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How does the agouti see?

The agouti (Dasyprocta leporina) is a mammal in the order Rodentia. Its eyes belong to the vision type Small prey mammal (UV).

Measured in this species: sharpness and night vision. 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 agouti (Dasyprocta leporina), catalogue-v1
DialValueEvidenceSources
ColourColour receptors
2 receptor classes: 400 nm (VS/SWS (violet)), 530 nm (MWS (green))
receptor set of nearest measured relative Cavia porcellus (same order Rodentia)
Group default[1][2]
SharpnessAcuity
6.21 cycles per degree
median of 1 anatomical-ganglion rows (method priority rule)
Measured[3]
Field of viewBinocular overlap
52°
median of 15 relatives in order Rodentia: Octodon degus, Octodon lunatus, Rattus rattus, Mus musculus, Mesocricetus auratus, Sciurus carolinensis
Group default[4][5][6][7]
Sharp zones (foveas)Number of foveas
0
median of 1 relatives in genus Dasyprocta: Dasyprocta punctata
Estimated[8]
Fovea type
horizontal streak		Estimated[8]
Night visionActivity pattern
diurnal
mode of 6 rows (of 6 rows): diurnal; diurnal/crepuscular; nocturnal; photopic
Measured (not re-verified)[9][10][11][12][13]
Rods vs cones
cone-dominated
nocturnal -> rod-dominated; crepuscular / cathemeral / mixed -> mixed; diurnal -> cone-dominated
Derived[9][10][11][12][13]
Motion (flicker fusion)Flicker fusion frequency
62.5 Hz
median of 7 relatives in order Rodentia: Rattus norvegicus, Cavia porcellus, Mus musculus, Callospermophilus lateralis, Tamias amoenus, Tamiasciurus hudsonicus
Group default[14][15][16][17]

Related animals

More mammals: all mammals with measured vision data.

Sources

  1. Longcore T. 2023. A compendium of photopigment peak sensitivities and visual spectral response curves of terrestrial wildlife to guide design of outdoor nighttime lighting. Basic Appl Ecol 73:40-50. doi:10.1016/j.baae.2023.09.002. doi.org/10.5281/zenodo.8432720
  2. 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
  3. Veilleux CC, Kirk EC 2014. Visual acuity in mammals. Brain Behav Evol 83:43, Supplementary Table 1 (cleaned CSV in Evo-M1-Trait-Data). doi.org/10.1159/000357830
  4. Heesy CP 2004. On the relationship between orbit orientation and binocular visual field overlap in mammals. Anat Rec 281A:1104, Table 1. doi.org/10.1002/ar.a.20116
  5. Heffner RS, Heffner HE 1992. Visual factors in sound localization in mammals. J Comp Neurol 317:219, Table 1 (via Evo-M1 sensory merge). doi.org/10.1002/cne.903170302
  6. Vega-Zuniga T, Medina FS, Fredes F, et al. 2013. Does nocturnality drive binocular vision? Octodontine rodents as a case study. PLoS ONE 8: e84199.. doi.org/10.1371/journal.pone.0084199
  7. Vega-Zuniga T, Medina FS, Marín G, Letelier JC, Palacios AG, Němec P, Schleich CE, Mpodozis J. (2017). Selective binocular vision loss in two subterranean caviomorph rodents: Spalacopus cyanus and Ctenomys talarum. Scientific reports
  8. Kopania EEK, Clark NL. 2025. Mammalian retinal specializations for high acuity vision evolve in response to both foraging strategies and morphological constraints. Evolution Letters 9: qrae072. Supplementary Tables S1-S2.. doi.org/10.1093/evlett/qrae072
  9. Wilman et al. 2014 EltonTraits 1.0, MamFuncDat.txt. doi.org/10.6084/m9.figshare.3559887.v1
  10. Maor R, Dayan T, Ferguson-Gow H, Jones KE. 2017. Temporal niche expansion in mammals from a nocturnal ancestor after dinosaur extinction. Nature Ecology & Evolution 1:1889-1895. Supplementary Table 1. doi.org/10.1038/s41559-017-0366-5
  11. Jones KE et al. 2009. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648. Ecological Archives E090-184. doi.org/10.1890/08-1494.1
  12. Schmitz L, Motani R. 2011. Science 332:705-708, SOM. doi.org/10.1126/science.1200043
  13. 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
  14. Haarlem CS, Hynes C, Jackson AL, Mitchell KJ, O'Connell RG, Healy K. 2026. Pace of ecology drives the tempo of visual perception across the animal kingdom. Nature Ecology & Evolution (doi:10.1038/s41559-026-02994-7). Figshare dataset 10.6084/m9.figshare.30556475. doi.org/10.6084/m9.figshare.30556475
  15. 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
  16. 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
  17. 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?