Core Ideas: Summary statistics were developed from a robust multiregional soil health (SH) dataset. Active carbon, organic matter, and penetration resistance were most useful soil health indicators. Midwestern soils had relatively lower mean values for measured biological properties than Northeast or Mid‐Atlantic soils. Soil health (SH) refers to the ability of a soil to function and provide ecosystem services. The Comprehensive Assessment of Soil Health (CASH) is an approach that measures 15 physical, biological, and chemical soil indicators, which are interpreted through scoring functions. This study reports on the SH status of 5767 samples from the Mid‐Atlantic, Midwest, and Northeast regions of the USA as evaluated using CASH. Descriptive statistics and ANOVAs of subdatasets by region and soil textural group for SH indicators, in addition to correlation coefficients, principal component (PC) analysis, and best subsets regression (BSR) were performed. From these analyses, new CASH scoring functions were developed. Separate scoring functions by textural group (fine, medium, coarse) were necessary for Wet Aggregate Stability (WAS), Available Water Capacity (AWS), Organic Matter (OM), Active Carbon (AC), and Protein. Differences existed among regions, especially for WAS, OM, Protein, and Respiration (Resp), where the Midwest had relatively lower mean values compared to the Mid‐Atlantic and Northeast. Biological properties and WAS showed moderately strong correlations ( r = 0.58–0.78) and the highest loadings for the first two PCs. BSR results using the overall soil quality index as the response variable indicated that AC accounts for 45% of the variation, with additional predictability from Penetration Resistance, Resp, and WAS (68%). These four indicators are suggested for simplified SH tests. We conclude that the CASH approach can be successfully applied to evaluate the health status of soils with differing pedogenetic histories.

The concept of soil health has evolved over the past several decades, recognizing that dynamic soil property response to management and land use is highly dependent on site‐specific factors that must be considered when interpreting soil health measurements. Initially, the Soil Management Assessment Framework (SMAF) and Comprehensive Assessment of Soil Health (CASH) were developed and used globally for scoring soil health indicators. However, both SMAF and CASH frameworks were developed using a relatively small dataset and their interpretation curves were not validated at the nationwide scale. Expanding upon these concepts, we propose the Soil Health Assessment Protocol and Evaluation (SHAPE) tool. The SHAPE was developed using 14,680 soil organic C (SOC) observations from across the United States, and accounts for edaphic and climate factors at the continental scale. Data were compiled from the literature, the Cornell Soil Health Laboratory, and the Kellogg Soil Survey Laboratory. In this approach, scoring curves are Bayesian model‐based estimates of the conditional cumulative distribution function (CDF) for defined soil peer groups reflecting five soil texture and five soil suborder classes adjusted for mean annual temperature and precipitation. Specifically, SHAPE produces scores between 0 and 1 (0–100%) for measured SOC values that reflect the quantile or position within the conditional CDF along with measures of uncertainty. Herein, we focus on development of the SHAPE scoring curve for SOC with our case studies. SHAPE is a flexible, quantitative tool that provides a regionally relevant interpretation of this key soil health indicator.

Core Ideas: Soil health metrics were sensitive in North Carolina soils. Tillage intensity and fertility practices were especially differentiated by biological soil health metrics. Soil health metrics associated with labile organic matter correlated well with crop yields. Soil health (SH) refers to the ability of a soil to function and provide ecosystem services. This study reanalyzes data from long‐term agronomic management experiments in North Carolina and addresses previous conclusions regarding the utility of SH test metrics. Data for 15 SH indicators in the Comprehensive Assessment of Soil Health (CASH) framework from three long‐term trials in North Carolina were analyzed to assess effects of tillage intensity and organic vs. conventional management. This included four soil biological indicators—organic matter (OM), active carbon (ActC), respiration (Resp), and protein (Prot); four soil physical indicators—available water capacity (AWC), water‐stable aggregation (Agstab), surface and subsurface penetration resistance (SurfHard, SubHard); and seven soil chemical (fertility) indicators (P, K, Mg, Fe, Mn, Zn, pH). Corn ( Zea mays L.) and soybean ( Glycine max L. Merr.) yield data and SH indicator values were correlated using site‐specific and multi‐site datasets. Long‐term management practices most commonly showed significant impacts with AgStab (up to 2.2′), ActC (2.1′), Prot (2.3′), and most chemical indicators. Tillage intensity had a greater impact than organic vs. conventional management and linear regression of multi‐year mean corn and soybean yield response to tillage showed significant correlations with eight SH indicators, highest among them ActC, Protein, Resp, and Mn ( R ² = 0.85–0.93). Contrary to previous conclusions, CASH indicators, especially those related to labile C and N, responded well to management practices and showed utility for SH assessment in agronomic trials.