Gamifying Archaeology’s Diet Breadth Model

By Mark Johnston

The Utah Food Festival just celebrated its third year exploring the intersections of food, human history, and science here in Utah. While the festival was anchored by a vibrant market and workshops showcasing Utah’s finest food makers and helping guests expand their palates and culinary skills, it also gave NHMU scientists a chance to share lessons in food history from the region. The challenge was making those lessons fit the model of fun museum learning for which NHMU is famous. 

Shannon Boomgarden, Ph.D., is the director of the Range Creek Field Station, a remote archaeology field station in Utah’s Book Cliffs where she trains University of Utah archaeology students. Every year, the staff and students at Range Creek conduct archaeological surveys of Fremont sites found in the canyon while also conducting experimental farming to better understand how early inhabitants sourced and cultivated food. When considering lessons she might share with Utah Food Festival guests, Boomgarden selected a foundational theoretical model taught to students at the University of Utah and Range Creek: The Diet Breadth Model (Krebs and Davies 1978, Macarther and Pianka 1966). 

What is the Diet Breadth Model? 

Archaeology is often oversimplified and glorified as the excavation of treasures from ancient civilizations, but the discipline is far more involved than one is led to believe through the lens of Hollywood. Today, it is a complex science in which researchers study the behaviors of past individuals to understand how individual decisions accumulated to reflect broader patterning in the archaeological record. Scientists like Boomgarden and her predecessor at Range Creek, Duncan Metcalfe, Ph.D., utilize and even develop theoretical models to standardize their approaches to understanding how the decisions of individuals once influenced life at Range Creek. And scientists often start with fitness-related decisions like food. 

One of these theoretical models is the Diet Breadth Model, a prediction model used to explain how individuals decided which foods to exploit based on efficiency (Krebs and Davies 1978) . In any environment, including that of Range Creek, one can find a range of high-return foods to low-return foods. Archaeologists rank these by the post-encounter return rate of calories gained minus the processing time expended. What does that mean to the rest of us? 

Students process seeds at Range Creek. © NHMU

Picture this: 1,000 years ago, you were a forager roaming a canyon in search of food for you, your family, and your community. Hunger drives you farther into rugged terrain in search of game such as deer, bighorn sheep, or antelope. These animals are appealing for the high calories they provide, but they are not always common on the landscape. So, you must decide how much time to spend hunting them before turning elsewhere. If that time comes, you will look to more commonly found but lower-return protein sources like gophers, rabbits, or plants like pinyon pine nuts, and cattail pollen. Lasty, you might turn to the lowest ranked items like peppergrass seeds, and Indian Rice Grass. The decision of “when” is an important one, a matter of survival, and you’ve likely developed a threshold based on experience, advice from others, and your own hunger! 

In this scenario, one that likely played out countless times in and around Range Creek, foragers will always take a high-return deer or bighorn sheep if they’re lucky enough to find them. It’s equally likely that lower-ranking plant resources — that take considerable time to forage and prepare — were pursued only when the presence of game declined. This is what scientists believe happened in Range Creek Canyon, when stress on animal populations and the ecosystem demanded that diets broaden. 

Bags of Indian Rice Grass in various stages of processing, from freshly picked stems to raw seeds to processed seeds. © NHMU

Using the Diet Breadth Model and other research techniques at Range Creek, Boomgarden and fellow archaeologists have determined that the former Fremont inhabitants relied heavily on corn, a low-return resource. When the canyon was last inhabited, the Fremont planted these domesticated, low-return resources to increase their return rate, allowing them to settle in one place longer, changing the history of their once hunting and gathering civilization. Settlement allowed them greater stability and community, offering more means for defense and food cultivation. This was likely followed by improvement of irrigation technology that would increase food productivity, which Metcalfe, Boomgarden, and their students have been studying in Range Creek (Boomgarden et al. 2019). 

“People who act more optimally have greater success in health, longevity, and raising offspring. Better decisions result in more kids, and those kids are likely to learn the same good habits and make the same optimal decisions and see greater success, which is evident in the archaeological record,” Boomgarden said. 

