strengths and weaknesses. The Visual Evaluation of Soil Structure (VESS) (Ball et al., 2017) and rangeland health assessment protocols (Pellant et al., 2020) represent approaches for cropland and rangeland, respectively.
The VESS was designed for arable production systems (Ball et al., 2017) based on the Peerlkamp Spade Test (Peerlkamp, 1959). It classifies top‐ and sub‐soil attributes into five scoring categories based on the size, shape, and visible porosity of soil aggregates, rooting characteristics, and presence/absence of macropores. VESS requires only a shovel and scoring guidelines (Scotland’s Rural College, 2019), so evaluators can quickly assess soil structure and assign a score between 1 (best) and 5 (worst). The tactile “hands‐on” nature of VESS enables it to work best when the soil is in a friable condition (neither too wet nor too dry). A limitation of VESS is that it does not work well in very sandy soils because of low structural cohesion (Franco et al., 2019).
The VESS has been used globally across a broad range of soil types and production systems to discern management impacts on soil health (Munkholm and Holden, 2015). The scores have also been correlated to various soil physical properties, soil‐atmosphere gas fluxes, and crop yield (Ball et al., 2017), thus confirming its value for soil health assessment.
Rangeland health assessments using three interrelated ecosystem attributes of soil/site stability, hydrological function, and biotic integrity (Pellant et al., 2020) have been shown to help characterize the status and trends of critical soil functions and effectively guide changes in management (Brown and Herrick, 2016). Using a combination of qualitative and quantitative indicators, Pellant et al. (2020) developed criteria for monitoring rangeland health using 17 indicators that include soil‐related evaluations of bare ground, gullies, resistance to erosion/degradation, and compaction. Rangeland health assessments using these criteria have been adopted by public agencies and private landowners throughout the world and have served to improve the systematic understanding of soil quality in rangeland ecosystems (Brown and Herrick, 2016). Effective use of rangeland health assessments, however, requires the evaluator to recognize and correctly identify site characteristics including landscape and temporal variability since evaluations are made relative to an ecological site or its equivalent.
Soil Health Test Kits
Soil test kits can provide land managers with expedient information on the status of soil physical, chemical, and biological properties. While many test kits focus on measurements of soil solution chemistry for horticultural applications, some test kits include a broad suite of measurements with linkages to soil functions relevant to maintaining productivity, regulating/partitioning water flow, and storing/cycling nutrients. The Soil Quality Test Kit (SQTK), developed by Dr. John Doran (USDA‐ARS, retired), includes equipment and supplies for the measurement of select soil properties recognized as components of a minimum data set for monitoring soil health (NRCS, 2001). In the intervening 25 years since its development, the SQTK has been used by NRCS resource soil scientists throughout the USA as a screening tool to guide more in‐depth soil health assessments. The SQTK also prompted the development of additional field‐based assessments for use in rangeland (e.g., soil slake test; Seybold and Herrick, 2001). While test kits provide a means for receiving near immediate feedback about a soil’s status, some tests can be time consuming. Moreover, measurements of soil solution chemistry by test kits require calibration against known standards to ensure accurate results.
Sensor‐based Measurements
Field‐scale soil property mapping, generally used to improve nutrient use efficiencies, can also document the trajectory of some soil health indicators (Mulla and Schepers, 1997; Smith et al., 1993). However, conventional soil sampling and laboratory analyses can be expensive, time consuming, and thus limit its value for making timely adjustments to management. In response, several novel sensor‐based technologies have been developed (Vol. 1, Chapter 8), thus increasing the likelihood of making real‐time soil health assessments.
Electromagnetic, optical, mechanical, electrochemical, airflow, and acoustic sensors for automated field measurements have been adapted to quantify changes in soil physical and chemical properties across agricultural landscapes (Adamchuk et al., 2004). Most sensors are property‐specific, with electromagnetic, mechanical, electrochemical, and airflow types associated with measurements of electrical conductivity, soil resistance, nutrients or pH, and air permeability, respectively. Optical sensors are useful for predicting both chemical and physical properties (Thomasson et al., 2001). Sensor‐based measurements can also be used to quantify field‐scale distributions of inferred soil properties which can then be partitioned into distinct management zones. It is important to acknowledge, however, that sensor‐based measurements provide either high‐resolution spatial or temporal data, but usually not both. With further technological advancement, sensor‐based measurements may ultimately provide real‐time control of input applications.
Summary
Soil health assessments should provide useful insights into the status of soil properties as they affect critical soil functions. Currently there is no single best method for soil health assessment because outcomes are intrinsically related to evaluator decisions related to method, time, location, and frequency of sampling. Multiple research endeavors are underway focused on improving assessments by tailoring collection, analysis, and data interpretation to inherent site attributes, project resources, intended data uses, and evaluator expertise.
Acknowledgments
We thank Robyn Duttenhefner for her helpful edits to improve an earlier draft of the chapter.
The U.S. Department of Agriculture (USDA) prohibits discrimination in all its programs and activities on the basis of race, color, national origin, age, disability, and where applicable, sex, marital status, family status, parental status, religion, sexual orientation, genetic information, political beliefs, reprisal, or because all or part of an individual’s income is derived from any public assistance program. (Not all prohibited bases apply to all programs.). USDA is an equal opportunity provider and employer. Mention of commercial products and organizations in this manuscript is solely to provide specific information. It does not constitute endorsement by USDA‐ARS over other products and organizations not mentioned.
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