Wisconsin Natural Resources magazine

Wisconsin Natural Resources magazine

The details collected from successful hunters help form the herd estimate. © Robert Queen

The details collected from successful hunters help form the herd estimate.
© Robert Queen

October 2009

Sizing up the herd

It takes ground tracking, aerial surveys, statistical know-how, and the stubs from more than 600,000 deer hunters to estimate the herd population after the hunting season.

Keith Warnke

Even though my hunting partners are long-time deer hunters, more than once they've asked how DNR wildlife biologists count deer. If that question keeps coming from my deer camp, I know a lot of others have the same question, especially in years like last hunting season when the number of deer that hunters saw dropped off. My first answer is, "Generally, DNR does not count deer, but we do make a population estimate."

That estimate of the pre-season deer population is a bit confusing because it can only be accurately calculated in hindsight by collecting information during the hunt and compiling it after the season. It's a bit like the college basketball season that starts with a lot of unknowns such as how good the recruiting class is (or fawn survival). There are pre-season rankings and predictions. Then the season takes place, the results are tallied and a much clearer picture of the team ranking (or population) emerges.

While the Sex-Age-Kill (SAK) calculation has used the same factors since the 1960s with some modifications, there are misconceptions about how the agency arrives at its annual population estimates. In most areas of the state, "the count" is made by compiling and analyzing the mandatory stubs provided by hunters registering each deer harvested in each Deer Management Unit (DMU). The stub tells the location and sex of each deer harvested and an age is determined for a representative sample of the registered deer. This data is combined with information gathered during field studies to calculate an estimate of what the deer population was like when the hunting season began.

Since the early 1960s, the DNR has used a statistical formula called the SAK model to estimate, not count, Wisconsin's deer population. Information from hunter harvests is the foundation for making this estimate. There is no way to duplicate the details about the deer herd that more than 600,000 hunters help us capture each year, and the SAK method capitalizes on this power. The specifics that hunters provide when registering their deer are the most important parts of the deer population estimate.

SAK incorporates the registered buck harvest and other data collected by hunters and field biologists using a series of equations developed with decades of sound population data to estimate the size and makeup of the buck, doe and fawn populations as they were prior to the hunting season.

SAK in detail

Let's look at the SAK method in more detail. There are several parts to the SAK model: the buck harvest, the buck harvest rate, the age structure of bucks and does harvested (the adult sex ratio), and the fall fawn-to-doe ratio.

The buck harvest is the combined registered buck kill from all seasons and includes bucks taken using damage permits. In Wisconsin, this harvest data comes from the registration stubs hunters have provided since 1953. At registration stations, DNR staff and volunteers age a representative sample of deer brought in by hunters – more than 20,000 animals are aged each year. These data are critical for accurately estimating the buck harvest rate and the adult buck-to-doe ratio.

The buck harvest rate relies heavily on the data collected by aging bucks harvested statewide and on past research gauging the proportion of all bucks taken during legal hunting seasons. In heavily hunted populations, about 90 percent of buck mortality is due to legal harvest. In more lightly hunted populations, the legal harvest may account for only 60 percent of buck mortality. The buck harvest rate is generally higher in the southern farmland areas of Wisconsin where the deer range is more fragmented and hunter densities are higher than in the extensive northern forests, although this has been changing recently.

The adult sex ratio of adult does to bucks in the fall population is estimated by measuring the proportion of yearling does to yearling bucks from the harvest data. This is another factor that relies on the information we gather when aging deer at the registration stations. The comparisons year to year show that does live much longer than bucks.

Let me show how this factor is used. Hypothetically, if buck and doe fawns were born in approximately equal numbers and if bucks were to die about twice as fast as does do, then the proportion of yearling does in the harvest would be about twice that of yearling bucks. In this example, the adult sex ratio would be about 2:1 – two does per buck. In reality, there are between 1.2 and 2.3 adult does for every adult buck (at the start of the hunting season). Generally, there are more does per buck in southern Wisconsin where hunting pressure on bucks is higher.

