Automated Author Profile

Tangen, Brian A.

0000-0001-5157-9882

Current S-Index

30.0

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

1.4

Average Dataset Index per dataset

Total Datasets

21

Total datasets for this author

Average FAIR Score

40.3%

Average FAIR Score per dataset

Total Citations

33

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Water quality data from wetlands in North Dakota, USA, 2019

This data release describes data that were contributed to the Global Lakes Ecosystem Observation Network (GLEON) FunAqua project, a global data compilation effort. Goals of the FunAqua project are to document the drivers of global aquatic fungal diversity and determine the breadth of the niche of aquatic fungi locally, globally, and in relation to soil and leaves. Data contributed by the U.S. Geological Survey, Northern Prairie Wildlife Research Center include standard water-quality parameters (dissolved oxygen, pH, water temperature) that were measured during the collection of water and soil samples, which were submitted to the project for fungal analyses. Data and samples were collected during August of 2019 from natural wetlands and experimental ponds located Stutsman County, North Dakota, USA.

Authors

  • Brian Tangen ;
  • Sheel Bansal
0 Citations0 Mentions46% FAIR1.1 Dataset Index
10.5066/p1s65i9xJanuary 2025

Greenhouse gas concentrations and water-quality parameters from experimental ponds in North Dakota, USA, 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.

Authors

  • Brian Tangen ;
  • Sheel Bansal
0 Citations0 Mentions46% FAIR1.0 Dataset Index
10.5066/p13wtathJanuary 2025

Greenhouse gas fluxes and dissolved greenhouse gas concentrations from wetland soil microcosms treated with herbicides

This data release presents data from a laboratory microcosm study examining the potential effects of herbicide application on the production and flux of greenhouse gases from wetland soils. Wetland soils were placed into glass mason jars and covered with water. Microcosms were treated with varying concentrations (none, low, medium, high) and combinations of the herbicides glyphosate and 2,4-D. Following herbicide application greenhouse gas fluxes were measured and concentrations of dissolved greenhouse gases were determined periodically over a 21-day period.

Authors

  • Sheel Bansal ;
  • Jacob A Meier ;
  • Olivia F Johnson ;
  • Brian Tangen
1 Citation0 Mentions13% FAIR0.7 Dataset Index
10.5066/p990rjt8January 2024

Chemical and isotopic data from wetland pond water samples collected in the Cottonwood Lake Study Area, Stutsman County, North Dakota, USA, 2015–2019

This U.S. Geological Survey data release contains chemical, isotopic, and physical data from wetland pond water samples collected at the Cottonwood Lake Study Area, Stutsman County, North Dakota, USA. Samples were collected monthly during the growing season (April or May through September) in 2015, 2016, 2017, and 2019 and in August 2018. Temperature, specific conductance, and pH were measured in situ. Major cations, select trace cations, chloride, fluoride, sulfate, and nitrate were determined for all samples. Stable oxygen and hydrogen isotope ratios of water were determined for samples collected from 2015 to 2017. Total dissolved nitrogen, dissolved organic carbon, absorbance at 254 nm, and stable carbon isotope ratios of dissolved inorganic carbon were determined for samples collected in 2015 and 2016. Dissolved ammonium and phosphate were determined for samples collected in 2016 and April and May 2017.

Authors

  • Brian Tangen ;
  • Christopher Mills ;
  • David M Mushet ;
  • Matthew J Solensky ;
  • R. Blaine McCleskey ;
  • JoAnn M Holloway
0 Citations0 Mentions46% FAIR0.3 Dataset Index
10.5066/p149emvxJanuary 2024

Carbon dioxide flux, vegetation, and soils data from artificial ponds in North Dakota, USA, 2021

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.

