Integrating wetland bird point count data from humans and acoustic recorders

Wetland loss is cause for concern for populations of many wetland bird species throughout North America. The North American Breeding Bird Survey, the primary resource for broad-scale avian population data, does not provide sufficient data for many marsh bird species. Targeted marsh bird monitoring p...

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Autores principales:	Laura N. Stewart, Douglas C. Tozer, Janine M. McManus, Lucas E. Berrigan, Kiel L. Drake
Formato:	article
Lenguaje:	EN
Publicado:	Resilience Alliance 2020
Materias:	aru autonomous recording unit avian monitoring bioacoustics detection probability detection radius marsh bird point count survey bias Plant culture SB1-1110 Environmental sciences GE1-350 Plant ecology QK900-989
Acceso en línea:	https://doaj.org/article/ffe349af58d3413c9c2b7096fcac12b2
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id	oai:doaj.org-article:ffe349af58d3413c9c2b7096fcac12b2
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spelling	oai:doaj.org-article:ffe349af58d3413c9c2b7096fcac12b22021-12-02T14:14:42ZIntegrating wetland bird point count data from humans and acoustic recorders1712-6568https://doaj.org/article/ffe349af58d3413c9c2b7096fcac12b22020-12-01T00:00:00Zhttps://www.ace-eco.org/vol15/iss2/art9/https://doaj.org/toc/1712-6568Wetland loss is cause for concern for populations of many wetland bird species throughout North America. The North American Breeding Bird Survey, the primary resource for broad-scale avian population data, does not provide sufficient data for many marsh bird species. Targeted marsh bird monitoring programs have been implemented across the continent in an attempt to fill this gap. Despite these efforts, a number of wetland species are so elusive that they remain an analytical challenge because of small sample sizes and low detectability. Thus, there is need for tools and approaches that will increase sampling efficiency and boost geographic representation. Autonomous recording units (ARUs) have the potential to address some of these challenges, but require the ability to combine in-person survey data with ARU data for collective analysis. Our primary objective was to estimate statistical offsets, or correction factors, to account for systematic differences between in-person and ARU counts of wetland-associated bird species. We found that ARU recordings were generally equivalent to in-person point counts, with bias in a small number of species (2 of 19 for Song MeterTM SM2 and 1 of 16 for Song MeterTM SM4 Acoustic Recorders; Wildlife Acoustics Inc. ©, Maynard, MA). However, bias was removed in all of the species through use of our correction factors. Therefore, our correction factors were effective for integrating in-person and ARU point count data even for species where differences exist. We also found that commercially available SM4 recorders have larger effective detection radii than SM2 recorders. Researchers should consider the microphone sensitivity and signal-to-noise ratios of any recording unit before purchasing, and more sensitive models with lower noise should be used where possible. Our results, and particularly our correction factors, are useful for biologists combining in-person and ARU point count data to achieve larger sample sizes, higher statistical power, and ultimately better information for more effective wetland conservation.Laura N. StewartDouglas C. TozerJanine M. McManusLucas E. BerriganKiel L. DrakeResilience Alliancearticlearuautonomous recording unitavian monitoringbioacousticsdetection probabilitydetection radiusmarsh birdpoint countsurvey biasPlant cultureSB1-1110Environmental sciencesGE1-350Plant ecologyQK900-989ENAvian Conservation and Ecology, Vol 15, Iss 2, p 9 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	aru autonomous recording unit avian monitoring bioacoustics detection probability detection radius marsh bird point count survey bias Plant culture SB1-1110 Environmental sciences GE1-350 Plant ecology QK900-989
spellingShingle	aru autonomous recording unit avian monitoring bioacoustics detection probability detection radius marsh bird point count survey bias Plant culture SB1-1110 Environmental sciences GE1-350 Plant ecology QK900-989 Laura N. Stewart Douglas C. Tozer Janine M. McManus Lucas E. Berrigan Kiel L. Drake Integrating wetland bird point count data from humans and acoustic recorders
description	Wetland loss is cause for concern for populations of many wetland bird species throughout North America. The North American Breeding Bird Survey, the primary resource for broad-scale avian population data, does not provide sufficient data for many marsh bird species. Targeted marsh bird monitoring programs have been implemented across the continent in an attempt to fill this gap. Despite these efforts, a number of wetland species are so elusive that they remain an analytical challenge because of small sample sizes and low detectability. Thus, there is need for tools and approaches that will increase sampling efficiency and boost geographic representation. Autonomous recording units (ARUs) have the potential to address some of these challenges, but require the ability to combine in-person survey data with ARU data for collective analysis. Our primary objective was to estimate statistical offsets, or correction factors, to account for systematic differences between in-person and ARU counts of wetland-associated bird species. We found that ARU recordings were generally equivalent to in-person point counts, with bias in a small number of species (2 of 19 for Song MeterTM SM2 and 1 of 16 for Song MeterTM SM4 Acoustic Recorders; Wildlife Acoustics Inc. ©, Maynard, MA). However, bias was removed in all of the species through use of our correction factors. Therefore, our correction factors were effective for integrating in-person and ARU point count data even for species where differences exist. We also found that commercially available SM4 recorders have larger effective detection radii than SM2 recorders. Researchers should consider the microphone sensitivity and signal-to-noise ratios of any recording unit before purchasing, and more sensitive models with lower noise should be used where possible. Our results, and particularly our correction factors, are useful for biologists combining in-person and ARU point count data to achieve larger sample sizes, higher statistical power, and ultimately better information for more effective wetland conservation.
format	article
author	Laura N. Stewart Douglas C. Tozer Janine M. McManus Lucas E. Berrigan Kiel L. Drake
author_facet	Laura N. Stewart Douglas C. Tozer Janine M. McManus Lucas E. Berrigan Kiel L. Drake
author_sort	Laura N. Stewart
title	Integrating wetland bird point count data from humans and acoustic recorders
title_short	Integrating wetland bird point count data from humans and acoustic recorders
title_full	Integrating wetland bird point count data from humans and acoustic recorders
title_fullStr	Integrating wetland bird point count data from humans and acoustic recorders
title_full_unstemmed	Integrating wetland bird point count data from humans and acoustic recorders
title_sort	integrating wetland bird point count data from humans and acoustic recorders
publisher	Resilience Alliance
publishDate	2020
url	https://doaj.org/article/ffe349af58d3413c9c2b7096fcac12b2
work_keys_str_mv	AT lauranstewart integratingwetlandbirdpointcountdatafromhumansandacousticrecorders AT douglasctozer integratingwetlandbirdpointcountdatafromhumansandacousticrecorders AT janinemmcmanus integratingwetlandbirdpointcountdatafromhumansandacousticrecorders AT lucaseberrigan integratingwetlandbirdpointcountdatafromhumansandacousticrecorders AT kielldrake integratingwetlandbirdpointcountdatafromhumansandacousticrecorders
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Integrating wetland bird point count data from humans and acoustic recorders

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