FEMS Microbiology Ecology Advance Access published June 1, 2015
1 1
Abiotic autumnal organic matter deposition and grazing disturbance effects on epilithic
2
biofilm succession.
3
Running Title: Leaf deposition and grazing effects on biofilm succession
4 5 Jennifer M. Lang2, Ryan W. McEwan2, and M. Eric Benbow1
6 7 2
8
Department of Biology, University of Dayton, Dayton, OH, 45469-2320
9 10 11 12
Keywords: 454 pyrosequencing/ARISA/leaf deposition/periphyton/priming effect/invertebrate
13
grazing
14 15 16 17
1
M. Eric Benbow Department of Entomology and Department of Osteopathic Medical Specialties Michigan State University 243 Natural Science Bldg. 288 Farm Lane East Lansing, MI 48824 517-410-9247 (Cell) 517-432-4577 (office) 517-355-6514 (lab) 517-432-7061 (fax) [email protected] (email)
2 18
ABSTRACT:
19
Stream epilithic biofilm community assembly is influenced in part by environmental factors.
20
Autumn leaf deposition is an annual resource subsidy to streams, but the physical effects of
21
leaves settling on epilithic biofilms has not been investigated. We hypothesized that bacterial and
22
micro-eukaryotic community assembly would follow a successional sequence that was mediated
23
by abiotic effects that were simulating leaf deposition (reduced light and flow) and by biotic
24
(snail grazing) disturbance. This hypothesis was tested using an in situ experimental
25
manipulation. Ambient biofilms had greater algal biomass and distinct ARISA community
26
profiles compared to biofilms developed under manipulated conditions. There were no
27
significant differences in biofilm characteristics associated with grazing, suggesting that results
28
were driven by reduced light/flow rather than invertebrate disturbance; however, grazing
29
appeared to increase bacterial taxon richness. Interestingly at day 38, all treatments grouped
30
together in ordination space and had similar algal/total biomass ratios. We suggest algal priming
31
promoted a shift in ambient biofilms but that this effect is dependent upon successional timing of
32
algal establishment. These data demonstrate that abiotic effects were more influential than local
33
grazing disturbance and imply that leaf litter deposition may have bottom-up effects on the
34
stream ecosystem through altered epilithic biofilms.
35 36 37 38 39 40
3 41
INTRODUCTION
42
Stream epilithic biofilms form on inorganic substrates and are matrix-enclosed microbial
43
communities comprised of bacterial, algal, fungal, and protozoan organisms. The abundance and
44
diversity of these organisms is dictated by environmental factors including light (Steinman et al.,
45
1991; Roeselers et al., 2007), flow (Arnon et al., 2007; Besemer et al., 2007; Besemer et al.,
46
2009a), nutrients (Olapade & Leff, 2005; Ardón & Pringle, 2007; Passy, 2008), and invertebrate
47
grazing (Tuchman & Stevenson, 1991; Lawrence et al., 2002), which can all interact to drive
48
biofilm community assembly (Rosemond et al., 1993; Wellnitz & Rader, 2003; Lange et al.,
49
2011). Understanding how these factors influence biofilms has been facilitated by treating
50
biofilms as micro-ecosystems that follow ecological principles (Battin et al., 2007; Fierer et al.,
51
2010).
52
Biofilm development is a result of dynamic community interactions and is commonly
53
described using successional patterns. Separately, algae (DeNicola & McIntire, 1990; Wellnitz &
54
Rader, 2003; Sekar et al., 2004) and bacteria (Jackson et al., 2001; Besemer et al., 2007) exhibit
55
independent successional sequences, but the algal-bacterial relationship can influence these
56
patterns of community assembly. Indeed, algae have been proposed as “ecosystem engineers”
57
that exert a biophysical control on bacteria because bacterial community composition under
58
different flow regimes became more similar once filamentous algae was established (Besemer et
59
al., 2007). Algae may also influence community composition through a priming effect, where
60
labile algae byproducts facilitate heterotrophic organisms to use complex organic matter;
61
however, this has only been studied in epixylic biofilms (Kuehn et al., 2014; Rier et al., 2014)
62
and has yet to be applied to interactions within epilithic biofilms. In general during epilithic
63
biofilm succession, bacteria dominate the pioneer community (Stock & Ward, 1989; Pohlon et
4 64
al., 2010) and are the base layer that promotes algal attachment (Hodoki, 2005; Roeselers et al.,
65
2007). Protozoans are present to feed on biofilm organisms, and their densities correlate with
66
diatom density (Kanavillil & Kurissery, 2013) and biofilm biomass (Romaní et al., 2014). These
67
micro-eukaryotic organisms include ciliates, flagellates, and amoeba and can have different
68
feeding mechanisms like raptorial or direct interception that affects biofilm morphology and
69
spatial arrangement (Böhme et al., 2009; Dopheide et al., 2011). Protozoan grazing can also
70
influence biofilm community composition (Corno & Jürgens, 2008; Wey et al., 2008), but
71
environmental and seasonal differences have been shown to be more influential on composition
72
than micro-eukaryotic grazing (Wey et al., 2012).
