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Late summer plateau pika spatial habitat use revealed by high-resolution wildlife tracking and unmanned aerial vehicle data on the Qinghai-Tibet Plateau

  • Dan Li
  • , Johannes Knops
  • , Li Li*
  • *Corresponding author for this work
  • University of Nebraska-Lincoln

Research output: Contribution to journalArticlepeer-review

Abstract

Background: The Qinghai–Tibet Plateau has significant grassland degradation. The plateau pika (Ochotona curzoniae), a small burrowing mammal, traditionally viewed as a pest, may strongly shape vegetation, yet its fine-scale spatial ecology remains unclear. Methods: Using custom-made wildlife trackers and high-resolution multispectral unmanned aerial vehicle (UAV) mapping to quantify fine-scaled movements, habitat utilization, and activity patterns of 10 plateau pikas in a summer pasture. Results: Plateau pikas demonstrated scale-nested habitat preferences: preferred fragmented vegetation at a 5-m scale, while favoring larger vegetation patches at a 1-m scale. Mean home range was 1633 m² (range 494–7443 m²), larger and more variable than prior reports. Activity patterns showed a distinct diurnal pattern, with aboveground activity from sunrise to sunset, and only belowground activity at night. Conclusions: Integrating high-resolution tracking with UAV yields novel, fine-scale insights into plateau pika spatial ecology. Pikas in a summer pasture had larger, variable home ranges and were strictly diurnal. They employed a scale-nested strategy, depending on a mosaic of vegetation and bare soil to provide foraging opportunities, safety from predators, and burrowing sites. These findings suggest that preventing the formation of optimal pika habitat through precise grazing management is an effective strategy to limit pika habitat use and abundance.

Original languageEnglish
JournalGrassland Research
DOIs
Publication statusPublished - Mar 2026

Keywords

  • habitat utilization
  • high-resolution multispectral UAV imagery
  • plateau pika
  • Qinghai-Tibet Plateau
  • spatial ecology
  • wildlife tracking

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