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Microbial community diversity and composition varies with habitat characteristics and biofilm function in macrophyte-rich streams

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Biofilms in streams play an integral role in ecosystem processes and function yet few studies have investigated the broad diversity of these complex prokaryotic and eukaryotic microbial communities. Physical habitat characteristics can affect the composition and abundance of microorganisms in these biofilms by creating microhabitats. Here we describe the prokaryotic and eukaryotic microbial diversity of biofilms in sand and macrophyte habitats (i.e. epipsammon and epiphyton, respectively) in five macrophyte-rich streams in Jutland, Denmark. The macrophyte species varied in growth morphology, C:N stoichiometry, and preferred stream habitat, providing a range in environmental conditions for the epiphyton. Among all habitats and streams, the prokaryotic communities were dominated by common phyla, including Alphaproteobacteria, Bacteriodetes, and Gammaproteobacteria, while the eukaryotic communities were dominated by Stramenopiles (i.e. diatoms). For both the prokaryotes and eukaryotes, the epipsammon were consistently the most diverse communities and the epiphytic communities were generally similar among the four macrophyte species. However, the communities on the least complex macrophyte, Sparganium emersum, had the lowest richness and evenness and fewest unique OTUs, whereas the macrophyte with the most morphological complexity, Callitriche spp., had the highest number of unique OTUs. In general, the microbial taxa were ubiquitously distributed across the relatively homogeneous Danish landscape as determined by measuring the similarity among communities (i.e. Sørensen similarity index). Furthermore, we found significant correlations between microbial diversity (i.e. Chao1 rarefied richness and Pielou's evenness) and biofilm structure and function (i.e. C:N ratio and ammonium uptake efficiency, respectively); communities with higher richness and evenness had higher C:N ratios and lower uptake efficiency. In addition to describing the prokaryotic and eukaryotic community composition in stream biofilms, our study indicates that 1) physical habitat characteristics influence microbial diversity and 2) the variation in microbial diversity may dictate the structural and functional characteristics of stream biofilm communities. This article is protected by copyright. All rights reserved.
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Microbial community diversity and composition varies with habitat
characteristics and biofilm function in macrophyte-rich streams
Peter S. Levi, Piotr Starnawski, Britta Poulsen, Annette Baattrup-Pedersen, Andreas Schramm
and Tenna Riis
P. S. Levi (peter.levi@drake.edu), A. Baattrup-Pedersen and T. Riis, Aquatic Biology, Dept of Bioscience, Aarhus University, Aarhus, Denmark.
Present address for PSL: Environmental Science and Policy, Drake University, Des Moines, IA, USA. – P. Starnawski, B. Poulsen and
A. Schramm, Microbiology, Dept of Bioscience, Aarhus University, Aarhus, Denmark.
Biofilms in streams play an integral role in ecosystem processes and function yet few studies have investigated the broad
diversity of these complex prokaryotic and eukaryotic microbial communities. Physical habitat characteristics can affect
the composition and abundance of microorganisms in these biofilms by creating microhabitats. Here we describe the
prokaryotic and eukaryotic microbial diversity of biofilms in sand and macrophyte habitats (i.e. epipsammon and
epiphyton, respectively) in five macrophyte-rich streams in Jutland, Denmark. e macrophyte species varied in growth
morphology, C:N stoichiometry, and preferred stream habitat, providing a range in environmental conditions for the
epiphyton. Among all habitats and streams, the prokaryotic communities were dominated by common phyla, including
Alphaproteobacteria, Bacteriodetes, and Gammaproteobacteria, while the eukaryotic communities were dominated by
Stramenopiles (i.e. diatoms). For both the prokaryotes and eukaryotes, the epipsammon were consistently the most diverse
communities and the epiphytic communities were generally similar among the four macrophyte species. However, the
communities on the least complex macrophyte, Sparganium emersum, had the lowest richness and evenness and fewest
unique OTUs, whereas the macrophyte with the most morphological complexity, Callitriche spp., had the highest number
of unique OTUs. In general, the microbial taxa were ubiquitously distributed across the relatively homogeneous Danish
landscape as determined by measuring the similarity among communities (i.e. Sørensen similarity index). Furthermore, we
found significant correlations between microbial diversity (i.e. Chao1 rarefied richness and Pielou’s evenness) and biofilm
structure and function (i.e. C:N ratio and ammonium uptake efficiency, respectively); communities with higher richness
and evenness had higher C:N ratios and lower uptake efficiency. In addition to describing the prokaryotic and eukaryotic
community composition in stream biofilms, our study indicates that 1) physical habitat characteristics influence microbial
diversity and 2) the variation in microbial diversity may dictate the structural and functional characteristics of stream
biofilm communities.
Our understanding of the role that microbes have in the
structure and function of living entities, from organisms to
ecosystems, is expanding at rapid speed. e recent devel-
opment of next-generation sequencing for prokaryotic and
eukaryotic organisms allows for more frequent and exten-
sive investigations of microbial diversity (Metzker 2010),
allowing ecologists to describe the composition of these
communities in detail and address questions on the rela-
tionships between microbial diversity and other ecosystem
attributes. In aquatic ecosystems, the relationship between
the physicochemical characteristics of the ecosystem, the
functional processes therein, and the microbial community
are often closely interwoven (Tatariw et al. 2013). Reciprocal
interactions exist among these ecosystem attributes implying
that as one changes, others do as well (Finlay et al. 1997).
For example, the diversity of microorganisms in stream bio-
films has been shown to influence hydrologic retention and,
in turn, the use of available resources (Battin et al. 2003 and
Singer et al. 2010, respectively). Furthermore, environmental
variation among different habitats within the same ecosys-
tem may create filters that determine which prokaryotes and
microbial eukaryotes can persist in certain niches (Hempel
et al. 2010, Besemer et al. 2012). ese studies demonstrate
that microbial communities can influence environmental
characteristics and, likewise, environmental characteristics
can dictate what microbes are present.
e diversity of microbial communities may vary within
and between ecosystems due to strong environmental
gradients and/or spatial variation. For instance, the diver-
sity of epilithic biofilms varied in a series of connected
lakes across an altitudinal gradient from montane to alpine
ecosystems (Bartrons et al. 2012). Similarly, spatial dis-
tance can influence diversity in disconnected ecosystems,
because certain prokaryotes and eukaryotes may be dispersal
limited (Lee et al. 2013). Much of our understanding on
the interactions of biofilms and their environment comes
© 2016 e Authors. Oikos © 2016 Nordic Society Oikos
Subject Editor: Silke Langenheder. Editor-in-Chief: Dries Bonte. Accepted 17 August 2016
Oikos 000: 001–012, 2016
doi: 10.1111/oik.03400
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from studies in marine and lentic ecosystems (reviewed by
Wahl et al. 2012), though environmental and/or spatial
variation have been shown to dictate microbial diversity in
stream ecosystems as well. For example, Acidobacteria domi-
nated the composition of microbial communities in streams
with low pH impacted by acid mine drainage, while more
neutral streams had higher abundances of alpha-, beta- and
gammaproteobacteria (Fierer et al. 2007), sub-groups of a
phylum that frequently dominates microbial communities
in aquatic ecosystems (He et al. 2014). In contrast, spatial
variation influenced diatom diversity more strongly than
habitat-specific environmental variation across a broad geo-
graphic region (Heino et al. 2010). Lotic ecosystems are
highly connected due to the constant flow of water yet also
have highly heterogeneous habitats and, therefore, provide
a strong model system to explore how spatial and environ-
mental variation may control the composition and diversity
of microbial communities.
Streams are highly connected ecosystems, receiving inputs
from upstream, riparian, and groundwater habitats, and
often have a high degree of heterogeneity among the various
habitats within a reach (e.g. pools, riffles, hyporheos). ere-
fore, microorganisms from many different source popula-
tions may be easily dispersed throughout stream networks
while habitat-specific physicochemical characteristics may
dictate the composition of microbial communities (Hempel
et al. 2010). Microbial communities grow and develop on
the myriad surfaces in stream habitats, forming biofilms held
together by water, microorganisms, polysaccharide excre-
tions, and other organic and inorganic materials (Sutherland
2001), and include epilithon on rocks, epipsammon on sand
and epiphyton on aquatic vegetation (i.e. macrophytes). e
formation and growth of aquatic biofilms are often initiated
by certain taxa that have an ability to co-aggregate, such
as certain beta- and gammaproteobacteria (Besemer et al.
2012). As the microbial biofilms continue to develop, they
can play an integral role in stream structure and function
(Finlay et al. 1997). Biologically, biofilms can assimilate and
transform water column nutrients, such as ammonium and
nitrate (Baker et al. 2009, Levi et al. 2015) and, in so doing,
alter the nutrient availability for other biota in adjacent and
downstream ecosystems. Physically, the microarchitecture of
biofilms alone can act as a zone of hydrologic storage (Battin
et al. 2003), briefly slowing the downstream transportation
of nutrients to allow greater processing and transformation
rates. e degree to which stream biofilms may influence
ecosystem structure and function depends, in part, on the
substrate on which the biofilms grow and develop.
In many lowland streams, macrophytes provide a
dynamic surface for biofilms as the plants themselves grow
and metabolize (Hempel et al. 2010). Marcophytes vary in
the complexity of their growth forms, which can alter physi-
cochemical attributes to different degrees (e.g. water velocity;
Dodds and Biggs 2002) and create additional niches with
habitats for microorganisms (Grossart et al. 2013). Biotic
complexity and patchiness can affect the diversity of micro-
organisms within macrophyte beds (Eriksson et al. 2006).
