The Northern Research Station’s Forest Inventory and Analysis Program (NRS-FIA) collects forest-related data throughout a 24-state region in the northeastern United States, ranging from North Dakota to Maryland and Kansas to Maine. The Wisconsin Department of Natural Resources (DNR) collects hunter harvest information and conducts aerial surveys to model deer populations in the state at the (75) Deer Management Unit (DMU) level. We obtained a GIS layer of the DMU’s with associated levels of deer harvest and deer population estimates for 2000-2008, and combined it with data from 6500 FIA plots where forest vegetation was observed. We compared the relative proportions of overstory (by basal area) and understory (by seedling count) for tree species across the state and found a distinct trend between relative deer population and the presence of selected classes of tree seedlings.

Results/Conclusions

The analysis of seedlings per deer showed the most striking differences between deer densities. Among the high browse-preference category, the 0-5 km^-2 density had approximately 3 times as many seedlings deer^-1 as the next lowest deer density level, 5-10 deer km^-2. This latter level, in turn, had ~10 times as many seedlings deer^-1 as the next deer density, 10-20 deer km^-2. There was a decline in seedlings per deer over time, although not all of the years were significantly different. Medium browse preference also displayed significant differences between deer densities with a sufficient number of plots, although the magnitude of the differences was not as large as with the high-preference species. Here, there were relatively few plots in the 0-5 deer km^-2 density level, but 5-10 deer km^-2 level had significantly more seedlings than 10+ deer km^-2. There was no significant difference over time. Low-moderate preference displayed significantly higher seedlings ha^-1 for the 5-10 deer km^-2 level and generally but not always, significantly lower seedling numbers compared to the 0-5 deer km^-2 level. The seedling numbers in the 5-10 deer km^-2 level did decline significantly over time; none of the other deer density levels showed significant temporal differences. The low-preference category had significantly more seedlings as deer density decreased.  The decline in seedling numbers over time was not statistically significant, however. A concatenation of deer- and non-deer influences masks the impact of deer browse on seedling numbers. We detected a threshold level where deer numbers seemed to have a permanent effect.