Deer Statistics

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Forest Regeneration

While not always realized, light to moderate deer browsing can increase forest biodiversity and provide positive benefits to forest health. However, if browsing is greater than what a forest can withstand, not only can the future forest regeneration become compromised, but available browse for future generations of deer can become depleted and can decrease the overall deer carrying-capacity of the forest. It is important to have an estimate of the abundance of tree seedlings (<1” dia.), small saplings (1-2” dia.), large saplings (2 - 5”) and pole-size trees (5 – 11”) across the region. These size classes are important as they are the size classes available to deer and other wildlife as browse. For foresters and forest managers, these size classes also provide important clues about future forest composition, quantity, quality, and value. For additional Information….

Background

To understand if the forest regeneration is becoming compromised, foresters will use the abundance of stems per acre, or in other words “stem density.” Stem density becomes even more valuable when analyzed by size class. When data are available, it is important to track the stem density of early-aged trees through time. These types of data provided valuable context for what has happened in the past and provides an understanding of what stem density is possible. The data provided in this report focuses specifically on important tree species for deer. While some may debate on the cause of changes in stem density or “availability” of these species, at the end of the day it is the availability that dictates the deer carry capacity of our forests and furthermore, the ability of our forests to sustain forest products and habitat for all other wildlife species.

Collection and analysis methods

The forest regeneration data presented here came from the U.S. Forest Service’s Forest Inventory Analysis (FIA). Fixed plots are spaced approximately every 2,000 acres across the U.S. on both public and private land. It is important to note that some of these plots fall on non-forested lands. For the purposes of this analysis, we only utilized forested FIA plots. Each plot is inventoried every five years, to provide valuable insight into how our forests are changing through time. We selected the years 1983, 1996, 2004, 2009 and 2015 to illustrate the change in our forests over time. We have further divided the data into the nine regions that span the state of Wisconsin, per the deer management zones. Providing data at a county level is not appropriate when only utilizing FIA as the sample size is too small.

The FIA dataset was used to provide density data for important tree species across Wisconsin that are highly palatable to deer and have the potential to be over browsed. Furthermore, we only focus on size classes between 1” and 9”. We provide data on tree seedlings between 0.01”-1” only for the 2004, 2009, and 2015 data collection periods because FIA did not collect these data during the 1983 and 1996 data collection periods. Size classes above 9” were not considered vulnerable to deer because of their height, nor do these size classes typically provide an abundance of deer browse. The tree species density is calculated using the entire forested area of a single deer management zone. It is important to note that while some of these densities appear to be low, it is because the calculation is based on entire forested zone area and we are only selecting certain species and certain size classes that are of importance to deer.

Using the metric

These data illustrate the direction of our future forests across each of Wisconsin’s nine deer management zones. The stem density by species provides an overview of what is available in each region. On this page, we provide data dating back to 1983, as well as, multiple intervals until the latest 2015 data. Those using this page should use these figures to understand how forest species are changing through time for a respective deer management zone. While changes in climate (e.g. long-term drought), and forest management can play significant factors in altering the abundance of certain species, we have tried to specifically select tree species that are highly susceptible to deer browse. Numerous deer browse studies have shown that Eastern hemlock and Northern white-cedar are not only the preferred deer browse for northern regions of Wisconsin, but necessary components of a winter diet. To contrast, we specifically did not include balsam fir, as this species while abundant for winter browse, will not provide a sufficient diet to solely sustain white-tailed deer during winter. Studies have shown that white-tailed deer will die when only balsam fir is available.

Limitations and precautions

One of the limitations to all scientific data is the number of plots used to collect data. The number of plots used to compile and calculate the data illustrated in the deer management zone graphs is available upon request. This analysis specifically did not use “browse indices” as part of our analyzed dataset. This is because there are no long-term data on deer browse, which means we would not be able to compare current day browsing rates to historical browsing rates. Secondly, the methodology of deer browse metrics is still being debated. As of today, only “current-year” deer browse is assessed, which can be challenging to measure and may often under-estimate the true amount of browsing. Finally, in some areas in which regeneration has failed, either due to over-browsing, climate or soil conditions, no stems are available to browse, thereby producing a result of “no browsing” and creating a false sense of assurance that our forests are in a healthy state. It is our desire to further refine the deer browse metric through time to provide CDACs with a thorough set of forest metrics in the future.

Future needs

These FIA data provide a good overview of each region’s tree species density. Increasing the amount of sampling plots in the future would provide a better spatial resolution, if desired. Furthermore, if enough plots were created per county, we could provide similar data on a county-level basis, verses a regional level. By partnering with county forests and industrial forests in the future, we may be able to secure these needed data and provide county-level forecasts.

While our data has the ability to show what species density was and currently is, what we don’t know are the critical tipping points for needed changes in management. For example, if we don’t have a sapling size class for Eastern hemlock, what are the long-term consequences? What is the number of hemlocks per acre needed to sustain a specific number of deer through a severe winter? At what density of hemlocks should we worry about long-term regeneration failure? These are the bigger questions that we need answers for. Answers to these types of questions will only be answered with further scientific research.

Additional background materials related to this metric

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The following reports summarize the overall risk deer currently pose to forest regeneration by county. These reports are the first attempt to summarize and communicate these data in a manner that is useful to CDAC members.