PROF E Jason

Stajich

D R Jeffrey

M Diez

Courtney G Collins

Marko J Spasojevic

Concepción L Alados

Emma L Aronson

Juan C Benavides

Nicoletta Cannone

Chatrina Caviezel

Oriol Grau

Hui Guo

Gaku Kudo

Nikolas J Kuhn

Jana Müllerová

Michala L Phillips

Nuttapon Pombubpa

Frédérique Reverchon

Hannah B Shulman

Jason E Stajich

Alexia Stokes

Sören E Weber

Jeffrey M Diez

Belowground Impacts of Alpine Woody Encroachment are determined by Plant Traits, Local Climate and Soil Conditions

Keywords: Woody encroachment, plant-soil interactions, alpine, global change, soil microbes, leaf traits

Global climate and land use change are causing woody plant encroachment in arctic, alpine, and arid/semiarid ecosystems around the world,

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Introduction

Global climate and land use change are altering the distributions of organisms worldwide [START_REF] Chen | Rapid range shifts of species of climate warming[END_REF][START_REF] Parmesan | Ecological and Evolutionary Responses to Recent Climate Change[END_REF][START_REF] Walther | Ecological responses to recent climate change[END_REF] and this is particularly true in arctic and alpine tundra ecosystems where warming is accelerated [START_REF] Elmendorf | Plot-scale evidence of tundra vegetation change and links to recent summer warming[END_REF][START_REF] Walker | Plant community responses to experimental warming across the tundra biome[END_REF][START_REF] Wilson | Arctic alpine vegetation change over 20 years[END_REF]. One prevalent change in tundra ecosystems is the encroachment of woody plants (shrubs and dwarf trees) into areas previously dominated by non-woody grasses, sedges and forbs [START_REF] Myers-Smith | Climate warming as a driver of tundra shrubline advance[END_REF][START_REF] Rundqvist | Tree and shrub expansion over the past 34 years at the tree-line near Abisko, Sweden[END_REF][START_REF] Sturm | Winter Biological Processes Could Help Convert Arctic Tundra to Shrubland[END_REF]. Woody plant encroachment can strongly impact aboveground productivity, the redistribution of snow by wind, and water and nutrient cycling in the tundra [START_REF] Demarco | Effects of arctic shrub expansion on biophysical vs. biogeochemical drivers of litter decomposition[END_REF][START_REF] Myers-Smith | Shrub expansion in tundra ecosystems: dynamics, impacts and research priorities[END_REF][START_REF] Myers-Smith | Shrub canopies influence soil temperatures but not nutrient dynamics: An experimental test of tundra snow-shrub interactions[END_REF][START_REF] Weintraub | Nitrogen cycling and the spread of shrubs control changes in the carbon balance of Arctic tundra ecosystems[END_REF]. However, few studies have considered the biotic impacts of woody encroachment, particularly belowground effects on soil microbial communities [START_REF] Myers-Smith | Shrub expansion in tundra ecosystems: dynamics, impacts and research priorities[END_REF]. Some case studies, primarily from the Arctic, show that encroachment alters soil microbial community structure and function via woody litter inputs, leading to increased soil organic matter mineralization and soil carbon C:N ratios [START_REF] Eskelinen | Links between plant community composition, soil organic matter quality and microbial communities in contrasting tundra habitats[END_REF][START_REF] Rousk | Microbial control of soil organic matter mineralization responses to labile carbon in subarctic climate change treatments[END_REF][START_REF] Wallenstein | Bacterial and fungal community structure in Arctic tundra tussock and shrub soils[END_REF]. However, we lack a general understanding of how woody encroachment affects soil microbial communities at the global scale, or whether observed impacts are species and site specific [START_REF] Donhauser | Alpine soil microbial ecology in a changing world[END_REF][START_REF] Myers-Smith | Shrub expansion in tundra ecosystems: dynamics, impacts and research priorities[END_REF].

To fill this knowledge gap, we conducted a coordinated global study of alpine woody encroachment on soil microbial communities. We assessed a diverse set of pathways by which plants can impact soil microbes, including changes in the quality and quantity of litter inputs (J. H. C. [START_REF] Cornelissen | Global negative vegetation feedback to climate warming responses of leaf litter decomposition rates in cold biomes[END_REF] Author Manuscript

This article is protected by copyright. All rights reserved [START_REF] Santonja | Plant litter diversity increases microbial abundance, fungal diversity, and carbon and nitrogen cycling in a Mediterranean shrubland[END_REF], alteration of soil abiotic conditions such as soil chemistry, moisture and pH [START_REF] Eskelinen | Links between plant community composition, soil organic matter quality and microbial communities in contrasting tundra habitats[END_REF][START_REF] Schimel | Increased snow depth affects microbial activity and nitrogen mineralization in two Arctic tundra communities[END_REF][START_REF] Yannarell | Influence of shrub encroachment on the soil microbial community composition of remnant hill prairies[END_REF], or through interactions with rhizospheric microbes such as dinitrogen (N 2 )-fixing bacteria or mycorrhizae [START_REF] Bengtson | Evidence of a strong coupling between root exudation, C and N availability, and stimulated SOM decomposition caused by rhizosphere priming effects[END_REF]. Due to fluctuating environmental conditions and extreme spatial heterogeneity, alpine soil microbial communities are highly specialized, and can vary greatly across vegetation types, soil properties, and microclimates [START_REF] Donhauser | Alpine soil microbial ecology in a changing world[END_REF]. Also, the effects of woody plant encroachment may interact with the direct effects of climate change (e.g. soil warming or drought) on soil microbes, making net outcomes difficult to predict [START_REF] Classen | Direct and indirect effects of climate change on soil microbial and soil microbial-plant interactions: What lies ahead?[END_REF][START_REF] Kardol | Soil ecosystem functioning under climate change: plant species and community effects[END_REF]. Thus understanding how woody plant encroachment directly and indirectly influences soil microbial communities is key to predicting long-term changes in the structure and function of alpine ecosystems [START_REF] Hagedorn | Above-and belowground linkages shape responses of mountain vegetation to Climate Change[END_REF].

