Data from: Starch and dextrose at 2 levels of rumen-degradable protein in iso-nitrogenous diets: Effects on lactation performance, ruminal measurements, methane emission, digestibility, and nitrogen balance of dairy cows.

This feeding trial was designed to investigate two separate questions. The first question is, “What are the effects of substituting two non-fiber carbohydrate (NFC) sources at two rumen-degradable protein (RDP) levels in the diet on apparent total-tract nutrient digestibility, manure production and nitrogen (N) excretion in dairy cows?”. This is relevant because most of the N ingested by dairy cows is excreted, resulting in negative effects on environmental quality. The second question is, “Is phenotypic residual feed intake (pRFI) correlated with feed efficiency, N use efficiency, and metabolic energy losses (via urinary N and enteric CH4) in dairy cows?”. The pRFI is the difference between what an animal is expected to eat, given its level of productivity, and what it actually eats. The goal was to determine whether production of CH4, urinary N or fecal N is a driver of pRFI.

Dairy CAP logo

The Range-Wide Bull Trout eDNA Project - USFS RMRS

The bull trout (Salvelinus confluentus) eDNA survey results Online Map allows users to view the survey results in an interactive map by coupling 1) predictions from the range-wide, spatially precise Climate Shield model on the location of natal habitats of bull trout with 2) a sampling template for every 8-digit hydrologic unit in the historical range of bull trout, based on the probability of detecting bull trout presence using environmental DNA (eDNA) sampling. The map provides the ability to zoom in and look at an area of interest, as well as to create queries or select an area to download points as a shapefile.

Genomics and Genetics

pySnobal

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.

Agroecosystems & Environment

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.

Agroecosystems & Environment

Data from: Agro-environmental consequences of shifting from nitrogen- to phosphorus-based manure management of corn.

This experiment was designed to measure greenhouse gas (GHG) fluxes and related agronomic characteristics of a long-term corn-alfalfa rotational cropping system fertilized with manure (liquid versus semi-composted separated solids) from dairy animals. Different manure-application treatments were sized to fulfill two conditions: (1) an application rate to meet the agronomic soil nitrogen requirement of corn (“N-based” without manure incorporation, more manure), and (2) an application rate to match or to replace the phosphorus removal by silage corn from soils (“P-based” with incorporation, less manure). In addition, treatments tested the effects of liquid vs. composted-solid manure, and the effects of chemical nitrogen fertilizer. The controls consisted of non-manured inorganic N treatments (sidedress applications). These activities were performed during the 2014 and 2015 growing seasons as part of the Dairy Coordinated Agricultural Project, or Dairy CAP, as described below. The data from this experiment give insight into the factors controlling GHG emissions from similar cropping systems, and may be used for model calibration and validation after careful evaluation of the flagged data.

Dairy CAP logo

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.

Arctic Peregrine Falcon

Greenhouse Gas Emissions from Croplands

This download provides three datasets aggregated from the original output of the 172 crops; total emissions from croplands, per kilocalorie emissions from croplands and per food kilocalorie emissions from cropland.

Agroecosystems & Environment

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.

Plants and Crops