# Resource availability drives bacterial succession during leaf-litter decomposition in a bromeliad ecosystem

Jean-Francois Carrias, Mélanie Gerphagnon, Hector Rodriguez Perez, Guillaume Borrel, Camille Loiseau, Bruno Corbara, Régis Céréghino, Isabelle Mary, Céline Leroy

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## ► To cite this version:

Jean-Francois Carrias, Mélanie Gerphagnon, Hector Rodriguez Perez, Guillaume Borrel, Camille Loiseau, et al.. Resource availability drives bacterial succession during leaf-litter decomposition in a bromeliad ecosystem. FEMS Microbiology Ecology, 2020, 96 (4), pp.fiaa045. 10.1093/fem-sec/fiaa045. hal-02880883

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RESEARCH ARTICLE

# Resource availability drives bacterial succession during leaf-litter decomposition in a bromeliad ecosystem

Jean-François Carrias¹,*,†, Mélanie Gerphagnon¹, Héctor Rodríguez-Pérez², Guillaume Borrel³, Camille Loiseau¹, Bruno Corbara¹, Régis Céréghino⁴, Isabelle Mary¹ and Céline Leroy²,⁵

¹Université Clermont-Auvergne, CNRS, LMGE (Laboratoire Microorganismes: Génome et Environnement), F-63000 Clermont-Ferrand, France, ²UMR EcoFoG, CNRS, CIRAD, INRA, AgroParisTech, Université des Antilles, Université de Guyane, 97310 Kourou, France, ³Institut Pasteur, Department of Microbiology, Unité de Biologie Évolutive de la Cellule Microbienne, Paris, France, ⁴Ecolab, Laboratoire Ecologie Fonctionnelle et Environnement, CNRS, Université de Toulouse, 118 route de Narbonne, 31062 Toulouse, France and ⁵AMAP, IRD, CIRAD, CNRS, INRA, Université Montpellier, Montpellier, France

*Corresponding author: LMGE UMR CNRS 6023, 1 impasse Amélie Murat, Campus des Cézeaux, 63178 Aubière, France. Tel: +33 (0)473 405 138; E-mail: j-francois.carrias@uca.fr

**One sentence summary:** This study details ecological succession patterns of litter-degrading bacteria in a natural environment and tests whether trends in primary succession can be predicted from niche-based concepts established for macro-organisms.

Editor: Petr Baldrian

Jean-François Carrias, http://orcid.org/0000-0002-6201-1544

ABSTRACT

Despite the growing number of investigations on microbial succession during the last decade, most of our knowledge on primary succession of bacteria in natural environments comes from conceptual models and/or studies of chronosequences. Successional patterns of litter-degrading bacteria remain poorly documented, especially in undisturbed environments. Here we conducted an experiment with tank bromeliads as natural freshwater microcosms to assess major trends in bacterial succession on two leaf-litter species incubated with or without animal exclusion. We used amplicon sequencing and a co-occurrence network to assess changes in bacterial community structure according to treatments. Alpha-diversity and community complexity displayed the same trends regardless of the treatments, highlighting that primary succession of detrital-bacteria is subject to resource limitation and biological interactions, much like macro-organisms. Shifts in bacterial assemblages along the succession were characterized by an increase in uncharacterized taxa and potential N-fixing bacteria, the latter being involved in positive co-occurrence between taxa. These findings support the hypothesis of interdependence between taxa as a significant niche-based process shaping bacterial communities during the advanced stage of succession.

**Keywords:** ecological succession; bacterial diversity; community ecology; decomposition; amplicon sequencing; 16S rRNA gene
## INTRODUCTION

Studying the processes that drive the sequential replacement of species within a community or an ecosystem has long been a central theme in ecology (Walker et al. 2010; Prach and Walker 2011; Sommer et al. 2012). However, most of our current understanding of ecological succession has come from studies of macro-organisms, notably plant communities (Tilman 1985; Pickett, Collins and Armesto 1987; Van Andel, Bakker and Grootjans 1993). Despite recognition of their role in multi-trophic processes (Delgado-Baquerizo et al. 2016) and a growing number of surveys of microbial succession, much less is known about the mechanisms that drive primary succession of bacteria (Redford and Fierer 2009; Fierer et al. 2010). Currently, the development of high-throughput sequencing yields high resolution of microbial taxonomic diversity (Xu 2006), providing microbial ecologists with relevant tools to assess patterns of microbial succession (Knelman et al. 2014; Nemergut et al. 2016). Nemergut et al. (2013) proposed four major processes in driving bacterial community assembly: (i) selection, which involves abiotic (e.g. habitat conditions, environmental filtering) and biotic factors (e.g. viral lysis, predation, species-species interaction such as competition or facilitation), (ii) dispersion, (iii) genetic diversification encompassing the historical processes of evolution and more rapid genetic variation related to mutation and gene transfer, and (iv) ecological drift, random changes in the relative abundance of the different taxa within the community. Disentangling the relative importance of these processes in space and/or time is a major challenge in current microbial ecology (Nemergut et al. 2013; Dini-Andreote et al. 2015; Louca et al. 2017). It is generally assumed that carbon sources (Goldfard et al. 2011; Bray, Kita-jima and Mack 2012), pH (Lindström, Kamst-Van Agterveld and Zwart 2005; Nicol et al. 2008; Goffredi, Kantor and Woodside 2011) and species-species interactions (Freilich et al. 2011; Zelezniaki et al. 2015; Rivett et al. 2016) are major drivers of bacterial community assembly, highlighting that non-neutral, deterministic processes play a greater role than neutral, stochastic processes. Stochasticity is however expected to prevail during the initial stage of bacterial colonization where dispersal limitation has a strong impact on community assembly (Fierer et al. 2010; Ferrenberg et al. 2013; Dini-Andreote et al. 2015).