Direct effects of woody plant encroachment on soil microbial communities include shifts in both the quality and quantity of leaf and root litter [START_REF] Wardle | Ecological linkages between aboveground and belowground biota[END_REF], Eldor Alvin Paul, 2007;) as well as interactions with microbial symbionts in their roots for nutrient and resource uptake (Smith & Read, 1997a;[START_REF] Wookey | Ecosystem feedbacks and cascade processes: Understanding their role in the responses of Arctic and alpine ecosystems to environmental change[END_REF]. A shift from primarily herbaceous (grasses, sedges, forbs) to woody plant cover generally increases the quantity and decreases the quality of litter inputs, and may result in slower decomposition of organic matter (J. H. C. [START_REF] Cornelissen | Global negative vegetation feedback to climate warming responses of leaf litter decomposition rates in cold biomes[END_REF]. However this pattern can differ across woody plant species based on chemical and morphological litter traits such as leaf carbon: nitrogen ratio (C:N), leaf dry matter content (LDMC) and specific leaf area (SLA) [START_REF] Cornwell | Plant species traits are the predominant control on litter decomposition rates within biomes worldwide[END_REF][START_REF] Gavazov | Dynamics of alpine plant litter decomposition in a changing climate[END_REF][START_REF] Urbina | Encroachment of shrubs into subalpine grasslands in the Pyrenees changes the plant-soil stoichiometry spectrum[END_REF]. Litter mixing between woody and herbaceous plants can increase the chemical complexity of the substrate pool, enhancing both microbial niche space and diversity [START_REF] Chapman | Biodiversity at the plant-soil interface: Microbial abundance and community structure respond to litter mixing[END_REF][START_REF] Mcguire | Slowed decomposition is biotically mediated in an ectomycorrhizal, tropical rain forest[END_REF]. Additionally, different types of microbial symbionts engage in distinct resource use strategies, and can greatly influence the resource economy of their plant host (J. [START_REF] Cornelissen | Carbon cycling traits of plant species are linked with mycorrhizal strategy[END_REF][START_REF] Gerz | Niche differentiation and expansion of plant species are associated with mycorrhizal symbiosis[END_REF]Smith & Read, 1997b, 1997c). For example, Ecto-and Ericoid mycorrhizal fungi (ECM, ERM) have a higher affinity for organic forms of N and phosphorus (P) than arbuscular mycorrhizal fungi (AMF) which primarily scavenge inorganic nutrients [START_REF] Read | Mycorrhizas and nutrient cycling in ecosystems -a journey towards[END_REF][START_REF] Wookey | Ecosystem feedbacks and cascade processes: Understanding their role in the responses of Arctic and alpine ecosystems to environmental change[END_REF], while N 2 -fixing bacteria directly convert elemental N 2 into plant available forms of N (van der Heijden, [START_REF] Van Der Heijden | The unseen majority: soil microbes as drivers of plant diversity and productivity in terrestrial ecosystems[END_REF]. Differences in leaf litter chemistry across plant symbiont types may further select for faster [START_REF] Cheeke | Dominant mycorrhizal association of trees alters carbon and nutrient cycling by selecting for microbial groups with distinct enzyme function[END_REF][START_REF] Taylor | Mycorrhizal associations of trees have different indirect effects on organic matter decomposition[END_REF] or slower [START_REF] Mcguire | Slowed decomposition is biotically mediated in an ectomycorrhizal, tropical rain forest[END_REF] decomposition by saprotrophic soil microbes. Furthermore, root symbionts can directly interact in numerous ways with

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This article is protected by copyright. All rights reserved saprotrophic fungi and bacteria in the rhizosphere. For example, mycorrhizal fungi release organic acids, hyphal exudates and provide hyphal necromass, which can enhance bacterial growth and serve as a food source for free-living soil biota [START_REF] Bending | Significance of microbial interactions in the mycorrhizosphere[END_REF][START_REF] Liang | The importance of anabolism in microbial control over soil carbon storage[END_REF]. Alpine soils usually have very low organic matter, and therefore changes in the quantity and quality of litter inputs, hyphal exudates, and microbial necromass as a result of woody encroachment have the potential to create major changes in free-living soil microbial communities and belowground ecosystem functioning [START_REF] Donhauser | Alpine soil microbial ecology in a changing world[END_REF][START_REF] Körner | Alpine Plant Life: Functional Plant Ecology of High Mountain Ecosystems[END_REF].

Woody plant encroachment can also indirectly influence soil microbes through changes in the abiotic soil environment [START_REF] Collins | Direct and indirect effects of native range expansion on soil microbial community structure and function[END_REF][START_REF] Grau | Encroachment of shrubs into subalpine grasslands in the Pyrenees modifies the structure of soil fungal communities and soil properties[END_REF] and via interactions with local climate [START_REF] Classen | Direct and indirect effects of climate change on soil microbial and soil microbial-plant interactions: What lies ahead?[END_REF]. Woody encroachment can alter C and nutrient cycling, water availability and pH, and can also drastically alter the spatial distribution of resources across a landscape [START_REF] Eldridge | Impacts of shrub encroachment on ecosystem structure and functioning: Towards a global synthesis[END_REF][START_REF] Myers-Smith | Shrub expansion in tundra ecosystems: dynamics, impacts and research priorities[END_REF]. Shading under woody plant canopies retains soil moisture higher in the soil profile in addition to physical trapping of snow, that concentrates snowmelt [START_REF] Gómez-Aparicio | Canopy vs. soil effects of shrubs facilitating tree seedlings in Mediterranean montane ecosystems[END_REF][START_REF] Sturm | Winter Biological Processes Could Help Convert Arctic Tundra to Shrubland[END_REF]. Enhanced soil moisture and thermal insulation from snow can promote decomposition and biogeochemical cycling (Schimel et al., 2004), while leaching of organic acids from woody litter can directly influence soil pH [START_REF] Jobbagyl | Patterns and mechanisms of soil acidification in the conversion of grasslands to forests[END_REF], which is a key driver of microbial community composition [START_REF] Lauber | Pyrosequencing-based assessment of soil pH as a predictor of soil bacterial community structure at the continental scale[END_REF][START_REF] Rousk | Soil bacterial and fungal communities across a pH gradient in an arable soil[END_REF]. Overall, resource accumulation below woody plant canopies can lead to increased microbial biomass [START_REF] Cable | Woody plant encroachment impacts on soil carbon and microbial processes: Results from a hierarchical Bayesian analysis of soil incubation data[END_REF][START_REF] Liao | Soil microbial biomass response to woody plant invasion of grassland[END_REF], diversity [START_REF] Hollister | Structural and functional diversity of soil bacterial and fungal communities following woody plant encroachment in the southern Great Plains[END_REF] and shifts in community composition [START_REF] Yannarell | Influence of shrub encroachment on the soil microbial community composition of remnant hill prairies[END_REF]. In addition, impacts of woody plant encroachment may be more or less severe depending on ambient temperature and precipitation, which are changing rapidly in alpine environments [START_REF] Rammig | Changes in alpine plant growth under future climate conditions[END_REF]. Interactions between plant growth form (i.e. woody or herbaceous) and experimental shifts in air temperature, soil moisture and CO 2 influenced soil microbial enzyme production and nematode community composition [START_REF] Kardol | Soil ecosystem functioning under climate change: plant species and community effects[END_REF]. Similarly, soil temperature and moisture determined whether arctic soils became net sources or sinks of CO 2 in woody but not herbaceous plant communities [START_REF] Cahoon | Interactions among shrub cover and the soil microclimate may determine future Arctic carbon budgets[END_REF]. Because of these complexities, we lack a clear understanding of how specific abiotic conditions or climate patterns will influence woody plant-soil interactions. Thus, assessing woody plant encroachment across multiple sites spanning diverse climates and environmental conditions is crucial [START_REF] Wookey | Ecosystem feedbacks and cascade processes: Understanding their role in the responses of Arctic and alpine ecosystems to environmental change[END_REF].

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The objectives of this research were to determine: 1) Is there a consistent global signature of woody plant encroachment on soil microbial communities in alpine ecosystems? and 2) What are the major abiotic and biotic drivers mediating the observed changes in soil microbial communities? We conducted this study across 13 alpine sites all undergoing woody plant encroachment, spanning four continents and ten mountain ranges (Table 1). We hypothesized that woody plant encroachment will: 1) alter soil microbial diversity and microbial community composition via changes in litter quality. Such changes are likely driven by differences in leaf functional traits and their influence on soil abiotic conditions; 2) impact soil microbial communities differently depending on root symbiont types (AMF, ECM and, N 2 -fixers) and associated resource use strategies; 3) influence soil microbial communities indirectly through changes in abiotic soil conditions; 4) have climate-dependent effects on soil microbial communities due to high microbial sensitivity to temperature and moisture.

