EXPOSED
Roughly half the job is screen work AI already does competently — literature reviews, species distribution modeling in R, population statistics, permit paperwork, grant boilerplate, and the endless technical reports and NEPA/ESA documentation. The other half is genuinely embodied: mist-netting, radio-collaring, scat and pellet transects, necropsies, boat and backcountry surveys in weather that doesn't cooperate. There's no license gate — 'wildlife biologist' is a job description, not a protected title — and camera traps plus automated bioacoustic and image classifiers are already shrinking the labor needed per survey.
Nearly all of this fall was the 2020 shock. It has been climbing back since.
Median pay $63,270 → $76,780 -2.9% in real terms
This line is counted by the Bureau of Labor Statistics — the one figure on this page that isn't a judgement of ours. Headcount moves on demand, offshoring, demographics and the business cycle, and automation is one term among several, often not the loudest.
So a falling line is not evidence that AI did it, and a rising one is not evidence that it won't. Both happen in this register: some occupations resist automation and shrink anyway, others are highly automatable and keep growing. The marked year is 2020.
BLS projection, 2024–2034
+1.6% 18,200 → 18,500 on the projections basis
Growing, and only partly exposed
The BLS expects +1.6% more of these jobs by 2034, and at 47/100 the work is only partly exposed — some tasks are automatable, the core of the job is not. Nothing here is in tension.
Different clocks. The score is what current AI could do to this work today. The projection is how many of these jobs will exist in 2034. Everything between the two — how fast employers actually adopt, whether demand grows in the meantime — is why they can point opposite ways without either being wrong.
~1,400 openings a year on average, including replacing people who leave.
AquaristZoologistEthologistNaturalistBehavioristLimnologistMammalogistEntomologistNematologistHerpetologistIchthyologistLepidopteristOrnithologistCell BiologistFish BiologistFish CulturistProtozoologistCryptozoologistShark BiologistAnimal BiologistField NaturalistMarine BiologistMarine ScientistAquatic Biologist
Holding it up: embodiment . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier Camera-trap image sorting, BirdNET-style acoustic ID, occupancy models in unmarked, and the first draft of a biological assessment are all things software now does at speed, but nobody has automated setting a mist net at the right height in the right flyway, sexing a sedated bear, or reading a fresh browse line — the 11 reflects that the field half stays and the analysis-and-writing half is already leaking.
Hands-on in uncontrolled environments A 14 covers work where the sampling site is the office: hip waders in spring runoff, elk capture from a helicopter, scat transects on unmaintained trails, necropsy on a carcass in whatever condition you found it — uncontrolled ground and weather, though not the sustained physical extremity of a smokejumper or commercial diver.
No licence, no signature requirement There is no state licensure for zoologists; the 4 exists only because collection, banding, and Section 10 take permits are issued to a named individual with demonstrated competency, so USFWS or a state agency can pull your authorization — but the permit follows the project, not a protected title, and a technician or contractor can hold it.
Meaningful discretion The 11 sits on real calls — declaring a nest active, setting a take threshold, deciding a population estimate is robust enough to underwrite a listing or delisting decision — but those calls go through agency review, peer review, and established survey protocols before anyone acts on them, so you are rarely the last signature.
The verdict above describes this occupation as a whole. Almost nobody does the typical version of a job — tick what's actually in your week and see how your own mix sits.
Your task mix speaks to task resistance (11/20 here) — how much of the day's work current AI already does. That is the dimension the boxes above are about.
It cannot move the other three. Liability shield (4/20) is whether the law requires a licensed human to sign. Trust premium (7/20) is whether buyers specifically pay for a person. Judgment and accountability (11/20) is whether the role exists to own consequential calls. Those are facts about the occupation's standing, not about which tasks are in your week — a paralegal who does only trial exhibits still holds no licence. Together they are 22 of this occupation's 47 points (47%).
Embodiment (14/20) is also a property of the work rather than the worker, but we don't tag individual tasks as physical or not, so the picker can't tell you anything about it. That's a limit of this tool, not a claim.
