Chemodiversity of riverine dissolved organic matter: Effects of local environments and watershed characteristics.

Riverine dissolved organic matter (DOM) is crucial to global carbon cycling and aquatic ecosystems. However, the geographical patterns and environmental drivers of DOM chemodiversity remain elusive especially in the waters and sediments of continental rivers. Here, we systematically analyzed DOM molecular diversity and composition in surface waters and sediments across 97 broadly distributed rivers using data from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium. We further examined the associations of molecular richness and composition with geographical, climatic, physicochemical variables, as well as the watershed characteristics. We found that molecular richness significantly decreased toward higher latitudes, but only in sediments (r = -0.24, p < 0.001). The environmental variables like precipitation and non-purgeable organic carbon showed strong associations with DOM molecular richness and composition. Interestingly, we identified that less-documented factors like watershed characteristics were also related to DOM molecular richness and composition. For instance, DOM molecular richness was positively correlated with the soil sand fraction for waters, while with the percentage of forest for sediments. Importantly, the effects of watershed characteristics on DOM molecular richness and composition were generally stronger in waters than sediments. This phenomenon was further supported by the fact that 11 out of 13 watershed characteristics (e.g., the percentages of impervious area and cropland) showed more positive than negative correlations with molecular abundance especially in waters. As the percentage of forest increased, there was a continuous accumulation of the compounds with higher molecular weight, aromaticity, and degree of unsaturation. In contrast, human activities accumulated the compounds with lower molecular weight and oxygenation, and higher bioavailability. Our findings imply that it may be possible to use a small set of broadly available data types to predict DOM molecular richness and composition across diverse river systems. Elucidation of mechanisms underlying these relationships will provide further enhancements to such predictions, especially when extrapolating to unsampled systems.

Microdiverse bacterial clades prevail across Antarctic wetlands.

Antarctica's extreme environmental conditions impose selection pressures on microbial communities. Indeed, a previous study revealed that bacterial assemblages at the Cierva Point Wetland Complex (CPWC) are shaped by strong homogeneous selection. Yet which bacterial phylogenetic clades are shaped by selection processes and their ecological strategies to thrive in such extreme conditions remain unknown. Here, we applied the phyloscore and feature-level ßNTI indexes coupled with phylofactorization to successfully detect bacterial monophyletic clades subjected to homogeneous (HoS) and heterogenous (HeS) selection. Remarkably, only the HoS clades showed high relative abundance across all samples and signs of putative microdiversity. The majority of the amplicon sequence variants (ASVs) within each HoS clade clustered into a unique 97% sequence similarity operational taxonomic unit (OTU) and inhabited a specific environment (lotic, lentic or terrestrial). Our findings suggest the existence of microdiversification leading to sub-taxa niche differentiation, with putative distinct ecotypes (consisting of groups of ASVs) adapted to a specific environment. We hypothesize that HoS clades thriving in the CPWC have phylogenetically conserved traits that accelerate their rate of evolution, enabling them to adapt to strong spatio-temporally variable selection pressures. Variable selection appears to operate within clades to cause very rapid microdiversification without losing key traits that lead to high abundance. Variable and homogeneous selection, therefore, operate simultaneously but on different aspects of organismal ecology. The result is an overall signal of homogeneous selection due to rapid within-clade microdiversification caused by variable selection. It is unknown whether other systems experience this dynamic, and we encourage future work evaluating the transferability of our results.

Rethinking Aerobic Respiration in the Hyporheic Zone under Variation in Carbon and Nitrogen Stoichiometry.

