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\title[Resources affect planktonic and biofilm communities]{The effect of carbon subsidies on planktonic niche partitioning and recruitment during biofilm assembly}
\author[\firstAuthorLast]{\Authors}
\address{}
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%\extraAuth{corresponding Author2 \\ Laboratory X2, Institute X2, Department X2, Organization X2, Street X2, City X2 , State XX2 (only USA, Canada and Australia), Zip Code2, X2 Country X2, email2@uni2.edu}
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\begin{document}

\title{The effect of carbon subsidies on marine planktonic niche partitioning and recruitment during biofilm assembly}


 \author{Chuck Pepe-Ranney, Edward Hall}


\date{\today}

\maketitle




\section{Introduction}
% Fakesubsubsection:Biofilms are diverse and complex
Biofilms are diverse and complex microbial consortia, and, the biofilm
lifestyle is the rule rather than the exception for microbes in many
environments. Large and small-scale biofilm architectural features 
play an important role in their ecology and influence their role in
biogeochemical cycles \citep{17170748}. Fluid mechanics impact biofilm
structure and assembly \citep{hoedl_2011,19571890, 14647381}, but it is less
clear how other abiotic factors such as resource availability affect biofilm
assembly. Aquatic biofilms initiate with seed propagules from the planktonic
community \citep{hoedl_2011, 22120588}. Thus, resource amendments that
influence planktonic communities may also influence the recruitment of
microbial populations during biofilm community assembly.

% Fakesubsubsection:In a crude sense, biofilm and planktonic microbial
In a crude sense, biofilm and planktonic microbial communities divide into two
key groups: oxygenic phototrophs including eukaryotes and cyanobacteria
(hereafter "photoautotrophs"), and heterotrophic bacteria and archaea. This
dichotomy, admittedly an abstraction (e.g. non-phototrophs can also be
autotrophs), can be a powerful paradigm for understanding community shifts
across ecosystems of varying trophic state \citep{Cotner_2002}. Heterotrophs
meet some to all of their organic carbon (C) requirements from photoautotroph
produced C while simultaneously competing with
photoautotrophs for limiting nutrients such as phosphorous (P) \citep{379}. The
presence of external C inputs, such as terrigenous C leaching from the
watershed \citep{Jansson_2008, Karlsson_2012} or C exudates derived from
macrophytes \citep{Stets_2008, Stets_2008b}, can alleviate heterotroph reliance
on photoautotroph derived C and shift the heterotroph-photoautotroph
relationship from commensal and competitive to strictly competitive
\citep[see][Figure~\ref{fig:conceptual}]{Stets_2008}. Therefore, increased
C supply should increase the resource space available to heterotrophs and
increase competition for mineral nutrients decreasing nutrients available for
photoautotrophs (assuming that heterotrophs are superior competitors for
limiting nutrients as has been observed
\citep[see][Figure~\ref{fig:conceptual}]{COTNER_1992}). These dynamics should
result in the increase in heterotroph biomass relative to the photoautotroph
biomass along a gradient of increasing labile C inputs. We refer to this
differential allocation of limiting resources among components of the microbial
community as niche partitioning.

% Fakesubsubsection:While these gross level dynamics have been discussed
While these gross level dynamics have been discussed conceptually
\citep{Cotner_2002} and to some extent demonstrated empirically
\citep{Stets_2008}, the effects of biomass dynamics on
photoautotroph and heterotroph membership and structure has not been directly
evaluated in plankton or biofilms. In addition, how changes in planktonic
communities propagate to biofilms during community assembly is not well
understood. We designed this study to test if C subsidies shift the
biomass balance between autotrophs and heterotrophs within the biofilm or its
seed pool (i.e. the plankton), and, to measure how changes in biomass pool size
alter composition of the plankton and biofilm communities. Specifically, we
amended marine mesocosms with varying levels of labile C input and evaluated
differences in photoautotroph and heterotrophic bacterial biomass in plankton
and biofilm samples along the C gradient. In each treatment we characterized
plankton and biofilm community composition by PCR amplifying and DNA sequencing
16S rRNA genes and plastid 23S rRNA genes.






    
    

\section{Materials and Methods} 
\subsubsection{Experimental Design} Test tube racks were placed in one smaller
(185 L, control) and 3 larger (370 L) flow-through mesocosms. All mesocosms
were fed directly with marine water from an inflow source in Great Bay, Woods
Hole, MA, approximately 200 m from the shore. Each mesocosm had an adjustable
flow rate that resulted in a residence time of approximately 12 h. Irregular
variation in inflow rate caused the actual mesocosm flow rate to vary around
the targeted flow rate throughout the day. However, regular monitoring ensured
that the entire volume of each system was flushed approximately two times per
day (i.e. maintained a residence time of $\sim$12 h). To provide a surface for
biofilm formation, we attached coverslips to glass slides using nail polish
and then attached each slide to the test tube racks using office-style binder
clips. Twice daily 10 mL of 37 mM KPO$_{4}$ and 1, 5 and 50 mL of 3.7 M glucose
were added to each of 3 mesocosms to achieve target C:P resource amendments of
10, 100 and 500. The goal of the resource amendments was to create
a gradient of labile carbon. The same amount of P was added to
each treated mesocosm to ensure that response to additions of C were not
inhibited by extreme P limitation. The control mesocosm did not receive any
C or P amendments.

