Long-term warming effects on the microbiome and nitrogen fixation associated with the moss Racomitrium lanuginosum in a subarctic alpine heathland
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* Ingeborg J. Klarenberg
* Christoph Keuschnig
* Ana J. Russi Colmenares
* Anne D. Jungblut
* Ingibjörg S. Jónsdóttir
* Oddur Vilhelmsson

## Abstract

Bacterial communities form the basis of biogeochemical processes and determine plant growth and health. Mosses, an abundant plant group in many Arctic ecosystems, harbour diverse bacterial communities that are for instance involved in nitrogen fixation. Global climate change is causing changes in aboveground plant biomass and shifting species composition in the Arctic, but little is known about the response of the moss microbiome. Here, we study the bacterial community associated with the moss *Racomitrium lanuginosum*, a common species in the Arctic, in a 20-year *in situ* warming experiment in an Icelandic heathland. We evaluate changes in bacterial community composition and diversity. Further, we assess the consequences of warming for *nifH* gene copy numbers and nitrogen fixation rates. Our findings indicate an increase in the relative abundance of Proteobacteria and a decrease in the relative abundance of Cyanobacteria and Acidobacteria with warming. The *nifH* gene copy number decreases, while the rate of nitrogen fixation is not affected. This contradiction could be explained by a shift in the nitrogen fixing bacterial community. Although climate warming might not change the contribution of *R. lanuginosum* to nitrogen input in nitrogen-limited ecosystems, the microbial community resilience and the nitrogen fixing taxa may shift.

## Introduction

Temperature in high-latitude regions is rising twice as fast as elsewhere [1], which has large impacts on Arctic ecosystems, for instance by altering species distributions and interactions among species [2, 3]. One such interaction that might be affected by warming is the interaction between mosses and their associated bacterial communities and related ecosystem processes.

Mosses comprise a large component of the vegetation in many high-latitude ecosystems and play important roles in biogeochemical cycles by forming a carbon (C) sink via their slow decomposition rates, by accounting for up to 7% of terrestrial net primary productivity and half of the terrestrial nitrogen (N2) fixation [4–8]. Most mosses consist of a upper living segment with photosynthetic tissue and a lower decaying dead segment and thus link above-ground and belowground processes [9]. They provide a habitat for a range of microbiota, micro- and mesofauna, which together with the alive and dead moss tissue have been defined as the ‘bryosphere’ [10]. Moss-associated microorganisms are involved in the decomposition of dead moss tissue and responsible for N2 fixation. N2 fixation by Cyanobacteria associated with mosses directly increases moss growth rates [11] and thereby controls C sequestration in moss tissues. These Cyanobacteria are also an important source of new available N in boreal and Arctic ecosystems [12, 13]. In order to understand the implications of climate change for the role of mosses in ecosystem C and N cycling, we need to understand how moss-associated microbial communities react to elevated temperatures.

The bacterial community composition of mosses is species specific and influenced by environmental factors such as pH and nutrient availability [14–16]. Bacterial associates can increase mosses survival and growth under extreme conditions [17], for instance by protecting moss tissue from freeze damage [18]. Commonly found phyla associated with mosses are Proteobacteria, Acidobacteria, Actinobacteria, Bacteroidetes, Armatimonadetes, Verrucomicrobia, Planctomycetes and Cyanobacteria [16, 19]. While Cyanobacteria have received most of the attention for their N2-fixing capability [11, 20–26], mosses harbour many other putative N2-fixing (diazotrophic) taxa such as members of the Alphaproteobacteria [14, 27–29]. The bacterial community composition of mosses has primarily been studied for peat and feather mosses, but we know little about the bacterial communities of other moss species.

N2 fixation rates of moss-associated diazotrophic bacteria can be expected to increase with temperature, as metabolic processes in microorganisms increase with temperature and the enzyme nitrogenase is more active at higher temperatures [30]. Temperature induced drought however, can inhibit N2 fixation rates, especially cyanobacterial N2 fixation [9, 24, 31–36]. Temperature effects on N2 fixation rates might also be influenced by physiological adaptation of diazotrophic communities, or shifts to a species composition better suited to the new conditions [31, 37, 38]. Despite the importance of microbial communities for plant functioning and ecosystem processes, the effect of warming on moss microbial communities has received little attention. Two studies describing warming related changes in peat moss bacterial community composition reported a decrease in overall bacterial and diazotrophic diversity with higher temperatures *in situ* and under laboratory conditions [39, 40]. Whether this warming induced decrease in diversity also holds for bacterial communities associated with other moss species in high latitudes is unknown. Moreover, long-term warming effects on moss-associated bacterial communities have yet to be explored.

In this study we investigated how two decades of experimental warming with open top chambers impact the bacterial community and N2 fixation rates associated with the moss *Racomitrium lanuginosum* (Hedw.) Brid in a subarctic-alpine dwarf shrub heath in northern Iceland. *R. lanuginosum* has a wide distribution at high altitudes in temperate regions of the Northern and Southern Hemisphere and at low altitudes in the Arctic [41]. Projected temperature increases for Iceland as a whole are estimated between 2.1 to 4.0 degrees °C by 2100 [42].

We assessed the bacterial community composition by 16S rRNA gene amplicon sequencing and we hypothesised (1) that long-term warming would reduce the bacterial richness and diversity and affect community composition as compared to non-warmed control plots. N2 fixation rates were measured with acetylene reduction assays (ARA) and N2 fixation potential was quantified by quantitative PCR (qPCR) of nitrogenase (*nifH*) genes. We hypothesised (2) that N2 fixation would be either positively or negatively influenced by long-term warming depending on the warming-induced changes in the abundance of potential N2-fixing taxa.

## Methods

### Field site

The sampling was conducted in permanent plots of a long-term warming simulation experiment, part of the International Tundra Experiment (ITEX), in northwest Iceland [43]. According to Köppen’s climate definitions, the sampling site, called Auðkúluheiði (65°16’N, 20°15’W, 480 m above sea level) is situated in the lower Arctic. The vegetation has been characterized as a relatively species-rich dwarf shrub heath, with *Betula nana* being the most dominant vascular species and the moss *R. lanuginosum* and the lichen *Cetraria islandica* as the dominating cryptogam species [44, 45]. The area has been fenced off since 1996 to prevent sheep from disturbing the experiment.

Ten open top plexiglass chambers (OTCs) were set up to simulate a warmer summer climate in August 1996 and 1997 [44, 46]. They raise the mean daily temperature during summer by 1-2 °C, and minimize secondary experimental effects such as differences in atmospheric gas concentration and reduction in ambient precipitation. Control plots were established next to the OTCs, but without any treatment, thus exposed to ambient temperatures.

### Acetylene reduction assays

For N2 fixation rate measurements, we collected three moss shoots of 5 cm length per control plot and OTC in June and August 2014. Acetylene reduction was used as a proxy for N2 fixation [47]. Moss shoots were acclimated in a growth chamber for 24 h at 10 °C and 200 μmol m−2 s−1 PAR. 10% of the headspace was replaced by acetylene. After an additional 72 h in the growth chamber under the same conditions, acetylene reduction and ethylene production were measured by gas chromatography.