Furthermore, the composition of microbial communities
associated with macrophytes often differs from the microbial
community suspended in the water column or in biofilms
on nearby inanimate objects (Hempel et al. 2010, He et al.
2014). However, few studies have investigated the patterns
in microbial communities across varying environmental
conditions at small scales (Lear et al. 2014), such as between
two macrophyte species with different growth morphology.
e influence of macrophytes on microbial community
composition may, in turn, affect the structure and function
of the stream biofilms.
e hypothesis that microbial diversity may influence
function is not new (Finlay et al. 1997). For example,
high diversity in algal assemblages had a positive effect on
nitrate uptake in stream ecosystems (Baker et al. 2009).
In addition, physical habitat complexity can increase both
microbial diversity and resource use in stream biofilms
(Singer et al. 2010). However, no studies have investigated
the role of both prokaryotic and eukaryotic diversity on
functional processes across a gradient in physical habitat
complexity such as that created by the growth morpholo-
gies of different macrophyte species. e goals of our study
were three-fold: 1) to describe the prokaryotic and eukary-
otic communities in epipsammic and epiphytic biofilms, 2)
to compare the composition of these communities across
habitats with varying physical substrate and environmental
conditions, and 3) to investigate whether microbial diver-
sity was related to biofilm structure and function, measured
as C:N ratio and ammonium (NH4
) uptake efficiency,
respectively.
Material and methods
Study sites, field collection, and sample preparation
We collected biofilm samples from five macrophyte-rich
streams in Jutland, Denmark, during the summer in 2012.
e streams were located in watersheds with mixed land-use
that were primarily dominated by agriculture (Table 1). We
determined the land cover of our study watersheds using
ArcGIS software and images from the geospatial database
maintained by the Geodata Board of the Danish Ministry of
Table 1. Watershed and stream characteristics of the five study streams in Jutland, Denmark. Streams are ordered by increasing macrophyte
coverage. Stream abbreviations are used throughout the manuscript.
Stream Lat. (N) Long. (E)
Watershed
area (km2)
Agricultural
land-cover (%)
Forested
land-cover (%)
Baseflow
discharge (l s–1)
Mean
width (m)
Macrophyte
coverage (%)
Fåremølle (FML) 56°278°1532.3 85.4 9.4 164 2.9 5.9
Lilleå (LIL) 56°1510°0421.7 72.8 16.8 142 2.5 27.6
Idom (IDM) 56°208°2821.5 49.5 26.9 223 3.3 37.7
Gryde (GRY) 56°198°3232.6 50.4 27.3 249 4.0 40.7
Madum (MAD) 56°148°2430.0 33.3 48.8 141 3.1 66.6
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the Environment (< www.gst.dk >). We selected the streams
based on their similar watershed size, land-use, and physi-
cochemical characteristics. Given that our research was an
in situ field study, the species richness of the macrophyte
communities and overall macrophyte coverage varied among
the replicate streams (2–4 species and 6 to 67%, respectively;
Table 1). e stream sediments were predominantly sand
with scant patches of gravel and fine benthic organic matter
(FBOM) in the margins.
To sample the epipsammic and epiphytic biofilms, we
collected a benthic core of sand (core diameter 28 mm,
depth 16 mm) and harvested several cuttings of the
various macrophyte species present in each study stream.
We immediately placed the samples in dark containers
with a small volume of stream water, set the containers on
ice, and transported them back to the laboratory. In the
laboratory, we carefully removed the epiphytic and epip-
sammic biofilms from the macrophytes and sediment,
respectively. For the epiphytic biofilms, we placed the mac-
rophyte samples in a plastic tray with a minimal amount of
deionized water and gently brushed the stems and leaves
of the macrophyte, creating a biofilm slurry. We removed
the macrophytes to a second tray and repeated the process.
After thoroughly rinsing and removing the macrophyte, we
combined the biofilm slurries from both trays, gently agi-
tated them, and filtered a portion of the slurry onto a Supor
polyethersulfone (PES) filter (pore size 0.2 mm). e
average wet mass of the samples was 0.03 g (range 0.01
to 0.1 g). For the epipsammic biofilms, we agitated the
sand and water by gently swirling the sample and using a
syringe to sample the suspended biofilm, fine particulate
matter and sand grains (Stevenson and Rollins 2007). We
then filtered a portion of the slurry onto a Supor PES filter
and the average wet mass was 0.1 g (range 0.02 to 0.2
g). To avoid contamination among samples, we changed
our gloves and soaked the trays and filtering apparatus in a
mild bleach solution for 10 min between processing each
sample. We sealed the filters into individual test tubes and
immediately placed them into a –80°C freezer until the
DNA extraction.
DNA extraction and sequencing
We used IonTorrent sequencing of 16S rRNA and 18S rRNA
gene amplicons to analyze the prokaryotic and eukaryotic
diversity of the epiphytic and epipsammic biofilms. We
extracted total DNA from the biofilm samples via enzymatic
and mechanical lysis with the Fast DNA Spin Kit for Soil,
a protocol optimized for biofilms (Foesel et al. 2008). To
quantify the DNA concentrations, we used a Qubit fluo-
rometer and the Qubit dsDNA HS Assay Kit. We amplified
bacterial and archaeal 16S rRNA genes using primer pair
Univ519F (5-CAGCMGCCGCGGTAA-3) and Univ802R
(5-TACNVGGGTATCTAATCC-3; Claesson et al. 2009,
Wang and Qian 2009) and amplified eukaryotic 18S rRNA
genes using primer pair Euk345f (5-AAGGAAGGCAG
CAGGCG-3) and Euk499r (5-CACCAGACTTGCCCT
CYAAT-3; Zhu et al. 2005). We conducted all the PCRs
with the KAPA HiFi PCR Kit. First, we ran 20 PCR
cycles at an annealing temperature of 49°C and 53°C for
the prokaryotes and eukaryotes, respectively; these initial
amplification reactions contained bovine serum albumin
(0.2 mg ml–1). Next, we barcoded the PCR products using
the Ion Torrent Xpress system for an additional 10 PCR
cycles, raising the annealing temperature to 61°C. en we
purified the barcoded PCR products with the Agencourt
AMPure XP Kit, quantified the DNA concentration with
the Qubit system, pooled the PCR products, and prepared
the sequencing libraries according to the Ion Torrent Manual
(Preparing Short Amplicon ( 350 basepairs) Libraries). For
quality control of the library, we used both a Qubit Fluo-
rometer and Bioanalyzer 2100 with High Sensitivity DNA
Analysis Kit. We performed an Emulsion PCR on a One
Touch Instrument with the Ion PGM Template OT2 400
Kit, and sequenced the samples on the Ion Torrent PGM
with an Ion 314 Chip and the Ion PGM Hi-Q Sequencing
Kit according to the manufacturer’s instructions.
We conducted the quality filtering and clustering of
the operational taxonomic units (OTUs) in Mothur, ver.
1.36.1 (Schloss et al. 2009). First, we discarded reads with
more than seven homopolymers and those with lengths
below 200 basepairs for prokaryotes and 150 basepairs
for eukaryotes. Next, we aligned and classified the data
using a combined prokaryote-eukaryote Silva reference
database, ver. 123 (Quast et al. 2013). We removed chime-
ras with the Uchime tool (Edgar 2013) and clustered the
resulting sequences into OTUs with a similarity cutoff of
97% and the furthest-neighbor algorithm. We processed
the OTU-frequency table and classification data in R and
the rarefaction curves, subsampling and diversity indices
(i.e. Shannon’s diversity index, Chao1 rarefied richness,
ACE, and Pielou’s evenness) using the Vegan package
(ver. 2.3). Our sequences are publicly available from MG-
RAST (< http://metagenomics.anl.gov >) under the IDs
4681462.3 and 4681503.3.
Stream ecosystem predictor variables
We measured various physical, chemical, and biological
characteristics at the habitat and biofilm scales, including
metrics of both structure and function. Here we briefly
describe the methods used during our present study and
include citations with more thorough descriptions of spe-
cific methods, particularly from our previous study on these
streams (Levi et al. 2015; see also Supplementary material
Appendix 1).
At the habitat scale, we quantified the biomass and
morphological complexity of the macrophyte species in
each stream. To determine macrophyte coverage and vol-
ume, we measured the median width, length, and depth
of every macrophyte bed in the study reaches. We sam-
pled the submerged macrophyte species that were found
in at least three of the five streams, which included Berula
erecta, Callitriche spp., Ranunculus peltatus and Sparganium
emersum (Table 2; Moeslund et al. 1990). We determined
the complexity of the macrophytes by measuring the perim-
eter-to-area ratio (P:A) of each species, which represented
the surface area available for epiphytic biofilm. We calcu-
lated the P:A with black-and-white images of the top 20 cm
of five replicate individuals of each macrophyte species. We
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factor and ‘stream’ as the block (Zar 2009). We conducted
a Tukey’s post hoc comparison test with all statistically
significant tests (i.e. p-value 0.05) to determine which
habitats varied from each other. To examine the variation
in diversity among habitats and streams (i.e. b-diversity),
we calculated the Sørensen index and ran separate one-way
ANOVAs with ‘habitat’ and ‘stream’ as the factors. We cre-
ated Venn diagrams to illustrate the shared OTUs among
habitats using the VennDiagram package (ver. 1.6.9) in R.
We examined the differences among the communities with
a permutational MANOVA to assess the patterns in micro-
bial composition between habitats and nested by stream
using the PERMANOVA add-on in the PRIMER soft-
ware package, ver. 6 (Clarke and Gorley 2006). Given the
significant results of the PERMANOVA, we conducted a
canonical analysis of the principal coordinates to assess the
differences among habitats (Anderson and Willis 2003).
