Multiple Forms of Uncertainty as a Barrier to the Adoption of Sustainable Farming Practices

Final Report for GW12-004

Project Type: Graduate Student
Funds awarded in 2012: $24,830.00
Projected End Date: 12/31/2015
Region: Western
State: Montana
Graduate Student:
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Project Information

Summary:

Large-scale dryland agricultural systems in North America are under increasing pressure from highly variable bioclimatic and economic stressors. Simultaneously, society is increasingly demanding that these systems become more sustainable ecologically and environmentally. The purpose of this study was to understand how these stressors influence the adoption of sustainable farming practices. Additionally, this project sought to identify leverage points within the decision-making process of producers that could be harnessed to promote adaptability and resiliency.

Using a mixed quantitative and qualitative approach that synthesized historical data, farmer interviews, and surveys, we discovered that dryland farmers in the Northern Great Plains (NGP) of Montana have experienced increasing economic stress since the 1970s and unpredictable yet damaging stress from drought. Spatial variability and weed/pest pressure were not primary stressors; however, they were occasionally strongly influential. Economic and climatic pressures constrained the ability of producers to adopt sustainable practices, depending on the immediacy and synergistic effects of the stressors.   

To facilitate greater adoption of sustainable practices, we identified the use of systematic on-farm experimentation as a primary means of promoting ecological and climate-resilient practices. Starting with trials that build on producers' trust in the value of rotations, these experiments could then be expanded to other practices. Finally, peer-to-peer farming networks emerged as the most effective means for promoting experimentation; thus, an effective strategy would be to identify early-adopter farmers who could facilitate a culture of experimentation.

Introduction

Dryland agricultural systems in the Northern Great Plains (NGP) are typified by low economic margins, high levels of biophysical variability, and high sensitivity to fluctuations in precipitation. Producers respond to these uncertainties by seeking to reduce economic and environmental risks. Their strategies for minimizing exposure are usually focused on the use of highly specialized crops, technology, and external inputs rather than diversified crop rotations and agroecological techniques. In order to facilitate the increased use of ecological management, it is important to understand how various forms of uncertainty propel farmers towards specific risk-reductions strategies. This requires knowledge about the actual and perceived vulnerability of NGP farming systems and of the decision-making process by which producers respond to stressors.

The most prominent uncertainties within NGP agricultural systems are climate, prices of inputs, crop prices, weeds/pests, and the spatial distribution of biophysical crop production factors. Weeds, pests, and their spatial distributions may have significant impacts upon crop productivity (Maxwell and Luschei 2005); some producers may experience significant effects while others may remain relatively unscathed. The spatial distribution of other yield-influencing factors such as soil water holding capacity can also impact sub-field scale productivity (Florin et al. 2011) and may lead to management approaches that are conservative with regards to minimizing productivity losses, despite obvious inefficiencies.

Climate and economic uncertainties are more obvious factors that may influence the adoption of sustainable agricultural practices and farm vulnerability in general. With increasing recognition of the potential impacts of climate change on agricultural production (e.g. Lobell et al. 2008), there is elevated concern over the vulnerability of crops and commodity farming systems to changes in temperature and precipitation. Simultaneously, drastic swings in commodity and input prices over the last few decades have produced highly volatile economic outcomes that challenge management decisions on individual farms. Together, these twin stressors have the potential to synergistically interact to threaten large numbers of commodity-reliant farms. What will ultimately determine the vulnerability of these farms is the magnitude and variability of the stressors, the tools that farmers have to mitigate impacts, and the ability of farmers to assimilate new practices that are better adapted to novel conditions (Berkes et al. 2007, Tarleton and Ramsey 2008).

The ability of farmers to resist the stressors outlined above, while gradually adopting more sustainable agricultural practices, depends on the tools that are available for mitigation and on the adaptability of farmers (individually and collectively) to novel conditions (Berkes et al. 2007). Historical events (McLeman 2008), farmer perceptions of risk and uncertainty (Sunding and Zilberman 2000), and pathways of social agricultural learning (Roling and Jiggins 1998) all lend insight into this adaptation process. Furthermore, qualitative understanding of the relationship between information sharing, learning, adaptive capacity and resilience can create a window into the adaptability of farmers and how it may be enhanced to endure climate change, fluctuating prices, and spatial variability (Tarnoczi 2011).

