Satellites reveal a small positive yield effect from conservation tillage across the US Corn Belt

• Published in: Environmental research letters Vol. 14; no. 12; pp. 124038 - 124048
• Main Authors: Deines, Jillian M, Wang, Sherrie, Lobell, David B
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01-12-2019
• Subjects: Agricultural conservation; Agricultural practices; Agricultural production; Belts; causal forests; causal inference; conservation agriculture; Conservation practices; Conservation tillage; Corn; Corn belt; Crop production; Crop yield; crop yields; Economics; Environmental degradation; Landsat; Learning algorithms; Machine learning; Profitability; Satellites; Soil conservation; Soil degradation; Soybeans; Tillage; US Corn Belt; United States > US
• DOI: 10.1088/1748-9326/ab503b
• EISSN: 1748-9326

Conservation tillage is a primary tenet of conservation agriculture aimed at restoring and maintaining soil health for long-term crop productivity. Because soil degradation typically operates on century timescales, farmer adoption is influenced by near-term yield impacts and profitability. Although numerous localized field trials have examined the yield impacts of conservation tillage, their results are mixed and often unrepresentative of real-world conditions. Here, we applied a machine-learning causal inference approach to satellite-derived datasets of tillage practices and crop yields spanning the US Corn Belt from 2005 to 2017 to assess on-the-ground yield impacts at field-level resolution across thousands of fields. We found an average 3.3% and 0.74% yield increase for maize and soybeans, respectively, for fields with long-term conservation tillage. This effect was diminished in fields that only recently converted to conservation tillage. We also found significant variability in these effects, and we identified soil and weather characteristics that mediate the direction and magnitude of yield responses. This work supports soil conservation practices by demonstrating they can be used with minimal and typically positive yield impacts.