Emerging technologies revolutionise insect ecology and monitoring
van Klink, Roel; August, Tom ORCID: https://orcid.org/0000-0003-1116-3385; Bas, Yves; Bodesheim, Paul; Bonn, Aletta; Fossøy, Frode; Høye, Toke T.; Jongejans, Eelke; Menz, Myles H.M.; Miraldo, Andreia; Roslin, Tomas; Roy, Helen E. ORCID: https://orcid.org/0000-0001-6050-679X; Ruczyński, Ireneusz; Schigel, Dmitry; Schäffler, Livia; Sheard, Julie K.; Svenningsen, Cecilie; Tschan, Georg F.; Wäldchen, Jana; Zizka, Vera M.A.; Åström, Jens; Bowler, Diana E. ORCID: https://orcid.org/0000-0002-7775-1668. 2022 Emerging technologies revolutionise insect ecology and monitoring. Trends in Ecology & Evolution, 37 (10). 872-885. 10.1016/j.tree.2022.06.001
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Abstract/Summary
Insects are the most diverse group of animals on Earth, but their small size and high diversity have always made them challenging to study. Recent technological advances have the potential to revolutionise insect ecology and monitoring. We describe the state of the art of four technologies (computer vision, acoustic monitoring, radar, and molecular methods), and assess their advantages, current limitations, and future potential. We discuss how these technologies can adhere to modern standards of data curation and transparency, their implications for citizen science, and their potential for integration among different monitoring programmes and technologies. We argue that they provide unprecedented possibilities for insect ecology and monitoring, but it will be important to foster international standards via collaboration.
Item Type: | Publication - Article |
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Digital Object Identifier (DOI): | 10.1016/j.tree.2022.06.001 |
UKCEH and CEH Sections/Science Areas: | Biodiversity (Science Area 2017-) |
ISSN: | 0169-5347 |
Additional Information. Not used in RCUK Gateway to Research.: | Open Access paper - full text available via Official URL link. |
Additional Keywords: | automated monitoring, computer vision, DNA Barcoding, eDNA, entomology, radar |
NORA Subject Terms: | Ecology and Environment Computer Science Data and Information |
Date made live: | 05 Jul 2023 15:48 +0 (UTC) |
URI: | https://nora.nerc.ac.uk/id/eprint/534693 |
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