To explore the stressors that impact dryland agricultural systems and how they shape farming practices, we chose to focus on a geographical region that is already impacted by high levels of uncertainty. Specifically, the Northern Great Plains (NGP) of Montana is an agricultural region that primarily produces dryland wheat and has a semi-arid climate (et al. 2004).

No previous research has explored the social adaptability and vulnerability against the backdrop of exposure to multiple stressors.This assessment of vulnerability for these farming systems was designed to fill this gap in understanding. To do so, we first reviewed the vulnerability of NGP farmers within a historical context. Second, the research explored the number and quality of options that farmers have to mitigate the impacts of these stressors. Finally, a conceptual map of the pathways of adaptation was constructed in order to understand the generalized adaptability of NGP farmers to multiple stressors. Together, these components and their exploration via quantitative and qualitative methods helped describe the resilience of marginal dryland agricultural systems and the barriers to adoption of sustainable farming practices.

Project Objectives:

Original Objectives

  1. Establish rapport with each of the three case study farmers, building an understanding of their management styles, perceptions of risk, and responses to vulnerability
  2. Qualitatively asses the case study farmers’ reactions to five forms of uncertainty within their systems:
    - Topographic/Spatial variability
    - Weed and pest variability
    - Climatic variability
    - Variability in price of inputs (fertilizer, fuel and herbicides) - Variability in the prices received for commodities
  3. Design a survey to assess the reaction of a larger group of farmers to uncertainty
  4. Administer the designed survey through a first series of five workshops and producer outreach events.     
  5. Use the three case studies and survey data to assess the relative response of the    farmers to uncertainty.  In particular, categorize the responses based on whether they perceive each source (Objectives 2a – e) of uncertainty to be a threat and what tools they think are viable to deal with the uncertainty.      
  6. Produce an extension webpage, a Mont Guide (extension publication) and develop the  workshop presentation to target producers. 
  7. Facilitate the second series of three workshops to a larger group of producers to disseminate results.   

Updated Objectives

  • Ten additional in-depth farmer interviews completed with Montana Grain Growers Associationa (MGGA) board members and seven with randomly selected MGGA conference participants.
  • Interviews transcribed, coded, and analyzed for themes
  • Publication materials prepared for submission
  • Results presented at Resilience 2014 conference
  • Report completed and relevant results displayed online

Cooperators

Click linked name(s) to expand/collapse or show everyone's info
  • Gary Arnst
  • Chuck Merja
  • Bob Quinn

Research

Materials and methods:

Qualitative Approach

To understand how uncertainties influence and structure decision-making among large-scale dryland producers in the NGP, an iterative mixed-methods approach was utilized. First, three case-study farmers were extensively interviewed (open-ended) to generate initial knowledge on options and theory about adaptability. Each farmer was chosen based upon previous interactions with Montana State University personnel; thus, they would be expected to be relatively innovative and research-oriented. These interviews were coded and inductively analyzed (Glaser and Strauss 1967) for themes that generally related to adaptation and the farmers’ responses to stressors. Second, a survey based on the derived themes was administered to a larger group of farmers associated with the Montana Grain Growers Association (MGGA) and farmers attending workshops on herbicides and precision agriculture facilitated by Montana State University personnel.

The survey first established that the respondents fit the criteria of having farming as their primary occupation, that they primarily grew wheat or other small grains, and their farm was larger than 500 acres. Once vetted, the farmers were provided with a scenario of extended drought and were asked about their available agronomic tools to respond to the situation and where they would seek additional information to respond. Questions covering the same subject matter were posed with several alternative wordings to validate the responses of each farmer. A total number of 54 surveys were returned electronically and in paper form.

Following the survey, ten semi-structured interviews were administered to MGGA board members who had not responded to the survey (non-respondents) and to seven randomly chosen MGGA members who attended the MGGA annual meeting. This final stage generated understanding of farmers’ responses to economic stressors and further refined the theory developed from the initial interviews and subsequent surveys.

