U.S. cereal rye winter cover crop growth database
Alexandra Huddell, Resham Thapa, Guillermo S. Marcillo, Lori Abendroth, Victoria J. Ackroyd, Shalamar D. Armstrong, Gautam Asmita, Muthukumar Bagavathiannan, Kipling S. Balkcom, Andrea Basche, Shawn C. Beam, Kevin W. Bradley, Lucas Pecci Canisares, Heather Darby, Adam S. Davis, Pratap Devkota, Warren A. Dick, Jeffery A. Evans, Wesley J. Everman, Tauana Ferreira de Almeida, Michael L. Flessner, Lisa M. Fultz, Stefan Gailans, Masoud Hashemi, Joseph Haymaker, Matthew J. Helmers, Nicholas R. Jordan, T. C. Kaspar, Quirine M. Ketterings, E. J. Kladivko, Alexandra Kravchenko, Eugene P. Law, Lauren Lazaro, Ramón G. León, Jeffrey Liebert, John L. Lindquist, Kristen A. Loria, Jodie M. McVane, Jarrod O. Miller, Michael J. Mulvaney, Nsalambi V. Nkongolo, Jason K. Norsworthy, Binaya Parajuli, Christopher Pelzer, Cara M. Peterson, Hanna Poffenbarger, Pratima Poudel, Mark S. Reiter, Matthew D. Ruark, Matthew R. Ryan, Spencer Samuelson, John E. Sawyer, Sarah Seehaver, Lovreet S. Shergill, Yogendra Raj Upadhyaya, Mark J. VanGessel, Ashley Waggoner, John M. Wallace, M. Scott Wells, Charles M. White, Bethany Wolters, Alex Woodley, Rongzhong Ye, Eric Youngerman, Brian A. Needelman, Steven B. Mirsky
Abstract
Abstract Winter cover crop performance metrics (i.e., vegetative biomass quantity and quality) affect ecosystem services provisions, but they vary widely due to differences in agronomic practices, soil properties, and climate. Cereal rye (S ecale cereale ) is the most common winter cover crop in the United States due to its winter hardiness, low seed cost, and high biomass production. We compiled data on cereal rye winter cover crop performance metrics, agronomic practices, and soil properties across the eastern half of the United States. The dataset includes a total of 5,695 cereal rye biomass observations across 208 site-years between 2001–2022 and encompasses a wide range of agronomic, soils, and climate conditions. Cereal rye biomass values had a mean of 3,428 kg ha −1 , a median of 2,458 kg ha −1 , and a standard deviation of 3,163 kg ha −1 . The data can be used for empirical analyses, to calibrate, validate, and evaluate process-based models, and to develop decision support tools for management and policy decisions.