Materials and Methods

Site selection

This study took place at 13 sites (Fig 1, Table 1) across North and South America, Europe and Asia. We selected sites based on the following criteria: 1) woody plant encroachment into alpine plant communities dominated by herbaceous species, was observed within the last 50 years. We confirmed that woody plants were not previously present using aerial photography, historical records, and personal knowledge or information from local groups. See citations in Table 1 for further details regarding woody encroachment at each site. 2) Sites were alpine or subalpine (close to or above treeline), not Arctic (one site in Abisko, Sweden was considered 'subarctic' alpine). 3) Sites were not actively grazed or managed for agriculture (low intensity grazing did occur at our sites on the Tibetan Plateau in China and in the Swiss Alps and pine (Pinus mugo) silviculture occurred historically around our site in the Czech Republic). 4) International shipping speeds allowed samples to arrive in 72 hours or less on dry ice so that soils would stay frozen (this requirement affected our choice of study sites that excluded the Southern Hemisphere, Africa, and remote parts of Asia in our study). Finally, while we use the term 'woody' to describe primarily shrubs and dwarf trees at our study sites, one site (Japan) has a dwarf bamboo species (Sasa kurilensis) which is technically a 'woody graminoid. ' This and other species of bamboo are common woody encroachers across Asia [START_REF] Xu | Rapid bamboo invasion (expansion) and its effects on biodiversity and soil processes +[END_REF].

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Soil sampling

We sampled soils from both directly under and outside woody plant canopies (~1.5-3.0 m outside) in the herbaceous plant interspace in areas where woody shrubs and dwarf trees were newly established (not present > 50 years). Soils were sampled during the growing season in either 2017 or 2018 (depending on site). All soils were sampled using an aseptic technique and sampling protocol as described in the USEPA/USGS Sample Collection Protocol for Bacterial Pathogens in Surface Soil (EPA, 2014). We collected ten soil samples from each vegetation type (woody and herbaceous) at each site for a total of 20 samples per site (20 x 13=260 soil samples). For each soil sample, three replicate soil cores were taken at a depth of 10-15 cm, combined into one sample with all excess rocks, roots, leaves or twigs removed and placed in sterile Whirlpak bags (Uline, Pleasant Prairie, WI, USA). Sampling locations within sites (individual woody plants and paired herbaceous soils) were at least 5 m apart. Soils were frozen within 24 hrs after sampling and remained in the freezer (-20° C) until being shipped. Soils were shipped on dry ice via expedited shipping to the University of California, Riverside, USA. All soils were sampled from within the same parent material and 100 m elevation differential or less at each site.

Soil abiotic parameters

At each soil sampling location (N=10 woody + 10 herbaceous=20 per site), we measured soil volumetric water content (VWC %) and soil pH in situ using handheld probes (Vegetronix VG-Meter-200 basic or equivalent; EXTECH Model PH100 or equivalent). For soil chemistry, shipped soils were thawed at room temperature (half of each sample, other half remained frozen for microbial analyses) sifted through a 2mm mesh sieve and ground via mortar and pestle. Soils were then oven dried at 60 ºC for 72 hours, weighed into tin capsules and measured for total C and N on a Flash EA 112 analyzer at the University of California Riverside Environmental sciences research laboratory, U.S.A.

Leaf sampling and traits

Ten leaves were sampled from the encroaching woody species at each study site (n=10 x 13 sites= 130 leaves). Leaves were kept moist and weighed within 24 hours of sampling on a microbalance to obtain fresh weight (g). Leaves were then placed in paper envelopes and left to air dry until shipping.

We measured the following leaf functional traits for each woody plant species: leaf dry matter content LDMC (g/g), specific leaf area SLA (cm 2 /g), leaf N (%), leaf C (%), δ13C, and δ15N. Leaves were scanned on a flatbed scanner to calculate leaf area (cm 2 ) using ImageJ software (https://imagej.nih.gov/ij/). Leaves were dried (60 C, 72 hours) and then weighed for dry weight (g). LDMC was calculated as the ratio of fresh weight (g) to dry weight (g) and SLA was calculated as leaf area

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This article is protected by copyright. All rights reserved (cm 2 ) to dry weight (g). Leaf chemical (C, N) and isotope (δ 13 C, and δ 15 N ) content were measured from dried leaf subsamples at the University of Wyoming Stable Isotope Facility (Laramie, WY, USA.).

Soil microbial analyses

We extracted microbial DNA from 0.25 g of soil (±0.025 g) of each sample using a Qiagen DNeasy PowerSoil Kit (Qiagen Inc., Germantown, MD, USA) and quantified the extracted DNA using a NanoDrop 2000 (Thermo Fisher Scientific Inc., Wilmington, DE, USA). After quantification, we standardized DNA extracts to 10 ng/µL. We performed PCR amplification using the 515F/806R primer set targeting V4 region of the 16S rRNA gene for bacteria [START_REF] Caporaso | Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample[END_REF] and the 5.8S-Fun/ITS4-Fun primer set targeting the ITS-2 region for Fungi (D. L. Taylor et al., 2016). PCR was run in 25 µl reactions including 1.25 µl of 1 µM for each primer (forward and reverse), 1 µl DNA template, 12.5 µl of Phusion Green Hot Start 2X Master Mix (Thermo Fisher Scientific Inc., USA), 1.5 µl of 3 µM MgCl 2 and 7.5 µl PCR grade water. Thermocycler settings were 95⁰C for 2 minutes, followed by 35 cycles of 95⁰C for 30 seconds, 55⁰C for 30 seconds, and 60⁰C for 4 minutes (ITS2) or 2:30 minutes (16S) with a 10⁰C hold. We then did PCR clean-up using Agencourt AMPure XP beads (Beckman Coulter, Inc., Indianapolis, USA, IN 46268). Purified PCR products (2.5 µl) were mixed with 2.5 µl of 100 nm custom universal tails indexing primers (forward and reverse) developed at EnGGen Laboratory, Northern Arizona University (Flagstaff, AZ, USA) [START_REF] Colman | Detection of low-level mixed-population drug resistance in Mycobacterium tuberculosis using high fidelity amplicon sequencing[END_REF] 12.5 µl of Phusion Green Master Mix, 1.5 µl of 3 µM MgCl 2 and 3.5 µl PCR grade water and were amplified using thermocycler settings of 95⁰C for 2 minutes, followed by 15 cycles of 95⁰C for 30 seconds, 60⁰C for 30 seconds, and 72⁰C for 1 minute with a 10⁰C hold. We then ran another round of cleanup and quantified PCR products using the Quant-iT PicoGreen dsDNA assay kit (Life Technologies Inc., Grand Island, NY, USA). As a final step, the samples were pooled in equimolar concentrations and sequenced in a multiplexed 2-x 300-bp paired-end sequencing run on the Illumina MiSeq platform (Illumina Inc., San Diego, CA, USA) at the Genomics Core Facility, University of California Riverside (USA). Bioinformatics ITS-2 sequences were analyzed using AMPtk: Amplicon Toolkit for NGS data [START_REF] Palmer | Non-biological synthetic spike-in controls and the AMPtk software pipeline improve mycobiome data[END_REF] (https://github.com/nextgenusfs/amptk). Demultiplexed paired-end sequences data were pre-processed by trimming primer sequences, trimming forward and reverse reads to 250 bp (reads length less than 100 bp were dropped), and merging paired-end reads using USEARCH v9.1.13 [START_REF] Edgar | Search and clustering orders of magnitude faster than BLAST[END_REF]. A total of 8,310,353 reads passed the preprocessing steps and reads were filtered based on quality scores with a cutoff of an expected error less than 0.9 [START_REF] Edgar | Error filtering, pair assembly and error correction for next-generation sequencing reads[END_REF] to produce

