Estimating population abundance with a mixture of physical capture and PIT tag antenna detection data

• Published in: Canadian journal of fisheries and aquatic sciences Vol. 77; no. 7; pp. 1163 - 1171
• Main Authors: Conner, Mary M, Budy, Phaedra E, Wilkison, Richard A, Mills, Michael, Speas, David, Mackinnon, Peter D, Mckinstry, Mark C
• Format: Journal Article
• Language: English
• Published: 1840 Woodward Drive, Suite 1, Ottawa, ON K2C 0P7 NRC Research Press 01.07.2020; Canadian Science Publishing NRC Research Press
• Subjects: Abundance; Analysis; Antennas; Antennas (Electronics); Bias; Capture-recapture studies; Case studies; Change detection; Coefficient of variation; Computer simulation; Estimation; fish; Fishes; Freshwater; Interrogation; mixing; Modelling; Population characteristics; Population statistics; Questioning; Salvelinus confluentus; Simulation; Sonic tags; Spawning; Spawning migrations; species abundance; Tagging; Tracking; transponders; USA, Utah, Utah Lake
• ISSN: 0706-652X; 1205-7533; 1205-7533
• DOI: 10.1139/cjfas-2019-0326

The inclusion of passive interrogation antenna (PIA) detection data has promise to increase precision of population abundance estimates ( ). However, encounter probabilities are often higher for PIAs than for physical capture. If the difference is not accounted for, may be biased. Using simulations, we estimated the magnitude of bias resulting from mixed capture and detection probabilities and evaluated potential solutions for removing the bias for closed capture models. Mixing physical capture and PIA detections (p det ) resulted in negative biases in . However, using an individual covariate to model differences removed bias and improved precision. From a case study of fish making spawning migrations across a stream-wide PIA (p det ≤ 0.9), the coefficient of variation (CV) of declined 39%–82% when PIA data were included, and there was a dramatic reduction in time to detect a significant change in . For a second case study, with modest p det (≤0.2) using smaller PIAs, CV ( ) declined 4%–18%. Our method is applicable for estimating abundance for any situation where data are collected with methods having different capture–detection probabilities.