Can we talk? Improving Weed Management Communication between Organic Farmers and Extension

1. Can we talk? Improving Weed Management Communication between Organic Farmers and Extension Sarah Zwickle, The Ohio State University MarleenRiemens, Wageningen University and Research Centre, the Netherlands November 13, 2012 http://www.extension.org/organic_production

2. MarleenRiemens Wageningen University and Research Centre The Netherlands Sarah Zwickle The Ohio State University Patrick Lillard Purdue University

3. Can we talk? Improving Weed Management Communication between Organic Farmers and Extension Presented by: MarleenRiemens, Wageningen University and Research Centre, the Netherlands and Sarah Zwickle, the Ohio State University

4. Weeds mean Decisions In a sense, farming might be called a warfare against weeds. Some farmers emerge from the struggle victorious, while others go down to defeat. So powerful are weed enemies in reducing crop yields, while at the same time multiplying labor, that the farmer should at every turn strengthen his position against them. He should bear these invaders in mind in planning the crops he will grow and in deciding on the fields where he will grow these crops, in choosing the implements he will use, in buying his seed, and in many other farm activities…Some men do not attack weeds with enough vigor; they look for rocking-chair methods of work. There is no royal road to weed control. In the main, the old doctrine of “hard work and plenty of it” must be observed, but unless this work is applied intelligently a vast amount of labor may be expended with but little accomplished other than a temporary abatement of the evil. (Cox, 1915 USDA Farm Bulletin)

5. Research Questions Collaboration and communication between land grant universities and organic farm community historically poor. (Lyson, 2004) Weed management research is extensive, and Ecological Weed Management (EWM) well known in the scientific community. (Liebman and Mohler 2001; Gallandt and Molloy 2008) What are the obstacles to successful EWM on organic farms?

6. Farmer Mental Model Allows an individual to interpret what they see, make decisions, and solve problems. (Kempton et al., Environmental Values in American Culture, 1997; Morgan, G., B. Fischhoff et al., Risk Communication: A Mental Models Approach, 2002) Internal representation of the external world Helps to explain everyday things Practical !@#%*... Canada thistle... out of place… more than last year… disc or hand pull…

7. Expert Mental Model Theoretical in nature and often research-based Possibly more complex than a lay-person’s mental model Canada Thistle… perennial… taproot… phenological traits…

8. TWO WAY COMMUNICATION Starts with the intended audience’s knowledge, beliefs, and perceptions EFFECTIVE MESSAGE “Weeds” out what the audience already knows INFORMATIVE NOT PRESCRIPTIVE Uses the actual knowledge, beliefs, and perceptions of farmers to communicate what they need to know (not what they should know) to make informed decisions

9. Generating a Mental Model • In-depth interviews • Coding to find categories and concepts • Visualize codes into diagrams/tables

10. Expert Model

11. Expert Model

12. Expert Model Farmer Model

13. Expert Model Farmer Model Salient concepts: Cultivation/Tillage, Cover Cropping, and Resources

14. Expert Model Farmer Model The risks agricultural and ecological risks of weed management were very similar, but farmers focus slightly more on the risks to soil health and have management, rather than ecologically, based risk perceptions.

15. Expert Model Farmer Model Unique farmer concepts of note: seed bank beliefs and indicator weeds. Values also more salient with farmers than experts.

17. How do the two models compare? Sharp alignment in almost every category • EWM knowledge concepts high among farmers (31% experts, 27% farmers) • Risks and benefits perceptions almost identical (risks of cover cropping slightly different) • Rare for mental models research • Explanation: farmers are also experts So why is EWM not implemented successfully? Why are weeds still such a problem?

18. If EWM knowledge is high, why are farmers still struggling? • Constraints and Complexity !@#%*... Canada thistle... need to transplant peppers… only 10% of field… not enough time to hand pull…

19. Decision Science Theories • Descriptive/Behavioral Model • Dual Processing (Damasio 1994; Epstein 1994; Kahneman 2003) • Balance of experience/emotion and deliberation • System 1 and system 2 • Rely on heuristics to speed complex decisions and to motivate behavior • can help and/or hinder (biases)

20. Ranking Exercise • What are the most important considerations when making a weed management decision? • Work fairly quickly (simulate time constraints) • 16 note cards based on system 1 and system 2 processing. For example: • What worked in the past (experience) system 1 • Latest science and research system 2

21. Rankings Decision Factor System • What worked in the past 1 • Time and labor 1 • Type and timing of weed 2 • Soil health 1

22. Rankings Decision Factor System • What worked in the past 1 • Time and labor 1 • Type and timing of weed 2 • Soil health 1 • Public perception 1 • NOP standards 2 • Latest research and science 2 • Extension recommendations 2

23. Most Important Least Important

24. System 1 Short-Cuts: Affect “We accepted an enormous amount of weed pressure on the farm when I took it over, and I accepted it, too. But now I realize that this is crazy.” • Affective Responses • Initial response to weeds • 95% negative • Lead to emotional reactions that could enhance dread/ uncontrollability and influence risk perceptions • If risk perception too high/low, bad • If risk perception balanced with deliberation, good • Motivate both short and long term choices

25. System 1 Short Cuts: Satisficing “You know corn, soybean, wheat is not a good enough rotation. There needs to be more than a three way rotation, but you know we’re so starved for money that you feel like you can’t do that.” “What can I do with the equipment that I have and the amount of time I have to best utilize it?” • Satisficing • Based on most important attributes of a choice • Economics • Ecology • Health

