PayCrunch Research · The exact AI playbook for your profession, sourced to the U.S. Bureau of Labor Statistics

PayCrunch AI Playbook · Science

The ecologist who stopped rebuilding the same report

$185,220top of the range in District of Columbia · middle $82,220 / yr
AI augments this role

Ecologists in the United States earn a median of $82,220 a year. Pay starts near $52,520. Pay reaches $185,220 at the top of the range in Washington D.C., the best-paying location for this work among those with at least 500 people in the job.

Source: U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025 (Environmental Scientists and Specialists, Including Health, SOC 19-2041). Last checked 9 September 2026.

Entry level
$52,520
Top of the range · District of Columbia
$185,220
Education
Master's degree in Ecology
Lower disruption Higher exposure AI augments this role
Entry · $52,520 Top of range · $185,220 (District of Columbia) Middle $82,220

Wages — U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025 (Environmental Scientists and Specialists, Including Health). Top of the range is the highest state-level figure among states with at least 500 people in the job. AI-impact rating is PayCrunch's editorial assessment. Updated September 2026.

🆕 New & Trending AI Tools for EcologistReviewed September 2026

We track new AI-tool launches every week and refresh this list — here’s what’s gaining traction for Ecologist work right now.

Julius AINEWFree / $20 mo

AI data analyst that runs statistics and charts from plain-language prompts.

How an Ecologist uses it: analyze datasets and generate figures without writing code

NotebookLMNEWFree / $7.99 mo

Google tool that answers questions grounded only in the documents you give it — with citations.

How an Ecologist uses it: load your own manuals, policies, or PDFs and ask questions that stay accurate to the source

ElicitFree / $12 mo

AI research assistant that finds and summarizes papers.

How an Ecologist uses it: run a literature review and extract findings across dozens of papers fast

ConsensusFree / $9 mo

AI search that answers questions from peer-reviewed research.

How an Ecologist uses it: get evidence-backed answers with the studies behind them

SciSpaceFree / paid

AI that explains papers and helps with literature review.

How an Ecologist uses it: decode dense papers and trace citations quickly

SciteFree / $20 mo

Shows whether other studies support or contradict a paper's claims (Smart Citations).

How an Ecologist uses it: check if a finding is actually backed by the wider literature before you cite it

ChatGPTFree / $20 mo

The most-used AI assistant — writing, analysis, research, and images from a plain-language chat.

How an Ecologist uses it: draft emails and documents, summarize long files, and get instant answers to on-the-job questions

ClaudeFree / $20 mo

AI assistant known for careful writing, long-document analysis, and coding.

How an Ecologist uses it: analyze big reports or spreadsheets and turn messy notes into clean, finished writing

Google GeminiFree / $20 mo

Google's AI assistant, built into Gmail, Docs, and Search.

How an Ecologist uses it: draft and reply inside Google Workspace and research without leaving the page

The truck is parked before the day heats up, and the site map is already creased from a pocket. You walk a line you marked yesterday, stop at each point, and write what is actually growing, nesting, or moving there, not what the proposal hoped would be there. An ecologist makes a living by paying attention outdoors and then defending that attention in data and prose. The glamorous version is a ridgeline at dawn. The ordinary version is a wet plot, a battery that died, a landowner waiting to know when you will be off the fence line, and a report that still has to be finished after the field kit is dry.

What a field day is for

Surveys are the core. You identify plants, animals, or communities, you record where they are, and you note the conditions that would make a second visit disagree with the first. Some projects are a single season of baseline work before a road, a restoration, or a conservation deal. Some are monitoring that returns to the same points so a change can be seen. You carry the method the project chose. You do not freelance a new one in the truck. You write down the deviations when weather or access forces a change. A beautiful memory of a bird does not count as a record. The record is the note someone else can audit.

