“There must be at least 100 does for every buck I see in the woods now!” How many times have you heard that exclamation? If you’re like me, more than you care to. Hey, look! We all do our share of complaining, of which the vast majority of it is just complaining out of lack of success or basic knowledge of what you’re seeing, or better yet, what you’re not seeing.
Is it biologically possible to have 100 doe deer for every one buck? Er, um, well……I guess it could be done but I think it would have to be under controlled circumstances with a deliberate intent to skew the ratio far out of balance. I might even be wrong on this and would wager a guess it wouldn’t be a very healthy population of deer if it did exist.
The truth is, none of us completely understands deer management and in this case managing to sustain a desired sex ratio. I’m not a scientist, biologist or a magician. I have stayed in a Holiday Inn before but I honestly don’t think that qualifies me to be an authority on deer management. What I would like to do is try to get hunters to understand a little bit better about the complexities and realities of whitetail deer management and managing for desired buck to doe ratios.
I must also point out that in the wild, managing whitetail deer varies considerably, not only from region to region but state to state and even within the wildlife management districts or units within each state. Much of my information comes from managing deer in Maine. The reason for this is I think I have a better understanding of Maine’s deer management programs, I grew up in Maine and I’m getting most of my information from Maine wildlife biologists. Maine also has a decent history of producing some very large deer and this interests hunters everywhere. How deer are managed in your state could vary drastically from that of Maine. As you will see, there are just so many variables and each of those variables is forever changing adding to the challenge of deer biologists to figure this science out.
So, where do we start? Let’s start in the Garden of Eden. W…..H…..A……T!?!? Why not? God looked into the Garden of Eden (GOE) and said, “Hey, I did okay. That place will support 100 deer and I’ll call that ‘carrying capacity’” So he stocked the GOE with 50 adult male deer and 50 adult female deer. He called that a buck to doe ratio of 1:1.
I suppose God knows best but as humans we have to ask if that is the ideal ratio? Not everyone agrees with that assessment and I’m sure it can and does vary nationwide but I have heard or read where anywhere from 1 buck to 1 - 5 does is an acceptable ratio depending on the desired outcome. I think it depends on a lot of circumstances but for the intent of this discussion, let’s say achieving a 1:1 ratio is what we’re looking to do.
When spring rolls around all 50 adult female deer fawned. Probably the GOE has ideal habitat, etc., after all, the Big Guy does things right, and under those conditions most mature does will have two and sometimes three fawns. Let’s keep it simple because I confuse easily. Each doe had one fawn.
This is the GOE so there is no mortality - you know the lion lays down with the lamb thing. By mid to late summer there now are 150 deer, 50 of those are of course the fawns. Once again for simplicity sake, let’s divide the new born deer 50/50, meaning 25 were males and 25 were females.
To get a further grasp on this you need to know that the 25 female deer born that first year will not breed during their first rutting season. In theory, if the original 50 adult does all fawned one deer apiece again the following spring, there would be 200 deer and we would also still have a 1:1 sex ratio. Being that we are in the GOE, no adult deer died of old age.
The following rutting season, the first year’s does are now of breeding age. Assuming the original 50 does are still able to breed, we now have 75 adult does that will fawn in the spring. By fall there are now 275 deer, still pretty close to a 1:1 sex ratio.
I hope you see where this is going. It won’t take too long under the ideals of the GOE to be overrun with too many deer. But this of course is fantasy.
God gave man dominion over the animals so he set up a hunting season so man could eat and he could keep the number of deer at carrying capacity (100 deer AND a ratio of 1:1, this is important). God reasoned and concluded that he couldn’t just let man take any deer at any time, so he devised a plan so that he would have to take some females and some males and it had to be done in such a way so as to as closely as possible maintain a deer herd of 100 deer - 50 males and 50 females. And so God created the Any-Deer permit system.
All was great until man sinned. Winters were thrust upon Mainers, coyotes began eating deer and bears were hungry too, tired of only eating apples and black berries. Disease became an issue for us to deal with as well as people who didn’t think the laws really pertained to them, so they took whatever they wanted for game and said to heck with everyone else. Man had to work by the sweat of his brow and so he began cutting his trees down to sell to support a family.
