Abstract

AbstractSoil respiration is one of the main soil health indicators and is influenced by several factors in agricultural fields. Identifying key factors that control soil respiration is desirable for informed soil management decisions and for promoting and scaling up soil health. This study aimed to (i) quantify the relationships between potential soil respiration and selected soil properties, crops, and slope positions, and (ii) identify key factors controlling these relationships using a neural network model. Ninety soil samples from 0‐ to 5‐ and 5‐ to 20‐cm soil depth were collected from footslope, backslope, and summit in three fields planted with soybean (Glycine max L. Merr.), alfalfa (Medicago sativa L.), and corn (Zea mays L.). The model provided great accuracy (coefficient of determination: 0.96; root‐mean square error: 7.8; and mean absolute deviation: 3.8) and explained nearly 96% of variations in soil respiration across soil depth, crop, and slope positions. Soil depth, ammoniacal nitrogen (NH4‐N), crop types, slope position, and silt content were identified as the top five factors influencing potential soil respiration at the field level. Potential soil respiration was more sensitive to potassium, phosphorus, pH, cation exchange capacity, and mean weight diameter and less sensitive to NH4‐N, nitrate nitrogen, soil organic matter, and clay content. It increased with pH, electrical conductivity, mean weight diameter, potential nitrogen mineralization, and potassium, and it decreased with increasing silt content. Soil from 0 to 5 cm under soybean or at the summit slope position exhibited a higher respiration. Using a small dataset, this pilot study accurately predicted potential soil respiration in agricultural fields and identified key drivers controlling it. The results from this study highlight the complexity of using potential soil respiration as a standalone test for evaluating soil health. This does not diminish the usefulness of potential soil respiration as a soil health indicator to support agricultural management decisions and as a reference in future soil health studies. However, it emphasizes the importance of considering multiple factors when interpreting the significance of soil biological indicators for soil health assessments.

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