Microbial communities have a great influence on the decomposition of organic matter (Gessner, Chauvet and Dobson 1999). The decomposition of plant litter in particular is a key ecosystem process in nutrient and carbon cycling on the local to global scale (Prescott 2010), sustaining successional stages of microbial communities from the early colonization of plant litter to advanced decomposition (Purahong et al. 2016). Therefore, plant decomposition provides a relevant context to shed interesting new light on microbial succession and related processes of community assembly. In many Neotropical terrestrial ecosystems, the interlocking leaves of tank bromeliads (Bromeliaceae, a speciose and ecologically important family of Neotropical flowering plants; Zizka et al. 2019) hold rainwater and capture leaf litter originating from the overhanging trees, forming a suitable habitat for diverse aquatic organisms that range from bacteria to macroinvertebrates (Frank and Lounibos 2009; Brouard et al. 2012). The aquatic bacteria, fungi and detritivorous invertebrates break down the leaf litter (Brouard et al. 2012) as in other detritus-based freshwater systems. Compared to larger freshwater ecosystems (i.e. lakes, streams), understory tank bromeliads offer quite homogeneous environmental

conditions and are highly replicated on nature (Farjalla et al. 2016). Moreover, important variables that may affect or interrupt the microbial succession (e.g. habitat size, incident light) inside the tanks can easily be controlled in field experiments (Srivastava et al. 2004; Trzcinski et al. 2016). Hence, this natural microcosm has been widely used as a model system in field observations and manipulative experiments to study ecosystem processes, metacommunity and food web assembly rules, as well as relationships between environmental variability, biological diversity and ecosystem function (Srivastava and Bell 2009; Céréghino et al. 2011; Dézerald et al. 2013; Hammill, Atwood and Srivastava 2015).

In this study, our general goal was to reveal patterns of microbial primary succession in a natural environment, and, more importantly, to decipher the mechanisms that drive community assembly during decomposition. Specifically, we recorded the bacterial colonization of leaf litter that decays within the rainwater-filled leaves of tank bromeliads in a primary forest plot of French Guiana. By using oven-dried leaves and controlling the abiotic environment, we were able to closely approximate the environmental conditions of a primary succession, i.e. the colonization of a new substrate by organisms in a single site where annual temperature variations remain low (see Finegan 1984). We used two common species of plant litter that slightly differed in their chemical composition, allowing us to test the role of local environmental factors (i.e. organic carbon source) on community assembly. Because shredder-scrapers invertebrates can influence mass loss rate and microbial activity and community composition (Gessner, Chauvet and Dobson 1999; Hättenschwiler et al. 2011), we used coarse and fine mesh size enclosures to selectively exclude invertebrates from the leaf packs, and thus further test the effect of animals on decomposition and bacterial succession. According to predictions of the resource-ratio theory (Tilman 1985) applied to microorganisms (Fierer et al. 2010), we expected that: (i) patterns of species replacement should occur along the time sequence, (ii) an initial increase in bacterial diversity during the early stage of succession should be followed by a stabilization phase, and (iii) the number of specialized taxa should increase over time. We tested whether leaf identity and the presence of invertebrates affect the directional replacement of species and community structure during succession. As nitrogen is an important limiting factor for tank bromeliads (Ngai and Srivastava 2006; Leroy et al. 2016), we tested the presence of nitrogen-fixing bacteria all along the succession. Finally, because species interactions (i.e. competition and facilitation) are a main driver of community composition (Calloway and Walker 1997; Bruno, Stachowicz and Bertness 2003) and affect community complexity, we used network co-occurrence analysis as a proxy of community complexity.

## MATERIAL AND METHODS

### Study area and bromeliads

The experiment was conducted in French Guiana, in a lowland rainforest located near the Petit-Saut hydroelectric dam, Sinamary (latitude: 5° 03' 43" N; longitude: 53° 02' 46" W; elevation a.s.l. 80 m). The climate is moist tropical, with a dry season extending between September and November, and 3000 mm of annual rainfall over 280 days. The maximum monthly temperature averages 33.5°C and the monthly minimum is 20.5°C. The tank bromeliad *Aechmea aquilega* (Salib.) Griseb. commonly
occurs in the study area and its large size eases manipulation of flow-through enclosures within its leaf axils (see Trzcinski et al. 2016 and Rodríguez-Pérez et al. 2018 for experiments at our study site). Thirty plants with similar vegetative traits (number of leaves, size, plant diameter) and with maximum water volume were potted and randomly placed within the experimental forest plot. We ensured that the mean (± SD) incident radiation above individual plants was consistent (30.6 ± 7.1%; calculated using a hemispherical photograph technique as described in Leroy et al. 2009). At day 0 (7 days prior to the first sampling date, see below), the wells of each tank bromeliad containing rainwater, aquatic communities and detrital organic matter, were carefully sampled by sucking out the content using 10-mL micropipettes with the end trimmed to widen the aperture (Jabiel et al. 2009; Jocqué et al. 2010). In order to maximize the sampling efficiency, the water was sucked in and out three times before extracting it. The samples were then pooled in a large bucket and the same volume was poured into each plant after careful mixing to homogenize detrital organic matter, microbial communities and macro-organisms between experimental tank bromeliads.

## Leaf litter and flow-through enclosures

We chose two leaf-litter species belonging to common tree species in French Guiana, *Goupia glabra* Aubl. (Goupiaceae) and *Platonia insignis* Mart. (Clusiaceae), that grow in the area and are frequently found in tank bromeliads. Their chemical composition has already been quantified in our study area (Coq et al. 2010; Table S1, see online supplementary material), and they are among the most rapidly decomposing leaf-litter species in French Guiana soils (Coq et al. 2010; Hättenschwiler et al. 2011). Freshly fallen leaves from both tree species were collected in litter traps, hydrated in filtered rainwater for 24 h, and then cut into strips. Leaf strips were oven dried at 60°C for 48 h and weighted to the nearest 0.1 mg. Flow-through enclosures were constructed from injection anchor sleeves (Fisher®, diameter = 16 mm, length = 85 mm, mesh size = 2 mm; Rodríguez-Pérez et al. 2018). A set of enclosures was modified by drilling large holes (~4 mm diameter) to improve water flow and invertebrate movement within the bromeliad leaf axils (hereafter coarse mesh enclosures). A second set of enclosures was covered with 80 µm Nitex® mesh to allow water flow but prevent invertebrates access (hereafter fine mesh enclosures). Each flow-through enclosure received six leaf strips, i.e. two 1 × 4 cm and one 1 × 5 cm strip of *G. glabra*, and two 1 × 4 cm and one 1 × 5 cm strip of *P. insignis*. The longer 1 × 5 cm strips were easily recognized at the end of the experiment and were used for genomic DNA extraction while the 1 × 4 cm strips were used to estimate leaf-litter mass loss.