The fall fawn-to-doe ratio is created by data collected by department staff and volunteers who keep records of deer observations from July through September. Biologists, foresters and many other volunteers record the number and type of deer they see and the DMU (management unit) in which the observation was made. The compiled data are used to estimate the yearly fawn production per doe around the state. That number is multiplied by the number of adult does to estimate the fawn population.

Essentially the number of bucks in the herd is estimated by dividing the number killed during the hunting season by the harvest rate. The doe estimate is made by multiplying the number of bucks harvested during the deer season by the ratio of adult does to adult bucks. The number of fawns is judged by multiplying this doe estimate by the fawn-to-doe ratio. Adding these three totals together provides an estimate of the deer population on the landscape before the hunting season opened.

To estimate the number of deer remaining after the hunting season, the total harvest is multiplied by 1.15 (to account for 15% of the population that we estimate may die from wounds or poaching mortality). That total is subtracted from the pre-hunt population to form a post-hunt population estimate. Those post-hunt estimates are built into the overwinter goals for the herd.

What SAK can and can not do

SAK is a time-tested model that has been independently reviewed for reliability and precision several times. According to outside experts, the amount of data collected and the way SAK is used make Wisconsin's deer population estimate one of the best in the nation. The SAK uses harvest information from hunters to estimate the deer population at two points:

  1. pre-hunt (September 15) and
  2. post-hunt (February 1)

The information used to form the SAK is robust because it is re-calculated every year from data collected when deer are harvested by more than 600,000 hunters. However, this model does have limits. SAK is not designed to predict how many deer will be in Wisconsin woods and fields before the fall hunting season begins. The harvest data can only be used to estimate the pre-hunt deer population in hindsight.

Long-term averages of historical data are used to estimate how deer herds change between February and September. Indices like the Winter Severity Index estimate how well the herd survives under various winter conditions. These averages are applied to project what may be expected to happen in any given year. Predicting the fall status of the herd is less accurate since these predictions are based on historic data on herd growth and are influenced by many factors, including winter weather and spring weather conditions that affect fawn survival.

For those of you who are a bit more interested in mathematics and statistics, we'll delve into the SAK a bit deeper. The precision of SAK decreases as the sample size decreases. So the population estimates are much more precise and accurate for larger Deer Management Units covering a larger area. The SAK cannot estimate the deer population on a single parcel of property. This can be frustrating to hunters as the average deer density calculated by SAK for a whole management unit is not likely to be reflected in what they see right under their treestands. Deer are not distributed evenly across the landscape and their travel patterns change with time.

SAK also does not directly estimate the impact of predators on deer populations. However, since the estimate is valid immediately prior to the hunting season, the impact of predation is accounted for in the population estimates.

Hunt by observing deer habits and patterns

Deer will largely stay put and stick to a small area of land following a daily pattern in moving from bedding areas to feeding areas to resting areas. To see the highest number of deer, hunters are best served to either set up along established deer trails or take actions to make the deer move. Changes in land ownership, access to hunting lands and hunting methods have definitely changed deer habits. Large family farms are being divided into smaller parcels. Smaller parcels make deer drives more difficult as hunters need to establish relationships with more landowners to get permission to hunt. Smaller parcels of land also usually mean more fences and more scattered development that can change deer movements.

Winter aerial surveys

In winter, one way to picture the deer population is to view it from above. Trees are leaf-free and on a sunny day with decent snow cover (four to six inches), teams of two observers and a pilot flying low and slow over farmland, wetlands and woods can get close enough to count deer on the landscape.

Helicopter surveys are flown either north-south or east-west, depending on winds, following a patterned transect at about 100 feet above the ground at 30-35 mph. Observers monitor the view on each side of the chopper and mark deer locations on aerial maps. If deer are running near the edge of a transect, they are not counted on a second sweep to avoid double counts. Transects are flown until all portions of the section of land have been surveyed. About 430 sections of land are surveyed in a typical winter.

Aerial winter surveys are also conducted in fixed-wing airplanes. Pilots follow an east-west tract across the length of a deer management unit. Each transect is spaced two miles apart at a height that allows observations within a quarter-mile of the flight path. Observers can search for deer within about 200 yards of each side of the route. In the last five years aerial surveys have concentrated on the Herd Reduction Zone in southern Wisconsin and about 16 Deer Management Units a year have been surveyed covering nearly 3,600 air miles.

