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The influence of coastal ecosystems on global greenhouse gas (GHG) budgets and their response to increasing inundation and salinization remains poorly constrained. In this study, we have integrated an uncertainty quantification (UQ) and ensemble machine learning (ML) framework to identify and rank the most influential processes, properties, and conditions controlling methane behavior in a freshwater floodplain responding to recently restored seawater inundation. Our unique multivariate, multiyear, and multi-site dataset comprises tidal creek and floodplain porewater observations encompassing water level, salinity, pH, temperature, dissolved oxygen (DO), dissolved organic carbon (DOC), total dissolved nitrogen (TDN), partial pressure of carbon dioxide (pCO2), nitrous oxide (pN2O), methane (pCH4), and the stable isotopic composition of methane (δ13CH4). Additionally, we incorporated topographical data, soil porosity, hydraulic conductivity, and water retention parameters for UQ analysis using a previously developed 3D variably saturated flow and transport floodplain model for a physical mechanistic understanding of factors influencing groundwater levels and salinity and, therefore, CH4. Principal component analysis revealed that groundwater level and salinity are the most significant predictors of overall biogeochemical variability. The ensemble ML models and UQ analyses identified DO, water level, salinity, and temperature as the most influential factors for porewater methane levels and indicated that approximately 80% of the total variability in hourly water levels and around 60% of the total variability in hourly salinity can be explained by permeability, creek water level, and two van Genuchten water retention function parameters: the air-entry suction parameter α and the pore size distribution parameter m. These findings provide insights on the physicochemical factors in methane behavior in coastal ecosystems and their representation in local- to global-scale Earth system models. [ABSTRACT FROM AUTHOR]

The influence of coastal ecosystems on global greenhouse gas (GHG) budgets and their response to increasing inundation and salinization remains poorly constrained. In this study, we have integrated an uncertainty quantification (UQ) and ensemble machine learning (ML) framework to identify and rank the most influential processes, properties, and conditions controlling methane behavior in a freshwater floodplain responding to recently restored seawater inundation. Our unique multivariate, multiyear, and multi-site dataset comprises tidal creek and floodplain porewater observations encompassing water level, salinity, pH, temperature, dissolved oxygen (DO), dissolved organic carbon (DOC), total dissolved nitrogen (TDN), partial pressure of carbon dioxide (pCO2), nitrous oxide (pN2O), methane (pCH4), and the stable isotopic composition of methane (δ13CH4). Additionally, we incorporated topographical data, soil porosity, hydraulic conductivity, and water retention parameters for UQ analysis using a previously developed 3D variably saturated flow and transport floodplain model for a physical mechanistic understanding of factors influencing groundwater levels and salinity and, therefore, CH4. Principal component analysis revealed that groundwater level and salinity are the most significant predictors of overall biogeochemical variability. The ensemble ML models and UQ analyses identified DO, water level, salinity, and temperature as the most influential factors for porewater methane levels and indicated that approximately 80% of the total variability in hourly water levels and around 60% of the total variability in hourly salinity can be explained by permeability, creek water level, and two van Genuchten water retention function parameters: the air-entry suction parameter α and the pore size distribution parameter m. These findings provide insights on the physicochemical factors in methane behavior in coastal ecosystems and their representation in local- to global-scale Earth system models.

Though community-based scientific approaches are becoming more common, many scientific efforts are conducted by small groups of researchers that together develop a concept, analyze data, and interpret results that ultimately translate into a publication. Here, we present a community effort that breaks these traditional boundaries of the publication process by engaging the scientific community from initial hypothesis generation to final publication. We leverage community-generated data from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium to study organic matter composition through the lens of ecological theory. This community endeavor will use a suite of paired physical and chemical datasets collected from 97 river corridors across the globe. With our first step aimed at ideation, we engaged a community of scientists from over 20 countries and 60 institutions, spanning disciplines and career stages by holding a virtual workshop (April 2021). In the workshop, participants generated content for questions, hypotheses, and proposed analyses based on the WHONDRS dataset. These ideation efforts resulted in several narratives investigating different questions led by different teams, which will be the basis for research articles in a Frontiers in Water collection. Currently, the community is collectively analyzing, interpreting, and synthesizing these data that will result in six crowdsourced articles using a single, existing WHONDRS dataset. The use of a shared dataset across articles not only lowers barriers for broad participation by not requiring generation of new data, but also provides unique opportunities for emergent learning by connecting outcomes across studies. Here we will explain methods used to enable this community endeavor aimed to promote a greater diversity of thinking on river corridor biogeochemistry through crowdsourced science.

