For 2020 to 2024, registered deer harvest for each square mile generally increased with forest cover across 462 counties spanning Iowa, Missouri, Wisconsin, Illinois and Ohio. Iowa showed the sharpest relationship: its highest-forest county quarter averaged 3.82 deer registrations for each square mile, compared with 0.55 for its lowest-forest quarter. Wisconsin showed the weakest relationship, with corresponding averages of 6.93 and 5.44. These figures count deer registered by hunters. Hunting effort and access therefore shape them alongside deer numbers. They show how counties compare but do not explain the pattern.
KEY FINDINGS
- In Iowa, the county quarter with the greatest forest share recorded 3.82 deer registrations for each square mile, compared with 0.55 in the quarter with the smallest share. The ratio was 7.0x.
- Ordering counties by forest share produces almost the same ranking as ordering them by harvest density in Iowa (+0.92), with Illinois (+0.86) and Ohio (+0.76) also closely aligned. Missouri's rankings align less closely (+0.52), while Wisconsin's show little agreement (+0.29).
- At 5.44 deer registrations for each square mile, Wisconsin's lowest-forest county quarter exceeded the highest-forest quarters of Iowa (3.82), Illinois (4.70) and Missouri (4.75).
- The 15 counties leading in registered harvest density include eight from Ohio and seven from Wisconsin. Wisconsin's Marquette leads the group with 15.15.
IPlain terms
How we use "per square mile"
We calculate county harvest density by dividing the deer hunters registered there by its mapped size in square miles. This area adjustment lets counties of different sizes share a common scale; an unadjusted county count cannot provide that comparison. We used the average for seasons spanning 2020 to 2024 to keep an unusual year from determining a county's score. County areas came from county summaries in the USDA Cropland Data Layer. Those mapped areas include rivers and inland lakes, which makes a county's result somewhat low when large lakes occupy it. This source also supplies the fraction of county land classified as evergreen, deciduous or mixed forest, along with the fraction planted in soybeans and corn.
IIIowa
Seven times as much harvest for each square mile in timber
The relationship is clearest in Iowa. Sorting its 99 counties by their forest fraction gives almost the same ranking as sorting them by area-adjusted harvest. The rank correlation is +0.92. Sorting by the fraction in soybeans and corn nearly reverses that harvest ranking, with a correlation of -0.90. Grouping counties into quarters according to forest share reveals a large difference. In the lowest-forest group, forest cover averaged 1.0%, and hunters registered 0.55 deer for each square mile. In the highest-forest group, the forest average was 21.1%, and registered harvest was 3.82. The resulting ratio is 7.0x.
Even a county in Iowa's "most-forested" quarter has relatively little woodland. Forest covers an average of 21.1% in that group, compared with 34.7% in Illinois's most-forested quarter and 47.9% in Wisconsin's. The 7.0x ratio also owes part of its size to Iowa's low bottom group. Iowa's least-forested quarter records fewer registered deer per square mile than the same quarter in every other state examined here. At 3.82, Iowa's most-forested quarter also has the lowest result among the five states' top quarters. This contrast agrees with our earlier analysis of The Two Iowas, which showed deer harvest clustered heavily in the northeast's woods and river country, with much less harvest across the northwest's corn and soybean country.
IIIIllinois, Ohio, Missouri
Similar relationships with narrower differences
After Iowa comes Illinois, with a 3.7x ratio: registered harvest for each square mile rises from 1.28 in the lowest-forest county quarter to 4.70 in the highest-forest quarter. Ohio follows with 2.7x (2.66 to 7.15), and Missouri follows Ohio with 1.8x (2.68 to 4.75).
Rank correlation measures how closely counties' positions match in separate rankings. A large positive result means the counties richest in forest and those highest in area-adjusted harvest appear in nearly the same sequence. When the result is close to zero, knowing a county's forest rank tells little about its harvest rank.
Missouri illustrates how both ends of the comparison affect the ratio. Forest cover averages 69.3% in its highest-forest county quarter, much more than Iowa's 21.1%. Even so, Missouri's ratio reaches only 1.8x. Its lowest-forest quarter already records 2.68 deer registrations for each square mile, despite having 12.1% forest cover.
Swipe table to see every column
| State | Counties | Forest vs harvest/sq mi (rank corr.) | Corn+soy vs harvest/sq mi | Least-forested quarter, deer/sq mi | Most-forested quarter, deer/sq mi | Ratio |
|---|---|---|---|---|---|---|
| Iowa | 99 | +0.92 | -0.90 | 0.55 | 3.82 | 7.0x |
| Illinois | 102 | +0.86 | -0.57 | 1.28 | 4.70 | 3.7x |
| Missouri | 113 | +0.52 | -0.31 | 2.68 | 4.75 | 1.8x |
| Ohio | 88 | +0.76 | -0.62 | 2.66 | 7.15 | 2.7x |
| Wisconsin | 60 | +0.29 | -0.14 | 5.44 | 6.93 | 1.3x |
IVWisconsin
Where the relationship levels off
For Wisconsin, the correlation between county forest rank and area-adjusted harvest is just +0.29. Ranking by the share in soybeans and corn yields -0.14. Among its 60 counties, the highest-forest quarter averaged 47.9% forest cover and 6.93 deer registrations for each square mile. The lowest-forest quarter averaged 6.6% forest and recorded 5.44. The ratio is 1.3x. Even that smaller harvest figure exceeds the highest-forest quarter's result in each of Iowa, Missouri and Illinois.
