Crop sequence complexity of the major land resource areas (MLRA) in the contiguous United States (CONUS)

Abstract

Quantifying spatial and temporal dynamics of crop sequences is often accomplished through crop biodiversity metrics. Existing metrics are confounded by crop sequence length, subsequence repetition, and perennialization. Our objective was to formulate a Crop Sequence Complexity Index (CSCI) that accounts for differences in crop sequence lengths, crop sequence compressibility, functional type transitions, and back-to-back perennials. Additionally, we mapped the distribution of crop sequence metrics across the Contiguous United States (CONUS). We joined Crop Sequence Boundary data from the USDA-NASS for two periods: (2008–2015) and (2016–2023) to assemble the 16-year crop sequence of 13.5 million field centroids between 2008 and 2023 and calculated crop sequence metrics aggregated by Major Land Resource Areas (MLRA). We also examined the correlations among crop sequence complexity metrics. We found CSCI was less correlated with both crop sequence length and the number of back-to-back perennials in a crop sequence compared to the Rotational Complexity Index (RCI). Consequently, RCI tended to be lower in MLRA where annual cropping systems dominated, such as the Corn Belt, Mississippi River Basin, and southern Great Plains, and RCI was highest in the irrigated southwestern US. In contrast, CSCI was highest in the northern Great Plains and lowest in the southern Great Plains, with intermediate values throughout most of CONUS. Crop sequences in CONUS usually consist of a very limited number of species. However, crop sequence complexity varies widely because of how sequences ordered functional type transitions, and perennialization. While biophysical constraints are important, socioeconomic factors drive crop sequence complexity.