0000000000268856

AUTHOR

Petra Quillfeldt

0000-0002-4450-8688

showing 2 related works from this author

Ecological insights from three decades of animal movement tracking across a changing Arctic

2020

Ecological “big data” Human activities are rapidly altering the natural world. Nowhere is this more evident, perhaps, than in the Arctic, yet this region remains one of the most remote and difficult to study. Researchers have increasingly relied on animal tracking data in these regions to understand individual species' responses, but if we want to understand larger-scale change, we need to integrate our understanding across species. Davidson et al. introduce an open-source data archive that currently hosts more than 15 million location data points across 96 species and use it to show distinct climate change responses across species. Such ecological “big data” can lead to a wider understandi…

0106 biological sciencesEcology (disciplines)Acclimatization[SDV]Life Sciences [q-bio]PopulationPopulationEcological Parameter MonitoringClimate change010603 evolutionary biology01 natural sciences010605 ornithologyOnderz. Form. D.ddc:570Life ScienceAnimals14. Life underwaterNo themeeducationComputingMilieux_MISCELLANEOUSeducation.field_of_studyMultidisciplinaryEcologyPhenologyArchivesArctic RegionsData discoveryEcological Parameter MonitoringPlan_S-Compliant_NO15. Life on landSubarctic climateGeographyArctic13. Climate actioninternational[SDE]Environmental SciencesWIASDierecologieAnimal MigrationAnimal Ecology
researchProduct

A new algorithm for the identification of dives reveals the foraging ecology of a shallow-diving seabird using accelerometer data

2017

International audience; The identification of feeding events is crucial to our understanding of the foraging ecology of seabirds. Technology has made small devices, such as time-depth recorders (TDRs) and accelerometers available. However, TDRs might not be sensitive enough to identify shallow dives, whereas accelerometers might reveal more subtle behaviours at a smaller temporal scale. Due to the limitations of TDRs, the foraging ecology of many shallow-diving seabirds has been poorly investigated to date. We thus developed an algorithm to identify dive events in a shallow-diving seabird species, the Scopoli’s shearwater, using only accelerometer data. The accuracy in the identification of…

0106 biological sciencesEcologybiologyEcology010604 marine biology & hydrobiologyEcology (disciplines)ForagingAquatic Sciencebiology.organism_classification010603 evolutionary biology01 natural sciencesShearwaterCalonectris diomedea foraging divingSettore AGR/11 - Entomologia Generale E Applicatabiology.animal[SDE]Environmental Sciences14. Life underwaterAccelerometer dataSeabirdAlgorithmEcology Evolution Behavior and Systematics
researchProduct