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The influence of the seasons: how the agricultural calendar impacts farmer perceptions of cover crops

Published online by Cambridge University Press:  06 December 2021

Margaret Beetstra Open the ORCID record for Margaret Beetstra [Opens in a new window] ,
Robyn Wilson  and
Eric Toman
Margaret Beetstra*
Affiliation:
The Ohio State University, School of Environment and Natural Resources, Columbus, Ohio, USA
Robyn Wilson
Affiliation:
The Ohio State University, School of Environment and Natural Resources, Columbus, Ohio, USA
Eric Toman
Affiliation:
The Ohio State University, School of Environment and Natural Resources, Columbus, Ohio, USA
*
Author for correspondence: Margaret Beetstra, E-mail: beetstra.2@osu.edu
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Abstract

Across the Midwest, substantial funding and personnel time have been allocated to encourage farmers to adopt a wide range of conservation practices but adoption rates for many of these practices remain low. Prior research focuses largely on the influence of individual-level factors (e.g., beliefs, attitudes) on conservation practice adoption rather than on contextual factors (e.g., seasons) that might also play a role. In the present study, we considered seasonal variation and its potential influence on farmer cover crop decision-making. We first established how farmer temporal and financial resources fluctuate across the year and then compared the annual agricultural decision and cover crop decision calendars. We also considered farmer cover crop perceptions and likely behaviors. To study this, we surveyed the same Midwestern farmers in the spring, summer and winter within a 12-month period. Results indicated that farmers were generally the least busy and the most financially comfortable in the winter months. Moreover, farmers perceived the benefits of cover crops differently throughout the year. These results indicate that seasonality can be a confounding factor which should be considered when designing and conducting research and farmer engagement. As researchers, it is our responsibility to understand the specific calendar experienced by our sample and how that may influence responses so we can examine theory-supported factors of interest rather than seasonality as a driver of farmer responses. As practitioners, it is important to use research findings to engage with farmers about conservation in a way that prioritizes communicating about the most salient aspects of the practice at the time of year when farmers will be most receptive.

Keywords

conservationcover cropsfinancesperceived benefitsresourcesseasonalitytime
Type
Preliminary Report
Information
Renewable Agriculture and Food Systems , Volume 37 , Issue 3 , June 2022 , pp. 187 - 197
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Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