Using Pearson’s correlation (Zar 2009), we examined
whether the richness and evenness of the microbial com-
munities were related to the measures of macrophyte com-
plexity (i.e. leaf P:A, bed density). Finally, we used both
one-way RB ANOVA and Pearson’s correlation to investi-
gate the relationship between microbial diversity and biofilm
characteristics (i.e. C:N, NH4
uptake efficiency). ough
we analyzed replicate samples for the biofilm characteris-
tics (n 5), we used the mean value in the correlations.
We used Chao1 rarefied richness and Pielous evenness for
these correlations rather than diversity indices like Shan-
non’s in order to separately account for species richness
and evenness. We tested all of our data for normality and
removed statistical outliers when studentized residuals
exceeded 2.5 (Zar 2009). We completed our statistical anal-
yses using SYSTAT (ver. 10) and R (ver. 3.2.0 in R-studio
< www.r-project.org >).
imported the images into ImageJ software, which measured
the perimeter and area of each individual sample (National
Institutes of Health, USA). We used the P:A and volume of
each macrophyte bed to calculate the amount of surface area
per cubic meter of macrophyte bed for each species (i.e. bed
density; m2 m–3).
At the biofilm scale, we measured metrics of both
structure and function of these communities. To calculate
the carbon-to-nitrogen ratio (C:N) of biofilms from each
stream and habitat, we determined the C and N content
using a total organic carbon analyzer. As a measure of biofilm
function, we quantified the in situ NH4
uptake efficiency
of these biofilms (Levi et al. 2015). In short, we conducted
24-h additions of 15N-NH4
in each study reach following
standard methods (Mulholland et al. 2000) within two to
four days of collecting the samples for the biofilm com-
munity analysis. We calculated the compartment-specific
NH4
uptake rate by measuring the concentration of 15N
in the epipsammon and epiphyton relative to the 15N con-
centration of the stream water (Levi et al. 2015). With these
data and the N biomass of the biofilms, we calculated the
biomass-specific NH4
uptake (i.e. uptake efficiency; mg N
mg Nbiomass–1 d–1) as follows:
uptake rate compartmentspecificNHuptake
Nbiomass
=+
4
Our stable isotope samples were analyzed with a mass
spectrometer.
Data and statistical analyses
To examine the variation in richness and evenness among
the communities, we used a one-way randomized-block
analysis of variance (RB ANOVA) with ‘habitat’ as the
Table 2. Mean ( SE) physical and biological measurements of the different macrophyte species ordered in terms of increasing bed density.
Leaf morphology photographs represent top 20 cm of each species. Data represent mean values with standard error in parentheses.
Macrophyte species
Leaf morphology
Presence in streams*F-I-G-M F-L-I-G L-I-G-M L-I-G
Dry mass (g m–3)#50 (8) 82 (15) 195 (20) 79 (12)
Bed density (m2 m–3)#2.4 (0.6) 5.5 (1.4) 9.7 (2.3) 11.6 (3.3)
Leaf P:A 2.5 (0.2) 2.1 (0.1) 13.4 (1.3) 10.0 (0.6)
C:N 13.1 (0.8) 9.7 (0.2) 9.4 (0.3) 9.2 (0.6)
*Streams abbreviated with first letter of stream (F Fåremølle, L Lilleå, I Idom, G Gryde, M Madum).
#Volume for dry mass and bed density were calculated for 1m 1m 0.1m of the macrophyte bed. The volume was only determined to
0.1m of depth because that was the depth to which we sampled (Levi et al. 2015).
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were still increasing in species number (Supplementary
material Appendix 3). However, given the magnitude of
bacterial OTUs reported, we are confident we sampled
these communities to an appropriate depth for our analysis
(Gotelli and Colwell 2001).
e Sørensen index (e.g. similarity coefficient) demon-
strated that the prokaryotic communities had comparable
similarity among habitats and streams (Table 3; one-way
ANOVA, p 0.3 and 0.6, respectively). However, the
eukaryotes of the epiphytic biofilms on S. emersum were
more variable between the streams than the eukaryotes in the
epipsammon or epiphyton of the other three macrophytes,
which all had comparable similarity among streams (one-
way ANOVA p 0.001; Table 3). In addition, the eukary-
otic communities in Fåremølle were more similar to each
other than the eukaryotic communities were to each other in
the other four streams (p 0.04).
In general, the majority of prokaryotes in the biofilm
communities were Alphaproteobacteria (mean SE
abundance 24.6 1.9%) and Bacteriodetes (21.4 2.0%;
Fig. 2A). Two epiphytic communities on S. emersum were
dominated by cyanobacteria (abundance 34%), though
cyanobacteria only accounted for 7.2% of the OTUs among
all the biofilms. Stramenopiles (i.e. diatoms) was the domi-
nant eukaryotic phylum in most streams (47.5 4.9%;
Fig. 2B). For example, diatoms alone accounted for more
than 75% of the eukaryotic OTUs among all habitats in
Results
Prokaryotic and eukaryotic diversity across streams
and habitats
Among all biofilms we collected across the five study streams,
the prokaryotes were more diverse than the eukaryotes
and, in both taxonomic domains, richness and evenness gen-
erally varied across the stream habitats. e mean ( SE)
Chao1 rarefied richness was 4050 320 and 2270 120
for the prokaryotes and eukaryotes, respectively, while the
mean ( SE) Pielou’s evenness was 0.840 0.015 and
0.576 0.23, respectively. A similar pattern was observed
for other measures of diversity, including the inverse of
Simpsons index, Shannon’s diversity index, and ACE
(Supplementary material Appendix 2). Across stream habi-
tats, the prokaryotes in the epipsammon and epiphyton of
Berula erecta had higher richness and evenness than the other
epiphytic communities (Fig. 1A, 1C; one-way RB ANOVA,
pHABITAT 0.001; Tukey’s PCT, p 0.05). e evenness
of the eukaryotic communities also varied by habitat (one-
way RB ANOVA, pHABITAT 0.01), where the epipsammon
and B. erecta epiphyton had higher evenness than the epi-
phyton on Sparganium emersum (Fig. 1D). e asymptotes
of the rarefaction curves for the eukaryotic communities
demonstrated that these communities were sampled deep
enough, though several of the prokaryotic communities
(A) Prokaryotes
Chao1 rarefied richness
0
2000
4000
6000
8000 (B) Eukaryotes FML
LIL
IDM
GRY
MAD
pHABITAT = 0.06
pSTREAM = 0.7
pHABITAT < 0.001
pSTREAM = 0.7
a
c
ab
bc
bc
(C) Prokaryotes
Sand
Callitrichespp.
R.peltatus
B.erecta
S.emersum
Pielou's evenness
0.0
0.2
0.4
0.6
0.8
1.0
(D) Eukaryotes
Sand
Callitrichespp.
R.peltatus
B.erecta
S.emersum
pHABITAT = 0.01
pSTREAM = 0.04
pHABITAT < 0.001
pSTREAM = 0.8
a
bc
ab
c
abc
a
b
a
ab
ab
Figure 1. Chao1 rarefied richness and Pielou’s evenness of the (A, C) prokaryotic and (B, D) eukaryotic biofilm communities. Letters
denote habitats with statistically different communities (Tukey’s PCT). Epiphytic communities listed along the x-axis in terms of decreasing
morphological complexity (i.e. macrophyte bed density; Table 2). Note: not all macrophyte species were found in all streams.
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between multiple, but not all, habitats (Fig. 3A). Among
the epiphyton communities, B. erecta had the highest per-
centage of unique prokaryotic OTUs (i.e. 10.7% of the
total OTUs) while S. emersum had the fewest unique OTUs
(2.3%). ere were fewer eukaryotic OTUs, but the pattern
among habitat was similar. More than half of the unique
OTUs were in the epiphytic biofilms alone (60.2%), 11.8%
were unique to the epipsammon, 9.7% were shared among
all habitats, and the remaining 18.3% were shared between
Fåremølle. Madum was an exception where Stramenopiles
was in much lower abundance (mean 13.4 5.3%) and
these biofilms were instead dominated by fungi or Alveolates
(32.0 40.8% and 28.5 19.2%, respectively).
e most abundant prokaryotic and eukaryotic OTUs
were present in all of the biofilms. Among the prokaryotes,
46.9% of the OTUs were unique to the epiphyton, 21.4%
were unique to epipsammon, 8.1% were present in all
habitats, and the remaining 23.5% of the OTUs were shared
Table 3. Similarity of prokaryotic and eukaryotic communities in biofilms among streams and habitats expressed as the Sørensen index
( SE). Bold values represent significantly different Sørensen indices for streams or habitats within a taxonomic domain.
Stream Prokaryotes Eukaryotes Habitat Prokaryotes Eukaryotes
FML 0.36 (0.04) 0.54 (0.02) Sand 0.36 (0.02) 0.39 (0.01)
LIL 0.40 (0.03) 0.47 (0.04) S. emersum 0.32 (0.02) 0.30 (0.03)
IDM 0.33 (0.03) 0.40 (0.03) B. erecta 0.35 (0.01) 0.41 (0.02)
GRY 0.33 (0.03) 0.38 (0.02) R. peltatus 0.31 (0.02) 0.36 (0.02)
MAD 0.32 (0.05) 0.39 (0.03) Callitriche spp. 0.33 (0.04) 0.38 (0.02)
Alphaproteobacteria
Betaproteobacteria
Deltaproteobacteria
Gammaproteobacteria
Bacteroidetes
Cyanobacteria
Verrucomicrobia
Chloroflexi
Acidobacteria
Actinobacteria
Planctomycetes
Nitrospirae
Firmicutes
Unclassified
Other
Madum
Gryde
IdomLilleåFaremølle
(A)
Sand
S. emersum
B. erectaR. peltatus
Callitriche spp.