### RNA and DNA extraction and sequencing

For RNA and DNA extraction we collected moss shoots in June 2017. Per warmed (OTC) and control plot, five shoots were collected with sterile tweezers. The samples were immediately soaked in RNAlater (Ambion) to prevent RNA degradation and kept cool until storage at −80 °C. Prior to extraction, the samples were rinsed with RNase free water to remove soil particles and RNAlater and ground for six minutes using a Mini-Beadbeater and two sterile steel beads. RNA and DNA were extracted simultaneously using the RNeasy PowerSoil Total RNA Kit (Qiagen) and the RNeasy PowerSoil DNA Elution Kit (Qiagen), following the manufacturer’s instructions. DNA and RNA concentrations were determined with a Qubit Fluorometer (Life Technologies) and quality was assessed with a nanodrop and bioanalyzer. cDNA was synthesized using the High-Capacity cDNA Reverse Transcription Kit (Thermofisher) following the manufacturer’s instructions and quantified on a Qubit Fluorometer. 48 DNA samples (24 from each treatment) and 48 cDNA samples (24 from each treatment) were sequenced. Library preparation and sequencing of the V3-V4 region of the 16S rRNA gene on an Illumina MiSeq platform was performed by Macrogen, Seoul, using the standard Illumina protocol and 16S rRNA gene V3-V4 primers.

### Sequence processing

In order to obtain high-resolution data and to better discriminate ecological patterns, we processed the raw sequences using the DADA2 pipeline [48, 49], which does not cluster sequences into operational taxonomic units (OTUs), but uses exact sequences or amplicon sequence variants (ASVs). Forward reads were truncated at 260 bp and reverse reads at 250 bp. Assembled ASVs were assigned taxonomy using the Ribosomal Database Project (RDP) naïve Bayesian classifier [50] in DADA2 and the SILVA_132 database [51]. We removed samples with less than 10.000 non chimeric sequences and we removed ASVs assigned to chloroplasts and mitochondria, singletons and ASVs abundant in only 1 sample. In total, for 85 samples, 3 598 ASVs remained. To account for uneven sequencing depths, the data were normalised using cumulative-sum scaling (CSS) [52]. The 16S rDNA based community is hereafter sometimes referred to as the ‘total bacterial community’ and the 16S rRNA (cDNA) based community is hereafter referred to as the ‘potentially metabolically active bacterial community’, acknowledging that 16S rRNA is not a direct indicator of activity but rather protein synthesis potential [53].

### Quantitative real-time PCR of nifH and 16S rRNA genes

We used all DNA extractions (50 replicates per treatment) for quantification of *nifH* and 16S rRNA genes, which was performed by quantitative PCR (Corbett Rotor-Gene) using the primer set PolF/PolR and 341F/534R respectively [54]. The specificity of the *nifH* primers for our samples was confirmed by SANGER sequencing of 10 clone fragments. Standards for *nifH* reactions were obtained by amplifying one cloned *nifH* sequence with flanking regions of the plasmid vector (TOPO TA cloning Kit, Invitrogen). Standard curves were obtained by serial dilutions (E = 0.9 – 1.1, R2 = > 0.99 for all reactions). Each reaction had a volume of 20 µL, containing 1x QuantiFast SYBR Green PCR Master Mix (Qiagen), 0.2 µL of each primer (10 µM), 0.8 µL BSA (5 µg/µL), 6.8 µL RNase free water and 2 µL template. The cycling program was 5 min at 95 °C, 30 cycles of 10 s at 95 °C and 30 s at 60 °C.

### Statistical analysis

Richness (number of ASVs) and Shannon diversity were calculated with the R packages ‘vegan’ [55] and ‘phyloseq’ [56]. Differences in N2 fixation rates, 16S rRNA and *nifH* gene abundance, ASV richness and Shannon diversity were assessed with MCMC generalised linear models using the R package ‘MCMCglmm’[57] with treatment as a fixed and plot as a random factor. The relative abundances between the warmed and the control samples were tested using Wilcoxon rank sum tests on plot averages.

Distances between the community composition of the control and OTC samples were based on Bray-Curtis distances. The warming effect of the OTCs on the bacterial community composition was tested by permutational-MANOVA (PERMANOVA) [58] analysis of the Bray-Curtis distance matrices using the *adonis* function in the R package ‘vegan’ with plot as a random factor. Principal coordinate analysis was used to ordinate the Bray-Curtis distance matrices and to visualise the relationships between samples from OTC and control plots.

Two methods were used to determine taxa sensitive to warming. First, differential abundance of bacterial genera between warmed and control samples was assessed using the DESeq2 procedure [59] on the non-CSS normalised datasets with the R package ‘DESeq2’ [59]. The adjusted *p*-value cut-off was 0.1 [59]. Differential abundance analysis only uses ASVs present in both the OTC and control samples. The second method we used to find taxa sensitive to warming, was the indicator species analysis. To find bacterial taxa indicative for the warming or the control treatment, correlation-based indicator species analysis was done with all possible site combinations using the function *multipatt* of the R package ‘indicSpecies’ [60] based on 103 permutations. The indicator species analysis takes into account ASVs present in both OTC and control samples, but also ASVs present in only one of the treatments. We combined results of the DESeq2 and indicator species analysis for a final list of ASVs sensitive to warming.

## Results

### Treatment effect on bacterial richness and diversity

The richness and Shannon diversity of the DNA and cDNA based bacterial communitues did not differ significantly between control and OTC samples (Figure 1). However, the ASV abundance the phylum Acidobacteria and the class Gammaproteobacteria showed significant differences between the control and OTC samples (Figure 1). The Shannon diversity of Gammaproteobacteria (which include the order Betaproteobacteriales) was higher in the warmed samples for both the DNA (p = 0.072) and cDNA based bacterial communities. The richness of Acidobacteria was significantly lower in the warmed samples for both the cDNA based bacterial communities. The Shannon diversity of Acidobacteria was lower (p = 0.096) in the warmed samples of the cDNA based bacterial communities.

![Figure 1](http://biorxiv.org/https://www.biorxiv.org/content/biorxiv/early/2019/11/12/838581/F1.medium.gif)

[Figure 1](http://biorxiv.org/content/early/2019/11/12/838581/F1)

Figure 1 
Bacterial ASV (amplicon sequence variant) richness (Observed) and Shannon diversity of DNA and RNA derived bacterial communities associated with the moss *R. lanuginosum*, with control samples in white and OTC or warmed samples in red. Total richness and diversity as well as phyla and classes with significant differences between the treatments are shown. Boxplots represent minimum values, first quartiles, medians, third quartiles and maximum values. Significance levels: * < 0.05, ** < 0.01.

### Treatment effects on bacterial community composition

No strong treatment specific clustering of the bacterial community composition could be observed in PCoA plots, although they showed some divergence between the control and the warmed samples (Figure S1). This divergence was reflected in the MANOVA permutation test of the Bray-Curtis dissimilarity: treatments significantly influenced the DNA and the cDNA based community compositions of the moss (DNA: R2 = 0.05 and P < 0.001 and cDNA: R2 = 0.04 and P < 0.001).

When looking only at the potential diazotrophic community composition, the control and warmed communities were significantly different, both for the DNA and the cDNA. The treatment explained more variation of the DNA derived diazotrophic communities than the cDNA derived diazotrophic community and the total cDNA and DNA derived bacterial communities (PERMANOVA: DNA: R2 = 0.08 and P < 0.001 and cDNA: R2 = 0.04 and P = 0.002).

