Item talk:Q227539

{

 "@context": "http://schema.org/",
 "@type": "WebPage",
 "additionalType": "Research",
 "url": "https://www.usgs.gov/centers/wetland-and-aquatic-research-center/science/wetland-methane-emissions-functional-type",
 "headline": "Wetland Methane Emissions: Functional-type Modeling and Data-driven Parameterization",
 "datePublished": "July 23, 2021",
 "author": [
   {
     "@type": "Person",
     "name": "Eric J Ward, Ph.D.",
     "url": "https://www.usgs.gov/staff-profiles/eric-j-ward",
     "identifier": {
       "@type": "PropertyValue",
       "propertyID": "orcid",
       "value": "0000-0002-5047-5464"
     }
   }
 ],
 "description": [
   {
     "@type": "TextObject",
     "text": "To better understand the environmental drivers of methane emissions in tidal saltmarsh, tidal freshwater swamp forest, tidal freshwater marsh, and non-tidal freshwater marsh habitats, researchers are collecting observations of CH4 emissions and porewater concentrations at research sites representative of each of these habitats."
   },
   {
     "@type": "TextObject",
     "text": "Wetlands are intrinsically heterogeneous environments. The large uncertainty of CH4 fluxes and the challenging aspects of modeling them are largely driven by (1) the small-scale spatial and temporal heterogeneity of CH4 fluxes; (2) the complex coupling between aboveground and belowground processes; and (3) the complexity of meteorological, hydrological, ecological, and microbial processes that affect these fluxes. Methane fluxes are the combined endpoint of microbial methane generation (methanogenesis) and consumption (methanotrophy); methane transport through soil, water, and plant tissue to the air (Fig.1); and the environmental conditions that affect these processes in different ecohydrological patches. Our goals are to improve understanding and quantitative representation of the multiple processes that affect methane emissions with observations collected at a high spatial and temporal resolution (patch level, vertically detailed, sub-hourly), and translate this understanding to improved modeling capability of coastal wetland fluxes using the Energy Exascale Earth System Model (E3SM) Land Model (ELM v1) wetland CH4 biogeochemistry module."
   },
   {
     "@type": "TextObject",
     "text": "Methodology for Addressing the Issue: We are collecting high-resolution observations of CH4 emissions and porewater concentrations at four key research sites (Fig. 2), including tidal saltmarsh, tidal freshwater swamp forest, tidal freshwater marsh, and non-tidal freshwater marsh habitats. Using the ELMv1 model, we will combine these observations with ecosystem-level monitoring and microbiological surveys to better understand the environmental drivers of methane emissions in these ecosystems, and improve our ability to predict CH4 emission responses to climate change, sea-level rise, and management decisions. Techniques employed in the field include eddy covariance, static chamber measurements, porewater peeper sampling, geochemistry, and microbial metatranscriptomics (the science that studies gene expression of microbes within natural environments)."
   },
   {
     "@type": "TextObject",
     "text": "Future Steps: This project provides more highly resolved data and improved modeling capabilities for two existing projects led by USGS WARC at these sites, concerning carbon cycling in critical coastal habitats targeted for restoration (https://www.usgs.gov/centers/wetland-and-aquatic-research-center-warc/science/critical-coastal-habitats-sustainability) and upper estuary habitats experiencing tidal range expansion with sea-level rise (https://www.usgs.gov/ecosystems/climate-research-and-development-program/science/impacts-coastal-and-watershed-changes). Built into the design of this study is the rapid assimilation of collected data and model improvements into the Department of Energy (DOE) E3SM (https://e3sm.org/), which is one of the U.S. Federal government\u2019s premier global climate and earth system modeling platforms, optimized for DOE supercomputing environments. Data from the three marsh habitat sites will also contribute to regional and global carbon flux data research through the Ameriflux (https://ameriflux.lbl.gov/) and FLUXNET (https://fluxnet.org/) networks."
   },
   {
     "@type": "TextObject",
     "text": "This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Biological & Environmental Research (BER), Environmental System Science Award 89243020SSC000054."
   },
   {
     "@type": "TextObject",
     "text": "Related Project(s) or Products:"
   },
   {
     "@type": "TextObject",
     "text": "The Science Issue and Relevance: Accurately predicting terrestrial net methane (CH4) fluxes from wetlands depends on multiple physical, biological, and chemical mechanisms that are poorly understood, oversimplified, or missing in regional and global biogeochemical models. The role of natural wetland emissions, including coastal wetlands, in the past decade\u2019s sharp increase of global methane atmospheric concentration is hotly debated. Part of that debate points to a divergence between model-based and observation-based bottom-up scaling approaches that add emission estimates per wetland type, and top-down approaches that interpret remote sensing observations of methane concentrations in the atmosphere. Methane emissions from wetland and other inland waters are considered the largest source of uncertainty in global CH4 fluxes. The global warming potential of CH4 is 28\u201345 times that of an equal mass of carbon dioxide (CO2) over 100 years and is thus a globally important flux for future climate projections."
   }
 ],
 "funder": {
   "@type": "Organization",
   "name": "Wetland and Aquatic Research Center",
   "url": "https://www.usgs.gov/centers/wetland-and-aquatic-research-center"
 },
 "about": [
   {
     "@type": "Thing",
     "name": "Freshwater"
   },
   {
     "@type": "Thing",
     "name": "Information Systems"
   },
   {
     "@type": "Thing",
     "name": "Wetland Ecology"
   },
   {
     "@type": "Thing",
     "name": "Monitoring and Detection"
   },
   {
     "@type": "Thing",
     "name": "Plants"
   },
   {
     "@type": "Thing",
     "name": "Energy"
   },
   {
     "@type": "Thing",
     "name": "coastal ecosystems"
   },
   {
     "@type": "Thing",
     "name": "wetlands"
   },
   {
     "@type": "Thing",
     "name": "Science Technology"
   },
   {
     "@type": "Thing",
     "name": "Coastal Ecology"
   },
   {
     "@type": "Thing",
     "name": "Biology"
   },
   {
     "@type": "Thing",
     "name": "Wetlands"
   },
   {
     "@type": "Thing",
     "name": "methane"
   },
   {
     "@type": "Thing",
     "name": "Environmental Health"
   },
   {
     "@type": "Thing",
     "name": "Water"
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     "@type": "Thing",
     "name": "Climate Change"
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     "name": "Brackish"
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     "@type": "Thing",
     "name": "Methods and Analysis"
   },
   {
     "@type": "Thing",
     "name": "Geology"
   },
   {
     "@type": "Thing",
     "name": "Priority Landscapes"
   },
   {
     "@type": "Thing",
     "name": "Ecosystems"
   },
   {
     "@type": "Thing",
     "name": "Saltwater"
   }
 ]

}