Hyporheic zones (HZs)─zones of groundwater-surface water mixing─are hotspots for dissolved organic matter (DOM) and nutrient cycling that can disproportionately impact aquatic ecosystem functions. However, the mechanisms affecting DOM metabolism through space and time in HZs remain poorly understood. To resolve this gap, we investigate a recently proposed theory describing trade-offs between carbon (C) and nitrogen (N) limitations as a key regulator of HZ metabolism. We propose that throughout the extent of the HZ, a single process like aerobic respiration (AR) can be limited by both DOM thermodynamics and N content due to highly variable C/N ratios over short distances (centimeter scale). To investigate this theory, we used a large flume, continuous optode measurements of dissolved oxygen (DO), and spatially and temporally resolved molecular analysis of DOM. Carbon and N limitations were inferred from changes in the elemental stoichiometric ratio. We show sequential, depth-stratified relationships of DO with DOM thermodynamics and organic N that change across centimeter scales. In the shallow HZ with low C/N, DO was associated with the thermodynamics of DOM, while deeper in the HZ with higher C/N, DO was associated with inferred biochemical reactions involving organic N. Collectively, our results suggest that there are multiple competing processes that limit AR in the HZ. Resolving this spatiotemporal variation could improve predictions from mechanistic models, either via more highly resolved grid cells or by representing AR colimitation by DOM thermodynamics and organic N.

A functional microbiome catalog crowdsourced from North American rivers.

Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires understanding the spatial drivers of river microbiomes. However, the unifying microbial processes governing river biogeochemistry are hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we employed a community science effort to accelerate the sampling, sequencing, and genome-resolved analyses of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). This resource profiled the identity, distribution, function, and expression of thousands of microbial genomes across rivers covering 90% of United States watersheds. Specifically, GROWdb encompasses 1,469 microbial species from 27 phyla, including novel lineages from 10 families and 128 genera, and defines the core river microbiome for the first time at genome level. GROWdb analyses coupled to extensive geospatial information revealed local and regional drivers of microbial community structuring, while also presenting a myriad of foundational hypotheses about ecosystem function. Building upon the previously conceived River Continuum Concept 1 , we layer on microbial functional trait expression, which suggests the structure and function of river microbiomes is predictable. We make GROWdb available through various collaborative cyberinfrastructures 2, 3 so that it can be widely accessed across disciplines for watershed predictive modeling and microbiome-based management practices.

Metabolic multireactor: Practical considerations for using simple oxygen sensing optodes for high-throughput batch reactor metabolism experiments.

We present a system for carrying out small batch reactor oxygen consumption experiments on water and sediment samples for environmental questions. In general, it provides several advantages that can help researchers achieve impactful experiments at relatively low costs and high data quality. In particular, it allows for multiple reactors to be operated and their oxygen concentrations to be measured simultaneously, providing high throughput and high time-resolution data, which can be advantageous. Most existing literature on similar small batch-reactor metabolic studies is limited to either only a few samples, or only a few time points per sample, which can restrict the ability for researchers to learn from their experiments. The oxygen sensing system is based very directly on the work of Larsen, et al. [2011], and similar oxygen sensing technology is widely used in the literature. As such we do not delve deeply into the specifics of the fluorescent dye sensing mechanism. Instead, we focus on practical considerations. We describe the construction and operation of the calibration and experimental systems, and answer many of the questions likely to come up when other researchers choose to build and operate a similar system themselves (questions we ourselves had when we first built the system). In this way, we hope to provide an approachable and easy to use research article that can help other researchers construct and operate a similar system that can be tailored to ask their own research questions, with a minimum of confusion and missteps along the way.

Coordination and divergence in community assembly processes across co-occurring microbial groups separated by cell size.