Background. The Worldwide Hydrobiogeochemistry Observation Network for Dy- namic River Systems (WHONDRS) is a consortium that aims to understand com- plex hydrologic, biogeochemical, and microbial connections within river corridors experiencing perturbations such as dam operations, floods, and droughts. For one ongoing WHONDRS sampling campaign, surface water metabolite and microbiome samples are collected through a global survey to generate knowledge across diverse river corridors. Metabolomics analysis and a suite of geochemical analyses have been performed for collected samples through the Environmental Molecular Sciences Laboratory (EMSL). The obtained knowledge and data package inform mechanistic and data-driven models to enhance predictions of outcomes of hydrologic perturbations and watershed function, one of the most critical components in model-data integration. To support efforts of the multi-domain integration and make the ever-growing data package more accessible for researchers across the world, a Shiny/R Graphical User Interface (GUI) called WHONDRS-GUI was created. Results. The web application can be run on any modern web browser without any programming or operational system requirements, thus providing an open, well- structured, discoverable dataset for WHONDRS. Together with a context-aware dy- namic user interface, the WHONDRS-GUI has functionality for searching, compiling, integrating, visualizing and exporting different data types that can easily be used by the community. The web application and data package are available at https://data. ess-dive.lbl.gov/view/doi:10.15485/1484811, which enables users to simultaneously obtain access to the data and code and to subsequently run the web app locally. The WHONDRS-GUI is also available for online use at Shiny Server (https://xmlin. shinyapps.io/whondrs/). [ABSTRACT FROM AUTHOR]

Abstract Geogenic enrichment of arsenic (As) in groundwater has been a topic of worldwide concern over the past several decades due to the severe health threat to an estimated over one hundred million people. Despite the genetic diversity and the spatial variability of As concentrations, the most common geogenic As-enriched groundwater occurs in flat, low-lying river floodplains and fluvial-lacustrine plains. Within river systems draining the Himalaya, tectonic movement, sedimentological processes and palaeoclimatic optima after the Last Glacial Maximum have created favorable conditions for the formation of high-As aquifer systems mainly within the Late Pleistocene-Holocene deposits. The co-deposition of As-bearing Fe oxides and reactive organic matter within sediments of deltas/floodplains or fluvial-lacustrine plains forms the premise for As release under reducing geochemical environments. However, depending on the reactivity of organic matter and As-bearing Fe oxides, as well as the availability of aqueous sulfate, geochemical mechanisms controlling As enrichment in the groundwater differ between the coastal floodplains of South and Southeast Asia and the fluvial-lacustrine plains of North and Central China. The indigenous geomicrobes thriving to adapt to specific aquifer environments may mediate Fe-S-As biogeochemical cycling responsible for As speciation transformation, dissolution/desorption, and hence mobilization. Hydrologic processes regulated by the local and regional groundwater flow regimes control As transport as well as its spatial distribution. Special attention must be paid to anthropogenic perturbation from intensive groundwater pumping and land use changes that affect the aquifer hydrological conditions and the biogeochemical processes, thus altering groundwater As levels. To decipher the patterns of As variation within the aquifers, an integrated approach characterizing the major sedimentological, hydrobiogeochemical and anthropogenic processes influencing As release and transport needs to be applied to ensure sustainable water supply for domestic and agricultural needs. Highlights • Sedimentogenesis explains high-As groundwater in Late Pleistocene-Holocene aquifers. • As mobilization processes differ between floodplains and fluvial-lacustrine basins. • Anthropogenic influences on As fate must be carefully discerned and managed. • Predicting As needs integrated knowledge of sedimentology and hydrobiogeochemistry. [ABSTRACT FROM AUTHOR]

