How Wisconsin Used Foxes And Deer To Revamp Science Education

More than 100 million trail camera photos of Wisconsin’s foxes, deer, and other wildlife—submitted by the public—are reshaping both science classrooms and state wildlife management. The unprecedented trove of citizen-sourced images gives students real-world data to analyze while helping biologists track animal populations with a precision never before possible.

Wisconsin’s Department of Natural Resources (DNR) launched the Snapshot Wisconsin project in 2016, enlisting volunteers to deploy trail cameras across the state. By 2026, the effort had accumulated over 100 million photos, making it one of the largest citizen-science camera-trap datasets in the world. The initiative didn’t just generate data—it fundamentally altered how the state teaches science and manages its fauna.

The project grew out of a need to monitor Wisconsin’s white-tailed deer population, which has economic and ecological significance. Traditional methods like aerial surveys and field counts are expensive and imprecise. Trail cameras, deployed by thousands of volunteers, capture animals in their natural habitats year-round. Each photo is tagged by volunteers through a web portal, with species identifications verified by DNR staff. The resulting dataset allows biologists to estimate population densities, track seasonal movements, and even spot rare species.

But the real transformation is in education. Schools across Wisconsin now integrate the photos into K-12 science curricula. Students analyze real data to learn about population ecology, habitat use, and the scientific method. The program has reached over 1,000 schools and 200,000 students, providing hands-on experience with big data and computational thinking. Teachers report higher engagement because students work with authentic, local content.

Key figures include Wisconsin DNR wildlife ecologist Dr. Jennifer Stenglein, who oversees the project’s biological analysis, and education coordinator Jessica Stubenbordt, who develops classroom materials. The Snapshot Wisconsin website allows anyone to classify photos, turning citizens into data contributors. Over 30,000 registered volunteers have contributed classifications, with accuracy rates exceeding 95% for common species.

The implications extend beyond Wisconsin. The model demonstrates how citizen science can simultaneously advance research and education at scale. Other states and countries have inquired about replicating the framework. The project also feeds into larger initiatives like eMammal, a global camera-trap database. By making data accessible and engaging, Snapshot Wisconsin proves that conservation and classroom innovation are not competing priorities.

Looking ahead, the DNR plans to expand the camera network to monitor additional species, including bears and bobcats. Machine learning algorithms are being developed to automate species identification, freeing up human volunteers for more complex tasks. Meanwhile, the educational arm is creating new modules on climate change and habitat fragmentation. If the model continues to succeed, expect more states to adopt similar programs—turning every trail camera into a learning tool.