Entomological photonic sensors: Estimating insect population density, its uncertainty and temporal resolution from transit data

Adrien P. Genoud, Joseph Torsiello, Michael Belson, Benjamin P. Thomas

Research output: Contribution to journalArticlepeer-review

Abstract

New methodologies based on photonic sensors to survey flying insect populations in their natural habitat have gained traction over the last decade. Instruments such as entomological lidars, radars, or standoff sensors using active or passive light sources can observe large numbers of insects transiting through their field of view. While counting transits can inform on the relative change in insect population, it does not inform on the absolute population size, nor allows data from different instruments to be compared with one another. We propose a methodology to convert transit counts into an absolute insect population density, expressed in number of flying insects per meter cube. The latter benefits from being independent from the instrument and experiment characteristics, making it an ideal metric to compare data originating from different sources. Due to the stochastic nature of the process, the uncertainty of the retrieved population density varies with its temporal resolution, the volume of air probed by the instrument and the population density itself. To study these complex relationships, a numerical model simulating the interactions of insects with a photonic sensor is presented. Finally, we offer an empirical solution to describe the relationship between the population density temporal resolution and its uncertainty.

Original languageEnglish (US)
Article number101186
JournalEcological Informatics
Volume61
DOIs
StatePublished - Mar 2021

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Ecology
  • Modeling and Simulation
  • Ecological Modeling
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Applied Mathematics

Keywords

  • Entomological sensor
  • Entomology
  • Insect
  • Lidar
  • Mosquito
  • Photonic sensor
  • Population density
  • Population dynamics

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