Did we get the list right? Tell us what's missing — the tasks are written from the outside, and you're reading this from the inside.
Foresters EXPOSED
The moves above are yours to make. This is the other half: what would have to change in the world for the occupation itself to score higher. None of it is in any one person's gift, but it is where the floor actually comes from. Scores here are not a one-way ratchet. Only two of the five dimensions — task resistance and embodiment — track what machines can do. The other three track law, what buyers will pay for, and who is answerable, and those move in both directions, often in response to the same pressure AI creates. If every lever below landed, this occupation would score around 67/100 — SAFE.
Genuine two-tier job: if classifier pipelines absorb the ID/counting/report-drafting tier, what remains is study design under sampling bias, defending methods at deposition or in litigated ESA challenges, and animal-handling judgment (anesthesia dosing, euthanasia, capture-myopathy calls) that no model performs. Watch for job postings shifting from 'GIS and R' to 'design and expert testimony'.
ESA Section 10 recovery/incidental-take permits and Section 7 biological assessments already require a named, agency-approved qualified biologist; the concrete escalation is USFWS/NOAA or state agencies (e.g. CDFW's designated 'Approved Biologist' lists, Army Corps mitigation monitoring conditions) formalizing a signed attestation of personal field verification for survey data used in take permits, plus explicit rejection of unverified AI/bioacoustic classifier output as sole evidence. Similar in motion: state wetland-delineator and arborist certification regimes, and USFWS bat/eagle survey protocols that name the permitted surveyor.
IACUC and state wildlife-handling permits assigning a named individual responsibility for animal welfare outcomes, plus expanded litigation exposure where a biologist's determination gates a project worth hundreds of millions (offshore wind right-whale monitoring is the live example) — the call becomes personally attributable rather than an agency product.
Rises only relatively, and only if protocols codify physical requirements automation can't meet: mandatory in-hand capture for disease sampling (CWD, white-nose, HPAI surveillance), necropsy and biobanking, or agency rules that camera-trap and eDNA results require paired physical verification transects.
The Wildlife Society's Certified Wildlife Biologist (CWB) credential moving from voluntary to a procurement requirement — e.g. federal/state contract solicitations or a state statute requiring CWB or equivalent for signed biological reports, the way Professional Geologist licensure spread state-by-state after being merely voluntary.
The limit. Even with all of these, this stays a small, grant- and appropriation-funded field with no protected title; liability gains attach to the permit-signing subset, not the bulk of survey and reporting work. Trust premium is omitted deliberately — buyers here are agencies and developers buying regulatory clearance at lowest cost, and there is no realistic route to them paying extra for human authorship.
| Seattle-Tacoma-Bellevue, WA | 720 | $96,450 +26% |
| Portland-Vancouver-Hillsboro, OR-WA | 350 | $89,880 +17% |
| Minneapolis-St. Paul-Bloomington, MN-WI | 310 | $61,050 -20% |
| San Francisco-Oakland-Fremont, CA | 300 | $99,230 +29% |
| Tampa-St. Petersburg-Clearwater, FL | 300 | $55,050 -28% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 270 | $104,330 +36% |
| Olympia-Lacey-Tumwater, WA | 250 | $82,500 +7% |
| San Diego-Chula Vista-Carlsbad, CA | 250 | $93,500 +22% |
| San Jose-Sunnyvale-Santa Clara, CA | 40 | $129,940 +69% |
| Santa Cruz-Watsonville, CA | 30 | $122,170 +59% |
| Gulfport-Biloxi, MS | 30 | $113,800 +48% |
We have no reported case of a named organisation automating this occupation. Not one deployment, not one announcement.
That is worth saying out loud next to a score of 47. The verdict above is about what the work exposes — what current AI could do to these tasks. It is not a claim that anyone has done it. For this occupation those two things have come apart completely: the capability argument is on this page, and the evidence column is empty.
Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.
Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.