73
Physical disturbances and invertebrate grazing can alter stream biofilm successional
74
trajectories. Specific grazing effects are dependent upon the type and density of the grazer
75
species, but in general, they reduce biofilm biomass and alter community composition and
76
spatial heterogeneity (Feminella & Hawkins, 1995; Hillebrand, 2008). If grazing occurs at
77
intermediate levels, biofilm diversity is expected to increase because the biofilm would contain
78
patches of various successional stages as described by the successional mosaic hypothesis
79
(Chesson & Huntly, 1997) and intermediate disturbance hypothesis (Connel, 1978; Resh et al.,
80
1988). The prediction is that intermittent grazing would allow organisms at early, late, and
81
intermediary stages to be present at the same time; therefore, the diversity would be greater when
82
compared to biofilms without grazing disturbance where the entire “landscape” is at the same
83
successional stage.
84
Autumn leaf deposition is a naturally occurring seasonal pulse event that transfers
85
nutrients into the aquatic habitat and also physically changes environmental conditions because
86
leaves will reduce light and flow when they settle on the benthos. Light availability (Steinman et
5 87
al., 1990; Hill & Dimick, 2002; Lange et al., 2011) and flow velocity (Biggs & Thomsen, 1995;
88
Battin et al., 2003a; Arnon et al., 2007) are important in shaping biofilm community structure
89
and function; algae use light during photosynthesis while flow directly influences physical
90
architecture (Battin et al., 2003a; Hödl et al., 2014) and therefore community composition
91
(Besemer et al., 2009b). Limiting flow also decreases the frequency and duration of flow
92
scouring events at the biofilm scale (Biggs & Thomsen, 1995; Hart et al., 2013) and indirectly
93
affects nutrient availability by altering nutrient diffusion and uptake rates (Horner et al., 1990;
94
Larned et al., 2004). This suggests that leaf deposition has the potential to affect stream biofilms
95
in a way that is unrelated to the nutrients provided by the leaves. Leaf deposition is typically
96
studied within the context of decomposition, organic matter budgets, and ecosystem metabolism
97
(Tank et al., 2010), where the leaves are considered energy inputs and substrates for epixylic
98
biofilms and invertebrates (Tank et al., 2010). Nevertheless, an unaccounted for effect of leaf
99
deposition on stream ecosystem processes could result from reduced light and flow altering the
100
structure and function of epilithic biofilms. These biofilms within stream ecosystems are the
101
predominant source of primary production, integral in nutrient processing, part of the food web,
102
and drive ecosystem processes (Battin et al., 2003b). Therefore, leaf deposition has the potential
103
for bottom-up effects on the stream ecosystem by altering epilithic biofilms, but this idea has not
104
been well studied.
105
We used an in situ manipulation experiment to assess the physical, abiotic effects of leaf
106
deposition (reduced light and flow) and biotic disturbance (invertebrate grazing) governing
107
succession and biomass development of epilithic biofilms developing during autumn leaf
108
deposition. Biofilms were grown on unglazed ceramic tiles under three conditions: ambient
109
(control – no mesh), inclusion (reduced light/flow from mesh with grazer snails included), and
6 110
exclusion (reduced light/flow from mesh without snail grazing). Bacterial and eukaryotic
111
community profiles were described using automatic ribosomal intergenic spacer analysis
112
(ARISA) to elucidate patterns of community composition. Next generation 454-pyrosequencing
113
was used to further describe the taxonomic diversity of the bacterial communities. We
114
hypothesized that (H1) treatment effects would be more significant than time in driving
115
community assembly because communities are expected to change over time while treatments
116
would mediate the species pool regardless of time. We also expected (H2) community differences
117
between treatments to be more pronounced later during succession when algal biomass peaks
118
and the effect of reduced light conditions is maximized. In addition, the (H3) effect of abiotic
119
factors was predicted to be more influential than invertebrate grazing disturbances because
120
grazing is a small-scale “local” disturbance compared to the constant and permanent influence of
121
reduced light and flow. Grazing was hypothesized (H4) to drive an increase in bacterial taxon
122
richness along with disrupting biofilm community succession in a way that would result in
123
unchanged community composition over time. This disrupted succession is a result of applying
124
the successional mosaic hypothesis over time where the overall bacterial communities would
125
appear unchanged because grazers would be continuously creating new micro-patches. These
126
continuously created patches would generate a mosaic of various stages of succession in the
127
biofilm landscape, hence, the entire biofilm would not proceed through succession as a unit and
128
the net community composition would remain unchanged.