Setting the pace of life and constraining the role of members in food webs, body size can affect the structure and dynamics of communities across multiple scales of biological organization (e.g., from the individual to the ecosystem). However, its effects on shaping microbial communities, as well as underlying assembly processes, remain poorly known. Here, we analyzed microbial diversity in the largest urban lake in China and disentangled the ecological processes governing microbial eukaryotes and prokaryotes using 16S and 18S amplicon sequencing. We found that pico/nano-eukaryotes (0.22-20 µm) and micro-eukaryotes (20-200 µm) showed significant differences in terms of both community composition and assembly processes even though they were characterized by similar phylotype diversity. We also found scale dependencies whereby micro-eukaryotes were strongly governed by environmental selection at the local scale and dispersal limitation at the regional scale. Interestingly, it was the micro-eukaryotes, rather than the pico/nano-eukaryotes, that shared similar distribution and community assembly patterns with the prokaryotes. This indicated that assembly processes of eukaryotes may be coupled or decoupled from prokaryotes' assembly processes based on eukaryote cell size. While the results support the important influence of cell size, there may be other factors leading to different levels of assembly process coupling across size classes. Additional studies are needed to quantitatively parse the influence of cell size versus other factors as drivers of coordinated and divergent community assembly processes across microbial groups. Regardless of the governing mechanisms, our results show that there are clear patterns in how assembly processes are coupled across sub-communities defined by cell size. These size-structured patterns could be used to help predict shifts in microbial food webs in response to future disturbance.

Laboratory evaluation of open source and commercial electrical conductivity sensor precision and accuracy: How do they compare?

Variation in the electrical conductivity (EC) of water can reveal environmental disturbance and natural dynamics, including factors such as anthropogenic salinization. Broader application of open source (OS) EC sensors could provide an inexpensive method to measure water quality. While studies show that other water quality parameters can be robustly measured with sensors, a similar effort is needed to evaluate the performance of OS EC sensors. To address this need, we evaluated the accuracy (mean error, %) and precision (sample standard deviation) of OS EC sensors in the laboratory via comparison to EC calibration standards using three different OS and OS/commercial-hybrid (OS/C) EC sensors and data logger configurations and two commercial (C) EC sensors and data logger configurations. We also evaluated the effect of cable length (7.5 m and 30 m) and sensor calibration on OS sensor accuracy and precision. We found a significant difference between OS sensor mean accuracy (3.08%) and all other sensors combined (9.23%). Our study also found that EC sensor precision decreased across all sensor configurations with increasing calibration standard EC. There was also a significant difference between OS sensor mean precision (2.85 µS/cm) and the mean precision of all other sensors combined (9.12 µS/cm). Cable length did not affect OS sensor precision. Furthermore, our results suggest that future research should include evaluating how performance is impacted by combining OS sensors with commercial data loggers as this study found significantly decreased performance in OS/commercial-hybrid sensor configurations. To increase confidence in the reliability of OS sensor data, more studies such as ours are needed to further quantify OS sensor performance in terms of accuracy and precision across different settings and OS sensor and data collection platform configurations.

Spatial and temporal metagenomics of river compartments reveals viral community dynamics in an urban impacted stream.

Although river ecosystems comprise less than 1% of Earth's total non-glaciated area, they are critical modulators of microbially and virally orchestrated global biogeochemical cycles. However, most studies either use data that is not spatially resolved or is collected at timepoints that do not reflect the short life cycles of microorganisms. As a result, the relevance of microbiome interactions and the impacts they have over time on biogeochemical cycles are poorly understood. To assess how viral and microbial communities change over time, we sampled surface water and pore water compartments of the wastewater-impacted River Erpe in Germany every 3 hours over a 48-hour period resulting in 32 metagenomes paired to geochemical and metabolite measurements. We reconstructed 6,500 viral and 1,033 microbial genomes and found distinct communities associated with each river compartment. We show that 17% of our vMAGs clustered to viruses from other ecosystems like wastewater treatment plants and rivers. Our results also indicated that 70% of the viral community was persistent in surface waters, whereas only 13% were persistent in the pore waters taken from the hyporheic zone. Finally, we predicted linkages between 73 viral genomes and 38 microbial genomes. These putatively linked hosts included members of the Competibacteraceae, which we suggest are potential contributors to carbon and nitrogen cycling. Together, these findings demonstrate that microbial and viral communities in surface waters of this urban river can exist as stable communities along a flowing river; and raise important considerations for ecosystem models attempting to constrain dynamics of river biogeochemical cycles.

