Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Emerging weed resistance increases tillage intensity and greenhouse gas emissions in the US corn–soybean cropping system

Abstract

Tillage is a common agricultural practice that helps prepare the soil and remove weeds. However, it remains unknown how tillage intensity has evolved and its effect on net greenhouse gas (GHG) emissions. Here, using a process-based modelling approach with a multi-source database, we examined the change in tillage intensity across the US corn–soybean cropping systems during 1998–2016 and the impact of tillage intensity on soil GHG emissions. We found that tillage intensity first decreased and then, after 2008, increased, a trend that is strongly correlated with the adoption of herbicide-tolerant crops and emerging weed resistance. The GHG mitigation benefit (−5.5 ± 4.8 TgCO2e yr−1) of decreasing tillage intensity before 2008 has been more than offset by increased GHG emissions (13.8 ± 5.6 TgCO2e yr−1) due to tillage reintensification under growing pressure of weed resistance. As weed resistance persists or grows, tillage intensity is anticipated to continue rising, probably increasing GHG emissions. Our results imply that farmers’ choices in managing herbicide resistance may help mitigate agricultural GHG emissions, underscoring the importance of an alternative strategy to control weeds.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Conceptual depiction of the hypothetical GHG fluxes in response to tillage intensity changes affected by HT crop adoption and emergence of herbicide-resistant weeds.
Fig. 2: Annual changes of crop acreage under each tillage practice since 1998 and possible factors regulating the tillage intensity shift.
Fig. 3: Model-estimated impacts of tillage practices on GHG emissions in the US corn–soybean cropping system during 1998–2016.
Fig. 4: Tillage intensity change-induced soil GHG emissions.
Fig. 5: Spatial patterns of the model estimated GHG fluxes due to the historical use of tillage across the US corn–soybean cropping system.
Fig. 6: Accumulated GHG fluxes (gCO2e m2) due to tillage intensity changes across the US corn–soybean cropping system.

Similar content being viewed by others

Data availability

The tillage maps used in this study were developed from a proprietary national survey conducted annually by Kynetec Group. The purchase agreement requires that the data remain confidential. Source data supporting the figures are provided with this paper. Source data are provided with this paper.

Code availability

The code used to perform analyses in this study is generated in ENVI/IDL and is available upon request.

References

  1. IPCC Climate Change 2014: Synthesis Report (eds Core Writing Team, Pachauri, R. K. & Meyer L. A.) (IPCC, 2014).

  2. US Inventory of US Greenhouse Gas Emissions and Sinks: 1990–2018 (EPA, 2020).

  3. Lu, C. et al. Century‐long changes and drivers of soil nitrous oxide (N2O) emissions across the contiguous United States. Glob. Chang. Biol. https://doi.org/10.1111/gcb.16061 (2022).

    Article  PubMed  Google Scholar 

  4. Tian, H. et al. A comprehensive quantification of global nitrous oxide sources and sinks. Nature 586, 248–256 (2020).

    Article  CAS  ADS  PubMed  Google Scholar 

  5. 2004 National Crop Residue Management Survey (Conservation Technology Information Center, 2004); www.ctic.purdue.edu

  6. Claassen, R., Bowman, M., Wallander, J., David, M. & Steven, S. Tillage Intensity and Conservation Cropping in the United States, EIB-197 (United States Department of Agriculture, Economic Research Service, 2018).

  7. Grant, R. F. Changes in soil organic matter under different tillage and rotation: mathematical modeling in ecosystems. Soil Sci. Soc. Am. J. 61, 1159–1175 (1997).

    Article  CAS  ADS  Google Scholar 

  8. Claassen, R., Langpap, C. & Wu, J. Impacts of federal crop insurance on land use and environmental quality. Am. J. Agric. Econ. 99, 592–613 (2017).

    Article  Google Scholar 

  9. Davis, A. S. Cover-crop roller–crimper contributes to weed management in no-till soybean. Weed Sci. 58, 300–309 (2010).

    Article  CAS  Google Scholar 

  10. Pittelkow, C. M. et al. Nitrogen management and methane emissions in direct-seeded rice systems. Agron. J. 106, 968–980 (2014).