### Taxonomic composition of control and OTC communities

In the control samples, where bacterial communities were under ambient environmental conditions, the most abundant phyla made up 97% of the total abundance of ASVs and included Proteobacteria (44% average relative abundance across all control DNA samples), followed by Acidobacteria (29%), Actinobacteria (8%), Cyanobacteria (7%), Planctomycetes (4%), Bacteroidetes (4%), Verrucomicrobia (2%) and Armatimonadetes (2%) (Figure 2A). The most abundant Proteobacterial class were Alphaproteobacteria (29%) (Figure 2B). Acetobacterales (15%), Myxococcales (12%), Caulobacterales (6%) and Rhizobiales (6%) were the most common orders of the Proteobacteria (Figure S2). The order Acetobacterales was dominated by the genus *Acidiphilium* (5%), the order Myxococcales was dominated by the genus *Haliangium* (4%). The order Rhizobiales was mainly represented by the genera *Nitrobacter* (0.08%) and *1174-901-12* (2%). The Acidobacteria were dominated by the orders Acidobacteriales (17%) and Solibacterales (11%) (Figure S2). The Acidobacteriales were dominated by the genus *Granulicella* (11%). The Solibacterales were dominated by the genera *Bryobacter* (5%) and *Ca*. *Solibacter* (6%). Actinobacteria mainly comprised the orders Solirubrobacterales (5%) and Frankiales (2%) (Figure S2). The genera *Jatrophihabitans* (1%), *Acidothermus* (0.05%) and *Nakamurella* (0.02%) accounted for the largest share of the order Frankiales. Planctomycetes were dominated by the orders Isosphaerales (1%) and Tepidisphaerales (2%) (Figure S2). The orders Fimbriimonadales (0.03%) and Chthonomonadales (1%) dominated the phylum Armatimonadetes (Figure S2). The phylum Bacteroidetes was dominated by the orders Chitinophagales (3%) and Sphingobacteriales (0.7%) (Figure S2). Chthoniobacterales (2%) was the most abundant order within the phylum Verrucomicrobia. Cyanobacteria were dominated by the genera *Nostoc* (5%) and *Stigonema* (1%).

![Figure 2](http://biorxiv.org/https://www.biorxiv.org/content/biorxiv/early/2019/11/12/838581/F2.medium.gif)

[Figure 2](http://biorxiv.org/content/early/2019/11/12/838581/F2)

Figure 2 
Boxplots of the relative abundances of (A) Phyla, (B) Classes and (C) potential nitrogen fixing taxa on phylum level in DNA and cDNA based bacterial communities associated with the moss *R. lanuginosum*. Controls are shown in white and OTC (warmed) samples are shown in red. Boxplots represent minimum values, first quartiles, medians, third quartiles and maximum values. Significance levels (* < 0.05, ** < 0.01, \***| < 0.001) are based on Wilcoxon rank sum tests.

We compared the relative abundances of taxa on phylum, class and order level in the control with the warmed samples from the OTC (Figure 2 and Figure S2). Acidobacteria, Gemmatimonadetes and Cyanobacteria decreased in relative abundance, while Proteobacteria increased in relative abundance in the DNA based bacterial communities (Figure 2A). No significant changes were detected in the cDNA based bacterial communities on phylum level. On class level, Acidobacteriia, Gemmatimonadetes and Oxyphotobacteria decreased relative abundance in the DNA based bacterial communities and Gammaproteobacteria increased in relative abundance in the DNA and the cDNA based bacterial communities (Figure 2B). On order level Betaproteobacteriales and Micrococcales were higher in relative abundance for the warmed DNA and cDNA based bacterial communities (Figure S2). Acidobacteriales had a lower relative abundance in the warmed DNA and cDNA based bacterial communities (Figure S2). In addition, in the DNA based bacterial communities, Sphingobacterales and Cytophagales increased in relative abundance under warming, while Nostocales decreased under warming. In the cDNA based bacterial communities, the orders Sphingomonadales and Rhizobiales increased in relative abundance under warming, while Acetobacterales decreased in relative abundance under warming (Figure S2).

The relative abundance of potential diazotrophic Proteobacteria was higher in the warmed plots than in the control plots for both the DNA and cDNA based bacterial communities (Figure 2C). Cyanobacteria in the DNA based bacterial communities had a lower relative abundance in the warmed plots (Figure 2C).

### Treatment related shifts in the relative abundance of ASVs

The DESeq2 differential abundance analysis showed that 33 ASVs were differentially abundant in the DNA based moss bacterial communities, of which 28 ASVs were significantly enriched in the control samples and 5 ASVs were significantly enriched in the warmed samples (Table S1). The indicator species analysis revealed 122 ASVs indicative for the control plots (Table S1). 23 ASVs were found indicative for the warmed plots (Table S1). The strongest indicator species for the control plots corresponded to the taxa that were less abundant in the warmed plots according the Deseq2 analysis. DESeq2 and indicator species analysis combined revealed 23 ASVs higher in relative abundance under warming and 122 ASVs with higher relative abundance in the controls (Table S1).

For the bacterial communities in the DNA based analysis, ASVs with increased relative abundance in the warmed samples belonged to the genera *Allorhizobium*-*Neorhizobium*-*Pararhizobium*-*Rhizobium, Nitrobacter* (Alphaproteobacteria) and *Galbitalea* (Actinobacteria). ASVs with increased relative abundance in the controls belonged to the genera *Acidipila*, *Bryocella*, *Bryobacter*, *Candiatus Solibacter, Granulicella* (Acidobacteria), *Acidiphilium*, *Endobacter* and *Bradyrhizobium* (Alphaproteobacteria), *Nostoc* (Cyanobacteria) and *Conexibacter* (Actinobacteria) (Figure 3 and Table 1).

![Figure 3](http://biorxiv.org/https://www.biorxiv.org/content/biorxiv/early/2019/11/12/838581/F3.medium.gif)

[Figure 3](http://biorxiv.org/content/early/2019/11/12/838581/F3)

Figure 3 
Number of ASVs (amplicon sequence variants) per genus sensitive to warming for DNA and CDNA based bacterial communities associated with the moss *R. lanuginosum*. Sensitivity was determined by differential abundance analysis (DESeq2) and indicator species analysis. ASVs not assigned to genus level are called ‘NA’. The number of ASVs indicative for the OTC (warmed) treatment is indicated in red and the number of ASVs indicative for the control treatment in indicated in white. Note that a division was made between non N2-fixing and N2-fixing taxa.

For the bacterial communities in cDNA based analysis, indicator species analysis revealed 51 potentially active ASVs indicative for the control plots and 14 potentially active ASVs indicative for the warmed plots (Figure 3, Table S2). DESeq2 detected 3 ASVs with a higher relative abundance in the control plots. ASVs more abundant in the control plots belonged to the genera *Acidipila*, *Bryocella*, *Granulicella* (Acidobacteria), *Nostoc* (Cyanobacteria) and *Acidiphilium* (Alphaproteobacteria). ASVs more abundant under warming belonged to the genera *Allorhizobium*-*Neorhizobium*-*Pararhizobium*-*Nitrobacter*, *Sphingomonas* (Alphaproteobacteria), *Galbitalea* (Actinobacteria) and *Rhizobacter* (Gammaproteobacteria) (Figure 3, Table S2).

### Treatment effect on 16S rRNA gene and nifH gene copy numbers and nitrogen fixation rates

We did not find any differences between N2 fixation in the control and warmed plots in June or August 2014 (Figure 4A), but N2 fixation in August was significantly lower (Wilcoxon rank sum test, p = < 0.0002) than in June (Figure 4A). No significant difference was found in the 16S rRNA gene copy number per ng of DNA between the control and warmed samples (Figure 4B). The *nifH* gene copy number per ng DNA was similar in the warmed and control samples (Figure 4C). However, *nifH* copy numbers in the warmed samples were significantly lower when expressing the *nifH* gene copy number per 16S rRNA gene copy (Figure 4D).

![Figure 4](http://biorxiv.org/https://www.biorxiv.org/content/biorxiv/early/2019/11/12/838581/F4.medium.gif)

[Figure 4](http://biorxiv.org/content/early/2019/11/12/838581/F4)

Figure 4 
Boxplots of (A) acetylene reduction rates (µmol C2H2 g−1 day−1) in June and August 2014, (B) 16S rRNA gene copy numers per ng DNA, (C) nifH gene copy number per ng DNA and (D) nifH gene copy number relative to 16S rRNA gene copy number in *R. lanuginosum* samples from control (in white) and warmed (in red) treatments. Boxplots represent minimum values, first quartiles, medians, third quartiles and maximum values.

