SKILL.md
iNaturalist API Guide
Overview
iNaturalist is a citizen science platform and social network for naturalists, jointly operated by the California Academy of Sciences and the National Geographic Society. The platform enables users to record and share observations of organisms in nature, which are then identified by the community and validated by computer vision models. With over 150 million observations of more than 400,000 species, iNaturalist is one of the largest biodiversity data sources in the world.
The iNaturalist API provides programmatic access to this massive observational dataset. Researchers can query observations by taxonomy, geography, time period, observer, and data quality grade. The API also provides access to taxonomic information, place boundaries, and project data. Research-grade observations (those with community-verified identifications) are automatically shared with GBIF for integration into the global biodiversity data infrastructure.
Ecologists, conservation biologists, evolutionary biologists, and citizen science coordinators use the iNaturalist API to analyze species distributions, track phenological patterns, study urban biodiversity, monitor invasive species, and validate species distribution models. The platform's broad geographic and taxonomic coverage makes it particularly valuable for large-scale ecological analyses.
Authentication
No authentication is required for read-only access to public data. The iNaturalist API v1 allows anonymous queries for observations, taxa, and places. Authentication via OAuth 2.0 is only needed for write operations such as creating observations, adding identifications, or managing projects.
For authenticated requests, register an application at https://www.inaturalist.org/oauth/applications and use the OAuth 2.0 flow to obtain an access token.
Core Endpoints
observations: Search Biodiversity Observations
Query the iNaturalist observation database with filters for taxonomy, geography, time, and data quality.
- URL:
GET https://api.inaturalist.org/v1/observations - :