129 130
METHODS
131
Site description
7 132
The study was conducted in a lower third order section of the upper region of the Little
133
Miami River in a small deciduous forest corridor of the Little Miami State Forest Preserve in
134
Xenia, Ohio, USA (39°76.552 83°90.062). The surrounding landcover of the catchment area was
135
predominately agriculture, and the riparian forest was dominated by maple (Acer sp.) and elm
136
(Ulmus sp.), but included hackberry (Celtis sp.), sycamore (Plantanus sp.), and walnut (Juglans
137
sp.). The stream has been categorized as an Exceptional Warmwater Habitat by the Ohio
138
Environmental Protection Agency because it supported high diversity of aquatic organisms
139
(OEPA, 2002). The study was conducted in a 35 x 20 m run habitat where the substrate was
140
predominately gravel and cobble with several intermittent boulders.
141 142 143
Water quality and flow The following water quality variables were recorded at the start of the study and on every
144
sampling date: temperature (ºC), specific conductivity (SpCond μS/cm), total dissolved solids
145
(TDS mg/L), pH, turbidity (NTU), and dissolved oxygen (DO mg/L). Measurements were
146
recorded every 30 sec for 10 min at upper, middle, and lower points along the reach using a YSI
147
6600 v2 Sonde (YSI Inc, Yellow Springs, OH, USA). In addition, water depth (cm) and flow
148
velocity (cm/s2) (FlowTracker® Handheld-ADV®; SonTek/Xylem, San Diego, CA, USA) were
149
measured at each experimental board (see below).
150 151 152
Experimental design Epilithic biofilms were allowed to naturally develop on two unglazed ceramic tiles (4.8 x
153
4.8 x 0.5 cm) attached to brick pavers (19.2 x 9 x 1.3 cm) with 100% silicone under three
154
conditions: ambient (control – no mesh), inclusion (reduced light/flow from mesh netting with
8 155
grazer snails included), exclusion (reduced light/flow from mesh netting without snail grazing).
156
The ambient condition was subjected to natural light and flow conditions and served as the
157
control. These biofilms represent natural biofilms found on rocks that are prominent in the water
158
column where leaf packs would not form. Abiotic effects simulating leaf deposition were created
159
with 500 μm nylon mesh netting (BioQuip Products, CA, USA) that was folded into an enclosure
160
(20 x 10 x 10 cm) and secured by hot glue. The mesh enclosure was attached to the paver with
161
100% silicone and the resulting effect was reduced light and flow conditions and excluded
162
grazers. Goniobasis (Elimia) sp. snails (1.5 cm; N = 2) at natural densities were added to the
163
inclusion treatment enclosures through a slit that was sewn closed with fishing line. Natural snail
164
density was determined on 1 October 2010 by quantifying the number of snails within nine, 50
165
cm2 areas of benthic substrate throughout the study reach. Using VELCRO® tape, the pavers of
166
each treatment were randomly distributed on wood boards (1 x 0.3 x 0.025 m) that were
167
anchored to the streambed approximately 3.6 m apart along the thalweg (deepest section of the
168
stream) to ensure as similar flow conditions as possible. Pavers were randomly sampled (N = 3
169
per treatment) at 14, 24, and 38 days of growth. Tiles were removed, transported in the dark on
170
ice to the lab, and stored at 4°C until processing within 24 h.
171
The study was conducted from 15 October 2010 to 22 November 2010 and encompassed
172
autumnal leaf deposition (Figure 1). Leaf packs that formed against the boards and biofilm
173
material that developed on enclosure structures were gently removed every four days (Figure 1)
174
to prevent the organic matter buildup from interfering with results by creating stagnant and
175
anoxic conditions inside the enclosures. This did not remove the visually obvious biofilm
176
material inside the enclosures so we feel the setup was still able to reflect physical effects of
177
leaves while still ensuring grazer manipulation. Also, leaves were rarely found on ambient
9 178
biofilms because there was not a protrusion for leaves to settle against and the slight elevation of
179
the boards in the water column subjected them to flow that was not conducive for leaf
180
deposition.
181 182
Biofilm biomass
183
Biofilm biomass from one tile per paver was removed using a sterile razor blade and
184
toothbrush and suspended in ultrapure water (NANOpure II; Barnstead, Boston, MA, USA).
185
Two sub samples for total biomass as ash free dry mass (AFDM) and algal-associated biomass as
186
chlorophyll a were collected on GB-140 glass membrane filters (diameter, 25 mm; pore size, 0.4
187
μm; Sterlitech, Kent, WA, USA) following techniques used by Steinman et al., (2007).
188
Chlorophyll a filters were stored at -20°C until extraction within three months and were used to
189
determine algal biomass by multiplying the chlorophyll a value by the biomass factor of 67
190
(APHA, 1999). Biofilm from the second tile was removed and stored in 90% ethanol at -20°C
191
until DNA extraction in autumn 2013 to determine community profiles.