Quantitative Approach

To gain a better understanding of how the three primary stressors identified in the interviews (input prices, crop prices, and climatic drivers) historically shaped farmer adaptability, a quantitative approach was utilized. Historical census and annual survey data (USDA NASS) on farm sizes, farm numbers, fertilizer use, and prices was used to assess the average commodity-scale wheat farmers’ exposure to economic risk. Economic risk was calculated as the ratio of the total cost of nitrogen fertilizer to the total returns from wheat sales, derived on a per-hectare basis. All prices were adjusted for inflation, with 1980 as the baseline year. The area (hectare) normalization procedure accounted for trends in productivity and the quantity of fertilizer used (fertilizer usage data from the Montana Dept. of Agriculture) and the final costs and returns factored in changes in market prices. Henceforth, we refer to this economic risk ratio as the N-W ratio.

The Palmer Drought Z-index (PZI), averaged over the growing season months from April until August, was used as a quantitative indicator of moisture stress (NCDC) and has been shown to be the index most highly correlated with yields in the NGP (Quiring 2003). To assess the magnitude of variations of the PZI and the N-W ratio and how they have changed over time, both indices were standardized by subtracting the long-run averages (over 38 years) of the time series from the annual values then dividing by their standard deviations. Finally, to construct a measure of total stress to the farmer, the indices were additively combined. This additive combination ignores the non-linear, interactive impact of drought on total stress, whereby greater intensities of drought would have proportionally increased physiological impacts on crop productivity. In contrast, the impact of an increase in the N-W price ratio on total stress would be expected to follow a more linear trend, even though a distinct profitability threshold (cliff) exists. Unfortunately, there are no empirically justifiable methods to weight the PZI more heavily than the N-W price ratio; therefore, this aspect of analysis was omitted.

Research results and discussion:

In general, the primary sources of variability that impacted producers were drought, low wheat prices, and high nitrogen prices. Spatial variability was relatively unimportant to producers, and weed variability substantially impacted a small number of producers but was overall less important. Thus, the focus of the project shifted substantially after the case studies and initial surveys to focus on these three primary stressors.

Economic Variability and Vulnerability

Within the U.S. and the NGP in particular, it was expected that the quantity used and cost of fertilizer had increased from 1970 until present, burdening farmers with increased input expenditures. The census data confirmed this expectation, with amount of fertilizer used per acre consistently increasing from 1970 onwards (Figure 1), even though the specific forms of nitrogen fertilizer changed from predominantly anhydrous ammonia to urea. Similarly, the price of fertilizer consistently increased (Figure 2), with the most common form of fertilizer in the NGP today, urea, costing $0.17/kg in 1960 and $0.58/kg in 2012.

The total cost of fertilizer, accounting for the different fertilizer mixes, prices, and quantities used across years, computed on a per-hectare basis, also increased substantially from 1970 through 2011 (Figure 3). However, the wheat price also increased during this time period, from $.08/bu in 1974 to $.28/bu in 2011 (Figure 4).

Despite the simultaneous rise in wheat and fertilizer prices, deviations in the N-W price ratio have consistently increased (Figure 5), with the exception of the 2002 census year. The PZI was more variable during this time period, with elevated periods of moisture stress (positive values = greater stress) during the early and late 1980s and during the early-mid 2000s. Together, the additive total stress of these components appeared to reach its zenith in 2001. These periods of total stress closely parallel events such as the extended droughts in the 1980s and early 2000s.

Number and Quality of Options for Mitigating Variability and Stressors

A total 54 survey responses, 17 semi-structured interviews, and three case studies were used to understand the suite of options that farmers would consider in response to drought or high nitrogen prices. The quantity and quality of tools available would be expected to partially determine the vulnerability of farmers to drought and economic trends outlined in the previous section.

IIA - DROUGHT

Planting a mix of drought-tolerant and drought-intolerant crops provides farmers with a way to hedge against the risks of low or high-moisture years. During dry years, drought-tolerant crops thrive while the drought-intolerant crops underperform, and vice versa. Such a strategy reduces the variance of net returns, eliminating the possibility of high profits during climatically favorable years but reducing the risk of failure when drought occurs.

When asked how they would respond to a scenario of prolonged drought, the majority of farmers indicated that they would only sow an alternative crop (31%), with fewer farmers suggesting they would sow two (28%), three (11%), four (6%), and six (1 respondent) alternative crops. The specific crops mentioned were highly variable (Table 1), with the largest numbers of farmers suggesting wheat, which is already the dominant crop, or that they were unsure or needed more information.

