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Scanning efficacy of p-Chips implanted in the wing and leg of the Big Brown Bat ( Eptesicus fuscus ).

Shane D I SeheultRaj PanchalAlex V BorisenkoPatrick J BennettPaul A Faure
Published in: Journal of mammalogy (2024)
Individual marking techniques are critical for studying animals, especially in the wild. Current marking methods for bats (Order Chiroptera) have practical limitations and some can cause morbidity. We tested the p-Chip (p-Chip Corp.)-a miniaturized, laser light-activated microtransponder-as a prospective marking technique in a captive research colony of Big Brown Bats ( Eptesicus fuscus ). We assessed long-term readability and postimplantation effects of p-Chips injected subcutaneously above the second metacarpal (wing; n = 30) and the tibia (leg; n = 13 in both locations). Following implantation (Day 0), p-Chips were scanned with a hand-held ID reader (wand) on postimplantation days (PIDs) 1, 8, 15, 22, 32, 60, 74, 81, 88, 95, and over 1 year later (PID 464). For each trial, we recorded: (1) animal handling time; (2) scan time; (3) number of wand flashes; (4) p-Chip visibility; and (5) overall condition of the bat. Average scan times for p-Chips implanted in both the wing and leg increased over the duration of the study; however, the number of wand flashes decreased, suggesting that efficacy of p-Chip recording increased with user experience. Importantly, over 464 days both the visibility and readability of p-Chips in the wing remained high and superior to tags in the leg, establishing the second metacarpal as the preferred implantation site. Observed morbidity and mortality in captive bats with p-Chips was similar to baseline values for bats without these tags. Because scan efficiency on PID 464 was comparable with earlier days, this indicates that p-Chips implanted in the wing may be suitable as a long-term marking method. Our provisional results suggest that p-Chips are viable for extended field testing to see if they are suitable as an effective alternative to traditional methods to mark bats.
Keyphrases
  • high throughput
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  • big data
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  • machine learning
  • high resolution
  • dual energy