Soil health indicator variability and management sensitivity across soils, bioregions, and agricultural systems

Authors: DYNARSKI, KATHERINE - Natural Resources Conservation Service (NRCS, USDA); ADELEKE, EKUNDAYO - Natural Resources Conservation Service (NRCS, USDA); BAUMHARDT, R - Retired ARS Employee; BURKE, JOSEPH - Texas A&M Agrilife; CARTER, TIFFANY - Natural Resources Conservation Service (NRCS, USDA); DELAUNE, PAUL - Texas A&M Agrilife; GAN, HUIJIE - Virginia Tech; GROSSMAN, JULIE - University Of Minnesota; HEITMAN, JOSHUA - North Carolina State University; KANDANOOL, DIVYA - University Of Missouri; LEWIS, KATIE - Texas A&M Agrilife; NAASKO, KATHERINE - Michigan State University; O'KELLEY, REGINA - Oregon State University; OSMOND, DEANNA - North Carolina State University; PERRONE, SHARON - University Of Minnesota; PRESLEY, DEANN - Kansas State University; RACELIS, ALEXIS - University Of Texas; TAO, HAIYING - University Of Connecticut; TOMLINSON, PETER - Kansas State University; STARR, LAURA - Kansas State University; UGARTE, CARMEN - University Of Illinois Urbana-Champaign; Veum, Kristen; WILLIAMS, CAITLIN - North Carolina State University; WILLS, SKYE - Natural Resources Conservation Service (NRCS, USDA)

Submitted to: Agriculture, Ecosystems & Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/28/2025
Publication Date: 1/2/2026
Citation: Dynarski, K.A., Adeleke, E., Baumhardt, R.L., Burke, J., Carter, T., Delaune, P., Gan, H., Grossman, J., Heitman, J., Kandanool, D., Lewis, K., Naasko, K., O'Kelley, R., Osmond, D., Perrone, S., Presley, D., Racelis, A., Tao, H., Tomlinson, P., Starr, L., Ugarte, C., Veum, K.S., Williams, C., Wills, S.A. 2026. Soil health indicator variability and management sensitivity across soils, bioregions, and agricultural systems. Agriculture, Ecosystems & Environment. 399. Article 110203. https://doi.org/10.1016/j.agee.2025.110203.
DOI: https://doi.org/10.1016/j.agee.2025.110203

Interpretive Summary: Soil health information systems have the potential to help farmers improve management decisions and optimize productivity and profitability outcomes across variable soil resources; however, current soil survey information systems do not include soil health data due to a lack of standardization and concerns related to reproducibility. This study evaluated 12 soil health indicators across a wide range of soils, regions, and management, and confirmed the need to account for site conditions to set benchmark soil health values. Further, this study identified multiple soil health indicators that were sensitive to management under warm and dry conditions. Overall, this study illustrates the potential to enhance soil information systems with soil health data to benefit farmers and land managers.

Technical Abstract: Soil health indicators inherently vary across soils and landscapes due to soil-forming factors unrelated to land management and thus should be interpreted in pedogenic-specific contexts. Dynamic Soil Properties for Soil Health (DSP4SH) is a nationwide effort organized by United States Department of Agriculture - Natural Resources Conservation Service to evaluate the inclusion of soil health metrics in soil survey mapping products. Twelve chemical, biological, and physical soil health indicators were measured with consistent methodologies across a wide range of soil types, bioregions, and agricultural production systems. We found significant variability in soil health indicators corresponding with soil taxonomic suborder, supporting the importance of context-specific soil health benchmarks. Relative values of all soil health indicators examined differed significantly between perennial reference ecosystems and agricultural systems, and about half of the indicators examined (soil organic carbon, autoclaved-citrate extractable [ACE] protein, permanganate-oxidizable carbon, ß-glucosidase activity, and arylsulfatase activity), were also significantly higher in soil health management agricultural systems compared to conventional agricultural systems. Aggregate stability, soil respiration, and enzyme activities exhibited the most variability across DSP4SH projects. We found that ACE protein was highly sensitive to management and strongly correlated with soil organic carbon and warrants further investigation as a soil health indicator. Surprisingly, arylsulfatase activity exhibited the largest overall effect size, as well as greater observed management sensitivity in warm, dry conditions. However, additional research into method reproducibility and interpretation is needed for either metric to be suitable for soil survey adoption.