Management practices that the farmers had at their disposal to manage the impact of drought (Table 2) were very limited, with many of the practices, such as no-till, being already used. Other responses reflected this lack of readily accessible options, including reducing expenses, lowering yield goals to reduce the amount of fertilizer used, changing planting dates, and utilizing crop rotations to increase moisture retention.

Pathways of Adaptation

The conceptual map depicting the process of farmer adaptation is best described as a funnel of constricting possibilities, with new practices filtered out (sieved) in discrete stages (Figure 6). The map is similar to the broader sociological literature on adoption (Mason 1964, Ruttan 1996, Marra 2003), which characterizes the process using the general stages of Awareness, Interest, Evaluation, Trial, and Adoption. The key component which differentiates this study is the inclusion of economic and climatic stressors as drivers in the process of adaptation. The very top of the funnel is where the greatest number of outcomes is possible. At this stage, which we refer to as the blank slate stage, farmers are exposed to the largest number of information sources, and they are unconstrained by any stressors or preconceptions which may limit their future choice of agricultural options.

For the descriptions of the stages a brief overview is provided; more details including specific producer comments may be found in the upcoming journal article in Climatic Change.

BLANK SLATE STAGE

During this stage, farmers consult a variety of information sources (Figure 8), seeking out different agronomic authorities for different solutions. Farmers have to be adept at accessing many different information sources; as the quality level of information provided by some of the previous technical sources was cited as declining (possibly due to breadth of information now required), it may help to explain why the majority of them most heavily rely on personal experience for day-to-day decisions. The interview data support this observation, with farmers citing a diversity of sources including internet forums, extension publications, university personnel, chemical dealers, and personal experience for their sources of agronomic information. During the blank slate stage, the farmers are also free of climatic, economic, or other stressors. Naturally, they are also exposed to these sources of information during times of stress, but when stressors are in play, they prevent (Stressor Constraint Stage) farmers from being able to act on any information obtained.

Whether from the internet, extension agents, or another source, farmers are thus exposed to new practices that they have not already employed. This may take the form of chemical/seed dealers proposing a new herbicide or farm magazines promoting a new crop. However, when farmers are stressed, they unanimously cut back on trials of new practices, operating reactively instead of proactively.

FARM FIT STAGE

During this stage, the most important criterion cited for evaluating a new practice was its economic viability, which means that it either lowers costs for the farmer or taps into a lucrative market (for a new crop). For example, many farmers are currently considering planting dryland corn due to relatively high current corn prices.

Secondary to economic opportunity, the prominent consideration for farmers is rotation. Every farmer interviewed emphasized a belief in the value of rotating crops, both for reducing weed and pest issues, but also for reducing nitrogen costs and for increasing the intensity of cropping (rather than having years of fallow).

Logistics and the time required to implement a new practice was the third most frequently cited constraint for adoption. Most NGP farmers work long hours during the growing season by themselves or with a limited number of other family members or employees; thus, the difficulty of dealing with new equipment, making more passes with the herbicide sprayer, or expending other precious time is a significant consideration.

MICRO-ANALYSIS STAGES

The final four stages that farmers go through before new crops or practices are integrated into their farming operations involve detailed considerations that may support or rule out the change. At first, farmers gather detailed information on equipment requirements, fertilization, or other factors that must be known to actually implement the change. Next, farmers re-visit observations or comments from their peers that may validate or reject the proposed practice. These observations and or social learnings may, at any point during the adaptation process, irreversibly convince farmers to abandon their exploration of the new practice. Social observations (farmers watching neighbor farmers), in particular, are very strong motivations or deterrents.

If everything appears to be suitable and feasible for the farmer, then every farmer surveyed mentioned that they will implement a test field of the new crop or practice. These trials range from 40-360 acres, with an average of 200 acres used.

PSYCHOLOGICAL DRIVERS

Throughout the adaptation process, there may also be psychological drivers or influences that propel farmers to increase or decrease the speed of adoption. One primary driver is the perception of farmer-to-farmer competition.

A variety of psychological drivers were mentioned; however, increasing the individual farmer's social recognition as a progressive or high-producing farmer was the most highly cited reason for making specific agronomic decisions. A preference for risk-taking was also a clear psychological driver for some farmers but was not examined in enough depth to draw generalizations.