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This article is protected by copyright. All rights reserved 6,441,443 reads which passed quality filtering. The quality filtered reads were clustered into 19,790 Operational Taxonomic Units (OTUs) using UPARSE [START_REF] Edgar | UPARSE: highly accurate OTU sequences from microbial amplicon reads[END_REF] at 97% identity threshold. The OTUs were further processed with VSEARCH (v 2.3.2) [START_REF] Rognes | VSEARCH: a versatile open source tool for metagenomics[END_REF] to identify and remove 569 chimeras based on comparison to the UNITE database v8.0 [START_REF] Nilsson | The UNITE database for molecular identification of fungi: Handling dark taxa and parallel taxonomic classifications[END_REF] leaving 19,221 OTUs . We assigned taxonomy with the AMPtk "hybrid" approach which uses Global Alignment, SINTAX, and UTAX. Lastly, sequences were rarefied to 10,000 sequences per sample and processed with QIIME Core Diversity pipeline [START_REF] Caporaso | QIIME allows analysis of high-throughput community sequencing data[END_REF] to estimating Alpha (OTU richness) and Beta diversity (Bray-Curtis dissimilarity).

16S sequences were analyzed using QIIME2 [START_REF] Bolyen | QIIME 2: Reproducible, interactive, scalable, and extensible microbiome data science[END_REF] (https://qiime2.org) following the 'Atacama soil microbiome' pipeline for demultiplexed paired-end sequences. We truncated sequences at 220 bp and trimmed the first 25 bp based on the interactive quality plots in QIIME2 and then denoised sequences using DADA2 after truncating all sequences Chimeras were removed using the default method in DADA2 [START_REF] Callahan | Dada2: High resolution sample inference from Illumina amplicon data[END_REF]. A total of 12,669,635 sequences passed quality filtering. Unique sequences were aligned using MAFFT [START_REF] Katoh | MAFFT Multiple sequence alignment software version 7: Improvements in performance and usability[END_REF], filtered using the masked alignment file, and used to construct a Maximum LIkelihood phylogeny with FastTree [START_REF] Price | FastTree 2 -Approximately Maximum-Likelihood Trees for Large Alignments[END_REF]. Alpha (OTU richness) and Beta diversity measures (Weighted UniFrac distance) [START_REF] Lozupone | UniFrac : a wew phylogenetic method for comparing microbial c ommunities[END_REF] were estimated using a subsampled feature table containing 10,000 sequences per sample. Taxonomy was assigned to 34,417 unique sequences using a Naïve Bayes classifier trained on the GreenGenes database [START_REF] Mcdonald | An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea[END_REF]) (version 13_8) using trimmed sequences pre-clustered at 99% similarity. After all sequence processing we retained N=224 unique samples for fungi and N=215 unique samples for bacteria.

Climate data

To test the interaction between site specific changes in climate and the influence of woody plant encroachment, we acquired climate data for each site through the WorldClim v 2.1 database at 30 second resolution [START_REF] Fick | WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas[END_REF]. We tested the influence of multiple climate parameters at each site including: Mean Annual Temperature (MAT), Temperature Seasonality (standard deviation x100), Maximum Temperature of Warmest Month, Minimum Temperature of Coldest Month, Mean Annual Precipitation (MAP), and Precipitation Seasonality (Coefficient of Variation). We chose to use the 30-year climate normals (WorldClim) rather than annual climate data because our analyses aimed at understanding climatic control over broad geographic variation in microbial communities. We found substantial climate variability across sites and symbiont types (Fig S1), but found that overall MAT was

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This article is protected by copyright. All rights reserved the best univariate predictor of microbial diversity (Fig S2). Therefore, we included MAT, and for consistency MAP, as the primary climate variables in subsequent models.

Statistical methods Leaf traits

We used Principal Components Analysis (PCA) to collapse the values of the six measured leaf traits into two PC axes to be used in hierarchical models (below). Prior to the PCA, we infilled missing leaf trait data (LDMC and leaf chemistry) for one site where only SLA could be measured (China) and any NA values using the package mice in R (R Core Team, 2019; van Buuren & Groothuis-oudshoorn, 2011), taking the average of 100 imputed values for each trait estimate. All data were logged prior to PCA. Leaf traits and principal components scores were averaged by (woody) plant species at each site.

We also tested for a difference in leaf N between root symbiont types, due to frequently higher N in tissues of N 2 -fixing plants. We used one way ANOVA with leaf N (%) (logged) as the response and symbiont type (N 2 -fix, ECM/ERM, AMF) as the predictor, followed by a Tukey's HSD test.

Alpha diversity (OTU richness)

We fit linear mixed-effects (hierarchical) models in a Bayesian SEM framework to test the impacts of woody plant encroachment on soil fungal and bacterial richness. First, we estimated the effects of vegetation type, climate, abiotic soil conditions, root symbiont type and their interactions on OTU richness. Next, we ran a second set of models to estimate the effects of woody plant leaf traits on soil abiotic conditions (soil C:N and soil pH), as we predicted that leaf traits would influence microbial richness via shifting abiotic soil conditions (Hypothesis 1). Thus, soil abiotic conditions were a predictor in the first set and a response in the second set of models (see General Model, Table S1). We did not hypothesize a relationship between leaf traits and soil moisture, however, so we simply used vegetation type as a predictor of soil moisture. Additionally, for the root symbiont type by vegetation interaction, we grouped symbiont types at the site level based on each woody plant species (see Table 1, Table S1), and thus we only estimate the effect of root symbionts for woody plants.

We fit Bayesian models using the brms package in R [START_REF] Bürkner | brms : An R package for bayesian multilevel models using Stan[END_REF]. All data were standard normalized prior to modeling to improve model convergence and we logged the bacterial response variable (16S OTU richness) for normality. All models contained a site level random intercept and hierarchical structure as described below and in Table S1. The Bayesian framework was convenient here due to the somewhat uneven design and multilevel structure of the data (Table S1), and was useful for

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This article is protected by copyright. All rights reserved predicting relationships with reasonable estimates of uncertainties. We used the posterior distributions of each parameter to calculate the probabilities that it was different from zero, and three probability levels are reported (85, 90 and 95% probabilities, respectively, that the parameter estimate is different from zero). We also used these parameter distributions to calculate pairwise post-hoc comparisons between root symbiont types. To assess the impacts of woody plant encroachment on bacterial and fungal community composition, we used non-metric multidimensional scaling (NMDS) of the Bray-Curtis (fungi) and weighted Unifrac (bacteria) dissimilarity metrics and permutational multivariate analysis of variance (perMANOVA) with the 'adonis' function in the Vegan package in R [START_REF] Oksanen | Vegan: community ecology package. R Package 2.3-3[END_REF] (999 permutations). We ran three perMANOVA models, first with vegetation type (woody versus herbaceous) as a predictor and site as a strata variable to restrict permutations within sites; next we used root symbiont type, climate, and soil abiotic parameters as predictors with vegetation type as a strata; third we ran a leaf trait model for woody soils only using leaf trait PCA axes 1 and 2 as predictors and no strata variable. All perMANOVA models had either bacterial or fungal community composition as the response variable. General Model:

Beta = Beta = + +

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This article is protected by copyright. All rights reserved To assess differences in the relative read abundance of microbial taxa between woody and nonwoody vegetation, we used linear mixed effects models (for normally distributed data) or generalized linear models with a Gamma distribution in the 'lmer' and 'glmer' functions in the lme4 package in R [START_REF] Bates | Fitting linear mixed-effects models using lme4[END_REF]. Read abundances (logged, zeroes removed) of microbial phyla were the response variable, vegetation type (woody/herbaceous) was a fixed effect and site was included as a random effect. General Model:

(1|)+ ℎ 3

We also used indicator species analysis to determine which taxa characterized soils from different vegetation types (woody versus herbaceous) using the function 'multipatt' in the indicspecies package in R(De Cáceres, Legendre, Wiser, & Brotons, 2012). We calculated Indicator Values (Indvalg) based on species (OTU) abundance and considered indicator taxa significant at α=0.05 based on permutation tests (n=999) and an indicator value (stat) of 0.2 or greater.