    Article  CAS  Google Scholar 

  11. Weber, J. F., Kunz, C., Peteinatos, G. G., Zikeli, S. & Gerhards, R. Weed control using conventional tillage, reduced tillage, no-tillage, and cover crops in organic soybean. Agric 7, 43 (2017).

    Google Scholar 

  12. Triplett, G. B. & Dick, W. A. No-tillage crop production: a revolution in agriculture!. Agron. J. 100, 153–165 (2008).

    Article  Google Scholar 

  13. Wade, T., Claassen, R. & Wallander, S. Conservation-Practice Adoption Rates Vary Widely by Crop and Region, EIB-147, 40 (United States Department of Agriculture, Economic Research Service, 2015).

  14. Perry, E. D., Ciliberto, F., Hennessy, D. A. & Moschini, G. Genetically engineered crops and pesticide use in US maize and soybeans. Sci. Adv. https://doi.org/10.1126/sciadv.1600850 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Heap, I. & Duke, S. O. Overview of glyphosate-resistant weeds worldwide. Pest Manag. Science 74, 1040–1049 (2018).

    Article  CAS  Google Scholar 

  16. Owen, M. D. K. Diverse approaches to herbicide-resistant weed management. Weed Sci. 64, 570–584 (2016).

    Article  Google Scholar 

  17. Van Deynze, B., Swinton, S. M. & Hennessy, D. A. Are glyphosate-resistant weeds a threat to conservation agriculture? Evidence from tillage practices in soybeans. Am. J. Agric. Econ. https://doi.org/10.1111/ajae.12243 (2021).

  18. Eagle, A. et al. Greenhouse Gas Mitigation Potential of Agricultural Land Management in the United States. A Synthesis of the Literature (Technical Working Group on Agricultural Greenhouse Gases, 2010).

  19. Parton, W. J. et al. Measuring and mitigating agricultural greenhouse gas production in the US Great Plains, 1870–2000. Proc. Natl. Acad. Sci. USA 112, E4681–E4688 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Stevanović, M. et al. Mitigation strategies for greenhouse gas emissions from agriculture and land-use change: consequences for food prices. Environ. Sci. Technol. 51, 365–374 (2017).

    Article  ADS  PubMed  Google Scholar 

  21. Glenk, K., Eory, V., Colombo, S. & Barnes, A. Adoption of greenhouse gas mitigation in agriculture: an analysis of dairy farmers’ perceptions and adoption behaviour. Ecol. Econ. 108, 49–58 (2014).

    Article  Google Scholar 

  22. Galik, C., Murray, B. & Parish, M. Near-term pathways for achieving forest and agricultural greenhouse gas mitigation in the US Climate 5, 69 (2017).

    Article  Google Scholar 

  23. Pape, D. et al. Managing Agricultural Land for Greenhouse Gas Mitigation within the United States (ICF/USDA, 2016); https://www.usda.gov/sites/default/files/documents/White_Paper_WEB71816.pdf

  24. Cooper, H. V., Sjögersten, S., Lark, R. M. & Mooney, S. J. To till or not to till in a temperate ecosystem? Implications for climate change mitigation. Environ. Res. Lett. 16, 054022 (2021).

    Article  CAS  ADS  Google Scholar 

  25. Baker, N. T. Tillage Practices in the Conterminous United States, 1989–2004—Datasets Aggregated by Watershed (No. 573), U.S. Geological Survey, 2011; https://pubs.usgs.gov/ds/ds573/pdf/dataseries573final.pdf

  26. Price, A. et al. Glyphosate-resistant Palmer amaranth: a threat to conservation agriculture. J. Soil Water Conserv. 66, 265–275 (2011).

    Article  Google Scholar 

  27. Livingston, M., Fernandez-Cornejo, J. & Frisvold, G. B. Economic returns to herbicide resistance management in the short and long run: the role of neighbor effects. Weed Sci. 64, 595–608 (2016).

    Article  Google Scholar 

  28. Cao, P., Lu, C. & Yu, Z. Historical nitrogen fertilizer use in agricultural ecosystems of the contiguous United States during 1850–2015: application rate, timing, and fertilizer types. Earth Syst. Sci. Data 10, 969–984 (2018).