Figure 2. Taxonomic composition of the (A) prokaryotic and (B) eukaryotic epipsammon and epiphyton at the phylum-level in the five
stream ecosystems.
EV-7
the other three macrophyte species overlapped with each
other.
e measures of macrophyte complexity (i.e. P:A, bed
density) were often not correlated with the richness or even-
ness of the microbial communities. e Pielou’s evenness of
the eukaryotes was positively correlated with bed density of
the macrophyte species (r 0.53, p 0.04). However, the
rarefied richness of both the prokaryotes and eukaryotes
as well as the Pielou’s evenness of the prokaryotes were not
correlated with either measure of macrophyte complexity.
Variation in structure and function among microbial
communities
e physical structure of the biofilm communities, expressed
as the C:N ratio, varied among habitats and was correlated
to the richness and evenness of the microbial communities.
C:N was consistently higher in the epipsammon relative
to the epiphyton (Fig. 5A; one-way RB ANOVA, pHABITAT
0.001). Among the macrophyte species, the epiphytic
C:N was lowest in S. emersum (Tukey’s PCT, p 0.01),
but did not vary among the other species. e C:N of
several habitats (Fig. 3B). Among the different macrophyte
species, Callitriche spp. had the most unique OTUs (20.0%
of the total) while S. emersum again had the fewest (2.9%).
In general, the most abundant OTUs were found across all
five streams and often shared among habitats (Supplemen-
tary material Appendix 4, 5). For instance, the most com-
mon eukaryotic OTU in the epiphyton and epipsammon
was a diatom in the order Naviculales (Supplementary mate-
rial Appendix 5).
Ecosystem- and habitat-scale predictors of biofilm
richness and evenness
e biofilm communities varied by habitat as demon-
strated using PERMANOVA and a canonical analysis of
principal coordinates (PERMANOVA, p 0.001 and
0.007, respectively). Both the prokaryotic and eukaryotic
communities in the 20 biofilms separated by habitat with
epipsammon clustering as a distinct group relative to the
epiphyton (Fig. 4). In addition, the microbial communi-
ties on Ranunculus peltatus appeared to cluster separately
for the prokaryotes and eukaryotes while the epiphyton on
Stramenopiles
Alveolata
Viridiplantae
Fungi
Haptophyceae
Cryptophyta
Other
Unclassified
Madum
Gryde
Idom
Lilleå
Faremølle
(B)
Sand
S. emersumB. erectaR. peltatus
Callitriche spp.
Figure 2. (Continued).
EV-8
NH4
mg Nbiomass–1 d
–1, respectively; Fig. 6A). While the
efficiency differed significantly between the sand and mac-
rophyte habitats (one-way RB ANOVA, pHABITAT 0.001),
uptake efficiency did not vary among the macrophyte spe-
cies. e Chao1 rarefied richness of the prokaryotic commu-
nities was negatively correlated to NH4
uptake efficiency
(r –0.66, p 0.004; Fig. 6B). e uptake efficiency of
the eukaryotes also decreased as richness increased, but the
correlation was not significant (Fig. 6D). Pielou’s evenness of
the prokaryotic and eukaryotic communities was also nega-
tively correlated with NH4
uptake efficiency (r –0.62
and –0.63, respectively; p  0.008; Fig. 6C, E). Among the
epiphyton communities alone, there were no significant
correlations between uptake efficiency and biofilm richness
or evenness.
Discussion
Microbial diversity and composition of biofilms
differed by habitat
e microbial communities in the epipsammon were
consistently more diverse than the epiphyton across all stream
biofilms in our study. e differences we observed between
the two habitats were largely driven by the rare OTUs (e.g.
abundance 0.005%) while the most abundant OTUs were
generally shared between all habitats and streams, a common
the prokaryotic communities was positively correlated
to the Chao1 rarefied richness (r 0.73, p 0.001;
Fig. 5B). Similarly, the richness of the eukaryotic com-
munities increased with C:N, but the correlation was not
significant (Fig. 5D). Pielou’s evenness was positively cor-
related with biofilm C:N of the prokaryotes and eukary-
otes (r 0.72 and 0.56, respectively; p 0.01; Fig. 5C,
E). When analyzing the epiphytic communities alone,
C:N was positively correlated with the rarefied richness of
the prokaryotes (r 0.53, p 0.04), eukaryotes (r 0.58,
p 0.02), and Pielou’s evenness of the eukaryotes (r 0.55,
p 0.03).
e biomass-specific NH4
uptake rates (i.e. uptake
efficiency) varied substantially between the microbial com-
munities from the different habitats. e uptake efficiency
of the epiphytic biofilms was nearly two orders of magnitude
higher than the efficiency of the epipsammic biofilms (mean
SE uptake efficiency 0.3 0.04 and 0.008 0.002 mg
Figure 3. Venn diagrams depicting the unique OTUs for the (A)
prokaryotic and (B) eukaryotic communities among the stream
habitats. e data represent OTUs found in 1 sample of each
habitat or combination of habitats (i.e. rare OTUs found in only
one sample are excluded).
(A) Prokaryotes
–0.3 –0.2 –0.10.0 0.10.2 0.30.4 0.5
–0.5 –0.4 –0.3 –0.2 –0.10.0 0.10.2 0.3
–0.6
–0.4
–0.2
0.0
0.2
0.4
0.6
Sand
S. emersum
B. erecta
R. pelatatus
Callitriche spp.
(B) Eukaryotes
Canonical analysis - Axis 1
Canonical analysis - Axis 2
–0.4
–0.2
0.0
0.2
0.4
0.6
Figure 4. Canonical analysis of principal coordinates of (A) prokary-
otic and (B) eukaryotic communities.
EV-9
inorganic nitrogen concentrations change rapidly in the top
0.3 mm of sand in stream ecosystems (Revsbech et al. 2005).
We sampled to a depth of 16 mm and, therefore, the strong
resource gradient allowed for the co-existence of a highly
diverse suite of microbes. In addition, the three-dimensional
matrix of the sand habitat provided the epipsammon with
more surface area for biofilm growth and development than
the surfaces of the macrophyte leaves. irdly, the high rich-
ness and evenness of the epipsammic communities may have
pattern in freshwater microbial communities (Besemer et al.
2012). Variation in the abundance and composition of
OTUs within the microbial communities was likely influ-
enced by variation in spatial and environmental conditions
as has been demonstrated in aquatic ecosystems (Heino et al.
2010, He et al. 2014, Lear et al. 2014). For one, the epip-
sammic communities experienced a higher degree of resource
heterogeneity within the microhabitats of the sand matrix
than the epiphytic communities. For example, oxygen and
(A)
Sand
Callitriche spp.
R. peltatus
B. erecta
S. emersum
C:N
0
5
10
15
20 FML
LIL
IDM
GRY
MAD
(B) Prokaryotes
1000 2000 3000 4000 5000 6000 7000
Sand
S. emersum
B. erecta
R. peltatus
Callitriche spp.
(D) Eukaryotes
Chao1 rarefied richness
1000 1500 2000 2500 3000 3500
C:N
0
5
10
15
20
r = 0.73
p < 0.001
r = 0.58
p = 0.02
pHABITAT < 0.001
pSTREAM < 0.001
a
c
bbb
(C) Prokaryotes
0.70 0.75 0.80 0.85 0.90 0.95 1.00
r = 0.72
p < 0.001
(E) Eukaryotes
Pielou's evenness
0.3 0.4 0.5 0.6 0.7 0.8
r = 0.56
p = 0.01
Figure 5. (A) C:N of epipsammon and epiphyton among the habitats and streams. Letters denote habitats with statistically different C:N
(Tukey’s PCT). Biofilm C:N of the prokaryotic and eukaryotic communities were correlated with Chao1 rarefied richness (B and D,
respectively) and Pielou’s evenness (C and E, respectively).
(A)
Sand
Callitriche spp.
R. peltatus
B. erecta
S. emersum
Uptake efficiency
(mg NH4
+ mg Nbiomass
-1 d-1)
0.0
0.1
0.2
0.3
0.4
0.5
0.6
LIL
IDM
GRY
MAD
(B) Prokaryotes
1000 2000 3000 4000 5000 6000 7000
Sand
S. emersum
B. erecta
R. peltatus
Callitriche spp.
(D) Eukaryotes
Chao1 rarefied richness
1000 1500 2000 2500 3000 3500
Uptake efficiency
(mg NH4
+ mg Nbiomass
-1 d-1)
0.0
0.1
0.2
0.3
0.4
0.5
0.6
r = –0.66
p = 0.004
r = –0.44
p = 0.08
pHABITAT < 0.001
pSTREAM < 0.001
a
bbb
b
(C) Prokaryotes
0.70 0.75 0.80 0.85 0.90 0.95 1.00
r = –0.62
p = 0.008
(E) Eukaryotes
Pielou's evenness
0.3 0.4 0.5 0.6 0.7 0.8
r = –0.63
p = 0.007
Figure 6. (A) Biomass-specific NH4
uptake (i.e. uptake efficiency) of epipsammon and epiphyton among the habitats and streams. Letters
denote habitats with statistically different uptake efficiency (Tukey’s PCT). Uptake efficiency of the prokaryotic and eukaryotic
communities were correlated with Chao1 rarefied richness (B and D, respectively) and Pielou’s evenness (C and E, respectively).
