Hostname: page-component-8448b6f56d-mp689 Total loading time: 0 Render date: 2024-04-19T13:27:54.868Z Has data issue: false hasContentIssue false

In the weeds: distinguishing organic farmers who want information about ecological weed management from those who need it

Published online by Cambridge University Press:  31 January 2018

Doug Bessette*
Affiliation:
Department of Community Sustainability, College of Agriculture & Natural Resources, Michigan State University, 480 Wilson Road, East Lansing, MI 48826, USA
Sarah Zwickle
Affiliation:
School of Environment & Natural Resources, College of Food, Agriculture & Environmental Sciences, The Ohio State University, 2021 Coffey Road, Columbus, OH 43210, USA
Robyn Wilson
Affiliation:
School of Environment & Natural Resources, College of Food, Agriculture & Environmental Sciences, The Ohio State University, 2021 Coffey Road, Columbus, OH 43210, USA
*
Author for correspondence: Doug Bessette, E-mail: bessett6@msu.edu

Abstract

The benefits of farming organically in the USA are increasingly known; however, organic farmers also encounter considerable risks, especially from weeds. Without herbicides, organic farmers can rely only on crop rotations, mechanical cultivation, manual weeding, beneficial insects and other cultural practices, termed ecological weed management (EWM), to control weeds. Despite promising results and the many ways in which EWM can be employed, it remains poorly adopted by the organic community. Organic farmers resist research and recommendations from University scientists and Extension, instead preferring to rely on local family and friends and their own experience to guide decisions. Here we investigate factors that may lead organic farmers to recognize that they need additional information about EWM and to seek that information out. Using a national survey of organic farmers (n = 554) and a risk-information seeking and processing model, we show that farmers’ risk and benefit perceptions, worry, social norms encouraging seeking out information, and farmers’ own perceived knowledge gaps, particularly with respect to their most problematic weed, influence information-seeking behavior. Identifying characteristics that may distinguish those organic farmers who need and want additional information, we provide recommendations to Extension and University scientists about how best to communicate, build trust and provide decision support to the organic community with respect to EWM.