## Discussion

Mosses form an important C and N sink in high latitudes, and their associated bacterial communities are to a large extent responsible for N inputs and organic matter decomposition in these environments. Elucidation of the effect of climate change on moss-associated bacterial communities will help to predict the C and N cycling driven by the bacterial component of the bryosphere in high latitude ecosystems. We assessed the effect of long-term (20 years) warming by open-top chambers (OTCs) on bacterial communities associated with the moss *R. lanuginosum* by comparing richness and diversity, community structure, taxonomic composition, N2 fixation rates *nifH* gene abundance, in control and warmed moss samples. Overall our results suggest that moss-associated bacterial communities are sensitive to long-term experimental warming.

### Effect of warming on the moss associated bacterial community structure

While the overall ASV richness and Shannon diversity of the total community was not significantly affected by the 20 years of warming as compared to the non-warmed controls, when assessed for individual phyla and classes, significant differences emerged for both the total and potentially metabolically active bacterial communities. Specifically, richness and diversity increased under warming for Gammaproteobacteria (including Betaproteobacteriales), whereas both richness and diversity of Acidobacteria decreased. These results contrast with our hypothesis and with trends of decreasing richness and diversity in *Sphagnum* moss observed by Carrell et al. (2017) and by Kolton et al. (2019). *R. lanuginosum* has a much lower water holding capacity than *Sphagnum* and grows in heathlands and therefore *R. lanuginosum* might react differently to warming. In addition, while our study describes the effect of 20 years warming *in situ*, those previous studies on *Sphagnum* were much shorter such as a four week laboratory [39] and one year *in situ* experimental warming study [40]. Long-term warming studies on soils have yielded various results ranging from a change in bacterial community structure in temperate forest soils [61], no effect on the microbial community structure in a sub-arctic peatland [62] to changes in the microbial community composition of soils in a subarctic heath and an arctic soil [63, 64]. In our study, the effect of warming on the moss bacterial community characterized by shifts in selected taxa.

Warming correlates with an increase in vascular plant canopy height and litter abundance and a decrease in bryophyte abundance [44]. In fact, in the OTC treatment, moss layer thickness was lower and soil organic matter content was higher, and a trend towards lower soil moisture was found compared to the controls [44, 65]. Temperature-induced changes in the amount of litter, surrounding plant species composition, moss traits such as leaf nutrient content, soil organic matter content and soil moisture are environmental factors that could potentially influence the moss bacterial community composition [66–68]. The large amount of unexplained variation in the bacterial community structure might thus be due to small-scale variation in moisture content, nutrient availability, temperature and shading of vascular plants.

Furthermore, bacterial communities and thereby their potential functions can be controlled by top-down factors such as predation which might change with the effects of long-term warming [69–72]. For instance, in a sub-Arctic peatland, year-round warming led to an increase in richness of the decomposing and fungivory oribatid mites, as well as a decrease in abundance of the predatory mesostigmatid mites [73]. While these mite taxa not necessarily feed on bacteria, it illustrates that foodwebs within the bryosphere are affected by warming. Micro- and mesofauna might also act as a source and distribution mechanism of bryophyte-associated bacteria [74]. The candidate genus *Xiphinematobacter* in our study is for instance likely to be nematode-born [75], but was not affected in relative abundance by warming in our study. Further studies could elucidate whether top-down controls via trophic cascades affect the moss bacterial community structure and whether warming induced changes at higher trophic levels could influence for example N2 fixation rates in *R. lanuginosum*, as has already been demonstrated for *Sphagnum* [69].

### Effect of warming on moss-associated bacterial taxa

We analysed changes in relative abundances in several ways to better understand the warming response of the moss bacterial community. This revealed changes in the relative abundances of taxa on all taxonomic levels. Shifts in individual taxa can affect microbe-microbe and microbe-host interactions and possibly alter functionality or stability of the moss-associated bacterial communities and affect host health and ecosystem functioning [76–78]. Plants might be able to shape their microbial communities [79, 80] to increase their tolerance to stress like drought [81] or nitrogen limitation [82, 83]. Many of the taxa responding to warming in our study are potentially plant-growth promoting, such as Rhizobiales.

The response of bacterial taxa to disturbances has been proposed to be due to specific traits or their life-histories. Several life strategy conceptual frameworks have been proposed for microbial organisms, such as the r-K-spectrum, where *r* strategists or copiotrophs have high growth rates and low substrate affinities and oligotrophs or *K* strategists low growth rates and high resource use efficiency [84, 85]. As the warming treatment was been in place for 20 years at the time of sampling, it is a press or long-term disturbance leading slowly to a different system with more nutrients available. The average relative abundance of Proteobacteria increased with warming and most proteobacterial indicator species were indicative for warming. Alphaproteobacteria showed multiple types of responses to warming. The positive effect of warming on Alphaproteobacteria has been linked to a copiotrophic growth strategy and dynamic response of this phylum to increasing substrate concentrations [84, 86–88]. The N2 fixing order Rhizobiales was more abundant under warming in our study, which has also been found in soils [61, 89], but not in peat mosses [40]. Negative responses of Alphaproteobacteria to warming might be due to certain taxa having a more oligotrophic lifestyle, such as members of the Caulobacteraceae that were more often indicative for ambient conditions in the controls than for warming. The Gammaproteobacteria (which include the order Betaproteobacteriales) increased relative abundance and in richness, but only one ASV indicative of warming was detected, an ASV that was classified as *Rhizobacter*. The phylum Acidobacteria decreased in relative abundance under warming. Acidobacteria are adapted to a wide range of temperatures in tundra soils [90] and its members have shown either negative or positive responses in warming experiments. Negative responses of Acidobacteria to increasing temperatures have been linked to their more oligotrophic lifestyle and inability to compete with more copiothrophic species in nutrient richer conditions resulting from the warming field conditions [84, 87, 88, 91].

*K* strategists have been hypothesized to be more resistant but less resilient to climate change related pulse disturbance than *r* strategists [85], if on the long-term resources may become limited [92]. Our results show an increase in copiotrophic taxa or *r* strategists and decrease in oligotrophic taxa or *K* strategists, probably because resources are not limited in the warmed conditions but rather more diverse due to an increase in vascular plant biomass and litter types. This also suggests that the bacterial communities under warming that are characterised by a decrease in *K* strategists, are less resistant and more resilient to short-term or pulse disturbances such as drought. In other words, a future short-term disturbance will potentially have a bigger impact on the bacterial community under warming, but the warmed bacterial community has more potential return to its original state before the disturbance than the control bacterial community.

### Implications of warming for the nitrogen-fixing moss microbiome in the Arctic

The second hypothesis we tested was that N2-fixing communities differ in species composition in the warmed plots compared to the control plots. Indeed, overall the relative abundance of Cyanobacteria decreased, and in particular the genus *Nostoc*. In a study on the effect of warming on peat moss microbiomes by Carell et al. [40], the relative abundance of Cyanobacteria decreased as well, but the relative abundance of *Nostoc* increased, potentially because peat mosses and the *R. lanuginosum* are typical for very different ecosystems (moist peat bogs versus dry tundra heath), and compared to our study they used up to 9 °C of warming. The other Cyanobacterial genus in our study, *Stigonema*, was not affected by warming. Patova et al. [94] found *Nostoc* in biological soil crusts in wet habitats and *Stigonema* in biological soil crusts in drier habitats. A difference in drought tolerance might thus explain the different response to warming between *Stigonema* and *Nostoc* in our study, since the OTCs generally decrease soil moisture [65]. Moss-associated *Stigonema* was also found to be more abundant than *Nostoc* in older sites with more developed soils, dwarf shrubs and forests during primary succession [94], so the decrease in *Nostoc* in our study could also be due to the richer conditions.

