Quantifying cover crop effects on soil health and productivity

Jinshi Jian; Xuan Du; Ryan D Stewart

doi:10.1016/j.dib.2020.105376

Quantifying cover crop effects on soil health and productivity

Data Brief. 2020 Mar 5:29:105376. doi: 10.1016/j.dib.2020.105376. eCollection 2020 Apr.

Authors

Jinshi Jian^{1

2}, Xuan Du³, Ryan D Stewart¹

Affiliations

¹ School of Plant and Environmental Sciences, Virginia Tech, 330 Smyth Hall, 185 Ag Quad Lane, Blacksburg, VA 24061, USA.
² Joint Global Change Research Institute, Pacific Northwest National Laboratory, 5825 University Research Ct. #3500, College Park, MD, USA.
³ Department of Hydraulic Engineering, Yangling Vocational & Technical College, Yangling, Shaanxi, China.

Abstract

The dataset presented here supports the research paper entitled "A calculator to quantify cover crop effects on soil health and productivity". Soil health (sometimes used synonymously with soil quality) is a concept that describes soil as a living system to sustain plants, animals, and human. Soil physical, chemical, and biological properties, along with their interactions, are required to quantify soil health. The use of cover crops in agricultural rotations may enhance soil health, yet there has been little progress in understanding how external factors such as climate, soil type, and agronomic practices affect soil and cash crop responses. In response, this dataset compiles measurements from 281 studies and provides an analysis of field-measured changes in 38 soil health indicators due to cover crop usage. Environmental and background indicators were also compiled to assess how climatic and management practices affect soil and cash crop responses to cover crops, with specific categories including climate type (tropical, arid, temperate, and continental), soil texture (coarse, medium, and fine), cover crop type (legume, grass, multi-species mixture, and other), and cash crop type (corn, soybean, wheat, vegetable, corn-soybean rotation, corn-soybean-wheat rotation, and other). An unbalanced analysis of variation was used to determine the hierarchy of most to least important factors that affected responsiveness of each soil health indicator. Based on the hierarchy structure, a soil health calculator was then developed to quantify the response of 13 parameters - erosion, runoff, weed suppression, soil aggregate stability, leaching, infiltration, microbial biomass carbon, soil bulk density, soil organic carbon, soil nitrogen, microbial biomass nitrogen, cash crop yield, and saturated hydraulic conductivity - to cover crops. The presented data in the calculator report the mean change in parameter values based on all combinations of climate, soil texture, cover crop type, and cash crop type.

Keywords: Agriculture; Conservation management; Cover crop; Soil health; Soil quality.