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Related Experiment Video

Updated: Feb 9, 2026

Measuring Light-Switching Behavior Using an Occupancy and Light Data Logger
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Identifying drivers of spatial variation in occupancy with limited replication camera trap data.

Staci A Hepler1,2, Robert Erhardt1,2, T Michael Anderson2,3

  • 1Department of Mathematics and Statistics, Wake Forest University, Winston-Salem, North Carolina, USA.

Ecology
|June 15, 2018
PubMed
Summary

New occupancy models allow reliable species estimation from camera trap data using a single survey per season, provided there are enough seasons. This advances ecological research and wildlife monitoring.

Keywords:
Serengeticamera trapimperfect detectionoccupancy modelspatio-temporal

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Area of Science:

  • Ecology
  • Wildlife Biology
  • Statistical Modeling

Background:

  • Occupancy models are crucial for camera trap studies, analyzing species presence and distribution.
  • These models address imperfect detection using latent variables, but parameter estimation can be challenging.
  • Existing guidelines suggest multiple surveys per season for reliable estimation.

Purpose of the Study:

  • To present a novel spatio-temporal occupancy model.
  • To demonstrate its applicability with limited survey data (one survey per season).
  • To assess the impact of season number on estimation reliability.

Main Methods:

  • Development of a spatio-temporal occupancy model incorporating time and space.
  • Simulation studies to evaluate model performance under varying survey and season numbers.
  • Application of the model to camera-trap data of Thomson's gazelle in Tanzania.

Main Results:

  • The spatio-temporal model can be reliably fit using data from a single survey per season.
  • Sufficiently large numbers of seasons are key for accurate parameter estimation.
  • The model successfully analyzed Thomson's gazelle occupancy in the Serengeti.

Conclusions:

  • Spatio-temporal occupancy models offer a flexible alternative to traditional methods requiring multiple surveys per season.
  • This approach enhances the efficiency of camera trap studies, especially in long-term monitoring.
  • The findings provide valuable insights for designing future wildlife occupancy surveys.