Automated image-based tracking and its application in ecology
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The behavior of individuals determines the strength and outcome of ecological interactions, which drive population, community, and ecosystem organization. Bio-logging, such as telemetry and animal-borne imaging, provides essential individual viewpoints, tracks, and life histories, but requires capture of individuals and is often impractical to scale. Recent developments in automated image-based tracking offers opportunities to remotely quantify and understand individual behavior at scales and resolutions not previously possible, providing an essential supplement to other tracking methodologies in ecology. Automated image-based tracking should continue to advance the field of ecology by enabling better understanding of the linkages between individual and higher-level ecological processes, via high-throughput quantitative analysis of complex ecological patterns and processes across scales, including analysis of environmental drivers.
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Machine learning is used to automate the classification of behaviours or activities and tracking movement trajectories from GPS, accelerometer and/or video data.
“ML is used to automate the classification of behaviours/activities (Kabra et al., 2013) and tracking movement trajectories (Dell et al., 2014).”
From Applications of machine learning in animal behaviour studies (2017) · cites this paper as Dell et al., 2014
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Visual animal biometrics: survey
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Rudolf, J., Dondorp, D. C., Canon, L., Tieo, S., & Chatzigeorgiou, M. (2019) · Scientific Reports · doi:10.1038/s41598-019-38791-5 · Cited by 51 · see citing works
Eisenhauer, N., Bonkowski, M., Brose, U., Buscot, F., Durka, W., Ebeling, A., Fischer, M., Gleixner, G., Heintz‐Buschart, A., Hines, J., et al. (2019) · Research Ideas and Outcomes · doi:10.3897/rio.5.e47042 · Cited by 48 · see citing works
Realizing the potential of trait‐based aquatic ecology: New tools and collaborative approaches
Kremer, C. T., Williams, A. K., Finiguerra, M. B., Fong, A. A., Kellerman, A. M., Paver, S. F., Tolar, B. B., & Toscano, B. J. (2016) · Limnology and Oceanography · doi:10.1002/lno.10392 · Cited by 51 · see citing works
Gómez-Marín, À., Stephens, G. J., & Brown, A. E. (2016) · Journal of The Royal Society Interface · doi:10.1098/rsif.2016.0466 · Cited by 49 · see citing works
Arena size modulates functional responses via behavioral mechanisms
Uiterwaal, S. F., Dell, A. I., & DeLong, J. P. (2018) · Behavioral Ecology · doi:10.1093/beheco/ary188 · Cited by 48 · see citing works
- Authors
- Dell, A. I., Bender, J. A., Branson, K., Couzin, I. D., de Polavieja, G. G., Noldus, L. P. J. J., Pérez-Escudero, A., Perona, P., Straw, A. D., Wikelski, M., & Brose, U.
- Affiliations
- University of Göttingen (DE)
- Howard Hughes Medical Institute (US)
- Princeton University (US)
- Noldus Information Technology (NL)
- California Institute of Technology (US)
- Research Institute of Molecular Pathology (AT)
- Max Planck Society (DE)
- ORCID
- Venue
- Trends in Ecology & Evolution
- Publisher
- Elsevier BV
- Published
- 2014-07
- Volume
- 29
- Issue
- 7
- Pages
- 417-428
- ISSN
- 0169-5347 (ISSN-L)
- OpenAlex
- W2087262824
- Cited by
- 492
- References
- 110
- Citations by year
- 2026: 24 · 2025: 35 · 2024: 36 · 2023: 43 · 2022: 47 · 2021: 59 · 2020: 44 · 2019: 52 · 2018: 39 · 2017: 43 · 2016: 39 · 2015: 23 · 2014: 6
- FWCI
- 3.96
- Type
- journal article
- Language
- en
- Open access
- green
- nbn-resolving.de
- Locations
- Trends in Ecology & Evolution (publishedVersion)
- PubMed (publishedVersion)
- KOPS (University of Konstanz) (submittedVersion)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion)
- HAL (submittedVersion, other-oa)
- GRO (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- National Science Foundation (1021010)
- Division of Environmental Biology
- Topics
- Physical Sciences › Environmental Science › Ecology › Wildlife Ecology and Conservation
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
- Physical Sciences › Environmental Science › Ecology › Animal Ecology and Behavior Studies
- Keywords
- animal behavior, biologging, telemetry, individual behavior, ecological interactions, life history, remote tracking, environmental drivers, high-throughput analysis
- MeSH terms
- Animals, Behavior, Animal, Ecology, Telemetry, Animal Distribution
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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