15 research outputs found

    The Microbiome Stress Project: Toward a Global Meta-Analysis of Environmental Stressors and Their Effects on Microbial Communities

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    Microbial community structure is highly sensitive to natural (e.g., drought, temperature, fire) and anthropogenic (e.g., heavy metal exposure, land-use change) stressors. However, despite an immense amount of data generated, systematic, cross-environment analyses of microbiome responses to multiple disturbances are lacking. Here, we present the Microbiome Stress Project, an open-access database of environmental and host-associated 16S rRNA amplicon sequencing studies collected to facilitate cross-study analyses of microbiome responses to stressors. This database will comprise published and unpublished datasets re-processed from the raw sequences into exact sequence variants using our standardized computational pipeline. Our database will provide insight into general response patterns of microbiome diversity, structure, and stability to environmental stressors. It will also enable the identification of cross-study associations between single or multiple stressors and specific microbial clades. Here, we present a proof-of-concept meta-analysis of 606 microbiomes (from nine studies) to assess microbial community responses to: (1) one stressor in one environment: soil warming across a variety of soil types, (2) a range of stressors in one environment: soil microbiome responses to a comprehensive set of stressors (incl. temperature, diesel, antibiotics, land use change, drought, and heavy metals), (3) one stressor across a range of environments: copper exposure effects on soil, sediment, activated-sludge reactors, and gut environments, and (4) the general trends of microbiome stressor responses. Overall, we found that stressor exposure significantly decreases microbiome alpha diversity and increases beta diversity (community dispersion) across a range of environments and stressor types. We observed a hump-shaped relationship between microbial community resistance to stressors (i.e., the average pairwise similarity score between the control and stressed communities) and alpha diversity. We used Phylofactor to identify microbial clades and individual taxa as potential bioindicators of copper contamination across different environments. Using standardized computational and statistical methods, the Microbiome Stress Project will leverage thousands of existing datasets to build a general framework for how microbial communities respond to environmental stress

    Light and flow regimes regulate the metabolism of rivers

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    Mean annual temperature and mean annual precipitation drive much of the variation in productivity across Earth's terrestrial ecosystems but do not explain variation in gross primary productivity (GPP) or ecosystem respiration (ER) in flowing waters. We document substantial variation in the magnitude and seasonality of GPP and ER across 222 US rivers. In contrast to their terrestrial counterparts, most river ecosystems respire far more carbon than they fix and have less pronounced and consistent seasonality in their metabolic rates. We find that variation in annual solar energy inputs and stability of flows are the primary drivers of GPP and ER across rivers. A classification schema based on these drivers advances river science and informs management.We thank Ted Stets, Jordan Read, Tom Battin, Sophia Bonjour, Marina Palta, and members of the Duke River Center for their help in developing these ideas. This work was supported by grants from the NSF 1442439 (to E.S.B. and J.W.H.), 1834679 (to R.O.H.), 1442451 (to R.O.H.), 2019528 (to R.O.H. and J.R.B.), 1442140 (to M.C.), 1442451 (to A.M.H.), 1442467 (to E.H.S.), 1442522 (to N.B.G.), 1624807 (to N.B.G.), and US Geological Survey funding for the working group was supported by the John Wesley Power Center for Analysis and Synthesis. Phil Savoy contributed as a postdoc- toral associate at Duke University and as a postdoctoral associate (contractor) at the US Geological Survey

    Classifying freshwater salinity regimes in central and western U.S. streams and rivers

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    Abstract Freshwater salinization of rivers is occurring across the globe because of nonpoint source loading of salts from anthropogenic activities such as agriculture, urbanization, and resource extraction that accelerate weathering and release salts. Multidecadal trends in river salinity are well characterized, yet our understanding of annual regimes of salinity in rivers draining diverse central and western U.S. landscapes and their associated catchment attributes is limited. We classified annual salinity regimes in 242 stream locations through dynamic time warping and fuzzy c‐medoids clustering of salinity time series. We found two dominant regimes in salinity characterized by an annual summer–fall peak or spring decline. Using random forest regression, we found that precipitation amount, stream slope, and soil salinity were the most important predictors of salinity regime classification. Advancing our understanding of salinity regimes in rivers will improve our ability to predict and mitigate the effects of salinization in freshwater ecosystems through management interventions

