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    Spatial Modeling for Resources Framework (SMRF) was developed at the USDA Agricultural Research Service (ARS) in Boise, ID, and was designed to increase the flexibility of taking measured weather data and distributing the point measurements across a watershed.

    Automated Water Supply Model (AWSM)

      Automated Water Supply Model (AWSM) was developed at the USDA Agricultural Research Service in Boise, ID, to streamline the workflow used to forecast the water supply of multiple water basins.

      Spatial Modeling for Resources Framework (SMRF)

        Spatial Modeling for Resources Framework (SMRF) was developed at the USDA Agricultural Research Service (ARS) in Boise, ID, and was designed to increase the flexibility of taking measured weather data and distributing the point measurements across a watershed.

        Orussus abietinus Official Gene Set OGSv1.0

          The Orussus abietinus genome was recently sequenced and annotated as part of the i5k pilot project by the Baylor College of Medicine. The Orussus abietinus research community has manually reviewed and curated the computational gene predictions and generated an official gene set, OGSv1.0. The general procedure for generating this OGS is outlined here: https://github.com/NAL-i5K/I5KNAL_OGS/wiki. OGSv1.0 was generated by merging gene set OABI-V0.5.3-Models generated by the Baylor College of Medicine, and community-curated models in the Apollo software, after QC of the Apollo output.

          Athalia rosae Official Gene Set OGSv1.0

            The Athalia rosae genome was recently sequenced and annotated as part of the i5k pilot project by the Baylor College of Medicine. The Athalia rosae research community has manually reviewed and curated the computational gene predictions and generated an official gene set, OGSv1.0. The general procedure for generating this OGS is outlined here: https://github.com/NAL-i5K/I5KNAL_OGS/wiki. OGSv1.0 was generated by merging gene set AROS-V0.5.3-Models generated by the Baylor College of Medicine, and community-curated models in the Apollo software, after QC of the Apollo output.

            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.

                Useful to Usable: Developing usable climate science for agriculture

                  Useful to Usable (U2U): Transforming Climate Variability and Change Information for Cereal Crop Producers, was a USDA-funded research and extension project designed to improve the resilience and profitability of U.S. farms in the Corn Belt amid a changing climate. Over a six-year period from April 2011 - April 2017, 122 faculty, staff, graduate students, and undergraduate students from ten Midwestern universities contributed to this interdisciplinary project. Our team integrated expertise in applied climatology, crop modeling, agronomy, cyber-technology, agricultural economics, sociology, Extension and outreach, communication, and marketing to improve the use and uptake of climate information for agricultural decision making. Together, and with members of the agricultural community, we developed a series of decision support tools, resource materials, and training methods to support data-driven decision making and the adoption of climate-resilient practices.

                  Anoplophora glabripennis Official Gene Set OGSv1.2

                    The *Anoplophora glabripennis* genome was recently sequenced, assembled and annotated as part of the i5k pilot project by the Baylor College of Medicine, in collaboration with the McKenna Laboratory at the University of Memphis. The *Anoplophora glabripennis* research community has manually reviewed and curated the computational gene predictions and generated an official gene set, OGSv1.2. OGSv1.2 was generated by merging gene set AGLA-c0.5.3-Models generated by the Baylor College of Medicine, and community-curated models in the Apollo software, after QC of the Apollo output.

                    Data from: Chromosome-level genome assembly and transcriptome of the green alga Chromochloris zofingiensis illuminates astaxanthin production

                      For genome assembly of *C. zofingiensis* strain SAG 211–14, we used a hybrid approach blending short reads (Illumina), long reads (Pacific Biosciences of California), and whole-genome optical mapping (OpGen) (SI Appendix, SI Text and Datasets S1–S19, and refer to SI Appendix, Datasets Key). The combined power of these approaches yielded a high-quality haploid nuclear genome of *C. zofingiensis* of ∼58 Mbp distributed over 19 chromosomes (Fig. 2) in the tradition of model organism projects, as opposed to the fragmentary “gene-space” assemblies typical of modern projects using high-throughput methods and associated software. Approximately 99% of reads from the Illumina genomic libraries were accounted for, and nonplaceholder chromosomal sequence covers ∼94% of the optical map. Because no automated pipeline was found able to achieve the desired quality, methods are described in SI Appendix, SI Text.