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Small population sizes put a species at extreme risk of extinction due to a lack of variation, and a consequent decrease in adaptability. This weakens the chances of survival under pressures such as climate change, competition from other species, or new diseases. Large populations are more likely to survive pressures such as these, as such populations are more likely to harbor individuals that have genetic variants that are adaptive under new stresses. Small populations are much less...
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Related Experiment Video

Updated: Mar 21, 2026

Spotting Cheetahs: Identifying Individuals by Their Footprints
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Spotting Cheetahs: Identifying Individuals by Their Footprints

Published on: May 1, 2016

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Spotting Cheetahs: Identifying Individuals by Their Footprints.

Zoe C Jewell1, Sky K Alibhai2, Florian Weise3

  • 1WildTrack and Nicholas School of the Environment, Duke University.

Journal of Visualized Experiments : Jove
|May 12, 2016
PubMed
Summary
This summary is machine-generated.

A new footprint identification technique accurately identifies individual cheetahs using smartphone images, aiding conservation efforts for this endangered species. This method offers a cost-effective and reliable alternative to traditional tracking methods.

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Area of Science:

  • Conservation Biology
  • Wildlife Monitoring
  • Biometrics

Background:

  • The cheetah (Acinonyx jubatus) is Africa's most endangered large felid, facing threats from livestock conflict and range contraction.
  • Accurate population estimates are crucial for cheetah conservation, but current monitoring techniques like invasive tagging are costly and unreliable.
  • Namibia is believed to host a significant cheetah population, yet estimates vary widely due to differing monitoring methodologies.

Purpose of the Study:

  • To introduce and validate a novel, non-invasive footprint identification technique for cheetahs.
  • To provide a cost-effective and accessible tool for cheetah monitoring that can be utilized by both scientists and citizen observers.
  • To improve the accuracy and reliability of cheetah population assessments.

Main Methods:

  • The footprint identification technique analyzes digital images of cheetah footprints using standardized protocols and data visualization software.
  • Measurements of footprint dimensions are processed through a customized discriminant analysis model, generating a Ward's cluster dendrogram.
  • Species-specific algorithms are developed from training databases of known cheetahs, enabling classification of unknown individuals.

Main Results:

  • The footprint identification technique achieved a prediction accuracy of over 90% for individual cheetah identification.
  • The technique utilizes a user-friendly graphic user interface (GUI) for immediate interpretation of results.
  • The method is species-specific and adaptable to different felid anatomies.

Conclusions:

  • The footprint identification technique presents a highly accurate and accessible method for monitoring cheetah populations.
  • This novel approach can significantly augment data collection efforts, overcoming limitations of traditional methods.
  • The technique holds potential for enhancing conservation strategies for endangered felids globally.