|CROOKSTON, BRADLEY - Utah State University|
|YOST, MATT - Utah State University|
|BOWMAN, MARIA - National Corn Growers Association|
|CARDON, GRANT - Utah State University|
|NORTON, JEANETTE - Utah State University|
Submitted to: The Global Journal of Soil Security Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/7/2021
Publication Date: 5/15/2021
Citation: Crookston, B.S., Yost, M.A., Bowman, M., Veum, K.S., Cardon, G.E., Norton, J.M. 2021. Soil health spatial-temporal variation influence soil security on Midwestern, U.S. farms. Soil Security. 3. Article 100005. https://doi.org/10.1016/j.soisec.2021.100005.
Interpretive Summary: Soil health testing is becoming increasingly popular, but interpretation of soil health indicators requires an understanding of how indicators vary across time and space and how they are influenced by climate and soil information. This study evaluated 16 soil health indicators and associated management and climate data collected from 2014-2019 from a multi-state, on-farm, strip-trial program in the Midwestern U.S. Indicators with high and low spatial and temporal variability were identified and several indicators exhibited similar trends in temporal variability. Important climate factors affecting variability were also identified, and select measurements, including soil respiration, organic matter, and water content, helped improve estimates of yield variation for corn and soybean. This information will benefit producers by providing a better understanding of soil and crop yield variability and will contribute to improved soil health interpretations for landowners.
Technical Abstract: Soil security is a multifaceted framework that considers soil as an integral part of addressing societal concerns towards global environmental challenges. Soil health assessments are tools that can be used to integrate knowledge about and social interest in soil resource sustainability. Appropriate interpretation of soil health assessments require robust databases of soil properties and their variation across large regional areas. This analysis explored field-scale spatial and temporal variation in 16 soil health indicators used in common soil health assessments at Soil Health Partnership (SHP) locations throughout the Midwestern U.S. from 2014–2019. Relationships among management, environment, and measured soil properties were examined using various combinations of correlation, principal component analysis (PCA), and multiple regression. Specifically, variability was evaluated using 1) the temporal average of indicator lab test values, 2) the temporal and spatial coefficient of variation (CV), and 3) corn (Zea mays) and soybean (Glycine max) yield variation. Solvita® had the highest spatial and temporal CV, while organic matter (OM), autoclaved citrate extractable protein (ACE), and pH had the lowest spatial and temporal CV values. The PCA analysis identified climate, soil texture, organic C and N pools, and soil water availability as factors that accounted for variation in soil health indicator values. Multiple regression showed that climate variables and field conditions strongly affect corn and soybean yield variation. Solvita, OM, and available water content improved corn and soybean yield variation estimates. These results show that considering spatial and temporal variation when monitoring soil health changes may improve soil health assessment interpretation.