Evaluating community-wide temporal sampling in passive acoustic monitoring: A comprehensive study of avian vocal patterns in subtropical montane forests [version 2; peer review: 1 approved, 2 approved with reservations]
Background From passive acoustic monitoring (PAM) recordings, the vocal activity rate (VAR), vocalizations per unit of time, can be calculated and is essential for assessing bird population abundance. However, VAR is subject to influences from a range of factors, including species and environmental...
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F1000 Research Ltd
2024-01-01
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Online Access: | https://f1000research.com/articles/12-1299/v2 |
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author | Chia-Hao Chang-Yang Hsueh-Wen Chang Jerome Chie-Jen Ko Ruey-Shing Lin Shih-Hung Wu |
author_facet | Chia-Hao Chang-Yang Hsueh-Wen Chang Jerome Chie-Jen Ko Ruey-Shing Lin Shih-Hung Wu |
author_sort | Chia-Hao Chang-Yang |
collection | DOAJ |
description | Background From passive acoustic monitoring (PAM) recordings, the vocal activity rate (VAR), vocalizations per unit of time, can be calculated and is essential for assessing bird population abundance. However, VAR is subject to influences from a range of factors, including species and environmental conditions. Identifying the optimal sampling design to obtain representative acoustic data for VAR estimation is crucial for research objectives. PAM commonly uses temporal sampling strategies to decrease the volume of recordings and the resources needed for audio data management. Yet, the comprehensive impact of this sampling approach on VAR estimation remains insufficiently explored. Methods In this study, we used vocalizations extracted from recordings of 12 bird species, taken at 14 PAM stations situated in subtropical montane forests over a four-month period, to assess the impact of temporal sampling on VAR across three distinct scales: short-term periodic, diel, and hourly. For short-term periodic sampling analysis, we employed hierarchical clustering analysis (HCA) and the coefficient of variation (CV). Generalized additive models (GAMs) were utilized for diel sampling analysis, and we determined the average difference in VAR values per minute for the hourly sampling analysis. Results We identified significant day and species-specific VAR fluctuations. The survey season was divided into five segments; the earliest two showed high variability and are best avoided for surveys. Data from days with heavy rain and strong winds showed reduced VAR values and should be excluded from analysis. Continuous recordings spanning at least seven days, extending to 14 days is optimal for minimizing sampling variance. Morning chorus recordings effectively capture the majority of bird vocalizations, and hourly sampling with frequent, shorter intervals aligns closely with continuous recording outcomes. Conclusions While our findings are context-specific, they highlight the significance of strategic sampling in avian monitoring, optimizing resource utilization and enhancing the breadth of monitoring efforts. |
first_indexed | 2024-04-24T06:42:15Z |
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issn | 2046-1402 |
language | English |
last_indexed | 2024-04-24T06:42:15Z |
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spelling | doaj.art-717fe757a44346ab8148e3bb8dce5bdd2024-04-23T00:00:02ZengF1000 Research LtdF1000Research2046-14022024-01-0112161617Evaluating community-wide temporal sampling in passive acoustic monitoring: A comprehensive study of avian vocal patterns in subtropical montane forests [version 2; peer review: 1 approved, 2 approved with reservations]Chia-Hao Chang-Yang0Hsueh-Wen Chang1Jerome Chie-Jen Ko2https://orcid.org/0000-0002-8343-604XRuey-Shing Lin3https://orcid.org/0000-0001-7705-9770Shih-Hung Wu4https://orcid.org/0000-0003-3619-0646Taiwan Biodiversity Research Institute, Nantou, 552, TaiwanTaiwan Biodiversity Research Institute, Nantou, 552, TaiwanDepartment of Biological Sciences, National Sun Yat-sen University, Kaohsiung, 804, TaiwanDepartment of Biological Sciences, National Sun Yat-sen University, Kaohsiung, 804, TaiwanTaiwan Biodiversity Research Institute, Nantou, 552, TaiwanBackground From passive acoustic monitoring (PAM) recordings, the vocal activity rate (VAR), vocalizations per unit of time, can be calculated and is essential for assessing bird population abundance. However, VAR is subject to influences from a range of factors, including species and environmental conditions. Identifying the optimal sampling design to obtain representative acoustic data for VAR estimation is crucial for research objectives. PAM commonly uses temporal sampling strategies to decrease the volume of recordings and the resources needed for audio data management. Yet, the comprehensive impact of this sampling approach on VAR estimation remains insufficiently explored. Methods In this study, we used vocalizations extracted from recordings of 12 bird species, taken at 14 PAM stations situated in subtropical montane forests over a four-month period, to assess the impact of temporal sampling on VAR across three distinct scales: short-term periodic, diel, and hourly. For short-term periodic sampling analysis, we employed hierarchical clustering analysis (HCA) and the coefficient of variation (CV). Generalized additive models (GAMs) were utilized for diel sampling analysis, and we determined the average difference in VAR values per minute for the hourly sampling analysis. Results We identified significant day and species-specific VAR fluctuations. The survey season was divided into five segments; the earliest two showed high variability and are best avoided for surveys. Data from days with heavy rain and strong winds showed reduced VAR values and should be excluded from analysis. Continuous recordings spanning at least seven days, extending to 14 days is optimal for minimizing sampling variance. Morning chorus recordings effectively capture the majority of bird vocalizations, and hourly sampling with frequent, shorter intervals aligns closely with continuous recording outcomes. Conclusions While our findings are context-specific, they highlight the significance of strategic sampling in avian monitoring, optimizing resource utilization and enhancing the breadth of monitoring efforts.https://f1000research.com/articles/12-1299/v2passive acoustic monitoring vocal activity rate temporal sampling Aveseng |
spellingShingle | Chia-Hao Chang-Yang Hsueh-Wen Chang Jerome Chie-Jen Ko Ruey-Shing Lin Shih-Hung Wu Evaluating community-wide temporal sampling in passive acoustic monitoring: A comprehensive study of avian vocal patterns in subtropical montane forests [version 2; peer review: 1 approved, 2 approved with reservations] F1000Research passive acoustic monitoring vocal activity rate temporal sampling Aves eng |
title | Evaluating community-wide temporal sampling in passive acoustic monitoring: A comprehensive study of avian vocal patterns in subtropical montane forests [version 2; peer review: 1 approved, 2 approved with reservations] |
title_full | Evaluating community-wide temporal sampling in passive acoustic monitoring: A comprehensive study of avian vocal patterns in subtropical montane forests [version 2; peer review: 1 approved, 2 approved with reservations] |
title_fullStr | Evaluating community-wide temporal sampling in passive acoustic monitoring: A comprehensive study of avian vocal patterns in subtropical montane forests [version 2; peer review: 1 approved, 2 approved with reservations] |
title_full_unstemmed | Evaluating community-wide temporal sampling in passive acoustic monitoring: A comprehensive study of avian vocal patterns in subtropical montane forests [version 2; peer review: 1 approved, 2 approved with reservations] |
title_short | Evaluating community-wide temporal sampling in passive acoustic monitoring: A comprehensive study of avian vocal patterns in subtropical montane forests [version 2; peer review: 1 approved, 2 approved with reservations] |
title_sort | evaluating community wide temporal sampling in passive acoustic monitoring a comprehensive study of avian vocal patterns in subtropical montane forests version 2 peer review 1 approved 2 approved with reservations |
topic | passive acoustic monitoring vocal activity rate temporal sampling Aves eng |
url | https://f1000research.com/articles/12-1299/v2 |
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