Play Like an Archaeologist 

How does one turn this complex theoretical model into an engaging museum game? That was the challenge faced by Boomgarden and Jamie Greenland, the Range Creek Lab Manager and Collections Assistant, along with two graduate students who helped on the task. 

“I wanted to teach people how [archaeologists] use models like this to think about the past rather than observing sites and artifacts and simply making up stories about them,” said Boomgarden, while the game design was in progress. 

First, Boomgarden’s team used a list of ranked food sources that might be encountered in Range Creek and the Great Basin in the past (Simms 1987) and divided a small selection of them onto a game wheel with 14 wedges. When selecting the abundance of each resource available, they wanted to make players experience a stressful environment with few high ranked resources. More commonly found foods were listed multiple times, while rare, high-return foods appeared only once or twice. 

Each food source was then assigned a cost, based on the time and energy required to harvest it, and benefit points, based on their caloric value. For example, deer, featured only once given its rarity, comes at a cost of two tickets for the less time and energy required to harvest it, but with a benefit of 100 points. A rabbit shows up twice at a cost of three tickets with a benefit of 75 points. However, a plant like rice grass, while showing up four times, comes at a cost of six tickets and a benefit of just 10 points! This is because rice grass took a lot of time to gather and process before it could be consumed by the Fremont.   

Shannon Boomgarden, Ph.D., tests the Diet Breadth Model game that she and other NHMU archaeologists developed for the Utah Food Festival in May 2026. Photo by Mark Johnston/NHMU

Players have 20 tickets to spend, signifying their total time and energy for foraging and processing food. Every spin of the wheel will demand a decision by the player: whether to harvest the resources they’ve landed on or spend more time and energy seeking other food. However, each turn comes at a cost: one ticket if playing in a wet year when resources are more abundant, or two tickets if playing in a dry year when resources are scarce.   

Those lucky enough to land a deer in their first few spins can harvest it if they didn’t already overspend time and energy elsewhere, like on a low-return grass. Those who do not come upon a high-return food will have to invest their time and energy differently to survive, which requires a minimum of 150 points by the end of the game! But there are twists to the game just like in real life. 

Rice grass seeds in the hand of a student harvesting them at Range Creek. Notice how small the seeds are and imagine how many it would take to feed one person. © NHMU

“Taking low-return rice grass every turn is not necessarily the best strategy because there are not enough calories for you and your family,” Boomgarden said. “When your optimal diet includes low ranked resources, the only way to improve your returns is to improve processing times with innovative techniques and technology.” 

The game helps illustrate the gravity of real-life decisions made by the Fremont, as the outcome for them would have been life or death. Using the Diet Breadth Model to understand these individual decisions helps archaeologists like Boomgarden determine how these former Range Creek inhabitants chose to spend their time and energy. 

Communicating complex science in a fun learning experience is exactly what NHMU aims to do with input from its scientists. This is evident in its many science-based exhibitions and events, including the Utah Food Festival. Guests who had a chance to meet with Boomgarden and her team and play the game came away with a greater appreciation for challenges faced by the hunter gatherers who once inhabited this region. Players were also encouraged to develop their own Diet Breadth Model to improve efficiency in selecting and harvesting food of their own, whether in the vegetable rows of a garden or the well-stocked aisles of a grocery store. 

Boomgarden, S., D. Metcalfe, and E. Simons (2019) An Optimal Irrigation Model: Theory, Experimental Results, and Implications for Future Research, American Antiquity 84(2), 252-273. 

Krebs, J. and N. Davies (1978) Behavioral Ecology: An Evolutionary Approach. Blackwell, Oxford. 

MacArthur, R. H., and E. R. Pianka. 1966. On the optimal use of a patchy environment. American Naturalist 100:603–609 

Simms, S. (1987) Behavioral Ecology and Hunter-Gatherer Foraging: An Example from the Great Basin. PhD Dissertation, B.A.R., Oxford.