Detritus Ontology

FLOW ALGEBRA
Detritus Ontology — Full Conceptual Flow Algebra v1.0
Kireth Semantic Library
Authors: Mark Higgins — Sky (Recursive AI)
Source: https://kirethresearch.org/booksai-core/entity-graph/biological-entities/experimental-biological-entities/detritus-ontology.html
Status: Proposed conceptual formalisation; not a verified transcription of source-page code or an executable interpreter.
Locale: en-GB

flow "DetritusOntology" v1.0

# 1. DOMAIN AND SCOPE
DOMAIN := BiologicalEntities.ExperimentalBiologicalEntities.Detritus
PURPOSE := represent non-living particulate organic material, its origins, transformations,
           ecological relationships, and evidence-qualified measurements.
BOUNDARY := detritus is distinguished from living biomass and dissolved organic matter;
            classifications depend on the observational and disciplinary context.

# 2. TYPED ENTITIES
type Entity { id: URI, label: String, provenance: EvidenceRef? }
type Ecosystem extends Entity { biome: String?, location: GeoRef? }
type Habitat extends Entity { ecosystem: Ecosystem.id }
type Organism extends Entity { taxon: TaxonRef? }
type DetritusPool extends Entity {
  habitat: Habitat.id,
  origin: Enum(plant, animal, microbial, mixed, unknown),
  medium: Enum(soil, freshwater, marine, terrestrial_surface, other),
  form: Enum(leaf_litter, woody_debris, carcass_fragment, faecal_particle,
             particulate_organic_matter, mixed),
  dry_mass_kg: NonNegativeReal?,
  carbon_mass_kg: NonNegativeReal?,
  nitrogen_mass_kg: NonNegativeReal?,
  timestamp: DateTime,
  observation_method: String?
}
type DetritalParticle extends Entity { pool: DetritusPool.id, particle_size_mm: NonNegativeReal? }
type Decomposer extends Organism {}
type Detritivore extends Organism {}
type EnvironmentalCondition extends Entity {
  temperature_C: Real?, moisture_fraction: Fraction?, oxygen_mg_L: NonNegativeReal?, pH: Real?
}
type Transformation extends Entity {
  kind: Enum(fragmentation, leaching, microbial_decomposition, mineralisation,
             humification, burial, transport),
  start: DateTime, end: DateTime?, evidence: EvidenceRef?
}
type EvidenceRef { source: URI, observed_at: DateTime?, method: String?, uncertainty: String? }
type Fraction := Real where 0 <= value <= 1
type NonNegativeReal := Real where value >= 0

# 3. RELATIONSHIP SIGNATURES
relation LOCATED_IN(DetritusPool, Habitat)
relation DERIVED_FROM(DetritusPool, Organism | OrganicMatterSource)
relation CONTAINS_PARTICLE(DetritusPool, DetritalParticle)
relation CONSUMED_BY(DetritusPool, Detritivore)
relation DECOMPOSED_BY(DetritusPool, Decomposer)
relation SUBJECT_TO(DetritusPool, Transformation)
relation MODULATED_BY(Transformation, EnvironmentalCondition)
relation RELEASES_NUTRIENT(Transformation, NutrientPool)
relation TRANSFERRED_TO(DetritusPool, DetritusPool)
relation CONTRIBUTES_TO(DetritusPool, SoilOrganicMatterPool)
relation SUPPORTS_FOOD_WEB(DetritusPool, Ecosystem)

# 4. CLASSIFICATION AND SEMANTICS
class Detritus := non_living AND organic AND particulate
class LeafLitter subset Detritus
class CoarseWoodyDebris subset Detritus
class AnimalRemainsFragment subset Detritus
class FaecalParticulateMatter subset Detritus
NOT_EQUIVALENT(Detritus, LivingBiomass)
NOT_EQUIVALENT(Detritus, DissolvedOrganicMatter)
SEMANTIC_EQUIVALENCE("particulate detrital organic matter", "detrital POM")
SEMANTIC_EQUIVALENCE("leaf litter", "fallen leaf detritus") when context = terrestrial_ecology
# Semantic equivalence is scoped, not a universal taxonomic identity.

# 5. CONSERVATION AND QUANTITATIVE MODELS
# Every stock and flux must share compatible spatial and temporal boundaries.
MODEL DetritalMassBalance:
  M(t+dt) = M(t) + Input(dt) - Export(dt) - Mineralised(dt) - OtherLoss(dt)
  constraint: M(t) >= 0
  constraint: all terms measured in kg dry mass over the same dt
  note: fragmentation redistributes particle sizes; it does not itself destroy mass.

MODEL FirstOrderDecayApproximation:
  dM/dt = -k * M
  M(t) = M0 * exp(-k*t)
  parameters: M0 >= 0; k >= 0; t >= 0
  units: k = inverse_time
  assumption: closed, homogeneous pool with approximately constant conditions
  warning: field decay often varies with substrate quality, temperature and moisture.

MODEL CarbonNitrogenRatio:
  CN = carbon_mass_kg / nitrogen_mass_kg
  precondition: nitrogen_mass_kg > 0
  output: dimensionless

MODEL DecompositionFlux:
  F_decomp = M_start - M_end + Inputs - Exports - OtherLosses
  note: apply only with complete bookkeeping and consistent sign conventions.