\subsubsection{DOC and Chlorophyll Measurements} To assess the efficacy of the
C additions, we sampled each mesocosm twice daily during the first week of the
experiment to evaluate dissolved organic C (DOC) content. After the initiation
of the experiment we collected plankton on filters regularly to evaluate
planktonic Chl \textit{a} and bacterial abundance. Once it was clear that pool
size of each community had been altered (day 8) we filtered plankton onto 0.2
$\mu$m filters and harvested coverslips to assess bacterial and algal biofilm
community composition (16S and plastid 23S rDNA). In addition, all mesocosms
were analyzed for community composition a second time (day 17) to assess how
community composition of both the plankton and biofilm communities had changed
over time. Control samples were only analyzed for community composition on day
17.

Samples for dissolved organic C (DOC) analysis were collected in acid
washed 50 mL falcon tubes after filtration through a 0.2 $\mu$m polycarbonate
membrane filter (Millipore GTTP GTTP02500, Sigma Aldrich P9199) attached to
a 60 mL syringe. Syringes and filters were first flushed multiple times with
the control sample to prevent leaching of C from the syringe or the filter into
the sample. Samples were then frozen and analyzed for organic C
content with a Shimadzu 500 TOC analyzer \citep{Wetzel_2000}. Biomass of all
biofilm samples were measured by difference in pre-(without biofilm) and
post-(with biofilm) weighed GF/F filters after oven drying overnight at
60 $\,^{\circ}$C.

For Chl \textit{a} analysis, we collected plankton on GF/F filters (Whatman,
Sigma Aldrich Cat. \# Z242489) by filtering between 500 mL and 1L from the
water column of each mesocosm for each treatment. For biofilm samples, all
biofilm was gently removed from the complete area of each coverslip (3
coverslips for each treatment per sampling event) before being placed in a test
tube for extraction with 90-95\% acetone for $\sim$32 hours at -20 $\,^{\circ}$C
and analyzed immediately using a Turner 10-AU fluorometer \citep{Wetzel_2000}.

Bacterial abundance of the planktonic samples was analyzed using DAPI staining
and direct visualization on a Zeis Axio epifluorescence microscope after
the methods of \citet{Porter1980}. Briefly, 1-3 mL
of water was filtered from three separate water column samples through
a 0.2 $\mu$m black polycarbonate membrane filter and post stained with
a combination of DAPI and Citifluor mountant media (Ted Pella Redding, Ca)
to a final concentration of 1 $\mu$L mL$^{-1}$.  

\subsubsection{DNA extraction} For plankton, cells were collected by filtering
between 20 {\textendash} 30 mL of water onto a 0.2 $\mu$m pore-size
polycarbonate filter (Whatman Nucleopore 28417598, Sigma-Aldrich cat\#
WHA110656). For biofilm communities, biomass from the entire coverslip area of
three separate slides was collected and combined in an Eppendorf tube by gently
scraping the slip surface with an ethanol rinsed and flamed razor blade. DNA
from both the filter and the biofilm was extracted using a Mobio Power Soil DNA
isolation kit (MoBio Cat. \# 12888). 

\subsubsection{PCR} Samples were amplified for 454 sequencing using
a forward and reverse fusion primer.  The forward primer was constructed
with (5{'}-3{'}) the Roche A linker, an 8-10 bp barcode, and the forward
gene specific primer sequence. The reverse fusion primer was constructed
with (5{'}-3{'}) a biotin molecule, the Roche B linker and the reverse
gene specific primer sequence. The gene specific primer pair for bacterial
SSU rRNA genes was 27F/519R \citep{LANED.J.:1991}. The primer pair
p23SrV\_f1/p23SrV\_r1 was used to target 23S rRNA genes on plastid genomes
\citep{Sherwood_2007}. Amplifications were performed in 25 $\mu$L
reactions with Qiagen HotStar Taq master mix (Qiagen Inc, Valencia,
California), 1 $\mu$L of each 5 uM primer, and 1 $\mu$L of template.
Reactions were performed on ABI Veriti thermocyclers (Applied Biosytems,
Carlsbad, California) under the following thermal profile: 95 $^{\circ}$C
for 5 min, then 35 cycles of 94$^{\circ}$C for 30 sec, 54$^{\circ}$C for
40 sec, 72$^{\circ}$C for 1 min, followed by one cycle of 72$^{\circ}$C
for 10 min and 4 $^{\circ}$C hold. Amplification products were
visualized with eGels (Life Technologies, Grand Island, New York).
Products were then pooled equimolar and each pool was cleaned with
Diffinity RapidTip (Diffinity Genomics, West Henrietta, New York), and
size selected using Agencourt AMPure XP (BeckmanCoulter, Indianapolis,
Indiana) following Roche 454 protocols (454 Life Sciences, Branford,
Connecticut). Size selected pools were then quantified and 150 ng of DNA
was hybridized to Dynabeads M-270 (Life Technologies) to create single
stranded DNA following Roche 454 protocols (454 Life Sciences). Single
stranded DNA was diluted and used in emPCR reactions, which were performed
and subsequently enriched. Sequencing followed established manufacture
protocols (454 Life Sciences).  

\subsubsection{Sequence quality control} The 16S rRNA gene and plastid 23S
rRNA gene sequence collections were demultiplexed and sequences with
sample barcodes not matching expected barcodes were discarded. We used the
maximum expected error metric \citep{23955772} calculated from sequence
quality scores to cull poor quality sequences from the dataset.
Specifically, we discarded any sequence with a maximum expected error
count greater than 1 after truncating the sequence to 175 nt. The forward
primer and barcode was trimmed from the remaining reads. We checked that
all primer trimmed, error screened, and truncated sequences were derived
from the targeted region of the LSU or SSU rRNA gene (23S and 16S
sequences, respectively) by aligning the reads to Silva LSU or SSU rRNA
gene alignment (``Ref'' collection, release 115) with the Mothur
\citep{19801464} NAST-algorithm \citep{16845035} aligner and inspecting
the alignment coordinates. Reads falling outside the expected alignment
coordinates were culled from the dataset. Remaining reads were trimmed to
consistent alignment coordinates such that all reads began and ended at
the same position in the SSU rRNA gene and screened for chimeras with
UChime in ``denovo'' mode \citep{21700674} via the Mothur UChime wrapper.
19,978 of 56,322 16S rRNA gene sequencing reads and 44,719 or 78,695
plastid 23S rRNA gene sequencing reads passed quality control.