Changing hunting methods also change the patterns and habits of the deer herd. Hunting from a treestand was legalized in the early 1970s and quickly became a favored method. Both hunters and deer are staying put. Deer are less likely to move and be seen as fewer drives are occurring. In addition, baiting and feeding for deer reduces deer movement and increases night feeding after hunting hours close for the day. If you are not seeing deer, here are some tips you can try that might increase your chances:

  • Still hunt for a while.
  • Organize deer drives – make sure you take extra safety precautions and know where all the hunters in your party are located.
  • Encourage other hunters to stop baiting in the area you are hunting.
  • Scout hunting areas before the season to find locations deer are frequenting. Just like fishing, if the fish aren't biting in one spot, it's often best to move to another spot.

Hunting restrictions that strongly influence the buck harvest rate can also cause biases in SAK estimates. For this reason, SAK is not used in management units with Earn-A-Buck seasons where hunters must first harvest a doe before shooting at bucks.

SAK scrutiny

SAK estimates of Wisconsin's deer population hold up well when compared to the results from other methods such as helicopter counts, pellet surveys, road-kill trends, deer trail surveys, and buck harvest trends. Several independent groups have reviewed and audited the SAK model. As recently as 2006, an independent panel of nationally recognized experts in deer population monitoring and biometrics audited Wisconsin's SAK method. The audit panel used a combination of computer simulations, literature review, and surveys by other states to better understand both the utility and credibility of the SAK model. The audit panel determined "Wisconsin has the most comprehensive and transparent deer management program for comparable states that harvest white-tailed deer." The audit panel concluded the model does reasonably well at retroactively estimating deer abundance immediately before the hunting season at the statewide level. The panel also concluded SAK allows for an extensive population assessment in contrast to more expensive and intensive procedures. The audit panel also recommended potential improvements that DNR wildlife managers are working to implement where feasible.

The panel recommended continuing to use five-year averages for yearling buck and doe percentages. The panel also recommended reporting deer population estimates as both the number of deer in a DMU and the deer density per square mile of deer range in each DMU. Both recommendations were implemented.

Strengthening deer population estimates

Improving the quality and quantity of data used to make deer population estimates is always a work in progress. Our deer management program is also exploring opportunities to take full advantage of field observations by hunters, landowners and other citizens to better monitor the herd. One option is expanding the circle of partners and volunteers who provide summer fawn/doe observations.

Increasing the number of deer we can age at harvest time would also improve the estimate's precision as would combining DMUs to form fewer but larger Deer Management Units, as recommended by the 2006 SAK audit panel.

Starting this year, the DNR wildlife team will collect more information from successful hunters on deer registration stubs to strengthen our information about the herd. Hunters will be asked how many deer they observed on the day their deer was harvested, the number of hours they hunted on the day of harvest, hunting weather conditions and buck/doe/fawn identification. In addition to the deer stub, we're starting an online survey where hunters can record their daily sightings each time they hunt.

How can you help? If you hunt and harvest a deer, please fill out the registration stub carefully and completely. As you can appreciate, accurate information is key to improving our understanding and management of the deer herd. We also believe new information collected this year will help provide an index of deer sightings per hour of hunting. After collecting this information for a period of years, we hope to develop an index that tracks deer population estimates and harvest. On those days when you hunt but don't harvest a deer, please take the time to log onto our website and complete the survey. The more you tell us about your hunting experiences, the more we will be able to build an index from hunter-collected data.

Sustaining Wisconsin's deer population is very important to our hunting tradition and our state's economy. Even if you don't hunt, deer influence your home, your business, your recreation and your travel. Dependable deer population estimates are important for proper deer herd management. The population estimator we use (SAK) is a tried-and-true model that provides an independent, reliable and cost-effective estimate every year. That model relies heavily on the observations and reports of more than 600,000 enthusiasts who hunt, harvest and register deer every year. This shared information and commitment from hunters gives Wisconsin one of the most reliable deer population estimates in the country.

Keith Warnke is the deer and game specialist for DNR's Bureau of Wildlife Management.

More information

For more details about managing Wisconsin's deer herd: