Abstract
Farmers in the USA have rapidly expanded the use of cover crops, with the national cover crop area nearly doubling since 2012. Despite many benefits that motivate public subsidies, questions remain about potential downsides. Here, using satellite observations from over 100,000 fields, half of which recently adopted cover crops, we demonstrate both positive and negative impacts of cover cropping, including: (1) declines in average yields for corn and soybean, by ~3% and ~2%, respectively; (2) delays in planting of corn (4 days) and soybean (2.5 days); and (3) reduced damages in the wet spring of 2019, with cover crop fields only half as likely to experience prevented planting as non-cover-crop fields. Cover cropping appears to reduce important aspects of farmer risk in wet conditions but increase them in dry conditions. Timely planting of the cash crop deserves emphasis moving forward, as we show eliminating planting delays would reduce yield penalties by roughly 50% for corn and 90% for soybean.
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Data availability
The data used in this study are available via Zenodo at https://doi.org/10.5281/zenodo.15492771 (ref. 38).
Code availability
The scripts used for all data analysis and figure generation in this study are available via Zenodo at https://doi.org/10.5281/zenodo.15492771 (ref. 38).
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Acknowledgements
Funding was provided by NASA Acres (NASA Applied Sciences grant no. 80NSSC23M0034, subaward 124245-Z6512205 to D.B.L.) and the Keck Foundation (to D.B.L.).
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D.B.L., J.S. and K.G. designed the research; Q.Z. and Y.M. contributed new data; S.D.T., Q.Z. and D.B.L. analysed the data; Q.Z. and K.G. developed cover crop data and conducted field validation; and D.B.L. wrote the initial manuscript. All authors contributed to final manuscript.
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Nature Sustainability thanks Timothy Bowles, Sami Khanal and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Extended data
Extended Data Fig. 1 Illustration of the difference-in-difference (DID) estimation of treatment effects for yield and planting date outcomes for each crop.
Dashed lines indicate the expected change in outcomes for the treatment group between the pre-treatment period (2000-2009) and post-treatment period (2016-2022) under a parallel trends assumption. The value of d represents the inferred effect of cover crop on each outcome, before adjusting for measurement error in cover crop estimates.
Extended Data Fig. 2 Distribution of covariates for 2000-2022 on treatment and control fields.
Boxplots show median as horizontal thick line, 25%-75% as colored box, and range as vertical lines (with outliers shown as separate points). Distributions are shown for corn samples, but distributions were very similar for soybean samples.
Extended Data Fig. 3 Trends in yields and planting dates for treatment and control fields during the pre-treatment period (2000–2009), shown separately for corn and soybean.
Panels a and b show yield (a) and planting date (b) trends for corn; panels c and d show yield (c) and planting date (d) trends for soybean.
Extended Data Fig. 4 Log yield vs planting date for corn (a) and soy (b) for each year, along with best-fit linear regression.
Values are centered to remove county effects, since the models included a fixed effect for county.
Extended Data Fig. 5 Fallow areas are a reliable measure of prevented planting in 2019.
Left panel shows reported area of prevented planted according to USDA Farm Service Agency (FSA) for corn and soy for the six states over time, illustrating the large increase in 2019 compared to other years in the study period. Right panel shows agreement between county-level prevented planted area in FSA and total area in the Cropland Data Layer Fallow/Idle Cropland class area, aggregated to the county scale in 2019.
Extended Data Fig. 6 Yield and planting date effects do not clearly diminish with longer adoption periods.
Panels show estimates of yield (left) and planting date (right) impacts when subsetting fields from the original treatment sample (3+ years of cover crop adoption) to more restrictive samples that consider fields with longer adoption histories. Data are presented as point estimates (means) ± 95% confidence intervals, based on standard errors clustered at the state level. The number of cover-cropped fields in each group is shown below each point in the figure, separately for corn and soybean.
Extended Data Fig. 7 Location of Control and Treatment samples.
Points show the samples for the corn analysis, with 55,921 control and 57,410 treatment locations. The corresponding numbers for soybean are 56,039 control and 58,000 treatment.
Extended Data Fig. 8 Results of difference-in-differences (DID) analysis when using absolute yield (t/ha) rather than log-transformed yield.
Results shown in Fig. 3 of the main paper are based on a model using log yield. Here, corn and soy results are shown separately due to differences in absolute yield scales (average yields in our sample are 10.9 t/ha for corn and 3.3 t/ha for soy). Values are shown for the pooled sample (a), individual years (b), and individual states (c). Data are presented as point estimates (means) ± 95% confidence intervals, based on standard errors clustered at the state level.
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Lobell, D.B., Di Tommaso, S., Zhou, Q. et al. The mixed effects of recent cover crop adoption on US cropland productivity. Nat Sustain 8, 1004–1012 (2025). https://doi.org/10.1038/s41893-025-01599-5
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DOI: https://doi.org/10.1038/s41893-025-01599-5
