# Forest and Conservation Workers

> Under supervision, perform manual labor necessary to develop, maintain, or protect areas such as forests, forested areas, woodlands, wetlands, and rangelands through such activities as raising and transporting seedlings; combating insects, pests, and diseases harmful to plant life; and building structures to control water, erosion, and leaching of soil. Includes forester aides, seedling pullers, tree planters, and gatherers of nontimber forestry products such as pine straw.

- **SOC code:** 45-4011.00
- **Canonical URL:** https://singulariki.com/roles/role-45-4011-00
- **Also known as:** Forest Ranger, Forestry Support Specialist, Tree Farmer, Tree Planter, Christmas Tree Farmer, Conservation Officer, Field Laborer, Forest Resource Specialist
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Check equipment to ensure that it is operating properly.
- Fight forest fires or perform prescribed burning tasks under the direction of fire suppression officers or forestry technicians.
- Perform fire protection or suppression duties, such as constructing fire breaks or disposing of brush.
- Maintain tallies of trees examined and counted during tree marking or measuring efforts.
- Confer with other workers to discuss issues, such as safety, cutting heights, or work needs.
- Explain or enforce regulations regarding camping, vehicle use, fires, use of buildings, or sanitation.
- Spray or inject vegetation with insecticides to kill insects or to protect against disease or with herbicides to reduce competing vegetation.
- Operate skidders, bulldozers, or other prime movers to pull a variety of scarification or site preparation equipment over areas to be regenerated.
- Thin or space trees, using power thinning saws.
- Identify diseased or undesirable trees and remove them, using power saws or hand saws.
- Select or cut trees according to markings or sizes, types, or grades.
- Prune or shear tree tops or limbs to control growth, increase density, or improve shape.

**Emerging tasks** (O*NET):
- Create field maps using geographic information systems technology.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Oral Comprehension _(ability)_
- Problem Sensitivity _(ability)_
- Public Safety and Security _(knowledge)_
- English Language _(knowledge)_
- Oral Expression _(ability)_
- Static Strength _(ability)_
- Customer and Personal Service _(knowledge)_
- Administration and Management _(knowledge)_
- Critical Thinking _(essential_skill)_
- Monitoring _(essential_skill)_
- Deductive Reasoning _(ability)_
- Flexibility of Closure _(ability)_

**Skills in demand:**
- English Language _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Geography _(Specialized Skill)_
- Biology _(Specialized Skill)_
- Visualization _(Specialized Skill)_
- Speech Recognition _(Specialized Skill)_
- Reading Comprehension _(Common Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft Windows _(Common Skill)_
- Microsoft Project _(Specialized Skill)_
- Microsoft PowerPoint _(Common Skill)_

**Tools & technology:**
- ESRI ArcGIS software _(hot technology, in demand)_
- Microsoft Access _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Project _(hot technology)_
- Microsoft Windows _(hot technology)_
- Microsoft Word _(hot technology)_
- Geographic information system GIS systems _(in demand)_
- Database software
- Geographic information system GIS software

## AI exposure & outlook

- **AI task-overlap index:** 10th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 15th percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 7th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 19th percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 74th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** -4.7% growth (Declining); 2k annual openings; 10.8k → 10.3k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $43,680; 5,630 employed.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-45-4011-00_