Table · dataset · 2024
Rising atmospheric levels of fine particulate matter reduce the degree of linear polarisation of light
Listed in Edmond
Many insects utilise optical information in linearly polarised light for navigation, with the degree of linear polarisation (DoLP) determining whether the ‘visibility’ of such optical information is available to them.
Description
However, changes in degree of linear polarisation in response to increased atmospheric levels of fine particulate matter (PM2.5) are poorly understood. Here, we specifically use honeybees as a representative case to illustrate how these changes may impact insect navigation.
We present analyses based on both ground-based monitoring and particulate matter modelling, establishing a quantitative relationship between PM2.5 mass concentration and the DoLP. We apply this relationship to a global PM2.5 projection for 2050 and estimate the increase in number and spatial extent of low visibility days for honeybees. We find an increase by up to 20% in the geographical extent of low visibility days in 2050, with an augmented frequency of low visibility days across an area exceeding 0.75 million km2 in India and 2 million km2 in China.
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More frequent and widespread low visibility conditions can reduce the ability of insects to navigate, especially in hotspot regions.
Links
Where it is published
- Dataverse dataset page edmond.mpg.de/dataset.xhtml?persistentId=doi%3A10.17617%2F3.K7ZDG5 ↗
landing page · from edmond mpdl mpg de
- DOI doi.org/10.17617/3.k7zdg5 ↗
DOI / persistent id · from edmond mpdl mpg de
Catalogue records · 1
- Dataverse API edmond.mpg.de/api/datasets/:persistentId/?persistentId=doi%3A10.17617%2F3.K7… ↗
metadata API · from edmond mpdl mpg de
Topics
- Stated by source
- Agriculture, Forestry and Veterinary Medicine · Agriculture, Forestry and Veterinary Medicine · Chemistry · Chemistry · Computer Science, Systems and Electrical Engineering · Computer Science, Systems and Electrical Engineering
- From keywords
- Astronomy & Astrophysics · Chemistry · Chemistry · Computer Science & AI · Computer Science & AI · Earth & Environmental Science · Economics & Finance · Engineering · Engineering · Humanities · Life Sciences · Life Sciences · Materials Science · Medicine & Health · Medicine & Health · Ocean & Atmospheric Science · Physics · Social Science
- Inferred from text
- Atmospheric sciences 69%
Provenance · 2 source records, 31 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Edmond | doi:10.17617/3.K7ZDG5 | 13 d ago | JSON v1 |
| Edmond | doi:10.17617/3.K7ZDG5 | 12 d ago | JSON v1 |
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