Skip to main content

Thank you for visiting 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.

Scaling up co-produced climate-driven decision support tools for agriculture


There is growing belief that the co-production of knowledge between academics and non-academics is critical to address sustainability problems. Yet, little is known about what happens after co-production and whether and how co-produced knowledge scales up. This article focuses on climate-driven decision support tools co-produced by researchers, farmers and agricultural advisers in the US Midwest. Through two surveys (N = 5,393) with farmers and agricultural advisers, it examines how engagement and marketing campaigns to disseminate the tools influenced their use. Here we find that beyond the highly iterative co-production process, other forms of user interaction such as outreach engagement and marketing campaigns are critical to scale up the impact of co-produced knowledge. Positively, we also show that most surveyed farmers and advisers who were not involved in the engagement phase reported having their needs met by the co-produced tools and were using, considering using or willing to recommend the climate-driven decision support tools. Hence, while co-production alone does not guarantee dissemination, it does increase knowledge fit and use. Dissemination for mass use, however, might require a committed effort from researchers and funders to promote and evaluate use post co-production to better understand societal impact and the role of co-produced knowledge in addressing sustainability problems.

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

Access options

Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: The U2U project.

Data availability

The advisers and farmers survey data and associated questionnaires that support the findings of this study are available in Purdue University Research Repository with identifiers and (refs. 41,43).


  1. Norström, A. V. et al. Principles for knowledge co-production in sustainability research. Nat. Sustain. 3, 182–190 (2020).

    Article  Google Scholar 

  2. Mach, K. J. et al. Actionable knowledge and the art of engagement. Curr. Opin. Environ. Sustain. 42, 30–37 (2020).

    Article  Google Scholar 

  3. Bremer, S. & Meisch, S. Co-production in climate change research: reviewing different perspectives. Wiley Interdiscip. Rev. Clim. Change 8, e482 (2017).

    Article  Google Scholar 

  4. Lemos, M. C. et al. To co-produce or not to co-produce. Nat. Sustain. 1, 722–724 (2018).

    Article  Google Scholar 

  5. Kirchhoff, C. J., Lemos, M. C. & Dessai, S. Actionable knowledge for environmental decision making: broadening the usability of climate science. Annu. Rev. Environ. Resour. 38, 393–414 (2013).

    Article  Google Scholar 

  6. Popovici, R. et al. Coproduction challenges in the context of changing rural livelihoods. J. Contemp. Water Res. Educ. 171, 111–126 (2020).

    Article  Google Scholar 

  7. Prokopy, L. S. et al. Useful to usable: developing usable climate science for agriculture. Clim. Risk Manage. 15, 1–7 (2017).

    Article  Google Scholar 

  8. Meadow, A. M. et al. Moving toward the deliberate coproduction of climate science knowledge. Weather Clim. Soc. 7, 179–191 (2015).

    Article  Google Scholar 

  9. Beier, P., Hansen, L. J., Helbrecht, L. & Behar, D. A how-to guide for coproduction of actionable science. Conserv. Lett. 10, 288–296 (2017).

    Article  Google Scholar 

  10. Meehan, K., Klenk, N. L. & Mendez, F. The geopolitics of climate knowledge mobilization: transdisciplinary research at the science–policy interface(s) in the Americas. Sci. Technol. Human Values 43, 759–784 (2017).

    Article  Google Scholar 

  11. Vincent, K., Carter, S., Steynor, A., Visman, E. & Wågsæther, K. L. Addressing power imbalances in co-production. Nat. Clim. Change 10, 877–878 (2020).

    Article  Google Scholar 

  12. Wall, T. U., Meadow, A. M. & Horganic, A. Developing evaluation indicators to improve the process of coproducing usable climate science. Weather Clim. Soc. 9, 95–107 (2017).

    Article  Google Scholar 

  13. Vincent, K., Daly, M., Scannell, C. & Leathes, B. What can climate services learn from theory and practice of co-production? Clim. Serv. 12, 48–58 (2018).

    Article  Google Scholar 

  14. Bremer, S. et al. Toward a multi-faceted conception of co-production of climate services. Clim. Serv. 13, 42–50 (2019).

    Article  Google Scholar 

  15. Cash, D. W., Borck, J. C. & Patt, A. G. Countering the loading-dock approach to linking science and decision making: comparative analysis of El Niño/Southern Oscillation (ENSO) forecasting systems. Sci. Technol. Human Values 31, 465–494 (2006).

    Article  Google Scholar 

  16. Lemos, M. C., Kirchhoff, C. J. & Ramprasad, V. Narrowing the climate information usability gap. Nat. Clim. Change 2, 789–794 (2012).

