Seasonal migration, driven by shifts in annual climate cycles and resources, is a key part of the life history and ecology of species across taxonomic groups. By influencing the amount of energy needed to move, external forces such as wind and ocean currents are often key drivers of migratory pathways exposing individuals to varying resources, environmental conditions, and competition pressures impacting individual fitness and population dynamics. Although wildlife movements in connection with wind and ocean currents are relatively well understood, movements within sea‐ice fields have been much less studied, despite sea ice being an integral part of polar ecology. Adélie penguins (
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Abstract Pygoscelis adeliae ) in the southern Ross Sea, Antarctica, currently exist at the southernmost edge of their range and undergo the longest (~12,000 km) winter migration known for the species. Within and north of the Ross Sea, the Ross Gyre drives ocean circulation and the large‐scale movement of sea ice. We used remotely sensed sea‐ice movement data together with geolocation‐based penguin movement data to test the hypothesis that penguins use gyre‐driven sea‐ice movement to aid their migration. We found that penguins traveled greater distances when their movement vectors were aligned with those of sea ice (i.e., ice support) and the amount of ice support received depended on which route a penguin took. We also found that birds that took an eastern route traveled significantly further north in two of the 3 years we examined, coinciding with higher velocities of sea ice in those years. We compare our findings to patterns observed in migrating species that utilize air or water currents for their travel and with other studies showing the importance of ocean/sea‐ice circulation patterns to wildlife movement and life history patterns within the Ross Sea. Changes in sea ice may have consequences not only for energy expenditure but, by altering migration and movement pathways, to the ecological interactions that exist in this region. -
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Abstract 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.