Results

Leaf Traits

PCA analysis showed that SLA, leaf N, δ15N, and LDMC loaded on PC1 which explained 37.3% of the variation among species, and high PC1 values were associated with low SLA, leaf N and δ15N and high LDMC. Leaf C and δ13C loaded on the second axis (PC2), which explained 17.5% of the variation among species, and high PC2 values were associated with high leaf C and low δ13C (Fig S3).

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This article is protected by copyright. All rights reserved ANOVA and post hoc analysis revealed N 2 -fixing woody plants had the highest leaf N content (%) overall, and significantly higher leaf N than AMF and ECM/ERM symbiont types (Fig S5).

Alpha diversity (OTU richness)

Woody plant encroachment influenced the richness of soil microbial communities, but interestingly, these impacts differed across sites, with woody plant soils having higher, lower or similar richness as herbaceous soil microbial communities (Fig 2 a,b). Bayesian hierarchical models showed that N 2 -fixing woody plants had higher soil fungal richness and lower soil bacterial richness than herbaceous plant communities within sites (Fig 3, Table S2). Additionally, ECM/ERM woody plants had higher soil bacterial richness and lower soil fungal richness than herbaceous plant communities within sites (Fig 3, Table S2). Post-hoc comparisons also revealed that N 2 -fixing woody plants had higher soil fungal richness than AMF and ECM/ERM woody plants across sites, while ECM/ERM plants had higher soil bacterial richness than AMF and N 2 -fixing woody plants across sites (Table S2,FigS6).

Soil abiotic conditions also predicted fungal and bacterial richness, including a positive relationship between pH and both fungal and bacterial richness, a negative relationship between soil C:N and fungal richness (Fig 4, Table S2), and a positive relationship between soil water content (VWC) and bacterial richness (Table S2). Woody plant soils had lower VWC than herbaceous soils and woody plant leaf traits predicted soil abiotic conditions (Table S2). The first axis of a principal components analysis (PC1) of multiple leaf traits was negatively related to soil pH and soil C:N, while PC2 was negatively related to soil pH in the Bayesian hierarchical model (Fig 4, Table S2).

Finally, there were interactions between woody encroachment and climate, including a negative interaction between mean annual precipitation (MAP) and vegetation type on fungal richness, a positive interaction between mean annual precipitation (MAP) and vegetation type on bacterial richness and a negative interaction between mean annual temperature (MAT) and vegetation type on bacterial and fungal richness (Fig 3, Table S2).

Beta diversity (Community composition)

Microbial beta diversity was generally higher between rather than within sites, as communities clustered strongly by sampling site (Fig 2 c,d). Within sites, microbial community composition differed among vegetation types and this pattern was stronger for bacterial than fungal communities based on perMANOVA results and NMDS overlap (Fig 5 a, d, Table S3,). Within vegetation types, plant traits, climate and soil abiotic conditions were significantly related to both fungal and bacterial community

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This article is protected by copyright. All rights reserved composition (Table S3). Environmental variables such as climate and soil abiotic conditions explained up to an order of magnitude more variation in bacterial than fungal community composition (maximum R 2 0.135 vs 0.012; mean R 2 0.06 vs 0.01, Table S3). Root symbiont type was a significant predictor of both fungal and bacterial communities, with the highest community similarity within N 2 -fixing soil fungal communities (Fig 5 b,e). Mean annual precipitation (MAP) and soil pH were the best abiotic predictors of fungal and bacterial community composition, respectively (Fig 5 c, f, Table S3). Woody plant leaf traits were also significant predictors of microbial community composition with PC2 being most predictive of fungal and bacterial communities (Table S3).

Taxonomic analyses

The soil fungal community comprised 10 phyla, with Ascomycota dominating (40.1%), followed by Basidiomycota (26.6%) and Mortierellomycota (13.9%), Glomeromycota (0.8%) and Chytridiomycota (0.5%) (Fig S4 a,b) . Six percent of the total ITS-2 sequences could not be assigned taxonomically, while two percent were assigned as unknown Fungi (i.e. only to Kingdom level) (red color-Fig S4). The soil bacterial community comprised 43 phyla with Proteobacteria making up the largest percentage (29.1%), followed by Acidobacteria (16.4%), Actinobacteria (12.9%), Bacteroidetes (8.7%), Planctomycetes (6.5%), Verrucomicrobia (6.5%), Chloroflexi (5.6%), unidentified bacteria (3.8%) and Firmicutes (1.5%) (Fig S4 c,d). Less than one percent of the total 16S sequences could not be assigned a taxonomy, while four percent were assigned as unknown Bacteria (red color-Fig S4).

Taxa abundance models of the dominant microbial phyla showed a lower abundance of Basidiomycota in woody versus herbaceous soils (Table S4, Fig S4 a,b). For bacterial phyla, soils from herbaceous communities had a higher abundance of Acidobacteria, Actinobacteria, Proteobacteria, Verrucomicrobia, and Planctomycetes than woody soils (Table S4, Fig S4 c,d).

Fifty-one fungal indicator OTUs (assigned to the species level) were found in woody plant soils and 23 indicator OTUs were in soils from herbaceous communities from Indicator species analysis. The six most prevalent indicator species were from the Mortierella, Penicillium, Vishniacozyma, Herpotrichia, and Metapochonia genera (OTUs 1585(OTUs , 16274, 1203(OTUs , 938, 101 and 1386) ) and were associated with soils beneath woody plants from at least ten sites (Table S5a). Species in the Penicillium, Clavaria, and Pyrenochaetopsis genera (OTUs 1611, 808, and 1271) were associated with soils from herbaceous communities at seven sites (Table S5a). There were only nine bacterial indicator OTUs assigned to the species level overall, but at the genus level, there were 32 bacterial indicator taxa (20 genera) for woody soils and 35 indicator taxa (22 genera) for herbaceous soils. Members of the genus Herminiimonas

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This article is protected by copyright. All rights reserved (Proteobacteria) and Segetibacter (Bacteroidetes) were strongly associated with woody plant soils while the DA101 (Verrucomicrobia), Rhodoplanes (Proteobacteria), and GOUTA19 (Nitrospirae) genera were associated with soils from herbaceous communities. Indicator taxa from Flavobacterium, Candidatus Koribacter, Candidatus Solibacter, Kaistobacter, and Pseudonocardia genera were common in soils from both woody and herbaceous plants (Table S5b).

