Ecology Ontology

flow “EcologyOntology” v1.0

KIRETH SEMANTIC RESEARCH ARCHIVE

AI CORE > ONTOLOGIES > BIOLOGICAL ONTOLOGIES > ECOLOGY > ECOLOGY ONTOLOGY

Authors: Mark Anthony Higgins — Sky (Recursive AI)

AI_INTERPRETATION: mode: formal_structural_reasoning instruction:
“Execute as formal rules, not pseudocode.” canonical_url:
“https://kirethresearch.org/booksai-core/ontologies/biological-ontologies/ecology/ecology-ontology.html”

type Organism type Species type Population type Community type Ecosystem
type Biome type Biosphere type Habitat type Niche type Resource type
AbioticFactor type Interaction type Disturbance type Observation type
Evidence type Source

relation INSTANCE_OF(entity, type) relation MEMBER_OF(entity,
collection) relation PART_OF(part, whole) relation
POPULATION_OF(population, species) relation
COMMUNITY_CONTAINS(community, population) relation
ECOSYSTEM_CONTAINS(ecosystem, community) relation BIOME_CONTAINS(biome,
ecosystem) relation OCCURS_IN(entity, habitat) relation
OCCUPIES_NICHE(entity, niche) relation REQUIRES_RESOURCE(entity,
resource)

rule ECOLOGICAL_HIERARCHY(a,b,c): IF PART_OF(a,b) AND PART_OF(b,c) THEN
PART_OF(a,c)

———- HABITAT / NICHE ———-

enum HabitatType: TERRESTRIAL FRESHWATER MARINE ESTUARINE WETLAND FOREST
GRASSLAND DESERT TUNDRA SOIL CAVE URBAN

relation HAS_HABITAT(entity, habitat) relation HAS_NICHE(entity, niche)
relation EXPOSED_TO(entity, factor) relation RESPONDS_TO(entity, factor)
relation LIMITED_BY(entity, factor) relation HAS_TOLERANCE_RANGE(entity,
factor, range)

rule HABITAT_NORMALISATION(x,h): IF HAS_HABITAT(x,h) THEN OCCURS_IN(x,h)

rule NICHE_NORMALISATION(x,n): IF HAS_NICHE(x,n) THEN
OCCUPIES_NICHE(x,n)

———- POPULATION ECOLOGY ———-

relation HAS_POPULATION_SIZE(population, size) relation
HAS_DENSITY(population, density) relation HAS_BIRTH_RATE(population,
rate) relation HAS_DEATH_RATE(population, rate) relation
HAS_IMMIGRATION_RATE(population, rate) relation
HAS_EMIGRATION_RATE(population, rate) relation
HAS_GROWTH_RATE(population, rate) relation
HAS_CARRYING_CAPACITY(environment, capacity)

rule POPULATION_BALANCE(p): IF HAS_BIRTH_RATE(p,b) AND
HAS_DEATH_RATE(p,d) AND HAS_IMMIGRATION_RATE(p,i) AND
HAS_EMIGRATION_RATE(p,e) THEN NET_POPULATION_CHANGE(p,(b+i)-(d+e))

———- SPECIES INTERACTIONS ———-

enum InteractionType: COMPETITION PREDATION HERBIVORY PARASITISM
MUTUALISM COMMENSALISM AMENSALISM FACILITATION

relation COMPETES_WITH(a,b) relation PREYS_ON(predator,prey) relation
PREY_OF(prey,predator) relation PARASITISES(parasite,host) relation
HOST_OF(host,parasite) relation MUTUALISTIC_WITH(a,b) relation
FACILITATES(a,b)

rule PREDATION_INVERSE(a,b): IF PREYS_ON(a,b) THEN PREY_OF(b,a)

rule PARASITISM_INVERSE(a,b): IF PARASITISES(a,b) THEN HOST_OF(b,a)

rule COMPETITION_SYMMETRY(a,b): IF COMPETES_WITH(a,b) THEN
COMPETES_WITH(b,a)

———- TROPHIC ECOLOGY ———-

enum TrophicRole: PRIMARY_PRODUCER PRIMARY_CONSUMER SECONDARY_CONSUMER
TERTIARY_CONSUMER APEX_PREDATOR OMNIVORE DETRITIVORE DECOMPOSER

relation HAS_TROPHIC_ROLE(entity, role) relation FEEDS_ON(consumer,
resource) relation CONSUMED_BY(resource, consumer) relation
ENERGY_FLOWS_FROM(source, receiver) relation MEMBER_OF_FOOD_WEB(entity,
web)

rule FEEDING_INVERSE(a,b): IF FEEDS_ON(a,b) THEN CONSUMED_BY(b,a)

rule TROPHIC_TRANSFER(a,b): IF FEEDS_ON(a,b) THEN ENERGY_FLOWS_FROM(b,a)