EV-10
eukaryotes on S. emersum further demonstrates that the
stoichiometry, morphological complexity, and/or high shear
stress of the macrophyte species likely limited the richness of
these communities.
Environmental characteristics at the stream scale likely
influenced the composition of the biofilm communities as
well. e most common eukaryotes in our study were dia-
toms (i.e. Stramenopiles) with the exception of the biofilms
in Madum, where heterotrophic Alveolata and Fungi were
the most dominant phyla. e macrophyte R. peltatus densely
covered two-thirds of the total stream area in Madum, which
may have led to shading of the epiphytic biofilms and higher
organic matter retention (Eriksson et al. 2006) while streams
with less dense macrophyte coverage and, therefore, higher
light availability, were dominated by autotrophic eukaryotes
(e.g. Stramenopiles). Among habitats, the comparably high
richness of epiphyton on B. erecta and epipsammon may be
due to the preferred habitat of B. erecta in the stream chan-
nel relative to the other three macrophyte species. Berula
erecta is most prominent in the stream margin, whereas R.
peltatus and Callitriche spp., which must remain submerged,
and are most prevalent in the thalweg (Riis et al. 2001).
erefore, the communities with high richness on B. erecta
may be subjected to less shear stress, but greater shading
and sediment deposition on the leaves (Piggott et al. 2012);
physical conditions that can affect the microbial community
composition in those epiphytic biofilms.
Previous studies have demonstrated that variation in
environmental characteristics across streams can strongly
dictate the composition of microbial communities therein.
However, differences among communities may not be appar-
ent unless the environmental gradients are drastic (e.g. pH
range from 4.0 to 6.3; Fierer et al. 2007). e streams in our
study were similar lowland, macrophyte-rich streams in a
relatively homogeneous landscape. Furthermore, each reach
was connected to upstream habitats and the surrounding
catchment by the unidirectional flow of water in the streams.
erefore, the high similarity among the streams was likely
the result of limited dispersal constraints on the microbes
in stream networks across a landscape with similar environ-
mental characteristics (Heino et al. 2010). Among streams,
the Sørensen similarity index indicated that the eukaryotic
communities across habitats in Fåremølle were more similar
to each other than communities across habitats within other
streams. Fåremølle was the stream most influenced by human
impacts with a highly straightened channel, low macrophyte
coverage, and high agricultural land-use, which likely acted
as environmental filters on the microbial composition of the
biofilms (Tatariw et al. 2013). Taken together, our results
demonstrate that both habitat and environmental charac-
teristics influence the richness and evenness of microbial
communities.
Is microbial richness and evenness related to biofilm
structure and function?
An objective of our study was to examine the relationship
between metrics of microbial diversity and metrics of biofilm
structure and function. e relationship between biodiversity
and ecosystem function is complex, with results indicating
both positive and negative relationships or, in some cases,
been related to more frequent disturbance at the biofilm-
water interface (e.g. bed movement) relative to the biofilm
communities on the macrophytes.
e richness and evenness of the microbial communities
in the epiphyton varied between species, with some com-
munities having comparable measurements of diversity to
the epipsammon and other communities having much lower
measurements (e.g. Berula erecta and Sparganium emersum,
respectively). e generally lower richness and evenness in
the epiphyton relative to the epipsammon suggests that
intense competition and species sorting dictated the com-
position of the microbial communities on the macrophytes
(Besemer et al. 2012, Lee et al. 2013), which may be related
to a higher degree of substrate stability (i.e. macrophyte leaf
versus sand grains; Eriksson et al. 2006). Furthermore, the
high proportion of unique OTUs in the epiphytic commu-
nities for both prokaryotes and eukaryotes (47 and 60%,
respectively) suggests that the epipsammon did not act as
a source population for the epiphyton. Rather, the OTUs
unique to the epiphyton likely came from upstream or
riparian habitats.
e variation we observed between epiphytic communi-
ties on the different macrophyte species may be related to
macrophyte morphology, chemical composition, habitat
conditions, or a combination of these factors. Among the
four macrophyte species, leaf P:A and bed density varied
by nearly an order of magnitude with complex macrophyte
species providing more microhabitats and niches for biofilm
growth and development (e.g. Callitriche spp. and R. pelata-
tus; Eriksson et al. 2006). For example, macrophytes with a
high degree of complexity decrease water velocity and shear
stress at the leaf–water interface (Dodds and Biggs 2002),
which may affect the richness and evenness of the microbial
communities (Grossart et al. 2013). We observed that Cal-
litriche spp., the most complex macrophyte, had the most
unique eukaryotic OTUs, while S. emersum, the species with
the lowest morphological complexity, had the fewest OTUs.
We also found that biofilms on S. emersum often had lower
richness and evenness than the other epiphytic communi-
ties. Similarly, other studies have reported that different
macrophyte species in marine and lentic ecosystems exhibit
distinct microbial communities (Burke et al. 2010) as a result
of environmental variation or the chemical composition of
the host species (Hempel et al. 2010). e simplified mor-
phology and/or chemical composition of S. emersum, which
had the highest C:N of the four species, may have limited
the eukaryotic richness and evenness. e chemical compo-
sition of a macrophyte species effects the exudates released
(e.g. N, phenolic compounds), which, in turn, can influ-
ence the composition of the microbial community (Hempel
et al. 2010, Kofoed et al. 2012). e stoichiometry and
complexity of B. erecta, Ranunculus peltatus and Callitriche
spp. were more similar, suggesting that variation in richness
and evenness among the epiphyton on these macrophtyes
was due to other characteristics, such as physicochemical
variation among the habitats. Additionally, the Sørensen
similarity index, a measure of the similarity in the compo-
sition of OTUs between communities, demonstrated that
the eukaryotic communities on S. emersum were less similar
to each other than epiphytic and epipsammic communities
were among the other habitats. e low similarity among
EV-11
Conclusions
Our study provides an assessment of the diversity and
composition of epipsammic and epiphytic biofilms in
macrophyte-rich streams, including the eukaryotic commu-
nity. e epipsammon had consistently higher diversity than
the epiphyton, though biofilms in both habitats had few
abundant OTUs and many rare ones. We observed consistent
habitat-scale differences in the composition and diversity of
the biofilm communities, as well as in their NH4
uptake
efficiency, across the five streams. Furthermore, variation
of growth morphology and C:N of the macrophyte species
influenced microbial richness and evenness, supporting our
hypothesis that the physical characteristics of freshwater
habitats determine microbial community composition by
creating microhabitats and niche heterogeneity (Eriksson
et al. 2006, Singer et al. 2010). e low diversity and number
of unique OTUs in the epiphyton of S. emersum, the mac-
rophyte species with the least complex growth morphology,
illustrates the effect morphological complexity can have
on biofilm communities. Our study provides a glimpse at
the intimate ecological linkages between microbial diver-
sity and ecosystem ecology. Further advances in sequenc-
ing technology and libraries of microbial taxa will continue
to illuminate the myriad of connections across vast spatial
scales in ecology.
Acknowledgements – We are grateful to Anne Stentebjerg, Andrea
Torti, Xihan Chen, Anette Baisner Alnøe, Kamilla Maetzke and
Christoffer Bruus Pedersen for technical, laboratory, and field
assistance. We thank Dr. Nanci J. Ross for her statistical expertise.
We appreciate the comments and suggestions from Dr. Silke
Langenheder which improved the manuscript.
Funding – We thank the Carlsberg Foundation (no. 2013010258;
TR), Danish Research Council (FNU, no. 272-09-0012; TR), EU
MARS project (no. 603378; ABP), and the Danish National
Research Foundation (DNRF104) for financial support.
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... Spatial variation in periphyton structure has been detected in alpine rivers (Levi et al., 2017;Mansfeldt et al., 2020). Proteobacteria, cyanobacteria, and bacteroidetes have been frequently reported in streams with periphyton worldwide (Levi et al., 2017;Mansfeldt et al., 2020;Tamminen et al., 2022;Zeglin, 2015). ...
... Spatial variation in periphyton structure has been detected in alpine rivers (Levi et al., 2017;Mansfeldt et al., 2020). Proteobacteria, cyanobacteria, and bacteroidetes have been frequently reported in streams with periphyton worldwide (Levi et al., 2017;Mansfeldt et al., 2020;Tamminen et al., 2022;Zeglin, 2015). Proteobacteria, an important component of bacterial communities in river environments, plays a crucial role in nitrogen fixation and degradation of organic matter, especially α-proteobacteria and γ-proteobacteria accounting for a large proportion of Proteobacteria (Newton et al., 2011;Wang et al., 2023;Zhang et al., 2019). ...
... Regarding eukaryotes, the occurrence of bacillariophyta, chrysophyceae, and chlorophyta has been reported in sandstone streams, macrophyte-rich streams, and Lake Malawi (Artmann et al., 2003;Higgins et al., 2003;Levi et al., 2017). Chlorophyta is a potential biomarker for monitoring the water pollution (Brayner et al., 2011;Stewart et al., 2021). ...