## Experimental design and sample collection

To follow the mass loss rate and the bacterial community on leaf-litter with and without invertebrates, we incubated one pair of enclosures (one coarse mesh and one fine mesh enclosure) in one leaf axil per plant for six different incubation times (7, 14, 28, 56, 112 and 224 days) replicated five times, for a total of 30 plants and 60 enclosures. For each plant, we selected a large, intermediate leaf axil, avoiding the central reservoir (young leaves in the process of formation) and the old, senescent ones. The experiment started on 30 September 2014 and ended on 5 May 2015 covering the dry and the short rainy seasons. In order to ensure stable abiotic conditions, we selected leaf axils that had

the same water-holding capacity, and the water level was maintained constant throughout the experiment by manually adding rainwater. Water temperature in each bromeliad was recorded hourly throughout the experiment using small Thermochron iButton® dataloggers immersed in a leaf axil adjacent to the one that contained the two enclosures. Bromeliad water pH was measured close to the enclosures using pH indicator papers (accuracy: 0.3 units; range: 3.9-6.9) for a total of 45 measurements randomly distributed with regard to time and leaf axil. At each sampling date, 10 enclosures from 5 plants were collected and kept in a cooler for transportation. In the laboratory, a careful inspection of each leaf strip from coarse mesh enclosures allowed us to pick up and sort all invertebrates prior to fixation in 90% ethanol. Invertebrates were also exhaustively sampled in all bromeliads by repeated pipetting. The 1 × 4 cm leaf strips were dried at 60°C for 48 h and weighted to the nearest 0.1 mg to assess dry mass loss. The 1 × 5 cm leaf strips were kept at -20°C prior to being processed for DNA extraction.

## DNA extraction

Leaf strips of three of the five original replicates were randomly selected for DNA extraction. We used an Ultra clean® soil DNA extraction kit (MOBio Laboratories, Inc) with modification of the manufacturer's instructions. In order to increase the efficiency of the mechanical lysis by bead beating, leaf strips were cut into pieces of ~1 × 2.5 mm. A first, lysis cycle was carried out by adding 600 µl of Bead solution and 50 µl of C1 solution to the leaves, followed by a bead-beating step at 5.5 m/s for 20 s with a Fastprep-24 (MP-Biomedicals). After centrifugation, the supernatant was transferred into a clean tube. A second lysis cycle with harsher conditions was carried out by adding an extra 250 µl of Bead solution and 20 µl of C1 solution to the leaves, incubating for 3 min at 60°C and bead-beating at 6.5 m/s for 30 s. After centrifugation, the supernatant was pooled with the supernatant of the first lysis cycle. gDNA purification part was achieved by following the manufacturer's instructions.

## Presence of the nitrogenase iron protein gene

Dilutions of the gDNA extracted from leaf strips were used to amplify the nitrogenase iron protein (nifH) gene with a polymerase chain reaction (PCR) procedure using polF (5'-TGCGA YCCSAARGCBGACTC-3') and polR (5'-ATSGCCATCATYTCRCC GGA-3') primers. The conditions of the PCR are described in Poly, Jocteur Monrozier and Bally (2001). A 100-fold dilution was applied to all gDNA samples. Amplification products were visualized with 1% agarose gels stained with ethidium bromide.

## Quantification of the bacterial 16S rRNA gene and fungal 18S rRNA gene

Bacteria and fungi were quantified by quantitative PCR (qPCR) using 338F (5'-ACTCCTACGGGAGGCAG-3')/515R (5'-ATTACCG CGGCTGCTGG-3') primers (annealing at 60°C) and FR1 (5'-G ATAACGAACGAGACCT-3')/FF390 (5'-AICCATTCAATCGGTAIT-3') primers (annealing at 50°C), respectively (see Rodríguez Pérez et al. 2018 for detailed conditions). All reactions were performed using the MESA green qPCR Master mix Plus for SYBR® assay (Eurogenetec). In order to minimize biases due to the presence of PCR inhibitors co-extracted with gDNA, several dilutions ranging from 10- to 200-fold were tested on a subset of gDNA samples. A 100-fold dilution was chosen and applied to all gDNA samples. A serial dilution of plasmids containing a partial bacterial 16S
rRNA gene or a partial fungal 18S rRNA gene was used as a stan-
dard curve. Quantifications were performed twice on each of the
three replicates by condition.

Amplicon sequencing on partial bacterial 16S rRNA
gene

All samples (replicates) were sequenced with Miseq sequencing.
The V3-V4 region of the 16S rDNA was amplified by PCR using
S-D-Bact-0341-b-S-17 forward primer (5'-CCTACGGNGGCWGC
AG) and S-D-Bact-0785-a-A-21 reverse primer (5'-GACTACHVG
GGTATCTAATCC-3') (Herlemann et al. 2011), following Illumina's
Miseq protocol for 16S amplicons. Amplicons were paired-end
sequenced (2 × 300) on an Illumina MiSeq platform (Gentyane,
Clermont-Ferrand, France) according to the standard Illumina
protocols.