Vertical Hydrologic Exchange Flows Control Methane Emissions from Riverbed Sediments.

CH4 emissions from inland waters are highly uncertain in the current global CH4 budget, especially for streams, rivers, and other lotic systems. Previous studies have attributed the strong spatiotemporal heterogeneity of riverine CH4 to environmental factors such as sediment type, water level, temperature, or particulate organic carbon abundance through correlation analysis. However, a mechanistic understanding of the basis for such heterogeneity is lacking. Here, we combine sediment CH4 data from the Hanford reach of the Columbia River with a biogeochemical-transport model to show that vertical hydrologic exchange flows (VHEFs), driven by the difference between river stage and groundwater level, determine CH4 flux at the sediment-water interface. CH4 fluxes show a nonlinear relationship with the magnitude of VHEFs, where high VHEFs introduce O2 into riverbed sediments, which inhibit CH4 production and induce CH4 oxidation, and low VHEFs cause transient reduction in CH4 flux (relative to production) due to reduced advective CH4 transport. In addition, VHEFs lead to the hysteresis of temperature rise and CH4 emissions because high river discharge caused by snowmelt in spring leads to strong downwelling flow that offsets increasing CH4 production with temperature rise. Our findings reveal how the interplay between in-stream hydrologic flux besides fluvial-wetland connectivity and microbial metabolic pathways that compete with methanogenic pathways can produce complex patterns in CH4 production and emission in riverbed alluvial sediments.

RNA Viruses Linked to Eukaryotic Hosts in Thawed Permafrost.

Arctic permafrost is thawing due to global warming, with unknown consequences on the microbial inhabitants or associated viruses. DNA viruses have previously been shown to be abundant and active in thawing permafrost, but little is known about RNA viruses in these systems. To address this knowledge gap, we assessed the composition of RNA viruses in thawed permafrost samples that were incubated for 97 days at 4°C to simulate thaw conditions. A diverse RNA viral community was assembled from metatranscriptome data including double-stranded RNA viruses, dominated by Reoviridae and Hypoviridae, and negative and positive single-stranded RNA viruses, with relatively high representations of Rhabdoviridae and Leviviridae, respectively. Sequences corresponding to potential plant and human pathogens were also detected. The detected RNA viruses primarily targeted dominant eukaryotic taxa in the samples (e.g., fungi, Metazoa and Viridiplantae) and the viral community structures were significantly associated with predicted host populations. These results indicate that RNA viruses are linked to eukaryotic host dynamics. Several of the RNA viral sequences contained auxiliary metabolic genes encoding proteins involved in carbon utilization (e.g., polygalacturosase), implying their potential roles in carbon cycling in thawed permafrost. IMPORTANCE Permafrost is thawing at a rapid pace in the Arctic with largely unknown consequences on ecological processes that are fundamental to Arctic ecosystems. This is the first study to determine the composition of RNA viruses in thawed permafrost. Other recent studies have characterized DNA viruses in thawing permafrost, but the majority of DNA viruses are bacteriophages that target bacterial hosts. By contrast RNA viruses primarily target eukaryotic hosts and thus represent potential pathogenic threats to humans, animals, and plants. Here, we find that RNA viruses in permafrost are novel and distinct from those in other habitats studied to date. The COVID-19 pandemic has heightened awareness of the importance of potential environmental reservoirs of emerging RNA viral pathogens. We demonstrate that some potential pathogens were detected after an experimental thawing regime. These results are important for understanding critical viral-host interactions and provide a better understanding of the ecological roles that RNA viruses play as permafrost thaws.

Genome-Resolved Metaproteomics Decodes the Microbial and Viral Contributions to Coupled Carbon and Nitrogen Cycling in River Sediments.

