How To Manage Whitetails on Private Land: Part 2

Last week on NorthAmericanWhitetail.com, I began a 7-part series (find part 1 here) on managing deer on private lands. This comprehensive series is designed to read like a one-on-one consultation meeting with myself and the landowner (you). I began with the first step: establishing your goals and objectives. I explained deer management as a “three-legged stool,” one leg of which is population management, another habitat management, and the last people management.

What’s the next step? You need to determine how many deer your land holds or hosts and if they’re healthy. One of the top five questions I am asked about managing deer is: “How many deer do I have on my land?” This question doesn’t need to be answered 100 percent correctly, because you don’t need to know exactly how many deer inhabit your land to know whether the herd is healthy. Yet, it is a good idea to obtain a reasonable estimate of the numbers of deer you have, or at least the approximate density of deer.

I have been part of the evolution of deer population estimation over my five-decade career. In my early professional days, the average Texas biologist used the Hahn Cruise Line to estimate deer numbers/ density. Here is how it worked. Named after Henry Hahn, the technique involved an observer walking a two-mile east-west line, counting the numbers of deer observed during the walk. Visibility (distance a deer could be seen) was estimated every 100 yards. Two observers were sometimes used, so one observer could walk out to the point where the other no longer could see him. At the end of the census, you calculated the average visibility, multiplied it by 2, then multiplied by the distance of the line. This gave you the total area censused. Then, by dividing that area by the number of deer seen, you had an estimated deer density.

On public lands, the estimate was in deer per square mile, while on smaller private lands it was acres per deer. For all deer census techniques (save one), a census is conducted in late summer to early fall.

Once this technique was deemed inaccurate and overly time-consuming, the next “best method” was the track count. I lost “track” of the number of times I performed this method. You had to have either roads or rights-of-way to do a track count. We constructed a heavy implement that could be dragged behind a vehicle for a mile or more, turning the soil to provide a fresh “canvas” for finding tracks.

Then, after 24-hours, we walked the line, counting the number of deer crossings. Assuming a deer had a 24-hour cruising radius of one mile, you could estimate deer per square mile. This technique was the first to really illicit criticism from the public. I have heard hundreds of times a landowner say: “I watched a deer walk across one of their lines, and then cross back over it. That biologist walked down the road and counted it as two deer!” Needless to say, that technique was short-lived.

Next came the spotlight count, which is a variation on the Hahn Line and the track count. Once again, you had to have roads for this census. We generally started at about 45 minutes to an hour after sunset. We later learned from my telemetry studies that many deer did not even begin to move until at least two hours after sunset. There were two observers in the back bed of a pickup, each with a spotlight. At 1/10-mile intervals, the two would call out how far they could have seen a deer from the truck. After recording how far you drove (hopefully in a straight line and not doubling back), and the average observation distance, you again calculated the area covered; then, you’d divide it by the number of deer observed to obtain acres per deer. That worked fine as long as the habitat was mostly open, but it produced poor results in most deer habitats. We used this technique when clearcutting first became popular in east Texas, then abandoned it when the plantations grew above deer height. Credibility again was the victim of this method!

Then we got “sophisticated” with deer census. We first used fixed wing aircraft, then helicopters to run what amounted to an “aerial Hahn Line.” You could either do what was called a complete census (in which the helicopter fl ew adjacent strips) or a percentage census (where you fl y X-number of strips at Y-distance). In the beginning we were paying about $200 per hour for a flight, but today the price is up to $1,200 or more. What do you get for your money? Well, you get to see some nice bucks, and a density estimate with an error of ±30 percent!

Perhaps the most questionable method was the pellet-count, which some biologists persist in using to this day! Again, it is a strip census, but this time you count the number of pellet groups along the line. Using a standard of the number of times a deer defecates, you can calculate an index or a density estimate. Several of my colleagues later showed that the number of times a deer defecates is variable, and again the error rate is terrible! So, how do you get a reasonable density estimate for your deer herd?