*Stigonema* has been suggested to be a more efficient N2-fixer than *Nostoc* associated with boreal forest feathermosses, because it was responsible for most of the N2 fixation while being less abundant than *Nostoc* [22]. Interestingly, while N2 fixation rates were not affected by the warming, the *nifH* gene abundance was lower under warming. While we cannot rule out yearly variations in the difference between control and warmed N2 fixation rates or diazotrophic communities, this suggests that *Nostoc* might not add much to N2 fixation and that *Stigonema* or other non-cyanobacterial diazotrophs are responsible for the N2 fixation. The decrease in *nifH* gene copy numbers could also be due to a difference in *nifH* gene copies in the genomes of the taxa present in the control plots and the warmed plots, or because these taxa possess multiple genomes [95]. An overlooked nitrogenase is the ‘alternative’ nitrogenase that uses vanadium (V) instead of molybdenum (Mo) as the most common nitrogenase (*nifH*) does [96]. Plant and lichen cyanobionts often possess this V-nitrogenase gene (*vnf*) [96, 97] and it has been suggested that it performs better at lower temperatures [98]. Our qPCR did not target the *vnf* gene, but it is possible that the presence of this gene influenced the acetylene reduction assays. Our results suggest that long-term warming can shift nitrogen fixing taxa with potential effects for N2 fixation rates.

Our study is among the first to assess the effect of long-term (20 years) experimental warming with OTCs on the bacterial part of a moss microbiome. Here we focussed on the moss *R. lanuginosum*, in a sub-Arctic-alpine dwarf shrub heath in Iceland. We observed an increase in the relative abundance of Proteobacteria, and a decrease in the relative abundance of Acidobacteria, probably due to their different life strategies (copiotrophic versus oligotrophic) that reflect warming-induced changes in nutrient availability. Our results also show that long-term warming leads to a shift in cyanobacterial genera, from *Nostoc* to *Stigonema* dominated and a decrease in the relative abundance of Cyanobacteria. At the same time, the *nifH* gene abundance tended to be lower under warming, while the N2 fixation rates did not differ. The bacterial community of the moss *R*. *lanuginosum* might thus be sensitive to future warming, with potential implications for moss growth, C sequestration, and N2 fixation rates.

## Supporting information

Supplementary Figure 1 [[supplements/838581_file02.tif]](pending:yes)

Supplementary Figure 2 [[supplements/838581_file03.tif]](pending:yes)

Supplementary Table 1 [[supplements/838581_file04.xlsx]](pending:yes)

Supplementary Table 2 [[supplements/838581_file05.xlsx]](pending:yes)

## Competing Interests

None.

**Supplementary Figure 1** Principal coordinate analysis (PCoA) of weighted Bray-Burtis distances between warmed and control 16S rDNA (A) and 16S rRNA based relative OTU abundance matrices (B) of the moss *R. lanuginosum*. Warmed samples are represented as black circles and control samples as grey circles.

**Supplementary Figure 2** Boxplots of the relative abundances of orders in DNA and cDNA based bacterial communities. Controls are shown in white and OTC (warmed) samples are shown in red. Boxplots represent minimum values, first quartiles, medians, third quartiles and maximum values. Significance levels (* < 0.05, ** < 0.01, \***| < 0.001) are based on Wilcoxon rank sum tests.

## Tables

**Supplementary Table 1** List of DESeq2 and indicator species for the warmed and the control conditions of the DNA based bacterial communities,. xlsx

**Supplementary Table 2** List of DESeq2 and indicator species for the warmed and the control conditions of the cDNA based bacterial communities,. xlsx

## Acknowledgements

We thank Dr. Ólafur S. Andrésson, Dr. Marie-Charlotte Nilsson and Dr. Matthias Zielke for help and advice on the RNA and DNA extractions and the ARAs. We would also like to thank Quentin J.B. Horta-Lacueva and Dr. Denis Warshan for advice on the statistical analysis. This work was funded by the MicroArctic Innovative Training Network grant supported by the European Commissions’s Horizon 2020 Marie Sklodowska-Curie Actions program under project number 675546.

*   Received November 12, 2019.
*   Revision received November 12, 2019.
*   Accepted November 12, 2019.


*   © 2019, Posted by Cold Spring Harbor Laboratory

This pre-print is available under a Creative Commons License (Attribution-NonCommercial-NoDerivs 4.0 International), CC BY-NC-ND 4.0, as described at [http://creativecommons.org/licenses/by-nc-nd/4.0/](http://creativecommons.org/licenses/by-nc-nd/4.0/)

## References

1.  1.IPCC. Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC). 2019.
    
    

2.  2.Wookey PA, Aerts R, Bardgett RD, Baptist F, Bråthen KA, Cornelissen JHC, et al. Ecosystem feedbacks and cascade processes: understanding their role in the responses of Arctic and alpine ecosystems to environmental change. Glob Change Biol 2009; 15: 1153–1172.
    
    

3.  3.Van der Putten WH. Climate Change, Aboveground-Belowground Interactions, and Species’ Range Shifts. Annu Rev Ecol Evol Syst 2012; 43: 365–383.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1146/annurev-ecolsys-110411-160423&link_type=DOI) 

4.  4.Cornelissen JHC, Lang SI, Soudzilovskaia NA, During HJ. Comparative Cryptogam Ecology: A Review of Bryophyte and Lichen Traits that Drive Biogeochemistry. Ann Bot 2007; 99: 987–1001.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1093/aob/mcm030&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=17353205&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 

5.  5.Turetsky MR. The Role of Bryophytes in Carbon and Nitrogen Cycling. The Bryologist 2003; 106: 395–409.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1639/05&link_type=DOI) 

6.  6.Turetsky MR, Bond-Lamberty B, Euskirchen E, Talbot J, Frolking S, McGuire AD, et al. The resilience and functional role of moss in boreal and arctic ecosystems: Tansley review. New Phytol 2012; 196: 49–67.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/j.1469-8137.2012.04254.x&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=22924403&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000308090000006&link_type=ISI) 

7.  7.Elbert W, Weber B, Burrows S, Steinkamp J, Büdel B, Andreae MO, et al. Contribution of cryptogamic covers to the global cycles of carbon and nitrogen. Nat Geosci 2012; 5: 459–462.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1038/ngeo1486&link_type=DOI) 

8.  8.Porada P, Weber B, Elbert W, Pöschl U, Kleidon A. Estimating global carbon uptake by lichens and bryophytes with a process-based model. Biogeosciences 2013; 10: 6989–7033.
    
    

9.  9.Whiteley JA, Gonzalez A. Biotic nitrogen fixation in the bryosphere is inhibited more by drought than warming. Oecologia 2016; 181: 1243–1258.
    
    

10. 10.Lindo Z, Gonzalez A. The Bryosphere: An Integral and Influential Component of the Earth’s Biosphere. Ecosystems 2010; 13: 612–627.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1007/s10021-010-9336-3&link_type=DOI) 

11. 11.Berg A, Danielsson Å, Svensson BH. Transfer of fixed-N from N2-fixing cyanobacteria associated with the moss Sphagnum riparium results in enhanced growth of the moss. Plant Soil 2013; 362: 271–278.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1007/s11104-012-1278-4&link_type=DOI) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000312729400021&link_type=ISI) 

12. 12.DeLuca TH, Zackrisson O, Nilsson M-C, Sellstedt A. Quantifying nitrogen-fixation in feather moss carpets of boreal forests. Nature 2002; 419: 917–920.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1038/nature01051&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=12410308&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000178909700041&link_type=ISI) 

13. 13.Rousk K, Sorensen PL, Michelsen A. Nitrogen fixation in the High Arctic: a source of ‘new’ nitrogen? Biogeochemistry 2017; 136: 213–222.
    