Thrown into this mix, God really came down hard on his creation and allowed for the evolution of the politician and as such a value of dollars and no sense was also put on deer and deer hunting. Things began to get messy.
God challenged the Maine Department of Inland Fisheries and Wildlife and told them to figure out how to take care of the deer and that’s what they’ve been trying to do ever since.
It wasn’t easy trying to figure out how many deer to allow to be taken and of what species. A bit of trial and error took place until over time records were kept and then MDIFW could get a better understanding of success rates, participation of hunters, recruitment, mortality, etc.
Let’s go back to the less confusing time in my little history lesson when hunting the deer became part of the equation. After the end of the first hunting season, if all went well, we ended up in reality with 100 or so deer. The majority of those deer were mature and of those mature deer we calculate that about half are bucks and half are does. The remainder of the herd are a mix of fawns - again, close to half males and half females. This is our “post hunt” calculations.
Remember that through all of this we want to sustain as close as we can to a 1 buck for every doe ratio. We are assuming (I hate to use that word), that all or at least nearly all of the adult female deer will fawn in the spring. Under ideal conditions, we could go ahead and figure out how many Any-Deer Permits to issue. We combine that with the number of licensed hunters we know we are going to have. With established success rates of the hunter, we think we are pretty good at figuring out how many deer will be taken during the next hunting season and how many will be female and how many male and approximately what ages those deer will be - in other words fawns or adults. This is called “pre-hunt” calculations.
If this was all we had to calculate, I might be smart enough, at least through trial and error, to keep the deer herd somewhere near on target. But, alas, this is not to be.
Lee Kantar, deer specialist and wildlife biologist at the Maine Department of Inland Fisheries and Wildlife, has been extremely helpful in providing me with information about how all this works. Let’s just say he’s been very patient as well. He told me that in Maine the average of male to female deer born in the spring is slightly in favor of the males. In other words, if 100 new fawns were born this spring, just over half would be little bucks, the rest does. He also describes the “pre-hunt” calculations this way.
1st realize that every year as part of our permitting process we calculate the pre-hunt sex ratio of bucks to does for each WMD. If the buck to doe ratio is skewed, in other words if it deviates from essentially 1 buck to 1 doe than we will adjust the doe permit levels to bring the population back to equity. Keep in mind that buck and doe mortality rates are different with bucks have much higher rates. So populations are always somewhat skewed.
Another thing Kantar points out is that when you have a WMD that is way under population objectives, you can’t be managing for a 1:1 sex ratio. You reduce or completely eliminate the taking of any female deer until population objectives are reached.
There are some things that the magicians and MDIFW can rely on to be relatively consistent. Some of those things they have established by keeping accurate records since the first day that God handed over the deer management to them. As some examples, they can get a pretty close estimate on how many people will buy a hunting license and go hunting. They can estimate because of record keeping, what percentage of those hunters will actually bag a deer. They know that with “X” number of Any-Deer Permits handed out, there is a certain success rate that goes with that. They also know what percentages of the deer taken with an Any-Deer Permit, will be fawn male deer, fawn female deer, adult does and adult bucks. They know these things because they keep accurate records.
Other known things will be the data they collect from samples taken during hunting season at tagging stations. We also know that they are constantly collecting data from their winter monitoring stations and field observations through the year. They have to have as much solid unchanging information as they possibly can. The more, the easier their job in managing this herd AND sustaining that desired sex ratio.
Are you confused yet? Well, I am but I’m trying to make some sense out of this. It gets even more complicated.
Mind you that even though I categorize this information as being a “known” bit of information, it does vary. Here’s an example. As I said, MDIFW has a pretty good idea how many licenses they will sell for deer hunting. From that they estimate how many will take a deer. This comes from comparisons of previous years’ data that tells what the success rate is. What they don’t know and can’t control is hunter participation. Simply buying a license is no guarantee that 1) a hunter will bag a deer, 2) that the hunter will hunt the same amount of time as previous seasons or will even hunt at all, and 3) what factors would increase or decrease hunter effort, like bad weather or good weather or ideal tracking conditions, etc.
