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mims-harvard/tooluniverse242 installs

tooluniverse-ecology-biodiversity

Ecology, biodiversity, and conservation biology research — species identification (GBIF, NCBI Taxonomy), invasive species impact, ecosystem dynamics, conservation status (IUCN), niche ecology. Use for biodiversity questions, species comparison, invasion biology, conservation prioritization, and ecology-related literature search.

How do I install this agent skill?

npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-ecology-biodiversity
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubpass

    This skill is designed for ecological and biodiversity research. It appears safe and follows standard research methodologies. A low-risk finding was identified regarding the processing of external scientific data which could potentially contain indirect instructions, a common characteristic of research-oriented AI skills.

  • Socketpass

    No alerts

  • Snykwarn

    Risk: MEDIUM · 1 issue

What does this agent skill do?

Ecology & Biodiversity Research

Reasoning Strategy

1. Species & Taxonomy Questions

When a question involves identifying or comparing species:

  1. LOOK UP DON'T GUESS — Use GBIF_search_species to get taxonomy, WoRMS_search_species for marine organisms
  2. If the question asks about invasive species impacts, consider: ecological niche overlap, reproductive rate, predator release, and ecosystem engineering effects
  3. Use PubMed_search_articles or EuropePMC_search_articles to find studies on specific ecological impacts

2. Invasive Species Impact Assessment

Reasoning framework — when comparing invasive species impacts:

  1. Identify the ecosystem: What habitat/biome is affected?
  2. Assess impact mechanisms: Competition? Predation? Disease vector? Habitat modification? Hybridization?
  3. Scale of impact: Local (single site) vs regional vs continental?
  4. Trophic position: Invasives at higher trophic levels (predators) often cause more damage than lower (herbivores)
  5. Ecosystem engineering: Species that modify habitats (beavers, earthworms, honeybees displacing native pollinators) cause outsized impacts
  6. Look up specifics — don't rely on general knowledge. Search for "[species name] invasive impact [region]" in literature

3. Pollinator Ecology

Reasoning framework for pollination questions:

  1. Foraging behavior: Distinguish investigation (approach/assessment) from actual feeding (proboscis insertion)
  2. Interaction types: Mutualistic (pollination reward), parasitic (nectar robbing), commensal
  3. Observation methods: Camera traps have resolution/FOV limitations — consider what's identifiable at given resolution
  4. Statistical considerations: Observer agreement (inter-rater reliability), sampling effort, temporal patterns
  5. Ethogram interpretation: Each behavior category has specific start/end criteria — follow them precisely

4. Population Dynamics

Reasoning framework for population ecology questions:

  1. Growth models: Exponential (unlimited), logistic (K-limited), Allee effects (low-density problems)
  2. Extinction analysis: Distinguish deterministic extinction (r < 0) from stochastic extinction (small population fluctuations)
  3. Survival analysis: Time-to-event analysis needs appropriate statistical tests (log-rank, Cox regression, Kaplan-Meier)
  4. Microbial ecology: For microbial stressor responses, use survival curve analysis with time-kill kinetics. To compare extinction points between populations, you need time-to-extinction data analyzed with survival statistics (not just endpoint comparisons)

5. Community Ecology & Food Webs

  1. Trophic cascades: Removing top predators → mesopredator release → prey decline
  2. Keystone species: Disproportionate impact relative to abundance
  3. Island biogeography: Species-area relationship, distance-colonization tradeoff
  4. Competitive exclusion: Two species cannot stably coexist on single limiting resource (Gause's principle)

6. Evolutionary Ecology

  1. Aposematism: Warning coloration signals toxicity/unpalatability
  2. Mimicry: Batesian (harmless mimics dangerous) vs Mullerian (dangerous mimics dangerous)
  3. Life history tradeoffs: r-selected (many offspring, low investment) vs K-selected (few offspring, high investment)
  4. Birth-death models: For phylogenetic questions, identifiability issues arise with time-varying rates. Strategies to resolve: constrain rate variation, add fossil data, use molecular data calibration, or restrict to specific functional forms