192 193
DNA extraction
194
DNA was extracted from 0.1 - 0.3 g of ethanol evaporated, dried biofilm using a
195
combination of methods from Miller et al., (1999) and Zhou et al., (1996) as suggested by Lear
196
et al., (2010). Samples were lysed by bead beating (0.5 g each of 0.1 mm and 0.5 mm glass lysis
197
beads; RPI, Mount Prospect, IL, USA) for 15 min on a horizontal vortex adaptor (MO BIO
198
Laboratories, Carlsbad, CA, USA) at full speed in 1.2 mL of extraction buffer (100 mM Tris-
199
HCl [pH 8.0], 100 mM EDTA disodium salt [pH 8.0], 100mM Sodium phosphate [pH 8.0], 1.5
200
M Sodium chloride, 1% CTAB), 12 μL proteinase K (20 mg/mL), and 30 μL SDS (20%). The
10 201
mixture was incubated at 65°C for 1 hr with gentle end-over-end inversions by hand every 15
202
min. Then, 4 μL of RNase (100 mg/μL) was added. DNA was isolated from organic debris with
203
chloroform/isoamyl alcohol extraction and was precipitated overnight at -20°C with isopropanol.
204
The mixture was warmed to 37°C to dissolve salt precipitates, and DNA was pelleted at 15,000 g
205
for 30 min. The DNA pellet was washed twice with ice cold 70% EtOH and dissolved in 25-50
206
μL ultrapure water (NANOpure II; Barnstead, Boston, MA, USA). Samples were purified using
207
PowerClean® DNA Clean-Up Kit (MO BIO Laboratories, Carlsbad, CA, USA) with a modified
208
protocol for low amounts of DNA to remove PCR inhibitors typical of biofilm samples.
209 210 211
ARISA Bacterial and eukaryotic communities were assessed using profiles created by automated
212
ribosomal intergenic spacer analysis (ARISA) (Fisher & Triplett, 1999), which generates a
213
unique ‘fingerprint’ of microbial communities using the 16S-23S intergenic space in bacteria and
214
the ITS1-5.8S-ITS2 region in eukaryotes (Ranjard et al., 2001). While ARISA does not
215
taxonomically identify organisms like next generation sequencing methods, this method
216
generates community profiles and produces similar patterns in results (Bienhold et al., 2012; van
217
Dorst et al., 2014). Approximately 15-20 ng of DNA quantified by spectrophotometer
218
(NanoPhotometerTM Pearl; Denville Scientific Inc., South Plainfield, NJ, USA) was amplified
219
by PCR using 25 μL GoTaq® Colorless Master Mix (Promega, Madison, WI, USA) with 0.5 μM
220
of forward and reverse primers. Bacteria ribosomal intergenic space regions were amplified with
221
primers ITSF (5’-GTCGTAACAAGGTAGCCGTA-3’) labeled with FAM at the 5’ end (IDT,
222
Coralville, IA, USA) and ITSReub (5’-GCCAAGGCATCCACC-3’) (Cardinale et al., 2004).
223
Eukaryote ribosomal intergenic space regions were amplified with primers 2234C (5’-
11 224
GTTTCCGTAGGTGAACCTGC-3’) labeled with ATTOTM 550 (IDT, Coralville, IA, USA) and
225
3126T (5’- ATATGCTTAAGTTCAGCGGGT-3’) (Ranjard et al., 2001). While the eukaryotic
226
primer set has typically been used for soil fungal communities (Ranjard et al., 2001), sequenced
227
clones of fragments from freshwater biofilms revealed it targets various algae and ciliates, and
228
therefore can be used to describe the general eukaryotic community (Fechner et al., 2010).
229
Fragments were created with the following PCR conditions: (i) 94°C for 3 min, (ii) 35 cycles of
230
94°C for 1 min, 56°C (57.5°C for eukaryotes) for 1 min, 72°C for 2 min, and finally (iii) 72°C
231
for 10 min (Fechner et al., 2010). Equal volumes of bacterial and eukaryotic PCR products from
232
a sample were combined and sent to DNA Analysis, LLC (Cincinnati, OH, USA) for
233
multiplexed fragment analysis on an ABI 3100 (Life Technologies, Carlsbad, CA, USA).
234
Fragments were interpreted using Genescan v 3.7 using the Local Southern Size Calling Method
235
with a peak height threshold of 100 fluorescence units to remove background fluorescence and
236
formulated using GeneMapper v 2.5 (Life Technologies, Carlsbad, CA, USA).
237
Fragment peak length and area was converted to column format using the treeflap Excel
238
Macro (http://www.wsc.monash.edu.au/~cwalsh/treeflap.xls) and processed with the
239
automatic_binner script to determine binning window size and the interactive_binner script to
240
determine the best starting window position (Ramette, 2009) in R v 3.1.0 (R Core Team 2014).
