🌈 species

• plants: hundreds of species in citadel genesis and batuka

• animals: dozens of species in citadel genesis and batuka

• fungi: dozens of species in batuka

• system of tagging

  • abundance: yes, limited, trial, none, gone
  • supply: yes, later, wishlist, no
  • margin: high, mid, low, none
  • autonomy: support, staple, extra

• all

• research

• sets

  • staple
  • available
  • super
  • major

• encoding

  practical spec for encoding the botanical knowledge graph into cyber

• one species = one particle

  each of the 205 species pages in this graph:

  • has content: description, ecology, uses, observations, images
  • gets content-addressed via IPFS → CID
  • becomes a particle in Bostrom
  • can be cyberlinked to anything: other species, locations, compounds, observations

• example: coffea arabica

  particle: QmXk7f...  (IPFS CID of the species page)
  
  cyberlinks from this particle:
    coffea arabica → "family" → Rubiaceae
    coffea arabica → "grows_at" → cv.land
    coffea arabica → "needs" → shade
    coffea arabica → "companion" → calliandra calothyrsus
    coffea arabica → "produces" → caffeine
    coffea arabica → "observed_by" → [neuron address]
  

• observation cyberlinks

  every time a neuron observes a species in the field:

  neuron → "observed" → photo_cid
  photo_cid → "depicts" → species_particle
  photo_cid → "location" → gps_cid
  photo_cid → "timestamp" → block_height
  

  the observation is permanent, verifiable, and linked to the knowledge graph

• what 205 species create

  with ~10 cyberlinks per species (conservative):

  • 2050 cyberlinks encoding ecological relationships
  • a queryable biological knowledge graph inside Bostrom
  • rank computation reveals: which species is most connected (ecologically central), which location has highest biodiversity, which compounds appear across most species

• search queries that become possible

  • “nitrogen fixing tree” → ranked list of species by relevance
  • “companion for coffea arabica” → species connected by “companion” cyberlinks
  • “medicinal fungi” → intersection of fungi particles and medicine cyberlinks
  • “what grows at 1500m elevation” → location-linked species subgraph

• bulk encoding

  the 205 species pages can be batch-uploaded:

  for each .md file in pages/ where tags contain "species":
      cid = ipfs.add(file)
      cyberlink(neuron, cid)                    // "created" link
      cyberlink(cid, genus_cid, "belongs_to")   // taxonomy edge
      cyberlink(cid, location_cid, "found_at")  // geography edge
  

  cost: ~600 cyberlink transactions. at current bandwidth rates, achievable with moderate CYB stake via investmint

• from graph to protocol

  this Logseq graph is a prototype. the species pages, the [[wiki-links]], the tags — they ARE a knowledge graph. the step from markdown to Bostrom is mechanical:

  • markdown page → IPFS CID → particle
  • [[wiki-link]] → cyberlink
  • tag → typed edge
  • the graph is already built. it just needs to be committed to the protocol