Joseph HeinrichSoftware engineer
← All Side Quests
Oct 20, 2026Data

What Entered the Record

See when national parks sent wildlife cases for testing, and how the records differ.

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How to use this project

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How to explore

National parks can submit sick, injured, or dead wildlife for testing. These files show what entered that reporting system; they do not count every animal or measure the chance of harm in a park.

  1. Start with one park

    Open Rocky Mountain National Park or choose another park unit with at least 10 animal records.

  2. Check the active years

    Select a year in the timeline to see when its records fall across the calendar.

  3. Read the recorded cause

    Choose one cause field and note how many records are blank or marked unknown.

  4. Compare park files

    See what share of each park's full file uses the same cause, then open another park.

Animal record
One unique animal-detail entry in the source; it can represent one animal or a recorded group.
Observation event
One reported event that can contain more than one animal record.
NPS unit
A National Park Service place, including national parks, monuments, battlefields, seashores, and other designations.
Active year
A calendar year with at least one animal record in this data package.
Recorded cause
The cause field attached to the animal record before laboratory findings; many entries are blank or unknown.
Side Quest / DataOpen Rocky Mountain National Park, choose a calendar year, compare its monthly and cause patterns, then carry one cause into the cross-park ranking.

Wildlife case records · 1990–2026

What entered the record

See when national parks sent wildlife cases for testing, and how the records differ.

A sick, injured, or dead animal can become a park case file. These records show what was submitted for testing. They do not count every animal or measure the chance of harm in a park.

NPS · WILDLIFE HEALTH
Unit fileROMO

Rocky Mountain
National Park

Animal records
1,301
Active years
25
Largest month
January
Cause named
22.8%

Record volume reflects reporting and testing activity, not wildlife population size.

FOR COMPARISON
01 · Choose a park

Start with one park’s submitted records.

The list includes 48 National Park Service units with at least 10 animal records. Your choice updates the time, month, and cause views.

CO

Rocky Mountain National Park

Jun 2, 2001 to Jun 13, 2025

Animal records
1,301
Observation events
1,005
Years with records
25

An observation event can contain more than one animal record. Counts below use animal records so different animals in one event remain separate.

02 · Choose a year

First, check when the file was active.

Each bar is one calendar year. Select a year to update the monthly pattern and recorded causes, or keep the whole file open.

Current view25 active years1,301 animal records
All recorded years

Records by month

Read clockwise through the year. A taller mark means more animal records in that month; it does not mean wildlife was more likely to be harmed.

January is the largest month in this view. It contains 418 records, or 32.1% of the selected total.

03 · Read the recorded cause

Then, see what the case file says happened.

These are the source’s cause fields before laboratory findings. Choose a cause to carry it into the park comparison.

04 · Compare park files

Finally, compare the same cause across parks.

The bars show the share of each park’s full file assigned to hit by car. Select a row to open that park.

Highest shares among 48 park filesHit by car

A larger share can reflect what staff noticed, submitted, or recorded, as well as what happened to wildlife. The package does not provide animal populations, visitor traffic, search effort, or a complete record of every event.

What the records can support

This is a view of a reporting system, not a league table for wildlife safety.

The National Park Service package contains 4,955 animal records inside 4,192 observation events. This experience keeps the 4,640 records from 48 units with at least 10 records, so the comparisons have enough entries to read. Exact animal locations, laboratory accessions, internal case numbers, and diagnoses are excluded.

I discovered the April 2026 Wildlife Mortality and Morbidity Observations package through the allowlisted Data.gov catalog, then verified the official National Park Service data and metadata files and the catalog's CC0 1.0 license on October 20, 2026. A deterministic standard-library reducer pins the exact CSV by byte count and SHA-256, separates repeated sample rows into unique animal-detail records, and publishes only park-level aggregates.

Why this exists

The question

How do the timing and recorded causes of submitted wildlife cases differ among the National Park Service units with at least 10 animal records in the April 2026 data package?

What to try

Open Rocky Mountain National Park, choose a calendar year, compare its monthly and cause patterns, then carry one cause into the cross-park ranking.

Method and limits

About the data

I discovered the Wildlife Mortality and Morbidity Observations Data Package, April 2026 through the allowlisted Data.gov catalog and followed it to the National Park Service Integrated Resource Management Applications data store. The catalog names the National Park Service as publisher, dates the package to April 13, 2026, and applies CC0 1.0. The official metadata says the package covers records from August 14, 1990 through February 25, 2026 and defines the park coordinates as unit centroids rather than animal locations.

The reproducible standard-library Python builder downloads the exact 11,323,608-byte CSV and verifies SHA-256 `cfe2a52fefe01656e9b691c0f97e9da5e9adae5449f1f5883e92737d3e233070`. It checks 23,859 source rows, the required schema, 4,192 unique observation events, and 4,955 unique animal-detail records. Repeated rows describe samples, submissions, diagnoses, tests, and tissues attached to the same animal detail, so the reduction counts each `detailID` once and verifies that the retained park, date, count, sex, age, and cause fields stay fixed within that detail.

The 44,098-byte static snapshot has SHA-256 `b95eec60de9148fdd8bb56879b0a698bf4d6748038a19d95ac4d9e9812befe85`. It retains aggregate year, month, and cause counts for the 48 National Park Service units with at least 10 animal records, covering 4,640 of the 4,955 animal-detail records. It excludes exact source rows, animal names, scientific names, park case numbers, NPS identifiers, sample and submission identifiers, laboratory names and accessions, tissues, tests, results, diagnoses, ages, sexes, coordinates, and individual counts. The page imports the snapshot and makes no runtime request.

Record volume is not a wildlife population, mortality rate, disease rate, survey, or safety score. Parks differ in reporting dates, testing programmes, observation effort, species, visitors, roads, management work, and missing fields. A cause field records what the case file says before laboratory findings. Blank and unknown causes remain separate, and 2026 is incomplete because the package ends on February 25. The data can show the shape of the reporting system but cannot establish why parks differ or how often harm occurred among all animals.

Skills used

  • Data analysis
  • Data engineering
  • Statistical reasoning
  • Visualization
  • Information design
  • Interaction design
  • Visual design
  • Creative coding
  • Product thinking
  • Editorial storytelling
  • Accessibility
  • Performance
  • Systems design

What the data shows

  1. The 48 included park units account for 4,640 of 4,955 animal records. Rocky Mountain and Wind Cave alone contribute 2,089, or 45.0% of the included records, showing how unevenly the package is distributed across parks.
  2. Rocky Mountain National Park has 1,301 animal records across 25 active years. January contains 418, or 32.1%, while 1,004 records have no named cause because the field is blank or marked unknown or other.
  3. Shenandoah records hit by car for 233 of 274 animal records, or 85.0%. Gettysburg records management action or cull for 60 of 79, or 75.9%. Those shares describe the submitted case files, not the chance that an animal experiences either event.
  4. Canyonlands has records in only four calendar years, and 142 of its 144 animal records fall in January or February. That concentration signals a narrow reporting pattern; it does not establish a winter wildlife risk.

Sources

Data.gov catalog · National Park Service · CC0 1.0Wildlife Mortality and Morbidity Observations Data Package, April 2026 ↗National Park Service · CC0 1.0Wildlife Mortality and Morbidity Observations official package profile ↗National Park Service · CC0 1.0WHMMO data CSV ↗