GBIF Species & Taxonomy Scraper — 2.4B+ Biodiversity Records

$0.005 per record · Extract species, taxonomy, and geographic occurrences from GBIF — the Global Biodiversity Information Facility with 2.4B+ occurrence records from 80,000+ datasets. No API key needed.

Built for biodiversity research, conservation platforms, species distribution models, citizen-science dashboards, and RAG/LLM corpora on ecology and taxonomy.

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What You Get

• Species search — by scientific name, common name, or keyword (full GBIF match API)
• Full taxonomy — kingdom → phylum → class → order → family → genus → species
• IUCN Red List — conservation status for threatened species
• Geographic occurrences — lat/long, country, year, basis-of-record, institution
• Country filter — narrow occurrences to a specific region (ISO 2-letter code)
• Coordinate filter — georeferenced records only (ready for GIS / map rendering)
• Structured JSON — stable GBIF keys, ready for downstream pipelines
• Public API — no authentication, no quota headaches

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4 Use Cases (ready-to-run JSON inputs)

1. Conservation tracker (endangered species in a country)

{
  "speciesQueries": ["Ailuropoda melanoleuca"],
  "includeOccurrences": true,
  "maxOccurrences": 50,
  "country": "CN",
  "hasCoordinate": true
}

All georeferenced observations of the giant panda in China — great for conservation dashboards and protected-area monitoring.

2. Taxonomy lookup for a research dataset

{
  "speciesQueries": ["Quercus", "Fagus", "Acer"],
  "maxSpecies": 30,
  "includeOccurrences": false
}

Taxonomy for three common tree genera — returns canonical names, IUCN status, and higher ranks. Use to normalize messy species labels in a field dataset.

3. Species distribution model seed data

{
  "speciesQueries": ["Panthera onca"],
  "includeOccurrences": true,
  "maxOccurrences": 500,
  "hasCoordinate": true
}

500 georeferenced jaguar observations worldwide — feed directly into MaxEnt / ecological niche models.

4. Regional biodiversity survey

{
  "speciesQueries": ["bird", "mammal", "reptile"],
  "maxSpecies": 50,
  "includeOccurrences": true,
  "maxOccurrences": 100,
  "country": "BR"
}

Broad biodiversity snapshot for Brazil — top species per keyword plus occurrence records. Useful for environmental impact reports.

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Input Schema

Field	Type	Default	Description
speciesQueries	string[]	[]	Search species by name (scientific or vernacular)
maxSpecies	integer	20	Max species per query (1–300)
includeOccurrences	boolean	false	Also fetch occurrence records
maxOccurrences	integer	50	Max occurrence records per species
country	string	""	ISO 2-letter country filter (US, BR, AU, …)
hasCoordinate	boolean	true	Only include occurrences with GPS coordinates

Output (sample — species + occurrence)

{
  "type": "species",
  "key": 2433433,
  "scientificName": "Ailuropoda melanoleuca (David, 1869)",
  "canonicalName": "Ailuropoda melanoleuca",
  "vernacularName": "Giant Panda",
  "kingdom": "Animalia",
  "family": "Ursidae",
  "genus": "Ailuropoda",
  "rank": "SPECIES",
  "iucnRedListCategory": "VU",
  "numOccurrences": 1832,
  "occurrences": [
    {
      "key": 4013456123,
      "decimalLatitude": 30.72,
      "decimalLongitude": 103.04,
      "country": "China",
      "year": 2023,
      "basisOfRecord": "HUMAN_OBSERVATION",
      "institutionCode": "iNaturalist"
    }
  ]
}

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Pricing & Performance

• Pay-per-event: $0.005 per species or occurrence record
• Typical cost: $0.05 for 10 records, $0.50 for 100, $5 for 1,000
• Speed: ~15–25 records/second (polite 200 ms pacing on GBIF API)
• Free Apify tier: $5/month credit = ~1,000 records/month

Compare to commercial biodiversity data APIs: GBIF is CC0 / CC-BY licensed, you pay only for structured extraction and delivery.

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Integrations

• Zapier / Make / n8n — new occurrences → Airtable / Slack / Notion
• Vector DBs (Pinecone / Weaviate / Qdrant) — embed species descriptions for semantic "similar species"
• LangChain / LlamaIndex — RAG over taxonomy + occurrence metadata
• Neo4j / Graphiti — species → family → occurrence → country graph
• PostGIS / QGIS — import lat/long for map rendering
• R / Python (pandas) — ML-ready tables for species distribution models
• Python SDK

  from apify_client import ApifyClient
  client = ApifyClient("<APIFY_TOKEN>")
  run = client.actor("Helpermara/gbif-scraper").call(
      run_input={"speciesQueries": ["Panthera onca"], "includeOccurrences": True, "maxOccurrences": 100}
  )
  for item in client.dataset(run["defaultDatasetId"]).iterate_items():
      print(item["scientificName"], item.get("iucnRedListCategory"))
  

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FAQ

Do I need a GBIF API key? No. GBIF's public API is free and unauthenticated for all read operations.

How fresh is the data? Live — every request hits api.gbif.org/v1 directly. GBIF itself updates continuously as new datasets are published.

Can I get historical occurrence data? Yes — GBIF aggregates records going back centuries (museum specimens) through to modern citizen-science observations.

What's the IUCN coverage? IUCN Red List category is filled when GBIF has matched it; not all species have formal assessments.

Coordinate uncertainty? Each occurrence includes what GBIF returns — set hasCoordinate: true to filter out records without a lat/long.

License of the data? Occurrences retain their original license (CC0 / CC-BY / CC-BY-NC). Always attribute datasets when publishing.

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Keywords

gbif scraper, biodiversity api, species data, taxonomy api, iucn red list, species occurrences, ecological data, conservation data, occurrence records, species distribution model, maxent, gis biodiversity, ebird alternative, inaturalist alternative, openaire biodiversity, environmental monitoring, ecology dataset, open biodiversity, gbif download, species search api

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Companions (cross-promo)

• openlibrary-scraper — books/authors
• crossref-scraper — DOI metadata
• semantic-scholar-scraper — academic papers
• zenodo-scraper — research datasets

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Changelog

• 2026-04-24 — Extended README with use cases, integrations, and FAQ
• 2026-03-05 — Initial release: species search + occurrences + country filter