BSK
Well-Known Member
This topic won't apply to everyone in TN, just those who hunt/manage in the areas hit hardest by the 2022 drought.
First, let me say I'm not conclusively sure this problem is an absolute fact. It is based on an interesting trend I've observed having looked at a lot of photo census data and compared notes with many landowners/managers who collect trail-camera data. And this trend is - when looking at a census of the bucks using a given property - an unusually high number of 3 1/2 year-old bucks and an unusually low number of mature bucks (4 1/2+) this year.
Many factors influence a local area's "age pyramid" - the percent of the total buck population in each age-class. But it goes without saying that there will almost always be fewer bucks in each older age-class, because of all forms of mortality. In essence, you should see less 2 1/2 year-old bucks than yearlings because some yearlings are going to die each year, so fewer bucks that are 2 1/2 will exist the following year. This continues with each age-class. A local area's age pyramid - especially looked at over a number of years - should show the largest cohort is yearlings, the second largest should be 2 1/2s, the third largest should be 3 1/2s, etc. on up through all the age-classes that exist in the area. Now how big of a difference there is from one age-class to the next oldest will depend on many factors, but I find that the biggest factor is hunter harvest pressure. In fact, hunter harvest pressure is usually so obvious in the data I don't need to be told where the age-based limit for a club or big landowner is. I can see it in the data. If a club/landowner is using a rule (and that rule has been in place for a number of years) that bucks must be 3 1/2 before they are killable by hunters, I will see only a small drop in the number of 2 1/2s from the number of yearlings. The only loss of yearlings to 2 1/2s is through natural mortality - yearling bucks dying of disease, injuries, car collisions, etc. The same will be true of the decline in bucks from 2 1/2 to 3 1/2 - only a fairly small percentage decline. But because bucks are "legal" for harvest at 3 1/2, I will see a big drop-off in bucks from 3 1/2 to 4 1/2, and every older age-class as well, as hunters pick off a significant portion of each of these "legal for harvest" age-classes each year.
The point of all this is that, looked at over a number of years, I don't see big swings in the buck age pyramid on individual properties from year to year. Once a local area's age pyramid has developed - based on local harvest pressure - it stays very close to the same from year to year, with only slight differences. Even when hunters/managers change their harvest rules in attempt to produce an older buck age structure, the changes occur slowly from year to year. When properties make major changes in harvest guidelines to produce more older or mature bucks, the changes from year to year are incremental - just a couple of percentage points better from one year to the next (but these add up over time). Now there will certainly be vast differences in the buck age pyramid from property to property because of different amounts of harvest pressure and different self-imposed buck restrictions, but when looking at years of data from a single property, the numbers don't change quickly from year to year.
OK, after that exhaustive explanation, back to the original problem. And let me state again, I'm only seeing this problem in areas hit hardest by the 2022 drought - those areas where the drought was so severe that the acorn crop was a total failure, agricultural crops failed, food plots failed, and even the native habitat dried up (and I saw locations where even the pokeweed and ragweed dried up and died). The problem is a very odd number of bucks field-judged as being 3 1/2 this year. And when I say an "odd number," I'm saying some of these properties have come up with almost as many - and in some cases MORE - 3 1/2 year-old bucks than 2 1/2 year-old bucks. The accuracy of this scenario is highly unlikely. Not impossible, but highly unlikely.
My concern is, did the severe drought last year, and post-rut bucks going into a difficult winter (no acorns, no food plots, no agriculture) prevent surviving 3 1/2 and older bucks from adding the body growth the following spring/summer to "look like" they are a year older? The only explanation I can come up with for how numerous properties suddenly have more 3 1/2s than they had 2 1/2s the previous year is that some of those 3 1/2s are not 3 1/2. They are 4 1/2s (or even older) that were severely underfed the previous winter. This is pure conjecture on my part, but the numbers don't lie. If this occurred on just one property, I could come up with all sorts of potential explanations for it. But on multiple properties, all in the same region that all share the commonality of the drought? Yet in areas not as heavily affected by the drought I am NOT seeing this unusual pattern?
Again, this is pure speculation on my part trying to explain a regional anomaly. But it is an educated guess based on a lot of data over many years. But I could be wrong too and it's just an odd, highly coincidental anomaly.