\subsubsection{Taxonomic annotations} Sequences were taxonomically classified
using the UClust \citep{20709691} based classifier in the QIIME package
\citep{20383131} with the Greengenes database and taxonomic nomenclature
(version ''gg\_13\_5'' provided by QIIME developers, 97\% OTU representative
sequences and corresponding taxonomic annotations, \citep{22134646}) for
16S reads or the Silva LSU database (``Ref'' set, version 115, EMBL
taxonomic annotations, \citep{23193283}) for the 23S reads as reference.
We used the default parameters for the algorithm (i.e. minimum consensus
of 51\% at any rank, minimum sequence identity for hits at 90\% and the
maximum accepted hits value was set to 3).

\subsubsection{Sequence clustering} Reads were clustered into OTUs following
the UParse pipeline. Specifically USearch (version 7.0.1001) was used to
establish cluster centroids at a 97\% sequence identity level from the
quality controlled data and to map quality controlled reads to the
centroids. The initial centroid establishment algorithm incorporates
a quality control step wherein potentially chimeric reads are not allowed
to become cluster seeds. Additionally, we discarded singleton reads.
Eighty-eight and 98\% of quality controlled reads could be mapped back to
our cluster seeds at a 97\% identity cutoff for the 16S and 23S sequences,
respectively. 

\subsubsection{Alpha and Beta diversity analyses} Alpha diversity calculations
were made using PyCogent Python bioinformatics modules \citep{17708774}. 
Rarefaction curves show average OTU counts from 25 re-samplings at 
intervals of 10 sequences for each sample. Beta
diversity analyses were made using Phyloseq \citep{24699258} and its
dependencies \citep{vegan}. A sparsity threshold of 25\% was used for
ordination of both plastid 23S and bacterial 16S libraries.  Additionally, we
discarded any OTUs from the plastid 23S rRNA gene data that could not be
annotated as belonging in the Eukaryota or cyanobacteria for differential
abundance, ordination and Adonis analyses. Cyanobacterial DNA sequences were
removed from 16S rRNA gene sequence collections for ordination, Adonis and
differential abundance analyses. We operated under the assumption that
non-cyanobacterial bacteria are predominantly heterotrophs in our mesocosm
setup and refer to non-cyanobacterial bacteria as
``heterotrophs'' in the manuscript (this abstraction is useful however there
are likely exceptions -- i.e. autotrophs among the non-cyanobacterial
bacteria). All DNA sequence based results were visualized using GGPlot2
\citep{Wickham_2009}. Adonis tests and principal coordinate ordinations were
performed using the Bray-Curtis similarity measure for pairwise library
comparisons. Adonis tests employed the default value for number of permutations
(999) ("adonis" function in Vegan R package, \citet{vegan}). Principal
coordinates of OTUs were found by averaging site principal coordinate values
for each OTU with OTU relative abundance values (within sites) as weights. The
principal coordinate OTU weighted averages were then expanded to match the
site-wise variances \citep{vegan}.

\subsubsection{Identifying enriched OTUs} We used an RNA-Seq differential
expression statistical framework to find OTUs enriched in the given sample
classes (R package DESeq2 developed by \citet{Love_2014}) (for review of
RNA-Seq differential expression statistics applied to microbiome OTU count data
see \citet{24699258}). We use the term differential abundance coined by
\citet{24699258} to denote OTUs that have different relative abundance across
sample classes. We were particularly interested in two sample classes: 1)
lifestyle (biofilm or planktonic) and, 2) high C (C:P = 500) versus not
high C (C:P = 10, C:P = 100 and C:P = control). A differentially abundant
OTU is enriched on one side of a sample class (e.g. enriched in the
biofilm versus the plankton). Differential abundance could mark an
enrichment of the OTU towards either side of the sample class and the
direction of the enrichment is apparent in the sign (positive or negative)
of the enrichment. Differential abundance was moderated (see
\citet{Love_2014}) such that the fold change OTU of an OTU across two
categories of a sample class can be used to rank the enrichment of OTUs
that span a wide range of base abundance. The DESeq2 RNA-Seq statistical
framework has been shown to improve power and specificity when identifying
differentially abundant OTUs across sample classes in microbiome
experiments \citet{24699258}.

The specific DESeq2 \citep{Love_2014} parameters we used were as
follows: All dispersion estimates from DESeq2 were calculated using a local fit
for mean-dispersion. Native DESeq2 independent filtering was disabled in
favor of explicit independent filtering by sparsity. The sparsity
thresholds that produced the maximum number of OTUs with adjusted p-values
for differential abundance below a false discovery rate of 10\% were
selected. Cook's distance filtering was also disabled
when calculating p-values with DESeq2. We used the Benjamini-Hochberg
method to adjust p-values for multiple testing \citep{citeulike:1042553}.
Identical DESeq2 methods were used to assess enriched OTUs from relative
abundances grouped into high C (C:P = 500) or low C (C:P $<$ 500 and
control) categories.