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References

Agriculture Improvement Act of 2018 (2018) H.R. 2, 115th Cong.Google Scholar
Andrews, AC, Clawson, RA, Gramig, BM and Raymond, L (2013) Why do farmers adopt conservation tillage? An experimental investigation of framing effects. Journal of Soil and Water Conservation 68, 501–511.CrossRefGoogle Scholar
Arbuckle, JG Jr and Roesch-McNally, G (2015) Cover crop adoption in Iowa: the role of perceived practice characteristics. Journal of Soil and Water Conservation 70, 418–429.CrossRefGoogle Scholar
Arbuckle, JG Jr, Morton, LW and Hobbs, J (2013) Farmer beliefs and concerns about climate change and attitudes toward adaptation and mitigation: evidence from Iowa. Climatic Change 118, 551–563.Google Scholar
Avemegah, E, Gu, W, Abulbasher, A, Koci, K, Ogunyiola, A, Eduful, J, Li, S, Barington, K, Wang, T, Kolady, D, Perkins, L, Leffler, AJ, Kovács, P, Clark, JD, Clay, DE and Ulrich-Schad, JD (2020) An examination of best practices for survey research with agricultural producers. Society & Natural Resources 34, 538–549.CrossRefGoogle Scholar
Bartlett, JE II, Kotrlik, JW and Higgins, CC (2001) Organizational research: determining appropriate sample size in survey research. Information Technology, Learning, and Performance Journal 19, 43–50.Google Scholar
Baumgart-Getz, A, Prokopy, LS and Floress, K (2012) Why farmers adopt best management practice in the United States: a meta-analysis of the adoption literature. Journal of Environmental Management 96, 17–25.CrossRefGoogle ScholarPubMed
Beetstra, M, Tellez, C and Wilson, R (2018) 4R nutrient stewardship in the Western Lake Erie Basin part II: a panel study. The Ohio State University, School of Environment and Natural Resources. Available at http://research.ipni.net/page/RNAP-7227.Google Scholar
Bergtold, JS, Ramsey, S, Maddy, L and Williams, JR (2017) A review of economic considerations for cover crops as a conservation practice. Renewable Agriculture and Food Systems 34, 62–76.CrossRefGoogle Scholar
Burnett, E, Wilson, RS, Heeren, A and Martin, J (2018) Farmer adoption of cover crops in the western Lake Erie basin. Journal of Soil and Water Conservation 73, 143–155.CrossRefGoogle Scholar
Dillman, DA (2011) Mail and Internet Surveys: The Tailored Design Method, 2nd Edn., Hoboken, New Jersey: John Wiley & Sons.Google Scholar
EWG (2019) EWG's farm subsidy database. Available at https://farm.ewg.org/index.php.Google Scholar
Farmer, JR, Ma, Z, Drescher, M, Knacknuhs, EG and Dickinson, SL (2017) Private landowners, voluntary conservation programs, and implementation of conservation friendly land management practices. Conservation Letters 10, 58–66.CrossRefGoogle Scholar
Floress, K, de Jalón, SG, Church, SP, Babin, N, Ulrich-Schad, JD and Prokopy, LS (2017) Toward a theory of farmer conservation attitudes: dual interests and willingness to take action to protect water quality. Journal of Environmental Psychology 53, 73–80.CrossRefGoogle Scholar
Guo, Y, Kopec, JA, Cibere, J, Li, LC and Goldsmith, CH (2016) Population survey features and response rates: a randomized experiment. American Journal of Public Health 106, 1422–1426.CrossRefGoogle Scholar
Hilbig, BE, Erdfelder, E and Pohl, RF (2012) A matter of time: antecedents of one-reason decision making based on recognition. Acta Psychologica 141, 9–16.CrossRefGoogle ScholarPubMed
King, KW, Williams, MR, Macrae, ML, Fausey, NR, Frankenberger, J, Smith, DR, Kleinman, PJ and Brown, LC (2015) Phosphorus transport in agricultural subsurface drainage: a review. Journal of Environment Quality 44, 467–485.CrossRefGoogle ScholarPubMed
Knowler, D (2014) Farmer adoption of conservation agriculture: a review and update. In Farooq, M and Siddique, KHM (eds), Conservation Agriculture. New York: Springer, pp. 621–642.Google Scholar
Lee-Mader, E, Stine, A, Fowler, J, Hopwood, J and Vaughan, M (2020) Cover cropping for pollinators and beneficial insects. Sustainable Agriculture Research and Education. Retrieved from https://www.sare.org/publications/cover-cropping-for-pollinators-and-beneficial-insects/cover-crops-on-your-farm/.Google Scholar