Between trips you clean the files. Spreadsheets, maps, photos, and specimen notes have to agree. You flag uncertain identifications instead of guessing a rare species into existence. You call a botanist, a wildlife biologist, or a soil scientist when the puzzle on the ground is really theirs. Field ecology stays collaborative even on days you walked alone, because the report will be read by people who fund, review, or oppose the project. Your job is to make the evidence clear enough that a disagreement can be about the conclusion, not about a plot number copied wrong.

The report is where the field day earns its keep. You state the question the project asked, you describe the method in enough detail that another ecologist could repeat the visit, and you present results without burying a weak finding under adjectives. Maps and tables carry numbers you actually counted or conditions you actually scored in the field notes. Recommendations, when the contract wants them, stay tied to those results. A client may dislike a conclusion. Your duty is to make the conclusion traceable, not to sand it down until it pleases everyone in the room. That writing, more than the dawn photograph, is what senior people are paid to defend.

The places vary more than the habit. A wetland crew, a forest inventory, a coastal survey, and a city biodiversity project all end in a written product. You may work for a consulting firm that serves builders and public agencies, for a land trust, for a state or federal program, for a university lab, or for a company with land of its own. Access is arranged by the employer, the landowner, or the agency that controls the site. You follow that arrangement. Scientific curiosity does not authorize you to enter, to collect, or to launch a drone because a habitat looked promising from the road.

Degrees, and the licence nobody issues for the whole country

A bachelor's degree is the usual start, most often in ecology, biology, environmental science, or a close field that taught identification and a statistics course you stayed awake for. A master's degree is common for people who design studies, lead crews, or want research-leaning seats. The degree shows you can handle the science and finish a long piece of work. It does not replace a season of muddy data collection. Employers lean toward the graduate who can also run a survey line, speak plainly with a rancher, and come back with notes that match the photos.

There is no single national licence for an ecologist. No board issues one card that authorizes field ecology in every state. Hiring turns on the degree, the field record, and sometimes a professional registration that one state uses for a narrower kind of environmental practice. Those registrations, where they exist, belong to particular duties in that place. They do not add up to a national ecologist licence under another name. If a posting names a registration, read it as a rule for that duty, and confirm it with the employer rather than assuming the degree covered it. Preparation remains the degree, the field seasons, and writing that separates what you saw from what you hope.

Preparation without a national card

A bachelor's or a master's is the usual preparation. There is no single national licence that makes someone an ecologist in every state.

Who posts the work, and what they want to see

Consulting firms hire in bursts around field seasons. Public agencies hire more slowly and care that you can follow a protocol already written. Land trusts and other nonprofits often want science plus the ability to explain it to a board or a neighbor. University labs hire technicians on one track and hire faculty on another. Read the posting for how the year splits between sites and a desk. A role full of meetings and document packages is a different life from a role that puts you outdoors across three seasons. Believe the task list, not the adjective in the title.

Show a short list of habitats you can honestly identify, software you have used to map a site, and one report or thesis chapter you are proud to hand over. Name the crew lead who will say whether your notes were trustworthy. If you are new, a seasonal technician post is a legitimate start: you learn the method, you carry gear, and you discover whether you like the work once the novelty of being outside has worn off. The first months at a firm are usually someone else's protocol, strict file naming, and a senior who edits your prose until a regulator could follow it. Take the edits. A lyrical paragraph that hides a missing sample helps nobody.

Technician, crew lead, then the name on the report

Technicians collect. Crew leads decide the day's route, keep people safe, and notice when the method is drifting. Project ecologists design the study, manage the schedule, and write the report the client will circulate. Principal scientists review, set scope, and stand in the meeting where a conclusion is unpopular. Side paths include restoration planning, data management, and mapping specialist roles for people who would rather wrangle records than walk another transect. Teaching at a college is a different appointment, with its own search, and it should not be treated as the automatic prize at the end of consulting.

A durable career mixes field credibility with writing. The ecologist who only loves the truck eventually bottlenecks on the report. The ecologist who only loves the report loses the trust of the crew. Keep a simple record of project types and your role on each, and keep one writing sample current. When you want to lead, ask to draft a section before you ask for the title. Firms promote people whose sections survive review. Agencies promote people who can train a seasonal crew without turning the protocol into folklore. Either path still rests on the same base: a degree, field seasons, and no imaginary national licence to hide behind.