    Article  ADS  Google Scholar 

  29. US Greenhouse Gas Emissions and Sinks, 1990–2016, Epa 430-R-18-003 (EPA, 2018).

  30. Deng, Q. et al. Assessing the impacts of tillage and fertilization management on nitrous oxide emissions in a cornfield using the DNDC model. J. Geophys. Res. Biogeosciences https://doi.org/10.1002/2015JG003239 (2016).

  31. Paustian, K. et al. Climate-smart soils. Nature 532, 49–57 (2016).

    Article  CAS  ADS  PubMed  Google Scholar 

  32. Yu, Z., Lu, C., Cao, P. & Tian, H. Long-term terrestrial carbon dynamics in the Midwestern United States during 1850–2015: roles of land use and cover change and agricultural management. Glob. Chang. Biol. 12, 3218–3221 (2018).

    Google Scholar 

  33. Lu, C. et al. Increasing carbon footprint of grain crop production in the US western Corn Belt. Environ. Res. Lett. 13, 124007 (2018).

    Article  CAS  ADS  Google Scholar 

  34. Wimberly, M. C. et al. Cropland expansion and grassland loss in the eastern Dakotas: new insights from a farm-level survey. Land Use Policy 63, 160–173 (2017).

    Article  Google Scholar 

  35. Adler, P. R., Del Grosso, S. J. & Parton, W. J. Life-cycle assessment of net greenhouse-gas flux for bioenergy cropping systems. Ecol. Appl. 17, 675–691 (2007).

    Article  PubMed  Google Scholar 

  36. Halvorson, A. D., Schweissing, F. C., Bartolo, M. E. & Reule, C. A. Corn response to nitrogen fertilization in a soil with high residual nitrogen. Agron. J. 97, 1222–1229 (2005).

    Article  Google Scholar 

  37. Al-Kaisi, M. M., Archontoulis, S. V., Kwaw-Mensah, D. & Miguez, F. Tillage and crop rotation effects on corn agronomic response and economic return at seven Iowa locations. Agron. J. 107, 1411–1424 (2015).

    Article  Google Scholar 

  38. Jarecki, M. et al. Long-term trends in corn yields and soil carbon under diversified crop rotations. J. Environ. Qual. 47, 635–643 (2018).

    Article  CAS  PubMed  Google Scholar 

  39. Gelfand, I. et al. Carbon debt of Conservation Reserve Program (CRP) grasslands converted to bioenergy production. Proc. Natl Acad. Sci. USA 108, 13864–13869 (2011).

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  40. West, T. O. & Post, W. M. Soil organic carbon sequestration rates by tillage and crop rotation. Soil Sci. Soc. Am. J. 66, 1930–1946 (2002).

    Article  CAS  ADS  Google Scholar 

  41. Ogle, S. M. et al. Scale and uncertainty in modeled soil organic carbon stock changes for US croplands using a process-based model. Glob. Chang. Biol. 16, 810–822 (2010).

    Article  ADS  Google Scholar 

  42. Al-Kaisi, M. M., Yin, X. & Licht, M. A. Soil carbon and nitrogen changes as influenced by tillage and cropping systems in some Iowa soils. Agric. Ecosyst. Environ. 105, 635–647 (2005).

    Article  CAS  Google Scholar 

  43. Perry, E. D., Moschini, G. C. & Hennessy, D. A. Testing for complementarity: glyphosate tolerant soybeans and conservation tillage. Am. J. Agric. Econ. https://doi.org/10.1093/ajae/aaw001 (2016).

  44. Perry, E. D., Hennessy, D. A. & Moschini, G. C. Product concentration and usage: behavioral effects in the glyphosate market. J. Econ. Behav. Organ. 158, 543–559 (2019).

    Article  Google Scholar 

  45. Yu, Z. & Lu, C. Historical cropland expansion and abandonment in the continental US during 1850 to 2016. Glob. Ecol. Biogeogr. 27, 322–333 (2018).

    Article  Google Scholar 

  46. Yu, Z., Lu, C., Tian, H. & Canadell, J. G. Largely underestimated carbon emission from land use and land cover change in the conterminous US. Glob. Chang. Biol. https://doi.org/10.1111/gcb.14768 (2019).

