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Nitrogen Decision Aid

    The Nitrogen Decision Aid is a computerized program that predicts the amount of N mineralized from planting to side-dress or 5-leaf growth-stage. By applying just enough N-fertilizer to reach the critical soil nitrate concentration it is possible reduce this waste. This model is designed for Northern climates that will have some frost in the soil during the winter.

    RZWQM2

      Root Zone Water Quality Model 2 (RZWQM2) is a whole-system model for studying crop production and environmental quality under current and changing climate conditions. It emphasizes the effects of agricultural management practices on physical, chemical and biological processes. RZWQM2 is a one-dimensional model with a pseudo 2-dimensional drainage flow. Crop simulation options include the generic plant growth model, DSSAT-CSM 4.0 and HERMES SUCROS models. It also can simulate surface energy balance with components from the SHAW model and water erosion from the GLEAMS model. An automated parameter estimation algorithm (PEST) was added to RZWQM2 for objective model calibration and uncertainty analysis.

      Data from: Range size, local abundance and effect inform species descriptions at scales relevant for local conservation practice

        This study describes how metrics defining invasions may be more broadly applied to both native and invasive species in vegetation management, supporting their relevance to local scales of species conservation and management. A sample monitoring dataset is used to compare range size, local abundance and effect as well as summary calculations of landscape penetration (range size × local abundance) and impact (landscape penetration × effect) for native and invasive species in the mixed-grass plant community of western North Dakota, USA.

        RF-CLASS: Remote-sensing-based Flood Crop Loss Assessment Service System

          The Remote-sensing-based Flood Crop Loss Assessment Service System (RF-CLASS) is an Earth Observation (EO) based flood crop loss assessment cyber-service system operated by the Center for Spatial Information Science and Systems (CSISS), George Mason University. RF-CLASS supports flood-related crop statistics and insurance decision-making.

          Complete Data and Analysis for: Fungicide Effectiveness on Soybean Rust in the Southeastern United States 2004-2014: A Meta-Analysis

            Soybean rust is a concern to soybean growers and management of soybean rust primarily depends on disease scouting and the timely use of fungicides. The goal of this study was to evaluate the efficacy of fungicide-use through a quantitative meta-analysis of data compiled from published and unpublished soybean fungicide trials across the southern United States from 2004 to 2014. The data included in this repository includes the complete dataset as a comma-separated-value file and all Program R code necessary to replicate the data processing, analysis, and graphing.

            Arctic Peregrine Falcon Abundance on Cliffs Along the Colville River, Alaska, 1981-2002 and Covariate Input Files

              This data set consists of fourteen data files. Rcode_arctic_peregrine_abundance.R contains R code that was used to analyze Arctic peregrine falcon data collected between 1981 and 2002. The code primarily uses the R package "UNMARKED" and is based on the Dail-Madsen model for estimating population abundance. To run this code in an R environment, download the file and open it in an R interpreter (such as RStudio). The remaining files are all covariate matrices that act as inputs to the R code.

              ELIGULUM-A regulates lateral branch and leaf development. Original figure files

                TIFF and JPEG files for the photographs used in constructing figures and supplemental figures in the manuscript, "ELIGULUM-A regulates lateral branch and leaf development," submitted to Plant Physiology. The images document a mutation that alters most of the structures of the plant and how the ELIGULUM-A gene interacts with different developmental pathways. The Figure Legend files describe the images individually.