A wide May 2025 series, then the pay you can actually cite

Occupational Employment and Wage Statistics for May 2025 are the source here. The series is Environmental Scientists and Specialists, Including Health, and it is broader than a field ecologist. Health-related environmental specialists sit in the same published figures. Read the dollars with that wider group in mind. Entry pay is $52,520. The national median is $82,220. That range's high end is $185,220 in the District of Columbia, in the places with enough environmental scientists for a high end to be published. The District's $185,220 is that range high end. The District's median is separate: $132,620.

The District leads state medians at $132,620, which is $50,400 above the national median. California's median is $106,510. Massachusetts is $100,640. Washington is $98,300. Oregon is $97,440. Florida posts the lowest state median in this set, and the gap from the District's median to that low end is $71,790. Compare medians when you are comparing places. Compare the range high end only when you mean the far published edge in the District. Treating $185,220 as "what the District typically pays" confuses a top-of-range figure with a median, and it will make every other offer look artificially low.

From entry to the national median is $29,700. That gap fits a story of moving from a junior seat, still closely supervised, toward independent field and writing responsibility. From the national median to the District's range high end is $103,000. That second gap is the long tail of published pay, useful as context, reckless as a demand for a routine promotion. Use $52,520 to test a new graduate or technician offer. Use $82,220 to test a working ecologist at the national middle. Use $132,620 only for a District median comparison. Use California's $106,510, Massachusetts's $100,640, Washington's $98,300, or Oregon's $97,440 when those are the states on the offer letter. Use $185,220 only with the label high end of the range.

Holding an offer up to the right figure

Ask whether the salary is for a full year or for a field season with a gap in winter. Seasonal work can be a smart start and a misleading comparison if you set a six-month check beside an annual median. Convert what you will actually receive across the year, then place that total next to $52,520 or $82,220. If the firm expects you to lead a crew and sign sections of a report, an offer stuck at the entry figure is worth a calm challenge. The $29,700 between entry and the national median is the size of that step in the national data. Name the duties that match the higher number: study design, quality control of other people's notes, and a client who will hear the results from you.

Geography needs the same care. A move toward the District median is a $50,400 conversation relative to the national median, and it is still not the same conversation as $185,220. California at $106,510 and Massachusetts at $100,640 are strong medians without being District pay. Washington at $98,300 and Oregon at $97,440 sit nearer each other than either sits to the District. Florida's place on the low end, $71,790 below the District median, matters if someone tells you all states cluster. They do not, on this series. Cost of housing is your own calculation. The Bureau figures do not adjust for rent, and you should not pretend a coastal premium is already inside $82,220.

Overtime in field season, a per diem, a vehicle, and support for identification guides or a professional society belong on separate lines. They can make a modest base livable. They should not be mashed into the base before you compare it with the median. A principal-level ask can look past $82,220 when you own client relationships and review other ecologists' work. Tie that ask to scope. The $103,000 from the median to the range high end is a description of the far published edge, mostly relevant in a place and a role that can actually land there. Bring the District median, $132,620, if the job is in the District and you mean the middle. Bring $185,220 only if you are talking about the top of the published range and you have the seniority the phrase implies.

Keep the science and the money in the same plain voice. You survey, you keep the data honest, and you write a report a stranger can check. You prepared with a bachelor's or a master's, plus field time. You do not carry a single national licence. The May 2025 series you are quoting is wider than field ecology alone. Inside it, entry is $52,520, the national median is $82,220, and the high end of the range in the District is $185,220. State medians, led by the District at $132,620, are a different statistic. Use the one you mean, and leave permit paperwork to the people whose job is the application, while yours remains the evidence.

The top of Ecologist pay — and how to get there with AI

$185,220what Ecologist pay reaches in District of Columbia

Highest state-level top-of-range annual wage for Environmental Scientists and Specialists, Including Health, among states with at least 500 people in the job. U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025.