Sequence analyses

Raw FASTQ files were de-multiplexed and quality-filtered using
TRIMMOMATIC V0.32 (Bolger, Lohse and Usadel 2014) with
the criteria specified below. All raw sequence data have been
deposited in the MG-RAST public database (Meyer et al. 2008)
under the accession ID mgp92102. The 300-bp reads that
obtained an average quality score <8 and shorter than 290 pb
were discarded. Illumnia reads were assembled with PANDAseq
(Masella et al. 2012) and then processed using Mothur version
1.36 (Schloss et al. 2009). Contigs longer than 466 pb, differing
by >1 nt from primer sequences, having at least one ambigu-
ous base, and/or having >8 nt homoplymers were removed. All
sequences with abundances of <2 were also removed. Chimeras
were discarded using UCHIME (Edgar et al. 2011). The classifica-
tion of operational taxonomic units (OTUs) at 97% identity using
furthest neighbour clustering was done using Mothur and the
ribosomal database project (RDP) taxonomic database release
v14 (Cole et al. 2009). To control for differences in contig numbers
at each time and biological condition, the number of sequences
was normalized by randomly subsampling to the number of con-
tigs in the sample, with the fewest number resulting in 7510 con-
tigs per sample. All contigs, whatever groups, were grouped by
OTU resulting in 13 128 OTUs. OTUs containing <0.01% of total
sequences were removed and sequences were normalized again
to the fewest number (i.e. 5360 sequences per sample). Anal-
yses were then carried out on 920 OTUs representing 369 840
sequences, corresponding to 36 samples for G. glabra (6 incuba-
tion times x 3 replicates x 2 enclosure treatments) and 33 sam-
ples for P. insignis (36 minus 3 samples that did not meet the
quality level: 7 days coarse mesh, 7 days fine mesh and 224 days
fine mesh). We estimated α-diversity using Chao1 and Invsimp-
son index. Phylogenetic β-diversity was estimated using prin-
cipal coordinates analysis (PCoA) of weighted and unweighted
UniFrac distances (Lozupone, Hamady and Knight 2006, 2007).
Network analysis of taxon co-occurrence patterns was per-
formed using Cytoscape V. 3.4.0 (Shannon et al. 2003). Prior to
network analyses, actual OTUs co-occurrence pattern was com-
pared with a null model to check for random co-occurrence
patterns. Networks were generated individually for each litter
species on a reduced OTUs database. Rare OTUs, with >50% of
zeroes, were filtered out (Weiss et al. 2016). Pair-wise Spearman's
correlation matrix was calculated and then, based on a ran-
dom matrix theory approach, significant thresholds at a P < 0.01
level were assessed (0.710 and 0.590 respectively for G. glabra.
and P. insignis litter-based networks). These statistical analyses
were performed by means of the Molecular Ecological Network

Approach Pipeline (http://ieg4.ou.edu/MENA) based on the χ²
test with Poisson distribution (Deng et al. 2012). The nodes in
the resulting networks thus represent the OTUs at 97% iden-
tity, coloured according to the stage during the time sequence
for which they exhibited their maximal abundance. Edges repre-
sent the correlation between OTUs as defined above. In order to
examine the complexity of the community (Barberan et al. 2012),
we calculated for each network the number of edges and nodes,
and different network metrics.

Statistical analyses

Leaf mass loss through time was fitted to an exponential model
$m_t/m_0 = e^{-kt}$, where $m_t$ is the mass remaining at time t, $m_0$ is
the initial mass, and $k$ is the breakdown rate constant (Boul-
ton and Boon 1991). Breakdown rates were estimated indepen-
dently for *G. glabra* and *P. insignis* incubated in the coarse and fine
mesh enclosures, using nonlinear regression. We used mixed
models to test the effect of incubation time (continuous vari-
able), mesh size (factorial variable with two levels, fine and
coarse) and leaf-litter species (factorial variable with two lev-
els, *G. glabra* and *P. insignis*) on microbial abundances (number
of 16S and 18S rRNA gene copies, for bacterial and fungal abun-
dances, respectively) and bacterial α-diversity indices (Invsimp-
son and Chao1). The number of 16S rRNA gene copies and val-
ues of the Invsimpson indice were log10-transformed to improve
residuals homoscedasticity and normality. Three independent
mixed models were run, including the aforementioned variables
as predictors and plant identity (18 levels) as random effects.
Model fit was evaluated graphically by exploring residuals pat-
terns (Bolker *et al. 2009*). The effects of time, treatments (mesh
size and leaf-litter species) and their interactions on phyloge-
netic β-diversity were tested with a PERMANOVA on weighted
and unweighted UniFrac distances matrices. In addition, based
on OTU abundances, we tested differences in bacterial composi-
tion with a PERMANOVA using Bray-Curtis distance on log(x+1)
transformed abundances, considering incubation time and lit-
ter donor species as factors. We also ran a PERMANOVA analy-
sis, including the same aforementioned factors, on OTU pres-
ence/absence data using Jaccard distance. Statistical analyses
were performed with R software (R Core Team 2014) and the fol-
lowing package: car (Fox and Weisberg 2011), EcoSimR ver. 0.1.0
(Gotelli, Hart and Ellison 2015), nlme ver. 3.1-118 (Pinheiro *et al.*
2014) and vegan ver. 2.2-1 (Oksanen *et al.* 2015).

RESULTS

Abiotic conditions in the wells and mass loss

Water temperature inside the leaf axils averaged 24.4 ± 0.6°C and was similar to the average air temperature (24.2 ± 0.7°C). Values of pH were also very stable (mean ± SD: 6.0 ± 0.1). Although *G. glabra* decomposed faster than *P. insignis* (Fig. 1) no significant differences in mass loss were recorded, either between fine and coarse mesh enclosures or between leaf species.

Abundance of microbial communities and bacterial
α-diversity

The number of 16S and 18S rRNA gene copies increased signif-
icantly with time, but no difference between mesh size enclo-
sures was found (Table 1, Fig. 2). The abundances were however
significantly higher for *G. glabra* than for *P. insignis*, with marked
<figure><img src="image_3.png" /><figcaption>Figure 1. Mass loss rates over time according to mesh size and leaf-litter species. Models for G. glabra (light grey) and P. insignis (dark grey) follow a negative exponential decay model ($W_t/W_0 = e^{-\delta t}$). Solid line models are based on fine mesh samples and dotted line models are based on coarse mesh samples.</figcaption></figure>

differences at 56 and 112 days of immersion for both bacteria (Fig. 2A) and fungi (Fig. 2B). Temporal changes of abundances were similar between leaf litter species, with a slight decline in bacteria at 112 days (Fig. 2A) in parallel with a marked peak in fungi (Fig. 2B). Time induced a significant increase in bacterial α-diversity ($P < 0.01$; Invsimpson and Chao1 indexes, Table 2, Fig. 3). Mesh size, litter species and the interaction between these treatments and time had no significant impact on bacterial α-diversity (except Chao1 index that increased significantly due to mesh size and time interaction, Table 2). Accordingly, the temporal patterns observed for the two indexes were comparable whatever the treatments (Fig. 3). Values increased markedly until the 56th day of immersion, and then remained relatively stable.

