You folks down south

I live close to 1-69 in the south, and let me tell you, the deer numbers are WAY down in my area. Not to that, but I don't know why, and I was just on it the other day and didn't see a single deer ran over on it.

Timex: that is nothing new the DNR as well as the insurance industry have been monitoring accident reports for decades and as you can tell it doesn't take long to get those stats.
It might make a person think that there is a program already in place to monitor such things a car/deer accidents.

Pretty sure these particular stats is from the ISP..

You are right, but the deer biologist does not need real time numbers to set next year's county limits. My guess is along about March or April he will start working on 2013-14 season bonus limits.

I think this is the same way that they are doing it now..

INDIANA DEPARTMENT OF NATURAL RESOURCES

Bloomington

DEPARTMENT MEMORANDUM DATE: 2/22/01

TO: Fish & Wildlife Personnel FROM: Jim Mitchell


SUBJECT: Interpretation of County Deer Data Statistical Sheets

I have been asked to provide a few comments about how I look at the available deer data when trying to predict: 1. what has been happening to a county’s deer herd and 2. what will likely be the effect of choosing different bonus county quota options.

We should first recognize that we have several semi independent indicators of the trend of each county’s deer herd that will often will lead to conflicting predictions. Thus the trick is to decide how to best resolve the conflicts or to decide which indicator to ignore when they offer substantially different predictions. It is relatively rare when every piece of data agrees as to the trend of the herd. Additionally any prediction in population trend is only as good as the assumption that conditions of data collection are constant. For example, we assume that misrepresentation of county of harvest is a small constant percent relative to the total harvest for the county. If differences in quotas through time (1 vs A vs 3) cause misrepresentation of county of kill to vary widely, then bad data will lead to bad predictions. Likewise if a check station doesn’t send in data for 1 year or writes down the wrong county for a week etc, bad data will cause bad predictions.

The first data that I look at is the trend in the antlered harvest. Since we have relatively constant numbers of hunters and relatively constant rules on antlered harvest, as a 1st approximation the trend in antlered harvest should parallel the trend in deer population. Since very few hunters ever took more than 1 antlered deer with a bow and 1 with a gun, the change in these regulations in the mid 90's really had no effect on whether harvest trends parallel population trends. (Hunter surveys have shown that only 10% of our hunters take more than 2 deer per year including all seasons and both sexes. Since approximately 65% of the harvest is antlerless, most of these hunters taking multiple deer are taking a combination of antlered and antlerless deer.)

The next thing that I look at is whether there has been a substantial change in the number of antlerless deer taken per year. Each year we find that approximately 27% of the antlerless take is comprised of button bucks (round to 25% for ease of calculations). Thus if a county takes 100 antlerless deer in 1990 that means that approximately 25 males were removed and were unavailable to show up in the antlered harvest in 1991. Let’s assume that the population remains constant but we change the bonus quota and instead allow 600 antlerless deer to be taken in 1990. Then approximately 150 males were removed and are unavailable to show up in the 1991 antlered harvest. The bucks were merely taken at different ages. Thus if the county has widely varying antlerless harvest, I consider a modified antlered trend that is created by adding 25% of the previous year’s antlerless harvest to the current antlered harvest. Unless the antlerless harvest varies widely, I ignore the impact of antlerless harvest on subsequent antlered harvest.

The next issue is how any change in antlerless harvest relates to changes in bonus permit quotas. A change in antlerless harvest under a constant bonus quota would be indicative of a change in population. However, a change in quota will confound the correlation of a change in antlerless harvest to a change in population trend. As we try to sort out the impact of changing quotas, we need to keep in mind that for a constant deer population, changing from an A to a 1 has a significant impact on antlerless harvest (generally will increase harvest by 2 to 3 times) while changing from 1 to 2 will have a much smaller impact and changing from 3 to 4 will have a very small impact. The decreasing effect of higher quotas is predictable from the low numbers of hunters who take multiple deer as discussed above. In general, changes in antlerless harvest are the hardest data to interpret unless the quota has been constant for several years. Obviously changing from an A to a 0 would have the biggest effect on antlerless harvest of any quota change and eliminating any antlerless harvest in the firearm season will lead to rapid herd growth. Such an extreme change in quota should be reserved for a unique situation where disease or other factor requires a major rapid increase in herd size.

Trends in accident rates, accidents per billion vehicle miles and number of damage reports generally parallel the trend of the deer population and are especially useful in evaluating the population trend since these indicators are independent of the hunting regulations / hunting conditions.

The percent antlerless in the harvest generally indicates how much pressure we are putting on the antlerless herd and thus is an indicator of whether the herd can be expected to grow. While a given percent antlerless would have a different effect in counties or states with greatly different pressure on the antlered deer, for the amount of pressure that we are putting on our bucks we find that 60% antlerless generally is the breaking point between growing or declining herds. If the % antlerless increases 5 or more % above 60%, our herds generally decline rapidly while if the % antlerless harvest declines 5 or more % below 60% our herds generally grow.

The percent 1.5 yr old males in the harvest is blank for a given year unless at least 15 1.5 yr old males were checked for the county at biological check stations that year. If the percent (not number) of 1.5 yr olds shows a significant decline for a single year, that most probably is the result of a declining herd due to high antlerless harvest (remember the 27% button bucks). The way this works is that we still have a relatively large number of older bucks due to the previously high herd but have low recruitment of 1.5 year olds due to the decreasing herd and due to the high antlerless harvest. Retention of older bucks coupled with the lack of recruitment of young bucks causes the % young bucks to decline. This is an important additional indicator of population trend! On the other hand, if we are simply merely putting a lot of pressure on the bucks, then few will live beyond 1.5 years. In this case the % 1.5 yr olds will increase and remain high through time.

After we look at all of the above, we then can estimate whether the herd is growing or not and where it stands relative to the previous 10 years. Then we turn to deciding whether to increase or decrease the antlerless harvest. As indicated above, a change to or from an "A" will significantly change the number of antlerless deer taken while any other change will have a much smaller effect. Regardless of the absolute deer population, if we want to increase antlerless harvest we need to liberalize the quota and vice versa. Thus the quota is primarily related to where people want to hunt (hunting demand) and secondarily related to where the herd is relative to desired level. We have counties with large herds and high hunting demand that have a low quota and vice versa.

Finally we need to keep in mind that rapidly fluctuating quotas make harvest data interpretation difficult and are not popular with the public. When in doubt, make changes progressive through time. The desire to avoid rapid large changes in quota also applies when considering setting a county quota at 0 which would need to be balanced by a much higher quota in a short time after the herd significantly grows.

The last 2 data sets to check your recommendation against are landowner and hunter attitude data. Keep in mind that we are trying to balance the herd so that both sides win something and neither side is sacrificed for the other’s desires.

Yep!..insurance companies will be lobby legislators for higher quotas along I-69...paying too many claims