Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Robust estimates of wildlife location using telemetry data

R Anderson-Sprecher1

  • 1Department of Statistics, University of Wyoming, Laramie 82071-3332.

Biometrics
|June 1, 1994
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Animal physiology. Summer declines in activity and body temperature offer polar bears limited energy savings.

Science (New York, N.Y.)·2015
Same author

Evidence of point-source exposure to Neospora caninum and protective immunity in a herd of beef cows.

Journal of the American Veterinary Medical Association·2000
Same author

Antibody responses of cows during an outbreak of neosporosis evaluated by indirect fluorescent antibody test and different enzyme-linked immunosorbent assays.

The Journal of parasitology·1997
Same author

Environmental sampling: a brief review.

Journal of exposure analysis and environmental epidemiology·1994
Same journal

Acknowledgment of Referees 2025.

Biometrics·2026
Same journal

Fast penalized generalized estimating equations for large longitudinal functional datasets.

Biometrics·2026
Same journal

Causally-interpretable random-effects meta-analysis.

Biometrics·2026
Same journal

Statistical inference for mean function of partially observed functional time series.

Biometrics·2026
Same journal

Subgroup identification via Interaction Tree and Mixed Model for Repeated Measures with application to Alzheimer's disease.

Biometrics·2026
Same journal

Finite mixtures of linear quantile regressions with concomitant variables: a solution to endogeneity in longitudinal data modeling.

Biometrics·2026
See all related articles

Wildlife tracking using telemetry data can be unreliable in mountains due to signal reflections. A robust state-space model improves location estimates when data are significantly contaminated, outperforming current methods.

Area of Science:

  • Wildlife ecology
  • Statistical modeling
  • Animal tracking

Background:

  • Telemetry data is crucial for wildlife location estimation.
  • Signal reflection in mountainous terrain causes significant observation errors.
  • Current location estimation techniques are unreliable under such conditions.

Purpose of the Study:

  • To investigate the impact of gross observation errors on wildlife location estimation.
  • To propose a robust state-space time-series modeling approach as an alternative analysis.
  • To compare the performance of robust and current methods using simulated and real data.

Main Methods:

  • Utilized robust state-space time-series modeling.
  • Applied current location estimation techniques for comparison.

Related Experiment Videos

  • Analyzed both simulated and real mule deer telemetry data.
  • Evaluated location estimates and their precisions.

    • Main Results:

    • The robust filter-smoother performs comparably to Gaussian methods with minimal data contamination.
    • The robust approach significantly enhances location estimates in the presence of large data contamination.
    • Performance was validated using both simulated and real-world mule deer tracking data.

    Conclusions:

    • Robust state-space modeling offers a reliable alternative for wildlife tracking in challenging environments.
    • The proposed method improves accuracy where traditional techniques fail due to signal interference.
    • Effective implementation requires careful specification of filter parameters.