Rivers have a significant role in global carbon and nitrogen cycles, serving as a nexus for nutrient transport between terrestrial and marine ecosystems. Although rivers have a small global surface area, they contribute substantially to worldwide greenhouse gas emissions through microbially mediated processes within the river hyporheic zone. Despite this importance, research linking microbial and viral communities to specific biogeochemical reactions is still nascent in these sediment environments. To survey the metabolic potential and gene expression underpinning carbon and nitrogen biogeochemical cycling in river sediments, we collected an integrated data set of 33 metagenomes, metaproteomes, and paired metabolomes. We reconstructed over 500 microbial metagenome-assembled genomes (MAGs), which we dereplicated into 55 unique, nearly complete medium- and high-quality MAGs spanning 12 bacterial and archaeal phyla. We also reconstructed 2,482 viral genomic contigs, which were dereplicated into 111 viral MAGs (vMAGs) of >10 kb in size. As a result of integrating gene expression data with geochemical and metabolite data, we created a conceptual model that uncovered new roles for microorganisms in organic matter decomposition, carbon sequestration, nitrogen mineralization, nitrification, and denitrification. We show how these metabolic pathways, integrated through shared resource pools of ammonium, carbon dioxide, and inorganic nitrogen, could ultimately contribute to carbon dioxide and nitrous oxide fluxes from hyporheic sediments. Further, by linking viral MAGs to these active microbial hosts, we provide some of the first insights into viral modulation of river sediment carbon and nitrogen cycling. IMPORTANCE Here we created HUM-V (hyporheic uncultured microbial and viral), an annotated microbial and viral MAG catalog that captures strain and functional diversity encoded in these Columbia River sediment samples. Demonstrating its utility, this genomic inventory encompasses multiple representatives of dominant microbial and archaeal phyla reported in other river sediments and provides novel viral MAGs that can putatively infect these. Furthermore, we used HUM-V to recruit gene expression data to decipher the functional activities of these MAGs and reconstruct their active roles in Columbia River sediment biogeochemical cycling. Ultimately, we show the power of MAG-resolved multi-omics to uncover interactions and chemical handoffs in river sediments that shape an intertwined carbon and nitrogen metabolic network. The accessible microbial and viral MAGs in HUM-V will serve as a community resource to further advance more untargeted, activity-based measurements in these, and related, freshwater terrestrial-aquatic ecosystems.

Continental-scale niche differentiation of dominant topsoil archaea in drylands.

Archaea represent a diverse group of microorganisms often associated with extreme environments. However, an integrated understanding of biogeographical patterns of the specialist Haloarchaea and the potential generalist ammonia-oxidizing archaea (AOA) across large-scale environmental gradients remains limited. We hypothesize that niche differentiation determines their distinct distributions along environmental gradients. To test the hypothesis, we use a continental-scale research network including 173 dryland sites across northern China. Our results demonstrate that Haloarchaea and AOA dominate topsoil archaeal communities. As hypothesized, Haloarchaea and AOA show strong niche differentiation associated with two ecosystem types mainly found in China's drylands (i.e. deserts vs. grasslands), and they differ in the degree of habitat specialization. The relative abundance and richness of Haloarchaea are higher in deserts due to specialization to relatively high soil salinity and extreme climates, while those of AOA are greater in grassland soils. Our results further indicate a divergence in ecological processes underlying the segregated distributions of Haloarchaea and AOA. Haloarchaea are governed primarily by environmental-based processes while the more generalist AOA are assembled mostly via spatial-based processes. Our findings add to existing knowledge of large-scale biogeography of topsoil archaea, advancing our predictive understanding on changes in topsoil archaeal communities in a drier world.

Disinfection byproducts formed during drinking water treatment reveal an export control point for dissolved organic matter in a subalpine headwater stream.

