Soil organic carbon (SOC) is closely tied to soil health. However, additional biological indicators may also provide insight about C dynamics and microbial activity. We used SOC and the other C indicators (potential C mineralization, permanganate oxidizable C, water extractable organic C, and beta-glucosidase enzyme activity) from the North American Project to Evaluate Soil Health Measurements to examine the continental-scale drivers of these indicators, the relationships among indicators, and the effects of soil health practices on indicator values. All indicators had greater values at cooler temperatures, and most were greater with increased precipitation and clay content. The indicators were strongly correlated with each other at the site-level, with the strongest relationship between SOC and permanganate oxidizable C. The indicator values responded positively to decreased tillage, inclusion of cover crops, application of organic nutrients, and retention of crop residue, but not the number of harvested crops in a rotation. The effect of decreased tillage on the C indicators was generally greater at sites with higher precipitation. The magnitude and direction of the response to soil health practices was consistent across indicators within a site but measuring at least two indicators would provide additional confi-dence of the effects of management, especially for tillage. All C indicators responded to management, an essential criterion for evaluating soil health. Balancing the cost, sensitivity, interpretability, and availability at commercial labs, a 24-hr potential C mineralization assay could deliver the most benefit to measure in conjunction with SOC.

Phospholipid fatty acid analysis (PLFA) provides an easy to use and robust measure of changing soil microbial condition. The method provides data on both the quantity and composition of the soil microbial community- critical knowledge because the community is an important component of soil health. However, it is challenging for new researchers to know how to process data, how to interpret the results, and to know its effectiveness in evaluating soil health management. We set out to address these challenges using the North American Project to Evaluate Soil Health Measurements PLFA dataset. The dataset is comprised of results of over 1800 agricultural soil samples from a range of environmental regions and management practices. Using this dataset, we identified that quantifying soil PLFA biomass through summing the biomarkers from C14:0 to C20:0 yielded greater biomass results than summing specific biomarkers and was almost identical to summing C9:0 to C20:0. We utilized microbial biomass with common and novel biomarker ratios to evaluate the response of the soil microbial community to changes in the environment or changes in management practice. These ratios were based on commonly used genotypic categorization (e.g., Gram-positive to Gram-negative) or based on chemical structure with chemical ratios of either universal characteristics (e.g., unsaturated to saturated) or targeted phenotypic biomarkers known to shift with changing growth conditions (e.g., a15:0 and a17:0 to i15:0 and i17:0). One novel phenotypic ratio, the adaptation response ratio (ARR), significantly correlated with mean annual temperature and soil pH across grassland reference plots, a wheat climate transect, an intensive vegetable agricultural dataset, and a wheat-corn dataset from Mexico. Neither the common genotypic ratio nor ratios based on chemical structure demonstrated clear and consistent trends with environmental conditions. Targeted phenotypic biomarker ratios and microbial biomass also detected significant differences with soil health management practices of decreased tillage, cover crops, organic nutrients, residue retention, and rotation diversity. Therefore, with standardized microbial biomass and biomarker calculations that significantly vary with environmental conditions and management practices, these results support a wider understanding and adoption of the PLFA method in soil health management.

Farmers, scientists, and other soil health stakeholders require interpretable indicators of soil hydraulic function. Determining which indicators to use has been difficult because of measurement disconformity, spatial and temporal variability, recently established treatments, and the effect of site characteristics on management practice differences. The North American Project to Evaluate Soil Health Measurements includes 124 sites uniformly sampled across a range of soil health management practices in North America in 2019. We compare and recommend indicators of hydraulic function that best characterize soil health. We assessed the relationship of each indicator to a suite of soil inherent properties and climate variables, the response of each indicator to soil health management practices, the effect that soil inherent properties (clay content, sand content, and pH) and climatic variables (10-yr mean annual precipitation and temperature) had on response to management practices, and the relationship among the responses of the indicators to soil health management practices. Field capacity measured on intact cores (theta(FC_INTACT)) was the best measure of soil hydraulic function, because it responded to management, represents a direct measure of soil hydraulic function, is proximal to stakeholder values, and its response to management was not significantly influenced by inherent and climatic variables. Other suitable indicators are bulk density, soil organic carbon (SOC), and aggregate stability, which are not direct measures of soil hydraulic function but do respond to management and may be practical in situations in which measuring theta(FC_INTACT) is not. This study informs selection of soil health indicators to measure soil hydraulic function.

