species · agnt.eco

A graph reads what an ecosystem holds dear.

Curated Species nodes from the nine agnt eco agents, ranked by a six-component centrality score derived from the knowledge graph itself — not from how often the curator typed "important".

How the centrality score is built

Importance in an ecosystem is multi-dimensional. A single number is a compromise — but a careful compromise is more useful than narrative pull alone. Each species gets six component scores, each normalised inside its agent's set, then combined into one 0–100 figure.

25 %
structural degree

Web of connections

A weighted sum of all the species' edges in the graph. Trophic edges (FEEDS, MYCORRHIZAL_WITH, DECAYS) count more than mention-edges. Total edge load is the strongest single signal that the network already treats a species as a hub.

20 %
cross-agent recognition

Seen across systems

Species that appear under more than one agent's Species_<Agent> label, or that connect to the central SharedSpecies hub via MANIFESTS_AS, are by definition relevant beyond a single river or forest. The network as a whole has voted.

15 %
trophic position

Where it sits in the food web

The FEEDS in-degree (how many species this one supports) plus a bonus when trophic_role contains "apex", "keystone", "foundation" or "ecosystem engineer". Predators and producers both score; passive consumers don't.

15 %
curation depth

How much we have written about it

log(1 + facts_attached + publications_attached). A species the curator returned to many times is, demonstrably, one the curator found load-bearing — provided we read this as attention paid, not as truth proven.

15 %
event load

Pressure it carries

The number of EcologicalEvent nodes that stress it plus the number of PolicyContext nodes that protect it. Species at the centre of management decisions or active threats score higher here.

10 %
habitat breadth

How many habitats it uses

Count of distinct HABITAT edges. Breadth without hub-status alone is weak signal — which is why this component has the smallest weight — but a species using many habitats is usually doing real work in each.

// each component is min-max normalised within the agent's species set
score = 100 × (
   0.25 · structural_degree
   + 0.20 · cross_agent_recognition
   + 0.15 · trophic_position
   + 0.15 · curation_depth
   + 0.15 · event_load
   + 0.10 · habitat_breadth
)
What this score is not. It is not an ecological truth claim. It is a graph-derived proxy: the more the network has already invested in a species — through trophic structure, curated facts, cross-agent reuse — the higher it scores. A species missing from our graph cannot be central here, however central it is in the world. Use this to find leverage points and gaps — not to declare winners.

Nine systems, their curated species

Each agent's curated Species_<Agent> set, with the top three by centrality. Click an agent to see the full ranked list and per-species component breakdowns.

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