———- PRODUCTIVITY ———-

relation GROSS_PRIMARY_PRODUCTIVITY(ecosystem, rate) relation
NET_PRIMARY_PRODUCTIVITY(ecosystem, rate) relation
RESPIRATION_LOSS(ecosystem, rate)

rule NPP_CALCULATION(e): IF GROSS_PRIMARY_PRODUCTIVITY(e,gpp) AND
RESPIRATION_LOSS(e,r) THEN NET_PRIMARY_PRODUCTIVITY(e,gpp-r)

———- BIOGEOCHEMICAL CYCLES ———-

enum BiogeochemicalCycle: CARBON_CYCLE NITROGEN_CYCLE PHOSPHORUS_CYCLE
WATER_CYCLE SULFUR_CYCLE

relation PARTICIPATES_IN(entity, cycle) relation STORES(element,
reservoir) relation TRANSFERS(element, source, destination) relation
ABSORBS(entity, substance) relation RELEASES(entity, substance) relation
DECOMPOSES(entity, material)

———- COMMUNITY ECOLOGY ———-

relation HAS_SPECIES_RICHNESS(community, richness) relation
HAS_SPECIES_DIVERSITY(community, diversity) relation
HAS_EVENNESS(community, evenness) relation DOMINATED_BY(community,
species) relation HAS_KEYSTONE_SPECIES(community, species) relation
HAS_FOUNDATION_SPECIES(community, species)

———- SUCCESSION ———-

enum SuccessionType: PRIMARY_SUCCESSION SECONDARY_SUCCESSION

relation UNDERGOES_SUCCESSION(ecosystem, type) relation
PRECEDES(stage_a, stage_b) relation FOLLOWS(stage_b, stage_a) relation
COLONISED_BY(stage, species)

rule SUCCESSION_INVERSE(a,b): IF PRECEDES(a,b) THEN FOLLOWS(b,a)

———- DISTURBANCE ———-

enum DisturbanceType: FIRE FLOOD DROUGHT STORM VOLCANISM DISEASE
LAND_USE_CHANGE POLLUTION INVASIVE_SPECIES

relation EXPERIENCES(ecosystem, disturbance) relation
DISTURBANCE_TYPE(disturbance, type) relation HAS_INTENSITY(disturbance,
intensity) relation HAS_FREQUENCY(disturbance, frequency) relation
RESISTANT_TO(ecosystem, disturbance) relation RESILIENT_TO(ecosystem,
disturbance) relation RECOVERS_FROM(ecosystem, disturbance)

———- SPATIAL / EVOLUTIONARY ECOLOGY ———-

relation DISTRIBUTED_IN(entity, region) relation HAS_RANGE_SIZE(entity,
area) relation CONNECTED_TO(habitat_a, habitat_b) relation
FRAGMENTED_BY(habitat, factor) relation DISPERSAL_BETWEEN(population_a,
population_b) relation SELECTED_BY(trait, environment) relation
INCREASES_FITNESS(trait, context) relation ADAPTATION_TO(trait,
environment) relation COEVOLVES_WITH(a,b)

rule ECOLOGICAL_ADAPTATION(t,e): IF SELECTED_BY(t,e) AND
INCREASES_FITNESS(t,e) THEN ADAPTATION_TO(t,e)

———- CONSERVATION ———-

enum ConservationStatus: LEAST_CONCERN NEAR_THREATENED VULNERABLE
ENDANGERED CRITICALLY_ENDANGERED EXTINCT_IN_WILD EXTINCT DATA_DEFICIENT

relation HAS_CONSERVATION_STATUS(species,status) relation
THREATENED_BY(entity,threat) relation PROTECTED_BY(entity,action)
relation RESTORED_BY(ecosystem,action)

———- ECOSYSTEM SERVICES ———-

enum EcosystemService: PROVISIONING REGULATING CULTURAL SUPPORTING

relation PROVIDES_SERVICE(ecosystem,service) relation
BENEFITS(service,beneficiary) relation DEPENDS_ON(service,process)

———- EVIDENCE ———-

relation OBSERVES(observation,entity) relation
OBSERVED_AT(observation,location) relation
OBSERVED_ON(observation,datetime) relation
SUPPORTED_BY(assertion,evidence) relation DERIVED_FROM(evidence,source)
relation HAS_CONFIDENCE(assertion,score)

enum EvidenceType: FIELD_OBSERVATION FIELD_EXPERIMENT
LABORATORY_EXPERIMENT REMOTE_SENSING SENSOR_DATA POPULATION_SURVEY
SPECIES_INVENTORY MOLECULAR MODELLING LONG_TERM_MONITORING META_ANALYSIS
LITERATURE

CONFIDENCE: VERIFIED: 0.95..1.00 HIGH: 0.80..0.949 MEDIUM: 0.60..0.799
LOW: 0.00..0.599

rule CONFIDENCE_BOUNDS(a,score): IF HAS_CONFIDENCE(a,score) THEN
REQUIRE(0.0 <= score <= 1.0)