## Bacterial phylogenetic β-diversity

Weighted UniFrac PCoA revealed important clustering of the bacterial communities over the different phases of the time sequence. Samples were clearly divided according to their incubation time along axis 1 ($PseudoF = 11.86$, $df = 5$, $P = 0.001$),

which accounted for 34.2% of the variation (Fig. 4). The highest turnover was observed between 28 and 56 days, resulting in marked phylogenetic dissimilarities between the bacterial communities of the initial and late stages of the time sequence. Leaf-litter species also had a significant effect on phylogenetic β-diversity ($PseudoF = 3.26$, $df = 1$, $P = 0.014$) but mesh size had no significant effect ($PseudoF = 1.01$, $df = 1$, $P = 0.3$). Unweighted UniFrac PCoA showed a similar pattern of sample distribution (data not shown).

## Overall bacterial community composition

Among the 920 OTUs, 91.7% were affiliated to 18 phyla. The relative abundance of phyla across all sequences showed Proteobacteria as a dominant taxonomic group, representing 43.7% of the total OTUs and 63.8% of the total bacterial sequences. A set of 9 different phyla, ranging from 2.6 to 8.5% of the total OTUs, comprised Acidobacteria (8.2% of sequences), Verrucomicrobia (6.8%), Actinobacteria (3.2%), Bacteroidetes (3.9%), Planktomycetes (1.0%), Firmicutes (3.5%), Armatimonadetes (1.3%) and Spirochaetes (2.2%). We also found eight phyla/candidate phyla (Candidate division WPS 1, Candidate division WPS 2, Candidatus Saccharibacteria, Chlamydiae, Hydrogenedentes, Chloroflexi, BCR1, Ignavibacteria, Latescibacteria), each representing <1.1% of the total OTUs. Finally, 76 OTUs (8.3% of the total OTUs, 4.0% of sequences) were not affiliated to identified phyla.

## Temporal variation in bacterial community composition

To visualize temporal changes in community composition at the order level, values from the three replicates of each mesh treatment were pooled (resulting in six replicates for each leaf litter species and time), because mesh size did not significantly affect bacterial community structure. We found that among the 41 bacterial orders detected during the study, only 11 orders represented >5% of the total number of sequences at at least one of the incubation times. These 11 orders represented on average 62.9 and 63.4% of the total bacterial abundance for G. glabra and P. insignis, respectively. For both leaf-litter species, the relative contribution of all these dominant orders was the highest at 7 days and decreased during the time sequence (Fig. 5A, B). Differences in community composition between leaf-litter species and incubation times were confirmed by PERMANOVA on OTU abundances (incubation time: pseudoF = 10.07, $df = 5$, $P = 0.001$; leaf-litter species: pseudoF = 3.50, $df = 1$, $P = 0.004$), and OTU presence/absence data (incubation time: pseudoF = 7.15, $df$

<table><caption>**Table 1.** Results of mixed-effect models testing the effects of immersion time (Time), mesh size enclosures (Mesh) and leaf litter species (Sp) as well as interactions between these factors on bacterial abundance (Log10 of 16S rRNA gene copy number) and fungal abundance (Log10 of 18S rRNA gene copy number) at the surface of the leaf strips. Num Df: numerator degree of freedom, Den Df: denominator degree of freedom, F: Fisher's F value.</caption><thead><tr><th rowspan="2"></th><th colspan="4">Bacteria</th><th colspan="4">Fungi</th></tr><tr><th>Num Df</th><th>Den Df</th><th>F</th><th>P</th><th>Num Df</th><th>Den Df</th><th>F</th><th>P</th></tr></thead><tbody><tr><td>Mesh</td><td>1</td><td>48</td><td>2.20</td><td>0.2</td><td>1</td><td>48</td><td>1.85</td><td>0.2</td></tr><tr><td>Time</td><td>1</td><td>16</td><td>10.1</td><td>0.006</td><td>1</td><td>16</td><td>19.7</td><td>0.005</td></tr><tr><td>Sp</td><td>1</td><td>48</td><td>29.85</td><td>&lt;0.0001</td><td>1</td><td>48</td><td>52.27</td><td>&lt;0.0001</td></tr><tr><td>Mesh x Time</td><td>1</td><td>48</td><td>0.76</td><td>0.4</td><td>1</td><td>48</td><td>3.6</td><td>0.06</td></tr><tr><td>Mesh x Sp</td><td>1</td><td>48</td><td>0.06</td><td>0.8</td><td>1</td><td>48</td><td>0.01</td><td>0.9</td></tr><tr><td>Time x Sp</td><td>1</td><td>48</td><td>0.09</td><td>0.8</td><td>1</td><td>48</td><td>0.09</td><td>0.8</td></tr><tr><td>Mesh x Sp x Time</td><td>1</td><td>48</td><td>0.29</td><td>0.6</td><td>1</td><td>48</td><td>0.2</td><td>0.7</td></tr></tbody></table>
<figure><img src="image_4.png" /><figcaption>**Figure 2.** Bacterial (A) and fungal (B) abundances on leaf-litter at the different incubation times according to mesh size (coarse mesh, open symbols; fine mesh, closed symbols) for *P. insignis* (triangles) and *G. glabra* (circles). Values are expressed as log10 of 16S and 18S rRNA gene copy number for bacteria and fungi, respectively. Trend lines show polynomial linear smoothers and logarithmic smoother for *P. insignis* and *G. glabra* respectively, with solid lines for fine mesh and dashed lines for coarse mesh enclosures.</figcaption></figure>