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Dr. Harry Jacobson, Ben Koerth, Randy Browning and I developed a method that, at least on small properties, provides a reliable estimate of the number of deer you have. After developing trail cameras, we felt they could be useful for deer census. Randy did his Master’s thesis research in Mississippi on using trail cameras to count deer. We used one of Dr. Jacobson’s study areas, where he had radio-collared and marked deer, so we had some basis for judging both precision and accuracy. Since then, most of the studies evaluating this methodology have supported its usefulness, with some modifications. However, it is time-consuming, and you have to use several reliable trail cameras. Here’s how we use it today.

My research over the years, and Dr. Jacobson’s calculations on his deer in Mississippi, suggested a camera density of one to 80-100 acres. We place one camera as near as possible to each 80-acre grid square, about two feet above the ground. Never face a camera any direction but north during the census! You do not want sun flare ruining your photographs. Where legal we place bait (usually corn) about 12 feet in front of the cameras, which must be replenished as consumed.

Where baiting, even for census, is illegal we just try to place the cameras on deer trails or edges of food plots within each square. Our research has shown that in 10-12 days you will photograph 95 percent of the deer frequenting that grid square. This was based on marked deer that were and were not photographed during our research. In those days, we had to use actual photographs, while today of course we have digital images stored on camera cards. The next step is to go through your photographs, culling all images that do not have deer. In areas where there are wild hogs, this can be quite troublesome, as hogs quickly come to bait and dominate camera stations.

Once you have removed all non-deer photographs, you are ready to process them. Go through each photograph and record the number of bucks, does and fawns you see in each photograph, even if they are duplicates from previous photographs. The method at this point constitutes repetitive sampling, no different from incidental sightings (discussed below). When finished, you will have the number of times a doe was photographed, then bucks and fawns. From these data, you can calculate the buck:doe and doe:fawn ratios.

The next step is to go through your photographs and pull out each buck in the study. We learned long ago that antlers are like fingerprints, unique to each individual. Even a “plain Jane” 8-pointer will have something about his antlers or body that identify him. We set up folders on our computer for each buck, then we assign a number to each buck. Some managers go so far as to give each buck a name, and it’s amusing the names bucks receive!

But, what about spike-antlered bucks? We also record the number of spike and forked photos we have, so we can calculate a spike:fork ratio, as well. With experience, however, we have learned to identify most spikes as unique. This technique is based on the number of unique bucks. Let’s take an example showing how you estimate the number of deer represented by the study. In our example, we have identified 6 unique forked bucks, a buck:doe ratio of 1:3, a doe:fawn ratio of 1:0.7, and a spike:fork ratio of 1:4. We then multiply 6 (unique bucks) by 3 to obtain our doe estimate (18). Then multiply the 18 by 0.7 to obtain the fawn number, 13. Last, we divide the 6 unique bucks by 4 to get 1.5 (rounding to 2) spikes. Adding these up (6+18+13+2) we have a 95 percent population estimate of 39 deer. If your land is 400 acres, that produces a total deer density estimate of 1/10.2 acres; and an adult deer estimate of 1/15.4 acres, which is pretty high for most areas.

We normally conduct two camera censuses, one in later summer/early fall and another in late winter/early spring. The first will give us an estimate of our fawn crop and the latter the true recruitment. Even biologists are known to confuse these two metrics. Fawn crop, expressed as a percentage, is an estimate of the number of fawns born that reached weaning age. The true recruitment is a measure of what proportion of these survived one year to enter the deer population. Why is this distinction necessary? In many areas, especially in the North, there is always a fairly high fawn crop; yet, the percentage of them surviving to spring can be quite small. We often see herds in northern areas of the country come into fall with a 70-80 percent fawn crop, yet they come out of winter with a 15 percent recruitment!

That there were lots of fawns at the end of summer is irrelevant in this case! If you do not have at least a 40 percent recruitment rate, under normal buck harvest, it is mathematically impossible to have significant numbers of mature bucks!

As an additional check on our data, we also conduct incidental sightings studies for each property. Over the month of August, we instruct everyone visiting the property to record each deer seen on a printed card, every time they visit. We provide a weatherproof box for depositing the cards. At the end of the month, we tally bucks, does and fawns; then, calculate another set of ratios from these data.

Well, for those of you who need to know how many deer you have, these are the ways to estimate that number. Yet, I remain steadfast that you really do not need to know how many deer you have, provided you use the right metrics for deer management progress. In coming installments, I will expand on this point. In the meantime, you might set up for conducting a deer count.