Discussion

One of the most striking ways that global change is restructuring alpine tundra plant communities is through the replacement of herbaceous plants by woody shrubs and dwarf trees [START_REF] Brandt | Regime shift on the roof of the world: Alpine meadows converting to shrublands in the southern Himalayas[END_REF][START_REF] Formica | Shrub expansion over the past 62 Years in Rocky Mountain Alpine tundra: Possible causes and consequences[END_REF][START_REF] Hallinger | Establishing a missing link: warm summers and winter snow cover promote shrub expansion into alpine tundra in Scandinavia[END_REF]. For example, conversion rates of alpine meadows to woody shrublands were estimated between 39-72% in the large portions of the southern Himalayas [START_REF] Brandt | Regime shift on the roof of the world: Alpine meadows converting to shrublands in the southern Himalayas[END_REF]. Here, using a global, coordinated field study we found that woody plant encroachment is influencing both richness and composition of soil microbial communities but that these changes depend on a combination of abiotic soil conditions, climate, root symbiont types and plant functional traits. This is an important first step in building a more predictive, functional understanding of how climate-driven shifts in woody plant cover will affect soil microbial communities and ecosystem processes worldwide.

Broadly, we did not find one 'global signature' of woody encroachment, but rather that woody encroachment was associated with increased, decreased, and no change in microbial alpha diversity (OTU richness) when comparing with soils of nearby herbaceous plant communities (Fig 2). This likely reflects the broad taxonomic and functional diversity of the woody plant species across these sites, leading to variable litter quality (Table 1,Fig S3). For example, study species included evergreen conifers, deciduous hardwoods, legumes and woody graminoids, highlighting the diversity of woody species expanding into different alpine ecosystems worldwide. However, when accounting for easily measurable characteristics, such as woody plant leaf traits and root symbiont types, consistent patterns emerged for effects of woody plants on both bacterial and fungal richness and community composition.

Woody plant leaf traits modulated shifts in soil microbial communities supporting our first hypothesis. Leaf traits predicted the community composition of both bacteria and fungi in woody plant soils and influenced soil microbial richness indirectly through changes in soil abiotic conditions (pH, soil C:N). Two distinct trait axes influenced microbial community structure. The first axis of the principal components analysis (PC1) was primarily characterized by low SLA, leaf N and δ15N and high LDMC and the second axis (PC2) was primarily characterized by high leaf C and low δ13C (Fig S3). Thus PC1

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This article is protected by copyright. All rights reserved represents variation in leaf economic traits and nitrogen acquisition strategies with low PC1 scores representing more resource-acquisitive species with higher N content and SLA [START_REF] Wright | The worldwide leaf economics spectrum[END_REF]. Moreover, PC2 represents variation in leaf C and water use with high PC2 scores representing species with resource-conservative strategies including high leaf C content and water use efficiency [START_REF] Moreno-Gutiérrez | Isotopes reveal contrasting water use strategies among coexisting plant species in a mediterranean ecosystem[END_REF]. There was a negative relationship between PC2 and soil pH (Fig 4), suggesting that woody plants with higher C content in leaves reduced soil pH, likely due to leaching of organic acids into soil solution via recalcitrant litter [START_REF] Eldridge | Impacts of shrub encroachment on ecosystem structure and functioning: Towards a global synthesis[END_REF][START_REF] Jobbagyl | Patterns and mechanisms of soil acidification in the conversion of grasslands to forests[END_REF]. Consistent with other studies, we also found that soil pH was a strong predictor of both bacterial and fungal richness [START_REF] Lauber | Pyrosequencing-based assessment of soil pH as a predictor of soil bacterial community structure at the continental scale[END_REF][START_REF] Rousk | Soil bacterial and fungal communities across a pH gradient in an arable soil[END_REF], providing a clear mechanism for how woody plant litter chemistry can influence soil microbial diversity. Plant traits also influenced bacterial and fungal community composition, but PC2 was a stronger predictor than PC1 (Table S3), further suggesting that leaf C content is an important determinant of woody encroachment impacts on soil microbial communities.

Woody plants with different root symbiont types (AMF, ECM/ERM, N 2 -fixers) had distinct impacts on soil microbial communities, supporting our second hypothesis. In particular, N 2 -fixing woody species had higher soil fungal richness and lower bacterial richness than both herbaceous soils (within sites) and AMF, ECM/ERM woody plant soils (across sites)(Fig 3a, FigS6a, Table S2). Conversely, ECM-ERM symbionts had higher soil bacterial richness but lower fungal richness than both herbaceous soils (within sites) and N 2 -fixing, AMF woody plant soils (across sites) (Fig 3a,FigS6b,Table S2). Root symbiont type was also an important predictor of both fungal and bacterial community composition (Fig 5b,e, Table S3). Root symbiont types can greatly influence plant resource use strategies, as well as litter chemistry and thus the impact of woody plants on soil microbial communities [START_REF] Cheeke | Dominant mycorrhizal association of trees alters carbon and nutrient cycling by selecting for microbial groups with distinct enzyme function[END_REF][START_REF] Wookey | Ecosystem feedbacks and cascade processes: Understanding their role in the responses of Arctic and alpine ecosystems to environmental change[END_REF]. For example, N 2 -fixing woody plants had higher leaf N content (%) than AMF symbiont types in our study (Fig S5) and thus may be altering soil microbial richness through high N leaf litter. Previous work has shown invasion of N 2 -fixing woody species reduces soil microbial diversity [START_REF] Lorenzo | Differential impact on soil microbes of allelopathic compounds released by the invasive Acacia dealbata Link[END_REF][START_REF] Lorenzo | Effect of invasive Acacia dealbata Link on soil microorganisms as determined by PCR-DGGE[END_REF], which we find to be true for bacteria, however we see the opposite response in fungi. Root symbionts, especially extraradical hyphal forming ecto-and ericoid mycorrhizas, may also interact directly with free-living microbes [START_REF] Bending | Significance of microbial interactions in the mycorrhizosphere[END_REF]. Woody plants utilizing ECM and ERM fungi had higher soil bacterial richness and distinct soil microbial community composition (Fig 3a,5b,e). ECM and ERM fungi release extracellular enzymes and organic acids for decomposition into the rhizosphere which can select for specific bacterial communities [START_REF] Churchland | Specificity of plant-microbe interactions in the tree mycorrhizosphere biome and consequences for soil C cycling[END_REF]. In addition, mycorrhizal helper bacteria (MHB) (Frey-Klett,

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This article is protected by copyright. All rights reserved Garbaye, & Tarkka, 2007) and/or chitinophagous species that feed on dead fungal hyphae may be enhanced in the rhizosphere of ECM and ERM woody plants [START_REF] Brabcová | Dead fungal mycelium in forest soil represents a decomposition hotspot and a habitat for a specific microbial community[END_REF], and several of these taxa were indicator species of woody plant soils in our analysis (Table S5).