The leading counties include both types of country. Green Lake has 9% forest and 31% corn and soy cover. At 11.13, it ranks seventh among all 462 counties. Vernon has 46% forest and 17% corn and soy cover and ranks eleventh at 10.62. In each type of country, hunters registered a large number of deer for every square mile.
These data cannot explain Wisconsin's different pattern. Rules for tags offer a possible explanation. The Density Paradox discusses generous antlerless-tag allowances, often without a limit, in Wisconsin's southern farmland zone. This analysis did not test that possibility.
VTop of the list
All fifteen leaders come from Ohio and Wisconsin
Swipe table to see every column
| Rank | County | Deer harvested per sq mi (2020 to 2024 avg) | Forest share | Corn + soy share |
|---|---|---|---|---|
| 1 | Marquette, WI | 15.15 | 27% | 19% |
| 2 | Coshocton, OH | 13.20 | 58% | 12% |
| 3 | Waupaca, WI | 12.93 | 23% | 20% |
| 4 | Holmes, OH | 12.23 | 40% | 14% |
| 5 | Carroll, OH | 12.02 | 56% | 7% |
| 6 | Tuscarawas, OH | 11.86 | 54% | 9% |
| 7 | Green Lake, WI | 11.13 | 9% | 31% |
| 8 | Waushara, WI | 11.08 | 31% | 17% |
| 9 | Shawano, WI | 10.74 | 23% | 21% |
| 10 | Knox, OH | 10.71 | 34% | 33% |
| 11 | Vernon, WI | 10.62 | 46% | 17% |
| 12 | Harrison, OH | 9.89 | 62% | 2% |
| 13 | Guernsey, OH | 9.83 | 64% | 2% |
| 14 | Richland, WI | 9.51 | 51% | 16% |
| 15 | Ashland, OH | 9.42 | 33% | 33% |
Ohio accounts for eight of the 15 counties leading in registered harvest density; Wisconsin accounts for seven. Iowa, Missouri and Illinois have no counties on that list. Wisconsin's Marquette takes the lead with 15.15, with forest covering 27% and soybeans and corn covering 19%. Ohio's Coshocton follows at 13.20. Five members of Ohio's eight-county group have forest on more than half their area: Coshocton has 58%, Carroll has 56%, Tuscarawas has 54%, Harrison has 62% and Guernsey has 64%. Among the seven Wisconsin counties, Richland alone exceeds half, with 51% forest.
VIMethod and limits
What these results can tell us and what they cannot
We used county deer registrations reported by each state's wildlife agency and averaged the harvests for 2020 to 2024. Iowa contributes 99 counties; Illinois, 102; Missouri, 113; Ohio, 88; and Wisconsin, 60. Area-adjusted harvest depends on hunting effort and access alongside the number of deer. It does not estimate the deer population. A large result tells us only that hunters registered a large number of deer for each square mile.
Within each state, we compare the quarter of counties having the smallest forest share with the quarter having the largest. Each comparison therefore stays within that state. We calculate ratios using county averages before rounding. Dividing the rounded values shown in the table can therefore produce a result a tenth different from the displayed ratio.
A county-level correlation identifies a relationship between two measurements, but it cannot establish that forest explains deer harvest. Counties with a larger share of forest generally have a smaller share of cropland. These data therefore cannot distinguish the relationship with "more forest" from the relationship with "less crop." We did not measure how many hunters were present or their access to land. Either could vary with land cover.
VIIIn the field
A useful starting filter in some states
Start county screening with forest share in Iowa, Illinois and Ohio. Its correlations with area-adjusted harvest are +0.92, +0.86 and +0.76, respectively. In those states, counties with greater forest cover have generally recorded more deer registrations for each square mile. Give this filter less weight in Missouri (+0.52). For Wisconsin (+0.29), leave it aside and use past harvest and access to compare counties.
After narrowing your choices, check the records behind each county's reputation before trusting it. Buying Deer Ground demonstrates that approach for people buying land. To see whether a state's leader in total deer harvest also leads after adjusting for area, turn to The County That Kills the Most Deer Isn't Always Top per Square Mile. It applies this same harvest measure for each square mile.
NOTES AND SOURCES
- Data source: county-level summaries from the USDA NASS Cropland Data Layer, obtained through our pipeline.
- Data source: county deer registrations reported by wildlife agencies in IA, IL, MO, OH and WI.
- Area-adjusted harvest depends on hunting effort, access and deer numbers. It does not estimate the deer population.
- A relationship between counties' measurements cannot establish that forest causes their harvest.
- The weak Wisconsin relationship is a result in its own right. Deer live in both its largely wooded north and its largely agricultural south.
Fully Drawn Research is an independent data analysis desk, not affiliated with any state wildlife agency, transportation agency, mapping provider or outfitter. Fully Drawn Research is an independent data and analysis desk. This paper reports FDR's analysis of public agency data. Harvest figures describe animals reported or estimated as harvested, not population size, and reflect hunter effort and regulations as well as animal numbers.
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