241
This method was used to account for inherent imprecision of analyzer machines. Peak area was
242
converted to relative abundance of each fragment as part of the entire sample, fragments with
243
1 1
Abiotic autumnal organic matter deposition and grazing disturbance effects on epilithic
2
biofilm succession.
3
Running Title: Leaf deposition and grazing effects on biofilm succession
4 5 Jennifer M. Lang2, Ryan W. McEwan2, and M. Eric Benbow1
6 7 2
8
Department of Biology, University of Dayton, Dayton, OH, 45469-2320
9 10 11 12
Keywords: 454 pyrosequencing/ARISA/leaf deposition/periphyton/priming effect/invertebrate
13
grazing
14 15 16 17
1
M. Eric Benbow Department of Entomology and Department of Osteopathic Medical Specialties Michigan State University 243 Natural Science Bldg. 288 Farm Lane East Lansing, MI 48824 517-410-9247 (Cell) 517-432-4577 (office) 517-355-6514 (lab) 517-432-7061 (fax) [email protected] (email)
2 18
ABSTRACT:
19
Stream epilithic biofilm community assembly is influenced in part by environmental factors.
20
Autumn leaf deposition is an annual resource subsidy to streams, but the physical effects of
21
leaves settling on epilithic biofilms has not been investigated. We hypothesized that bacterial and
22
micro-eukaryotic community assembly would follow a successional sequence that was mediated
23
by abiotic effects that were simulating leaf deposition (reduced light and flow) and by biotic
24
(snail grazing) disturbance. This hypothesis was tested using an in situ experimental
25
manipulation. Ambient biofilms had greater algal biomass and distinct ARISA community
26
profiles compared to biofilms developed under manipulated conditions. There were no
27
significant differences in biofilm characteristics associated with grazing, suggesting that results
28
were driven by reduced light/flow rather than invertebrate disturbance; however, grazing
29
appeared to increase bacterial taxon richness. Interestingly at day 38, all treatments grouped
30
together in ordination space and had similar algal/total biomass ratios. We suggest algal priming
31
promoted a shift in ambient biofilms but that this effect is dependent upon successional timing of
32
algal establishment. These data demonstrate that abiotic effects were more influential than local
33
grazing disturbance and imply that leaf litter deposition may have bottom-up effects on the
34
stream ecosystem through altered epilithic biofilms.
35 36 37 38 39 40
3 41
INTRODUCTION
42
Stream epilithic biofilms form on inorganic substrates and are matrix-enclosed microbial
43
communities comprised of bacterial, algal, fungal, and protozoan organisms. The abundance and
44
diversity of these organisms is dictated by environmental factors including light (Steinman et al.,
45
1991; Roeselers et al., 2007), flow (Arnon et al., 2007; Besemer et al., 2007; Besemer et al.,
46
2009a), nutrients (Olapade & Leff, 2005; Ardón & Pringle, 2007; Passy, 2008), and invertebrate
47
grazing (Tuchman & Stevenson, 1991; Lawrence et al., 2002), which can all interact to drive
48
biofilm community assembly (Rosemond et al., 1993; Wellnitz & Rader, 2003; Lange et al.,
49
2011). Understanding how these factors influence biofilms has been facilitated by treating
50
biofilms as micro-ecosystems that follow ecological principles (Battin et al., 2007; Fierer et al.,
51
2010).
52
Biofilm development is a result of dynamic community interactions and is commonly
53
described using successional patterns. Separately, algae (DeNicola & McIntire, 1990; Wellnitz &
54
Rader, 2003; Sekar et al., 2004) and bacteria (Jackson et al., 2001; Besemer et al., 2007) exhibit
55
independent successional sequences, but the algal-bacterial relationship can influence these
56
patterns of community assembly. Indeed, algae have been proposed as “ecosystem engineers”
57
that exert a biophysical control on bacteria because bacterial community composition under
58
different flow regimes became more similar once filamentous algae was established (Besemer et
59
al., 2007). Algae may also influence community composition through a priming effect, where
60
labile algae byproducts facilitate heterotrophic organisms to use complex organic matter;
61
however, this has only been studied in epixylic biofilms (Kuehn et al., 2014; Rier et al., 2014)
62
and has yet to be applied to interactions within epilithic biofilms. In general during epilithic
63
biofilm succession, bacteria dominate the pioneer community (Stock & Ward, 1989; Pohlon et
4 64
al., 2010) and are the base layer that promotes algal attachment (Hodoki, 2005; Roeselers et al.,
65
2007). Protozoans are present to feed on biofilm organisms, and their densities correlate with
66
diatom density (Kanavillil & Kurissery, 2013) and biofilm biomass (Romaní et al., 2014). These
67
micro-eukaryotic organisms include ciliates, flagellates, and amoeba and can have different
68
feeding mechanisms like raptorial or direct interception that affects biofilm morphology and
69
spatial arrangement (Böhme et al., 2009; Dopheide et al., 2011). Protozoan grazing can also
70
influence biofilm community composition (Corno & Jürgens, 2008; Wey et al., 2008), but
71
environmental and seasonal differences have been shown to be more influential on composition
72
than micro-eukaryotic grazing (Wey et al., 2012).