Changes in climate, season, and vegetation can alter organic export from watersheds. While an accepted tradeoff to protect public health, disinfection processes during drinking water treatment can adversely react with organic compounds to form disinfection byproducts (DBPs). By extension, DBP monitoring can yield insights into hydrobiogeochemical dynamics within watersheds and their implications for water resource management. In this study, we analyzed temporal trends from a water treatment facility that sources water from Coal Creek in Crested Butte, Colorado. These trends revealed a long-term increase in haloacetic acid and trihalomethane formation over the period of 2005-2020. Disproportionate export of dissolved organic carbon and formation of DBPs that exceeded maximum contaminant levels were consistently recorded in association with late spring freshet. Synoptic sampling of the creek in 2020 and 2021 identified a biogeochemical hotspot for organic carbon export in the upper domain of the watershed that contained a prominent fulvic acid-like fluorescent signature. DBP formation potential analyses from this domain yielded similar ratios of regulated DBP classes to those formed at the drinking water facility. Spectrometric qualitative analyses of pre and post-reacted waters with hypochlorite indicated lignin-like and condensed hydrocarbon-like molecules were the major reactive chemical classes during chlorine-based disinfection. This study demonstrates how drinking water quality archives combined with synoptic sampling and targeted analyses can be used to identify and understand export control points for dissolved organic matter. This approach could be applied to identify and characterize analogous watersheds where seasonal or climate-associated organic matter export challenge water treatment disinfection and by extension inform watershed management and drinking water treatment.

Implications of sample treatment on characterization of riverine dissolved organic matter.

High-resolution mass spectrometry techniques are widely used in the environmental sciences to characterize natural organic matter and, when utilizing these instruments, researchers must make multiple decisions regarding sample pre-treatment and the instrument ionization mode. To identify how these choices alter organic matter characterization and resulting conclusions, we analyzed a collection of 17 riverine samples from East River, CO (USA) under four PPL-based Solid Phase Extraction (SPE) treatment and electrospray ionization polarity (e.g., positive and negative) combinations: SPE (+), SPE (-), non-SPE (-), and non-SPE (+). The greatest number of formula assignments were achieved with SPE-treated samples due to the removal of compounds that could interfere with ionization. Furthermore, the SPE (-) treatment captured the most formulas across the widest chemical compound diversity. In addition to a reduced number of assigned formulas, the non-SPE datasets resulted in altered thermodynamic interpretations that could cascade into incomplete assumptions about the availability of organic matter pools for heterotrophic microbial respiration. Thus, we infer that the SPE (-) treatment is the best single method for characterizing environmental organic matter pools unless the focus is on lipid-like compounds, in which case we recommend a combination of SPE (-) and SPE (+) to adequately characterize these molecules.

Inferring the Contribution of Microbial Taxa and Organic Matter Molecular Formulas to Ecological Assembly.

Understanding the mechanisms underlying the assembly of communities has long been the goal of many ecological studies. While several studies have evaluated community wide ecological assembly, fewer have focused on investigating the impacts of individual members within a community or assemblage on ecological assembly. Here, we adapted a previous null model ß-nearest taxon index (ßNTI) to measure the contribution of individual features within an ecological community to overall assembly. This new metric, called feature-level ßNTI (ßNTIfeat), enables researchers to determine whether ecological features (e.g., individual microbial taxa) contribute to divergence, convergence, or have insignificant impacts across spatiotemporally resolved metacommunities or meta-assemblages. Using ßNTIfeat, we revealed that unclassified microbial lineages often contributed to community divergence while diverse groups (e.g., Crenarchaeota, Alphaproteobacteria, and Gammaproteobacteria) contributed to convergence. We also demonstrate that ßNTIfeat can be extended to other ecological assemblages such as organic molecules comprising organic matter (OM) pools. OM had more inconsistent trends compared to the microbial community though CHO-containing molecular formulas often contributed to convergence, while nitrogen and phosphorus-containing formulas contributed to both convergence and divergence. A network analysis was used to relate ßNTIfeat values from the putatively active microbial community and the OM assemblage and examine potentially common contributions to ecological assembly across different communities/assemblages. This analysis revealed that P-containing formulas often contributed to convergence/divergence separately from other ecological features and N-containing formulas often contributed to assembly in coordination with microorganisms. Additionally, members of Family Geobacteraceae were often observed to contribute to convergence/divergence in conjunction with both N- and P-containing formulas, suggesting a coordinated ecological role for family members and the nitrogen/phosphorus cycle. Overall, we show that ßNTIfeat offers opportunities to investigate the community or assemblage members, which shape the phylogenetic or functional landscape, and demonstrate the potential to evaluate potential points of coordination across various community types.