    Not all pavements lead to streams: Variation in impervious surface connectivity affects urban stream ecosystems

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    Watershed urbanization leads to chemical and thermal pollution of urban streams and significant declines in aquatic biodiversity. Most investigators have focused on variation in total watershed impervious surface cover (ISC) as the primary driver of urban stream degradation. We asked instead whether the degree of connectivity between ISC and urban stream channels alters its effect. We compared 7 streams in the Raleigh–Durham metropolitan area of the southeastern USA that drained watersheds with similar amounts of pavement (ISC 5 7–16% of watershed area) but spanning a wide range of hydrologic connectivity between these pavements and their receiving streams via both subsurface (pipe density range: 1.1–6.9 km/km2) and surface (road density range: 5.8–10.7 km/ km2) flowpaths. Despite draining watersheds with similarly low levels of development, these 7 streams exhibited remarkable variability in their hydrologic and thermal regimes and varied in their macroinvertebrate diversity from a low of only 11 taxa to a high of 22. Both macroinvertebrate community composition and the tissue concentrations of Cu, Pb, and Zn in 3 stream invertebrate taxa (Cambaridae, Tipulidae, and Hydropsychidae) found across all sites were correlated with watershed hydrologic connectivity. These results suggest that the connectivity of ISC may drive considerable variation in the magnitude of ecosystem degradation associated with the same level of watershed development, with less connected or disconnected impervious surfaces having proportionally lower negative effects on aquatic organisms

    The Microbiome Stress Project: Toward a Global Meta-Analysis of Environmental Stressors and Their Effects on Microbial Communities

    Get PDF
    Microbial community structure is highly sensitive to natural (e.g., drought, temperature, fire) and anthropogenic (e.g., heavy metal exposure, land-use change) stressors. However, despite an immense amount of data generated, systematic, cross-environment analyses of microbiome responses to multiple disturbances are lacking. Here, we present the Microbiome Stress Project, an open-access database of environmental and host-associated 16S rRNA amplicon sequencing studies collected to facilitate cross-study analyses of microbiome responses to stressors. This database will comprise published and unpublished datasets re-processed from the raw sequences into exact sequence variants using our standardized computational pipeline. Our database will provide insight into general response patterns of microbiome diversity, structure, and stability to environmental stressors. It will also enable the identification of cross-study associations between single or multiple stressors and specific microbial clades. Here, we present a proof-of-concept meta-analysis of 606 microbiomes (from nine studies) to assess microbial community responses to: (1) one stressor in one environment: soil warming across a variety of soil types, (2) a range of stressors in one environment: soil microbiome responses to a comprehensive set of stressors (incl. temperature, diesel, antibiotics, land use change, drought, and heavy metals), (3) one stressor across a range of environments: copper exposure effects on soil, sediment, activated-sludge reactors, and gut environments, and (4) the general trends of microbiome stressor responses. Overall, we found that stressor exposure significantly decreases microbiome alpha diversity and increases beta diversity (community dispersion) across a range of environments and stressor types. We observed a hump-shaped relationship between microbial community resistance to stressors (i.e., the average pairwise similarity score between the control and stressed communities) and alpha diversity. We used Phylofactor to identify microbial clades and individual taxa as potential bioindicators of copper contamination across different environments. Using standardized computational and statistical methods, the Microbiome Stress Project will leverage thousands of existing datasets to build a general framework for how microbial communities respond to environmental stress

    A Classification Framework to Assess Ecological, Biogeochemical, and Hydrologic Synchrony and Asynchrony