Discussion

TOTAL STRESS

In this report, we have illustrated the gradually increasing stress experienced by farmers since 1974, which has been primarily driven by the nitrogen cost to wheat price received ratio. Drought has amplified this stress during key periods, such as in the early and late 1980s, and in the late 1990s to early 2000s, yet it remains relatively unpredictable. In contrast, the N-W ratio has been driven steadily higher by higher fertilizer prices (relative to wheat prices) and increased fertilizer use. The explanations for increased fertilizer use are complex; however, they may be partially explained by the concept that farmers “fertilize for the good years” (Babcock 1992), with the assumption that increased profits under favorable weather conditions offset the costs of over-fertilizing during bad years. This assumption depends on the rate of increase of the marginal productivity of nitrogen as precipitation increases, and the marginal increase in net returns from increased yields. In dryland scenarios with a non-linear yield response and extended periods of drought, this strategy of over-fertilization may be detrimental to net returns and, therefore, may increase total stress. Farmer adaptation to these stressors parallels their temporal predictability, which, as discussed later, suggests specific approaches for increasing adaptability.

DROUGHT ADAPTATIONS

Given the paucity of crops and management practices cited by farmers for managing drought, farmers could face serious consequences if a severe drought were to develop in the NGP. Such droughts are not uncommon, with the most severe of the 20th century occurring during the dust bowl of the 1930s and the drought of the mid to late 1980s. During such conditions, most farmers chose to exclusively plant wheat and fallow their fields more frequently, which are economically rational decisions over short time periods. Unfortunately, such decisions are not rational over longer time scales, because cutting back on rotational crops ultimately reduces long-term resilience to drought by reducing the formation of soil organic matter which is important for retention of soil moisture. This is consistent with the observation that adverse events that are low-probability, high-consequence, and primarily observable through statistics, are less likely to elicit evasive actions than those that have immediate, visible effects (Weber 2006).

N-W RATIO ADAPTATIONS

Although rotations were more widely viewed as a benefit for weed and pest suppression than for mitigating the effects of high nitrogen prices, their status as the second-most cited mitigation technique (behind cutting back on application rates) points to their future potential. Simply reducing the amount of nitrogen applied has the advantage of a quick reduction in costs; however, it also depletes the pool of soil N and inevitably results in lower yields. Leguminous rotations; however, are able to supply a significant quantity of N to the cash crop, albeit only after used continuously for six years (Campbell et al. 1992, Walley et al. 2007). Whether by emphasizing the reduced costs of weed and pest control or by promotion as a way to reduce nitrogen costs, pulse crops are the most viable method for increasing resilience to a high N-W ratio. Both justifications fit in with the primary concern of farmers being economic viability. Furthermore, leguminous rotations simultaneously assist in building soil organic matter, which has concurrent implications for mitigating drought by increasing soil moisture holding capacity. Interestingly, controlled-release fertilizers (formulations that release slowly) were not mentioned despite their potential for reducing fertilizer costs by lowering the amount of nitrogen lost to volatilization or leaching (Gioacchini et al. 2002).

ADAPTABILITY AND INTERACTING STRESSORS

The squeeze of the bioeconomic vise discussed in this paper is driven by jaws that move at different speeds and frequencies. The inexorable increase of the N-W ratio moves one jaw of the vise with enough apparent predictability that farmers have the option of slowly adapting through the gradual incorporation of pulse crops or other methods of increasing nitrogen use efficiency. The jerky motion of the opposing drought vise makes adaptation far more difficult, and it excludes mitigation strategies and experimentation at the time that they are most needed. Resilience through crop rotation does appear to be slowly increasing, with 51,000 acres devoted to pulse crops in 1998 and 638,000 (11.3% of NGP cropland) acres in 2013 (USDA NASS). However, this resilience is interrupted during periods of drought, and it remains to be seen whether adoption can outpace the slow yet continuous increases of the N-W price ratio.