    Article  Google Scholar 

  17. Jagannathan, K. et al. Great expectations? Reconciling the aspiration, outcome, and possibility of co-production. Curr. Opin. Environ. Sustain. 42, 22–29 (2020).

    Article  Google Scholar 

  18. Moss, R. H. et al. Evaluating knowledge to support climate action: a framework for sustained assessment. Report of an independent advisory committee on applied climate assessment. Weather Clim. Soc. 11, 465–487 (2019).

    Article  Google Scholar 

  19. Goodrich, K. A. et al. Who are boundary spanners and how can we support them in making knowledge more actionable in sustainability fields? Curr. Opin. Environ. Sustain. 42, 45–51 (2020).

    Article  Google Scholar 

  20. Vogel, J., McNie, E. & Behar, D. Co-producing actionable science for water utilities. Clim. Serv. 2–3, 30–40 (2016).

    Article  Google Scholar 

  21. U2U Final Project Report of Useful to Usable (U2U): Transforming Climate Variability and Change Information for Cereal Crop Producers (Purdue Univ., 2017).

  22. Lubell, M., Niles, M. & Hoffman, M. Extension 3.0: managing agricultural knowledge systems in the network age. Soc. Nat. Resour. 27, 1089–1103 (2014).

    Article  Google Scholar 

  23. Prokopy, L. S. et al. Agricultural advisors: a receptive audience for weather and climate information? Weather Clim. Soc. 5, 162–167 (2013).

    Article  Google Scholar 

  24. Haigh, T. et al. Agricultural advisors as climate information intermediaries: exploring differences in capacity to communicate climate. Weather Clim. Soc. 7, 83–93 (2015).

    Article  Google Scholar 

  25. Klink, J. et al. Enhancing interdisciplinary climate change work through comprehensive evaluation. Clim. Risk Manage. 15, 109–125 (2017).

    Article  Google Scholar 

  26. Prokopy, L. S. et al. Using a team survey to improve team communication for enhanced delivery of agro-climate decision support tools. Agric. Syst. 138, 31–37 (2015).

    Article  Google Scholar 

  27. Arbuckle, J. G. et al. Climate Change beliefs, concerns, and attitudes toward adaptation and mitigation among farmers in the Midwestern United States. Clim. Change 117, 943–950 (2013).

    Article  Google Scholar 

  28. Haigh, T. et al. Provision of climate services for agriculture: public and private pathways to farm decision-making. Bull. Am. Meteorol. Soc. 99, 1781–1790 (2018).

    Article  Google Scholar 

  29. Mase, A. S., Gramig, B. M. & Prokopy, L. S. Climate change beliefs, risk perceptions, and adaptation behavior among Midwestern U.S. crop farmers. Clim. Risk Manage. 15, 8–17 (2017).

    Article  Google Scholar 

  30. Mase, A. S., Cho, H. & Prokopy, L. S. Enhancing the Social Amplification of Risk Framework (SARF) by exploring trust, the availability heuristic, and agricultural advisors’ belief in climate change. J. Environ. Psychol. 41, 166–176 (2015).

    Article  Google Scholar 

  31. Rogers, E. M. Diffusion of Innovations 5th edn (Free Press, 2003).

  32. Haigh, T. et al. Mapping the decision points and climate information use of agricultural producers across the U.S. Corn Belt. Clim. Risk Manage. 7, 20–30 (2015).

    Article  Google Scholar 

  33. Prokopy, L. S. et al. Adoption of agricultural conservation practices in the United States: evidence from 35 years of quantitative literature. J. Soil Water Conserv. 74, 520–534 (2019).

    Article  Google Scholar 

  34. Prokopy, L. S., Floress, K., Klotthor-Weinkauf, D. & Baumgart-Getz, A. Determinants of agricultural best management practice adoption: evidence from the literature. J. Soil Water Conserv. 63, 300–311 (2008).

    Article  Google Scholar 

  35. Beaman, L. & Dillon, A. Diffusion of agricultural information within social networks: evidence on gender inequalities from Mali. J. Dev. Econ 133, 147–161 (2018).

    Article  Google Scholar 

  36. Warriner, G. K. & Moul, T. M. Kinship and personal communication network influences on the adoption of agriculture conservation technology. J. Rural Stud. 8, 279–291 (1992).

    Article  Google Scholar 

  37. Brugger, J. & Crimmins, M. Designing institutions to support local-level climate change adaptation: insights from a case study of the U.S. cooperative extension system. Weather Clim. Soc. 7, 18–38 (2015).

