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How does the Australian lungfish see?

The Australian lungfish (Neoceratodus forsteri) is a animal in the order Ceratodontiformes. Its eyes belong to the vision type .

Measured in this species: colour. Measured colour or sharpness: a measured receptor set or acuity in this species; other dials come from relatives or group defaults. Every value below carries its evidence level and sources; nothing is typed by hand.

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What stands out

The six dials

Evidence levels: how the tiers work. "Measured" means a value measured in this species; "Estimated" values come from a close relative or an eye-size formula.

Vision values for the Australian lungfish (Neoceratodus forsteri), catalogue-v1
DialValueEvidenceSources
ColourColour receptors
4 receptor classes: 366 nm (UVS), 479 nm (SWS (blue)), 558 nm (LWS (long)), 623 nm (LWS (long))
measured in this species
Measured[1][2]
Ultraviolet
yes: at least one receptor peaks in the ultraviolet
Measured
SharpnessNo value in the catalogue.
Field of viewNo value in the catalogue.
Sharp zones (foveas)No value in the catalogue.
Night visionActivity pattern
nocturnal
group default: mode of tier-A values in vision type phylum Chordata within phylum Chordata (1 species: Sphenodon punctatus)
Group default[3][4][5][6]
Rods vs cones
rod-dominated
Group default[3][4][5][6]
Motion (flicker fusion)Flicker fusion frequency
55.4 Hz
group default: median of tier-A values in vision type phylum Chordata within phylum Chordata (1 species: Sphenodon punctatus)
Group default[7][8][9]

Related animals

More other: all other with measured vision data.

Sources

  1. VPOD in-vivo (MSP / single-cell) lambda max compendium, file scp_cleaned.csv, VPOD GitHub (Frazer et al. 2025 bioRxiv 10.1101/2025.08.22.671864). github.com/VisualPhysiologyDB/visual-physiology-opsin-db/tree/main/scripts_n_notebooks/vpod_ML_workflows/mine_n_match/data_sources/lmax/vpod
  2. Schweikert LE, Fitak RR, Caves EM, Sutton TT, Johnsen S. 2018. Spectral sensitivity in ray-finned fishes: diversity, ecology and shared descent. J Exp Biol 221:jeb189761. Table S1. doi.org/10.1242/jeb.189761
  3. Anderson SR, Wiens JJ. 2017. Out of the dark: 350 million years of conservatism and evolution in diel activity patterns in vertebrates. Evolution 71:1944-1959. Dryad doi:10.5061/dryad.fg700. doi.org/10.5061/dryad.fg700
  4. Banks MS, Sprague WW, Schmoll J, Parnell JAQ, Love GD. 2015. Science Advances 1:e1500391. doi.org/10.1126/sciadv.1500391
  5. Oskyrko O, Mi C, Meiri S, Du W. 2024. ReptTraits: a comprehensive dataset of ecological traits in reptiles. Scientific Data 11 (doi:10.1038/s41597-024-03079-5). Dataset v1-2 (includes Meiri 2018 lizard traits). doi.org/10.6084/m9.figshare.24572683.v4
  6. Moura et al. 2024. A phylogeny-informed characterisation of global tetrapod traits addresses data gaps and biases. PLoS Biol 22:e3002658. TetrapodTraits v3.0.1.. doi.org/10.5281/zenodo.22536349
  7. Healy K, McNally L, Ruxton GD, Cooper N, Jackson AL. 2013. Metabolic rate and body size are linked with perception of temporal information. Animal Behaviour 86:685-696. Table 1. doi.org/10.1016/j.anbehav.2013.06.018
  8. Inger R, Bennie J, Davies TW, Gaston KJ. 2014. Potential biological and ecological effects of flickering artificial light. PLoS ONE 9(5): e98631. Table 3. doi.org/10.1371/journal.pone.0098631
  9. Lafitte A, Sordello R, Legrand M, Nicolas V, Obein G, Reyjol Y. 2022. A flashing light may not be that flashy: A systematic review on critical fusion frequencies. PLoS ONE 17(12): e0279718. S10 File (CFF database). doi.org/10.1371/journal.pone.0279718

Every value cites its sources (all sources). Data: catalogue-v1, built 2026-09-29. Accuracy notes: how accurate is this?