Evidence map›Paper›PMID 36274987›Full record

ArticleFrontiers in cellular neuroscience2022

Night skies through animals' eyes-Quantifying night-time visual scenes and light pollution as viewed by animals.

Anna Lisa Stöckl, James Jonathan Foster

Abstract read
In one paragraph

Article in Frontiers in cellular neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Review
  2. The diversity of lepidopteran spatial orientation strategies - neuronal mechanisms and emerging challenges in a changing world.Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology · 2026
    Review
  3. Vibrissal sensing in mammals in a changing world.The Journal of experimental biology · 2026
    Review
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Anna Lisa StöcklDepartment of Biology, University of Konstanz, Konstanz, Germany.
James Jonathan FosterDepartment of Biology, University of Konstanz, Konstanz, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A large proportion of animal species enjoy the benefits of being active at night, and have evolved the corresponding optical and neural adaptations to cope with the challenges of low light intensities. However, over the past century electric lighting has introduced direct and indirect light pollution into the full range of terrestrial habitats, changing nocturnal animals' visual worlds dramatically. To understand how these changes affect nocturnal behavior, we here propose an animal-centered analysis method based on environmental imaging. This approach incorporates the sensitivity and acuity limits of individual species, arriving at predictions of photon catch relative to noise thresholds, contrast distributions, and the orientation cues nocturnal species can extract from visual scenes. This analysis relies on just a limited number of visual system parameters known for each species. By accounting for light-adaptation in our analysis, we are able to make more realistic predictions of the information animals can extract from nocturnal visual scenes under different levels of light pollution. With this analysis method, we aim to provide context for the interpretation of behavioral findings, and to allow researchers to generate specific hypotheses for the behavior of nocturnal animals in observed light-polluted scenes.

Indexed as

ALANall-sky imagingdim light visionfruitflyhawkmothlight pollutionmousenatural visual scenes

Identifiers

PMID36274987
PMCPMC9582234

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.