Available Tools

ToolUse For
IUCN_get_conservation_statusRed List conservation status (CR/EN/VU/NT/LC) by scientific name — the authoritative extinction-risk source (needs a free IUCN_API_KEY)
GBIF_search_speciesSpecies taxonomy, occurrence data, distribution
GBIF_search_occurrencesWhere has a species been observed?
GBIF_get_taxon_parentsWalk UP the GBIF Backbone tree — ranked ancestor lineage (kingdom→genus) for a taxonKey
GBIF_get_taxon_childrenWalk DOWN the tree — direct child taxa (e.g. species in a genus) for a taxonKey
GBIF_get_taxon_synonymsAlternative / historical scientific names for an accepted taxonKey
GBIF_get_vernacular_namesCommon names (with language code) for a taxonKey; optional language filter
GBIF_parse_nameParse messy/authored name strings into canonical name + genus/epithet/author/year
iDigBio_search_recordsSearch 130M+ digitized museum/herbarium specimen records (Darwin Core) by genus/scientificname/locality — use to complement GBIF with physical-specimen provenance
iDigBio_get_recordFull Darwin Core detail for one specimen by uuid (from iDigBio_search_records)
WoRMS_search_speciesMarine species taxonomy
BOLDSystems_search_by_taxon / _search_by_bin / _get_recordDNA barcode-based species identification (COI barcoding); BIN clusters group specimens by barcode similarity, useful for cryptic-species questions GBIF's name-based search can't resolve
ensembl_get_taxonomyTaxonomic classification
NCBIDatasets_get_taxonomyNCBI taxonomy lookup
PubMed_search_articlesLiterature on ecology topics
EuropePMC_search_articlesEuropean literature including ecology

Navigating the GBIF taxonomic tree

Resolve a name to a GBIF usageKey once, then navigate the Backbone tree:

key = tu.run_tool("GBIF_match_name", {"name": "Panthera leo"})["data"]["usageKey"]  # 5219404
tu.run_tool("GBIF_get_taxon_parents", {"taxon_key": key})        # Animalia→...→Felidae→Panthera
tu.run_tool("GBIF_get_taxon_synonyms", {"taxon_key": key})       # Felis leo Linnaeus, 1758, ...
tu.run_tool("GBIF_get_vernacular_names", {"taxon_key": key, "language": "eng"})  # Lion, African Lion
# Walk down from a genus key (Panthera = 2435194) to its species:
tu.run_tool("GBIF_get_taxon_children", {"taxon_key": 2435194, "limit": 8})
# Normalize an authored name string without a key:
tu.run_tool("GBIF_parse_name", {"name": "Quercus robur L."})     # canonicalName 'Quercus robur'

All five tools hit the public GBIF API with no key. Get the starting taxon_key from GBIF_match_name or GBIF_search_species.

Additional Taxonomy & Biodiversity Sources

GBIF/WoRMS/BOLDSystems/iDigBio (above) are the primary sources. These eight add authority-specific, phylogenetic, and observational coverage GBIF alone doesn't provide — use them when GBIF is ambiguous, when you need a phylogenetic tree rather than a flat classification, or when you need citizen-science occurrence density rather than museum-specimen records.

ToolUse For
EOL_search_species / EOL_get_page / EOL_get_hierarchy_entry / EOL_get_collectionEncyclopedia of Life — aggregated species pages (images, text, multiple classification systems per page), curated topical collections
ITIS_search_by_scientific_name / _search_by_common_name / ITIS_get_hierarchy / ITIS_get_full_recordITIS (Integrated Taxonomic Information System) — the authoritative North American taxonomy standard; returns a tsn (Taxonomic Serial Number)
CoL_search_species / CoL_get_taxon / CoL_get_childrenCatalogue of Life — the broadest single global species checklist (consolidates 190+ source databases); good first stop when GBIF's backbone doesn't have a clean match
OpenTree_match_names / OpenTree_get_taxon / OpenTree_get_mrca / OpenTree_get_induced_subtreeOpen Tree of Life — a synthetic phylogenetic tree (not just a rank hierarchy) across all of life; use when the question is about evolutionary relationships/branch order, not just classification
iNaturalist_search_taxa / _get_taxon / _search_observations / _get_species_countsiNaturalist — citizen-science observation records with photos/location/date; use for occurrence density and recent sightings, not authoritative taxonomy
OBIS_search_taxa / OBIS_search_occurrencesOBIS (Ocean Biodiversity Information System) — marine-species occurrence records with coordinates/time, resolved to AphiaID (WoRMS' identifier); the marine analog of GBIF occurrence search
eBird_get_taxonomy / eBird_get_taxon_groupseBird (Cornell Lab) — bird-specific taxonomy and species groupings; use for bird questions instead of generic taxonomy sources, which are shallower on avian subspecies/hybrid codes
MarineRegions_search_by_name / MarineRegions_get_recordMarine Regions Gazetteer (VLIZ) — geographic/political marine boundaries (seas, EEZs, bays) by MRGID; pairs with OBIS for "which occurrences fall inside this named sea" questions