= 5, P = 0.001; leaf-litter species: pseudoF = 2.20, df = 1, P = 0.005, Fig. S1 and S2, see online supplementary material). The highest differences between leaf-litter species were recorded at 7 days, with a higher contribution of Enterobacteriales on *P. insignis* (46.4%) compared with *G. glabra* (21.0%) although the genus *Pantoea* (Enterobacteriales) was dominant for both leaf litter species (Fig. 5). The relative contribution of Rhizobiales (Genus *Rhodomicrobium* and unclassified OTUs), Rhodocyclales (mainly an unclassified OTU of the Rhodocyclaceae family) and Lactobacillales (Genus *Lactococcus*) at 7 days was higher on *G. glabra* (16.2, 12.4 and 12.1% for Rhizobiales, Rhodocyclales and Lactobacillales, respectively) compared with *P. insignis* (7.9, 4.2 and 0.0%). For incubation times >7 days, the relative abundance of each dominant order displayed minor differences between *P. insignis* and *G. glabra* (Fig. 5). For both species, the Burkholderiales had a higher contribution between 7 and 28 days (11.6–34.8%) than between 56 and 224 days (2.4–6.8%) with a major contribution of the genus *Massilia* (Fig. 5C) forming up to 76% of the sequences assigned to the Burkholderiales and 9.9% of the total bacterial sequences. Other significant taxa included Rhodospirillales (0.7–9.3%, mainly the genus *Telmatospirillum*; Fig. 5F), Sphingomonadales (1.1–6.8%, an unclassified OTU and genera *Sphingomonas* and *Novosphingobium*), Myxococcales (0.1–5.4%, genus *Anaeromyxobacter*), Spirochaetales (0.3–6.3%, unclassified OTUs of the Family Spirochaetaceae) and Clostridiales (0.4–6.3%, genera *Sporobacter* and *Clostridium*) (Fig. S3, see online supplementary material). The contribution of non-dominant bacterial orders (i.e. orders that formed <5% of the total number of sequences at at least one of the incubation times) was the highest after 28 days of immersion for both leaf-litter species (Fig. 5). A large part of these sequences could not be affiliated to any characterized order. Non-affiliated taxa increased markedly according to time (Fig. 5H and Fig. S4, see online supplementary material).

## Presence of N-fixing bacteria

Amplification products of the target nifH gene were found in 100% of our samples (Fig. S5, see online supplementary material) indicating the ubiquity of N-fixing bacteria during the decomposition process of leaf litter in the bromeliad ecosystem. The

<table><caption>**Table 2.** Results of mixed-effect models testing the effects of immersion time (Time), mesh size enclosures (Mesh) and leaf litter species (Sp) on bacterial α-diversity (Invsimpson and Chao1 index). Num Df: numerator degree of freedom, Den Df: denominator degree of freedom, F: Fisher's F value.</caption><thead><tr><th></th><th>Num Df</th><th>Den Df</th><th>F</th><th>P</th></tr></thead><tbody><tr><td colspan="5"><strong>Invsimpson index</strong></td></tr><tr><td>Mesh</td><td>1</td><td>45</td><td>0.84</td><td>0.4</td></tr><tr><td>Time</td><td>1</td><td>16</td><td>21.78</td><td>0.0003</td></tr><tr><td>Sp</td><td>1</td><td>45</td><td>1.89</td><td>0.2</td></tr><tr><td>Mesh x Time</td><td>1</td><td>45</td><td>0.00</td><td>1</td></tr><tr><td>Mesh x Sp</td><td>1</td><td>45</td><td>2.10</td><td>0.2</td></tr><tr><td>Time x Sp</td><td>1</td><td>45</td><td>0.00</td><td>1</td></tr><tr><td>Mesh x Sp x Time</td><td>1</td><td>45</td><td>0.23</td><td>0.6</td></tr><tr><td colspan="5"><strong>Chao1 index</strong></td></tr><tr><td>Mesh</td><td>1</td><td>45</td><td>2.45</td><td>0.1</td></tr><tr><td>Time</td><td>1</td><td>16</td><td>13.434</td><td>0.002</td></tr><tr><td>Sp</td><td>1</td><td>45</td><td>2.94</td><td>0.09</td></tr><tr><td>Mesh x Time</td><td>1</td><td>45</td><td>4.61</td><td>0.04</td></tr><tr><td>Mesh x Sp</td><td>1</td><td>45</td><td>1.67</td><td>0.2</td></tr><tr><td>Time x Sp</td><td>1</td><td>45</td><td>0.04</td><td>0.8</td></tr><tr><td>Mesh x Sp x Time</td><td>1</td><td>45</td><td>0.08</td><td>0.8</td></tr></tbody></table>
<figure><img src="image_5.png" /><figcaption>**Figure 3.** Bacterial α-diversity (A: Invsimpson index, B: Chao1 richness index) at different incubation times according to mesh size (coarse mesh, open symbols; fine mesh, closed symbols) for *P. insignis* (triangles) and *G. glabra* (circles).</figcaption></figure>

intensity of the band fluorescence in the agarose gels was gen-
erally higher from 28 days of immersion, in parallel with the
increase in bacterial α-diversity (Fig. 3) and the relative abun-
dance of *Rhodomicrobium* and *Telmatospirillum* (Fig. 5F and G).

Network co-occurrence analysis

Comparisons of co-occurrence null models and co-occurrence
matrices of observed data did not reveal a random pattern
(95% confidence interval of the co-occurrence null model for G.
*glabra* 0.61–1.50, observed v-ratio of the co-occurrence matrix of
OTUs = 8.11; 95% confidence interval for P. insignis 0.56–1.57 and
observed v-ratio = 11.89). The microbial networks (Fig. 6) con-
sist of 87 nodes (OTUs) and 202 edges, and 100 nodes and 245
edges, representing the bacterial associations for G. glabra and P.
insignis, respectively. No clear temporal clustering was observed
for both leaf-litter species. OTUs with a maximal abundance at
112 days dominated the networks, representing 39 and 47% of
the nodes for G. glabra and P. insignis, respectively. Differences

in network characteristics (Table S2, see online supplementary
material) between bacterial communities of the two leaf-litter
species were low. Nodes for *P. insignis* were however more clus-
tered (average clustering coefficient: 0.277 for *P. insignis* and 0.090
for *G. glabra*) with more homogeneous numbers of short paths
that pass through them (centralization of stress centrality: 0.774
for *P. insignis* and 1.469 for *G. glabra*).

DISCUSSION

Based on the number of 16S and 18S rRNA gene copies, the abundances of bacteria and fungi increased significantly with time, with clear patterns according to leaf-litter identity. Values of both communities were continuously higher on *G. glabra* than on *P. insignis*, probably because of differences in the chemical composition of the leaves, with higher concentrations of recalcitrant materials in *P. insignis* (Table S1, see online supplementary material). The successional patterns of bacterial α-diversity were similar whatever the treatments, with a significant increase in the first 2 months of the succession and then stabilization over the time course. We also recorded well-defined patterns with gradual replacements of the dominant bacterial taxa along the time sequence, both at the order and genus/OTU taxonomic levels (Fig. 5 and Fig. S3, see online supplementary material). This trend fits the conceptual model of an exogenous heterotrophic succession as proposed by Fierer *et al.* (2010) and supports the role of resource limitations in driving microbial succession, much like existing theory that highlights nutrients as a control in plant succession (Vitousek *et al.* 1993; Chapin *et al.* 1994). Our study is also in agreement with a recent meta-analysis on bacterial primary succession patterns across various habitats that reported an increase in both taxonomic and functional diversity over the time sequence (Ortiz-Alvarez *et al.* 2018), highlighting that resource availability is a common process in the selection of microbial taxa during primary succession (Nemergut *et al.* 2016; Ortiz-Alvarez *et al.* 2018).

