Terrestrial animal tracking as an eye on life and planet
By R. Kays, Margaret C. Crofoot, Walter Jetz, Martin Wikelski. Science, 2015
1,474 citations recorded by the source corpus.
Subfields: Ecology, Molecular Biology, Oceanography
View Paper: https://www.semanticscholar.org/paper/42e90cea1ecc76cab741832d4105bf655af5aad7
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Ecology
In Molecular Biology
- Michael G. Harvey
- D. Rabosky
- Sara Beery
- Martin Wikelski
- Grant Van Horn
- Iain D. Couzin
- Damien Farine
- Rob Harcourt
In Oceanography
- Marie Beger
- C. Dudgeon
- Simon Wotherspoon
- D. Rabosky
- Hugh P. Possingham
- G. Hays
- Rob Harcourt
- C. McMahon
Citations in the corpus
- Drones count wildlife more accurately and precisely than humans (2017, methodology): “Emerging technologies, such as camera traps (Rowcliffe & Carbone 2008) and radio telemetry (Hussey et al. 2015; Kays et al. 2015), have increasingly been used to address this challenge (Moll et al. 2007; Hebblewhite & Haydon 2010; Pimm et al. 2015), especially when wildlife populations are rapidly…”
- Estimating utilization distributions from fitted step-selection functions (2017, background): “Technological advances in animal tracking over the last two decades have led to an increase in animal position data by several orders of magnitude (Tomkiewicz et al. 2010, Kays et al. 2015).”
- Perspectives in machine learning for wildlife conservation (2021, background): “• On-animal sensors are the most common remote sensing devices deployed in animal ecology (10).”
- Ten years tracking the migrations of small landbirds: Lessons learned in the golden age of bio-logging (2018, background): “We have now entered a golden age of bio-logging (Wilmers et al. 2015), where tracking technology has become both smaller and more sophisticated, allowing unprecedented studies of movements of individual animals (Kays et al. 2015).”
- Satellite Tracking Sea Turtles: Opportunities and Challenges to Address Key Questions (2018, background): “Here turtle biologists can benefit from the developments made from studies involving other taxa such as fish and birds (Humphries et al., 2010; Hussey et al., 2015; Kays et al., 2015).”
- ctmm: an r package for analyzing animal relocation data as a continuous‐time stochastic process (2016, methodology): “Additionally, as.telemetry can import move objects from the move R package (Kranstauber & Smolla 2015). ctmm users can therefore leverage the move package’s well-developed functionality for interacting with Movebank programmatically.”
- Beyond Reproductive Isolation: Demographic Controls on the Speciation Process (2019, background): “In particular, the tracking of small animals is now possible due to the development of small tags and a more powerful, spacebased, animal-tracking infrastructure (Kays et al. 2015).”
- DeepPoseKit, a software toolkit for fast and robust animal pose estimation using deep learning (2019, methodology): “, 2019), applying these methods to the study of individuals and groups in 424 the wild can provide high-resolution behavioral data that goes beyond the capabilities of current 425 GPS and accelerometry-based technologies (Nagy et al., 2010, 2013; Kays et al., 2015; Strandburg426 Peshkin et al., 2015”
- Integrating research using animal‐borne telemetry with the needs of conservation management (2017, background): “The rapid ascent of animal-borne telemetry research reflects the ability of this approach to improve our understanding of fundamental ecology, enhance monitoring of the planet’s natural resources and inform conservation practices (Hussey et al. 2015; Kays et al. 2015).”
- The role of habitat configuration in shaping social structure: a gap in studies of animal social complexity (2019, background): “Integrating concepts from movement ecology (how and where animals move) with social behaviour (who animals interact with and when) will strengthen our understanding of the generative processes underlying the structure of animal societies we study (Kays et al. 2015; Sih et al. 2018; Spiegel et al. 20”
- A phylogenetically controlled meta‐analysis of biologging device effects on birds: Deleterious effects and a call for more standardized reporting of study data (2017, background): “Increasingly, biologging devices carried by animals are being used as monitoring tools, providing insights into abiotic environmental processes, ecosystem function and human activities (Kays et al., 2015).”