Article
Periphyton in aquatic ecosystems play a crucial ecological role in element cycling and are susceptible to natural disturbances and anthropogenic activities. To understand the responses of periphytic communities to water quality factors and altitude gradients, DNA metabarcoding was employed to investigate the distribution characteristics of epilithic periphyton (comprising prokaryotes and eukaryotes). Epilithic periphyton and water were sampled at 26 sampling sites with an altitude ranging from 445 to 1,565 m in the Jue River and its three tributaries in Qinling Mountain, China. The altitudinal patterns of water quality variables were initially investigated, followed by redundancy analysis and distance‐based linear models to explore the responses of community structure to altitudes and water quality. Meanwhile, the relationship between these variables and fluorescence parameters to reflect the photosynthesis of epilithic periphyton along an altitudinal gradient was examined. The results indicated that with decreasing elevation, water quality variables including total dissolved solids (TDS), water temperature, conductivity, salinity, and concentrations of NO3−$$ {\mathrm{NO}}_3^{-} $$‐N, total nitrogen, and NO2−$$ {\mathrm{NO}}_2^{-} $$‐N increased. This pattern was closely associated with the intensification of anthropogenic disturbance downstream. Specifically, higher salinity and water temperature downstream may reduce the prokaryotic biodiversity but promote the diversity and evenness of eukaryotes; higher concentrations of total nitrogen may increase the diversity, richness, and evenness of the whole periphyton community. Furthermore, salinity, nutrients, and TDS were identified as crucial variables shaping periphyton community structure, especially salinity and TDS, which were linked to the growth of chlorophytes. The attenuated maximum photochemical efficiency of periphyton at high altitudes indicated that photosystem II was inhibited, while the enhancement of maximum photochemical efficiency at low altitudes may be attributed to the reduced abundance of synurophyceae and increased chlorophyte abundance with strong photosynthetic capacity. The spatial distribution of the structure and photosynthetic activity of the periphyton community along the altitudinal gradient of the Jue River and its tributaries showed that most water quality variables were negatively correlated with altitude. The photosynthetic efficiency of periphyton declined at high altitudes because the abundance of chlorophytes was lower at higher altitude reaches. This pattern of periphyton structural composition and function with altitude may also exist in other alpine rivers influenced by anthropogenic impacts.
... Epiphytic biofilm plays multiple roles in aquatic ecosystems ( Fig. 1) and is important for maintaining ecosystem structure, specifically community composition and diversity (Jones and Thornber, 2010) and functions, such as primary production and respiration (Allen, 1971;Alnoee et al., 2016;Cattaneo and Kalff, 1979;Sand-Jensen et al., 1989;Shamsudin and Sleigh, 1995;Squires et al., 2009;Vadeboncoeur and Steinman, 2002), trophic interactions (Brönmark, 1985;Jones and Sayer, 2003;Vadeboncoeur and Steinman, 2002), nutrient uptake and cycling (Levi et al., 2015(Levi et al., , 2017Sudo et al., 1978;Vadeboncoeur and Steinman, 2002), decomposition (Rybakova, 2010;Sudo et al., 1978), pollutant removal (Lindell et al., 2016;Phillips et al., 2010), and microbial gene pool preservation (Levi et al., 2017;Rusznyák et al., 2008). Macrophytes are 'ecosystem engineers' as they shape the physical properties of aquatic ecosystems; they alter hydraulics by resisting water flow, aid in sediment particle settlement, and influence light availability by shading and maintaining clear water status (Polvi and Sarneel, 2018). ...
... Epiphytic biofilm plays multiple roles in aquatic ecosystems ( Fig. 1) and is important for maintaining ecosystem structure, specifically community composition and diversity (Jones and Thornber, 2010) and functions, such as primary production and respiration (Allen, 1971;Alnoee et al., 2016;Cattaneo and Kalff, 1979;Sand-Jensen et al., 1989;Shamsudin and Sleigh, 1995;Squires et al., 2009;Vadeboncoeur and Steinman, 2002), trophic interactions (Brönmark, 1985;Jones and Sayer, 2003;Vadeboncoeur and Steinman, 2002), nutrient uptake and cycling (Levi et al., 2015(Levi et al., , 2017Sudo et al., 1978;Vadeboncoeur and Steinman, 2002), decomposition (Rybakova, 2010;Sudo et al., 1978), pollutant removal (Lindell et al., 2016;Phillips et al., 2010), and microbial gene pool preservation (Levi et al., 2017;Rusznyák et al., 2008). Macrophytes are 'ecosystem engineers' as they shape the physical properties of aquatic ecosystems; they alter hydraulics by resisting water flow, aid in sediment particle settlement, and influence light availability by shading and maintaining clear water status (Polvi and Sarneel, 2018). ...
... Epiphytic biofilms on live macrophytes are different and unique in both structure and function compared to the other periphytic biofilms in inert freshwater habitats (e.g., sand: epipsammon, stone/rock: epilithon, and sediment: epipelon) (Levi et al., 2017). Autotrophic communities in epiphytic biofilm are usually dominated by diatoms, green algae, cyanobacteria, and euglenoids (Costicȃ et al., 2018;Shamsudin and Sleigh, 1995;Xia et al., 2020), and dominant algal groups may differ with season and grazing pressure (Jones and Sayer, 2003;Roberts et al., 2003). ...
Article
Epiphytic biofilm is an important component in freshwater ecosystems and is one of the main primary producers in shallow freshwater ecosystems. The epiphytic biofilm is comprised of an autotrophic community made up of diatoms, green algae, and cyanobacteria, and a heterotrophic community consisting of bacteria, protozoa, fungi, and other microorganisms. Macrophytes are the host domain for epiphytic biofilm, providing substrate and influencing epiphytic biofilm via structural characteristics. Strong competitive, mutualistic, and commensalistic relationships between epiphytic biofilm and macrophytes have resulted from interactions for resources (e.g., light and nutrients) and trophic and allelopathic dynamics. Even though these interactions have wider implications on ecosystem structure, function, and integrity, the current understanding of epiphytic biofilm-macrophyte interactions is limited. In this review, we highlight the current understanding of epiphytic biofilms in freshwater ecosystems and synthesize their different interactions with macrophytes by providing illustrative examples. Furthermore, we identify key areas where research is currently lacking and provide directions for future research in this field, which will allow for better integrated aquatic ecosystem management and conservation strategies.
... Our current study allowed in addition to identify OTUs within these community shifts. The bacterial OTUs found at our study sites belong to groups previously reported in association with stream water and stream biofilms, including Actinobacteria, Proteobacteria, Bacteroidetes and Planctomycetes (Besemer et al., 2012;Levi et al., 2017;Mansfeldt et al., 2020;Zeglin, 2015). For instance, we found certain Burkholderia (belonging to Betaproteobacteria) which have the potential to degrade xenobiotics (O'Sullivan and Mahenthiralingam, 2005), and Rhizobiales (belonging to Alphaproteobacteria) which are known for The relative presence of the most common phylogenetic classes is presented as pie charts for each study location. ...
... We found a high abundance of Ciliophora (protozoans) and some fungi -particularly Cryptomycota and Bacillariophyceae, corresponding to previous reports of stream biofilms (Dopheide et al., 2008;Heino et al., 2010;Levi et al., 2017). Ciliophora (ciliates) are grazers in stream biofilms and highly important in transferring nutrients to higher trophic levels (Dopheide et al., 2009). ...
Article
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Microbial life in natural biofilms is dominated by prokaryotes and microscopic eukaryotes living in dense association. In stream ecosystems, microbial biofilms influence primary production, elemental cycles, food web interactions as well as water quality. Understanding how biofilm communities respond to anthropogenic impacts, such as wastewater treatment plant (WWTP) effluent, is important given the key role of biofilms in stream ecosystem function. Here, we implemented 16S and 18S rRNA gene sequencing of stream biofilms upstream (US) and downstream (DS) of WWTP effluents in four Swiss streams to test how bacterial and eukaryotic communities respond to wastewater constituents. Stream biofilm composition was strongly affected by geographic location – particularly for bacteria. However, the abundance of certain microbial community members was related to micropollutants in the wastewater – among bacteria, micropollutant-associated members were found e.g. in Alphaproteobacteria, and among eukaryotes e.g. in Bacillariophyta (algal diatoms). This study corroborates several previously characterized responses (e.g. as seen in diatoms), but also reveals previously unknown community responses – such as seen in Alphaproteobacteria. This study advances our understanding of the ecological impact of the current wastewater treatment practices and provides information about potential new marker organisms to assess ecological change in stream biofilms.
... k microbial was positively correlated with the number of plant species across all study streams, which suggests that the richness of macrophyte species plays a role for k microbial. This may indicate that higher macrophyte richness may support higher microbial diversity at reach scale, which was supported by Levi et al. (2017) who found higher microbial diversity on morphologically complex macrophyte species compared to simpler macrophyte species. Zak et al. (2003) also showed that increasing plant diversity increased the microbial biomass, microbial respiration, fungal abundance, and microbial-induced N mineralization rates in soil. ...
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Restoration has been increasingly applied over the last decades as a way to improve the ecological conditions in stream ecosystems, but documentation of the impact of restoration on ecosystem functions is sparse. Here, we applied a space-for-time approach to explore effects of stream restoration on metabolism and organic matter decomposition in lowland agricultural streams. We included stream reaches that were restored >10 years ago and compared ecosystem functioning in these streams with those in channelized and naturally meandering stream reaches from the same geographical region. Specifically, we tested the following hypotheses: 1) rates of stream metabolism (gross primary production, GPP, and ecosystem respiration, ER) and organic matter decomposition in restored reaches resemble rates in naturally meandering reaches more than rates in channelized stream reaches and 2) higher resemblance in ecosystem metabolism and organic matter decomposition between restored reaches and meandering reaches can be attributed to the improved physical habitat conditions in the restored stream reaches. Overall, we did not find that stream metabolism or organic matter decomposition differed among restored, channelized and naturally meandering stream reaches even though habitat conditions differed among the three stream types. Instead, we found a large variation in ecosystem function characteristics across all sites. When analyzing all stream types combined, we found that GPP increased with increasing plant coverage and that ER increased with increasing stream size and with the coverage of coarse substratum on the stream bottom. Organic matter decomposition, on the other hand, only slightly increased with the number of plant species and declined with increasing concentrations of nutrients. Overall, our findings suggest that physical habitat improvements in restored stream reaches can affect ecosystem functions, but also that the restoration outcome is context-dependent since many of the physical characteristics playing a role for the measured functions were only to some extent affected by the restoration and/or clouded by interference with factors operating at a larger-scale.
