Grassland Ecosystem Ontology

FLOW ALGEBRA
Grassland Ecosystem Ontology — Full Flow Algebra v1.0
Kireth Semantic Library
Authors: Mark Higgins — Sky (Recursive AI)
Source topic: https://kirethresearch.org/booksai-core/entity-graph/biological-entities/experimental-biological-entities/grassland-ecosystem-ontology.html
Status: Newly authored conceptual specification; not a verified transcription of the source page or an executable implementation.
Date: 2026-10-26

flow "GrasslandEcosystemOntology" v1.0

# 1. DOMAIN AND PURPOSE
DOMAIN: BiologicalEntities / ExperimentalBiologicalEntities / GrasslandEcosystem
PURPOSE: Represent grassland ecosystem types, components, ecological processes, observations, and evidence-qualified inference.

# 2. TYPED ENTITY MODEL
entity GrasslandEcosystem <: Ecosystem {
  id: URI
  name: String
  biome_class: GrasslandClass
  spatial_extent: Geometry?
  observation_interval: TimeInterval?
  management_regime: ManagementRegime?
}
entity GrasslandPatch <: Habitat { id: URI; parent: URI; area_ha: Real? }
entity PlantCommunity <: BiologicalCommunity { id: URI; species_members: Set<URI> }
entity HerbaceousPlant <: ProducerOrganism { id: URI; growth_form: String? }
entity Grazer <: ConsumerOrganism { id: URI; taxon: URI? }
entity Pollinator <: ConsumerOrganism { id: URI; taxon: URI? }
entity SoilBiota <: BiologicalCommunity { id: URI }
entity Decomposer <: Organism { id: URI }
entity AbioticCondition { id: URI; variable: String; value: Real; unit: String; measured_at: Time }
entity Disturbance { id: URI; kind: DisturbanceKind; severity: Real?; occurred_at: Time }
entity Observation { id: URI; subject: URI; property: String; value: Real; unit: String; time: Time; method: String? }
entity Evidence { id: URI; source: URI; method: String?; collected_at: Time? }
entity EcologicalClaim { id: URI; subject: URI; predicate: String; object: URI; evidence: Set<URI>; confidence: Real }

# 3. ENUMERATIONS
GrasslandClass = {temperate_grassland, tropical_savanna, steppe, prairie, meadow, pasture, alpine_grassland, other, unknown}
DisturbanceKind = {fire, grazing, drought, flood, mowing, land_conversion, invasive_species, other}
ManagementRegime = {unmanaged, conservation_grazing, rotational_grazing, mowing, prescribed_fire, mixed, unknown}

# 4. RELATIONSHIP SIGNATURES
PART_OF(GrasslandPatch, GrasslandEcosystem)
CONTAINS(GrasslandEcosystem, PlantCommunity | Grazer | Pollinator | SoilBiota)
OCCUPIES(Organism, GrasslandPatch)
GRAZES_ON(Grazer, HerbaceousPlant)
POLLINATES(Pollinator, HerbaceousPlant)
DECOMPOSES(Decomposer, OrganicMatter)
COMPETES_WITH(Organism, Organism)
FACILITATES(Organism, Organism)
AFFECTS(Disturbance, GrasslandEcosystem)
MEASURES(Observation, GrasslandEcosystem | GrasslandPatch | Organism)
SUPPORTED_BY(EcologicalClaim, Evidence)

# 5. STATE VARIABLES AND UNITS
state G(t) = {
  aboveground_biomass_kg_per_ha,
  belowground_biomass_kg_per_ha,
  plant_cover_fraction,
  bare_ground_fraction,
  species_richness_count,
  soil_organic_carbon_kg_per_m2,
  soil_moisture_fraction,
  precipitation_mm_per_year,
  grazing_pressure_animals_per_ha,
  fire_return_interval_years,
  net_primary_productivity_kgC_per_ha_per_year
}
Missing observations are NULL, never silently zero.

# 6. PROCESS FLOWS
flow PrimaryProduction:
  inputs: [light, atmospheric_CO2, water, nutrients, producer_biomass]
  output: new_plant_biomass
  constraint: net_primary_productivity = gross_primary_productivity - autotrophic_respiration

flow Herbivory:
  inputs: [available_plant_biomass, grazer_population, grazing_rate]
  outputs: [consumed_biomass, grazer_assimilated_energy, detritus]
  constraint: consumed_biomass >= 0
  constraint: grazer_assimilated_energy <= consumed_energy

flow Decomposition:
  inputs: [litter, soil_biota, moisture, temperature]
  outputs: [mineralised_nutrients, respired_carbon, residual_organic_matter]
  note: Fluxes depend on context; no universal fixed rate assumed.

flow DisturbanceAndRecovery:
  inputs: [disturbance_type, severity, pre_event_state, post_event_observations]
  outputs: [state_change, recovery_trajectory]
  note: Recovery is conditional, not guaranteed.