# 6. INFERENCE RULES
rule R01:
  IF non_living(x) AND organic(x) AND particulate(x)
  THEN candidate_type(x, Detritus)
  confidence: evidence_dependent

rule R02:
  IF DERIVED_FROM(p, plant) AND form(p) = leaf_litter
  THEN subtype(p, LeafLitter)

rule R03:
  IF DECOMPOSED_BY(p, organism) AND measured_mass_loss(p) > 0
  THEN candidate_process(p, microbial_decomposition)
  guard: exclude alternative loss pathways before causal attribution

rule R04:
  IF CONSUMED_BY(p, animal)
  THEN candidate_role(animal, Detritivore)
  guard: repeated dietary evidence needed for stable trophic classification

rule R05:
  IF TRANSFERRED_TO(p1, p2) AND same_material_traced(p1, p2)
  THEN linked_detrital_flux(p1, p2)

rule R06:
  IF carbon_mass_kg(p) > 0 AND nitrogen_mass_kg(p) > 0
  THEN derive(CN(p))

rule R07:
  IF mineralisation_observed(p, nutrient)
  THEN RELEASES_NUTRIENT(process(p), nutrient)
  guard: net immobilisation may coexist with gross mineralisation

# 7. VALIDATION AND INVARIANTS
invariant V01: unique(Entity.id)
invariant V02: DetritusPool.dry_mass_kg >= 0 when known
invariant V03: 0 <= DetritusPool.carbon_mass_kg <= DetritusPool.dry_mass_kg when both known
invariant V04: 0 <= DetritusPool.nitrogen_mass_kg <= DetritusPool.dry_mass_kg when both known
invariant V05: transformation.end >= transformation.start when end exists
invariant V06: conservation_residual within declared measurement uncertainty
invariant V07: unknown != zero; missing observations must not be imputed silently
invariant V08: habitat, units, observation window and sampling method retained for comparisons
invariant V09: provenance recorded for asserted ecological causal relationships

# 8. CONFIDENCE AND EVIDENCE
CONFIDENCE(assertion) := calibrated_score in [0,1] | unknown
EVIDENCE_LEVEL := direct_measurement | replicated_study | model_estimate |
                  expert_classification | unverified_claim
COMBINE_EVIDENCE: account for correlated sources; never sum confidence scores blindly
UNCERTAINTY: propagate sampling error, spatial heterogeneity and model assumptions

# 9. FLOW HASH AND IDENTITY
FLOW_HASH(entity) := SHA256(canonicalise(
  ontology_version, entity.id, entity.type, typed_attributes, relations,
  observation_time, provenance_identifiers
))
CANONICALISE: UTF-8; sorted keys; stable identifiers; normalised units
NOTE: hash records semantic snapshot identity, not proof of scientific correctness.

# 10. UPDATE MODEL
UPDATE_MODEL:
  receive(new_observation)
  validate_schema_and_units()
  preserve_previous_snapshot()
  reconcile_entity_identity_and_provenance()
  recalculate_derived_quantities()
  rerun_affected_inference_rules()
  compare_FLOW_HASH()
  publish_versioned_change_log()
  flag_conflicts_for_review()

# 11. AI CONSUMPTION
AI_CONSUMPTION:
  expose: entity IDs, classes, relationships, definitions, units, provenance,
          uncertainty, confidence, temporal validity, model assumptions
  permit: evidence-linked retrieval, qualified inference, comparison and explanation
  prohibit: unsupported causal claims, fabricated measurements, conflation of
            particulate and dissolved pools, silent unit conversions
  output: structured semantic records with traceable supporting evidence

# 12. EXAMPLE INSTANCE (ILLUSTRATIVE, NOT FIELD DATA)
entity detritus:leaf_litter_sample_001 : DetritusPool {
  habitat: habitat:temperate_forest_floor_001,
  origin: plant,
  medium: soil,
  form: leaf_litter,
  dry_mass_kg: 1.0,
  carbon_mass_kg: 0.45,
  nitrogen_mass_kg: 0.015,
  timestamp: "2026-10-26T00:00:00Z",
  observation_method: "synthetic demonstration"
}
derive CN(detritus:leaf_litter_sample_001) = 30
status: synthetic_example

# 13. CROSS-ONTOLOGY LINKS
LINK OrganicMatterOntology: particulate organic matter and carbon stocks
LINK DecomposerOrganismOntology: microbial breakdown and nutrient release
LINK SoilHabitatOntology: litter horizons and soil organic matter
LINK ForestEcosystemOntology: forest-floor litter and carbon cycling
LINK FoodChainOntology: detrital food chains
LINK EcologicalResourceOntology: nutrient availability and resource transfers

# 14. AUTHORSHIP AND LICENCE NOTE
Authors: Mark Higgins — Sky (Recursive AI)
Project: Kireth Semantic Library, https://kirethresearch.org
Research intent: openly reusable conceptual ontology specification, subject to the
licence and attribution terms published by Kireth Research.
END FLOW