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Serving Northern St. Louis County, Minnesota

Three-year deer study set in region

Posted 6/5/24

REGIONAL—The Department of Natural Resources is beginning a new three-year research project in northeastern Minnesota to gather additional data on deer populations. The DNR will place cameras …

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Three-year deer study set in region

Posted

REGIONAL—The Department of Natural Resources is beginning a new three-year research project in northeastern Minnesota to gather additional data on deer populations.
The DNR will place cameras on public and private lands to gather additional deer density data in deer permit areas 169, 176, 177, 178, 197 and 679 in portions of Cass, Beltrami, Itasca, Hubbard and St. Louis counties.
Traditional deer population modeling relies heavily on hunter harvest data. This project will provide additional data to increase confidence in making harvest decisions in the study area. The data will also help managers better understand if deer densities differ between private and public lands, which could potentially be the basis for changing the way antlerless tags are allocated in the future.
“Working with private landowners is an important part of this project,” said lead researcher Eric Michel. “Hunting pressure and land management practices can vary greatly across land ownerships, and we hope to quantify that difference and use this new information to improve our understanding of deer populations in the forested region of the state.”
In June, DNR researchers will contact private landowners by mail in preselected locations to request access to their property to install an unbaited trail camera. Trail cameras will collect time-lapsed data from July to September and be removed before the start of fall hunting seasons. Cameras will be placed in different locations each year to capture data in varying locations. Camera location information derived from private properties will be considered private data.
To assist in processing the massive amounts of data collected with time-lapsed photography, the project will use machine learning and artificial intelligence programs. This technology and methodology were successfully used in prior feasibility studies conducted in 2021 and 2023. Results and final analysis of the data are expected in 2027.