Accommodating false positives within acoustic spatial capture-recapture, with variable source levels, noisy bearings and an inhomogeneous spatial density Article Swipe
Felix T. Petersma
,
Len Thomas
,
Aaron M. Thode
,
Danielle Harris
,
Tiago A. Marques
,
Gisela V Cheoo
,
Katherine H. Kim
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2207.09343
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2207.09343
Passive acoustic monitoring is a promising method for surveying wildlife populations that are easier to detect acoustically than visually. When animal vocalisations can be uniquely identified on an array of sensors, the potential exists to estimate population density through acoustic spatial capture-recapture (ASCR). However, sound classification is imperfect, and in some situations a high proportion of sounds detected on just a single sensor ('singletons') are not from the target species. We present a case study of bowhead whale calls (Baleana mysticetus) collected in the Beaufort Sea in 2010 containing such false positives. We propose a novel extension of ASCR that is robust to false positives by truncating singletons and conditioning on calls being detected by at least two sensors. We allow for individual-level detection heterogeneity through modelling a variable sound source level, model inhomogeneous call spatial density, and include bearings with varying measurement error. We show via simulation that the method produces near-unbiased estimates when correctly specified. Ignoring source level variation resulted in a strong negative bias, while ignoring inhomogeneous density resulted in severe positive bias. The case study analysis indicated a band of higher call density approximately 30km from shore; 59.8% of singletons were estimated to have been false positives.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2207.09343
- https://arxiv.org/pdf/2207.09343
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4286224426
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4286224426Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2207.09343Digital Object Identifier
- Title
-
Accommodating false positives within acoustic spatial capture-recapture, with variable source levels, noisy bearings and an inhomogeneous spatial densityWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-07-19Full publication date if available
- Authors
-
Felix T. Petersma, Len Thomas, Aaron M. Thode, Danielle Harris, Tiago A. Marques, Gisela V Cheoo, Katherine H. KimList of authors in order
- Landing page
-
https://arxiv.org/abs/2207.09343Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2207.09343Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2207.09343Direct OA link when available
- Concepts
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False positive paradox, Bioacoustics, Computer science, Mark and recapture, Variable (mathematics), Acoustics, Statistics, Population, Pattern recognition (psychology), Artificial intelligence, Mathematics, Physics, Sociology, Demography, Mathematical analysisTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2023: 1Per-year citation counts (last 5 years)
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.(Baleana | 79 |
| abstract_inverted_index.Beaufort | 84 |
| abstract_inverted_index.However, | 43 |
| abstract_inverted_index.Ignoring | 157 |
| abstract_inverted_index.acoustic | 1, 39 |
| abstract_inverted_index.analysis | 179 |
| abstract_inverted_index.bearings | 139 |
| abstract_inverted_index.density, | 136 |
| abstract_inverted_index.detected | 57, 113 |
| abstract_inverted_index.estimate | 35 |
| abstract_inverted_index.ignoring | 168 |
| abstract_inverted_index.negative | 165 |
| abstract_inverted_index.positive | 174 |
| abstract_inverted_index.produces | 151 |
| abstract_inverted_index.resulted | 161, 171 |
| abstract_inverted_index.sensors, | 30 |
| abstract_inverted_index.sensors. | 118 |
| abstract_inverted_index.species. | 69 |
| abstract_inverted_index.uniquely | 24 |
| abstract_inverted_index.variable | 128 |
| abstract_inverted_index.wildlife | 9 |
| abstract_inverted_index.collected | 81 |
| abstract_inverted_index.correctly | 155 |
| abstract_inverted_index.detection | 123 |
| abstract_inverted_index.estimated | 195 |
| abstract_inverted_index.estimates | 153 |
| abstract_inverted_index.extension | 96 |
| abstract_inverted_index.indicated | 180 |
| abstract_inverted_index.modelling | 126 |
| abstract_inverted_index.positives | 104 |
| abstract_inverted_index.potential | 32 |
| abstract_inverted_index.promising | 5 |
| abstract_inverted_index.surveying | 8 |
| abstract_inverted_index.variation | 160 |
| abstract_inverted_index.visually. | 18 |
| abstract_inverted_index.containing | 88 |
| abstract_inverted_index.identified | 25 |
| abstract_inverted_index.imperfect, | 47 |
| abstract_inverted_index.monitoring | 2 |
| abstract_inverted_index.population | 36 |
| abstract_inverted_index.positives. | 91, 200 |
| abstract_inverted_index.proportion | 54 |
| abstract_inverted_index.simulation | 147 |
| abstract_inverted_index.singletons | 107, 193 |
| abstract_inverted_index.situations | 51 |
| abstract_inverted_index.specified. | 156 |
| abstract_inverted_index.truncating | 106 |
| abstract_inverted_index.measurement | 142 |
| abstract_inverted_index.mysticetus) | 80 |
| abstract_inverted_index.populations | 10 |
| abstract_inverted_index.acoustically | 16 |
| abstract_inverted_index.conditioning | 109 |
| abstract_inverted_index.approximately | 187 |
| abstract_inverted_index.heterogeneity | 124 |
| abstract_inverted_index.inhomogeneous | 133, 169 |
| abstract_inverted_index.near-unbiased | 152 |
| abstract_inverted_index.vocalisations | 21 |
| abstract_inverted_index.('singletons') | 63 |
| abstract_inverted_index.classification | 45 |
| abstract_inverted_index.individual-level | 122 |
| abstract_inverted_index.capture-recapture | 41 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 7 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/14 |
| sustainable_development_goals[0].score | 0.8899999856948853 |
| sustainable_development_goals[0].display_name | Life below water |
| citation_normalized_percentile |