Leaf-litter identity has a mixed impact on successional pat-
terns of microbial communities. Bacterial and fungal abun-
dances, taxonomic turnover (phylogenetic β-diversity) and com-
munity composition of bacteria were significantly different
between leaf-litter species while bacterial α-diversity was not.
A substantial number of sequences belonging to the Lactobacil-
lales was recorded at 7 days on G. glabra only, but this differ-
ence in colonization did not affect inter-species difference in
α-diversity level, nor decomposition rates. Differences in taxo-
nomic composition of early colonizers in close, similar environ-
ments may be due to stochastic processes as expected by the-
ory (Hubbel 2001). Because G. glabra leaves had slightly lower
amounts of hemicellulose, cellulose and condensed tannin than
P. insignis leaves (Coq et al. 2010, Table S1), a more rapid colo-
nization on G. glabra leading to greater abundances of bacteria
including Lactobacillales could also be a possible explanation.
Newman, Liles and Feminella (2015) assessed the difference
in leaf breakdown and microbial succession between two leaf
species in a forest stream and found that the physicochemical
characteristics of leaf species influence the rate of leaf litter col-
onization by bacteria but play a minor role in structuring bacte-
rial assemblage. In addition, distinct litter-degrading bacteria in
bromeliads may be functionally similar (Louca et al. 2017), mak-
ing it difficult to disentangle the factors that drive the first steps
of microbial colonization and community assembly. Our results
clearly indicated that mesh size and the time x mesh size inter-
action did not significantly affect microbial abundances, bact-
terial community structure and litter decomposition. Microbial
<figure><img src="image_6.png" /><figcaption>**Figure 4.** Principal coordinate analysis (PCoA) of weighted UniFrac distances of bacterial communities. β-Diversity pattern is visualized as a plot of the first two PCoA axes (factors) showing the distribution of triplicate samples according to treatments (incubation time, colours; leaf litter species, symbol shapes; mesh size, open or closed symbols). P, *P. insignis*; G, *G. glabra*; C, coarse mesh size; F, fine mesh size.</figcaption></figure>

communities were not affected by the feeding activity of leaf-
shredder and -scraper invertebrates, probably because of their
very low density and biomass in bromeliads of French Guiana
(Table S3, see online supplementary material; see also Brouard
et al. 2012; Trzcinski et al. 2016). In agreement with our results,
recent studies found that microorganisms largely ensure leaf lit-
ter decomposition in tank bromeliads (see Rodríguez-Pérez et al.
2018 and LeCraw, Romero and Srivastava 2017 for decomposition
experiments in French Guiana and Brazil, respectively). Thus,
although leaf litter identity affects some structural parameters
of the microbial community, none of the treatments induced sig-
nificant change in bacterial α-diversity and decomposition rate.

According to the resource-ratio theory (Tilman 1985; Fierer
et al. 2010) changes in litter-associated bacteria reflect both the
various catabolic activities required for decomposition and the
interactions between species (i.e. competition or facilitation)
growing under limited resources. Accordingly, the early stage
of colonization was dominated by ubiquist taxa belonging to
Proteobacteria, with Pantoea (Gammaproteobacteria) and Mas-
silia (Betaproteobacteria) being the numerically dominant taxa
on both leaf litter species. These early colonizers were previously
found in temperate soils (Cleveland et al. 2007) and in the rhizo-
sphere (Ofek, Hadar and Minz 2012). The preferential association
of Pantoea and Massilia with soil enriched in labile compounds
(Pascault et al. 2010) and in the early stage of bacterial succes-
sion on leaf litter (this study; Kim et al. 2014) attests they act as
copiotrophs and are highly competitive when the labile pool of
organic matter is not depleted. Moreover, members of these two
genera are common constituents of the leaf phyllosphere across
a wide range of plant species (Rastogi, Coaker and Leveau 2013),
which could favour their early dominance in the first step of the

degradation. Their dominance in early decomposition of leaf lit-
ter in temperate environments and tropical forests (Kim et al.
2014; this study) suggests an important global significance.