Choosing among the identity/taxonomy sources (EOL, ITIS, CoL, GBIF all answer "what is this species"):

  • ITIS if you need the North American regulatory-standard identifier (tsn).
  • CoL for the broadest global checklist coverage when GBIF's backbone misses a match.
  • EOL when you want an aggregated page (images, multiple hierarchies, curated collections) rather than a bare taxonomic record.
  • Open Tree of Life only when the question is genuinely phylogenetic (MRCA, branch order, a Newick subtree) — none of the others return evolutionary relationships.
  • Cross-check IDs are NOT interchangeable: the same species has a different key in each system (GBIF usageKey, ITIS tsn, CoL taxon_id, EOL page_id, Open Tree ott_id, iNaturalist taxon_id, OBIS AphiaID) — always resolve within one system, don't mix an ID from one database into another's lookup call.

Example: cross-checking a species across four identity systems (verified live, real IDs):

tu.run_tool("EOL_search_species", {"query": "Panthera leo"})            # page_id 1270491
tu.run_tool("ITIS_search_by_scientific_name", {"scientific_name": "Panthera leo"})  # tsn 183803
tu.run_tool("CoL_search_species", {"q": "Panthera leo"})                # 293 CoL-database matches
tu.run_tool("OpenTree_match_names", {"names": "Panthera leo,Panthera tigris"})
# -> ott_id 563151 (leo), 42314 (tigris); note `names` is a comma-separated
# STRING, not a JSON array, even though it takes multiple names

Example: phylogenetic MRCA and subtree (verified live):

tu.run_tool("OpenTree_get_mrca", {"ott_ids": "417950,770315"})
# -> mrca_name "Homininae", mrca_ott_id 312031, num_tips 19
tu.run_tool("OpenTree_get_induced_subtree", {"ott_ids": "417950,770315,312031"})
# -> real Newick tree with supporting_studies citations (pg_2741@tree6645, ...)

Example: marine species + region (verified live):

tu.run_tool("OBIS_search_taxa", {"scientificname": "Rhincodon typus"})   # whale shark occurrence-resolved AphiaID
tu.run_tool("MarineRegions_search_by_name", {"name": "Mediterranean Sea"})  # MRGID 25180

Example: citizen-science occurrence density (verified live):

tu.run_tool("iNaturalist_search_taxa", {"query": "Panthera leo"})
# -> genus-level hit "Panthera" (59,036 observations) if the exact binomial
# isn't the top match — check the returned `rank` before assuming species-level

LOOK UP DON'T GUESS

Ecology questions often have counter-intuitive answers. For example:

  • Honeybees (Apis mellifera) are invasive in the Americas and displace native pollinators — this surprises people who think of bees as "good"
  • The most damaging invasive species are often not the most obvious ones
  • Microbial extinction points require survival analysis, not simple t-tests

Always search the literature before answering ecology questions. Use PubMed_search_articles with specific terms like "[species] invasive impact [region]" or "[organism] [ecological process]".

COMPUTE, DON'T DESCRIBE

When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

<a href="https://skillzs.dev/skills/mims-harvard/tooluniverse/tooluniverse-ecology-biodiversity">View tooluniverse-ecology-biodiversity on skillZs</a>