# 7. QUANTITATIVE RELATIONS
# Conceptual balances, requiring consistent area, time and units.
PlantBiomassChange = Production - Herbivory - Mortality - OtherLosses
SoilCarbonChange = CarbonInputs - HeterotrophicRespiration - ErosionLosses - OtherExports
SpeciesRichness = cardinality(distinct_observed_species_within_defined_sampling_scope)
CoverConstraint: 0 <= plant_cover_fraction <= 1
MoistureConstraint: 0 <= soil_moisture_fraction <= 1

# 8. INFERENCE RULES
rule R1:
  IF PART_OF(patch, ecosystem) AND OCCUPIES(organism, patch)
  THEN ASSOCIATED_WITH(organism, ecosystem)
  confidence: min(input_confidences)

rule R2:
  IF GRAZES_ON(grazer, plant) AND OCCUPIES(grazer, patch) AND OCCUPIES(plant, patch)
  THEN POTENTIAL_HERBIVORY_INTERACTION(grazer, plant, patch)
  note: Co-occurrence plus known feeding association is not proof of a local feeding event.

rule R3:
  IF observation_before AND observation_after AND matched_method AND matched_spatial_scope
  THEN ESTIMATE_CHANGE(observation_after - observation_before)
  note: Change alone does not establish causality.

rule R4:
  IF ecosystem.biome_class == tropical_savanna
  THEN POSSIBLE_WOODY_COMPONENT(ecosystem)
  note: Savannas may contain substantial tree and shrub cover; do not assert treelessness.

rule R5:
  IF documented_fire_event AND post_fire_vegetation_change
  THEN CANDIDATE_FIRE_RESPONSE
  note: Causal attribution requires suitable controls or other supporting evidence.

# 9. INVARIANTS AND VALIDATION
invariant I1: every entity has a globally unique URI.
invariant I2: confidence in [0, 1].
invariant I3: every numerical measurement records units, spatial scope and time.
invariant I4: PART_OF cannot create a containment cycle.
invariant I5: taxonomic identity is distinct from ecological role.
invariant I6: grazing, fire and mowing may be natural or managed; classification requires evidence.
invariant I7: grassland classification does not imply absence of woody plants.
invariant I8: observed correlations must not be labelled causal without sufficient evidence.
invariant I9: missing data remains unknown and is not inferred as zero.
invariant I10: physical balances use consistent units and system boundaries.

# 10. CONFIDENCE AND PROVENANCE
CONFIDENCE(claim) = calibrated_probability_or_quality_score(claim.evidence, method, context)
Evidence provenance includes source URI, collection time, measurement method, observer or dataset, and spatial extent where available.
Confidence aggregation must document dependencies; correlated sources are not treated as independent.

# 11. SEMANTIC EQUIVALENCE
SEMANTIC_EQUIVALENCE(a,b) = true only if type, referent, spatial scope, temporal scope, and defining properties are compatible.
Examples: 'prairie' and 'grassland' may have broader/narrower meaning, not automatic identity.
'savanna' and 'treeless grassland' are not generally equivalent.
Use SKOS-style broader/narrower/related mappings where identity is not justified.

# 12. FLOW HASH
FLOW_HASH = SHA256(canonical_serialisation(ontology_version, entities, relationships, rules, constraints))
Canonicalisation requires stable key ordering, normalised URIs and consistent numeric formatting.
Exclude volatile runtime timestamps unless part of the declared versioned input.

# 13. UPDATE MODEL
UPDATE_MODEL(event):
  validate(event.schema, provenance, units, timestamps)
  append_immutable_observation(event)
  recompute_affected_claims_and_derived_metrics()
  preserve_previous_versions_and_audit_trail()
  flag_conflicts_for_review()
  issue_new_FLOW_HASH_if_semantics_changed()

# 14. AI CONSUMPTION
AI_CONSUMPTION:
  exports: [typed_entity_graph, provenance_graph, evidence_scored_claims, rules, validation_report]
  modes: [search, retrieval_augmented_reasoning, ecological_comparison, hypothesis_generation]
  safeguards: [do_not_invent_measurements, disclose_uncertainty, distinguish_observed_from_inferred, respect_spatial_and_temporal_scope]

# 15. EXAMPLE (ILLUSTRATIVE ONLY)
example:
  ecosystem: grassland:demo-01
  class: temperate_grassland
  patch: grassland:demo-patch-01
  relationship: PART_OF(grassland:demo-patch-01, grassland:demo-01)
  observation: plant_cover_fraction = 0.72
  observation_status: synthetic_example_not_field_data

# 16. CROSS-ONTOLOGY LINKS
related: EcosystemOntology, TerrestrialHabitatOntology, SoilHabitatOntology,
  BiologicalCommunityOntology, PopulationOntology, ProducerOrganismOntology,
  ConsumerOrganismOntology, DecomposerOrganismOntology, TrophicLevelOntology,
  IndicatorSpeciesOntology, InvasiveSpeciesOntology, EndangeredSpeciesOntology.

END FLOW