While we designated root symbiont types based on current literature and site-specific information, several of the woody plant species in our study can utilize multiple types of root symbionts. For example, Salix spp. [START_REF] Teste | Dual-mycorrhizal plants : their ecology and relevance[END_REF] and Juniperus communis [START_REF] Thomas | Biological Flora of the British Isles : Juniperus communis L[END_REF]) can be dually colonized by ECM and AMF, and the relative abundance of each mycorrhizal type often differs across habitats, with alpine Salix varieties being more ECM dominant [START_REF] Dhillion | Ectomycorrhizae , Arbuscular Mycorrhizae , and Rhizoctonia sp . of Alpine and Boreal Salix spp . in Norway. Arctic[END_REF]. In addition, Nitrogen fixers may utilize different bacterial symbionts; for example, Alnus alnobetula is an actinorhizal species which associates with bacteria in the genus Frankia [START_REF] Richardson | Plant invasionsthe role of mutualisms[END_REF], while Echinospartum horridum is a legume which associates with bacterial species in the genus Rhizobium [START_REF] Komac | Influence of topography on the colonization of subalpine grasslands by the thorny cushion dwarf Echinospartum horridum[END_REF]. Rhizobial strains are considered more host-specific than Frankia, and N 2 -fixing plant species may also have cooccurring AMF or ECM fungi [START_REF] Teste | Dual-mycorrhizal plants : their ecology and relevance[END_REF]. Despite these discrepancies, these very broad categories still proved to be useful predictors of complex soil microbial communities undergoing woody plant encroachment.

Soil abiotic conditions influenced microbial communities, supporting our third hypothesis, and soil pH was the most consistent driver of soil microbial richness (Fig 3, Table S2) and community composition (Table S3). Further, abiotic conditions were influenced by woody plant leaf traits, suggesting that woody plants affect soil microbial communities indirectly through changes in abiotic soil conditions (Fig 4). For example, soil pH had a positive effect on both fungal and bacterial richness and was the best predictor of bacterial community composition (Fig 3a,5f). As described previously, there was also a negative relationship between woody plant leaf traits, particularly leaf C content, and pH (Fig 4). Soil pH is a consistently strong predictor of microbial community structure [START_REF] Lauber | Pyrosequencing-based assessment of soil pH as a predictor of soil bacterial community structure at the continental scale[END_REF][START_REF] Rousk | Soil bacterial and fungal communities across a pH gradient in an arable soil[END_REF], however it is often framed as an abiotic driver decoupled from plant litter chemistry. Soil C:N had a negative effect on fungal richness and also influenced fungal and bacterial community composition (Fig 3a,Table S3). On the other hand, Soil C:N was negatively associated with N related leaf traits (PC1) , however the direction of this relationship was the opposite of what we predicted (Fig 4). This may be due to the fact that in low N environments such as the alpine, N mineralization is very low and direct microbial uptake of organic N from is high [START_REF] Schimel | Nitrogen mineralization: Challenges of a changing paradigm[END_REF], potentially weakening the link between leaf N traits and soil C:N. Finally, VWC had a positive effect on bacterial richness, and influenced microbial and fungal community composition (Fig 3a, Table S3), however unlike our initial

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This article is protected by copyright. All rights reserved prediction, soils from beneath woody plants had slightly lower VWC (Table S2). Thus, woody plants may be depleting soil moisture as compared to herbaceous vegetation through deeper roots, or via accessing water later into the growing season (Acharya, Kharel, Zou, Wilcox, & Halihan, 2018;Awada et al., 2013). Overall, these patterns highlight that woody plant effects on abiotic soil conditions are an important indirect pathway between woody plant encroachment and soil microbial community structure.

While changing climate is among the major drivers of woody plant encroachment, our results demonstrate that woody encroachment may also modulate climate effects on soil microbes. In support of our fourth hypothesis, the effects of woody plants interacted with climate at the site level, including interactions between vegetation type and MAP, MAT on fungal and bacterial richness (Fig 3,Table S2). This suggests that soil microbial communities undergoing woody encroachment are more distinct from those of herbaceous plants at the more extreme ends of temperature and precipitation gradients (Fig 3 b,c). Fungal richness was more sensitive to the precipitation by vegetation type interaction, which is consistent with previous work showing MAP to be the best predictor of fungal richness worldwide [START_REF] Tedersoo | Disentangling global soil fungal diversity[END_REF]. Bacterial richness was more sensitive to the temperature by vegetation type interaction, likely because bacteria tend to be less cold tolerant than fungi, and fewer strains can maintain their biomass under winter snowpack [START_REF] Lazzaro | Structures of microbial communities in alpine soils: Seasonal and elevational effects[END_REF][START_REF] Zinger | Microbial diversity in alpine tundra soils correlates with snow cover dynamics[END_REF]. Furthermore, MAT was one of the best predictors of fungal richness overall and MAP was among the top predictors of both fungal and bacterial community composition (Fig 3a,Fig 5c,Table S3), emphasizing the strong influence of climate on soil microbial communities in alpine environments. All together, we find that woody encroachment can significantly influence how soil microbial communities respond to temperature and precipitation and may alter both the magnitude and influence of the climate driver. Thus, future predictions of climate impacts on alpine soil microbial communities must also consider co-occurring shifts in plant community structure.

Due to this study's observational rather than experimental approach, we cannot conclusively state that observed differences in soil microbial communities are in response to woody plant encroachment rather than a potential cause of woody plant establishment. However, there are several reasons why we believe the former to be true. First, soil microbial communities were highly correlated with attributes of the woody plants themselves, including leaf traits, root symbiont type, and soil abiotic conditions related to litter chemistry. In addition, we selected sites where woody plant encroachment began within the last 50 years, and at most sites, woody encroachment has been present for between 30-40 years. In a previous study, alpine soil microbial communities reflected the transition from a woody to herbaceous plant community in under 5 years [START_REF] Collins | Direct and indirect effects of native range expansion on soil microbial community structure and function[END_REF] and thus we believe our sampling interval

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This article is protected by copyright. All rights reserved provides sufficient time for woody plants to have cultivated distinct soil communities. Next, our analysis of soil microbial community composition has focused on the saprotrophic, generalist species which are most abundant in bulk soil and unlikely to directly influence plant community composition [START_REF] Fierer | Embracing the unknown: Disentangling the complexities of the soil microbiome[END_REF]. This analysis does not test for species-specific soil mutualists or pathogens, the taxa which most strongly influence the success of plant establishment and range expansion [START_REF] Mccarthy-Neumann | Tree range expansion may be enhanced by escape from negative plant-soil feedbacks[END_REF][START_REF] Nuñez | Lack of belowground mutualisms hinders Pinaceae invasions[END_REF][START_REF] Tomiolo | Species migrations and range shifts: A synthesis of causes and Author Manuscript This article is protected by copyright. All rights reserved consequences[END_REF]. Finally, while all soils were collected during the growing season (alpine summer), sampling times varied among sites due to differences in growing season length and snowmelt timing. Differences in sampling time can influence site-specific patterns in soil microbial communities [START_REF] Bjork | Temporal variation in soil microbial communities in Alpine tundra[END_REF][START_REF] Lazzaro | Structures of microbial communities in alpine soils: Seasonal and elevational effects[END_REF][START_REF] Lipson | Seasonal Changes in an Alpine Soil Bacterial Community in the Colorado Rocky Mountains[END_REF]), yet despite this, we observed many consistent patterns across sites in response to woody encroachment, suggesting that vegetation strongly influences soil microbial community structure in alpine ecosystems.

This study documents the global impacts of woody plant encroachment on soil microbial communities, but we emphasize that multiple pathways must be considered to disentangle these impacts. Specifically, divergent functional trait strategies and functional groups of woody plants based on root symbionts have consistent impacts belowground regardless of woody plant species or site. In addition, the influence of woody plants on soil microbes can be indirect through changes in the soil abiotic environment, such as reduced soil pH driven by high C content of woody plant litter. Finally, woody encroachment can influence both the direction and magnitude of direct climate effects on microbial richness, and bacteria and fungi respond to distinct climate and woody plant drivers. Our work highlights the complexity of plant-soil interactions in rapidly changing alpine ecosystems, an understanding that will influence our ability to predict feedbacks to terrestrial ecosystem function and climate, particularly the global C cycle, where soil microbes play an integral role.

