TY - JOUR
T1 - Entomological photonic sensors
T2 - Estimating insect population density, its uncertainty and temporal resolution from transit data
AU - Genoud, Adrien P.
AU - Torsiello, Joseph
AU - Belson, Michael
AU - Thomas, Benjamin P.
N1 - Funding Information:
Research reported in this publication was supported by the National Institutes of Health under award number R03AI138133 . The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Publisher Copyright:
© 2020
PY - 2021/3
Y1 - 2021/3
N2 - 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.
AB - 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.
KW - Entomological sensor
KW - Entomology
KW - Insect
KW - Lidar
KW - Mosquito
KW - Photonic sensor
KW - Population density
KW - Population dynamics
UR - http://www.scopus.com/inward/record.url?scp=85095848693&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85095848693&partnerID=8YFLogxK
U2 - 10.1016/j.ecoinf.2020.101186
DO - 10.1016/j.ecoinf.2020.101186
M3 - Article
AN - SCOPUS:85095848693
SN - 1574-9541
VL - 61
JO - Ecological Informatics
JF - Ecological Informatics
M1 - 101186
ER -