The number of very small farms (<10 acres) is increasing and beginning farmers (in practice for <10 years) are more likely to run them. Very small farms are typically complex systems in which the farmer manages both production of a diverse array of crops and marketing of crops directly to consumers and their failure rate in early years is high. This work seeks to increase the likelihood of success for beginning farmers by understanding these complex systems better. We collected qualitative and quantitative data from interviews with three successful beginning farm operations in Southwest Virginia covering practical and philosophical aspects of farm production, sales and management. We mapped social, environmental and economic aspects of farming systems and studied how farmers use resources (Community Capitals) and management to enhance their system's success, developing a broader definition of success that encompasses what farmers gain from farming beyond profitability. Using these maps, we created a system dynamics model of a small farm system in STELLA including unique components such as customer attraction and retention. Through model development, we learned that these successful farmers began their operations with experience and financial resources, and employed their skills, resourcefulness and cultural and social capital to charge prices for their products that could sustain their operations financially. Using our model, current and aspiring farmers, service providers, and small farm advocates will be able to simulate real or hypothetical farm systems to better understand what establishing a successful small farm might require and how to confront potential challenges. / Master of Science

The United States is facing a rising average age of principal farm operators and a decline in number of beginning farmers. With numerous barriers and challenges resulting in many farm failures, a majority of beginning farmers are relying on off-farm income to support their households. Decision-making and farm business planning are difficult skills to develop and improve, and the ability to develop a plan to balance on- and off-farm labor could allow farmers to make more profitable decisions. In this study, a General Algebraic Modeling System (GAMS) is used to develop a labor management planning framework for use by Virginia's beginning vegetable farmers or service providers, such as extension agents, with the goal of improving total (on- and off-farm) profitability and farm viability. Study findings suggest that a willingness to work of 12 hours per day, 365 days per year and hired labor costs of $9.30 per hour, which is the national average for agricultural workers encourage a farmer to maintain an off-farm job, while a relatively lower off-farm wage or salary may encourage a farmer to work on the farm only. Lastly, higher hired labor costs may encourage a farmer to pursue his or her most profitable work opportunity, be it on- or off-farm, without hiring labor to maintain the farm. The model developed in this study may be used to plan multiple years of farm management to include anticipated changes in off-farm employment opportunities, land availability, product mix, and access to farm labor. The author suggests that beginning farmers who use this planning tool are able to make more informed decisions related to allocation of labor time and resources, resulting in lower failure rates for beginning farmers in Virginia. A user-friendly interface may be developed based on the study framework, to strengthen the results and increase the practicality of the tool. / Master of Science