The ecological assembly of bacterial communities in Antarctic wetlands varies across levels of phylogenetic resolution.

As functional traits are conserved at different phylogenetic depths, the ability to detect community assembly processes can be conditional on the phylogenetic resolution; yet most previous work quantifying their influence has focused on a single level of phylogenetic resolution. Here, we have studied the ecological assembly of bacterial communities from an Antarctic wetland complex, applying null models across different levels of phylogenetic resolution (i.e. clustering ASVs into OTUs with decreasing sequence identity thresholds). We found that the relative influence of the community assembly processes varies with phylogenetic resolution. More specifically, selection processes seem to impose stronger influence at finer (100% sequence similarity ASV) than at coarser (99%-97% sequence similarity OTUs) resolution. We identified environmental features related with the ecological processes and propose a conceptual model for the bacterial community assembly in this Antarctic ecosystem. Briefly, eco-evolutionary processes appear to be leading to different but very closely related ASVs in lotic, lentic and terrestrial environments. In all, this study shows that assessing community assembly processes at different phylogenetic resolutions is key to improve our understanding of microbial ecology. More importantly, a failure to detect selection processes at coarser phylogenetic resolution does not imply the absence of such processes at finer resolutions.

Contrasting Community Assembly Forces Drive Microbial Structural and Potential Functional Responses to Precipitation in an Incipient Soil System.

Microbial communities in incipient soil systems serve as the only biotic force shaping landscape evolution. However, the underlying ecological forces shaping microbial community structure and function are inadequately understood. We used amplicon sequencing to determine microbial taxonomic assembly and metagenome sequencing to evaluate microbial functional assembly in incipient basaltic soil subjected to precipitation. Community composition was stratified with soil depth in the pre-precipitation samples, with surficial communities maintaining their distinct structure and diversity after precipitation, while the deeper soil samples appeared to become more uniform. The structural community assembly remained deterministic in pre- and post-precipitation periods, with homogenous selection being dominant. Metagenome analysis revealed that carbon and nitrogen functional potential was assembled stochastically. Sub-populations putatively involved in the nitrogen cycle and carbon fixation experienced counteracting assembly pressures at the deepest depths, suggesting the communities may functionally assemble to respond to short-term environmental fluctuations and impact the landscape-scale response to perturbations. We propose that contrasting assembly forces impact microbial structure and potential function in an incipient landscape; in situ landscape characteristics (here homogenous parent material) drive community structure assembly, while short-term environmental fluctuations (here precipitation) shape environmental variations that are random in the soil depth profile and drive stochastic sub-population functional dynamics.

Assembly of the Populus Microbiome Is Temporally Dynamic and Determined by Selective and Stochastic Factors.

