U.S. flag

An official website of the United States government

Data from: Effect of Source on Trust of Pulse Nutrition Information and Perceived Likelihood of Following Dietary Guidance

    The purpose of the present study was to examine how information source (control—no source, USDA, fictitious hospital, or fictitious social media) impacts perceptions of diet information. Participants included 943 American adults who were aged 18-74 years and were recruited from across the United States through Amazon Mechanical Turk (MTurk). ANOVA results indicated that the USDA and hospital sources were perceived as more accurate, trustworthy, reliable, and more desirable to learn more from relative to control and social media. There were no differences in likelihood of following guidance depending on source.

    Sorption Isotherm Spreadsheet

      Spreadsheet from the paper entitled: On the Use of Linearized Langmuir Equations by C.H. Bolster and G.M. Hornberger, Soil Science Society of America Journal, 2007, 71(6): 1796-1806.


        Statistical software package for estimating field scale spatial salinity patterns from electromagnetic induction signal data (for Windows XP)

        Stream Temperature Modeling and Monitoring: Air Temperature Based Thermal Stream Habitat Model

          The Air Temperature Based Thermal Stream Habitat Model was originally developed from weather station information across the Columbia River basin in the Pacific Northwest. Multiple regression was used to predict mean annual air temperatures from elevation, latitude, and longitude with good success R^2 ~ 0.89). The model was developed as an alternative to PRISM data interpolations based on spline surface smoothing and should more accurately represent thermal conditions in stream valleys.

          Stream Temperature Modeling and Monitoring: Multiple Regression Stream Temperature Model

            This simple Stream Temperature Modeling and Monitoring approach uses thermograph data and geomorphic predictor variables from GIS software and digital elevation models (DEM). Multiple regression models are used to predict stream temperature metrics throughout a stream network with moderate accuracy (R^2 ~ 0.65). The models can provide basic descriptions of spatial patterns in stream temperatures, suitable habitat distributions for aquatic species, or be used to assess temporal trends related to climate or management activities if multiple years of temperature data are available.