This data release presents data that were collected as part of a larger effort to assess the carbon balance of recently exposed (i.e., no vegetation cover) wetland sediments. This work was part of an international collaborative effort associated with the Dryflux II project. During June and July 2021, data were collected from three artificial ponds located near Jamestown, North Dakota, to estimate carbon dioxide flux, vegetation characteristics, and soil properties. Numerous covariates related to atmospheric and soil conditions also were measured. Water levels of the artificial ponds, which are managed by the U.S. Geological Survey Northern Prairie Wildlife Research Center, were manipulated to mimic the natural drying cycle of prairie wetlands. This management resulted in exposed sediments where samples were collected. Data from this collaborative study will be used to better understand the carbon balance of wetland soils associated with fluctuating wet and dry conditions, and to refine global estimates of carbon dioxide emissions from dry inland waters.

A study was conducted to assess the relationships among carbon mineralization, sulfate reduction and greenhouse gas emissions in prairie pothole wetlands. These data are for dissolved methane and carbon dioxide concentrations and fluxes. Dissolved gas concentrations in the water column and fluxes to the atmosphere were estimated from April through November, 2015 for wetlands P7 and P8 of the Cottonwood Lake Study area, Stutsman County, North Dakota. Dissolved gases in the water column were collected every two weeks using a pumping-induced ebullition device. Gas flux samples were collected concurrently at the water-atmosphere interface using the vented static-chamber method. Gas concentrations of the gas samples were determined using gas chromatography. Air and water temperature and water depth also were collected concurrently. These data directly support the associated publication “Abundant carbon substrates drive extremely high sulfate reduction rates and methane fluxes in Prairie Pothole Wetlands” which is referenced within the Metadata.

A study was conducted to assess the relationships among carbon mineralization, sulfate reduction and greenhouse gas emissions in prairie pothole wetlands. These data are for dissolved methane and carbon dioxide concentrations and fluxes. Dissolved gas concentrations in the water column and fluxes to the atmosphere were estimated from April through November, 2015 for wetlands P7 and P8 of the Cottonwood Lake Study area, Stutsman County, North Dakota. Dissolved gases in the water column were collected every two weeks using a pumping-induced ebullition device. Gas flux samples were collected concurrently at the water-atmosphere interface using the vented static-chamber method. Gas concentrations of the gas samples were determined using gas chromatography. Air and water temperature and water depth also were collected concurrently. These data directly support the associated publication “Abundant carbon substrates drive extremely high sulfate reduction rates and methane fluxes in Prairie Pothole Wetlands” which is referenced within the Metadata.

This data release describes data that were contributed to the GasHype project, a global data compilation effort. Goals of the GasHype project include assessing concentrations of carbon dioxide and methane in the hypolimnion of lakes, reservoirs, and ponds, and identifying important drivers of these concentrations. Data contributed by the U.S. Geological Survey, Northern Prairie Wildlife Research Center include concentrations of dissolved greenhouse gases along with various water quality parameters from experimental ponds located near Jamestown, North Dakota, USA. Samples and data were collected from four ponds during the period of May through September, 2019.

This data release describes data that were contributed to the GasHype project, a global data compilation effort. Goals of the GasHype project include assessing concentrations of carbon dioxide and methane in the hypolimnion of lakes, reservoirs, and ponds, and identifying important drivers of these concentrations. Data contributed by the U.S. Geological Survey, Northern Prairie Wildlife Research Center include concentrations of dissolved greenhouse gases along with various water quality parameters from experimental ponds located near Jamestown, North Dakota, USA. Samples and data were collected from four ponds during the period of May through September, 2019.

This data release encompass numerous studies examining soil properties and greenhouse gas fluxes of Prairie Pothole Region (PPR) wetland catchments. The PPR is one of the largest wetland ecosystems in the world, encompassing approximately 770,000 square kilometers of the north-central U.S. and south-central Canada, with the U.S. portion including parts of Iowa, Minnesota, South Dakota, North Dakota, and Montana. The data included in this release span a 19-year period (1997–2016) and represent a diversity of studies ranging from localized (e.g., wetland catchments and complexes) to region-wide efforts that span the PPR’s climate and land-use gradient. Data from individual wetland catchments encompass a variety of wetland classes ranging from small, ephemerally-ponded wetlands to large, shallow lakes. Although study designs and methodologies differ slightly among the studies, the overarching methods are comparable and allow the data to be combined into a single data release. The data release consists of combined datasets (i.e., all studies) for soils, greenhouse gases, topography, water chemistry, weather, and covariate or explanatory variables such as water depth, soil moisture, and temperature. A majority of the studies also present data from the entire wetland catchment, with data collected from numerous landscape positions along transects spanning from the wetland center to the catchment boundary. Sample frequency among the studies ranges from a single site visit per year, to season-long, biweekly sample events across multiple years.

