At Michigan Public, I produced this data visualization to accompany a collaborative reporting project on deer overabundance .
I developed the methodology in collaboration with my editor, Adam Yahya Reyes.

What's the best way to measure and visualize deer overabundance?

Experts emphasized that (a) deer population estimates are usually inaccurate and (b) there’s pre-determined level of deer that is “too many.”

The biggest indicator of overabundance is when deer populations clash with humans — eating crops and colliding with cars.

I mapped deer-vehicle collision rates so that readers could understand what overabundance might mean in their community.

Working at the county level, I took the three-year average of deer-crash data from the U-M Transportation Research Institute (after consulting with an expert there). I then divided the crash data by the three-year average of traffic data from Michigan DOT to control the comparison for road use.

To determine change over time, I did the same calculation for a three-year average from a decade prior, and compared the two results.

Finally, I did the same analysis at the regional level and found that the southwestern coast had seen a particularly large increase in collisions.