Light-level geolocator analyses: A user's guide.

Light-level geolocator tags use ambient light recordings to estimate the whereabouts of an individual over the time it carried the device. Over the past decade, these tags have emerged as an important tool and have been used extensively for tracking animal migrations, most commonly small birds. Analysing geolocator data can be daunting to new and experienced scientists alike. Over the past decades, several methods with fundamental differences in the analytical approach have been developed to cope with the various caveats and the often complicated data. Here, we explain the concepts behind the analyses of geolocator data and provide a practical guide for the common steps encompassing most analyses - annotation of twilights, calibration, estimating and refining locations, and extraction of movement patterns - describing good practices and common pitfalls for each step. We discuss criteria for deciding whether or not geolocators can answer proposed research questions, provide guidance in choosing an appropriate analysis method and introduce key features of the newest open-source analysis tools. We provide advice for how to interpret and report results, highlighting parameters that should be reported in publications and included in data archiving. Finally, we introduce a comprehensive supplementary online manual that applies the concepts to several datasets, demonstrates the use of open-source analysis tools with step-by-step instructions and code and details our recommendations for interpreting, reporting and archiving.

[1]  Felix Liechti,et al.  What makes Alpine swift ascend at twilight? Novel geolocators reveal year-round flight behaviour , 2018, Behavioral Ecology and Sociobiology.

[2]  Simeon Lisovski,et al.  Geolocation by light: accuracy and precision affected by environmental factors , 2012 .

[3]  Melissa S. Bowlin,et al.  Technology on the Move: Recent and Forthcoming Innovations for Tracking Migratory Birds , 2011 .

[4]  Simeon Lisovski,et al.  Tracking the Stejneger's stonechat Saxicola stejnegeri along the East Asian–Australian Flyway from Japan via China to southeast Asia , 2017 .

[5]  Anders Nielsen,et al.  State–space model for light-based tracking of marine animals , 2007 .

[6]  Martin Wikelski,et al.  Tracking migratory songbirds: accuracy of light‐level loggers (geolocators) in forest habitats , 2012 .

[7]  S. Lisovski Light-level geolocation in polar regions with 24-hour daylight , 2018, Wader Study.

[8]  Willem Bouten,et al.  Comparing inferences of solar geolocation data against high-precision GPS data: annual movements of a double-tagged black-tailed godwit , 2016 .

[9]  Bengt Hansson,et al.  Barometer logging reveals new dimensions of individual songbird migration , 2018, Journal of Avian Biology.

[10]  Simeon Lisovski,et al.  Migratory routes and wintering locations of declining inland North American Common Terns , 2018, The Auk.

[11]  Simeon Lisovski,et al.  GeoLight – processing and analysing light‐based geolocator data in R , 2012 .

[12]  Thomas Alerstam,et al.  Actogram analysis of free-flying migratory birds: new perspectives based on acceleration logging , 2017, Journal of Comparative Physiology A.

[13]  Anders Nielsen,et al.  Improving light-based geolocation by including sea surface temperature , 2006 .

[14]  Silke Bauer,et al.  A full annual perspective on sex-biased migration timing in long-distance migratory birds , 2019, Proceedings of the Royal Society B.

[15]  Susan M. Haig,et al.  Seasonal Movements, Winter Range use, and Migratory Connectivity of the Black Oystercatcher , 2010 .

[16]  Benjamin Merkel,et al.  A probabilistic algorithm to process geolocation data , 2016, Movement ecology.

[17]  Robert G. Clark,et al.  Constructing and evaluating a continent-wide migratory songbird network across the annual cycle , 2018 .

[18]  Simeon Lisovski,et al.  Tracking the full annual-cycle of the Great Knot, Calidris tenuirostris, a long-distance migratory shorebird of the East Asian-Australasian Flyway , 2016 .

[19]  Makiko Takenaka,et al.  Weak effects of geolocators on small birds: A meta-analysis controlled for phylogeny and publication bias. , 2019, The Journal of animal ecology.

[20]  Eldar Rakhimberdiev,et al.  A hidden Markov model for reconstructing animal paths from solar geolocation loggers using templates for light intensity , 2015, Movement Ecology.

[21]  A. Bond,et al.  Preliminary survival and movement data for a declining population of Flesh-footed Shearwater Ardenna carneipes in Western Australia provides insights into marine threats , 2018, Bird Conservation International.

[22]  Aevar Petersen,et al.  Tracking of Arctic terns Sterna paradisaea reveals longest animal migration , 2010, Proceedings of the National Academy of Sciences.

[23]  Vsevolod Afanasyev,et al.  Accuracy of geolocation estimates for flying seabirds , 2004 .

[24]  M. A. O. Ignacio,et al.  How to cite this article , 2016 .

[25]  Scott A. Shaffer,et al.  Comparison of light- and SST-based geolocation with satellite telemetry in free-ranging albatrosses , 2005 .

[26]  Vsevolod Afanasyev,et al.  Tracking Long-Distance Songbird Migration by Using Geolocators , 2009, Science.

[27]  Martins Briedis,et al.  Breeding latitude leads to different temporal but not spatial organization of the annual cycle in a long‐distance migrant , 2016 .

[28]  Michael D. Sumner,et al.  Bayesian Estimation of Animal Movement from Archival and Satellite Tags , 2009, PloS one.

[29]  M. T. Murphy,et al.  Follow the rain? Environmental drivers of Tyrannus migration across the New World , 2018, The Auk.

[30]  Anders Nielsen,et al.  Incorporating sea-surface temperature to the light-based geolocation model TrackIt , 2010 .

[31]  Tom Finch,et al.  Low migratory connectivity is common in long‐distance migrant birds , 2017, The Journal of animal ecology.

[32]  Julia Karagicheva,et al.  FLightR: an r package for reconstructing animal paths from solar geolocation loggers , 2017 .

[33]  O. Love,et al.  Ten years tracking the migrations of small landbirds: Lessons learned in the golden age of bio-logging , 2018, The Auk.

[34]  Simeon Lisovski,et al.  Flexible reaction norms to environmental variables along the migration route and the significance of stopover duration for total speed of migration in a songbird migrant , 2017, Frontiers in Zoology.

[35]  Simeon Lisovski,et al.  Spatiotemporal Group Dynamics in a Long-Distance Migratory Bird , 2018, Current Biology.

[36]  Simeon Lisovski,et al.  First tracks of individual Blackcaps suggest a complex migration pattern , 2017, Journal of Ornithology.

[37]  Simeon Lisovski,et al.  An unknown migration route of the ‘globally threatened’ Aquatic Warbler revealed by geolocators , 2012, Journal of Ornithology.