  47. Yu, Z., Lu, C., Hennessy, D. A., Feng, H. & Tian, H. Impacts of tillage practices on soil carbon stocks in the US corn–soybean cropping system during 1998 to 2016. Environ. Res. Lett. 15, 014008 (2020).

    Article  CAS  ADS  Google Scholar 

  48. Liu, M. et al. Long-term trends in evapotranspiration and runoff over the drainage basins of the Gulf of Mexico during 1901–2008. Water Resour. Res. 49, 1988–2012 (2013).

    Article  ADS  Google Scholar 

  49. Lu, C. & Tian, H. Net greenhouse gas balance in response to nitrogen enrichment: perspectives from a coupled biogeochemical model. Glob. Chang. Biol. 19, 571–588 (2013).

    Article  ADS  PubMed  Google Scholar 

  50. Tian, H. et al. The terrestrial biosphere as a net source of greenhouse gases to the atmosphere. Nature 531, 225–228 (2016).

    Article  CAS  ADS  PubMed  Google Scholar 

  51. Chen, G. et al. Drought in the southern United States over the 20th century: variability and its impacts on terrestrial ecosystem productivity and carbon storage. Clim. Change 114, 379–397 (2012).

    Article  CAS  ADS  Google Scholar 

  52. Lu, C. et al. Effect of nitrogen deposition on China’s terrestrial carbon uptake in the context of multifactor environmental changes. Ecol. Appl. 22, 53–75 (2012).

    Article  PubMed  Google Scholar 

  53. Ren, W. et al. Spatial and temporal patterns of CO2 and CH4 fluxes in China’s croplands in response to multifactor environmental changes. Tellus 63, 222–240 (2011).

    Article  CAS  Google Scholar 

  54. Tian, H. et al. Net exchanges of CO2, CH4, and N2O between China’s terrestrial ecosystems and the atmosphere and their contributions to global climate warming. J. Geophys. Res. Biogeosci. 116, 1–13 (2011).

    Google Scholar 

  55. Ren, W., Tian, H., Tao, B., Huang, Y. & Pan, S. China’s crop productivity and soil carbon storage as influenced by multifactor global change. Glob. Chang. Biol. 18, 2945–2957 (2012).

    Article  ADS  PubMed  Google Scholar 

  56. Residue Management Choices: A Guide to Managing Crop Residues in Corn and Soybeans (USDA Natural Resources Conservation Service and University of Wisconsin, 2019).

Download references

Acknowledgements

This work is supported by NSF grants (1903722, 1945036), the new faculty start-up fund of Iowa State University, and Michigan State University’s Elton R. Smith Endowment for the promotion of academic programmes in food and agricultural policy. This work was initiated while D.A.H. and H.F. were employed at Michigan State University. D.H. was supported by NSF grants (1919897, 2000058). We acknowledge the editor and four reviewers for providing constructive comments and suggestions to improve this manuscript.

Author information

Authors and Affiliations

Authors

Contributions

C.L., D.A.H. and H.F. conceived and designed the research. C.L. and Z.Y. developed tillage data sets, carried out model simulations, analysed the model results and wrote the manuscript. D.A.H. synthesized and interpreted the farmers’ survey data and contributed to the tillage data development. H.F., H.T. and D.H. helped with model validation, result interpretation and discussion. All co-authors reviewed and contributed to the manuscript.

Corresponding author

Correspondence to Chaoqun Lu.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Food thanks Moakes Simon, Magdalena Necpalova, Zhangcai Qin and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–9, Table 1, information on model representation, input data and simulation experiment design.

Reporting Summary

Source data

Source Data Fig. 2

Time-series data of crop acreage under tillage practices, HT crop adoption percentage and species number of weeds resistant to herbicide.

Source Data Fig. 3

Model-estimated impacts of historical tillage practices on GHG fluxes in the US corn–soybean cropping system during 1998–2016.

Source Data Fig. 4

Model-estimated impacts of tillage intensity change on annual and accumulated GHG fluxes during 1998–2016.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lu, C., Yu, Z., Hennessy, D.A. et al. Emerging weed resistance increases tillage intensity and greenhouse gas emissions in the US corn–soybean cropping system. Nat Food 3, 266–274 (2022). https://doi.org/10.1038/s43016-022-00488-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s43016-022-00488-w

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing