Integration of mark-recapture and acoustic detections for unbiased population estimation in animal communities

Jarrett, Crinan; Haydon, Daniel T.; Morales, Juan M.; Ferreira, Diogo F.; Alemanji Forzi, Francis; Welch, Andreanna J.; Powell, Luke L.; Matthiopoulos, Jason

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 dataset 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.

Citation

Jarrett, C., Haydon, D. T., Morales, J. M., Ferreira, D. F., Alemanji Forzi, F., Welch, A. J., Powell, L. L., & Matthiopoulos, J. (2022). Integration of mark-recapture and acoustic detections for unbiased population estimation in animal communities. Ecology, 103(10), Article e3769. https://doi.org/10.1002/ecy.3769

• Journal Article Type: Article
• Acceptance Date: Apr 21, 2022
• Online Publication Date: May 27, 2022
• Publication Date: 2022-10
• Deposit Date: May 3, 2022
• Publicly Available Date: Jan 31, 2023
• Journal: Ecology
• Print ISSN: 0012-9658
• Publisher: Ecological Society of America
• Peer Reviewed: Peer Reviewed
• Volume: 103
• Issue: 10
• Article Number: e3769
• DOI: https://doi.org/10.1002/ecy.3769
• Public URL: https://durham-repository.worktribe.com/output/1209487