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Integration of mark-recapture and acoustic detections for unbiased population estimation in animal communities.
- Source :
-
Ecology [Ecology] 2022 Oct; Vol. 103 (10), pp. e3769. Date of Electronic Publication: 2022 Jul 15. - Publication Year :
- 2022
-
Abstract
- Abundance estimation methods that combine several types of data are becoming increasingly common because they yield more accurate and precise parameter estimates and predictions than are possible from a single data source. These beneficial effects result from increasing sample size (through data pooling) and complementarity between different data types. Here, we test whether integrating mark-recapture data with passive acoustic detections into a joint likelihood improves estimates of population size in a multi-guild community. We compared the integrated model to a mark-recapture-only model using simulated data first and then using a data set of mist-net captures and acoustic recordings from an Afrotropical agroforest bird community. The integrated model with simulated data improved accuracy and precision of estimated population size and detection parameters. When applied to field data, the integrated model was able to produce, for each bird guild, ecologically plausible estimates of population size and detection parameters, with more precision compared with the mark-recapture model. Overall, our results show that adding acoustic data to mark-recapture analyses improves estimates of population size. With the increasing availability of acoustic recording devices, this data collection technique could readily be added to routine field protocols, leading to a cost-efficient improvement of traditional mark-recapture population estimation.<br /> (© 2022 The Authors. Ecology published by Wiley Periodicals LLC on behalf of The Ecological Society of America.)
- Subjects :
- Animals
Population Density
Probability
Sample Size
Acoustics
Subjects
Details
- Language :
- English
- ISSN :
- 1939-9170
- Volume :
- 103
- Issue :
- 10
- Database :
- MEDLINE
- Journal :
- Ecology
- Publication Type :
- Academic Journal
- Accession number :
- 35620844
- Full Text :
- https://doi.org/10.1002/ecy.3769