A mathematician, should be able to take all this information I’ve given to this point and come up with a algorithmic formula that would tell him how many Any-Deer Permits to give out for each WMD based on objectives. We know we want to maintain 100 deer in the Garden of Eden with a sex ratio of 1:1. How hard can that be. If nothing else, we can make a trip or two into the Garden just before hunting season and do a head count, then we’ll no for sure how many does to take and how many bucks, right? Fantasy!
Well, the algorithmic formula isn’t that far fetched but the information used in that formula gets more and more complicated. Let’s quickly recap. We started out with 50 does and 50 bucks which grew to 150 deer. We know that a bit more than half of the new-born deer were males, the rest females. So we have roughly 75 male deer now and 75 females not all of which are adult and of breeding age.
We got to figure out how to end the hunting season with 50 bucks and 50 does.
If we have statistics that tell us how many people will hunt, those same statistics will tell us how many will shoot a buck and how many will shoot a doe, or better defined here as an antlerless deer. Of the antlerless deer taken, statistics will tell us approximately how many are mature does (breedable), how many are fawn males and how many fawn females.
I think it is fair and reasonable to state that because of good record keeping, it is easier to use the methods and tools I’ve described, to keep a deer population in check, increase it or decrease it, whatever the goals for a certain Wildlife Management District are.
Well, that was simple! Not quite. We’ve only just begun really. We have to add to this magical algorithmic formula an array of variables and unknowns. I probably won’t cover them all but I’ll get enough to help you better understand and get a picture of where I’m coming from.
I look at it from two perspectives. What kills deer and what makes them thrive? Most of these factors are things we cannot control, are ever changing and difficult at best to predict but all play an important role in knowing how to manage the herd. Let’s take a look. First the things that make deer thrive.
Deer thrive best in an ideal habitat. In Maine, the habitat will vary greatly. We all know that if deer have the right kinds of foods and ample supplies, they will grow big and healthy. When there’s ample food, some magical little voice inside the female deer will tell them it’s alright to have more than one deer (I’m just kidding of course. The doe deer can’t consciously make that decision and there is no little voice).
To some degree deer will biological adjust how many deer they have depending on the health of their surroundings. On the opposite end of that, the health of the fawns will depend on the same surroundings. More on the negative aspects of this in a bit.
In Maine, we know that deer need places to go and hang out in the winter that provides them with as much natural protection from the elements as is possible as well as some food, although not the most nutritious. These, or course, are called deer yards or deer wintering areas.
In short, when deer have an abundant and varied diet, ideal weather conditions, few stresses and a healthy habitat to carry out all these things, they will prosper and prosper quite rapidly if allowed.
Now to look at what kills them or negatively affects their health and survivability. The obvious negative factors are to take the positive ones I’ve just given you and turn them around. When food becomes scarce, the weather is extreme with limited habitat, including wintering areas, compounded with stresses from predators, including man, things can begin to turn south.
But there are more negative things that can affect the deer herd. There’s disease, poaching, out of balance species of predators, man’s influence on habitat through development and forestry practices and other natural occurrences like plant disease and fungi, ticks, chronic wasting disease (not found in Maine) and more.
When we look at every possible aspect of what influences the deer, both negatively and positively, we quickly see that most of it is never constant. As a matter of fact, much of it is the opposite. If the guys and gals at MDIFW are intelligent enough to devise an algorithmic formula under ideal conditions, just think how difficult it is when these conditions are rapidly changing right before our eyes.
Below, I am going to give you a bit of information that I find fascinating. If you’re like me, you’ll have to read it more than once to get a decent enough grasp on the concept to be able to ask the question, “Am I, in fact, making this management of deer too complicated?” *Note* anything surrounded by [ ], I added for clarification.