73
Physical disturbances and invertebrate grazing can alter stream biofilm successional
74
trajectories. Specific grazing effects are dependent upon the type and density of the grazer
75
species, but in general, they reduce biofilm biomass and alter community composition and
76
spatial heterogeneity (Feminella & Hawkins, 1995; Hillebrand, 2008). If grazing occurs at
77
intermediate levels, biofilm diversity is expected to increase because the biofilm would contain
78
patches of various successional stages as described by the successional mosaic hypothesis
79
(Chesson & Huntly, 1997) and intermediate disturbance hypothesis (Connel, 1978; Resh et al.,
80
1988). The prediction is that intermittent grazing would allow organisms at early, late, and
81
intermediary stages to be present at the same time; therefore, the diversity would be greater when
82
compared to biofilms without grazing disturbance where the entire “landscape” is at the same
83
successional stage.
84
Autumn leaf deposition is a naturally occurring seasonal pulse event that transfers
85
nutrients into the aquatic habitat and also physically changes environmental conditions because
86
leaves will reduce light and flow when they settle on the benthos. Light availability (Steinman et
5 87
al., 1990; Hill & Dimick, 2002; Lange et al., 2011) and flow velocity (Biggs & Thomsen, 1995;
88
Battin et al., 2003a; Arnon et al., 2007) are important in shaping biofilm community structure
89
and function; algae use light during photosynthesis while flow directly influences physical
90
architecture (Battin et al., 2003a; Hödl et al., 2014) and therefore community composition
91
(Besemer et al., 2009b). Limiting flow also decreases the frequency and duration of flow
92
scouring events at the biofilm scale (Biggs & Thomsen, 1995; Hart et al., 2013) and indirectly
93
affects nutrient availability by altering nutrient diffusion and uptake rates (Horner et al., 1990;
94
Larned et al., 2004). This suggests that leaf deposition has the potential to affect stream biofilms
95
in a way that is unrelated to the nutrients provided by the leaves. Leaf deposition is typically
96
studied within the context of decomposition, organic matter budgets, and ecosystem metabolism
97
(Tank et al., 2010), where the leaves are considered energy inputs and substrates for epixylic
98
biofilms and invertebrates (Tank et al., 2010). Nevertheless, an unaccounted for effect of leaf
99
deposition on stream ecosystem processes could result from reduced light and flow altering the
100
structure and function of epilithic biofilms. These biofilms within stream ecosystems are the
101
predominant source of primary production, integral in nutrient processing, part of the food web,
102
and drive ecosystem processes (Battin et al., 2003b). Therefore, leaf deposition has the potential
103
for bottom-up effects on the stream ecosystem by altering epilithic biofilms, but this idea has not
104
been well studied.
105
We used an in situ manipulation experiment to assess the physical, abiotic effects of leaf
106
deposition (reduced light and flow) and biotic disturbance (invertebrate grazing) governing
107
succession and biomass development of epilithic biofilms developing during autumn leaf
108
deposition. Biofilms were grown on unglazed ceramic tiles under three conditions: ambient
109
(control – no mesh), inclusion (reduced light/flow from mesh with grazer snails included), and
6 110
exclusion (reduced light/flow from mesh without snail grazing). Bacterial and eukaryotic
111
community profiles were described using automatic ribosomal intergenic spacer analysis
112
(ARISA) to elucidate patterns of community composition. Next generation 454-pyrosequencing
113
was used to further describe the taxonomic diversity of the bacterial communities. We
114
hypothesized that (H1) treatment effects would be more significant than time in driving
115
community assembly because communities are expected to change over time while treatments
116
would mediate the species pool regardless of time. We also expected (H2) community differences
117
between treatments to be more pronounced later during succession when algal biomass peaks
118
and the effect of reduced light conditions is maximized. In addition, the (H3) effect of abiotic
119
factors was predicted to be more influential than invertebrate grazing disturbances because
120
grazing is a small-scale “local” disturbance compared to the constant and permanent influence of
121
reduced light and flow. Grazing was hypothesized (H4) to drive an increase in bacterial taxon
122
richness along with disrupting biofilm community succession in a way that would result in
123
unchanged community composition over time. This disrupted succession is a result of applying
124
the successional mosaic hypothesis over time where the overall bacterial communities would
125
appear unchanged because grazers would be continuously creating new micro-patches. These
126
continuously created patches would generate a mosaic of various stages of succession in the
127
biofilm landscape, hence, the entire biofilm would not proceed through succession as a unit and
128
the net community composition would remain unchanged.
