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      Groundwater–surface water mixing shifts ecological assembly processes and stimulates organic carbon turnover

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          Abstract

          Environmental transitions often result in resource mixtures that overcome limitations to microbial metabolism, resulting in biogeochemical hotspots and moments. Riverine systems, where groundwater mixes with surface water (the hyporheic zone), are spatially complex and temporally dynamic, making development of predictive models challenging. Spatial and temporal variations in hyporheic zone microbial communities are a key, but understudied, component of riverine biogeochemical function. Here, to investigate the coupling among groundwater–surface water mixing, microbial communities and biogeochemistry, we apply ecological theory, aqueous biogeochemistry, DNA sequencing and ultra-high-resolution organic carbon profiling to field samples collected across times and locations representing a broad range of mixing conditions. Our results indicate that groundwater–surface water mixing in the hyporheic zone stimulates heterotrophic respiration, alters organic carbon composition, causes ecological processes to shift from stochastic to deterministic and is associated with elevated abundances of microbial taxa that may degrade a broad suite of organic compounds.

          Abstract

          Groundwater-surface water mixing zones link critical ecosystem domains, but attendant microbe-biogeochemistry-hydrology interactions are poorly known. Here, the authors show that groundwater-surface water mixing stimulates respiration, alters carbon composition, and shifts the ecology from stochastic to deterministic.

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          Most cited references20

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          Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample.

          The ongoing revolution in high-throughput sequencing continues to democratize the ability of small groups of investigators to map the microbial component of the biosphere. In particular, the coevolution of new sequencing platforms and new software tools allows data acquisition and analysis on an unprecedented scale. Here we report the next stage in this coevolutionary arms race, using the Illumina GAIIx platform to sequence a diverse array of 25 environmental samples and three known "mock communities" at a depth averaging 3.1 million reads per sample. We demonstrate excellent consistency in taxonomic recovery and recapture diversity patterns that were previously reported on the basis of metaanalysis of many studies from the literature (notably, the saline/nonsaline split in environmental samples and the split between host-associated and free-living communities). We also demonstrate that 2,000 Illumina single-end reads are sufficient to recapture the same relationships among samples that we observe with the full dataset. The results thus open up the possibility of conducting large-scale studies analyzing thousands of samples simultaneously to survey microbial communities at an unprecedented spatial and temporal resolution.
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            Quantifying community assembly processes and identifying features that impose them.

            Spatial turnover in the composition of biological communities is governed by (ecological) Drift, Selection and Dispersal. Commonly applied statistical tools cannot quantitatively estimate these processes, nor identify abiotic features that impose these processes. For interrogation of subsurface microbial communities distributed across two geologically distinct formations of the unconfined aquifer underlying the Hanford Site in southeastern Washington State, we developed an analytical framework that advances ecological understanding in two primary ways. First, we quantitatively estimate influences of Drift, Selection and Dispersal. Second, ecological patterns are used to characterize measured and unmeasured abiotic variables that impose Selection or that result in low levels of Dispersal. We find that (i) Drift alone consistently governs ∼25% of spatial turnover in community composition; (ii) in deeper, finer-grained sediments, Selection is strong (governing ∼60% of turnover), being imposed by an unmeasured but spatially structured environmental variable; (iii) in shallower, coarser-grained sediments, Selection is weaker (governing ∼30% of turnover), being imposed by vertically and horizontally structured hydrological factors;(iv) low levels of Dispersal can govern nearly 30% of turnover and be caused primarily by spatial isolation resulting from limited exchange between finer and coarser-grain sediments; and (v) highly permeable sediments are associated with high levels of Dispersal that homogenize community composition and govern over 20% of turnover. We further show that our framework provides inferences that cannot be achieved using preexisting approaches, and suggest that their broad application will facilitate a unified understanding of microbial communities.
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              Stochastic and deterministic assembly processes in subsurface microbial communities.

              A major goal of microbial community ecology is to understand the forces that structure community composition. Deterministic selection by specific environmental factors is sometimes important, but in other cases stochastic or ecologically neutral processes dominate. Lacking is a unified conceptual framework aiming to understand why deterministic processes dominate in some contexts but not others. Here we work toward such a framework. By testing predictions derived from general ecological theory we aim to uncover factors that govern the relative influences of deterministic and stochastic processes. We couple spatiotemporal data on subsurface microbial communities and environmental parameters with metrics and null models of within and between community phylogenetic composition. Testing for phylogenetic signal in organismal niches showed that more closely related taxa have more similar habitat associations. Community phylogenetic analyses further showed that ecologically similar taxa coexist to a greater degree than expected by chance. Environmental filtering thus deterministically governs subsurface microbial community composition. More importantly, the influence of deterministic environmental filtering relative to stochastic factors was maximized at both ends of an environmental variation gradient. A stronger role of stochastic factors was, however, supported through analyses of phylogenetic temporal turnover. Although phylogenetic turnover was on average faster than expected, most pairwise comparisons were not themselves significantly non-random. The relative influence of deterministic environmental filtering over community dynamics was elevated, however, in the most temporally and spatially variable environments. Our results point to general rules governing the relative influences of stochastic and deterministic processes across micro- and macro-organisms.
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                Author and article information

                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group
                2041-1723
                07 April 2016
                2016
                : 7
                : 11237
                Affiliations
                [1 ]Pacific Northwest National Laboratory , 902 Battelle Boulevard, P.O. Box 999, Richland, Washington 99352, USA
                [2 ]Department of Microbiology, The Ohio State University , Columbus, Ohio 43210, USA
                [3 ]School of Earth Sciences, The Ohio State University , Columbus, Ohio 43210, USA
                Author notes
                Article
                ncomms11237
                10.1038/ncomms11237
                4829693
                27052662
                3269968e-29c0-4f42-b5ae-5b0a3dd0277d
                Copyright © 2016, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/

                History
                : 02 June 2015
                : 04 March 2016
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