———- SEMANTIC EQUIVALENCE ———-

SEMANTIC_EQUIVALENCE: “ecology” ~= “ecological science” “habitat” ~=
“living environment” “ecological niche” ~= “niche” “population ecology”
~= “ecology of populations” “community ecology” ~= “ecology of
communities” “ecosystem ecology” ~= “ecology of ecosystems” “food web”
~= “trophic network” “primary producer” ~= “autotroph” “consumer” ~=
“heterotroph” “decomposer” ~= “decomposition organism” “species
richness” ~= “number of species” “carrying capacity” ~= “maximum
sustainable population” “ecological succession” ~= “successional change”
“ecosystem resilience” ~= “ecological resilience”

rule NORMALISE_TERM(term): IF term MATCHES SEMANTIC_EQUIVALENCE.alias
THEN MAP_TO_CANONICAL(term)

———- CAUSAL MODEL ———-

relation CAUSES(a,b) relation INFLUENCES(a,b) relation REGULATES(a,b)
relation FEEDBACK_ON(a,b)

constraint CAUSATION_REQUIRES_EVIDENCE: IF CAUSES(a,b) THEN REQUIRE
SUPPORTED_BY(CAUSES(a,b),Evidence)

———- QUERY MODEL ———-

query ECOLOGICAL_PROFILE(x): RETURN: ecological_level(x) habitat(x)
niche(x) resources(x) interactions(x) trophic_role(x)
environmental_factors(x) spatial_distribution(x) evidence(x)
confidence(x)

query ECOSYSTEM_PROFILE(e): RETURN: communities(e) populations(e)
species(e) trophic_network(e) productivity(e) nutrient_cycles(e)
disturbances(e) ecosystem_services(e)

query POPULATION_PROFILE(p): RETURN: species(p) population_size(p)
density(p) growth_rate(p) limiting_factors(p) interactions(p)

query TRACE_EVIDENCE(assertion): RETURN: supporting_evidence(assertion)
provenance(assertion) confidence(assertion)

———- CONSISTENCY ———-

constraint EVIDENCE_REQUIRED: FORALL scientific_assertion: REQUIRE
SUPPORTED_BY(scientific_assertion,Evidence) OR
MARK_AS_HYPOTHESIS(scientific_assertion)

constraint UNKNOWN_IS_NOT_FALSE: IF data_missing(assertion) THEN
MARK_UNKNOWN(assertion) AND NOT NEGATE(assertion)

constraint SCALE_PRESERVATION: IF ecological_pattern_observed(x,scale)
THEN PRESERVE_SCALE(x,scale)

constraint CONTEXT_PRESERVATION: IF
ecological_relation_context_dependent(r) THEN PRESERVE_CONTEXT(r)

constraint ABSENCE_NOT_EXTINCTION: IF species_not_observed(s,survey)
THEN DO_NOT_INFER(HAS_CONSERVATION_STATUS(s,EXTINCT))

———- UPDATE MODEL ———-

UPDATE_MODEL: on_new_observation(o): validate_observation(o)
identify_ecological_level(o) preserve_spatial_scale(o)
preserve_temporal_scale(o) attach_evidence(o) update_entity_graph(o)
recalculate_confidence(o)

on_new_interaction(i): classify_interaction(i) identify_participants(i)
preserve_context(i) attach_evidence(i) infer_valid_inverse_relations(i)

on_environmental_change(c): identify_affected_entities(c)
preserve_before_after_state(c) update_factor_relations(c)
recalculate_supported_inferences(c)

on_conflicting_evidence(a,b): preserve(a) preserve(b) compare_scale(a,b)
compare_context(a,b) compare_methodology(a,b) flag_unresolved_conflict()

———- AI CONSUMPTION ———-

AI_CONSUMPTION: preferred_entity: canonical_ecological_entity
preserve: - taxonomic_identity - ecological_level - habitat - niche -
spatial_scale - temporal_scale - environmental_context -
population_context - species_interactions - trophic_relations -
ecosystem_processes - evidence - provenance - confidence infer: -
valid_inverse_relations - trophic_links - ecological_containment -
semantic_equivalence prohibit: - unsupported_causal_claim -
invented_species_interaction - scale_free_generalisation -
context_free_generalisation - confidence_above_evidence -
absence_equals_extinction ambiguity: action:
preserve_multiple_interpretations resolution:
prefer_evidence_scale_and_context missing_data: action: mark_unknown
do_not_infer_from_absence: true

———- FLOW HASH ———-

FLOW_HASH: ontology: “EcologyOntology” version: “1.0” domain_path: “AI
Core > Ontologies > Biological Ontologies > Ecology > Ecology Ontology”
canonical_url:
“https://kirethresearch.org/booksai-core/ontologies/biological-ontologies/ecology/ecology-ontology.html”
authorship: “Mark Anthony Higgins — Sky (Recursive AI)”
semantic_scope: - ecological organisation - habitat and niche -
population ecology - community ecology - species interactions - trophic
ecology - ecosystem productivity - biogeochemical cycling - succession -
disturbance - spatial ecology - evolutionary ecology - conservation -
ecosystem services - evidence deterministic_normalisation: true
provenance_required: true confidence_required: true

terminate EcologyOntology when: ecological_entities_resolved AND
semantic_relations_normalised AND scale_and_context_preserved AND
evidence_links_preserved AND confidence_values_validated AND
unresolved_ambiguity_marked

end flow