129 130
METHODS
131
Site description
7 132
The study was conducted in a lower third order section of the upper region of the Little
133
Miami River in a small deciduous forest corridor of the Little Miami State Forest Preserve in
134
Xenia, Ohio, USA (39°76.552 83°90.062). The surrounding landcover of the catchment area was
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predominately agriculture, and the riparian forest was dominated by maple (Acer sp.) and elm
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(Ulmus sp.), but included hackberry (Celtis sp.), sycamore (Plantanus sp.), and walnut (Juglans
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sp.). The stream has been categorized as an Exceptional Warmwater Habitat by the Ohio
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Environmental Protection Agency because it supported high diversity of aquatic organisms
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(OEPA, 2002). The study was conducted in a 35 x 20 m run habitat where the substrate was
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predominately gravel and cobble with several intermittent boulders.
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Water quality and flow The following water quality variables were recorded at the start of the study and on every
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sampling date: temperature (ºC), specific conductivity (SpCond μS/cm), total dissolved solids
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(TDS mg/L), pH, turbidity (NTU), and dissolved oxygen (DO mg/L). Measurements were
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recorded every 30 sec for 10 min at upper, middle, and lower points along the reach using a YSI
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6600 v2 Sonde (YSI Inc, Yellow Springs, OH, USA). In addition, water depth (cm) and flow
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velocity (cm/s2) (FlowTracker® Handheld-ADV®; SonTek/Xylem, San Diego, CA, USA) were
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measured at each experimental board (see below).
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Experimental design Epilithic biofilms were allowed to naturally develop on two unglazed ceramic tiles (4.8 x
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4.8 x 0.5 cm) attached to brick pavers (19.2 x 9 x 1.3 cm) with 100% silicone under three
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conditions: ambient (control – no mesh), inclusion (reduced light/flow from mesh netting with
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grazer snails included), exclusion (reduced light/flow from mesh netting without snail grazing).
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The ambient condition was subjected to natural light and flow conditions and served as the
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control. These biofilms represent natural biofilms found on rocks that are prominent in the water
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column where leaf packs would not form. Abiotic effects simulating leaf deposition were created
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with 500 μm nylon mesh netting (BioQuip Products, CA, USA) that was folded into an enclosure
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(20 x 10 x 10 cm) and secured by hot glue. The mesh enclosure was attached to the paver with
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100% silicone and the resulting effect was reduced light and flow conditions and excluded
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grazers. Goniobasis (Elimia) sp. snails (1.5 cm; N = 2) at natural densities were added to the
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inclusion treatment enclosures through a slit that was sewn closed with fishing line. Natural snail
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density was determined on 1 October 2010 by quantifying the number of snails within nine, 50
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cm2 areas of benthic substrate throughout the study reach. Using VELCRO® tape, the pavers of
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each treatment were randomly distributed on wood boards (1 x 0.3 x 0.025 m) that were
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anchored to the streambed approximately 3.6 m apart along the thalweg (deepest section of the
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stream) to ensure as similar flow conditions as possible. Pavers were randomly sampled (N = 3
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per treatment) at 14, 24, and 38 days of growth. Tiles were removed, transported in the dark on
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ice to the lab, and stored at 4°C until processing within 24 h.
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The study was conducted from 15 October 2010 to 22 November 2010 and encompassed
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autumnal leaf deposition (Figure 1). Leaf packs that formed against the boards and biofilm
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material that developed on enclosure structures were gently removed every four days (Figure 1)
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to prevent the organic matter buildup from interfering with results by creating stagnant and
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anoxic conditions inside the enclosures. This did not remove the visually obvious biofilm
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material inside the enclosures so we feel the setup was still able to reflect physical effects of
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leaves while still ensuring grazer manipulation. Also, leaves were rarely found on ambient
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biofilms because there was not a protrusion for leaves to settle against and the slight elevation of
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the boards in the water column subjected them to flow that was not conducive for leaf
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deposition.
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Biofilm biomass
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Biofilm biomass from one tile per paver was removed using a sterile razor blade and
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toothbrush and suspended in ultrapure water (NANOpure II; Barnstead, Boston, MA, USA).
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Two sub samples for total biomass as ash free dry mass (AFDM) and algal-associated biomass as
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chlorophyll a were collected on GB-140 glass membrane filters (diameter, 25 mm; pore size, 0.4
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μm; Sterlitech, Kent, WA, USA) following techniques used by Steinman et al., (2007).
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Chlorophyll a filters were stored at -20°C until extraction within three months and were used to
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determine algal biomass by multiplying the chlorophyll a value by the biomass factor of 67
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(APHA, 1999). Biofilm from the second tile was removed and stored in 90% ethanol at -20°C
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until DNA extraction in autumn 2013 to determine community profiles.