And the role it leads to — Natural Sciences Managers — reaches $330,050 in California.

$52,520entry$82,220middle$185,220top end

An ecologist at the top of this range is not the one writing the most reports; it is the one whose monitoring data turns into a compliance document almost by itself, leaving hours free for the technical guidance clients are short of.

Environmental work drowns in reporting. Sample results arrive, get transcribed, get charted, get written up against a standard, and the same shape of document goes out quarter after quarter for years. Meanwhile the scarce work waits for whatever time is left: reading a regulation and telling an agency what it means for a project, judging whether a development's environmental impacts are acceptable, defending a finding at a public hearing. Build the pipeline instead. Data into a database, charts generated rather than redrawn, recurring sections assembled from the data, and a drafting model turning your findings into first-pass prose you then correct line by line.

Your playbook, by where you are now

Just startingStop retyping your own data

  1. Get every sampling result into a database or one structured workbook the day it arrives, with units, method and detection limit attached.
  2. Generate charts and graphs from that single source instead of pasting numbers into a fresh figure each quarter.
  3. Learn the regulation your reports are written against well enough to explain a limit without looking it up.
  4. Script the transformations you currently do by hand, unit conversion, exceedance flagging, station summaries, and store them with the data.
  5. Keep the standards and guidance documents in NotebookLM so you can ask which clause applies rather than scrolling for it.

What proves it: A quarterly report produced from a repeatable pipeline rather than assembled by hand.

Realistic span: your first two or three years

A few years inTurn your pipeline into the team's

  1. Template the recurring report so that only the interpretation changes between issues.
  2. Put templates, data dictionary and figure scripts on Microsoft Office SharePoint Server MOSS where technicians can use them without asking you.
  3. Have ChatGPT draft the methods and site description sections from your notes, then rewrite every sentence making a technical claim.
  4. Train the technicians you supervise on the pipeline, so field staff produce environmental data that lands clean.
  5. Spend the recovered hours on impact monitoring and on the guidance you give agencies and project teams.

What proves it: A reporting system used across projects, with your name on its documentation.

Realistic span: years three to seven

ExperiencedBe the person the agency telephones

  1. Take the public-facing work, briefings, workshops and hearings, because those hours cannot be automated by anyone.
  2. Advise on the standards and codes of practice themselves rather than only complying with them.
  3. Lead a modelling capability, whether ADMS pollution modeling software or whatever your sector trusts, and own its assumptions in writing.
  4. Supervise a group and answer for its technical output, since natural sciences management is the standard step up.
  5. Note where the policy work sits, because the District of Columbia pays this occupation the most and that is regulatory concentration, not coincidence.

What proves it: Technical guidance you authored that a regulator or agency adopted.

Realistic span: eight years on

The next 90 days

Take the report you produce most often and time yourself honestly through one full cycle, writing down how each section came to exist. You will find most hours went into moving numbers, redrawing figures and rewording boilerplate, and almost none into interpreting what the data means. Pick the largest of those mechanical blocks and remove it within ninety days: a query in place of a transcription, a generated figure in place of a rebuilt one, a template in place of a fresh document. Then put the returned time somewhere only an ecologist can go, reading the monitoring results against the regulation and saying plainly what the project must change.

Wage figures: BLS OEWS, May 2025. The playbook is PayCrunch editorial guidance, not a guarantee of pay or placement.

Careers related to Ecologist

Similar pay, same field

Where this can lead

Every figure is the national median from the U.S. Bureau of Labor Statistics (OEWS) shown on that role’s own page.

Never used AI before? Start here (2 minutes).

Start with the AI that fits your data. If you run camera traps, Wildlife Insights or MegaDetector will sort and identify animals across thousands of images automatically; if you do acoustic surveys, BirdNET and Kaleidoscope Pro identify species from sound. Turning weeks of manual review into hours is what lets you take on more surveys, the throughput that raises an ecologist's income, especially in consulting.