IPython Notebooks with computational methods used to create all figures and
tables as well as taking raw sequences through quality control preprocessing
are provided at the following URL:

\url{https://github.com/chuckpr/BvP\_manuscript\_figures}.

Version information for all R libraries is provided at the end of each 
IPython Notebook.


\section{Results} \subsection{Bulk community characteristics} We first assessed
the effect of the resource treatments on the dissolved chemistry and bulk
community characteristics of the plankton and the biofilms. In the control
treatment the mean DOC level was 0.12 $+/-$ 0.02 $\mu$moles L$^{-1}$. The lower
C treatment (C:P $=$ 10) was statistically indistinguishable from the control at
0.10 $+/-$ 0.02 $\mu$moles C L$^{-1}$. The intermediate treatment (C:P $=$ 100)
increased in DOC to 0.70 $\mu$moles C L$^{-1}$ before decreasing to 0.12
$\mu$moles C L$^{-1}$ at the end of the experiment, with a mean of 0.28 $+/-$
0.16 $\mu$moles C L$^{-1}$ over the course of the experiment. Only the highest
C treatment (C:P $=$ 500) had DOC levels that were significantly higher (2.53
$+/-$ 1.6 $\mu$moles C L$^{-1}$) than the control treatment, over the course of
the experiment. The high DOC levels in the highest C treatment were consistent
with C being supplied in excess of the metabolic requirements of the community
(i.e. C saturation), but not higher than what has been observed in coastal
marine ecosystems.

% Fakesubsubsection:This increase in DOC
This increase in DOC in the higher C treatments was associated with decreases
in planktonic Chl \textit{a} in each treatment (Figure~\ref{fig:pool_size}A),
however there was no significant difference in biofilm Chl \textit{a} among
treatments (Figure~\ref{fig:pool_size}B). In combination with the decrease in
planktonic Chl \textit{a} on the 6th day of the experiment the highest
C treatment had approximately 4-fold higher planktonic heterotroph abundance
than the control and the 10 $\mu$M C treatment (Figure~\ref{fig:pool_size}D).
Similarly, biofilms had significantly higher total biomass in the high
C treatment compared to the other treatments (Figure~\ref{fig:pool_size}D).
Thus the shift in resource C:P altered the pool size of both the photoautotroph
and heterotroph communities. Clear differences in heterotroph and
photoautotroph pool size among treatments allowed us to address how shifts in
pool sizes were related to community membership and structure within and among
plankton and biofilm communities.

\subsection{Planktonic and biofilm community structure} \subsubsection{Alpha
diversity} We used rarefaction curves to evaluate alpha diversity in all
treatments for both the plankton and the biofilm communities. Rarefaction
curves showed heterotroph and photoautotroph OTU richness was consistently
higher in the biofilm compared to the planktonic communities
(Figure~\ref{fig:rarefaction}). For both the photoautotroph and heterotroph
sequence datasets the biofilm and plankton communities had the fewest OTUs in
the highest C treatment (C:P $=$ 500) (Figure~\ref{fig:rarefaction}). When
planktonic rRNA gene sequences from all planktonic samples were pooled,
individual biofilm heterotroph community richness still generally exceeded the
pooled planktonic heterotroph richness. For photoautotrophs, the individual
biofilm richness was similar to the pooled photoautotroph planktonic richness
(Figure~\ref{fig:integ_rarefaction}).

\subsubsection{Community membership biofilm versus plankton} Heterotroph
community membership between the plankton and biofilm communities was notably
different for all treatments except for the highest C treatment where the
plankton and biofilm communities during the second sampling event (day 17) were
more similar to each other than any other community (Figure~\ref{fig:pcoa}).
Photoautotroph plankton and biofilm communities were also different in OTU
composition, however, the similarity among photoautotroph plankton and biofilm
communities in the highest C treatment was not observed as it was for the
heterotroph communities (Figure~\ref{fig:pcoa}).

% Fakesubsubsection:In bacterial libraries, sequences
In heterotroph libraries, 19,978 sequences were distributed into 636 OTUs and
58\% of quality controlled sequences fell into the top 25 OTUs in order of
decreasing sum of relative abundance across all samples. In photoautotroph
libraries 44,719 23S plastid rRNA gene sequences were distributed into 359 OTUs
and 71\% of sequences fell into the top 25 OTUs sorted by mean relative
abundance across all samples.

% Fakesubsubsection:To investigate differences in
To investigate differences in community structure and membership between
the heterotroph biofilm and overlying planktonic communities we identified the
most enriched OTUs in biofilm compared to the planktonic communities and vice
versa. The most enriched OTUs were enriched in planktonic samples (with respect
to biofilm) as opposed to biofilm samples (Figure~\ref{fig:l2fc}). This is
consistent with the higher alpha diversity in biofilm communities compared to
planktonic communities and evidence that sequence counts were spread across
a greater diversity of taxa in the biofilm libraries compared to the planktonic
libraries (i.e. biofilm communities had higher evenness than planktonic
communities). Of the top 5 enriched heterotroph OTUs between the two lifestyles
(biofilm or plankton), 1 is annotated as \textit{Bacteroidetes},
1 \textit{Gammaproteobacteria}, 1 \textit{Betaproteobacteria},
1 \textit{Alphaproteobacteria} and 1 \textit{Actinobacteria} and all 5 were
enriched in the planktonic libraries relative to biofilm
(Table~\ref{Tab:01}). Of the 25 most enriched OTUs among lifestyles only
2 heterotroph OTU centroid DNA sequences shared high sequence identity ($>=$
97\%) with cultured isolates ("OTU.32" and "OTU.48", Table~\ref{Tab:01}). 