First, let me say I'm not conclusively sure this problem is an absolute fact. It is based on an interesting trend I've observed having looked at a lot of photo census data and compared notes with many landowners/managers who collect trail-camera data. And this trend is - when looking at a census of the bucks using a given property - an unusually high number of 3 1/2 year-old bucks and an unusually low number of mature bucks (4 1/2+) this year.
Many factors influence a local area's "age pyramid" - the percent of the total buck population in each age-class. But it goes without saying that there will almost always be fewer bucks in each older age-class, because of all forms of mortality. In essence, you should see less 2 1/2 year-old bucks than yearlings because some yearlings are going to die each year, so fewer bucks that are 2 1/2 will exist the following year. This continues with each age-class. A local area's age pyramid - especially looked at over a number of years - should show the largest cohort is yearlings, the second largest should be 2 1/2s, the third largest should be 3 1/2s, etc. on up through all the age-classes that exist in the area. Now how big of a difference there is from one age-class to the next oldest will depend on many factors, but I find that the biggest factor is hunter harvest pressure. In fact, hunter harvest pressure is usually so obvious in the data I don't need to be told where the age-based limit for a club or big landowner is. I can see it in the data. If a club/landowner is using a rule (and that rule has been in place for a number of years) that bucks must be 3 1/2 before they are killable by hunters, I will see only a small drop in the number of 2 1/2s from the number of yearlings. The only loss of yearlings to 2 1/2s is through natural mortality - yearling bucks dying of disease, injuries, car collisions, etc. The same will be true of the decline in bucks from 2 1/2 to 3 1/2 - only a fairly small percentage decline. But because bucks are "legal" for harvest at 3 1/2, I will see a big drop-off in bucks from 3 1/2 to 4 1/2, and every older age-class as well, as hunters pick off a significant portion of each of these "legal for harvest" age-classes each year.
The point of all this is that, looked at over a number of years, I don't see big swings in the buck age pyramid on individual properties from year to year. Once a local area's age pyramid has developed - based on local harvest pressure - it stays very close to the same from year to year, with only slight differences. Even when hunters/managers change their harvest rules in attempt to produce an older buck age structure, the changes occur slowly from year to year. When properties make major changes in harvest guidelines to produce more older or mature bucks, the changes from year to year are incremental - just a couple of percentage points better from one year to the next (but these add up over time). Now there will certainly be vast differences in the buck age pyramid from property to property because of different amounts of harvest pressure and different self-imposed buck restrictions, but when looking at years of data from a single property, the numbers don't change quickly from year to year.
OK, after that exhaustive explanation, back to the original problem. And let me state again, I'm only seeing this problem in areas hit hardest by the 2022 drought - those areas where the drought was so severe that the acorn crop was a total failure, agricultural crops failed, food plots failed, and even the native habitat dried up (and I saw locations where even the pokeweed and ragweed dried up and died). The problem is a very odd number of bucks field-judged as being 3 1/2 this year. And when I say an "odd number," I'm saying some of these properties have come up with almost as many - and in some cases MORE - 3 1/2 year-old bucks than 2 1/2 year-old bucks. The accuracy of this scenario is highly unlikely. Not impossible, but highly unlikely.
My concern is, did the severe drought last year, and post-rut bucks going into a difficult winter (no acorns, no food plots, no agriculture) prevent surviving 3 1/2 and older bucks from adding the body growth the following spring/summer to "look like" they are a year older? The only explanation I can come up with for how numerous properties suddenly have more 3 1/2s than they had 2 1/2s the previous year is that some of those 3 1/2s are not 3 1/2. They are 4 1/2s (or even older) that were severely underfed the previous winter. This is pure conjecture on my part, but the numbers don't lie. If this occurred on just one property, I could come up with all sorts of potential explanations for it. But on multiple properties, all in the same region that all share the commonality of the drought? Yet in areas not as heavily affected by the drought I am NOT seeing this unusual pattern?
Again, this is pure speculation on my part trying to explain a regional anomaly. But it is an educated guess based on a lot of data over many years. But I could be wrong too and it's just an odd, highly coincidental anomaly.
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