Recent work shows that the plant microbiome, particularly the initial assembly of this microbiome, influences plant health, survival, and fitness. Here, we characterize the initial assembly of the Populus microbiome across ten genotypes belonging to two poplar species in a common garden using 16S rRNA gene and ITS2 region amplicon sequencing of the leaf endosphere, leaf surface, root endosphere, and rhizosphere. We sampled these microbiomes three times throughout the first growing season and found that the composition of the microbiome changed dramatically over time across all plant-associated habitats and host genotypes. For archaea and bacteria, these changes were dominated by strong homogenizing selection (accounting for 29 to 62% of pairwise comparisons). However, fungal assembly was generally characterized by multiple ecological assembly processes (i.e., a mix of weak selective and dispersal processes). Interestingly, genotype, while a significant moderator of microbiome composition, generally explained less variation than sample date across plant-associated habitats. We defined a set of core genera that accounted for, on average, 36% of the microbiome. The relative abundance of this core community was consistent over time. Additionally, using source tracking modeling, we determined that new microbial taxa colonize from both aboveground and belowground sources, and combined with our ecological assembly null models, we found that both selective and dispersal processes explained the differences between exo- (i.e., leaf surface and rhizosphere) and endospheric microbiomes. Taken together, our results suggest that the initial assembly of the Populus microbiome is time-, genotype-, and habitat-dependent and is moderated by both selective and stochastic factors. IMPORTANCE The initial assembly of the plant microbiome may establish the trajectory of forthcoming microbiome states, which could determine the overall future health of the plant. However, while much is known about the initial microbiome assembly of grasses and agricultural crops, less is known about the initial microbiome of long-lived trees, such as poplar (Populus spp.). Thus, a greater understanding of initial plant microbiome assembly in an ecologically and economically important plant such as Populus is highly desirable. Here, we show that the initial microbiome community composition and assembly in the first growing season of Populus is temporally dynamic and is determined by a combination of both selective and stochastic factors. Our findings could be used to prescribe ecologically informed microbial inoculations and better predict the composition of the Populus microbiome into the future and to better understand its influence on plant health.

Ecological theory applied to environmental metabolomes reveals compositional divergence despite conserved molecular properties.

Stream and river systems transport and process substantial amounts of dissolved organic matter (DOM) from terrestrial and aquatic sources to the ocean, with global biogeochemical implications. However, the underlying mechanisms affecting the spatiotemporal organization of DOM composition are under-investigated. To understand the principles governing DOM composition, we leverage the recently proposed synthesis of metacommunity ecology and metabolomics, termed 'meta-metabolome ecology.' Applying this novel approach to a freshwater ecosystem, we demonstrated that despite similar molecular properties across metabolomes, metabolite identity significantly diverged due to environmental filtering and variations in putative biochemical transformations. We refer to this phenomenon as 'thermodynamic redundancy,' which is analogous to the ecological concept of functional redundancy. We suggest that under thermodynamic redundancy, divergent metabolomes can support equivalent biogeochemical function just as divergent ecological communities can support equivalent ecosystem function. As these analyses are performed in additional ecosystems, potentially generalizable concepts, like thermodynamic redundancy, can be revealed and provide insight into DOM dynamics.

Using metacommunity ecology to understand environmental metabolomes.

Environmental metabolomes are fundamentally coupled to microbially-linked biogeochemical processes within ecosystems. However, significant gaps exist in our understanding of their spatiotemporal organization, limiting our ability to uncover transferrable principles and predict ecosystem function. We propose that a theoretical paradigm, which integrates concepts from metacommunity ecology, is necessary to reveal underlying mechanisms governing metabolomes. We call this synthesis between ecology and metabolomics 'meta-metabolome ecology' and demonstrate its utility using a mass spectrometry dataset. We developed three relational metabolite dendrograms using molecular properties and putative biochemical transformations and performed ecological null modeling. Based upon null modeling results, we show that stochastic processes drove molecular properties while biochemical transformations were structured deterministically. We further suggest that potentially biochemically active metabolites were more deterministically assembled than less active metabolites. Understanding variation in the influences of stochasticity and determinism provides a way to focus attention on which meta-metabolomes and which parts of meta-metabolomes are most likely to be important to consider in mechanistic models. We propose that this paradigm will allow researchers to study the connections between ecological systems and their molecular processes in previously inaccessible detail.