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Sticky Pi, a high-frequency smart trap to study insect circadian activity under natural conditions

View ORCID ProfileQuentin Geissmann, View ORCID ProfilePaul K. Abram, View ORCID ProfileDi Wu, View ORCID ProfileCara H. Haney, View ORCID ProfileJuli Carrillo
doi: https://doi.org/10.1101/2021.08.11.455750
Quentin Geissmann
1Department of Microbiology and Immunology, The University of British Columbia, Vancouver, Canada V6T 1Z3
2Michael Smith Laboratories, The University of British Columbia, Vancouver, Canada V6T 1Z4
3The University of British Columbia, Faculty of Land and Food Systems, Centre for Sustainable Food Systems and Biodiversity Research Centre, Vancouver, British Columbia, Unceded xwmәTkwәýәm Musqueam Territory, Canada, V6T 1Z3
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  • For correspondence: qgeissmann@gmail.com
Paul K. Abram
4Agriculture and Agri-Food Canada, Agassiz Research and Development Centre, 6947 Highway #7, Agassiz, BC, V0M 1A0, Canada
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Di Wu
3The University of British Columbia, Faculty of Land and Food Systems, Centre for Sustainable Food Systems and Biodiversity Research Centre, Vancouver, British Columbia, Unceded xwmәTkwәýәm Musqueam Territory, Canada, V6T 1Z3
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Cara H. Haney
1Department of Microbiology and Immunology, The University of British Columbia, Vancouver, Canada V6T 1Z3
2Michael Smith Laboratories, The University of British Columbia, Vancouver, Canada V6T 1Z4
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Juli Carrillo
3The University of British Columbia, Faculty of Land and Food Systems, Centre for Sustainable Food Systems and Biodiversity Research Centre, Vancouver, British Columbia, Unceded xwmәTkwәýәm Musqueam Territory, Canada, V6T 1Z3
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Abstract

In the face of severe environmental crises that threaten insect biodiversity, new technologies are imperative to monitor both the identity and ecology of insect species. Traditionally, insect surveys rely on manual collection of traps, which provide abundance data but mask the large intra- and inter-day variations in insect activity, an important facet of their ecology. Although laboratory studies have shown that circadian processes are central to insects’ biological functions, from feeding to reproduction, we lack the high-frequency monitoring tools to study insect circadian biology in the field. To address these issues, we developed the Sticky Pi, a novel, autonomous, open-source, insect trap that acquires images of sticky cards every twenty minutes. Using custom deep-learning algorithms, we automatically and accurately scored where, when and which insects were captured. First, we validated our device in controlled laboratory conditions with a classic chronobiological model organism, Drosophila melanogaster. Then, we deployed an array of Sticky Pis to the field to characterise the daily activity of an agricultural pest, Drosophila suzukii, and its parasitoid wasps. Finally, we demonstrate the wide scope of our smart trap by describing the sympatric arrangement of insect temporal niches in a community, without targeting particular taxa a priori. Together, the automatic identification and high sampling rate of our tool provide biologists with unique data that impacts research far beyond chronobiology; with applications to biodiversity monitoring and pest control as well as fundamental implications for phenology, behavioural ecology, and ecophysiology. We released the Sticky Pi project as an open community resource on https://doc.sticky-pi.com.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Major revision. Results revised, Discussion revised, Method clarified. Figures 3-6 updated.

  • https://doc.sticky-pi.com

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted April 29, 2022.
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Sticky Pi, a high-frequency smart trap to study insect circadian activity under natural conditions
Quentin Geissmann, Paul K. Abram, Di Wu, Cara H. Haney, Juli Carrillo
bioRxiv 2021.08.11.455750; doi: https://doi.org/10.1101/2021.08.11.455750
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Sticky Pi, a high-frequency smart trap to study insect circadian activity under natural conditions
Quentin Geissmann, Paul K. Abram, Di Wu, Cara H. Haney, Juli Carrillo
bioRxiv 2021.08.11.455750; doi: https://doi.org/10.1101/2021.08.11.455750

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