Type
Research Paper
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ajzen, I (1991) The theory of planned behavior. Organizational Behavior and Human Decision Processes 50, 179211.Google Scholar
Amundson, R, Berhe, AA, Hopmans, JW, Olson, C, Sztein, AE and Sparks, DL (2015) Soil and human security in the 21st century. Science 348, 1261071.Google Scholar
Anderson, RL (2010) A rotation design to reduce weed density in organic farming. Renewable Agriculture and Food Systems 25, 189195.Google Scholar
Bastiaans, L, Paolini, R and Baumann, D (2008) Focus on ecological weed management: What is hindering adoption? Weed Research 48, 481491.Google Scholar
Bessette, DL, Arvai, J and Campbell-Arvai, V (2014) Decision support framework for developing regional energy strategies. Environmental Science & Technology 48, 14011408.Google Scholar
Bretagnolle, V and Gaba, S (2015) Weeds for bees? A review. Agronomy for Sustainable Development 35, 891909.Google Scholar
Browning, SR, Westneat, SC and Mcknight, RH (2008) Suicides among farmers in three southeastern states, 1990–1998. Journal of Agricultural Safety and Health 14, 461472.Google Scholar
Chaiken, S, Liberman, A and Eagly, AH (1989) Heuristic and systematic information processing within and beyond the persuasion context. In Uleman, J and J, Bargh's (eds). Unintended Thought. pp. 212252.Google Scholar
Cohen, J, Cohen, P, West, SG and Aiken, LS (2013) Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. Lawrence Erlbaum Associates Inc.Google Scholar
Constance, DH and Choi, JY (2010) Overcoming the barriers to organic adoption in the United States: A look at pragmatic conventional producers in Texas. Sustainability 2, 163188.Google Scholar
Dedecker, JJ, Masiunas, JB, Davis, AS and Flint, CG (2014) Weed management practice selection among Midwest US organic growers. Weed Science 62, 520531.Google Scholar
De Ponti, T, Rijk, B and Van Ittersum, MK (2012) The crop yield gap between organic and conventional agriculture. Agricultural Systems 108, 19.Google Scholar
Doohan, D, Wilson, R, Canales, E and Parker, J (2010) Investigating the human dimension of weed management: New tools of the trade. Weed science 58, 503510.Google Scholar
Earle, TC and Cvetkovich, G (1995) Social Trust: Toward A Cosmopolitan Society. London: Greenwood Publishing Group.Google Scholar
Gabriel, D, Sait, SM, Kunin, WE and Benton, TG (2013) Food production vs. biodiversity: Comparing organic and conventional agriculture. Journal of Applied Ecology 50, 355364.Google Scholar
Gallandt, E and Molloy, T (2008) Exploiting weed management benefits of cover crops requires pre-emption of seed rain. Poster at: Cultivating the Future Based on Science: 2nd Conference of the International Society of Organic Agriculture Research ISOFAR, Modena, Italy, June 18–20, 2008.Google Scholar
Gardner, GT and Stern, PC (1996). Environmental Problems and Human Behavior. Vancouver, BC: Allyn & Bacon.Google Scholar
Griffin, RJ, Dunwoody, S and Neuwirth, K (1999) Proposed model of the relationship of risk information seeking and processing to the development of preventive behaviors. Environmental Research 80, S230S245.Google Scholar
Griffin, RJ, Neuwirth, K, Dunwoody, S and Giese, J (2004) Information sufficiency and risk communication. Media Psychology 6, 2361.Google Scholar
Griffin, RJ, Yang, Z, Ter Huurne, E, Boerner, F, Ortiz, S and Dunwoody, S (2008) After the flood: Anger, attribution, and the seeking of information. Science Communication 29, 285315.Google Scholar
Hanson, J, Dismukes, R, Chambers, W, Greene, C and Kremen, A (2004) Risk and risk management in organic agriculture: Views of organic farmers. Renewable Agriculture and Food Systems 19, 218227.Google Scholar
Hatcher, P and Melander, B (2003) Combining physical, cultural and biological methods: Prospects for integrated non-chemical weed management strategies. Weed Research 43, 303322.Google Scholar
Henckel, L, Börger, L, Meiss, H, Gaba, S and Bretagnolle, V (2015) Organic fields sustain weed metacommunity dynamics in farmland landscapes. Proceedings of the Royal Society B: Biological Sciences 282, 20150002.Google Scholar
Jabbour, R, Zwickle, S, Gallandt, ER, Mcphee, KE, Wilson, RS and Doohan, D (2014) Mental models of organic weed management: Comparison of New England US farmer and expert models. Renewable Agriculture and Food Systems 29, 319333.Google Scholar
Jackson, LE (1997). Ecology in Agriculture. San Diego: Academic Press.Google Scholar
Kahlor, L, Dunwoody, S, Griffin, RJ and Neuwirth, K (2006) Seeking and processing information about impersonal risk. Science Communication 28, 163194.Google Scholar
Kahlor, LA (2007) An augmented risk information seeking model: The case of global warming. Media Psychology 10, 414435.Google Scholar
Kasperson, RE, Golding, D and Tuler, S (1992) Social distrust as a factor in siting hazardous facilities and communicating risks. Journal of Social Issues 48, 161187.Google Scholar
Keeney, RL (1992) Value-focused Thinking. A Path to Creative Decision Making. Cambridge, MA, Harvard University Press.Google Scholar
King, S and White, T (2017). 2017 Census of Agriculture Gets Underway. Washington, DC: USDA.Google Scholar
Kopittke, PM and Menzies, NW (2007) A review of the use of the basic cation saturation ratio and the ‘ideal’ soil. Soil Science Society of America Journal 71, 259265.Google Scholar
Letter, D, Seidel, R and Liebhardt, W (2003) The performance of organic and conventional cropping systems in an extreme climate year. American Journal of Alternative Agriculture 18, 146154.Google Scholar
Liebman, M, Mohler, CL and Staver, CP (2001). Ecological Management of Agricultural Weeds. Cambridge, UK: Cambridge University Press.Google Scholar
Lyson, TA (2012) Civic Agriculture: Reconnecting Farm, Food, and Community. Medford, MA, USA: UPNE.Google Scholar