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DNA extraction
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DNA was extracted from 0.1 - 0.3 g of ethanol evaporated, dried biofilm using a
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combination of methods from Miller et al., (1999) and Zhou et al., (1996) as suggested by Lear
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et al., (2010). Samples were lysed by bead beating (0.5 g each of 0.1 mm and 0.5 mm glass lysis
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beads; RPI, Mount Prospect, IL, USA) for 15 min on a horizontal vortex adaptor (MO BIO
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Laboratories, Carlsbad, CA, USA) at full speed in 1.2 mL of extraction buffer (100 mM Tris-
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HCl [pH 8.0], 100 mM EDTA disodium salt [pH 8.0], 100mM Sodium phosphate [pH 8.0], 1.5
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M Sodium chloride, 1% CTAB), 12 μL proteinase K (20 mg/mL), and 30 μL SDS (20%). The
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mixture was incubated at 65°C for 1 hr with gentle end-over-end inversions by hand every 15
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min. Then, 4 μL of RNase (100 mg/μL) was added. DNA was isolated from organic debris with
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chloroform/isoamyl alcohol extraction and was precipitated overnight at -20°C with isopropanol.
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The mixture was warmed to 37°C to dissolve salt precipitates, and DNA was pelleted at 15,000 g
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for 30 min. The DNA pellet was washed twice with ice cold 70% EtOH and dissolved in 25-50
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μL ultrapure water (NANOpure II; Barnstead, Boston, MA, USA). Samples were purified using
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PowerClean® DNA Clean-Up Kit (MO BIO Laboratories, Carlsbad, CA, USA) with a modified
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protocol for low amounts of DNA to remove PCR inhibitors typical of biofilm samples.
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ARISA Bacterial and eukaryotic communities were assessed using profiles created by automated
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ribosomal intergenic spacer analysis (ARISA) (Fisher & Triplett, 1999), which generates a
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unique ‘fingerprint’ of microbial communities using the 16S-23S intergenic space in bacteria and
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the ITS1-5.8S-ITS2 region in eukaryotes (Ranjard et al., 2001). While ARISA does not
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taxonomically identify organisms like next generation sequencing methods, this method
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generates community profiles and produces similar patterns in results (Bienhold et al., 2012; van
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Dorst et al., 2014). Approximately 15-20 ng of DNA quantified by spectrophotometer
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(NanoPhotometerTM Pearl; Denville Scientific Inc., South Plainfield, NJ, USA) was amplified
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by PCR using 25 μL GoTaq® Colorless Master Mix (Promega, Madison, WI, USA) with 0.5 μM
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of forward and reverse primers. Bacteria ribosomal intergenic space regions were amplified with
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primers ITSF (5’-GTCGTAACAAGGTAGCCGTA-3’) labeled with FAM at the 5’ end (IDT,
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Coralville, IA, USA) and ITSReub (5’-GCCAAGGCATCCACC-3’) (Cardinale et al., 2004).
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Eukaryote ribosomal intergenic space regions were amplified with primers 2234C (5’-
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GTTTCCGTAGGTGAACCTGC-3’) labeled with ATTOTM 550 (IDT, Coralville, IA, USA) and
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3126T (5’- ATATGCTTAAGTTCAGCGGGT-3’) (Ranjard et al., 2001). While the eukaryotic
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primer set has typically been used for soil fungal communities (Ranjard et al., 2001), sequenced
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clones of fragments from freshwater biofilms revealed it targets various algae and ciliates, and
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therefore can be used to describe the general eukaryotic community (Fechner et al., 2010).
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Fragments were created with the following PCR conditions: (i) 94°C for 3 min, (ii) 35 cycles of
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94°C for 1 min, 56°C (57.5°C for eukaryotes) for 1 min, 72°C for 2 min, and finally (iii) 72°C
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for 10 min (Fechner et al., 2010). Equal volumes of bacterial and eukaryotic PCR products from
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a sample were combined and sent to DNA Analysis, LLC (Cincinnati, OH, USA) for
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multiplexed fragment analysis on an ABI 3100 (Life Technologies, Carlsbad, CA, USA).
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Fragments were interpreted using Genescan v 3.7 using the Local Southern Size Calling Method
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with a peak height threshold of 100 fluorescence units to remove background fluorescence and
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formulated using GeneMapper v 2.5 (Life Technologies, Carlsbad, CA, USA).
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Fragment peak length and area was converted to column format using the treeflap Excel
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Macro (http://www.wsc.monash.edu.au/~cwalsh/treeflap.xls) and processed with the
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automatic_binner script to determine binning window size and the interactive_binner script to
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determine the best starting window position (Ramette, 2009) in R v 3.1.0 (R Core Team 2014).
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This method was used to account for inherent imprecision of analyzer machines. Peak area was
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converted to relative abundance of each fragment as part of the entire sample, fragments with
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