Lee, D, Arbuckle, JG, Zhu, Z and Nowatzke, LW (2018) Conditional causal mediation analysis of factors associated with cover crop adoption in Iowa, USA. Water Resources Research 54, 1–19.CrossRefGoogle Scholar
Lempert, KM and Phelps, EA (2016) The malleability of intertemporal choice. Trends in Cognitive Sciences 20, 64–74.CrossRefGoogle ScholarPubMed
Liu, T, Bruins, RJ and Heberling, MT (2018) Factors influencing farmers’ adoption of best management practices: a review and synthesis. Sustainability 10, 432.CrossRefGoogle ScholarPubMed
Loewenstein, G, O'Donoghue, T and Rabin, M (2003) Projection bias in predicting future utility. The Quarterly Journal of Economics 118, 1209–1248.CrossRefGoogle Scholar
McGuire, J, Morton, LW and Cast, AD (2013) Reconstructing the good farmer identity: shifts in farmer identities and farmer management practices to improve water quality. Agriculture and Human Values 30, 57–69.CrossRefGoogle Scholar
McGuire, JM, Morton, LW, Arbuckle, JG Jr and Cast, AD (2015) Farmer identities and responses to the social–biophysical environment. Journal of Rural Studies 39, 145–155.CrossRefGoogle Scholar
Mullainathan, S and Shafir, E (2013) Scarcity: Why Having Too Little Means So Much. New York: Macmillan.Google Scholar
Olson, B and Davenport, MA (2017) An inductive model of farmer conservation decision making for nitrogen management. Landscape Journal 36, 59–73.CrossRefGoogle Scholar
Pennings, JM, Irwin, SH and Good, DL (2002) Surveying farmers: a case study. Review of Agricultural Economics 24, 266–277.CrossRefGoogle Scholar
Prokopy, LS, Floress, K, Klotthor-Weinkauf, D and Baumgart-Getz, A (2008) Determinants of agricultural best management practice adoption: evidence from the literature. Journal of Soil and Water Conservation 63, 300–311.CrossRefGoogle Scholar
Prokopy, LS, Floress, K, Arbuckle, JG, Church, SP, Eanes, FR, Gao, Y, Gramig, BM, Ranjan, P and Singh, AS (2019) Adoption of agricultural conservation practices in the United States: evidence from 35 years of quantitative literature. Journal of Soil and Water Conservation 74, 520–534.CrossRefGoogle Scholar
Pyone, JS and Isen, AM (2011) Positive affect, intertemporal choice, and levels of thinking: increasing consumers’ willingness to wait. Journal of Marketing Research XLVIII, 532–543.CrossRefGoogle Scholar
Ranjan, P, Church, SP, Floress, K and Prokopy, LS (2019) Synthesizing conservation motivations and barriers: what have we learned from qualitative studies of farmers’ behaviors in the United States? Society & Natural Resources 32, 1171–1199.CrossRefGoogle Scholar
Reimer, AP and Prokopy, LS (2014) Farmer participation in U.S. Farm Bill conservation programs. Environmental Management 53, 318–332.CrossRefGoogle ScholarPubMed
Reimer, AP, Weinkauf, DK and Prokopy, LS (2012) The influence of perceptions of practice characteristics: an examination of agricultural best management practice adoption in two Indiana watersheds. Journal of Rural Studies 28, 118–128.CrossRefGoogle Scholar
Reimer, A, Thompson, A, Prokopy, LS, Arbuckle, JG, Genskow, K, Jackson-Smith, D, Lynne, G, McCann, L, Morton, LW and Nowak, P (2014) People, place, behavior, and context: a research agenda for expanding our understanding of what motivates farmers’ conservation behaviors. Journal of Soil and Water Conservation 69, 57A–61A.CrossRefGoogle Scholar
Reinl, KL, Sterner, RW, Lafrancois, BM and Brovold, S (2020) Fluvial seeding of cyanobacterial blooms in oligotrophic Lake Superior. Harmful Algae 100, 101941.CrossRefGoogle ScholarPubMed
Reutter, JM (2019) Lake Erie: past, present, and future. Encyclopedia of Water: Science, Technology, and Society 1, 1–15.Google Scholar
Roesch-McNally, GE, Basche, AD, Arbuckle, JG, Tyndall, JC, Miguez, FE, Bowman, T and Clay, R (2017) The trouble with cover crops: farmers’ experiences with overcoming barriers to adoption. Renewable Agriculture and Food Systems 33, 322–333.CrossRefGoogle Scholar
SARE-CTIC (Sustainable Agriculture Research and Education – Conservation Technology Information Center) (2020) National cover crop survey: annual report 2019–2020. Available at https://www.sare.org/publications/cover-crops/national-cover-crop-surveys/.Google Scholar
