Concepedia

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Animal ecology meets GPS-based radiotelemetry: a perfect storm of opportunities and challenges

769

Citations

42

References

2010

Year

TLDR

GPS telemetry provides extensive movement data even for cryptic species, enabling detailed mapping of animal paths and ecosystem interactions, and its integration with animal ecology offers both new research opportunities and technical challenges. The authors aim to demonstrate that spatial movement data can advance mechanistic insights into resource use, home range, dispersal, and population dynamics. Future intensive movement sampling combined with detailed habitat information will allow modeling of animals’ cognitive maps and link behavior to fitness, while long‑term, large‑scale data will support robust inferences on complex issues such as climate change impacts on behavior and distribution.

Abstract

Global positioning system (GPS) telemetry technology allows us to monitor and to map the details of animal movement, securing vast quantities of such data even for highly cryptic organisms. We envision an exciting synergy between animal ecology and GPS-based radiotelemetry, as for other examples of new technologies stimulating rapid conceptual advances, where research opportunities have been paralleled by technical and analytical challenges. Animal positions provide the elemental unit of movement paths and show where individuals interact with the ecosystems around them. We discuss how knowing where animals go can help scientists in their search for a mechanistic understanding of key concepts of animal ecology, including resource use, home range and dispersal, and population dynamics. It is probable that in the not-so-distant future, intense sampling of movements coupled with detailed information on habitat features at a variety of scales will allow us to represent an animal's cognitive map of its environment, and the intimate relationship between behaviour and fitness. An extended use of these data over long periods of time and over large spatial scales can provide robust inferences for complex, multi-factorial phenomena, such as meta-analyses of the effects of climate change on animal behaviour and distribution.

References

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