Long-term research avoids spurious and misleading trends in sustainability attributes of no-till
- PMID: 32175629
- DOI: 10.1111/gcb.15080
Long-term research avoids spurious and misleading trends in sustainability attributes of no-till
Abstract
Agricultural management recommendations based on short-term studies can produce findings inconsistent with long-term reality. Here, we test the long-term environmental sustainability and profitability of continuous no-till agriculture on yield, soil water availability, and N2 O fluxes. Using a moving window approach, we investigate the development and stability of several attributes of continuous no-till as compared to conventional till agriculture over a 29-year period at a site in the upper Midwest, US. Over a decade is needed to detect the consistent effects of no-till. Both crop yield and soil water availability required 15 years or longer to generate patterns consistent with 29-year trends. Only marginal trends for N2 O fluxes appeared in this period. Relative profitability analysis suggests that after initial implementation, 86% of periods between 10 and 29 years recuperated the initial expense of no-till implementation, with the probability of higher relative profit increasing with longevity. Importantly, statistically significant but misleading short-term trends appeared in more than 20% of the periods examined. Results underscore the importance of decadal and longer studies for revealing consistent dynamics and emergent outcomes of no-till agriculture, shown to be beneficial in the long term.
Keywords: LTER; N2O fluxes; long-term research; moving window; power analysis; profitability of no-till adoption; soil moisture; soil water availability; sustainable intensification; yield.
© 2020 John Wiley & Sons Ltd.
References
REFERENCES
-
- Al-Kaisi, M. M., Archontoulis, S. V., Kwaw-Mensah, D., & Miguez, F. (2015). Tillage and crop rotation effects on corn agronomic response and economic return at seven Iowa locations. Agronomy Journal, 107, 1411-1424. https://doi.org/10.2134/agronj14.0470
-
- Bahlai, C. (2019). GitHub, bad_breakup. Retrieved from https://github.com/cbahlai/bad_breakup
-
- Baker, C. J., Saxton, K. E., & Ritchie, W. R. (1996). No-tillage seeding: Science and practice. Cambridge, UK: Cambridge University Press.
-
- Basso, B., & Ritchie, J. T. (2015). Simulating crop growth and biogeochemical fluxes in response to land management using the SALUS model. In S. K. Hamilton & G. P. Robertson (Eds.), The ecology of agricultural landscapes: Long-term research on the path to sustainability (pp. 252-274). New York, NY: Oxford University Press.
-
- Bates, D., Maechler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67, 1-48. https://doi.org/10.18637/jss.v067.i01
MeSH terms
Substances
Grants and funding
LinkOut - more resources
Full Text Sources