Natural Resources and Conservation

What the occupations pay

Median annual wage across the occupations this field of study leads to, from BLS OEWS (national, cross-industry, May 2024). The middle range is the 25th–75th percentile of those occupation medians — it describes the field, not any one job or graduate.

AI exposure of this field of study

Two published studies estimate how exposed each occupation is to today's AI. The OpenAI "GPTs are GPTs" study rates the share of an occupation's tasks a large language model (with tools) could speed up by half or more; averaged across the occupations this field of study leads to it is 39% — 42nd percentile of all fields of study. The independent Felten/Raj/Seamans AI Occupational Exposure index averages 0.30 here.

Computed across the 27 of 27 occupations this field leads to that carry a published exposure score.

The most-exposed fields of study lead to knowledge, language and analytical work; the least-exposed lead to physical trades and hands-on production. Exposure measures where AI could assist tasks, not a prediction that these jobs will be automated; high exposure most often means augmentation. Bands are comparable across the cluster, education, job-zone and field-of-study tiers (same two studies, same percentile method).

Where this field of study leads

The largest occupations connected to this field by the CIP–SOC crosswalk, by employment. Wage and employment describe the occupation, not an individual.

Programs in this field

A sample of the detailed CIP programs within this family. The full family contains 22 programs.

• 03.0209 Energy and Environmental Policy
• 03.0104 Environmental Science
• 03.0103 Environmental Studies
• 03.0204 Environmental/Natural Resource Economics
• 03.0207 Environmental/Natural Resource Recreation and Tourism
• 03.0208 Environmental/Natural Resources Law Enforcement and Protective Services
• 03.0201 Environmental/Natural Resources Management and Policy, General
• 03.0299 Environmental/Natural Resources Management and Policy, Other
• 03.0301 Fishing and Fisheries Sciences and Management
• 03.0506 Forest Management/Forest Resources Management
• 03.0510 Forest Resources Production and Management
• 03.0502 Forest Sciences and Biology
• 03.0511 Forest Technology/Technician
• 03.0501 Forestry, General
• 03.0599 Forestry, Other
• 03.0206 Land Use Planning and Management/Development
• 03.9999 Natural Resources and Conservation, Other
• 03.0101 Natural Resources/Conservation, General
• 03.0508 Urban Forestry
• 03.0205 Water, Wetlands, and Marine Resources Management
• 03.0601 Wildlife, Fish and Wildlands Science and Management
• 03.0509 Wood Science and Wood Products/Pulp and Paper Technology/Technician

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

• O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
• BLS Occupational Employment and Wage Statistics (OEWS) May 2024 U.S. Bureau of Labor Statistics
• CIP-2020 2020 U.S. National Center for Education Statistics
• “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
• AI Occupational Exposure (AIOE) Felten, Raj & Seamans academic

Data compiled June 3, 2026. Figures are estimates, not advice.

@misc{singulariki-natural-resources-and-conservation,
  title  = {Natural Resources and Conservation},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; CIP-2020 2020; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans. Accessed June 7, 2026},
  url    = {https://singulariki.com/programs/natural-resources-and-conservation}
}