% Fakesubsubsection:We similarly assessed membership
We similarly assessed membership among biofilm and plankton in the
photoautotroph communities. Photoautotroph 23S plastid rRNA gene sequence
libraries also clustered strongly by lifestyle (Figure~\ref{fig:pcoa}). Biofilm
libraries were predominantly enriched in \textit{Stramenopile} OTUs whereas
planktonic libraries were enriched in \textit{Haptophyceae},
\textit{Cryptophyta} and \textit{Viridiplantae} OTUs based on OTU positions in
sample ordination space (Figure~\ref{fig:pcoa}, see Ordination Methods). When
photoautotroph OTUs were ordered by differential abundance between lifestyles
(see Figure~\ref{fig:l2fc}), 16 of the 25 most enriched OTUs were enriched in
the biofilm and 9 were enriched in the planktonic samples. Fourteen of these 16
biofilm enriched OTUs were \textit{Stramenopiles} of class
\textit{Bacillarophyta}, the remaining OTUs were classified as members of the
\textit{Chlorophyta} and \textit{Dinophyceae}. The 9 planktonic enriched OTUs
(above) were distributed into the \textit{Viridiplantae} (5 OTUs),
\textit{Cryptophyta} (1 OTUs), \textit{Haptophyceae} (1 OTU),
\textit{Stramenopiles} (1 OTU) and cyanobacteria (1 OTU). The 10 most enriched
photoautotroph OTUs between lifestyles were evenly split between planktonic and
biofilm enriched OTUs. As with the heterotrophs, photoautotroph OTU fold change
between lifestyles are qualitatively consistent with OTU positions in sample
ordination space (see Figures~\ref{fig:l2fc} and \ref{fig:pcoa}).

% Fakesubsubsection:The separation in community
In both the heterotroph and photoautotroph communities low abundance members of
the planktonic communities became highly abundant members of the biofilm
(Figure~\ref{fig:rank_abund}). The separation in community membership among
biofilm and planktonic communities is supported statistically by the Adonis
test \citep{Anderson_2001} for both the heterotroph and photoautotroph
libraries (p-value 0.003 and 0.002, respectively). The lifestyle category
represents 18\% and 45\% for pairwise sample distance variance in heterotroph
and photoautotroph libraries, respectively. The Adonis test result is also
consistent with lifestyle (biofilm versus planktonic) clustering along the
first principal component for the photoautotroph libraries but not for the
heterotroph libraries (Figure~\ref{fig:pcoa}).

\subsubsection{Heterotroph community membership changes with C amendments}
Although community membership was predominately driven by lifestyle, we also
investigated how resource amendments affected community membership and
structure. Because the abiotic (e.g. DOC) and all biomass indicators (e.g.
heterotroph abundance, Chl \textit{a}) were only significantly different in the
highest resource C:P treatment we compared resource C:P $=$ 500 (high C) to all
other mesocosms (i.e. control, C:P $=$ 10, and C:P $=$ 100 -- low C). The high
and low carbon amended mesocosms had statistically different heterotroph
communities (Adonis p-value 0.018) but not photoautotroph communities (Adonis
p-value 0.59). Nine heterotroph OTUs were enriched in the high C treatment
relative to low C. Four of the 9 high C enriched OTUs were annotated as
\textit{Alteromonadales}, 3 as \textit{Campylobacterales} and 1 each into
\textit{Vibrionales} and \textit{Pseudomonadales}. The most enriched OTU in low
C mesocosms was annotated as belonging to the "HTCC2188" candidate order and
shared 99\% identity with a 16S sequence annotated as "marine gamma
proteobacterium HTCC2089" (accession AY386332). We only observed differences at
the community level between high and low C amendments in the heterotroph
communities and therefore did not assess differential abundance of OTUs between
high and low C treatments in photoautotroph communities.  


\section{Discussion} 
\subsection{Biomass Pool Size} The goal of this study was to evaluate how
changes in available C affected the biomass pool size and composition of
planktonic and biofilm communities. Our results suggest that C subsidies
increased heterotroph biomass in both plankton and biofilm communities.
C amendments also resulted in decreased photoautotroph biomass in the plankton
community, but there was no significant change in biofilm
photoautotroph biomass between resource treatments. Although the DOC
concentration in the highest C treatment was significantly higher than the
other treatments, the concentrations we measured were in the range of those
reported in natural marine ecosystems \citep{Mopper1980} and it is has been
noted that glucose concentrations in coastal marine ecosystems may fluctuate
over several orders of magnitude \citep{Alonso2006}. The changes in the biomass
pool size that did occur were consistent with changing relationships (commensal
to competitive) between the autotrophic and heterotrophic components of the
plankton communities but not necessarily of the biofilm communities. While we
recognize that other mechanisms may drive the shift in biomass pool size of
these two components of the microbial community (e.g. increased grazing
pressure on the photoautotrophs with C additions, or production of secondary
metabolites by the heterotrophs that inhibit algal growth) previous studies
\cite{Stets_2008,Cotner_2002} and the data reported here suggest that altered
nutrient competition among heterotrophic and photoautotrophic members of the
plankton is the most parsimonious explanation for the observed shift in biomass
pool size.

