This python script performs simple sorting and prioritizing on wildlife management unit (WMU) data in NY. The data is from 2016 and for the 2017 deer season. I used it to help me select units in which to apply for deer management permits -- antlerless only bonus tags.
virtualenv venv
. venv/bin/activate
pip install -r requirements.txt
Pandas: "Powerful data structures for data analysis, time series, and statistics"
Two data files are used to generate tables of NY deer unit statistics.
wmu area dmp_target dmp_per_sq_mile success_avg res_1 res_2 nres_1 nres_2
1C 903.3 max NA 12.8 HIGH HIGH HIGH HIGH
3A 694.3 0 0.0 NA NONE NONE NONE NONE
3C 316.1 2000 6.3 13.9 MED NONE NONE NONE
...
This file contains dmp-specific information.
- wmu: wildlife management unit
- area: total land area of the WMU in square miles
- dmp_target: the target number of distributed dmp tags. 'max' indicates that the NY DEC will distribute as many as possible.
- dmp_per_sq_mile: the dmp density for the WMU
- success_avg: success average of dmp tags
- res_1: first-choice resident tag selection chance
- res_2: second-choice resident tag selection chance
- nres_1: first-choice non-resident tag selection chance
- nres_2: second-choice non-resident tag selection chance
Source data was hand transfered from the NY DEC website. A few vim macros normalized the dataset for analysis.
From the website, per NY DEC 2017:
Statewide Total: 625,300 excluding units without DMP targets.
High = more than 2/3 of applicants receive a DMP.
Medium = between 1/3 & 2/3 receive a DMP.
Low = less than 1/3 of applicants will receive a DMP.
PP Req = only applicants with preference points have a chance of receiving a DMP. May require 1, 2, or 3 preference points to be selected.
LO/DV = only qualifying landowners (greater than 50 acres) and veterans with disabilities will receive a DMP.
None = No DMPs are available.
NA = DEC is not authorized to issue DMPs in these units.
Notes:
WMU 1C is bowhunting-only from October - December. A special permit is Required during the January Firearms Season.
WMUs 3S, 4J, and 8C are bowhunting-only during all deer seasons.
Antlerless-only Bonus DMPs are available in WMUs 1C, 3S, 4J, and 8C for hunters who fill a DMP in these units.
Preference points increase the chances of selection but do not guarantee issuance. Preference points are won and lost on the 1st DMP selection. If preference points are required on the 2nd permit, only applicants who were denied a 1st permit are eligible.
Qualifying landowners and veterans with disabilities will receive their 1st choice DMP in all open WMUs.
wmu bucks_taken buck_sq_mile total_deer total_sq_mile
1C 1321 1.5 3207 3.6
3A 652 0.9 774 1.1
3C 692 2.2 1020 3.2
...
The total taken statistics file provides information about deer harvest in general (for 2016).
- wmu: wildlife management unit
- bucks_taken: the number of antlered deer harvested in the WMU
- bucks_sq_mile: the antelered take density for the WMU
- total_deer: The combined antlered/antlerless take count for the WMU
- total_sq_mile: The combined take density for the WMU
Source data was hand transfered from the NY DEC website. A few vim macros normalized the dataset for analysis.
From the 2016 harvest summary:
The values presented here are calculated estimates.
The precision of the statewide take estimate is within 1-2 percent.
To be honest I mostly did some rough hacking via ipython :)
I've put together something a little more traditional too:
python -m dmp.py
As set up, dmp will return sorted tables of three measures:
-
an arbitrary-unit value 's1': (deer taken / sq mile) * (dmp success avg) * (num target dmps)
-
total combined take density.
-
dmps per square mile (5 if max total dmps)
- the max dmps throw a wrench into the match, but 5 is a fair, perhaps conservative value
python -m dmp
**** Sorted by s1: (deer taken / sq mile) * (dmp success avg) * (num target dmps)
area dmp_target dmp_per_sq_mile success_avg res_1 res_2 bucks_taken buck_sq_mile total_deer total_sq_mile s1 dmps_sq_mile
wmu
3M 749.2 35900 47.9 10.9 HIGH HIGH 2880 3.8 6781 9.1 1.000000 47.9
7J 838.9 31300 37.3 11.0 HIGH HIGH 2385 2.8 6164 7.3 0.705826 37.3
...
**** Sorted by deer taken / sq mile
area dmp_target dmp_per_sq_mile success_avg res_1 res_2 bucks_taken buck_sq_mile total_deer total_sq_mile s1 dmps_sq_mile
wmu
3M 749.2 35900 47.9 10.9 HIGH HIGH 2880 3.8 6781 9.1 1.000000 47.9
4C 164.8 1400 8.5 23.2 MED NONE 725 4.4 1331 8.1 0.073882 8.5
...
**** Sorted by dmps per square mile (5 if max total dmps)
area dmp_target dmp_per_sq_mile success_avg res_1 res_2 bucks_taken buck_sq_mile total_deer total_sq_mile s1 dmps_sq_mile
wmu
4J 148.9 max NaN 9.3 HIGH HIGH 223 1.5 495 3.3 0.064165 50.0
3S 430.8 max NaN 9.8 HIGH HIGH 562 1.3 1259 2.9 0.171912 50.0
...