Periods of intense stress, when both the N-W ratio is high and soil moisture is limited, are thus unlikely to be profitable times for increasing farmer adaptability. Farmers’ economic freedom to experiment is also more limited during these periods, as crop insurance reimbursement rates decrease (calculated based on five-year averages) and insurance for non-standard crops remains more difficult to obtain. Although farmers are constantly exposed to a variety of information sources, their economic conservatism will likely trump their belief in the value of rotations. Furthermore, their peers are unlikely to have positive demonstrations of rotational crop performance during such periods, which prompts an even greater reduction in experimentation. It has been argued by some economists that farmers are correct in this hesitation because the costs of experimentation outweigh the value of information gained by waiting for the trajectory of future conditions to become clear (Lombardi 2009). Yet while this “option value” would be rational for a stressor like the N-W price ratio that appears to have a somewhat predictable signal, it would not hold true for climatic stressors that are highly variable and uncertain for specific locations.

Thus there exists a conflict between short and long-term economic and agronomic rationality that ultimately serves to decrease the resilience to these stressors during times of drought. Drought mitigation through the improvement of soil organic matter requires ~20 years (West and Post 2002), and increasing the nitrogen supplying power of soil requires at the very least six years (Campbell et al. 1992, Walley et al. 2007); hence, economic incentives may be required to maintain rotations even in the presence of drought. These incentives could be aligned with efforts to increase carbon sequestration, which have found that increasing rotational complexity could sequester an average of 20 ± 12 g Carbon m−2 yr−1 (West and Post 2002). However, without incentives, even producers (such as organic farmers) who may have a stronger long-term motivation to increase organic matter and who are aware of the benefits in doing so are subject to the short-term need to maximize profits (Knutson et al. 2011). Therefore, market development for drought-tolerant crops or policy incentives to increase long-term drought resilience may be required.

REFERENCES

Antle, J.M., Capalbo, S.M., Elliott, E.T., Paustian, K.H. 2004. Adaptation, spatial heterogeneity, and the vulnerability of agricultural systems to climate change and CO2 fertilization: an integrated assessment approach. Climatic change 64: 289-315.

Babcock, B.A. 1992. The effects of uncertainty on optimal nitrogen applications. Applied economic perspectives and policy 14: 271-280.

Berkes F., Armitage D., Doubleday N. 2007. Synthesis: adapting, innovating, evolving. In: Armitage D, Berkes F, Doubleday N (eds) Adaptive co-management: collaboration, learning and multi-level governance. UBC Press, Vancouver.

Bradshaw, B., Dolan, H., Smit, B. 2004. Farm-level adaptation to climatic variability and change: crop diversification in the Canadian prairies. Climatic Change 67: 119-141.

Campbell CA, Zentner RP, Selles F, Biederbeck VO, Leyshon AJ. 1992. Comparative effects of grain lentil wheat and monoculture wheat on crop production, N-economy and N-fertility in a Brown Chernozem. Can J Plant Sci 72:1091–1107

Florin, M.J., McBratney, A.B., Whelan, B.M., Minasny, B. 2011. Inverse meta-modelling to estimate soil available water capacity at high spatial resolution across a farm. Precision Agriculture 12: 421-438.

Gioacchini, P., Nastri, A., Marzadori, C., Giovannini, C., Antisari, L.V., Gessa, C. 2002. Influence of urease and nitrification inhibitors on N losses from soils fertilized with urea. Biol Fertil Soils 36: 129-135.

Glaser, B.G, Strauss, A.L. 1967. The discovery of grounded theory: strategies for qualitative research. Wiedenfeld and Nicholson, London.

Hudson, B.D. Soil Organic Matter and Available Water Capacity. 1994. Journal of Soil and Water Conservation 49:189-194.

Knutson, C.L., Haigh, T., Hayes, M.J., Widhalm, M., Nothwehr, J., Kleinschmidt, M., Graf, L. 2011. Farmer perceptions of sustainable agriculture practices and drought risk reduction in Nebraska, USA. Renewable Agriculture and Food Systems 26: 255-266.

Lobell D.B., Burke M.B, Tebaldi C., Mastrandrea M.C., Falcon W.P., Naylor R.L. 2008. Prioritizing Climate Change Adaptation Needs for Food Security in 2030. Science 319: 607-610.

Lombardi, D. 2009. Business Investment under Uncertainty and Irreversibility. Oxonomics 4: 25 – 31.

Marra, M., Pannell, D.J., Abadi Ghadim, A. 2003. The economics of risk, uncertainty and learning in the adoption of new agricultural technologies: where are we on the learning curve? Agricultural Systems 75: 215-234.