\subsection{Biofilm and Plankton Alpha and Beta Diversity} Beyond changes
in the biomass pool size of each community, we explored how shifts in
resource C affected the membership and structure of each community, and
the recruitment of plankton during biofilm community assembly.
Intuitively, shifts in planktonic community composition should alter the
available pool of microorganisms that can be recruited into a biofilm. For
example, if planktonic diversity increases, the number of potential 
taxa that can be recruited to the biofilm should also increase, potentially
increasing diversity within the biofilm. Similarly, a decrease in
mineral nutrients available to photoautotrophs should decrease photoautotroph
pool size, potentially decreasing photoautotroph diversity and therefore
candidate photoautotroph taxa that are available for biofilm formation. In
addition, C in excess of resource requirements may increase the production of
extracellular polysaccharides (EPS) by planktonic cells thus increasing the
probability that planktonic cells are incorporated into a biofilm by adhesion.
Each of these mechanisms suggest that an increase in labile C to the system
should result in increased alpha diversity in heterotrophic plankton and
heterotrophic biofilm communities while decreasing alpha diversity within both
planktonic and biofilm photoautotroph communities. 

We highlight three key results that we find important for understanding
aquatic biofilm assembly. First, biofilm community richness exceeded
planktonic community richness (Figure~\ref{fig:rarefaction}) in all mesocosms.
Second, for the control, C:P $=$ 10 and C:P $=$ 100 resource treatments the
membership and structure of the heterotroph biofilm and plankton communities
were more similar within a lifestyle (plankton versus biofilm) than within
a resource treatment. However, for the bacteria in the highest C treatment (C:P
$=$ 500) both membership and structure of biofilm and planktonic communities at
day 17 were more similar to each other than to communities from other
treatments (Figure~\ref{fig:pcoa}). Third, C subsides acted differently on the
photoautotroph and heterotroph communities. Specifically, while the highest
level of C subsidies (C:P = 500) resulted in a merging of membership in the
heterotroph plankton and heterotroph biofilm communities the same merging of
membership was not observed for the photoautotroph biofilm and plankton
communities which had distinct membership in all treatments. 

% Fakesubsubsection:We propose two potential
We propose two potential mechanisms for the increased richness of the biofilm
communities relative to the planktonic community richness. First, it is
possible that the planktonic community composition of our flow through
incubators was dynamic in time. In this case the biofilm community would
represent a temporally integrated sample of the planktonic organisms moving
through the reactor resulting in higher apparent alpha diversity (i.e. mass
effects would be the dominant assembly mechanism). Second, the biofilm
environment may disproportionately enrich the low abundance members of the
planktonic community. In this case it is probable that the biofilm would
incorporate the most abundant members from the planktonic community (i.e. mass
effects) but also select and enrich (i.e. species sorting) the least abundant
members of the planktonic community resulting in a higher level of detectable
alpha diversity. The second mechanism would result if the biofilm environment
represented a more diverse microhabitat including sharply delineated oxygen,
nutrient and pH gradients that are not present in the planktonic environment.
In this case the more diverse microhabitat would be able to support a more
diverse community due to an abundance of additional environmental habitats
(i.e. niches). 

We evaluated the first mechanism by comparing membership among the plankton
samples taken 9 days apart (day 8 and day 17). While heterotrophic
plankton communities were not identical between the time points
(Figure~\ref{fig:pcoa}), communities within a treatment were more similar to
each other than other heterotroph plankton communities regardless of time. In
addition, the control and two lowest C treatments (C:P $=$ 10 and C:P $=$ 100)
separated completely from biofilm communities in principle coordinate space
(Bray-Curtis distance metric). This suggests that the biofilm community was not
integrating variable bacterioplankton community membership, but rather was at
least in part selecting for a community that was composed of distinct
populations when compared to the most abundant members of the plankton
community. As noted above, in the highest C treatment (C:P $=$ 500) the
heterotroph biofilm and plankton community membership had significant overlap
at the final timepoint (Figure~\ref{fig:pcoa}). However, heterotrophic plankton
community composition for the highest C treatment among timepoints (8 and
17 days) were also qualitatively as similar to each other as any other
community. Thus, variable planktonic community composition among timepoints
would not explain the higher diversity observed in the biofilm compared to the
planktonic community. Rather, two results point to enrichment of planktonic
community members within the biofilm as the mechanism for higher diversity in
the biofilm compared to the plankton. First, the increasing similarity between
the plankton and the biofilm communities between each time point in the highest
resource C treatment suggests that \textit{in situ} resource conditions were
sufficient to alter the relative abundance of the populations within each
community. Second, an analysis of the OTU relative abundance in biofilm and
planktonic libraries where OTUs are sorted by planktonic sample rank
(Figure~\ref{fig:rank_abund}) shows that the least abundant members of the
plankton community were routinely highly abundant within the biofilm community.
This was true for both photoautotroph and heterotroph communities, at all
treatment levels and both timepoints. While we did not (could not) specifically
measure niche diversity within the biofilm communities our results suggest that
the biofilm habitat selected for unique members of the photoautotroph and
heterotrophic community that were in low abundance in the planktonic habitat
but readily became major constituents of the biofilm community.

