How do they work?
Solar geolocation has been used for centuries by mariners and explorers. The concept is based on the fact that day length varies with latitude while time of solar noon varies with longitude. Measuring these variables, one is able to determine general position on the globe.
Geolocation dataloggers or “geologgers,” take advantage of this solar principle. However, rather than tracking the exact position of the sun, geologgers use a light sensor to generate and store light-level data at regular intervals. During twilight periods, a simple series of light measurements can deduce the sun’s position based on the correspondence between light intensity and the angle of the sun. Usually a low sun angle is designated as a threshold for determining sunrise and sunset, and solar noon is assumed to occur midway between the two. One can then infer a location based on the length of the day (latitude) and the time of solar noon (longitude). The same calculations can be applied to nocturnal measurements as well, using solar midnight for longitude.
At first glance, this method appears to be an elegant solution to the problem of how to track small birds. With a minimal electronic circuit and a small battery, you can generate location data over an entire migration cycle and obtain two data points every day (diurnal and nocturnal points). However, there are many challenges associated with it.
- Tags must be recovered in order to obtain the data
- Error caused by environmental factors (e.g. weather and vegetative cover)
- Lack of tools and standards to analyze data analysis and report error (at least at present)
Nevertheless, geologgers are the only practical means of tracking small migratory birds over large distances, and there is great interest in them among the ornithological community.
There are two fronts in the pursuit geologger tracking: hardware and software. On the hardware front lie the challenges of miniaturization (to allow tracking of smaller species), precision,, durability, and operating life. On the software front there are a variety of approaches to problems, including determining time of sunrise and sunset from continuous light-level data. The simplest software uses a light threshold level to define sunup and sundown and then apply an algorithm that translates day length and solar noon into discrete data points. More sophisticated methods employ template fitting techniques to determine sunup and sundown, and some have incorporated a Bayesian framework that incorporates known data (e.g. expected behavior, landscape features, and previous locations) into location estimates.
Edited by Eli Bridge, University of Oklahoma, email@example.com
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