We recorded the highest increase in bacterial α-diversity
from 14 to 56 days of immersion, along with a rise in bacterial
and fungal abundances. A high turnover in phylogenetic diver-
sity occurred simultaneously, leading to an important shift in
the relative dominance of bacterial orders from 56 days. This
change was characterized by a rise in the relative abundance
of Verrucomicrobia, Acidobacteria and numerous uncharacter-
ized taxa, while Enterobacteriales and Burkholderiales declined
sharply. Verrucomicrobia and Acidobacteria are recognized to
degrade complex polymers (Rawat et al. 2012). A significant con-
tribution of Rhizobiales and Rhodospirillales throughout the
time sequence was recorded for both leaf-litter species, suggest-
ing a key role of these Alphaproteobacteria during the decom-
position process. Members of Rhizobiales and Rhodospirillales
(Rhodomicrobium, Telmatospirillum; Fig. 5) are known for their
ability to fix atmospheric nitrogen (Lindstrom, Lewis and Pin-
sky 1951; Madigan, Cox and Stegeman 1984; Sizova et al. 2007)
and their significance in the bromeliad ecosystem is now doc-
umented (Goffredi, Kantor and Woodside 2011; Lehours et al.
2016). The results of our PCR on the nifH gene confirmed the pres-
ence of nitrogen-fixing bacteria throughout the time sequence in
all treatments (Fig. S5, see online supplementary material), and
the relative abundance of both Rhodomicrobium and Telmatospir-
ilium increase markedly from 56 days of immersion (Fig. 5F, 5G).
These bacteria could actually provide inorganic nitrogen to other
microorganisms living in the water tank, and to the bromeliad
itself for which nitrogen is an important limiting factor (Ngai and
Srivastava 2006; Leroy et al. 2016). The increase in the diversity
<figure><img src="image_7.png" /><figcaption>**Figure 5.** Relative abundance (% of 16S rRNA gene sequences) of order-level bacterial taxa at the different incubation times for (A) *G. glabra* and (B) *P. insignis*, and box plots of the dominant OTUs according to time (x-axis) and leaf identity (colours: red, *G. glabra*; blue, *P. insignis*) for (C) *Massilia* (Burkhoderiales, Betaproteobacteria), (D) *Lactococcus* (Lactobacillales, Bacilli), (E) *Pantoea* (Enterobacteriales, Gammaproteobacteria), (F) *Telmatospirillum* (Rhodospiralles, Alphaproteobacteria), (G) *Rhodomicrobium* (Rhizobiales, Alphaproteobacteria) and (H) unclassified taxa at the order level. Values on the y-axis of the box plots represent the proportion of sequences that the taxon contributes to per sample. Orders in (A) and (B) are represented in colour if their relative abundance is >5% at least one incubation time. Orders with relative abundance <5% are in grey and pooled in four main groups. The group 'Other Phyla' includes Actinobacteria, Bacteroidetes, Planctomycetes, Firmicutes, Armatimonadetes, Spirochaetes and eight phyla/candidate phyla.</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>**Figure 6.** Network co-occurrence diagram of Spearman correlations (edges) between the OTUs (nodes) for (A) *G. glabra* and (B) *P. insignis*. Positive correlations with P < 0.01 were considered (see Sequence analyses in Material and Methods for details). Nodes (= OTUs) are coloured according to the stage during the time sequence for which they exhibited their maximal abundance. Values in bracket are the contribution (%) of each node modality (incubation time) for *G. glabra* and *P. insignis*, respectively.</figcaption></figure>
of obligate anaerobic bacteria such as *Clostridium* and *Sporobacter* in the late colonization (224 days; Fig. S3, see online supplementary material) suggests the development of anoxic niches. The greater heterogeneity of the conditions on the leaf surface likely contributes to colonization by a more diverse range of bacteria. The replacement of characterized taxa by uncharacterized ones along the succession (Fig. S4, see online supplementary material) can be interpreted in the light of biases related to culture approaches. Indeed, isolation of new microorganism is intrinsically biased toward species that are less dependent on other members of the community and often rely on media containing concentrations of nutrients as well as energy and carbon sources considerably higher than in natural environments. This shift could thus reflect a replacement of species that are competitive at high labile carbon concentration by species that are more interdependent and more competitive for recalcitrant carbon and low nutrient availability.

The number, direction and strength of the relationships between taxa provide important information for understanding mechanisms of community assembly and ecosystem properties (Freilich et al. 2011). Co-occurrence patterns derived from network analysis were therefore used to reveal how interactions among OTUs and community complexity change according to leaf identity and time (see Barberan et al. 2012). An increase in community complexity is assumed to result from a strong time-driven niche partitioning, promoting species coexistence (McKane et al. 2002). It is also established that the multiplication of ecological niches during biofilm development results from an increase in the diversity of resources and habitat heterogeneity (Jackson 2003). Here, we found no clear increase in community complexity through time for both leaf-litter species, while we detected slight differences in the network metrics between leaf litter species (Table S2, see online supplementary material). For both leaf-litter species, the networks were largely dominated by OTUs with a maximal abundance at 112 days (Fig. 5) belonging to the putative N-fixing bacteria *Rhodomicrobium* and *Telmatospirillum* (Fig. 5F and G), thus indicating a key role of these taxa within the community. It is then likely that the coexistence of highly diverse taxa in the late stage of the succession could be the result of interdependence through cross-feeding (Pande and Kost 2017). The late colonizers of leaf litter could be auxotrophs, and/or dependent on factors produced by other members of the community for their growth when both labile compounds and physical support are becoming scarce. The highest richness at 112 and 224 days might result from interdependence between the numerous uncharacterized taxa and N-fixing bacteria that are able to alleviate nutrient limitation. In addition, interdependence through cross-feeding interactions is considered an important stabilizing factor of bacterial communities (Pande et al. 2014) and could explain the congruent stabilization of α-diversity with the increase in uncharacterized taxa from 56 days of immersion for both leaf-litter species. Finally, it is unlikely that competition between species would be an important mechanism of community assembly for these late colonizers, because competition generally leads to a decline in both diversity and complexity of the community (Ortiz-Alvarez et al. 2018). Also, bacteria probably interact with fungi during leaf litter decomposition (Tlaskal, Voriskova and Baldrian 2016) and wood decay (Kielak et al. 2016), presumably by providing essential nutrients (Purahong et al. 2016). This role is undoubtedly important in nutrient-limited ecosystems such as tank bromeliads (Leroy et al. 2016). Here, we found that the highest richness of bacteria at 112 and 224 days was also related to the highest abundance (i.e. number of genes

copies) of fungi, suggesting putative interactions between the two communities. This potential interdependence between bacteria and fungi during leaf decomposition in the bromeliad ecosystem should be clarified in future studies. Further research should also focus on the broad diversity of interactions between all the microorganisms during the succession, including bacteria, archaea, fungi and protists. Such a survey would be particularly relevant in detritus-based ecosystems such as tank bromeliads, where decomposition is mainly ensured by microorganisms.

## SUPPLEMENTARY DATA

Supplementary data are available at FEMSEC online.

## ACKNOWLEDGEMENTS

We thank the members of the *Laboratoire Environnement de Petit-Saut* (HYDRECO) for technical support and the use of their facilities, and M. Fichaux and F. Petitclerc (CNRS, UMR ECO-FOG, Kourou, French Guiana) for field assistance. We gratefully acknowledge the Plateforme Gentyane of the Institut National de la Recherche Agronomique (INRA, Clermont-Ferrand, France) for guidance and technical support. We are grateful to two anonymous reviewers for their helpful comments on a first version of the manuscript.

## FUNDING

This work was supported by the Agence Nationale de la Recherche throughout the Rainwebs project (grant number ANR-12-BSV7-0022-01) and an ‘Investissement d’Avenir’ (Labex CEBA, grant number ANR-10-LABX-25-01).

**Conflict of Interest.** None declared.

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