Potential carbon mineralization (Cmin) is a commonly used indicator of soil health, with greater Cmin values interpreted as healthier soil. While Cmin values are typically greater in agricultural soils managed with minimal physical disturbance, the mechanisms driving the increases remain poorly understood. This study assessed bacterial and archaeal community structure and potential microbial drivers of Cmin in soils maintained under various degrees of physical disturbance. Potential carbon mineralization, 16S rRNA sequences, and soil characterization data were collected as part of the North American Project to Evaluate Soil Health Measurements (NAPESHM). Results showed that type of cropping system, intensity of physical disturbance, and soil pH influenced microbial sensitivity to physical disturbance. Furthermore, 28% of amplicon sequence variants (ASVs), which were important in modeling Cmin, were enriched under soils managed with minimal physical disturbance. Sequences identified as enriched under minimal disturbance and important for modeling Cmin, were linked to organisms which could produce extracellular polymeric substances and contained metabolic strategies suited for tolerating environmental stressors. Understanding how physical disturbance shapes microbial communities across climates and inherent soil properties and drives changes in Cmin provides the context necessary to evaluate management impacts on standardized measures of soil microbial activity.

Aggregate stability is a commonly used indicator of soil health because improvements in aggregate stability are related to reduced erodibility and improved soil-water dynamics. During the past 80 to 90 years, numerous methods have been developed to assess aggregate stability. Limited comparisons among the methods have resulted in varied magnitudes of response to soil health management practices and varied influences of inherent soil properties and climate. It is not clear whether selection of a specific method creates any advantage to the investigator. This study assessed four commonly used methods of measuring aggregate stability using data collected as part of the North American Project to Evaluate Soil Health Measurements. The methods included water stable aggregates using the Cornell Rainfall Simulator (WSACASH), wet sieved water stable aggregates (WSAARS), slaking captured and adapted from SLAKES smart-phone image recognition software (STAB10), and the mean weight diameter of water stable aggregates (MWD). Influence of climate and inherent soil prop-erties at the continental scale were analyzed in addition to method responses to rotation diversity, cash crop count, residue management, organic nutrient amendments, cover crops, and tillage. The four methods were moderately correlated with each other. All methods were sensitive to differences in climate and inherent soil properties between sites, although to different degrees. None measured significant effects from rotation diversity or crop count, but all methods detected significant increases in aggregate stability resulting from reduced tillage. Significant increases or positive trends were observed for all methods in relation to cover cropping, increased residue retention, and organic amendments, except for STAB10, which expressed a slightly negative response to organic amendments. Considering these results, no single method was clearly superior and all four are viable options for measuring aggregate stability. Therefore, secondary considerations (e.g., cost, method availability, increased sensitivity to a specific management practice, or minimal within-treatment variability) driven by the needs of the investigator, should determine the most suitable method.

The North American Project to Evaluate Soil Health Measurements was initiated with the objective to identify widely applicable soil health measurements for evaluation of agricultural management practices intended to improve soil health. More than 20 indicators were chosen for assessment across 120 long-term agricultural research sites spanning from north-central Canada to southern Mexico. The indicators being evaluated include common standard measures of soil, but also newer techniques of visible and near-infrared reflectance spectroscopy, a smart phone app, and metagenomics. The aim of using consistent sampling and analytical protocols across selected sites was to provide a database of soil health indicator results that can be used to better understand how land use and management has affected the condition of soil ecosystem provisioning for agricultural biomass production and water resources, as well as nutrient and C cycling. The objective of this paper is to provide documentation of the overall design, and methods being employed to identify soil health indicators sensitive across agricultural management practices, pedologies, and geographies.

Soil microbes drive biological functions that mediate chemical and physical processes necessary for plants to sustain growth. Laboratory soil respiration has been proposed as one universal soil health indicator representing these functions, potentially informing crop and soil management decisions. Research is needed to test the premise that soil respiration is helpful for profitable in‐season nitrogen (N) rate management decisions in corn ( Zea mays L.). The objective of this research was two‐fold: (i) determine if the amount of N applied at the time of planting effected soil respiration, and (ii) evaluate the relationship of soil respiration to corn yield response to fertilizer N application. A total of 49 N response trials were conducted across eight states over three growing seasons (2014–2016). The 4‐day Comprehensive Assessment of Soil Health (CASH) soil respiration method was used to quantify soil respiration. Averaged over all sites, N fertilization did not impact soil respiration, but at four sites soil respiration decreased as N fertilizer rate applied at‐planting increased. Across all site‐years, soil respiration was moderately related to the economical optimum N rate (EONR) (r 2 = 0.21). However, when analyzed by year, soil respiration was more strongly related to EONR in 2016 (r 2 = 0.50) and poorly related for the first two years (r 2 < 0.20). These results illustrate the factors influencing the ability of laboratory soil respiration to estimate corn N response, including growing‐season weather, and the potential of fusing soil respiration with other soil and weather measurements for improved N fertilizer recommendations.