Sax, LJ, Gilmartin, SK and Bryant, AN (2003) Assessing response rates and nonresponse bias in web and paper surveys. Research in Higher Education 44, 409–432.CrossRefGoogle Scholar
Schnitkey, G and Zulauf, C (2019) Late planting decisions in 2019. Farmdoc daily, 9(83). Department of Agricultural and Consumer Economics, University of Illinois at Urbana-Champaign, May 7, 2019.Google Scholar
Shah, AK, Mullainathan, S and Shafir, E (2012) Some consequences of having too little. Science (New York, N.Y.) 338, 682–685.CrossRefGoogle ScholarPubMed
Sheeran, P and Webb, TL (2016) The intention-behavior gap. Social and Personality Psychology Compass 10, 503–518.CrossRefGoogle Scholar
Shelley, K (2015) Cover crops: 16 demonstration plots and their seed mixes [Video]. University of Wisconsin-Madison, Nutrient and Pest Management Program. Retrieved from https://www.youtube.com/watch?v=hx2c0SThQNg.Google Scholar
Sommer, J, Hoppe, RA, Greene, RC and Korb, PJ (1998., 1–118.Google Scholar
Stedman, RC, Connelly, NA, Heberlein, TA, Decker, DJ and Allred, SB (2019) The end of the (research) world as we know it? Understanding and coping with declining response rates to mail surveys. Society & Natural Resources 32, 1139–1154.CrossRefGoogle Scholar
Stuart, D, Schewe, RL and McDermott, M (2014) Reducing nitrogen fertilization application as a climate change mitigation strategy: understanding farmer decision-making and potential barriers to change in the US. Land Use Policy 36, 210–218.CrossRefGoogle Scholar
Stuart, D, Denny, RCH, Houser, M, Reimer, AP and Marquart-Pyatt, S (2018) Farmer selection of sources of information for nitrogen management in the US Midwest: implications for environmental programs. Land Use Policy 70, 289–297.CrossRefGoogle Scholar
Swinton, SM, Rector, N, Robertson, GP, Jolejole-Foreman, CB and Lupi, F (2015) Farmer decisions about adopting environmentally beneficial practices. In Hamilton, SK, Doll, JE and Robertson, GP (Eds), The Ecology of Agricultural Landscapes: Long-Term Research on the Path to Sustainability. New York: Oxford University Press, pp. 340–359.Google Scholar
Thompson, AW, Reimer, A and Prokopy, LS (2015) Farmers’ views of the environment: the influence of competing attitude frames on landscape conservation efforts. Agriculture and Human Values 32, 385–399.CrossRefGoogle Scholar
Ulrich-Schad, JD, de Jalon, SG, Babin, N, Pape, A and Prokopy, LS (2017) Measuring and understanding agricultural producers’ adoption of nutrient best management practices. Journal of Soil and Water Conservation 72, 506–518.CrossRefGoogle Scholar
USDA-ERS (United States Department of Agriculture Economic Research Service) (2020) Government payments by program. Available at https://data.ers.usda.gov/reports.aspx?ID=17833.Google Scholar
USDA-NASS (United States Department of Agriculture National Agricultural Statistics Service) (2019) 2017 Census of agriculture. Available at https://www.nass.usda.gov/Publications/AgCensus/2017/index.php.Google Scholar
Wauters, E and Mathijs, E (2013) An investigation into the socio-psychological determinants of farmers’ conservation decisions: method and implications for policy, extension and research. The Journal of Agricultural Education and Extension 19, 53–72.CrossRefGoogle Scholar
Williams, MR, King, KW, Ford, W, Buda, AR and Kennedy, CD (2016) Effect of tillage on macropore flow and phosphorus transport to tile drains. Water Resources Research 52, 2868–2882.CrossRefGoogle Scholar
Wilson, RS, Howard, G and Burnett, EA (2014) Improving nutrient management practices in agriculture: the role of risk-based beliefs in understanding farmers’ attitudes toward taking additional action. Water Resources Research 50, 6735–6746.CrossRefGoogle Scholar
Wilson, RS, Schlea, DA, Boles, CM and Redder, TM (2018) Using models of farmer behavior to inform eutrophication policy in the Great Lakes. Water Research 139, 38–46.CrossRefGoogle ScholarPubMed
Yoshida, Y, Flint, CG and Dolan, MK (2017) Farming between love and money: US Midwestern farmers’ human-nature relationships and impacts on watershed conservation. Journal of Environmental Planning and Management 61, 1–18.Google Scholar