    

14. 14.Holland-Moritz H, Stuart J, Lewis LR, Miller S, Mack MC, McDaniel SF, et al. Novel bacterial lineages associated with boreal moss species. Environ Microbiol 2018; 20: 2625–2638.
    
    

15. 15.Bragina A, Berg C, Cardinale M, Shcherbakov A, Chebotar V, Berg G. Sphagnum mosses harbour highly specific bacterial diversity during their whole lifecycle. ISME J 2012; 6: 802–813.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1038/ismej.2011.151&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=22094342&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000301945500010&link_type=ISI) 

16. 16.Tang JY, Ma J, Li XD, Li YH. Illumina sequencing-based community analysis of bacteria associated with different bryophytes collected from Tibet, China. BMC Microbiol 2016; 16.
    
    

17. 17.Bragina A, Oberauner-Wappis L, Zachow C, Halwachs B, Thallinger GG, Müller H, et al. The Sphagnum microbiome supports bog ecosystem functioning under extreme conditions. Mol Ecol 2014; 23: 4498–4510.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/mec.12885&link_type=DOI) 

18. 18.Raymond JA. Dependence on epiphytic bacteria for freezing protection in an Antarctic moss, *Bryum argenteum*: Epiphytic bacteria on an Antarctic moss. Environ Microbiol Rep 2016; 8: 14–19.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/1758-2229.12337&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=26417678&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 

19. 19.Kostka JE, Weston DJ, Glass JB, Lilleskov EA, Shaw AJ, Turetsky MR. The *Sphagnum* microbiome: new insights from an ancient plant lineage. New Phytol 2016; 211: 57–64.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/nph.13993&link_type=DOI) 

20. 20.Lindo Z, Nilsson M-C, Gundale MJ. Bryophyte-cyanobacteria associations as regulators of the northern latitude carbon balance in response to global change. Glob Change Biol 2013; 19: 2022–2035.
    
    

21. 21.Gentili F. Physiological and molecular diversity of feather moss associative N2-fixing cyanobacteria. J Exp Bot 2005; 56: 3121–3127.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1093/jxb/eri309&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=16263908&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000233491300011&link_type=ISI) 

22. 22.Warshan D, Bay G, Nahar N, Wardle DA, Nilsson M-C, Rasmussen U. Seasonal variation in nifH abundance and expression of cyanobacterial communities associated with boreal feather mosses. ISME J 2016; 10: 2198.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1038/ismej.2016.17&link_type=DOI) 

23. 23.Warshan D, Espinoza JL, Stuart RK, Richter RA, Kim S-Y, Shapiro N, et al. Feathermoss and epiphytic Nostoc cooperate differently: expanding the spectrum of plant–cyanobacteria symbiosis. ISME J 2017; 11: 2821–2833.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1038/ismej.2017.134&link_type=DOI) 

24. 24.Stewart KJ, Lamb EG, Coxson DS, Siciliano SD. Bryophyte-cyanobacterial associations as a key factor in N2-fixation across the Canadian Arctic. Plant Soil 2011; 344: 335–346.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1007/s11104-011-0750-x&link_type=DOI) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000291654600022&link_type=ISI) 

25. 25.Ininbergs K, Bay G, Rasmussen U, Wardle DA, Nilsson M-C. Composition and diversity of nifH genes of nitrogen-fixing cyanobacteria associated with boreal forest feather mosses. New Phytol 2011; 192: 507–517.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/j.1469-8137.2011.03809.x&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=21714790&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 

26. 26.Rousk K, Jones DL, DeLuca TH. Moss-cyanobacteria associations as biogenic sources of nitrogen in boreal forest ecosystems. Front Microbiol 2013; 4.
    
    

27. 27.Bragina A, Maier S, Berg C, Müller H, Chobot V, Hadacek F, et al. Similar Diversity of Alphaproteobacteria and Nitrogenase Gene Amplicons on Two Related Sphagnum Mosses. Front Microbiol 2012; 2.
    
    

28. 28.Leppänen SM, Rissanen AJ, Tiirola M. Nitrogen fixation in Sphagnum mosses is affected by moss species and water table level. Plant Soil 2015; 389: 185–196.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1007/s11104-014-2356-6&link_type=DOI) 

29. 29.Warren MJ, Lin X, Gaby JC, Kretz CB, Kolton M, Morton PL, et al. Molybdenum-Based Diazotrophy in a Sphagnum Peatland in Northern Minnesota. Appl Environ Microbiol 2017; 83: e01174–17.
    
    

30. 30.Houlton BZ, Wang Y-P, Vitousek PM, Field CB. A unifying framework for dinitrogen fixation in the terrestrial biosphere. Nature 2008; 454: 327–330.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1038/nature07028&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=18563086&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000257665300037&link_type=ISI) 

31. 31.Rousk K, Sorensen PL, Michelsen A. What drives biological nitrogen fixation in high arctic tundra: Moisture or temperature? Ecosphere 2018; 9: e02117.
    
    

32. 32.Stewart KJ, Coxson D, Grogan P. Nitrogen Inputs by Associative Cyanobacteria across a Low Arctic Tundra Landscape. Arct Antarct Alp Res 2011; 43: 267–278.
    
    

33. 33.Stewart KJ, Grogan P, Coxson DS, Siciliano SD. Topography as a key factor driving atmospheric nitrogen exchanges in arctic terrestrial ecosystems. Soil Biol Biochem 2014; 70: 96–112.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1016/j.soilbio.2013.12.005&link_type=DOI) 

34. 34.Zielke M, Solheim B, Spjelkavik S, Olsen RA. Nitrogen fixation in the high arctic: role of vegetation and environmental conditions. Arct Antarct Alp Res 2005; 37: 372–378.
    
    

35. 35.Rousk K, Jones DL, DeLuca TH. The resilience of nitrogen fixation in feather moss (Pleurozium schreberi)-cyanobacteria associations after a drying and rewetting cycle. Plant Soil 2014; 377: 159–167.
    
    

36. 36.Rousk K, Sorensen PL, Lett S, Michelsen A. Across-Habitat Comparison of Diazotroph Activity in the Subarctic. Microb Ecol 2015; 69: 778–787.
    
    

37. 37.Deslippe JR, Egger KN, Henry GHR. Impacts of warming and fertilization on nitrogen-fixing microbial communities in the Canadian High Arctic. FEMS Microbiol Ecol 2005; 53: 41–50.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1016/j.femsec.2004.12.002&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=16329928&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 

38. 38.Rousk K, Michelsen A. Ecosystem nitrogen fixation throughout the snow-free period in subarctic tundra: effects of willow and birch litter addition and warming. Glob Change Biol 2017; 23: 1552–1563.
    
    

39. 39.Kolton M, Marks A, Wilson RM, Chanton JP, Kostka JE. Impact of Warming on Greenhouse Gas Production and Microbial Diversity in Anoxic Peat From a Sphagnum-Dominated Bog (Grand Rapids, Minnesota, United States). Front Microbiol 2019; 10.
    
    

40. 40.Carrell AA, Kolton M, Glass JB, Pelletier DA, Warren MJ, Kostka JE, et al. Experimental warming alters the community composition, diversity, and N 2 fixation activity of peat moss (*Sphagnum fallax*) microbiomes. Glob Change Biol 2019; 25: 2993–3004.
    
