Geolocation by light: accuracy and precision affected by environmental factors

Abstract

Summary1. Geolocation by light allows for tracking animal movements, based on measurements of light intensity over time by a data-logging device ('geolocator'). Recent developments of ultra-light devices (<2 g) broadened the range of target species and boosted the number of studies using geolocators. However, an inherent problem of geolocators is that any factor or process that changes the natural light intensity pattern also affects the positions calculated from these light patterns. Although the most important factors have been identified, estimation of their effect on the accuracy and precision of positions estimated has been lacking but is very important for the analyses and interpretation of geolocator data. 2. The 'threshold method' is mainly used to derive positions by defining sunrise and sunset times from the light intensity pattern for each recorded day. This method requires calibration: a predefined sun elevation angle for estimating latitude by fitting the recorded day ⁄ night lengths to theoretical values across latitudes. Therewith, almost constant shading can be corrected for by finding the appropriate sun elevation angle. 3. Weather, topography and vegetation are the most important factors that influence light intensities. We demonstrated their effect on the measurement of day ⁄ night length, time of solar midnight ⁄ noon and the resulting position estimates using light measurements from stationary geolocators at known places and from geolocators mounted on birds. Furthermore, we investigated the influence of different calibration methods on the accuracy of the latitudinal positions. 4. All three environmental factors can influence the light intensity pattern significantly. Weather and an animal's behaviour result in increased noise in positioning, whereas topography and vegetation result in systematic shading and biased positions. Calibration can significantly shift the estimated latitudes and potentially increase the accuracy, but detailed knowledge about the particular confounding factors and the behaviour of the studied animal is crucial for the choice of the most appropriate calibration method.

A multi-isotope (δ13C, δ15N, δ2H) approach to connecting European breeding and African wintering populations of barn swallow (Hirundo rustica)

“…development of miniaturized light-sensitive geolocators suitable for deployment on relatively small passerines (> 18g) promises to provide provenance data accurate to within a few hundered kilometers [12,13], although significant fitness costs to birds from use of geolocators will require inclusion of untreated and shamtreated control groups, something that is rarely if ever done currently. These developments will undoubtedly revolutionize the field of migration research, although the lack of untreated controls may render any conclusions dependent on other approaches such as stable isotope and trace element analyses.…”

“…Our objectives were to evaluate isotopic evidence for migratory connectivity between European breeding grounds and African wintering grounds of barn swallows using an established theoretical multi-isotope (δ 13 Africa [21]. Our approach was to sample feathers from swallows from known breeding colonies throughout Europe and to assign individuals to known isotopic clusters in Africa.…”

Unexpected diversity in socially synchronized rhythms of shorebirds

“…For 643 nests, the exact breeding location was known (nests or individuals were monitored at the breeding ground). For the remaining 86 nests (from 27 populations representing 8 species, where individuals were tagged with light loggers on the wintering ground), the breeding location was roughly estimated from the recorded 24-h variation in daylight, estimated migration tracks, and the species' known breeding range [44][45][46][47][48][49][50][51] . One exact breeding location was in the Southern Hemisphere, so we used absolute latitude in analyses.…”

Consistent variation in individual migration strategies of brown skuas

“…Positions during the non-breeding season were estimated from raw light intensity data using the threshold method (Lisovski et al 2012). Twilight events (i.e.…”