Biologically meaningful moonlight measures and their application in ecological research

Author(s)
Smielak, Michał Krysztof
Publication Date
2023-02-10
Abstract
<p>Light availability is one of the key drivers of animal activity, and moonlight is the brightest source of natural light at night. Moon phase is commonly used but, while convenient, it can be a poor proxy for lunar illumination on the ground. While the moon phase remains effectively constant within a night, actual moonlight intensity is affected by multiple factors such as disc brightness, position of the moon, distance to the moon, angle of incidence, and cloud cover. A moonlight illumination model is presented for any given time and location, which is significantly better at predicting lunar illumination than moon phase. The model explains up to 92.2% of the variation in illumination levels with a residual standard error of 1.4%, compared to 60% explained by moon phase with a residual standard error of 22.6%. Importantly, the model not only predicts changes in mean illumination between nights but also within each night, providing greater temporal resolution of illumination estimates. An R package <i>moonlit</i> facilitating moonlight illumination modelling is also presented. Using a case study, it is shown that modelled moonlight intensity can be a better predictor of animal activity than moon phase. More importantly, complex patterns of activity are shown where animals focus their activity around certain illumination levels. This relationship could not be identified using moon phase alone. The model can be universally applied to a wide range of ecological and behavioural research, including existing datasets, allowing a better understanding of lunar illumination as an ecological resource.</p>
Citation
Behavioral Ecology and Sociobiology, v.77, p. 1-13
ISSN
1432-0762
0340-5443
Link
Language
en
Publisher
Springer
Rights
Attribution 4.0 International
Title
Biologically meaningful moonlight measures and their application in ecological research
Type of document
Journal Article
Entity Type
Publication

Files:

NameSizeformatDescriptionLink
openpublished/BiologicallySmielak2024JournalArticle.pdf 2573.305 KB application/pdf Published Version View document