IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v10y2019i1d10.1038_s41467-018-08142-5.html
   My bibliography  Save this article

Avian UV vision enhances leaf surface contrasts in forest environments

Author

Listed:
  • Cynthia Tedore

    (Lund University
    University of Hamburg)

  • Dan-Eric Nilsson

    (Lund University)

Abstract

UV vision is prevalent, but we know little about its utility in common general tasks, as in resolving habitat structure. Here we visualize vegetated habitats using a multispectral camera with channels mimicking bird photoreceptor sensitivities across the UV-visible spectrum. We find that the contrast between upper and lower leaf surfaces is higher in a UV channel than in any visible channel, and that this makes leaf position and orientation stand out clearly. This was unexpected since both leaf surfaces reflect similarly small proportions (1–2%) of incident UV light. The strong UV-contrast can be explained by downwelling light being brighter than upwelling, and leaves transmitting

Suggested Citation

  • Cynthia Tedore & Dan-Eric Nilsson, 2019. "Avian UV vision enhances leaf surface contrasts in forest environments," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-018-08142-5
    DOI: 10.1038/s41467-018-08142-5
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-018-08142-5
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-018-08142-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pengshan Xie & Yunchao Xu & Jingwen Wang & Dengji Li & Yuxuan Zhang & Zixin Zeng & Boxiang Gao & Quan Quan & Bowen Li & You Meng & Weijun Wang & Yezhan Li & Yan Yan & Yi Shen & Jia Sun & Johnny C. Ho, 2024. "Birdlike broadband neuromorphic visual sensor arrays for fusion imaging," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    2. Marie-Christin Hardenbicker & Cynthia Tedore, 2023. "Peacock spiders prefer image statistics of average natural scenes over those of male ornamentation," Behavioral Ecology, International Society for Behavioral Ecology, vol. 34(5), pages 719-728.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-018-08142-5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.