Mason, R.G. 1964. The use of information sources in the process of adoption. Rural Sociology 29: 40-52.

Maxwell, B.D., Luschei, E.C. 2005. Justification for site-specific weed management based on ecology and economics. Weed Science 53: 221-227.

McLeman, R., Mayo, D., Strebeck, E., Smit, B. 2008. Drought adaptation in rural eastern Oklahoma in the 1930s: lessons for climate change adaptation research. Mitigation and Adaptation Strategies for Global Change 13: 379-400.

Quiring, S.M., Papakryiakou, T.N. 2003. An evaluation of agricultural drought indices for the Canadian prairies. Agricultural and forest meteorology 118: 49-62.

Roling NG, Jiggins J. 1998. The ecological knowledge system. In: Roling NG, Wagemakers MAE (eds) Facilitating sustainable agriculture: participatory learning and adaptive management in times of environmental uncertainty. Cambridge University Press, UK

Ruttan, V.W. 1996. What happened to technology adoption-diffusion research? Sociologia Ruralis 36: 51-73.

Saltiel, J., Bauder, J.W., Palakovich, S. 1994. Adoption of sustainable agricultural practices: diffusion, farm structure, and profitability. Rural sociology 59: 333-349.

Sunding D, Zilberman D. 2000. The agricultural innovation process: research and technology adoption in a changing agricultural industry. In: Gardner B, Rausser GC (eds) Handbook of agricultural and resource economics. Elsevier, Amsterdam, pp 207–261

Tarnoczi, T. 2011. Transformative learning and adaptation to climate change in the Canadian Prairie agro-ecosystem. Mitig. Adapt Strateg. Glob. Change 16: 387-406.

Tarleton M., Ramsey D. 2008. Farm-level Adaptation to Multiple Risks: Climate Change and Other Concerns. Journal of Rural and Community Development 3: 47-63.

USDA NASS – Census of Agriculture. 1970-2012. http://www.agcensus.usda.gov/Publications/2012/Full_Report/Volume_1,_Chapter_1_State_Level/Montana/. Last accessed online January 12, 2015.

Walley FL, Clayton GW, Miller PR, Carr PM, Lafond GP. 2007. Nitrogen economy of pulse crop production in the Northern Great Plains. Agronomy Journal 99:1710–1718.

Weber, E.U. 2006. Experience-Based and Description-Based Perceptions of Long-Term Risk: Why Global Warming Does Not Scare Us (Yet). Climatic Change 77: 103-120.

West, T.O., Post, W.M. Soil Organic Carbon Sequestration Rates by Tillage and Crop Rotation. Soil Science Society of America Journal 66:1930-1946.

Participation Summary

Research Outcomes

No research outcomes

Education and Outreach

Participation Summary:

Education and outreach methods and analyses:

Academic Papers
Lawrence, PG, Maxwell BD, Rew LJ, Miller PM, Ellis, C. In prep, to be submitted April 2015. Vulnerability of Dryland Agricultural Regimes to Economic and Climatic Change. Climatic Change.

Lawrence, PG, Rew LJ, Maxwell BD. 2014. In Press. A Probabilistic Bayesian Framework for Progressively Updating Site-Specific Recommendations. Precision Agriculture.

Conference Presentations
Lawrence, PG, Rew LJ, Maxwell BD. May 4-8, 2014. A Probabilistic Framework for Analyzing Long-term Resilience of Dryland Agroecosystems to Economic and Climatic Change. Poster Presentation. Resilience 2014 Conference, Montpellier, France.

Lawrence, PG, Barroso JB, Maxwell BD, Bekkerman A, Jones C, Rew LJ. August 8, 2012. Effects of agroecological optimization and decision-making on threshold behavior. Poster Presentation. The Ecological Society of America Annual Meeting, Portland, Oregon.

Field day/producer presentations and outreach:
July 12, 2012.  Uncertainty and decision-making for dryland agricultural producers.  Post Farm Agricultural Research Center, Bozeman, MT.

October 24, 2013.  Producer dialogue on decision-making under uncertainty.  Precision Ag Seminar, Great Falls, MT.

The extension webpage, MontGuide, and workshop as mentioned in Objective 6 and 7 are currently under development and will be deployed in Summer 2015.

Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.