This data release encompass numerous studies examining soil properties and greenhouse gas fluxes of Prairie Pothole Region (PPR) wetland catchments. The PPR is one of the largest wetland ecosystems in the world, encompassing approximately 770,000 square kilometers of the north-central U.S. and south-central Canada, with the U.S. portion including parts of Iowa, Minnesota, South Dakota, North Dakota, and Montana. The data included in this release span a 19-year period (1997–2016) and represent a diversity of studies ranging from localized (e.g., wetland catchments and complexes) to region-wide efforts that span the PPR’s climate and land-use gradient. Data from individual wetland catchments encompass a variety of wetland classes ranging from small, ephemerally-ponded wetlands to large, shallow lakes. Although study designs and methodologies differ slightly among the studies, the overarching methods are comparable and allow the data to be combined into a single data release. The data release consists of combined datasets (i.e., all studies) for soils, greenhouse gases, topography, water chemistry, weather, and covariate or explanatory variables such as water depth, soil moisture, and temperature. A majority of the studies also present data from the entire wetland catchment, with data collected from numerous landscape positions along transects spanning from the wetland center to the catchment boundary. Sample frequency among the studies ranges from a single site visit per year, to season-long, biweekly sample events across multiple years.

This data release presents input data for plot- and landscape-scale models of Prairie Pothole Region wetland methane emissions as a function of explanatory variables and remotely sensed predictors. Field data for the plot- and landscape-scale models span the years 2003-2016 and 2005-2016, respectively. The data release also includes R programming code to run the generalized additive model (GAM; plot scale) and random forest (RF; landscape scale) model of methane flux rates. Input data were extracted and modified from existing sources, and combined to facilitate model development, as well as six scenario-based model runs (two historical, four future). Briefly, a bottom-up approach was used to develop a spatially explicit, temporally dynamic model of methane emissions from Prairie Pothole Region (PPR) wetlands. A dataset of greater than 18,000 static-chamber flux measurements along with environmental covariates was used to develop a chamber-based (plot) model of methane flux, which was then used to inform a landscape-model using remotely sensed predictors. Covariates for the chamber-based model included soil water-filled pore space, soil temperature, wetland size, hydroperiod, land cover, growing season interval, and normalized difference vegetation index (NDVI). Predictors for upscaling included the Dynamic Surface Water Extent based on Landsat 4, 5, 7, and 8 for the presence, permanence, and extent of surface water, ClimateNA for historical and future temperatures, and the North American Land Change Monitoring System for land cover. Model runs included historical dry (1991) and wet (2011) years, as well as future Socioeconomic Pathways emissions scenarios (SSP2-4.5, SSP5-8.5).

This data release presents input data for plot- and landscape-scale models of Prairie Pothole Region wetland methane emissions as a function of explanatory variables and remotely sensed predictors. Field data for the plot- and landscape-scale models span the years 2003-2016 and 2005-2016, respectively. The data release also includes R programming code to run the generalized additive model (GAM; plot scale) and random forest (RF; landscape scale) model of methane flux rates. Input data were extracted and modified from existing sources, and combined to facilitate model development, as well as six scenario-based model runs (two historical, four future). Briefly, a bottom-up approach was used to develop a spatially explicit, temporally dynamic model of methane emissions from Prairie Pothole Region (PPR) wetlands. A dataset of greater than 18,000 static-chamber flux measurements along with environmental covariates was used to develop a chamber-based (plot) model of methane flux, which was then used to inform a landscape-model using remotely sensed predictors. Covariates for the chamber-based model included soil water-filled pore space, soil temperature, wetland size, hydroperiod, land cover, growing season interval, and normalized difference vegetation index (NDVI). Predictors for upscaling included the Dynamic Surface Water Extent based on Landsat 4, 5, 7, and 8 for the presence, permanence, and extent of surface water, ClimateNA for historical and future temperatures, and the North American Land Change Monitoring System for land cover. Model runs included historical dry (1991) and wet (2011) years, as well as future Socioeconomic Pathways emissions scenarios (SSP2-4.5, SSP5-8.5).

These datasets represent a revised national scale estimate of wetland soil carbon stock assessments by improving representation of soil organic carbon densities. This assessment is based on a three-step approach to harmonize survey and point-based data for predicting soil organic carbon density from percent organic carbon alone (or percent organic matter, with conversion), when reliable dry bulk density information is not available. Given issues with survey-level extrapolation of soil pedons into discontinuous hydric soils, quantile, segmented data analysis provides a more accurate spatially explicit soil organic carbon density product. These modeled data leverage spatial and statistical distributions of soil organic carbon percent data of the conterminous United States (CONUS) for two national-scale soil datasets: a wetland-specific field campaign, the EPA National Wetland Condition Assessment, and the USDA NRCS SSURGO survey. See https://doi.org/10.3389/fsoil.2021.706701 for details.