Our recurring series of op-eds is aimed at sharing the diversity of voices in the food movement, from chefs to diners to farmers and beyond. Our most recent entry comes from Holland Dougherty, one of the first class of JBF National Scholars, who is completing a doctoral degree in agriculture at University of California, Davis, specializing in animal studies. Below, Holland shares her motivation for studying sustainable agriculture, and how big data can help farmers build a better food future for themselves and the nation.
My route to animal science and sustainability research started not just with a love of animals, but also with a love of food: specifically, sustainable, safe, and healthy food. I grew up with a sister who has celiac disease, and was eventually diagnosed with it myself. This meant I was always aware of just how hard it is to eat safely with medical needs, and how often people take their ability to eat whatever they want for granted. Even when gluten-free diets became more visible, it was still viewed as more of a fad than a medically necessary diet that needed to be taken seriously. And to make matters worse, gluten-free foods are expensive, often in the realm of $8 loaves of bread and $5 boxes of pasta, prices out of reach for many of the people who need those foods the most. Not only is this current model not fair, it’s not sustainable: once the gluten-free fad fades, where does that leave people with celiac?
Sustainable agriculture has experienced a similar rise in public awareness, and it’s equally important that this focus is not just a blip on the cultural radar. People have become increasingly interested in where their food comes from and what its production means for the environment, but in all likelihood don’t yet know what is needed to make a food system sustainable in the long run.
On my own animal science blog, my motto is “for a revolution to be truly sustainable, it must be accessible to everyone.” This is especially important for agriculture: if we as a culture are serious about sustainable agriculture, it needs to be produced in such a way that farmers are able to survive economically, but without pricing the average consumer out of the market. One of the best means of achieving that is through creating a wider understanding of what sustainability really means.
The USDA defines sustainable agriculture as “an integrated system of plant and animal production practices … that will, over the long term: (1) satisfy human food and fiber needs; (2) enhance environmental quality and the natural resource base upon which the agricultural economy depends; (3) make the most efficient use of nonrenewable resources and on-farm resources and integrate, where appropriate, natural biological cycles and controls; (4) sustain the economic viability of farm operations; and (5) enhance the quality of life for farmers and society as a whole."
In other words, sustainable agriculture works to feed the current population, while ensuring that future generations benefit from a stable food supply and a healthy environment. This is what I love about my work: that by helping producers make their farms and ranches more economically and environmentally efficient, I’m helping to ensure that everyone will be able to eat well for years to come.
Modeling is one of the most exciting tools in sustainability research, because it allows us to combine large amounts of data from many different sources to look at the bigger picture. Whether I’m looking at how different feeds might affect cow digestion (and therefore how much greenhouse gas they emit) or if I’m trying to track the environmental impact of producing one pound of lamb by accounting for every required input, modeling allows me get an in-depth picture of how biology and agriculture fit together.
For sustainability research, that view must include not only what we feed cows and how that affects the gases they produce, but also the large-scale impacts of producing cows, like the costs of transportation, slaughter, and butchery. Modeling allows me to estimate how a change in livestock management at one step in the production cycle affects the others, and ultimately how all it all comes together to result in different environmental costs. Combining computing power with my knowledge of biology to understand what makes a system truly sustainable, and using that understanding to help producers make better management decisions, is one of the most exciting things about the work I do.
Modeling can also help us tailor solutions to a particular environment. The various climate conditions across the country support many different types of agriculture, and regional models tailored to a specific set of conditions allow us to look at environmental impacts on a local level. For example, sheep and cattle production on native rangelands in the western United States is not only important to meat production overall, it is also important for managing these specific ecosystems. Models of the interactions between animals, plants, and the soil allow us not only to understand the combination of the many moving parts that create the modern food system, but also to help producers find the best strategies to protect the long-term health and economic and environmental sustainability of their farms.
I’ve always been someone who likes to knit pieces of information together to see the big picture, and that’s why I love using modeling to help make agriculture more sustainable. As researchers collect and analyze larger amounts of data using computer models, our ability to see what’s happening and to use what we find to help people keeps growing. By using modeling to improve both the economic and environmental aspects of production, we ensure a stable, sustainable food supply that benefits everyone.
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Holland Doughtery is a doctoral candidate at U.C. Davis, studying sustainable agriculture modeling. Find out more about her research here.
