Ecological Relationship Ontology

FLOW ALGEBRA
TITLE: Ecological Relationship Ontology
VERSION: 1.0
SOURCE: https://kirethresearch.org/booksai-core/ontologies/relationship-ontologies/scientific-relationships/ecological-relationship-ontology.html
AUTHORS: Mark Anthony Higgins — Sky (Recursive AI)
STATUS: Companion formalisation; source-page specification not independently verified.

flow "EcologicalRelationshipOntology" v1.0

ENTITY_TYPES:
  Organism(id, taxon, traits, provenance)
  Population(id, taxon, location, time_interval)
  Species(id, scientific_name)
  Community(id, populations)
  Ecosystem(id, biotic_components, abiotic_components, boundary)
  Habitat(id, environmental_conditions)
  Resource(id, kind, availability, unit)
  Interaction(id, participants, type, context, evidence)
  Observation(id, subject, measurement, timestamp, method)

RELATIONSHIP_TYPES:
  PREYS_ON(predator, prey)
  COMPETES_WITH(organism_a, organism_b, resource)
  MUTUALISM(partner_a, partner_b)
  COMMENSALISM(beneficiary, host)
  PARASITISES(parasite, host)
  INHABITS(organism_or_population, habitat)
  CONSUMES(organism, resource)
  POLLINATES(pollinator, plant)
  DECOMPOSES(decomposer, organic_material)
  DEPENDS_ON(entity, resource_or_entity, context)
  AFFECTS_POPULATION(entity, population, direction, context)
  PART_OF(population, community_or_ecosystem)

TYPE_RULES:
  PREYS_ON: Organism|Population x Organism|Population -> Interaction
  INHABITS: Organism|Population x Habitat -> Interaction
  PART_OF: Population x Community|Ecosystem -> Membership
  COMPETES_WITH: Organism|Population x Organism|Population x Resource -> Interaction

INFERENCE_RULES:
  R1: PREYS_ON(A,B) => TROPHIC_LINK(A,B)
  R2: POLLINATES(A,B) => INTERACTS_WITH(A,B)
  R3: MUTUALISM(A,B) => BENEFITS_FROM(A,B) AND BENEFITS_FROM(B,A), subject to evidence
  R4: PART_OF(P,C) AND PART_OF(C,E) => ASSOCIATED_WITH_ECOSYSTEM(P,E)
  R5: COMPETES_WITH(A,B,R) => SHARES_RESOURCE_PRESSURE(A,B,R)
  R6: PARASITISES(A,B) => ECOLOGICAL_DEPENDENCY(A,B)
  NOTE: Associations and trophic links do not alone establish measured causal effects.

SEMANTIC_EQUIVALENCE:
  aliases: ["ecological interaction", "biotic relationship"]
  scope: contextual, not universal identity
  distinguish: ["correlation", "causation", "co-occurrence", "dependence"]

CONFIDENCE:
  range: [0.0, 1.0]
  evidence_factors: [source_quality, replication, sampling_coverage, temporal_relevance, ecological_context]
  rule: Derived confidence must not exceed unsupported source certainty.

PROVENANCE:
  required: [source_id, observation_or_study, date, method, ecological_context]
  optional: [doi, dataset_id, licence, uncertainty]

VALIDATION:
  - Enforce declared entity and relationship types.
  - Check taxonomic identifiers and temporal/spatial scope.
  - Reject self-predation unless explicitly documented.
  - Preserve directionality of predation, parasitism and consumption.
  - Do not infer mutualism from mere co-occurrence.
  - Record missing evidence and uncertainty explicitly.

FLOW_HASH:
  method: SHA-256
  input: canonical_serialisation(ontology_version, entities, relationships, rules, provenance)
  rule: Recompute when canonical content changes.

UPDATE_MODEL:
  strategy: versioned_incremental_update
  steps: [ingest, normalise, type_check, reconcile, validate, version, rehash, publish]
  conflict_policy: retain competing evidence with provenance; do not silently overwrite

AI_CONSUMPTION:
  format: typed_semantic_graph
  supports: [retrieval, knowledge_graph_construction, explainable_inference, ecological_question_answering]
  safeguards: [evidence_traceability, uncertainty_preservation, context_awareness, no_unsupported_causality]

end flow