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ARS Home » Plains Area » Mandan, North Dakota » Northern Great Plains Research Laboratory » Research » Publications at this Location » Publication #424062
Research Project: Transdisciplinary Research that Improves the Productivity and Sustainability of Northern Great Plains Agroecosystems and the Well-Being of the Communities They Serve

Location: Northern Great Plains Research Laboratory

Title: Crop Sequence Complexity of the Major Land Resource Areas (MLRA) in the Contiguous United States (CONUS)

Author
item Whippo, Craig
item COALE, ELLEN - University Of California, Davis
item IGATHINATHANE, C. - North Dakota State University
item Friedrichsen, Claire
item Archer, David
item Heintzman, Lucas

Submitted to: Agriculture, Ecosystems & Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/23/2025
Publication Date: 9/25/2025
Citation: Whippo, C.W., Coale, E., Igathinathane, C., Friedrichsen, C.N., Archer, D.W., Heintzman, L.J. 2025. Crop Sequence Complexity of the Major Land Resource Areas (MLRA) in the Contiguous United States (CONUS). Agriculture, Ecosystems & Environment. v396. Article 110003. https://doi.org/10.1016/j.agee.2025.110003.
DOI: https://doi.org/10.1016/j.agee.2025.110003

Interpretive Summary: We developed and tested a new way to measure crop sequence complexity and analyzed crop sequence patterns across the lower 48 states of the United States using 16 years (2008-2023) from 13.6 million fields. The new Crop Sequence Complexity Index (CSCI) improves upon existing measurement tools by better accounting for factors like crop sequence length, repeating patterns, crop functional types, and use of perennial crops. When compared to a previous measurement called the Rotational Complexity Index (RCI), the CSCI provided different insights into regional crop sequence patterns. The northern Great Plains had the most complex crop sequences, while the southern Great Plains had the simplest. Crop sequences in the Corn Belt also had relatively simple patterns when measured by RCI but had moderate complexity when measured with the new CSCI measurement. While most producers use a limited number of different crop species, the way they arrange these crops over time varies across regions. These decisions are influenced not only by environmental factors like weather and soil, but also by economic and social factor.

Technical Abstract: Diverse cropping systems can provide many benefits. But existing ways to measure crop biodiversity do not capture details that may be important for understanding potential benefits. We developed and tested a new way to measure crop sequence complexity. We analyzed crop sequence patterns across the lower 48 states of the United States during 16 years (2008-2023) from 13.6 million fields. The new Crop Sequence Complexity Index (CSCI) better accounts for factors like crop sequence length, repeating patterns, crop types, and perennial crops. Compared to a previous measurement called the Rotational Complexity Index (RCI), the CSCI provided different insights into regional crop sequence patterns. While most producers use a limited number of different crop species, the way they arrange these crops over time varies across regions. The northern Great Plains had the most complex crop sequences, while the southern Great Plains had the simplest. Crop sequences in the Corn Belt had relatively simple patterns when measured by RCI but had moderate complexity with the new CSCI measurement. The CSCI is useful to producers, land managers, researchers, and policy makers for better understanding regional cropping practices and ways that management changes could increase crop system biodiversity and associated benefits.