Data Collection

[DPinTN]

As managers, what data do you collect and what indices do you feel are most important to track historically? We have kept harvest data (age, weight, score, lactation etc) and observation data but I'm always wondering if we are missing something. Dr Craig Harper talked to me about the importance of kidney fat index and that's one we haven't collected.

Saw this article online and the linked study got me thinking about data correlation. https://southeastwhitetail.com/2024/07/28/qdm-data-within-jawbones/

https://naturalresources.tennessee.edu/wp-content/uploads/sites/24/2024/06/Correlating-antler-size-with-female-body-mass.pdf

 

[BSK]

From a herd management perspective, some of the data I would highly recommend are:

Harvest Data

(for all deer)
Sex
Age
Live and/or dressed weight (make sure to be consistent)

(for females)
lactation status

(for adult males [1 1/2+])
Antler points
Outside spread
left and right beam lengths
left and right basal circumference
gross score


Observation Data

number of bucks, does, fawns, and unidentifiable deer observed

(for bucks)
estimated age
number of points

I would also highly recommend collecting some sort of unit of time, such as hours hunted or just number of hunts. I've looked at my data analyzed by "per hunting hour" versus "per hunt" and the trends are very close.

 

[BSK]

From the harvest data, the trends to watch are average body weights per age-class (for both males and females), percent of does lactating per age-class, average antler points and gross score of bucks by age-class.

From the observation data, observed adult sex ratio, observed fawn recruitment, total deer observed per unit effort, bucks observed per unit effort, bucks of each age-class observed per unit effort.

[Note: Observation data can be heavily influenced by many things and does not necessarily represent actual population numbers, but it absolutely does track hunter success/satisfaction quite well. In essence, are hunters seeing more of the desired deer per unit effort, which is great measure of hunter experience/satisfaction]

 

[BSK]

I CANNOT stress enough the power of trail-cameras for monitoring herd composition and population. In my opinion, the trail-camera and the ability to run photo censuses is the greatest management tool available. I realize owning enough cameras to run a census, the amount of labor involved in a census can be a daunting task, but the data collected is invaluable. And although the late summer baited census (the way the system was originally designed) produces useful data, I highly recommend running a season-long running census without bait. Who is living on your hunting property in late summer might be very different than who is living on your property during the hunting season. And it is the hunting season population that is most important, as they are the only deer you can hunt and manage.

 

[BSK]

From the Observation Data, you can produce the standard analyses, such as Observed Adult Sex Ratio (first graph below) and Fawn Recruitment Rate (second graph below). But sometimes you need to be creative to see things of interest. The third graph below is the percent of observed bucks that are 2 1/2 or older. This is a decent indicator of buck age structure. The fourth graph below is something few managers think about, and that is the average number of points of observed yearling bucks. Yearling buck growth is heavily influenced by habitat conditions, hence the antler growth of yearlings is a great indicator of habitat quality THAT YEAR. And although some yearlings observed on a property came from "somewhere else" (yearling buck dispersal), tracking antler growth of yearling bucks does tend to produce a pretty good picture of local habitat quality.

 

[BSK]

With season-long photo census data, all sorts of critically important hard data can be tracked, especially deer population by sex and age, as well as buck age structure. The first graph below is the population by sex and age (bucks, does, fawns) over time. The second graph is the same data stacked to produce a total population. This graph was critical in identifying the trend of - on a hardwood dominant property - the population flourishing every time timber was harvested, with the population peaking about three years post timber harvest right when food sources and cover peak. The last graph is the actual buck age structure for the same property. Relying on Observation Data for these trends is very "iffy." Only camera data can show you realistic hard numbers.

 

[Ski]

I CANNOT stress enough the power of trail-cameras for monitoring herd composition and population.

Relying on Observation Data for these trends is very "iffy." Only camera data can show you realistic hard numbers.

100% absolute ^.

Observations, especially while hunting are anecdotal conjecture at best. The only way to quantify it is keeping some semblance of consistent record, and the data collected from trail cams is HUGE in that regard.

 

[BSK]

100% absolute ^.

Observations, especially while hunting are anecdotal conjecture at best. The only way to quantify it is keeping some semblance of consistent record, and the data collected from trail cams is HUGE in that regard.

Before trail-cameras and the development of the camera census technique were developed, all we had to go on was Observation Data. Now, I don't use Observation data for much. I basically use it for tracking the "hunter experience." In essence, how often are hunters experiencing certain things, such as seeing deer, seeing a buck, seeing a "shooter" buck, etc.

Below are graphs for "older" (2 1/2+ year-old) buck observation rates during November and 3 1/2+ year-old buck observation rates during November. November is peak buck activity for this property. These graphs don't mean anything biologically. They are just a measure of hunter experience.

 

[DPinTN]

Bryan - looking at last year's doe harvest we really hammered them late season (late Dec and early January). As such we had a high number that weren't lactating. Is this something you expect as mothers dry out post wean and how do you account for that in years with a large harvest number coming in late season?

 

[BSK]

Bryan - looking at last year's doe harvest we really hammered them late season (late Dec and early January). As such we had a high number that weren't lactating. Is this something you expect as mothers dry out post wean and how do you account for that in years with a large harvest number coming in late season?

I try to separate the doe harvests by month and just compare same time-period data. For example, only look at lactation for does killed November and earlier. You can definitely run into does killed late season that would have been lactating if they had been killed say MZ season.

 

[DPinTN]

I try to separate the doe harvests by month and just compare same time-period data. For example, only look at lactation for does killed November and earlier. You can definitely run into does killed late season that would have been lactating if they had been killed say MZ season.

Yep... we killed 44 does last year.

Post 12/18 - 1 of 20 harvested was lactating

Prior to 12/18 - 19 of 24 were lactating

 

[BSK]

Not surprising at all.