Now, this is something–depending on how much hunting pressure a herd has it can only become skewed [sex ratio] to a certain point based on differential mortality of bucks and does and recruitment rates. In Maine pressure is relatively low to moderate compared to most whitetail states. On average our annual buck mortality is around 45%, many states are more in the 60 to 70% range.
Now you can test the skewed sex ratio deal. If you take a population of 1000 deer, 500 adult bucks and 500 adult does and then apply known mortality rates to the bucks and does, then apply known production, fawn mortality, and recruitment rates to this population, after 5 years the sex ratio will remain the same. So for example in a population where annual adult buck mortality is 45%, annual adult doe mortality is 25%, fawn mortality is 40%, and the recruitment sex ratio is 112:100 males to females (Maine data), then this population starts out even with an adult sex ratio of 1 to 1, after year 5 the buck to doe ratio increases to 1.2 does to 1 buck and stays that way every year after.
You can apply different known mortality rates from Maine data and try to skew the ratio. I took an extreme value of annual adult buck mortality of 67% (Heavily hunted population), an adult doe mortality of 25%, a fawn mortality rate of 51% and after 5 years the sex ratio works out to 1.7 does to 1 buck.
Biologically it is hard to make the case for adult buck to doe ratios being more skewed than 2 does for every 1 buck. You start to get skewed when you have high annual buck mortality and extremely low doe mortality. Also keep in mind that we manage on a fairly large landscale, so locally and in smaller areas different things could be happening.
This is all very well and good and as I said, fascinating but it depends on one important aspect. You have to believe the data MDIFW is providing and the formulas they use. If you don’t have that trust, none of this really matters. Is it perfect? No and I think Kantar or any of the other biologists would say so but it seems to work quite well. Can sex ratios become skewed in Maine? I believe they can but given the information provided to me, this would mean that MDIFW biologists would have to have completely lost track of what’s going on within any of WMDs and ignored it. Kantar himself gives reasons why a sex ratio would become out of whack - high buck mortality, low doe mortality.
When I began this piece, it started with a fictitious quote saying that there must be 100 does to every buck seen by hunters. Perhaps biologically, you have come to better understand that this probably isn’t true. Lee Kantar took some extra time to provide me with some reasons why we might not be seeing the number of bucks that we would like to.
Now why do people observe more does (sometimes a lot more does) than bucks in the field? A number of things are at play here:
1. Bucks and does use habitats and forage differently at different times of the year. Large bodied deer (bucks) can afford to forage on food that is less nutritious than does, in other words larger deer can eat more low quality food to maintain body condition while smaller bodied deer need better forage to maintain and increase body mass. So females are seen along field edges and openings where they may find better nutrition versus the woods or swamp buck.
2. It is more common to observe groups of deer (many times a social group of related deer–i.e., adult female with yearlings and fawns) versus a single deer (buck)–although buck bachelor groups form as well.
3. An observed group of antlerless deer will likely include fawn bucks, sometimes yearling bucks where antlers are not apparent.
4. Bucks are notorious for being dodgy. We have done deer drives in exclosures with known numbers of deer and never see all the deer. Research has been conducted on large exclosure where they have gone into the fenced area and harvested all the deer using all kinds of methods. Getting every last one proves extremely difficult, and in a classic experiment in the mid-west, after they thought they had killed all the deer, they eventually found one last deer-a mature buck.
5. During the hunting season, especially in areas where there is lots of hunting pressure, the sex and age dynamics of the herd is being changed before your eyes. The greatest cause of buck mortality is hunting and that mortality is often condensed into a 4 week period where the herd dynamics are rapidly changing. So those are a few points.
I would like to once again point out that I am not an “authority” on deer management. The intent of this writing is to help hunters, particularly those who insist buck to doe ratios are extremely out of whack, a chance to better understand what it is they are seeing, not seeing and why.
I probably have missed some aspects of this debate and may have even misrepresented some but I believe the time and research I put into this article it is accurate. It is not intended to be a research or study document, just information that I hope will compliment your knowledge of Maine’s whitetail deer management and whitetail deer in general.
Tom Remington
buck to doe ratio,
lee kantar,
Maine Department of Inland Fisheries and Wildlife,
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