Authors

  • Bansal, Sheel ;
  • Meier, Jacob A ;
  • Johnson, Olivia F ;
  • Tangen, Brian
0 Citations0 Mentions46% FAIR1.0 Dataset Index
10.5066/p9gg4mt4January 2022

Water and ice characteristics from Hobart Lake National Wildlife Refuge, Barnes County, North Dakota, USA, 2021

This data release presents data that were collected as part of a larger effort to refine knowledge pertaining to the origin, composition, and seasonality of dissolved organic matter in lakes. This work was part of an international collaborative effort with the Global Lake Ecological Observatory Network (GLEON). Water samples were collected monthly during 2021 and shipped to GLEON for determination of dissolved organic matter. In conjunction with each monthly sample event, several water-quality variables and ice thickness were measured. Data from this collaborative study will be used to understand how the origin and composition of dissolved organic matter varies through time.

Authors

  • Bansal, Sheel ;
  • Meier, Jacob A ;
  • Tangen, Brian
1 Citation0 Mentions46% FAIR1.3 Dataset Index
10.5066/p9aqwy13January 2022

Methane flux model for wetlands of the Prairie Pothole Region of North America: Model input data and programming code

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).

Authors

  • Bansal, Sheel ;
  • Tangen, Brian
5 Citations0 Mentions46% FAIR2.7 Dataset Index
10.5066/p9pki29cJanuary 2022

Properties of ice cores from Hobart Lake, North Dakota, USA, 2021

This data release presents data that were collected as part of a larger effort (Global Lake Ecological Observatory Network [GLEON] IceBlitz) to enhance understanding of the spatial and temporal variation in global lake ice properties. During January and February of 2021 ice cores were extracted from Hobart Lake, North Dakota, USA and characterized following standard procedures. Characteristics of the cores were recorded, including thickness of distinct layers and presence of visible bubbles and impurities. Surface conditions (e.g., snow, slush) were also characterized and water and air temperature were measured and recorded.

Authors

  • Bansal, Sheel ;
  • Meier, Jacob A ;
  • Johnson, Olivia F ;
  • Tangen, Brian
0 Citations0 Mentions13% FAIR0.1 Dataset Index
10.5066/p90cn2tiJanuary 2022

Dissolved oxygen, temperature, and light measured along the water-depth profile of wetlands in North Dakota, USA, 2019

This data release presents data that were collected as part of a larger effort to assess factors that regulate ecosystem metabolism in small ponds. This work was part of an international collaborative effort with the Global Lake Ecological Observatory Network (GLEON). From May to October 2019, dissolved oxygen, temperature, and light were measured throughout the water-depth profile of two natural wetlands and four artificial ponds located near Jamestown, North Dakota. Meteorological and bathymetric data also were collected. The natural wetlands are representative of semipermanent wetlands of the Prairie Pothole Region of North America. The artificial ponds, while smaller than the natural ponds, were managed to represent small inland wetlands of the Prairie Pothole Region. The Artificial ponds are managed by the U.S. Geological Survey Northern Prairie Wildlife Research Center. Data from this collaborative study will be used to understand how small inland ponds differ from large lakes and coastal systems, specifically with regard to nutrient recycling, primary production, greenhouse gas emissions, and oxygen dynamics.

Authors

  • Bansal, Sheel ;
  • Meier, Jacob A ;
  • Johnson, Olivia F ;
  • Tangen, Brian
0 Citations0 Mentions46% FAIR1.0 Dataset Index
10.5066/p9cmfewpJanuary 2022

Soil profile characteristics of Prairie Pothole Region wetland catchments, 2004

A study was conducted during 2004 to examine soil carbon storage of Prairie Pothole Region wetland catchments. These data represent the soil profile descriptions performed during that study; the remaining data were published previously (https://doi.org/10.5066/F7KS6QG2). Soil profile descriptions were performed at 270 temporary, seasonal, and semipermanent wetland catchments distributed throughout the Glaciated Plains and Missouri Coteau physiographic regions of the Prairie Pothole Region. Data were collected from four to six wetland and upland zones of the catchment. Study sites included cropland, restored grassland (formerly cropland), and native prairie (no cultivation history) catchments located in Iowa, Minnesota, Montana, North Dakota, and South Dakota.

Authors

  • Tangen, Brian
0 Citations0 Mentions13% FAIR0.1 Dataset Index
10.5066/p9hg4eqoJanuary 2021