How To Manage Whitetails on Private Land: Part 3

One of the greatest tools in deer population management has been the trail camera. In this month’s column, I’ll explain how my colleagues and I use trail cameras to determine the following: fawn crop, true recruitment, buck:doe ratio and buck age structure.

At the Institute for White-tailed Deer Management & Research at Stephen F. Austin State University, we were instrumental in the development of this technology. In the early 1970s, we were investigating a natural mineral lick on the North Boggy Slough Hunting & Fishing Club, belonging to Temple-Inland, Inc. (the largest timber company in Texas). At the same time, the Wilderness Act was passed, and the U.S. Forest Service was busy converting managed forests to wilderness.

The National Forests of Texas wanted to know how many hikers were using the newly created wilderness trails and had adopted an instrument that put out an infrared beam to a reflector that returned the signal to the source. When a hiker walked down the trail, he or she would break the beam and a counter recorded the event. We decided to use this device on the natural mineral lick in a cut-bank of a creek on North Boggy.

In no time, we had lots of events recorded, but being a doubting scientist, I wanted to find out how many events were deer and how many were other species, such as wild hogs. I learned of a company in California that had developed a trigger system for 35mm SLR cameras, and quickly called them. They sent me some, and we hooked one up to a camera outfitted with a 400-shot magazine and a motor drive.

Obviously, since that camera cost $2,000 more than 40 years ago, we did not put it out in the rain. We ended up with proof positive that deer indeed were gnawing into the dirt to get the mineral-rich soil! Later, we would work on a product called “StumpCam,” that controlled one of the “new-then” Sony HandyCams to record video. (There were no computer chips at that time, so we used tape recording).

Some years later, Dr. Harry Jacobson, Ben Koerth, Randy Browning and I conducted scientific research on the use of trail cameras for censusing deer. We used a marked (radio-collared) population of deer at one of Dr. Jacobson’s research areas in Mississippi to test the accuracy of population estimations. By then, biologists were using technical quality cameras for wildlife research and management applications. At the Institute, we began looking into other applications of trail cameras in deer research and management. The addition of video allowed us to see what the deer were doing. Along the way, we worked with the folks at DeerChannel to place video cameras on the deer themselves; and, that’s when we really learned a significant amount about deer behavior. For one thing, we were somewhat surprised that the average deer really did not do much during a 24-hour period, other than eat and rest!

By the 1990s, we were routinely using trail cameras for a host of applications to deer management; and one of the most useful is the topic of this column. In 1991, we produced a best-selling video called “Aging and Judging Trophy Whitetails.” That year the Institute sold more than 10,000 copies. Later that year, we also published a book by that name, also a best-seller.

At first, professional biologists criticized our position that the average person could learn to accurately age deer (especially bucks). We used the following age classes: fawn, yearling and each year thereafter. I learned that we could teach folks to age with acceptable accuracy in a short time, given proper instruction and age clues. The greatest confusion among laymen was differentiating between 3 1/2 and 4 1/2-year-old bucks.

Our research, however, showed that accuracy increased significantly (80 percent+) when we used age classes instead of years. These are fawns, yearlings, immature bucks (2 1/2 to 3 1/2 years), mature bucks (4 1/2 to 5 1/2 years) and over-mature (6 1/2 years+). The whitetail buck reaches his full body size and disposition at 4 1/2 years. And, where deer herds are allowed to reach a natural age distribution, the majority of breeding occurs within the “breeding pool,” which is the mature age class. DNA studies on sires of bucks showed that all bucks contribute to the fawn crop, but they also show that, when mature bucks are present, they contribute the most.

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How do we calculate these metrics? In the fall, we conduct a camera herd survey, counting the number of photos of bucks (including repeats), does and fawns. Once this is done, we simply add up the number of total buck, doe and fawn photos and calculate the ratios and fawn crop. We also use the number of unique bucks (see Part 2 of this series) as the basis for a population estimate. In the fall, we also use the buck photos to obtain the number of yearling, immature, mature and over-mature buck photos in our sample.

From these data, we produce a demographic structure of the herd. Demographics can be defined as “statistics that describe populations and their characteristics.” In the case of deer, the demographic categories are fawn crop, true recruitment, buck:doe ratio and buck age structure.

Notice I keep using the term “true recruitment” throughout these discussions. Why? It’s because it is not correct to use the fawn crop as this metric; and, the persistence of some biologists to continue calling fawn crop recruitment is quite irritating! Recruitment is defined as, “the process by which new individuals are added to a population, whether by birth and maturation or by immigration.” The does in your herd get pregnant (pregnancy rate), and then grow 1 to 2 fetuses (average fetal count), then they fawn (birth rate); then many of these fawns die during spring and summer, arriving at early fall in much reduced numbers. When we calculate the percent of does with at least one fawn in fall, that is expressed as fawns per 100 does, or “percent” fawn crop. This is the acceptable method.

So, there is a reason deer are aged in half-year increments; they are not truly added to the population until they reach the next spring! That number, again as a percentage, is the true recruitment rate; determined at the point when they are added to the herd.

We have developed a series of “metrics” for assessing the health of a deer herd, and the ones you can obtain from trail camera surveys are the most important. Over the years, we have learned there is a reason why does have, on average, two fawns. That is the number the species has evolved to that assures some survive to recruitment. When we include annual buck mortality, a deer herd with less than 40 percent recruitment is not going to have enough mature bucks to satisfy hunters!

There is much debate about the “natural” buck:doe ratio, but I assert it is one buck to 1.5 does. Without hunting mortality, that is the buck:doe ratio a herd will attain under natural conditions. Just like humans, bucks do not live as long as does, accounting for the disparity in numbers. If you want to get into an argument either with a layman or a professional biologist, just throw out the comment that an area has a 1:4 buck to doe ratio! I must admit, I have seen ratios as high as 1:8; so, am I right or wrong?

Most professional deer biologists include buck fawns in the ratio calculation, and that usually comes from fawn crop, not recruitment. Second, in herds that have been mismanaged for decades, we have what I refer to as a “stagnant” herd. In these herds, hunters seldom harvest enough does, but over-harvest the bucks. When you combine a very low recruitment with does that can live to be as much as 20 years of age, you have a stockpile of does and a deficiency of bucks.

When you conduct trail camera herd surveys year after year, you not only see what is happening to your herd, but also you can develop plans to “fix” problems clearly identified. I also like to produce graphs that show the actual buck demographics (based on camera counts) versus the demographics of the buck harvest from the same year and property. These comparisons can be quite telling about how you are harvesting your deer herd.

There are a number of great deer managers out there using the techniques I’ve described above to manage their herds. For example, Wayne Sitton (former QDMA Deer Manager of the Year) has used these metrics to manage the Turtle Lake Club near Hillman, Michigan, to completely turn a herd around; prior to 2000, the herd had almost no mature bucks. He accomplished this task by adjusting his management plan, not only in his buck harvest, but also in habitat management and nutritional supplementation through food plots.

Like Wayne, you too have the capabilities to learn more about your deer herd and adjust your herd’s ratios. Hopefully, some of the tips in this column, specifically related to using trail cameras to acquire valuable intel about your herd’s demographics, will assist in your management journey!