Karst subterranean estuaries (KSEs) extend into carbonate platforms along 12% of all coastlines. A recent study has shown that microbial methane (CH4) consumption is an important component of the carbon cycle and food web dynamics within flooded caves that permeate KSEs. In this study, we obtained high‐resolution (~2.5‐day) temporal records of dissolved methane concentrations and its stable isotopic content (δ13C) to evaluate how regional meteorology and hydrology control methane dynamics in KSEs. Our records show that less methane was present in the anoxic fresh water during the wet season (4,361 ± 89 nM) than during the dry season (5,949 ± 132 nM), suggesting that the wet season hydrologic regime enhances mixing of methane and other constituents into the underlying brackish water. The δ13C of the methane (−38.1 ± 1.7‰) in the brackish water was consistently more 13C‐enriched than fresh water methane (−65.4 ± 0.4‰), implying persistent methane oxidation in the cave. Using a hydrologically based mass balance model, we calculate that methane consumption in the KSE was 21–28 mg CH4·m−2·year−1 during the 6‐month dry period, which equates to ~1.4 t of methane consumed within the 102‐ to 138‐km2 catchment basin for the cave. Unless wet season methane consumption is much greater, the magnitude of methane oxidized within KSEs is not likely to affect the global methane budget. However, our estimates constrain the contribution of a critical resource for this widely distributed subterranean ecosystem. Plain Language Summary: Subterranean estuaries occur worldwide where fresh and marine‐derived waters mix within coastal aquifers, creating a chemical reaction zone that alters the composition of materials transported to the sea. According to a recent study, methane—a potent greenhouse gas—and the bacteria that feed on it form the basis of a complex food web restricted to cave networks flooded by the subterranean estuary. Questions about the seasonality and magnitude of this methane sink remain unclear. Unprecedented chemical records collected during this study with simultaneous meteorological and hydrological data reveal that methane accumulation is significantly greater during the dry season than during the wet season when rainfall is more prevalent and greater mixing in the coastal aquifer facilitates methane consumption. We estimate that ~1.4 t of methane are consumed during a 6‐month‐long dry period within the ~100‐km2 catchment region. This estimate constrains the contribution of a critical energy source for karst subterranean estuary ecosystems. Key Points: Concurrent meteorological, hydrological, and chemical records are used to study sources and sinks of methane in a karst subterranean estuaryIncreased precipitation enhances methane oxidation by mixing anoxic methane‐rich waters with oxygenated watersA hydrologically based mass balance model provides a first‐order estimate for the magnitude of the methane sink within the catchment region [ABSTRACT FROM AUTHOR]

Biogeochemical hotspots are pervasive at terrestrial-aquatic interfaces, particularly within groundwater-surface water mixing zones (hyporheic zones), and they are critical to understanding spatiotemporal variation in biogeochemical cycling. Here, we use multi 'omic comparisons of hotspots to low-activity sediments to gain mechanistic insight into hyporheic zone organic matter processing. We hypothesized that microbiome structure and function, as described by metagenomics and metaproteomics, would distinguish hotspots from low-activity sediments by shifting metabolism towards carbohydrate-utilizing pathways and elucidate discrete mechanisms governing organic matter processing in each location. We also expected these differences to be reflected in the metabolome, whereby hotspot carbon (C) pools and metabolite transformations therein would be enriched in sugar-associated compounds. In contrast to expectations, we found pronounced phenotypic plasticity in the hyporheic zone microbiome that was denoted by similar microbiome structure, functional potential, and expression across sediments with dissimilar metabolic rates. Instead, diverse nitrogenous metabolites and biochemical transformations characterized hotspots. Metabolomes also corresponded more strongly to aerobic metabolism than bulk C or N content only (explaining 67% vs. 42% and 37% of variation respectively), and bulk C and N did not improve statistical models based on metabolome composition alone. These results point to organic nitrogen as a significant regulatory factor influencing hyporheic zone organic matter processing. Based on our findings, we propose incorporating knowledge of metabolic pathways associated with different chemical fractions of C pools into ecosystem models will enhance prediction accuracy. [ABSTRACT FROM AUTHOR]

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Background: The Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) is a consortium that aims to understand complex hydrologic, biogeochemical, and microbial connections within river corridors experiencing perturbations such as dam operations, floods, and droughts. For one ongoing WHONDRS sampling campaign, surface water metabolite and microbiome samples are collected through a global survey to generate knowledge across diverse river corridors. Metabolomics analysis and a suite of geochemical analyses have been performed for collected samples through the Environmental Molecular Sciences Laboratory (EMSL). The obtained knowledge and data package inform mechanistic and data-driven models to enhance predictions of outcomes of hydrologic perturbations and watershed function, one of the most critical components in model-data integration. To support efforts of the multi-domain integration and make the ever-growing data package more accessible for researchers across the world, a Shiny/R Graphical User Interface (GUI) called WHONDRS-GUI was created., Results: The web application can be run on any modern web browser without any programming or operational system requirements, thus providing an open, well-structured, discoverable dataset for WHONDRS. Together with a context-aware dynamic user interface, the WHONDRS-GUI has functionality for searching, compiling, integrating, visualizing and exporting different data types that can easily be used by the community. The web application and data package are available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1484811, which enables users to simultaneously obtain access to the data and code and to subsequently run the web app locally. The WHONDRS-GUI is also available for online use at Shiny Server (https://xmlin.shinyapps.io/whondrs/)., Competing Interests: Timothy D. Scheibe is an Academic Editor for PeerJ., (©2020 Battelle Memorial Institute.)