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Continuous Audio-Visual Sensor Monitoring Is More Effective Than Human Observers for Detecting Moor Macaques.

Víctor Beltrán Francés1, Anja Hutschenreiter2, Hjalmar S Kühl3,4,5

  • 1Instituto de Neuroetología, Universidad Veracruzana, Veracruz, México.

American Journal of Primatology
|January 21, 2026
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Summary
This summary is machine-generated.

Audio-visual sensors like camera traps and passive acoustic monitoring significantly improve primate detection probability compared to traditional transect surveys. Combining these technologies offers the highest detectability for effective conservation planning.

Keywords:
camera trapsdetectabilitypassive acoustic monitoringpoint transectspopulation surveys

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Area of Science:

  • Wildlife Conservation Biology
  • Primate Ecology
  • Remote Sensing in Ecology

Background:

  • Increasing extinction rates necessitate accurate population estimates for conservation.
  • Species detectability is crucial for reliable population monitoring.
  • Audio-visual sensors (camera traps, passive acoustic monitoring) show promise for primate monitoring, but comparative detectability data is scarce, especially in challenging forest environments.

Purpose of the Study:

  • To systematically compare the detection probability of audio-visual sensors versus human-based transect surveys for monitoring wild moor macaques (Macaca maura).
  • To evaluate sensor performance across different habitat types (forest and open areas).
  • To assess the impact of survey duration on the detectability of different monitoring methods.

Main Methods:

  • Conducted 40-day continuous monitoring using camera traps (N=19) and passive acoustic monitoring (PAM, N=7).
  • Compared sensor data with human-based point transects (N=20) involving three survey visits.
  • Utilized occupancy models to estimate and compare detection probability (p) across methods and habitats.

Main Results:

  • Camera traps (p=0.63±0.04) and PAM (p=0.79±0.08) demonstrated significantly higher detection probabilities than point transects (p=0.33±0.07) across all habitats.
  • After equalizing survey time, camera traps and PAM matched transect performance at two survey days, outperforming them in shorter surveys.
  • Combining both audio-visual sensors achieved the highest overall detectability (p=0.87±0.05).

Conclusions:

  • Audio-visual sensors are highly effective tools for enhancing primate detectability, particularly in dense forests.
  • A multi-method approach combining camera traps and PAM offers superior monitoring capabilities for elusive species.
  • Findings support the development of more efficient and effective monitoring protocols crucial for primate conservation strategies.