... This connection is based on the similarity of these two habitats and the finite physical distance. The relationship between the physicochemical characteristics of the habitats, the functional processes therein, and the microbial community are often closely interwoven [22]. In addition, the promoting effect of biological movements can also promote the communication of microbes between two habitats. ...
Article
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This study investigated ammonia-oxidizing bacterial communities in water and surface sediments of three tilapia ponds and their relationship with differences in the ponds, monthly variations in the water, and the physico-chemical parameters. Samples were collected from ponds with different stocking densities, after which DNA was extracted, 16S rRNA genes were amplified, the Illumina high-throughput sequencing was performed, and then the Silva and FunGene databases were used to investigate the ammonia-oxidizing bacterial communities. In total, 308,488 valid reads (144,931 in water and 163,517 in sediment) and 240 operational taxonomic units (207 in water and 225 in sediment) were obtained. Further analysis showed that the five genera of Nitrosospira, Nitrosococcus, Nitrosomonas, Proteobacteria_unclassified, and Nitrosomonadaceae_unclassified were distributed not only in the water, but also in surface sediments of all three ponds. Further, not only the abundance of these five genera, but also their diversities were affected by monthly variations in the water and by sediment differences among the ponds. Moreover, the total nitrogen (TN), nitrate, total phosphorus (TP), and sulphate were the main factors influencing the ammonia-oxidizing bacterial communities in the water, whereas TP was the main influencing factor in the sediments. Moreover, the parameter changes, especially those caused by differences in the ponds, were closely related to the cultivation management (stocking density and feed coefficients).
... In our study, macrophytes were predominantly submerged (Myriophyllum sp., Elodea nuttalli, and Stuckenia striata) and emergent (Ludwigia peploides, and Hydrocotyle ranunculoides) species, and only in one spot of one stream (D18), we measured CO 2 flux on a floating species (Lemna minima). As stated earlier, macrophytes may have strongly contributed to in-stream pCO 2 in the studied streams through their attached heterotrophic epiphytic biofilms, their shading effect on benthic algae, and the enhancement of benthic respiration via decomposing organic matter (Sand-Jlnsen et al. 1989;O'Brien et al. 2014;Levi et al. 2017). It is worth mentioning here that the contribution of macrophytes to CO 2 emissions may be even larger after their senescence, when large quantities of their organic tissues are decomposed within these streams. ...
Article
Carbon dioxide (CO2) emission from fluvial systems represents a substantial flux in the global carbon cycle. However, variation in fluvial CO2 fluxes at the air–water interface as well as its drivers are poorly understood, especially in non-forested headwaters. Here, we measured CO2 concentration and fluxes in 14 lowland open-canopy streams (Pampean region, Argentina) that cover a wide range of land use and water quality. We also analyzed drivers of CO2 concentration and fluxes, including factors related to metabolism, gas solubility, alkalinity, and gas transfer. Metabolic rates varied considerably among the study sites, but most streams (i.e., 8 out of the 11 where we were able to estimate ecosystem metabolism) were net heterotrophic. Metabolic differences among sites were mostly driven by the aromatic carbon content and the percent of the stream reach covered by primary producers. All streams, even those that were not net heterotrophic were CO2 supersaturated. Alkalinity combined with in-stream primary production explained 52.3% of the variance in the partial pressure of CO2 (pCO2), but our observations suggest that pCO2 might be controlled by external groundwater inputs of dissolved inorganic carbon rather than by internal metabolism. All streams were net emitters of CO2 to the atmosphere. Significantly more variance in CO2 flux was explained by gas transfer velocity (63.7%) than by pCO2 (21.9%). We also observed high spatial heterogeneity in CO2 fluxes within each stream, which was associated with flow variation and the presence of different macrophyte and algae patches. Overall, our results indicate that CO2 emission in these extremely low turbulence streams is controlled by a combination of external and internal biogeochemical processes and limited atmospheric exchange.
... For example, the sediment communities experienced a higher degree of resource heterogeneity within the sediment matrix than the epiphytic communities. Furthermore, the 3D matrix of the sediment habitat provided the epipelon with more surface area for biofilm growth than the surfaces of the macrophyte leaves (Levi et al., 2017). The generally lower eukaryotic diversity in the epiphyton relative to the surface sediments suggests that intense competition (e.g. ...
Article
Microbial communities in epiphytic biofilms and surface sediments play a vital role in the biogeochemical cycles of the major chemical elements in freshwater. However, little is known about the diversity, composition, and ecological functions of microbial communities in shallow tropical lakes dominated by aquatic macrophytes. In this study, epiphytic bacterial and eukaryotic biofilm communities on submerged and floating macrophytes and surface sediments were investigated in Lake Rumira, Rwanda in August and November 2019. High-throughput sequencing data revealed that members of the phyla, including Firmicutes, Proteobacteria, Cyanobacteria, Actinobacteria, Chloroflexi, Bacteriodetes, Verrumicrobia, and Myxomycota, dominated bacterial communities, while the microeukaryotic communities were dominated by Unclassified (uncl) SAR(Stramenopiles, Alveolata, Rhizaria), Rotifers, Ascomycota, Gastrotricha, Platyhelminthes, Chloroplastida, and Arthropoda. Interestingly, the eukaryotic OTUs (operational taxonomic units) number and Shannon indices were significantly higher in sediments and epiphytic biofilms on Eicchornia crassipes than Ceratophyllum demersum (p < 0.05), while no differences were observed in bacterial OTUs number and Shannon values among substrates. Redundancy analysis (RDA) showed that water temperature, pH, dissolved oxygen (DO), total nitrogen (TN), and electrical conductivity (EC) were the most important abiotic factors closely related to the microbial community on C. demersum and E. crassipes. Furthermore, co-occurrence networks analysis (|r| > 0.7, p < 0.05) and functional prediction revealed more complex interactions among microbes on C. demersum than on E. crassipes and sediments, and those interactions include cross-feeding, parasitism, symbiosis, and predatism among organisms in biofilms. These results suggested that substrate-type and environmental factors were the strong driving forces of microbial diversity in epiphytic biofilms and surface sediments, thus shedding new insights into microbial community diversity in epiphytic biofilms and surface sediments and its ecological role in tropical lacustrine ecosystems.
... Given that river restoration programs improve the habitat characteristics of previously degraded channels, which may, in turn, influence the diversity and composition of sediment microbial communities Levi et al., 2017), microorganisms can provide powerful insights into the progression of aquatic habitat restoration. Microbial community structure and functional diversity have been commonly used as indicators of lotic ecosystem health (Morris et al., 2020;Sackett et al., 2019;Staley et al., 2013). ...
Article
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• Comprehensive restoration programs are expected to influence sediment-associated microbial community structure and functional diversity following changes attributed to the restoration of habitat characteristics in the dam-impacted channel. • To address if the construction or recreation of in-channel structures, i.e., gravel bars, by implementing gravel augmentation and ecological flow restoration, resulted in habitat restoration and enhanced environmental heterogeneity, we profiled the community composition, estimated diversity, and annotated putative metabolic functions of the sediment microbial communities of the dam-regulated Trinity River in northern California. • Our results provided supporting evidence on the positive impact of habitat restoration conducted in the Trinity River with the non-dam influenced, undisturbed tributaries as the basis of comparison. In addition, gravel bar recreation and restoration contributed to the increased microbial beta diversity, possibly through the increased environmental heterogeneity at the river scale. • The significant positive correlation between the taxonomic and functional diversity of the identified microbial taxa suggests that differences in the detected putative metabolic functions were closely related to dissimilarities in community composition. We also provided valuable insights into the potential microbial processes in the sediment that might be contributing to the biogeochemical processes carried out by the microbial communities in the river. • The results of this study have implications on the impact of construction and restoration of gravel bars in a dam-impacted river on environmental heterogeneity and how this influences the taxonomic and functional diversities of sediment-associated microbial communities.
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To investigate the effect of submerged macrophytes on heterotrophic bacterioplankton communities in response to nutrient enrichment, we simulated mesocosms to test two factors, namely, the presence of Ceratophyllum demersum (L.) and the level of nutrients (slight and medium nutrient enrichment) under four possible system combinations for a duration of more than 3 months. The results show that C. demersum can affect the temporal dynamics of heterotrophic bacterioplankton density (HBD) and cause it to decrease. However, the effect of C. demersum on HBD was more pronounced under medium nutrient enrichment. The mean values of HBD in the treatment and control systems under slight nutrient enrichment were 1.30 × 105 cells mL−1 and 1.34 × 105 cells mL−1, respectively; whereas for medium nutrient enrichment, they were 1.78 × 105 cells mL−1 and 2.65 × 105 cells mL−1, respectively. The total nitrogen (TN) and total phosphorus (TP) concentrations were maintained throughout the experiment, and no significant differences were observed in the pH value, chlorophyll a (Chl. a) concentrations or dissolved organic carbon (DOC) levels between the systems with and without macrophytes, regardless of the nutrient level. Furthermore, linear mixed models revealed that environmental variables had a limited impact on HBD and that C. demersum had no significant direct effect on the environmental variables in the systems. A likely explanation is higher predation on bacterioplankton in the mesocosms, although allelopathic effects exerted by C. demersum cannot be excluded.