Macrae, RJ, Frick, B and Martin, RC (2007) Economic and social impacts of organic production systems. Canadian Journal of Plant Science 87, 10371044.Google Scholar
Marshall, E, Brown, V, Boatman, N, Lutman, P, Squire, G and Ward, L (2003) The role of weeds in supporting biological diversity within crop fields. Weed Research 43, 7789.Google Scholar
Mccann, E, Sullivan, S, Erickson, D and De Young, R (1997) Environmental awareness, economic orientation, and farming practices: A comparison of organic and conventional farmers. Environmental Management 21, 747758.Google Scholar
Misiewicz, T, Shade, J, Crowder, D, Delate, K, Sciligo, A and Silva, E (2017). Increasing Agricultural Sustainability Through Organic Farming: Outcomes From the 2016 Organic Confluences Summit. The Organic Center.Google Scholar
Mohler, CL and Johnson, SE (2009). Crop Rotation on Organic Farms: A Planning Manual. Ithaca, NY: Natural Resource, Agriculture, and Engineering Service (NRAES) Cooperative Extension.Google Scholar
Montgomery, DR (2007) Soil erosion and agricultural sustainability. Proceedings of the National Academy of Sciences 104, 1326813272.Google Scholar
Moynihan, M (2011). Status of Organic Agriculture in Minnesota: A Report to the Minnesota Legislature. St Paul: Minnesota Department of Agriculture.Google Scholar
NIFA 2017. Organic Agriculture Program [Online]. https://nifa.usda.gov/program/organic-agriculture-program (Accessed).Google Scholar
Norman, D, Bloomquist, L, Janke, R, Freyenberger, S, Jost, J, Schurle, B and Kok, H (2000) The meaning of sustainable agriculture: Reflections of some Kansas practitioners. American Journal of Alternative Agriculture 15, 129136.Google Scholar
Poortinga, W and Pidgeon, NF (2003) Exploring the dimensionality of trust in risk regulation. Risk Analysis 23, 961972.Google Scholar
Reganold, JP and Wachter, JM (2016) Organic agriculture in the twenty-first century. Nature Plants 2, 15221.Google Scholar
Rogers, EM (2010). Diffusion of Innovations. New York, NY: Simon and Schuster.Google Scholar
Rosmann, M (2005) Sowing the seeds of hope: Providing regional behavioral health supports to the agricultural population. Journal of Agricultural Safety and Health 11, 431439.Google Scholar
Siegrist, M (2000) The influence of trust and perceptions of risks and benefits on the acceptance of gene technology. Risk Analysis 20, 195204.Google Scholar
Siegrist, M, Cvetkovich, G and Roth, C (2000) Salient value similarity, social trust, and risk/benefit perception. Risk Analysis 20, 353362.Google Scholar
Slovic, P (1987) Perception of risk. Science 236, 280285.Google Scholar
Slovic, P, Finucane, ML, Peters, E and Macgregor, DG (2004) Risk as analysis and risk as feelings: Some thoughts about affect, reason, risk, and rationality. Risk Analysis 24, 311322.Google Scholar
Stallones, L, Doenges, T, Dik, BJ and Valley, MA (2013) Occupation and suicide: Colorado, 2004–2006. American Journal of Industrial Medicine 56, 12901295.Google Scholar
Stofferahn, CW (2009) Personal, farm and value orientations in conversion to organic farming. Journal of Sustainable Agriculture 33, 862884.Google Scholar
Sullivan, S, Mccann, E, De Young, R and Erickson, D (1996) Farmers’ attitudes about farming and the environment: A survey of conventional and organic farmers. Journal of Agricultural and Environmental Ethics 9, 123143.Google Scholar
Tautges, NE, Goldberger, JR and Burke, IC (2016) A survey of weed management in organic small grains and forage systems in the Northwest US. Weed Science 64, 513522.Google Scholar
Tiesman, HM, Konda, S, Hartley, D, Menéndez, CC, Ridenour, M and Hendricks, S (2015) Suicide in US workplaces, 2003–2010: A comparison with non-workplace suicides. American Journal of Preventive Medicine 48, 674682.Google Scholar
USDA (2017a) Farm Computer Usage and Ownership [Online]. United States Department of Agriculture. Economics, Statistics and Market Information System. National Agricultural Statistics Service. http://usda.mannlib.cornell.edu/MannUsda/viewDocumentInfo.do?documentID=1062Google Scholar
USDA (2017b) Organic Integrity Database [Online]. United States Department of Agriculture. Agricultural Marketing Service. https://organic.ams.usda.gov/integrity/ (Accessed)Google Scholar
Walz, E (1999) Final Results of the Third Biennial National Organic Farmers’ Survey: Sustaining Organic Farms in a Changing Organic Marketplace. Santa Cruz, CA: Organic Farming Research Foundation.Google Scholar
Willer, H and Lernoud, J (2016) The World of Organic Agriculture, Statistics and Emerging Trends 2016. Bonn, Germany: FIBL, IFOAM First Edition Handbook. ISBN 978-3-03736-306-5.Google Scholar
Wynne, B (1980) Technology, risk and participation: On the social treatment of uncertainty. Society, Technology and Risk Assessment 1980, 173208.Google Scholar
Yang, ZJ, Aloe, AM and Feeley, TH (2014a) Risk information seeking and processing model: A meta-analysis. Journal of Communication 64, 2041.Google Scholar
Yang, ZJ, Rickard, LN, Harrison, TM and Seo, M (2014b) Applying the risk information seeking and processing model to examine support for climate change mitigation policy. Science Communication 36, 296324.Google Scholar
Zwickle, S, Wilson, R and Doohan, D (2014) Identifying the challenges of promoting ecological weed management (EWM) in organic agroecosystems through the lens of behavioral decision making. Agriculture and Human Values 31, 355370.Google Scholar
Zwickle, S, Wilson, R, Bessette, DL, Herms, C and Doohan, D (2016) Facilitating ecological weed management decisions by assessing risk-benefit tradeoffs. Agroecology and Sustainable Food Systems 40, 635659.Google Scholar
Zwickle, SL (2011) Weeds and Organic Weed Management: Investigating Farmer Decisions with A Mental Models Approach. Columubs, OH, USA: The Ohio State University.Google Scholar