For analysis and writing, use ChatGPT or GitHub Copilot to write and debug your R and Python, Elicit for literature, and Google Earth Engine for remote sensing. Always ground-truth AI classifications, and keep rare-species locations protected.

The one rule, forever: AI species identification and detection carry real error rates. Verify and ground-truth classifications, especially for rare, protected, or cryptic species where a wrong call has legal (permitting, EIA) and ecological consequences. Never fabricate or over-interpret data, document your methods and AI's role transparently for reproducibility, and protect sensitive location data for endangered species so it cannot enable poaching or disturbance.
The plays — exact steps, exact prompts

Do these in order. Each one is copy-paste ready. You do not need to know anything about AI going in.

1
Process survey data at scale with detection AI
Why this pays: Camera-trap and acoustic surveys generate mountains of data that used to take weeks to review by hand. AI classification turns that into hours, so you run more surveys and deliver faster, the direct throughput lever behind a busy, well-paid consulting or research practice.
Wildlife InsightsMegaDetectorBirdNET
1
Run camera-trap images through Wildlife Insights or MegaDetector to auto-detect and classify animals and filter empty frames, and audio through BirdNET or Kaleidoscope Pro for acoustic species ID.
2
Set up a verification workflow so accuracy holds.
Copy-paste this prompt
I am using AI to classify [5,000 camera-trap images] from a [mammal survey]. Design a verification protocol: what confidence threshold to accept automatically, how to sample and manually check classifications, how to handle rare or protected-species detections, and how to report the AI's accuracy and my verification in the methods.
AI classifies; you must ground-truth a sample and manually confirm every rare or protected-species detection before it enters a report.
What you'll haveSurvey data processed in hours instead of weeks: the capacity to run more projects, the throughput that lifts consulting income.
2
Map habitat and change with remote sensing
Why this pays: Habitat mapping, land-cover change, and vegetation analysis are central to EIAs and conservation plans. Google Earth Engine plus AI lets you analyze satellite data at scale without a GIS team, the capability that wins larger landscape-level contracts.
Google Earth EngineQGISChatGPT
1
Use Google Earth Engine to pull and analyze satellite imagery (land cover, NDVI, deforestation, or habitat change over time) and QGIS to finish maps for reports.
2
Get AI to write the geospatial code.
Copy-paste this prompt
Write a Google Earth Engine (JavaScript) script to quantify land-cover change in [a study area I will define by coordinates] between [2015 and 2025] using [Sentinel-2] imagery: cloud masking, NDVI computation, a simple change classification, and area statistics by class. Comment it so I can adapt it.
AI writes the code; verify the classification against ground-truth or reference data before you report any change figures.
What you'll haveLandscape-scale habitat and change analysis you can run solo: the capability that wins bigger EIA and conservation contracts.
3
Analyze and model data with an AI coding partner
Why this pays: Rigorous statistics and modeling separate a credible ecologist from a technician. Using AI to write and debug R and Python lets you run analyses you would otherwise farm out or avoid, the analytical depth that earns senior and PI roles.
GitHub CopilotChatGPTR
1
Use ChatGPT or GitHub Copilot to write, explain, and debug your R or Python analysis, from data cleaning to mixed models, occupancy models, or ordination.
2
Get the right method and defensible code.
Copy-paste this prompt
I have [repeated point-count bird survey data across 40 sites and 3 visits] and want to estimate occupancy while accounting for imperfect detection. Recommend the appropriate model, the R package to use (e.g., unmarked), write commented code to fit it, and explain the assumptions I must check and how to report the results.
AI suggests methods and code; you must confirm the method fits your design and check every model assumption before trusting the output.
What you'll haveMore sophisticated, defensible analyses done in-house: the statistical rigor that distinguishes a senior ecologist or PI.
4
Draft EIAs and technical reports faster
Why this pays: Consulting ecology runs on reports: EIAs, monitoring reports, management plans. AI accelerates drafting and synthesis so you turn projects around faster and take on more, directly increasing billable output.
ClaudeNotebookLMChatGPT
1
Load your data summaries, survey results, and relevant guidance into NotebookLM, then use Claude to draft report sections grounded in those sources.
2
Draft a defensible impact-assessment section.
Copy-paste this prompt
Draft the [potential impacts and mitigation] section of an environmental impact assessment for [a solar farm on former agricultural land]: structure it by receptor (habitats, birds, bats, reptiles), summarize likely impacts during construction and operation, and propose standard mitigation and enhancement measures. Flag where site-specific survey data must replace my placeholders.
AI drafts structure and standard content; every impact conclusion must rest on your actual survey data and professional judgment, not AI assumptions.
What you'll haveReports and EIAs drafted faster with your data and judgment on top: more projects delivered, the core of consulting income.
5
Accelerate literature reviews and grant proposals
Why this pays: Whether you are funded by grants or by clients, staying current and writing winning proposals drives income. AI compresses literature review and strengthens proposals, so more of your time is spent on funded work.
ElicitConsensusClaude
1
Use Elicit and Consensus to synthesize the literature for a proposal or a study's background, pulling real papers with extracted findings.
2
Strengthen the proposal itself.
Copy-paste this prompt
Help me sharpen the [aims and significance] of a grant proposal on [the effect of hedgerow restoration on farmland bird populations]: tighten the research questions, articulate the knowledge gap and why it matters for conservation policy, and suggest a defensible study design and analysis approach reviewers will trust.
AI helps structure and argue; verify every cited finding exists and that the design is sound before submitting.
What you'll haveFaster literature reviews and stronger proposals: more funded projects and contracts, the engine behind pay at the top of the range.
Your 12-month sequence to the top of the range