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Periphyton communities in freshwater systems play an essential role in biogeochemical processes, but knowledge of their structure and dynamics lags far behind other environments. We used eDNA metabarcoding of 16S and 18S rRNA markers to investigate the formation and establishment of a periphytic community, in addition to morphology-based analyses of its most abundant group (peritrich ciliates). We sampled two nearby sites within a large Neotropical lake at four time points, aiming to assess whether periphyton establishment can be replicated on this local scale. Producers and denitrifiers were abundant in the community, illustrating the relevant role of biofilms in freshwater nutrient recycling. Among microeukaryotes, peritrich ciliates dominated the community, with genera Epistylis and Vorticella being the most abundant and showing a clear succession at both sites. Other ciliates were identified and, in some cases, their occurrence was strongly related to bacterial abundance. The structure and succession dynamics of both prokaryotic and eukaryotic components of periphyton differed between the two sites, in spite of their adjacent locations and similar abiotic properties, indicating that the establishment of these communities can vary even on a local scale within a lake ecosystem.
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Macrophytes act as ecosystem engineers in lowland stream ecosystems, enhancing habitat complexity and physical structure. Studies have demonstrated that macrophyte abundance and growth form can dictate the degree to which physical and biological stream characteristics are altered. However, few studies have investigated the influence of macrophytes and their species-specific variation in morphological complexity on functional processes, such as nutrient uptake. We injected 15N-labeled ammonium (15N-NH4 +) into four macrophyte-rich lowland streams in Denmark to quantify the uptake of NH4 + by macrophytes, epiphytic biofilms, benthic biofilms, and suspended particulate organic matter in the water column. Overall, macrophytes and their epiphytic biofilms accounted for 71-98% of the reach-weighted uptake across the study streams. While macrophytes had the highest rates of NH4 + uptake among the compartments we measured, the epiphytic biofilms had the highest uptake efficiency, ranging from 0.06 to 0.6 mg N mg N biomass −1 d−1. Among all compartments, the uptake efficiency was inversely related to the carbon-to-nitrogen ratio. Macrophyte complexity, expressed as leaf perimeter-to-area ratio (P:A), varied among the five species found in the study streams. The uptake rates by macrophyte species with high leaf P:A were, on average, an order of magnitude higher than the rates for species with simple leaf morphology (430 vs. 49 mg N m−2 d−1). In summary, our results indicate that macrophytes regulate stream function both via direct uptake of NH4 + from the water column and by providing a substrate for epiphytic biofilms. Furthermore, the effect of leaf architecture on nutrient uptake rates provides evidence that physical complexity can enhance ecosystem function.
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The extent to which non-host-associated bacterial communities exhibit small-scale biogeographic patterns in their distribution remains unclear. Our investigation of biogeography in bacterial community composition and function compared samples collected across a smaller spatial scale than most previous studies conducted in freshwater. Using a grid-based sampling design, we abstracted 100+ samples located between 3.5 and 60 m apart within each of three alpine ponds. For every sample, variability in bacterial community composition was monitored using a DNA-fingerprinting methodology (automated ribosomal intergenic spacer analysis) whereas differences in bacterial community function (that is, carbon substrate utilisation patterns) were recorded from Biolog Ecoplates. The exact spatial position and dominant physicochemical conditions (for example, pH and temperature) were simultaneously recorded for each sample location. We assessed spatial differences in bacterial community composition and function within each pond and found that, on average, community composition or function differed significantly when comparing samples located >20 m apart within any pond. Variance partitioning revealed that purely spatial variation accounted for more of the observed variability in both bacterial community composition and function (range: 24-38% and 17-39%) than the combination of purely environmental variation and spatially structured environmental variation (range: 17-32% and 15-20%). Clear spatial patterns in bacterial community composition, but not function were observed within ponds. We therefore suggest that some of the observed variation in bacterial community composition is functionally 'redundant'. We confirm that distinct bacterial communities are present across unexpectedly small spatial scales suggesting that populations separated by distances of >20 m may be dispersal limited, even within the highly continuous environment of lentic water.
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Ecological theory argues that the controls over ecosystem processes are structured hierarchically, with broader-scale drivers acting as constraints over the interactions and dynamics at nested levels of organization. In river ecosystems, these interactions may arise from broadscale variation in channel form that directly shapes benthic habitat structure and indirectly constrains resource supply and biological activity within individual reaches. To evaluate these interactions, we identified sediment characteristics, water chemistry, and denitrifier community structure as factors influencing benthic denitrification rates in a sixth-order river that flows through two physiographic provinces and the transitional zone between them, each with distinct geomorphological properties. We found that denitrification rates tracked spatial changes in sediment characteristics and varied seasonally with expected trends in stream primary production. Highest rates were observed during the spring and summer seasons in the physiographic province dominated by fine-grained sediments, illustrating how large-scale changes in river structure can constrain the location of denitrification hotspots. In addition, nirS and nirK community structure each responded differently to variation in channel form, possibly due to changes in dissolved oxygen and organic matter supply. This shift in denitrifier community structure coincident with higher rates of N removal via denitrification suggests that microbial community structure may influence biogeochemical processes.
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Periphyton and macrophytes alter water velocity in streams, influencing movement of solutes and providing microhabitat for other organisms. How assemblages with different growth form and architecture influence water velocity attenuation across mm to dm scales is not well de- scribed. A thermistor microprobe was used to measure water velocity through 4 morphologically distinct stream periphyton assemblages and 4 distinct stream macrophyte assemblages in flumes. All assemblages resulted in an exponential decay in velocity with depth. A dense assemblage of diatoms (primarily Cymbella) attenuated velocity more than filamentous green algae, filamentous green algae with interspersed diatoms, or a red alga (ANOVA, p < 0.05).External water velocity had no significant influence on the coefficient of attenuation in a filamentous green alga (ANOVA, p = 0.76). Macro- phytes also attenuated water velocity, but attenuation was more variable and, in all cases, attenuation coefficients were less for macrophytes than for peripl~yton. A model unifying attenuation by periph- yton and macrophytes was developed using biomass density (g ash-free dry mass/m" as the inde- pendent variable and it explained 80% of the variation in attenuation. The relative variance of atten- uation coefficients increased sharply as Reynolds number increased above -500 to 700, suggesting that variance in water velocity was dependent upon the spatial scale of the primary producer through which water is flowing, and that the distinction between periphyton and macrophytes may have real physical ramifications. Key zwrds: algae, current, flow, l~ydrodynamics, micropl~ytobenthos, primary producers, sub- merged plants.
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Nitrogen uptake and cycling was examined using a six-week tracer addition of N-15-labeled ammonium in early spring in Walker Branch, a first-order deciduous forest stream in eastern Tennessee. Prior to the N-15 addition, standing stocks of N were determined for the major biomass compartments. During and after the addition, 15N was measured in water and in dominant biomass compartments upstream and at several locations downstream. Residence time of ammonium in stream water (5-6 min) and ammonium uptake lengths (23-27 m) were short and relatively constant during the addition. Uptake rates of NH4 were more variable, ranging from 22 to 37 mu g N.m(-2).min(-1) and varying directly with changes in streamwater ammonium concentration (2.7-6.7 mu g/L). The highest rates of ammonium uptake per unit area were by the liverwort Porella pinnata, decomposing leaves, and fine benthic organic matter (FBOM), although epilithon had the highest N uptake per unit biomass N. Nitrification rates and nitrate uptake lengths and rates were determined by fitting a nitrification/nitrate uptake model to the longitudinal profiles of N-15-NO3 flux. Nitrification was an important sink for ammonium in stream water, accounting for 19% of the total ammonium uptake rate. Nitrate production via coupled regeneration/nitrification of organic N was about one-half as large as nitrification of streamwater ammonium. Nitrate uptake lengths were longer and more variable than those for ammonium, ranging from 101 m to infinity. Nitrate uptake rate varied from 0 to 29 mu g.m(-2).min(-1) and was similar to 1.6 times greater than assimilatory ammonium uptake rate early in the tracer addition. A sixfold decline in instream gross primary production rate resulting from a sharp decline in light level with leaf emergence had little effect on ammonium uptake rate but reduced nitrate uptake rate by nearly 70%. At the end of the addition, 64-79% of added N-15 was accounted for, either in biomass within the 125-m stream reach (33-48%) or as export of N-15-NH4 (4%), N-15-NO3 (23%), and fine particulate organic matter (4%) from the reach, Much of the N-15 not accounted for was probably lost downstream as transport of particulate organic N during a storm midway through the experiment or as dissolved organic N produced within the reach. Turnover rates of a large portion of the N-15 taken up by biomass compartments were high (0.04-0.08 per day), although a substantial portion of the N-15 in Porella (34%), FBOM (21%), and decomposing wood (17%) at the end of the addition was retained 75 d later, indicating relatively long-term retention of some N taken up from water. In total, our results showed that ammonium retention and nitrification rates were high in Walker Branch, and that the downstream loss of N was primarily as nitrate and was controlled largely by nitrification, assimilatory demand for N, and availability of ammonium to meet that demand. Our results are consistent with recent N-15 tracer experiments in N-deficient forest soils that showed high rates of nitrification and the importance of nitrate uptake in regulating losses of N. Together these studies demonstrate the importance of N-15 tracer experiments for improving our understanding of the complex processes controlling N cycling and loss in ecosystems.
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