September 20, 2018

I Still Don’t Understand How You Can “Manage” Wildlife Without Counting

And evidently, I’m not the only one scratching their head just a bit in trying to figure this nonsense out. It sure appears on the surface as though claiming counting is no longer important as a vital tool to responsibly manage game populations, like bear, deer, moose, and turkeys is another convenient excuse to hide problems or simply provide alibis for where you were when the moose population dropped dead.

V. Paul Reynolds, in his article today, states the following: “When the moose aerial studies were commenced in 2010, getting a handle on the ever-elusive question of how many moose there actually are was an avowed purpose of the surveys, along with understanding moose mortality and productivity. Eight years later, it seems that, although we have gained useful data on moose sex ratios and causes of mortality, and other indices, we have fallen short in counting heads.”

And in and around 2010 (It wasn’t immediately made known to the public that the Department of Inland Fisheries and Wildlife (MDIFW) had undertaken a moose study.), I questioned whether MDIFW would ever get to the real, honest, explanation of life as a moose in Maine or would it be just another in a long line of “studies” backed and crafted by Environmentalism’s Scientismic hocus-pocus. So far, it appears it’s leaning toward the scientismic end result.

However, it was encouraging when MDIFW reported that their data “suggested” that ticks were the real culprit in taking control over moose populations, although there still exists fuzzy voodoo science and romance biology over whether it’s Global Warming or too many ticks that are causing moose mortality.

As Reynolds points out, one of the great selling points of this current moose study was the need to get a solid grasp on the moose population and what is controlling it. The Second Grade question remains how do you accomplish this task while at the same time removing from the new Game Management Plan the importance of population densities and replacing it with “healthy populations?”

At the drop of a hat, or perhaps if it fits the current moose management narrative for political purposes, moose biologists and MDIFW officials seemed almost boastful in stating Maine had 76,000 (or lot’s more) moose. After eight years of study and many dollars later, MDIFW is reluctant to utter a guess?

Perhaps what’s really going on is a matter of attempting to save face. Is it that MDIFW has discovered that Global Warming can’t be blamed for a decline in moose? Has MDIFW discovered that winter ticks really are killing off the moose (you know, some of that “natural balance”) and it is NOT Global Warming that has caused the epidemic? Has MDIFW discovered that trying to grow too many moose has caused the prevailing tick problem? Has MDIFW discovered that there isn’t even close to 76,000 moose and, as yet, has not come up with a workable lie as to why they were so far off in their estimations?

If so, perhaps now they don’t know what to do because taking action to scientifically correct the “unhealthy” moose population means bucking the Environmentalists and Animal Rights groups who not only want more moose they want uncontrolled numbers of every wild animal that exists…despite the consequences.

Being politically on the wrong side of Environmentalism is a place MDIFW does not want to be.

For now, better to act stupid and not reveal your hand, and then maybe it will just magically go away.

In the meantime, let’s practice…1, 2, 3, 4, 5, 6, 7, 8, 9, 10… I knew you could.

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The Hocus-Pocus of Estimating Deer Harvest….or Something

I recall at a very young age learning the true meaning of the word “assume.” For those not fortunate to have had such a high degree of education, let me help you out – ASSUME = ASS(out of)U(and)ME. Yup! That’s what often happens.

I was reading an article just a few minutes ago by someone trying to explain why the methods of guessing deer numbers and harvest were “good enough.” Here’s what I giggled at in the article: “Say we flip a coin ten times. We know that the chances of getting heads is 50%, but just ten flips may not show that. The more sets of ten coin flips we do, the closer we get to the 50% – to a point. But there also reaches a point where it doesn’t matter if we flip the coin 1,000 times or a million, either way, we will be very close to 50%. The same logic comes to the amount of data on deer harvest we need to collect to accurately illustrate the statewide harvest numbers. Knowing that point, is where the complexities of statistics come in, but be rest assured that they are reliable.”

Perhaps it is “good enough” to flip coins and make assumptions, while disregarding other influencing circumstances, when guessing on deer populations as well as how many deer were harvested. Those who buy into the “good enough” scheme also buy into the idea described above that there’s always a 50-50 chance when flipping a penny a few million times. Actually, it might be more accurate to say the odds are 51-49, but even that estimate can be flawed. What mint of penny is being used? Is it the same penny all the time? Is the coin dirty? Etc.

Science is science – is it not? Yeah, I know. Not for everybody. It’s more exciting to just “assume,” as the article says that regardless of how many times you flip a coin, half the time it’s heads, the other half, tails. This is, of course “assuming” it’s always the same coin, always clean, with no irregularities, flipped by a calibrated machine, the same number of flips, in a vacuum, blah, blah, blah.

Odds are odd. Do we “assume” that with the millions of deer in this country that half the new-born fawns will be male and half female? Yup! (Unless you are one of those that believes there are no bucks left) But scientists tell us that it’s closer to 51-49. It matters not which sex wins….or does it. What causes the skew? Is it man’s influence? Is it 100% natural? If that’s an average, what are the extremes in those birth rates and what causes them? A lot of questions, I know, but, but, but….

When a scientist begins his work to seek an outcome, isn’t the work already flawed once the scientist “assumes” the odds are 50-50? Throughout a scientific progression, the more times “assumptions” are made, it probably is accurate to “assume” there are more errors rendering the results less accurate. The first assumption might be “good enough,” but for whom?

So, does any of this matter when it comes to managing and establishing deer management programs? Mostly likely not. Does it matter if this same “assuming” approach is used in areas where there are but 10,000 estimated deer versus those with 500,000 or more? Do managers continue, for years and years, to make the same “assumptions?” If changes are made to the methods, is it “assumed” that it will not effect the outcome?

Has anyone spent the time to determine what the “odds” are in making “assumptions”, that those “assumptions” are skewing reality in any one direction more than another? If there are “assumed” outcomes in two directions, is it “assumed” that half the time it’s one way and half the time the other? I assume you have had just about enough of this gibberish.

Seems silly doesn’t it? One of the problems with this method of making assumptions, is that it really is the beginning stages of outcome-based political manipulation disguised as science – I mean, honestly, isn’t it? That 50-50 odds for coin flipping is perfect for politics, but is worthless when dealing in scientific terms.

There are certain things deer biologists can do that will improve the results of their guessing. And that’s good enough…evidently. However, one of those things should be a scientific-based survey to right the ship and get it reconnoitered and back on course. That works better than relying, always, on a coin flip. After all, it takes a person to flip the coin and somehow I have little faith in the direction of the wind or the Flim-Flam Man.

TaleANumber

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