + P treatments. Interestingly, this increase occurred in the P treatments in spite of the relatively low N:P ratios
found in the Fryxell Basin streams, and was contrary to our predictions. Given that a nutrient tracer experiment in Green Creek
also showed a strong demand for added P (McKnight et al. 2004),
P availability within the mat may not be reflected by the nutrient ratios in the overlying stream water, and MDV stream microbial diversity may instead respond positively to low-level nutrient enrichment (Wakelin, Colloff and Kookana 2008; BurgosCaraballo, Cantrell and Ramı́rez 2014). Furthermore, research in
other aquatic habitats suggests that different aquatic bacteria
have varying P utilization strategies (Cotner et al. 2010; Scott,
Cotner and LaPara 2012), with some maintaining homeostatic
regulation of their biomass stoichiometry, while others demonstrate flexibility (Godwin and Cotner 2015). Additionally, Stanish
et al. (2013b) reported much greater observed OTU and Chao1 values in Green Creek (ranging 292–354 and 603–740, respectively)
compared to NDS units in this study. This is likely due to differences between mature and newly colonized mats, and may suggest that P amendments accelerate community assembly processes toward a later successional flora.
The predictable alteration of the microbial community
composition by P amendments was also of interest. The
Bacteroidetes-dominated communities found in the control and
N addition treatments are comparable to previous freshwater
surveys from the region (Michaud, Šabacká and Priscu 2012;
Stanish et al. 2013b) and from other stream habitats (Zeglin
2015). However, the addition of P shifted the communities to
dominance by Proteobacteria. Several other studies have reported a strong response by aquatic Proteobacteria to nutrient addition (Newton and McMahon 2011; Staley et al. 2014);
however, the relationship between eutrophication and Pro-
11
teobacterial dominance deserves further study. The dramatic
responses in both microbial diversity and community composition highlight the potential importance of future changes in
nutrient regimes in MDV streams for biomass production and
microbially-mediated biogeochemical cycling.
Conclusions and further directions
Previous stream-scale studies in the MDVs have examined the
uptake and transformations of stream nutrients, and demonstrated that nutrient concentrations are generally lower in
streams with abundant mats compared to those where mats
are sparse. However, the relationship between ambient nutrient
concentration and mat growth and composition has been more
difficult to resolve. By utilizing NDS units, we here show that nutrients have significant effects on both the quantity and composition of biofilms, and could help account for reach-scale heterogeneity observed within these streams. However, whether variable nutrient concentrations as a function of patchy hyporheic
flow or thermokarst wasting can directly influence microbial
communities remains to be tested. Therefore, we suggest future investigators consider the different mechanisms responsible for the mobilization of N and P as potentially important variables to understanding patterns in polar and alpine microbial
community structure in light of deglaciation, the evolution of
streambeds and newly formed lotic environments.
ACKNOWLEDGEMENTS
We thank Chris Jaros, Dan Liptzin, Pat Kociolek, Kalina
Manoylov, Steve Juggins, Devin Castendyk, Lee Stanish, Jeremy
Dyke, Kelli Feeser, Jon Denner, Garrett Rue, John Berggren, Rae
Spain and the McMurdo Carpenters for field, laboratory and intellectual assistance. Detailed comments by three anonymous
reviewers greatly improved the manuscript.
FUNDING
This work was supported by the National Science Foundation
[NSF-1245991 to DJVH] and the McMurdo Long-Term Ecological
Research project [NSF-1115245].
Conflict of interest. None declared.
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