How the plays above stack into a path from median pay toward the $185,220 tier.

Month 1
Put your camera-trap or acoustic data through Wildlife Insights, MegaDetector, or BirdNET, with a verification protocol; measure the review time saved.
Months 2-3
Adopt an AI coding partner for your R/Python analyses and start using Google Earth Engine for habitat mapping.
Months 3-6
Speed EIA and report drafting with AI grounded in your own data; accelerate literature reviews with Elicit.
Months 6-12
Package an AI-accelerated survey-to-report workflow and target larger consulting contracts or lead-PI roles.
Gear for this job

As an Amazon Associate, PayCrunch earns from qualifying purchases. Links to books and tools are for the job on this page; we only recommend what we’d use in the work.

McKinney Python for Data Analysis, 3rd

Same live O’Reilly 3rd already on data-scientist / python-developer / market-research-analyst / botanist. This leftover page’s third play is Analyze and model data with an AI coding partner and names write and debug your R or Python analysis; Months 2–3 is Adopt an AI coding partner for your R/Python analyses. Not CompTIA Data+ and not leftover Ross Exam P (that is actuary). Confirm 109810403X. Live page HTTP 200, no PC_GEAR / amazon.com/dp / tag=paycrunch-20 at 2026-09-17 3:31 PM PT.

Next steps for an Ecologist

Some links below are affiliate or partner links. PayCrunch may earn a commission if you enroll or subscribe through them, at no extra cost to you. Wage figures on this page still come from the Bureau of Labor Statistics, not from these programs.

Ecologist work is specific enough that a stamped 'check out these courses' block would be noise. BLS files this work as Environmental Scientists and Specialists, Including Health (SOC 19-2041). O*NET Job Zone 4 is typical: a bachelor's degree, so the honest next credential is a professional certificate or bachelor's-level coursework — not a random catalog dump.

The occupation's listed knowledge areas include Biology and Engineering and Technology; the links search those subjects, not a generic 'career courses' list.

Ecologists in this dataset list Adobe InDesign among the tools in use, so a program that names that stack is a better fit than a survey course.

Biology programs on Coursera for Ecologist work

Coursera search for biology — a professional certificate or bachelor's-level coursework that lines up with science, not a generic professional-development aisle.

Biology courses on edX

edX search for biology, aimed at science (SOC 19-2041). Same field as the Coursera link, different university catalog.