    

41. 41.Tallis JH. Climate and Erosion Signals in British Blanket Peats: The Significance of Racomitrium Lanuginosum Remains. J Ecol 1995; 83: 1021–1030.
    
    

42. 42.Gosseling M. CORDEX climate trends for Iceland in the 21st century. 2017. Icelandic Meteorological Office, Reykjavík.
    
    

43. 43.Henry GHR, Molau U. Tundra plants and climate change: the International Tundra Experiment (ITEX). Glob Change Biol 1997; 3: 1–9.
    
    

44. 44.Jonsdottir IS, Magnusson B, Gudmundsson J, Elmarsdottir A, Hjartarson H. Variable sensitivity of plant communities in Iceland to experimental warming. Glob Change Biol 2005; 11: 553–563.
    
    

45. 45.Arnalds O. The Soils of Iceland. 2015. Springer Netherlands, Dordrecht.
    
    

46. 46.Hollister RD, Webber PJ. Biotic validation of small open-top chambers in a tundra ecosystem. Glob Change Biol 2000; 6: 835–842.
    
    

47. 47.Hardy RW, Holsten RD, Jackson EK, Burns RC. The acetylene-ethylene assay for N2 fixation: laboratory and field evaluation. Plant Physiol 1968; 43: 1185–1207.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6MTI6InBsYW50cGh5c2lvbCI7czo1OiJyZXNpZCI7czo5OiI0My84LzExODUiO3M6NDoiYXRvbSI7czozNzoiL2Jpb3J4aXYvZWFybHkvMjAxOS8xMS8xMi84Mzg1ODEuYXRvbSI7fXM6ODoiZnJhZ21lbnQiO3M6MDoiIjt9) 

48. 48.Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods 2016; 13: 581–583.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1038/nmeth.3869&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=27214047&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 

49. 49.Callahan BJ, McMurdie PJ, Holmes SP. Exact sequence variants should replace operational taxonomic units in marker-gene data analysis. ISME J 2017; 11: 2639–2643.
    
    

50. 50.Wang Q, Garrity GM, Tiedje JM, Cole JR. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 2007; 73: 5261–5267.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6MzoiYWVtIjtzOjU6InJlc2lkIjtzOjEwOiI3My8xNi81MjYxIjtzOjQ6ImF0b20iO3M6Mzc6Ii9iaW9yeGl2L2Vhcmx5LzIwMTkvMTEvMTIvODM4NTgxLmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ==) 

51. 51.Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res 2013; 41: D590–D596.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1093/nar/gks1219&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=23193283&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000312893300084&link_type=ISI) 

52. 52.Paulson JN, Stine OC, Bravo HC, Pop M. Differential abundance analysis for microbial marker-gene surveys. Nat Methods 2013; 10: 1200–1202.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1038/nmeth.2658&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=24076764&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000327698100020&link_type=ISI) 

53. 53.Blazewicz SJ, Barnard RL, Daly RA, Firestone MK. Evaluating rRNA as an indicator of microbial activity in environmental communities: limitations and uses. ISME J 2013; 7: 2061–2068.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1038/ismej.2013.102&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=23823491&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000326090800001&link_type=ISI) 

54. 54.Poly F, Monrozier LJ, Bally R. Improvement in the RFLP procedure for studying the diversity of nifH genes in communities of nitrogen fixers in soil. Res Microbiol 2001; 152: 95–103.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1016/S0923-2508(00)01172-4&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=11281330&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000167518500011&link_type=ISI) 

55. 55.Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O’hara RB, et al. Package ‘vegan’. Community Ecol Package Version 2013; 2: 296.
    
    

56. 56.McMurdie PJ, Holmes S. phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data. PLOS ONE 2013; 8: e61217.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1371/journal.pone.0061217&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=23630581&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 

57. 57.Hadfield JD. MCMC Methods for Multi-Response Generalized Linear Mixed Models: The MCMCglmm R Package. J Stat Softw 2010; 33: 1–22.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/j.1467-9868.2005.00503.x&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=20808728&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000275203200001&link_type=ISI) 

58. 58.Anderson MJ. A new method for non-parametric multivariate analysis of variance. Austral Ecol 2001; 26: 32–46.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1093/nar/gky1022&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=30371820&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 

59. 59.Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 2014; 15.
    
    

60. 60.De Caceres M, Legendre P. Associations between species and groups of sites: indices and statistical inference. Ecology 2009; 90: 3566–3574.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1890/08-1823.1&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=20120823&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000272700800026&link_type=ISI) 

61. 61.DeAngelis KM, Pold G, Topçuoğlu BD, van Diepen LTA, Varney RM, Blanchard JL, et al. Long-term forest soil warming alters microbial communities in temperate forest soils. Front Microbiol 2015; 6.
    
    

62. 62.T. Weedon J, A. Kowalchuk G, Aerts R, van Hal J, van Logtestijn R, Taş N, et al. Summer warming accelerates sub-arctic peatland nitrogen cycling without changing enzyme pools or microbial community structure. Glob Change Biol 2012; 18: 138–150.
    
    

63. 63.Rinnan R, Michelsen A, Bååth E, Jonasson S. Fifteen years of climate change manipulations alter soil microbial communities in a subarctic heath ecosystem. Glob Change Biol 2007; 13: 28–39.
    
    

64. 64.Deslippe JR, Hartmann M, Simard SW, Mohn WW. Long-term warming alters the composition of Arctic soil microbial communities. FEMS Microbiol Ecol 2012; 82: 303–315.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/j.1574-6941.2012.01350.x&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=22404643&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000310261900008&link_type=ISI) 

65. 65.Björnsdóttir K. Decomposition responses to climate warming and sheep grazing in the high and sub-Arctic. 2018. University of Iceland, Reykjavík.
    
    

66. 66.Vandenkoornhuyse P, Quaiser A, Duhamel M, Van AL, Dufresne A. The importance of the microbiome of the plant holobiont. New Phytol 2015; 206: 1196–1206.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/nph.13312&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=25655016&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 

67. 67.Koyama A, Steinweg JM, Haddix ML, Dukes JS, Wallenstein MD. Soil bacterial community responses to altered precipitation and temperature regimes in an old field grassland are mediated by plants. FEMS Microbiol Ecol 2018; 94: fix156.
    
    

68. 68.Sayer EJ, Oliver AE, Fridley JD, Askew AP, Mills RTE, Grime JP. Links between soil microbial communities and plant traits in a species-rich grassland under long-term climate change. Ecol Evol 2017; 7: 855–862.
    
    

69. 69.Kardol P, Spitzer CM, Gundale MJ, Nilsson M-C, Wardle DA. Trophic cascades in the bryosphere: the impact of global change factors on top-down control of cyanobacterial N2-fixation. Ecol Lett 2016; 19: 967–976.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/ele.12635&link_type=DOI) 

70. 70.Jiang Y, Liu M, Zhang J, Chen Y, Chen X, Chen L, et al. Nematode grazing promotes bacterial community dynamics in soil at the aggregate level. ISME J 2017; 11: 2705–2717.
    
    

71. 71.Jassey VE, Chiapusio G, Binet P, Buttler A, Laggoun-Défarge F, Delarue F, et al. Above- and belowground linkages in Sphagnum peatland: climate warming affects plant-microbial interactions. Glob Change Biol 2013; 19: 811–823.
    