    Article  Google Scholar 

  38. Lu, J. et al. Explaining the use of online agricultural decision support tools with weather or climate information in the Midwestern United States. J. Environ. Manage. 279, 111758 (2021).

    Article  Google Scholar 

  39. Cash, D. W. et al. Knowledge systems for sustainable development. Proc. Natl Acad. Sci. USA 100, 8086–8091 (2003).

    Article  CAS  Google Scholar 

  40. Useful to Usable (U2U) Decision Support Tools (U2U, 2018);

  41. Koundinya, V. et al. Advisors’ climate risk perceptions and use of climate information: 2016 survey data. Purdue University Research Repository (2018).

  42. Dillman, D. A., Smyth, J. D. & Christian, L. M. Internet, Phone, Mail and Mixed-Mode Surveys: The Tailored Design Method (Wiley & Sons, 2014).

  43. Singh, A. et al. Farmers’ climate risk perceptions and use of climate information: 2016 survey data. Purdue University Research Repository (2018).

  44. Agresti, A. An Introduction to Categorical Data Analysis 2nd edn (Wiley & Sons, 2006).

  45. Ott, R. L. & Longnecker, M. T. An Introduction to Statistical Methods and Data Analysis 6th edn (Cengage, 2008).

  46. Yates, F. Contingency tables involving small numbers and the χ2 test. Suppl. J. R. Stat. Soc. 1, 217–235 (1934).

    Article  Google Scholar 

  47. AgClimate View (HPRCC, 2014);

  48. About AgClimate Viewer (MRCC, 2014);

  49. Angel, J. R., Widhalm, M., Todey, D., Massey, R. & Biehl, L. The U2U Corn Growing Degree Day tool: tracking corn growth across the US Corn Belt. Clim. Risk Manage. 15, 73–81 (2017).

    Article  Google Scholar 

  50. Corn GDD Tool (HPRCC, 2015);

  51. About Corn GDD (MRCC, 2015);

  52. Gramig, B. M., Massey, R. & Yun, S. D. Nitrogen application decision-making under climate risk in the US Corn Belt. Clim. Risk Manage. 15, 82–89 (2017).

    Article  Google Scholar 

  53. Corn Split Nitrogen Application (HPRCC, 2015);

  54. About Corn Split N (MRCC, 2015);

  55. Climate Patterns Viewer (HPRCC, 2015);

  56. About Climate Patterns Viewer (MRCC, 2015);

  57. Irrigation Investment Calculator (HPRCC, 2016);

  58. About Irrigation Investment Calculator (MRCC, 2016);

  59. Van Dop, M. A. Irrigation Adoption, Groundwater Demand and Policy in the U.S. Corn Belt, 2040–2070. MSc thesis, Purdue Univ. (2016).

  60. Bowling, L. C. et al. Agricultural Impacts of Climate Change in Indiana and Potential Adaptations (IN CCIA, 2020).

Download references


This research was part of ‘Useful to Usable (U2U): Transforming Climate Variability and Change Information for Cereal Crop Producers’ and was supported by Agriculture and Food Research Initiative Competitive Grant no. 2011-68002-30220 from the USDA National Institute of Food and Agriculture, project website: The U2U project team was composed of faculty, staff and students from the following land grant and other universities: Purdue University, Iowa State University, Michigan State University, South Dakota State University, University of Illinois, University of Michigan, University of Missouri, University of Nebraska-Lincoln and University of Wisconsin. M.C.L. was also supported by National Oceanic and Atmospheric Administration (NOAA) Climate Program Office (grant no. NA15OAR4310148). We also thank L. Esman (Department of Forestry and Natural Resources at Purdue University) for editorial assistance and K. Paine for graphic design assistance.

Author information

Authors and Affiliations



J.L., M.C.L. and L.S.P. designed the research; J.L., M.C.L., V.K. and L.S.P. performed the research; J.L. analysed the data; L.S.P. supervised and administrated the project; L.S.P. acquired funding; J.L. and M.C.L. wrote the initial draft; J.L., M.C.L., V.K. and L.S.P. reviewed and revised the draft.

Corresponding authors

Correspondence to Junyu Lu or Linda S. Prokopy.

Ethics declarations

Competing interests

The authors declare no competing interests

Additional information

Peer review information Nature Sustainability thanks Suraje Dessai and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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

Supplementary information

Supplementary Information

Supplementary Fig. 1 and Tables 1–4.

Reporting Summary

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Lu, J., Lemos, M.C., Koundinya, V. et al. Scaling up co-produced climate-driven decision support tools for agriculture. Nat Sustain 5, 254–262 (2022).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


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