% Fakesubsubsection:few studies have
Few studies have simultaneously evaluated the relationship among membership
and/or diversity of the plankton and the biofilm community from complex
environmental microbial communities. One notable study looked at planktonic
community composition and biofilm formation on glass beads placed for three
weeks in three boreal freshwater streams \citep{22237539}. While that study
system is markedly different than our study, the analyses and questions
addressed in each study were sufficiently similar to merit comparison.
\citet{22237539} concluded that the biofilm community membership was most
likely driven by species sorting over mass effects. This is consistent with
what we report here. However, in the \citet{22237539} study the authors
reported that planktonic diversity was significantly higher relative to biofilm
diversity (the opposite of what we found in our study). Given the differences
in the source of the planktonic community among studies, this result is not
surprising. While biofilm communities were established on glass beads in
\citet{22237539} and glass slides (this study) over a similar time period (~21
days, \citet{22237539} and ~17 days this study) the origin of the planktonic
community in each study was different. The \citet{22237539} study was
conducted in three boreal streams during snow melt when connectivity between
the terrestrial and aquatic habitats was high and potentially highly variable
depending on how hydrologic pathways differed among precipitation events. In
this study the source community was a marine intake located approximately 200
m from the shore during July when communities are more stable over the 17 day
period of the incubation. A separate study conducted in alpine and sub-alpine
streams clearly showed that stream plankton communities reflected localized
precipitation events and could be traced largely to soil source communities
from drainages within the watershed \citep{22626459}. While planktonic
communities in lake ecosystems can be linked to soil communities in the
watershed, as residence time of the system slows the relative influence of
species sorting increases. Thus, in headwater ecosystems stream plankton
communities can often be composed primarily of soil organisms \citep{22378536}.
In addition to the diverse source communities the \citet{22237539} study
sampled the plankton community at multiple timepoints and integrated the
samples before sequencing further increasing community richness as compared to
the current study where the plankton community was sampled and analyzed only at
two independent timepoints. Indeed, when we pool OTU counts from all planktonic
libraries and compare the rarefaction curve of the pooled planktonic libraries
(photoautotrophs and heterotrophs) against sample-wise biofilm libraries, we
found more total heterotroph and photoautotroph planktonic OTUs than in any
given single biofilm sample. It appears, however, that sample-wise heterotroph
biofilm rarefaction curves may exceed the integrated planktonic curve upon
extrapolation and most exceed the integrated planktonic curve at sampling
depths where data is present for the biofilm and pooled planktonic library
(Figure~\ref{fig:integ_rarefaction}). This result is consistent with our
conclusion that temporal heterogeneity in the plankton was not sufficient to
explain the higher diversity in the biofilm sample but would explain the
relative differences between planktonic and biofilm diversity found in
\citet{22237539} compared to this study.

% Fakesubsubsection:In addition, for this
In addition, for this study, it is important to note that biofilm community
richness peaked at the intermediate treatment (C:P = 100) and appeared to
decrease between each time point although with only two time points it was unclear how
pronounced the temporal effect was nor is it possible assess the statistical
significance of this effect (Figure~\ref{fig:rarefaction}). Since biomass of
the plankton and the biofilm increased with increasing C subsidies the
intermediate peak in OTU richness is consistent with a classic
productivity-diversity relationship that has been shown for many ecosystems and
communities both microbial and otherwise. However, as with other experiments
our experimental design did not allow us to tell whether resources drove
productivity that subsequently drove changes in diversity or whether resources
drove diversity which altered productivity. Rather, we note that as diversity
decreased in the highest C treatment, heterotrophic plankton and biofilm
membership became increasingly similar. This suggests that environments that
contained high amounts of labile C selected for fewer dominant taxa,
overwhelming the lifestyle species sorting mechanisms that appeared to dominate
biofilm community assembly in all other treatments. Similarly, while we did not
measure extracellular polymeric substances (EPS), direct microscopy showed that
planktonic cells in the highest C treatment (C:P $=$ 500) were surrounded by
what appeared to be EPS. Because biofilm EPS also appeared to increase
from the low to high C treatments it is possible that abundant
planktonic cells were more readily incorporated into biofilms due both to
increased "stickiness" of the planktonic cells as well as the biofilm itself.
While we did not observe flocculating DOC which has been shown to dominate high
DOC environments in nature, we did measure a substantial increase in DOC in the
C:P $=$ 500 treatment which was more than 2-fold higher than any of the other
treatments. Thus additional adhesion of the plankton and the biofilm may also
explain the merging of the planktonic and biofilm heterotroph membership in the
highest C treatment.

\subsection{Lifestyle (biofilm or planktonic)  Enriched OTUs} There are only a
few studies that attempt to compare biofilm community composition and the
overlying planktonic community \citep{Besemer_2007, 22237539, Jackson_2001,
Lyautey_2005}. Those studies illustrate community composition among the two
habitats are unique, with few taxa found in both. This is consistent with
our findings in this experimental system with a natural marine planktonic
source community. In addition, our study also evaluated photoautotroph
community composition which showed a similar result suggesting that both the
photoautotroph and heterotroph biofilm communities are comprised of phylogenetically
distinct organisms that exist in low abundance in the surrounding habitat (i.e.
the plankton) but are readily enriched in the biofilm lifestyle. Most of the
biofilm enriched photoautotroph OTUs were \textit{Bacillariophyta} although
there were also many \textit{Bacillariophya} OTUs enriched in the planktonic
libraries. We also found more \textit{Cryptophyta} and \textit{Viridiplantae}
were enriched in the planktonic photoautotroph libraries. It appears that
these broad taxonomic groups were selected against in biofilms under our
experimental conditions. Heterotroph OTUs enriched in planktonic samples
displayed more dramatic differential abundance patterns than heterotroph OTUs
enriched in biofilm samples, but, biofilm enriched heterotroph OTUs were spread
across a greater phylogenetic breadth (Figure~\ref{fig:l2fc}). This is also
consistent with the idea of greater niche diversity in the biofilm environment
as opposed to the plankton. Greater niche diversity should select for a more
diverse set of taxa but individual taxa would not be as numerically dominant in
a more uniform environment like the planktonic environment. At the Order level,
enriched heterotroph OTUs tended to have members that were enriched in both the
plankton and the biofilm suggesting the phylogenetic coherence of lifestyle is
not captured at the level of Order. It should be noted, however, that taxonomic
annotations in reference databases and therefore environmental sequence
collections show little equivalency in phylogenetic breadth between groups at
the same taxonomic rank \citep{Schloss_2011}. Unfortunately, at higher
taxonomic resolution (e.g. Genus-level), groups did not possess a sufficient
numbers of OTUs to evaluate coherence between taxonomic annotation and
lifestyle. Carbon amendments did not affect photoautotroph library membership
and structure to the same degree as it affected heterotroph library
composition. As expected, heterotroph OTUs enriched in the high C amended
mesocosm (C:P $=$ 500) include OTUs in classic copiotroph families such as
\textit{Altermonodales} and \textit{Pseudomonadaceae}. Interestingly, the most
depleted OTU in the high C treatments is annotated as being in the HTCC2188
order of the \textit{Gammaproteobacteria} and shares 99\% sequence identity
with another "HTCC" strain (accession AY386332). HTCC stands for 'high
throughput culture collection' and is a prefix for strains cultured under low
nutrient conditions \citep{Cho_2004, Connon_2002}.