Screened remote and flexible Ecologist listings on FlexJobs

FlexJobs screens remote, hybrid, freelance, and flexible listings so you are not wading through unverified ads. This is a job-board search for Ecologist work, not a claim that they list a counted SOC 19-2041 inventory.

Build an Ecologist resume on Resume Now

Write an Ecologist resume, or one aimed at Natural Sciences Managers, instead of a blank template. Resume Now is a resume builder; we are not claiming a counted template set for this SOC.

Build an Ecologist resume on Zety

An Ecologist resume that names the actual tasks on this page, or the step-up title Natural Sciences Managers, beats a blank template when you apply.

What Ecologists earn by state

These are the Bureau of Labor Statistics’ own figures for Environmental Scientists and Specialists, Including Health, state by state — not a cost-of-living adjustment applied to the national number. Only states employing at least 500 people in the occupation are shown, because a state median drawn from a handful of workers is noise rather than a signal.

District of Columbia
$132,620
highest of them · +61% vs the national median
Florida
$60,830
lowest of the 39 states and D.C. that qualify · -26% vs the national median
The same job pays $71,790 more a year at the median in District of Columbia than in Florida — 118% higher. That gap is what the Bureau measured, before any question of what it costs to live in either place. District of Columbia also carries the top of this job’s range, $185,220 — the figure quoted at the head of this page.
District of Columbia$132,620California$106,510Massachusetts$100,640Washington$98,300Oregon$97,440Texas$92,000Alaska$91,960Utah$90,710

Source: U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025, SOC 19-1023. 39 states and D.C. clear the 500-employee reporting floor for this occupation; those below it are left out rather than shown with a wide error band.

Free data. Use any of it.

PayCrunch publishes verified, BLS-sourced salary + AI-playbook data on 1,000+ professions — free, no signup.

Frequently asked
Will AI replace ecologists?
No. Ecology depends on field skill, study design, and interpretation in messy real-world conditions, and someone must be legally and scientifically accountable for the conclusions. AI replaces the manual bottlenecks: sorting images, writing code, drafting reports. Ecologists who use it process more data and take on more work; the risk is not AI, it is a competitor who delivers surveys faster and cheaper than you.
Can I trust AI species identifications?
Only after verification. AI classifiers have real error rates that spike for rare, cryptic, or region-specific species, and a wrong call can misdirect a permit or an EIA. Ground-truth a sample, manually confirm every protected-species detection, and report the AI's accuracy and your verification in your methods. The classification is a first pass, not a determination.
Is it okay to use AI to write my analysis code?
Yes, with judgment. AI is excellent at writing and debugging R and Python and at suggesting methods, but it will confidently propose an inappropriate model or subtly wrong code. Confirm the method fits your study design, check every model assumption, and validate results against what you would expect; you remain responsible for the analysis's correctness.
How does AI actually increase an ecologist's pay?
By increasing throughput and capability, which matters most in consulting where pay is highest. Automated data processing and faster reporting let you deliver more projects; remote sensing and stronger statistics let you win bigger, more technical contracts; and faster proposals bring in more funded work. More and larger projects is the path to the $185,220 top of the range.
Which AI tool should an ecologist learn first?
Whatever matches your biggest data bottleneck: Wildlife Insights or MegaDetector for camera traps, BirdNET for acoustics. Then add an AI coding assistant for your analyses, since that unlocks rigor across every project. Google Earth Engine follows when you need landscape-scale mapping.
Methodology & sources
  • Salary (median, 10th, top of the range) — U.S. Bureau of Labor Statistics, OEWS.
  • By state — the Bureau of Labor Statistics’ own state medians, limited to states employing at least 500 people in the occupation. No cost-of-living arithmetic is applied to a wage anywhere on this page.
  • The plays — PayCrunch's own step-by-step guidance using publicly available AI tools. Tool names/URLs are real and current as of August 2026; prompts written to work as-is. Verify any professional output before relying on it.

Sources