26. Trade-Offs “Why aren’t you cutting hay?” they ask, and I had the “lame” excuse that the bobolinks are nesting. “Bobolinks are nesting!” I said. “Well you don’t worry about bobolinks” they said. “Well, yes I do.” • Trade-offs • How do farmers weigh their values and their perceptions of weed management options in their decisions? • Short term economics, long term soil health? • Clean fields or weed thresholds? • Ecological partnership or economic maximization? (Marleen has a good slide on this one)

27. Decision Tools:Trade-offs Table

28. Conclusions • Farmer knowledge is management (experience/system 1) based • Organic farmers observe how their actions effect weed populations. Focus less on ecology and more on management based causes and solutions for weeds. • Farmers have strong risk perceptions in relation to soil health

29. Recommendations • Emphasize benefits of weed management to soil health • Recognize farmer’s skill in cultivation and tillage • Research Farmer Short-Cuts • Emphasize seedbank strategies (cover cropping/rotations) as saving time and labor in the long run with data • Facilitate trade-offs with farmers by providing the costs and benefits of different management practices according to their values • Research mechanisms behind indicator weed observations • Conduct on-farm research that matches their way of learning about weeds and weed mgt.(trial and error/experience)

30. Thank you for listening • Sarah Zwickle zwickle.2@osu.edu http://ess.osu.edu/sites/drupal-essl.web/files/OWE_report2%20(2).pdf

31. Weed management is more than technology:the importance of the farmer Observations in the Netherlands

32. About the Netherlands • Population: ~16,7 million • Total area for agricultural land: 1.858.390 ha • Total area organic: 55.182 ha ~3%, but increasing with 10% per year

33. Farming systems in the Netherlands • Average size conventional farm: 26.4 ha • Average size organic farm: 36.5 ha • Main AGF crops: • Potatoes • Carrot • Onions • Peas • Cabbage

34. Typical Crop Rotation 1 out of 4-7,e.g. • Sugarbeet • Summerwheat • Carrot • Peas • Consumption potatoes • Grass/clover • Seed onions

35. Dutch organisation of agricultural knowledge development and dissemination • Several institutions active: • OVO-model • Green education • Knowledge vouchers • Regional knowledge centres • Regional knowledge managers

36. 3 general types of innovation* • Linear model, science driven: • fundamental-> applied-> adaptive research->extensions-> application by farmers • Chain link model, demand-pulled: • Many feedback loops between innovation, testing, redesign, distribution, production and marketing. • Participatory technology development model, farmers in control: • Adaptive oriented research, farmers in control, strong emphasis on local knowledge *(Rölings and Seegers, 1992)

37. OVO- model (1880-1990s)(OVO meaning Research Extension and Education) • Linear model • All agricultural research carried out under the Ministry of Agriculture: • 1 university • 34 research institutes • 49 regional research centres (experimental farms) • Systematic research programmes

38. Highly successful • 1950s -1980s: Clear goal: increase production volumes, lower costs and improve quality

39. Global Changes, different demands • 1990s: • Overproduction and environmental problems • Global demand for more liberalization and diversity of markets. Innovation became responsible of markets. • More diverse goals and diversification of production systems

40. Participatory Technology Development • 1990s-today: • extension and (part of) research privatized • shift from linear OVO-model to Participatory Technology Development models via the Chain Link model. • Research institutes serve participants in networks of farmers, agribusiness and public sector. • Research demand-pulled system (demands of both farmers as well as agribusiness and public)

41. Basic rules for research in demand pulled systems* • Understand the system in which you participate. • Be aware of your role: • problem observation and methodology development. * Van Dijk & Van Boekel, 2001

42. Understanding the system • Need to understand the system where we as weed scientists are part of. • Start of explorative study in 2003 on weed management systems. • Investigate farmer beliefs on weed management and weed management behavior, identify problems they encounter and link that to outcome of behavior (weed pressure).

43. Explorative 3 year study on weed management behavior • Specific question Can we relate: • weed pressure to weed management behavior, • weed pressure to farmer beliefs about weeds and weed management, • weed management beliefs to weed management behavior? • Approach 16 farms in NL Investigated: • Weed pressure (weed seed production and weed density) • Application of type of Management Strategies (EWM or CWF) • Beliefs on Weeds and Weed management

44. Weed pressure explained by management behavior • Variation in weed pressure was best explained by two management activities: • Timing of the main soil tillage treatment (spring or fall) • Number of applied preventive measures (EWM strategies) • Ploughing in autumn prevented seed production during winter and early spring of abundant species such as Stellaria media and Poaannua. • Preventive measures were activities targeting the seed bank, e.g. stale seed bed preparations, use of competitive cover crops.

45. Weed pressure related to farmer beliefs • Beliefs on soil structural damage

46. Weed pressure related to farmer beliefs • Beliefs on importance of long term strategizing (short term market oriented vs. long term rotation oriented)

47. Weed management beliefs related to weed management behavior • Long term oriented farmers (with lower weed pressure) grow different crops from farmers that are more short term market oriented. • Long term thinkers grow more competitive crops such as Cabbages, potatoes, cereals, grass, legumes, with lower yield ($). • Short term market oriented farmers grow more crops with less competitive qualities such as flower bulbs, onions, sunflower, pumpkin, but with higher yield ($).

48. Conclusion of explorative study The incorporation of the human dimension, in terms of farmers’ beliefs, attitudes and behavior, can lead to a better understanding of the (organic) farming systems and lead to more effective communication on weed management in those systems. MM Riemens et al., 2010. Weed Science 58(4): 490-496

49. Dutch results within current project • Similar to Midwest: • Knowledge of (experience) EWM principles high • External farm constraints are a barrier • In addition to Midwest: • Farmers indicate that species specific EWM requires more experiment based EWM knowledge (knowledge research can not provide yet). • No or reduced till systems are a big issue: farmers want to know whether these systems will reduce or increase weed seed banks.

50. Factors taken into consideration