    

72. 72.Petchey OL, McPhearson PT, Casey TM, Morin PJ. Environmental warming alters food-web structure and ecosystem function. Nature 1999; 402: 69–72.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1038/47023&link_type=DOI) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000083638600043&link_type=ISI) 

73. 73.Markkula I, Cornelissen JHC, Aerts R. Sixteen years of simulated summer and winter warming have contrasting effects on soil mite communities in a sub-Arctic peat bog. Polar Biol 2019; 42: 581–591.
    
    

74. 74.Frank AC, Saldierna Guzmán JP, Shay JE. Transmission of Bacterial Endophytes. Microorganisms 2017; 5(4).
    
    

75. 75.Vandekerckhove TT, Willems A, Gillis M, Coomans A. Occurrence of novel verrucomicrobial species, endosymbiotic and associated with parthenogenesis in Xiphinema americanum-group species (Nematoda, Longidoridae). Int J Syst Evol Microbiol 2000; 50: 2197–2205.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1099/00207713-50-6-2197&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=11155997&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000166156700030&link_type=ISI) 

76. 76.Aydogan EL, Moser G, Müller C, Kämpfer P, Glaeser SP. Long-Term Warming Shifts the Composition of Bacterial Communities in the Phyllosphere of Galium album in a Permanent Grassland Field-Experiment. Front Microbiol 2018; 9.
    
    

77. 77.van der Heijden MGA, Hartmann M. Networking in the Plant Microbiome. PLOS Biol 2016; 14: e1002378.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1371/journal.pbio.1002378&link_type=DOI) 

78. 78.Agler MT, Ruhe J, Kroll S, Morhenn C, Kim S-T, Weigel D, et al. Microbial Hub Taxa Link Host and Abiotic Factors to Plant Microbiome Variation. PLOS Biol 2016; 14: e1002352.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1371/journal.pbio.1002352&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=26788878&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 

79. 79.Vorholt JA. Microbial life in the phyllosphere. Nat Rev Microbiol 2012; 10: 828–840.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1038/nrmicro2910&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=23154261&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 

80. 80.Lebeis SL. The potential for give and take in plant–microbiome relationships. Front Plant Sci 2014; 5.
    
    

81. 81.Compant S, Van Der Heijden MGA, Sessitsch A. Climate change effects on beneficial plant–microorganism interactions. FEMS Microbiol Ecol 2010; 73: 197–214.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/j.1574-6941.2010.00900.x&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=20528987&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000279651900001&link_type=ISI) 

82. 82.Vries FT de, Bardgett RD. Plant–microbial linkages and ecosystem nitrogen retention: lessons for sustainable agriculture. Front Ecol Environ 2012; 10: 425–432.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1890/110162&link_type=DOI) 

83. 83.Bay G, Nahar N, Oubre M, Whitehouse MJ, Wardle DA, Zackrisson O, et al. Boreal feather mosses secrete chemical signals to gain nitrogen. New Phytol 2013; 200: 54–60.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/nph.12403&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=23795916&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000323475000009&link_type=ISI) 

84. 84.Fierer N, Bradford MA, Jackson RB. TOWARD AN ECOLOGICAL CLASSIFICATION OF SOIL BACTERIA. Ecology 2007; 88: 1354–1364.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1890/05-1839&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=17601128&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000247203100003&link_type=ISI) 

85. 85.De Vries FT, Shade A. Controls on soil microbial community stability under climate change. Front Microbiol 2013; 4.
    
    

86. 86.Yergeau E, Bokhorst S, Kang S, Zhou J, Greer CW, Aerts R, et al. Shifts in soil microorganisms in response to warming are consistent across a range of Antarctic environments. ISME J 2012; 6: 692–702.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1038/ismej.2011.124&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=21938020&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000300883200021&link_type=ISI) 

87. 87.Xiong J, Sun H, Peng F, Zhang H, Xue X, Gibbons SM, et al. Characterizing changes in soil bacterial community structure in response to short-term warming. FEMS Microbiol Ecol 2014; 89: 281–292.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/1574-6941.12289&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=24476229&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 

88. 88.Stark S, Männistö MK, Ganzert L, Tiirola M, Häggblom MM. Grazing intensity in subarctic tundra affects the temperature adaptation of soil microbial communities. Soil Biol Biochem 2015; 84: 147–157.
    
    

89. 89.Oliverio AM, Bradford MA, Fierer N. Identifying the microbial taxa that consistently respond to soil warming across time and space. Glob Change Biol 2017; 23: 2117–2129.
    
    

90. 90.Männistö MK, Kurhela E, Tiirola M, Häggblom MM. Acidobacteria dominate the active bacterial communities of Arctic tundra with widely divergent winter-time snow accumulation and soil temperatures. FEMS Microbiol Ecol 2013; 84: 47–59.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/1574-6941.12035&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=23106413&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 

91. 91.Kielak AM, Barreto CC, Kowalchuk GA, van Veen JA, Kuramae EE. The Ecology of Acidobacteria: Moving beyond Genes and Genomes. Front Microbiol 2016; 7.
    
    

92. 92.Shade A, Peter H, Allison SD, Baho DL, Berga M, Bürgmann H, et al. Fundamentals of Microbial Community Resistance and Resilience. Front Microbiol 2012; 3.
    
    

93. 93.Patova E, Sivkov M, Patova A. Nitrogen fixation activity in biological soil crusts dominated by cyanobacteria in the Subpolar Urals (European North-East Russia). FEMS Microbiol Ecol 2016; 92: fiw131.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1093/femsec/fiw131&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=27306556&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 

94. 94.Arróniz-Crespo M, Pérez-Ortega S, De los Ríos A, Green TGA, Ochoa-Hueso R, Casermeiro MÁ, et al. Bryophyte-Cyanobacteria Associations during Primary Succession in Recently Deglaciated Areas of Tierra del Fuego (Chile). PLoS ONE 2014; 9: e96081.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1371/journal.pone.0096081&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=24819926&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 

95. 95.Griese M, Lange C, Soppa J. Ploidy in cyanobacteria. FEMS Microbiol Lett 2011; 323: 124–131.
    
    [CrossRef](http://biorxiv.org/lookup/external-ref?access_num=10.1111/j.1574-6968.2011.02368.x&link_type=DOI) 
    
    [PubMed](http://biorxiv.org/lookup/external-ref?access_num=22092711&link_type=MED&atom=%2Fbiorxiv%2Fearly%2F2019%2F11%2F12%2F838581.atom) 
    
    [Web of Science](http://biorxiv.org/lookup/external-ref?access_num=000295528200004&link_type=ISI) 

96. 96.Darnajoux R, Zhang X, McRose DL, Miadlikowska J, Lutzoni F, Kraepiel AML, et al. Biological nitrogen fixation by alternative nitrogenases in boreal cyanolichens: importance of molybdenum availability and implications for current biological nitrogen fixation estimates. New Phytol 2016; 213: 680–689.
    
    

97. 97.Nelson JM, Hauser DA, Gudiño JA, Guadalupe YA, Meeks JC, Salazar Allen N, et al. Complete Genomes of Symbiotic Cyanobacteria Clarify the Evolution of Vanadium-Nitrogenase. Genome Biol Evol 2019; 11: 1959–1964.
    
    

98. 98.Miller RW, Eady RR. Molybdenum and vanadium nitrogenases of Azotobacter chroococcum. Low temperature favours N2 reduction by vanadium nitrogenase. Biochem J 1988; 256: 429–432.
    
    [Abstract/FREE Full Text](http://biorxiv.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6MTA6InBwYmlvY2hlbWoiO3M6NToicmVzaWQiO3M6OToiMjU2LzIvNDI5IjtzOjQ6ImF0b20iO3M6Mzc6Ii9iaW9yeGl2L2Vhcmx5LzIwMTkvMTEvMTIvODM4NTgxLmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ==)