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    Ecosystems in the Anthropocene face pressures from multiple, interacting forms of environmental change. These pressures, resulting from land use change, altered hydrologic regimes, and climate change, will likely change the synchrony of ecosystem processes as distinct components of ecosystems are impacted in different ways. However, discipline-specific definitions and ad hoc methods for identifying synchrony and asynchrony have limited broader synthesis of this concept among studies and across disciplines. Drawing on concepts from ecology, hydrology, geomorphology, and biogeochemistry, we offer a unifying definition of synchrony for ecosystem science and propose a classification framework for synchrony and asynchrony of ecosystem processes. This framework classifies the relationships among ecosystem processes according to five key aspects: 1) the focal variables or relationships representative of the ecosystem processes of interest, 2) the spatial and temporal domain of interest, 3) the structural attributes of drivers and focal processes, 4) consistency in the relationships over time, and 5) the degree of causality among focal processes. Using this classification framework, we identify and differentiate types of synchrony and asynchrony, thereby providing the basis for comparing among studies and across disciplines. We apply this classification framework to existing studies in the ecological, hydrologic, geomorphic, and biogeochemical literature, and discuss potential analytical tools that can be used to quantify synchronous and asynchronous processes. Furthermore, we seek to promote understanding of how different types of synchrony or asynchrony may shift in response to ongoing environmental change by providing a universal definition and explicit types and drivers with this framework

    Sediment Chemistry of Urban Stormwater Ponds and Controls on Denitrification

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    Stormwater ponds and retention basins are ubiquitous features throughout urban landscapes. These ponds are potentially important control points for nitrogen (N) removal from surface water bodies via denitrification. However, there are possible trade-offs to this water quality benefit if high N and contaminant concentrations in stormwater pond sediments decrease the complete reduction of nitrous oxide (N2O), a potent greenhouse gas, to dinitrogen (N2) during denitrification. This may occur through decreasing the abundance or efficiency of denitrifiers capable of producing the N2O reductase enzyme. We predicted that ponds draining increasingly urbanized landscapes would have higher N and metal concentrations in their sediments, and thereby greater N2O yields. We measured potential denitrification rates, N2O reductase (nosZ) gene frequencies, as well as sediment and porewater chemistry in 64 ponds distributed across eight U.S. cities. We found almost no correlation between the proportion of urban land cover surrounding ponds and the nutrient and contaminant concentrations in the stormwater pond sediments within or across all cities. Regression analysis revealed that the proportion of potential N2 and N2O production that could be explained was under different environmental controls. Our survey raises many new questions about why N fluxes and transformations vary so widely both within and across urban environments, but also allays the concern that elevated metal concentrations in urban stormwater ponds will increase N2O emissions. Urban stormwater ponds are unlikely to be a problematic source of N2O to the atmosphere, no matter their denitrification potential

    At the Interfaces of the Hydrologic Sciences: Connecting Water, Elements, Ecosystems, and People Through the Major Contributions of Dr. Emily Bernhardt

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    In this paper, we describe the major contributions of Professor Emily Bernhardt to the hydrologic sciences. Dr. Bernhardt’s work addresses how carbon, nutrient, and contaminant dynamics respond to a wide range of environmental perturbations that alter hydrologic dynamics within and connectivity among ecosystems. Her research leverages intensive and extensive field sampling, experimental manipulations, macroscale data harmonization and exploration, and continental to global-scale synthesis activities to uncover key drivers and patterns of the impacts human perturbations have on water and elemental cycles. Dr. Bernhardt’s research program is defined by her ability to ask questions and use approaches that explicitly consider connectivity and interfaces in a variety of ways. Here, we highlight significant contributions from Dr. Bernhardt’s work, organized by connectivity, interfaces, and interactions among and across (1) elemental cycles, (2) ecosystems, (3) watersheds, (4) scales, and (5) disciplines. We conclude with a section on Dr. Bernhardt’s impact on the hydrologic sciences and beyond through her exceptional dedication to mentorship, engagement, and service
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