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This article is protected by copyright. All rights reserved Fig 1 . Map and images of 13 alpine woody encroachment sites included in this study. Sites span 10 countries and 4 continents. See Table 1 for further information. Asterisks denote probabilities that the effect of a parameter is greater or less than zero based on credible intervals (*** = probability> 95%; ** = probability> 90%; * = probability > 85%). Parameter estimates and credible intervals are listed in Table S2. All values are standard normalized as was done prior to modeling. b,c) Interactions between vegetation type and mean annual precipitation (MAP) and mean annual temperature (MAT) on fungal and bacterial richness. Points are raw data, lines are fitted model estimates, and all values are standard normalized. Interactions showed that encroachment by woody plants lead to increased, decreased fungal richness in sites with lower, higher precipitation and increased, decreased bacterial richness in sites with lower, higher temperature as compared to herbaceous plant communities. All values are standard normalized as was done prior to modeling

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This article is protected by copyright. All rights reserved microbial group (MAP-Fungi and soil pH-Bacteria) is plotted on the right with a color ramp for continuous values. Model parameter estimates are listed in Table S3. Tables andFigures Table 1

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  General Model: Alpha = (1|)+ * + *+ = (1|)+ BRMS model syntax = OTU richness ~ (1|site) + Symbiont*Vegetation type+ MAT*Vegetation type + MAP*Vegetation type + VWC + pH + soilC:N soilC:N~ (1 | site) + PC Axis1 (leaf traits) + PC Axis2 (leaf traits) pH ~ (1 | site) + PC Axis1 (leaf traits) + PC Axis2 (leaf traits) VWC ~ (1 | site) + Vegetation type Beta diversity (Community composition)

  Beta = Woody leaf traits Adonis model syntax = Bray Curtis/Unifrac distance ~ Vegetation type, strata=site Bray Curtis/Unifrac distance ~ Symbiont + MAT + MAP + VWC + pH + soilC:N , strata=vegetation type Bray Curtis/Unifrac distance ~ PC Axis1 (leaf traits) + PC Axis2 (leaf traits) Taxonomic analyses

Fig 2 .

 2 Fig 2.Box and whisker plots of soil a) fungal and b) bacterial OTU richness (logged) and NMDS ordination plots of soil c) fungal (stress =0.13) and d) bacteria (stress =0.11) beta diversity (community composition) at each site. For richness, box fill color designates whether the soil was sampled in woody encroached or herbaceous plant community and box outline color designates the root symbiont type of the woody plant at each site. Here both fungal and bacterial richness are plotted on the log scale for consistency but we only logged bacterial richness in Bayesian models. For beta diversity, colored ovals represent 95% confidence intervals of sample ordination grouped by sampling site and shapes represent the vegetation community (woody or herbaceous) of each soil sample.

Fig 4 .

 4 Fig 4. Diagram of impacts of woody plant leaf traits on bacterial and fungal richness via changes in soil abiotic conditions based on the Bayesian SEM. Red lines show significant negative relationships and blue lines show significant positive relationships. Slope coefficients (standardized) show the magnitude and line thickness reflects the associated credible interval of each relationship (85%, 90%, 95%). Leaf traits shown in each corner reflect loadings on each Principal coordinates (PC) axis. Parameter estimates and credible intervals are listed in table S2 and trait loadings are shown in Fig S3.

  Fig 1.

  Fig 2.

  Fig 4.

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.

  Woody Encroachment study sites included in this synthesis and corresponding information. Symbiont type refers to root microbial symbionts of woody plant species Arbuscular mycorrhizal (AMF), Ecto-or Ericoid mycorrhizal (ECM.ERM) and N 2 -fixing bacterial (Nfix). Reference manuscripts describe woody encroachment patterns at each site.

	Mexico	19.064165 -97.2669115 4110.500 AMF	Chionolaena	Ramírez-
			lavandulifolia	Amezcua et
				al. 2016
	Site China Colombia Czech Rep France Italy Japan Spain Spain Ordesa Sweden Switzerland 46.621100 Latitude 33.66536 101.8663515 3506.000 AMF Longitude Elevation (m) Symbiont type 4.792977 -75.4254868 4024.000 AMF 50.768887 15.5398797 1343.749 ECM.ERM Pinus mugo Woody species Potentilla fruticosa Hesperomeles obtusifolia 45.421500 6.1780400 1797.946 Nfix Alnus alnobetula 46.673611 10.5919444 2357.600 ECM.ERM Rhododendron ferrugineum 43.563258 142.9011030 1771.600 AMF Sasa kurilensis Kudo et al Reference Klein et al. 2007 Matson and Bart 2013 Soukupová et al. 1995 Anthelme et al. 2007 Cannone et al. 2007 2011 42.575821 1.3667150 2100.000 AMF Juniperus communis Montané et al. 2007 42.602807 0.0332073 1942.007 Nfix Echinospartum horridum Komac et al. 2011 68.360658 18.7368890 740.000 ECM.ERM Salix lapponum Rundqvist et al. 2011 8.6349430 1598.800 Nfix Alnus alnobetula Caviezel et al. 2014 US CA 37.576447 -118.240913 3750.000 AMF Artemisia rothrockii Kopp and Cleland 2014 US CO 40.153600 -105.670750 3530.000 ECM.ERM Salix glauca Bueno de Mesquita et Author Manuscript al. 2018

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Acknowledgements

This research was funded by an NSF Doctoral Dissertation Improvement Grant (DDIG) (Award No. (FAIN):

1701979) awarded to C. Collins and J. Diez. C. Collins was also supported by a UC President's Dissertation Year Fellowship and a UCR Graduate Dean's Dissertation Research Grant. M. Spasojevic was supported by the Niwot Ridge LTER (NSF DEB-1637686). A. Stokes and F. Reverchon were supported by the French and Mexican governments (ECOPICS project, ANR-16-CE03-0009 and CONACYT-2 73659). J. Mullerová was supported by a long-term research development project RVO 67985939 (The Czech Academy of Sciences) and Fulbright Grant. C. Alados was supported by the Ministerio de Economía y Competitividad-MINECO Project Nº: CGL2016-80783-R. Oriol Grau was supported by the ERC Synergy project, SyG-2013-610028 IMBALANCE-P and an INTERACT grant agreement No: 730938 EU-H2020. Jason Stajich is a CIFAR Fellow in the program Fungal Kingdom: Threats and Opportunities and supported by United States Department of Agriculture -National Institute of Food and Agriculture

Hatch project CA-R-PPA-5062-H. Nuttapon Pombubpa was supported by a Royal Thai Government Fellowship. JCB acknowledges the support of Javeriana University. We thank Maximillien Osbourne-Thacker, Amulya Kunduru, and Chloe Hull for assistance with processing soil samples and molecular sequencing prep. We thank the following for assistance with site selection, plant identification, and soil sampling: Nevados National Park in Colombia and its staff, Katrin Sieron, Marco Morales, Leonor Jiménez, Daniel Hernández, Fabien Anthelme, Luis Merino-Martin, and Miguel Castillo.

Data Availability

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This article is protected by copyright. All rights reserved All raw data and analysis scripts for thus study may be found at the following repository: https://github.com/cour10eygrace/woody-encroachment-microbes.git. Raw Sequences may be found in the NCBI Short Read Archive (SRA) accession # PRJNA659596.

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