\subsection{Conclusion} In summary this study shows that changes in low
resolution community level dynamics are concurrent with changes in the
underlying constituent populations that compose them. We found that autotrophic
pools and heterotrophic pools responded differently to amendments of labile
C as hypothesized. Notably while C amendments altered both pool size and
membership of the heterotroph communities we did not see similar dynamics
within the photoautotroph communities. Planktonic photoautotrophs decreased in
response to C amendments presumably in response to increased competition for
mineral nutrients from a larger heterotroph community, however there was not
a similar decrease in biofilm photoautotroph community. In addition membership
of the photoautotroph communities between the plankton and biofilm lifestyles
did not become more similar in the photoautotrophs as it did for the bacterial heterotrophs
in the highest C treatment. Consistent with a growing body of work our results
suggest that complex environmental biofilms are a unique microbial community
that form from taxa that are found in low abundance in the neighboring
communities. This membership was affected by C amendments for heterotrophic but
not photoautotrophic microbes and then only in the most extreme resource
environment. This suggests that lifestyle is a major division among
environmental microorganisms and although biofilm forming microbes must travel
in planktonic form at some point, reproductive success and metabolic
contributions to biogeochemical processes comes from those taxa primarily if
not exclusively while they are part of a biofilm. Our results point to
lifestyle (planktonic or biofilm) as an important trait that explains a portion
of the exceptional diversity found in snapshots used to characterize
environmental microbial communities in space and time.\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/conceptualmodel/biofilmsubsidiesFigs06252013.001}
\caption{{Carbon subsidies in the form of glucose alleviate the dependence of
heterotrophic bacteria on photoautotroph derived C exudates. This should result in
an increase in resource space and biomass for heterotrophs and a decrease in
resource space and biomass for photoautotrophs due to increased competition for
mineral nutrients (for simplicity we illustrate competition for P but this is equally applicable other elements that may limit primary production). We hypothesized that this predicted change in biomass pool size
of these two groups will result in changes in the plankton community
composition of both groups that will propagate to to the composition of biofilm
communities for both groups. We refer to shifts in the demand and availability of resources among components of the microbial community as 'partitioning. Blue rods represent heterotrophs, green stars represent photoautotrophs, brown diamonds represent EPS or other cohesive components of a biofilm.%
}}
\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/pool-size/chachiefigure2final.003}
\caption{{Increased C amendments diminished A) planktonic photoautotroph biomass (estimated as
Chl \textit{a}) but B) not biofilm photoautotroph biomass. In contrast, both C)
biofilm total biomass and D) number of planktonic bacterial cells increased
with increasing C subsidies. Only the highest C treatment produced biomass that
was significantly greater than (p $<$ 0.05) the other treatments
(significant differences among treatments are denoted by different letters). The bacterial abundance sample for the C:P
$=$ 100 treatment was lost before analysis and is therefore not reported in
panel D.%
}}
\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=1.00\columnwidth]{figures/combined-rarefaction5/combined-rarefaction}
\caption{{Rarefaction curves for all biofilm versus plankton libraries.  Each panel 
represents a single C:P treatment and time point. Richness is greater for all
biofilm communities when compared to corresponding planktonic communities. Gray
ribbons are 99\% confidence intervals around each rarefaction point based on
variance from 25 re-samplings.%
}}
\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.84\columnwidth]{figures/biplot-combined1/biplot-combined}
\caption{{Principal coordinates ordination of bray-curtis distances for 23S rRNA plastid
libraries and 16S rRNA gene libraries. OTU points are weighted principal
coordinate averages (weights are relative abundance values in each sample) and
the variance along each principal axis is expanded to match the site variance.
Point annotations denote the amended C:P ratio for the mesocosm from which each
sample was derived.%
}}
\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=1.00\columnwidth]{figures/integrated-rarefaction/integrated-rarefaction}
\caption{{Rarefaction plots for all samples. Planktonic libraries have been integrated
such that the count for each OTU is the sum of counts across all samples. 
Gray ribbons are 99\% confidence intervals around each rarefaction point based 
on variance from 25 re-samplings.%
}}
\end{center}
\end{figure}

\section{Acknowledgements}

This research was conducted as part of the 2010 Marine Biological
Laboratory{'}s Microbial Diversity Course. Funding was supplied by the MBL, the
Bernard Davis Endowed Scholarship Fund, and the Selman A. Waksman Endowed
Scholarship. We would like to thank Dan Buckley and Steve Zinder for
organizing the course, Marshall Otter, Mathew Erickson, Hugh Ducklow and Jay T.
Lennon for analytical support and the Austrian FWF MICDIF award to Tom Battin
for salary support.

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