Much data work rests on an unspoken belief: today's readable source will still be readable tomorrow. That often fails for deer records. The finest detail, whether a record for each registered animal, unit-level tables or a county's historical series, frequently has the shortest life. Each season, Minnesota replaces its registration view and erases the previous season's animal-level information. North Dakota's files for previous years quietly produce errors. Wisconsin removed eleven counties outright from the public series, as a separate paper describes. We see no evidence that these changes were intentional; their causes lie within the agencies' publishing systems, beyond our view. The result is clear, though: many of the most detailed deer records are perishable. Saving them as soon as they turn up is the sole protection.
KEY FINDINGS
- Minnesota publishes deer registrations as a snapshot of the current season. Its animal-level feed assigns each registered deer a separate row, roughly 186,000 for the latest season, then replaces the data each year. Skip that season's download and you lose its individual-deer detail.
- Our reproduced registered-deer count for Minnesota's most recent season totals 186,333, calculated by adding the deer-permit-area counts. The summary also has a gap: 2014 is missing entirely from the source's season sequence, between 2013 and 2015.
- North Dakota adds another failure: releases for earlier years give access errors. After a new file is posted, the previous season's file can be out of reach. Access rolls from season to season rather than building a lasting collection.
- Wisconsin cut eleven Northern-Forest counties out of its public county series during a 2025 rebuild, a change covered separately. It shares Minnesota's and North Dakota's failure pattern, but here the map contracts as opposed to a time window advancing.
IWHAT PERISHABLE MEANS
Replaced instead of preserved
Records that last add each new season while retaining earlier ones, so their history grows. Records that perish work as moving windows: a new period arrives and a previous period drops away. You will not notice the difference until you need the missing portion. Both publishing approaches occur with deer records. Statewide harvest figures often appear in series covering several years. Minnesota's annual reports, for instance, list a sequence of seasons. Some sources with finer detail display only the current season as a live view. Minnesota's individual-deer registration feed is one such source; we located no collection of its earlier versions. A late visit does not produce an error labeled “deleted.” It delivers less history and less detail, without showing that more once existed.
IIMINNESOTA: A SNAPSHOT, NOT AN ARCHIVE
A separate row for each deer, replaced annually
Minnesota provides the clearest case. The state’s registration feed covers individual animals and shows the current season (think of a separate row for each registered deer, roughly 186,000 rows for the latest season). Separate versions are not saved each year as an archive of individual-deer files. The record lives in the feed, which changes with the season. Save it once the season ends and you keep that year’s individual-deer details. Wait, and the following season replaces the view. For the 2025 season, we reproduced an aggregate of 186,333 registered deer by adding the totals from every deer-permit area. Annual reports retain statewide and permit-area totals. Replacing the feed removes each deer’s weapon type, permit area, sex, age class and kill date from the live view. Our series of summed permit-area totals is missing a value for 2014 because that season is absent from the annual report files we added together. The 2014 report file returns 404, but the missing total can be recovered from the 2015 report. The Minnesota wildlife agency’s statewide Table 1 in both the 2015 and 2025 harvest reports lists 139,442 as the total registered harvest for 2014.
The statewide count remains available. The individual-deer rows supporting it exist only in the current seasonal view. Download them now. There is no version history for that feed, although annual state reports retain totals for the whole state and for permit areas.
IIINORTH DAKOTA AND WISCONSIN
A moving time window and fewer counties on the map
The Minnesota feed illustrates one way records perish. North Dakota illustrates another: Game and Fish release pages for previous deer seasons produce Access denied errors, even as pages for the current season open. The previous season's release can therefore become inaccessible. Readers receive no notice of deletion; the requested release is replaced by an Access denied message. Wisconsin illustrates the third pattern. Its 2025 rebuild removed eleven Northern-Forest counties, reducing county coverage in the public harvest series from 72 to 61. Here, perishability changes the record's geographic reach: the map shrinks instead of the time window advancing. (We reconstructed the Wisconsin series using archived tables, as described in a separate paper.) Taken together, these cases show that public deer records can shift or grow harder to access.
IVCAPTURE WHEN YOU FIND IT
Saving data before it disappears
When the most detailed data can disappear without notice, we need to adjust how we keep it. A public feed with fine detail cannot be counted on like a library you can revisit; collecting it is a harvest with its own season. That leads to our approach: save each version together with the date we retrieved it. Never count on being able to open a source again just because you opened it once. We download Minnesota's individual-deer feed again after every season closes, because the following year's feed will cover only that following year. We rebuilt Wisconsin's deleted county data using an archive that could also disappear during the next rebuild. Our concern is the guarantee attached to “public”. The word tells us only that an agency made the data available. It gives no assurance of access in the future. We therefore keep a copy as soon as we find the data.
NOTES AND SOURCES
- We reproduced Minnesota's seasonal registered-deer figures from consolidated harvest records by adding registrations across deer-permit areas. The newest season totals 186,333. The annual report files behind those sums omit 2014. Requests for the 2014 report produce 404; the 2015 report lets us recover the missing figure. The 139,442 total comes from the statewide Table 1.
- Minnesota's registration feed is described as a snapshot with one record per deer for the current season, replaced each year, with roughly 186,000 records in a season. This description reflects a documented characteristic of the source; a record-by-record count is not reproduced here. We reproduce the aggregate by summing the counts and treat the detail for each deer as temporary data to retrieve again each year after the season closes.
- Documented publishing behavior includes access errors on North Dakota releases for earlier years. It also includes Wisconsin removing eleven Northern-Forest counties in 2025 from the county series it publishes. A separate paper covers our reconstruction of the Wisconsin records. North Dakota provides context here; its surveys are reported at the statewide level rather than county by county.
- Limits: the way sources publish information makes records perishable; that description does not apply to deer herds. Aggregated harvest counts are governed by effort and regulations. The figures are a snapshot tied to the corpus dated 2026-07, reflecting what each source provided when captured.
Fully Drawn Research is an independent data analysis desk, not affiliated with any state wildlife agency, transportation agency, mapping provider or outfitter. Figures are Minnesota Department of Natural Resources public registration data analyzed independently by FDR; the summed registered total is current to the 2025 season. Statements about source perishability (annual overwrite, expiring prior-year releases, deleted county series) describe documented publishing behavior of the respective agencies. North Dakota is discussed contextually and is not represented at county grain. FDR is an independent data analysis desk, not affiliated with any state wildlife agency.
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