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Rasmussen JH, Stowell D, Briefer EF. Sound evidence for biodiversity monitoring. Science 2024; 385:138-140. [PMID: 38991079 DOI: 10.1126/science.adh2716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/13/2024]
Abstract
Bioacoustics and artificial intelligence facilitate ecological studies of animal populations.
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Affiliation(s)
- Jeppe H Rasmussen
- Behavioural Ecology Group, Section for Ecology and Evolution, Department of Biology, University of Copenhagen, Copenhagen, Denmark
- Center for Coastal Research and Center for Artificial Intelligence Research, University of Agder, Kristiansand, Norway
| | - Dan Stowell
- Tilburg University, Tilburg, Netherlands
- Naturalis Biodiversity Center, Leiden, Netherlands
| | - Elodie F Briefer
- Behavioural Ecology Group, Section for Ecology and Evolution, Department of Biology, University of Copenhagen, Copenhagen, Denmark
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2
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Martin K, Cornero FM, Clayton NS, Adam O, Obin N, Dufour V. Vocal complexity in a socially complex corvid: gradation, diversity and lack of common call repertoire in male rooks. ROYAL SOCIETY OPEN SCIENCE 2024; 11:231713. [PMID: 38204786 PMCID: PMC10776222 DOI: 10.1098/rsos.231713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 12/08/2023] [Indexed: 01/12/2024]
Abstract
Vocal communication is widespread in animals, with vocal repertoires of varying complexity. The social complexity hypothesis predicts that species may need high vocal complexity to deal with complex social organization (e.g. have a variety of different interindividual relations). We quantified the vocal complexity of two geographically distant captive colonies of rooks, a corvid species with complex social organization and cognitive performances, but understudied vocal abilities. We quantified the diversity and gradation of their repertoire, as well as the inter-individual similarity at the vocal unit level. We found that males produced call units with lower diversity and gradation than females, while song units did not differ between sexes. Surprisingly, while females produced highly similar call repertoires, even between colonies, each individual male produced almost completely different call repertoires from any other individual. These findings question the way male rooks communicate with their social partners. We suggest that each male may actively seek to remain vocally distinct, which could be an asset in their frequently changing social environment. We conclude that inter-individual similarity, an understudied aspect of vocal repertoires, should also be considered as a measure of vocal complexity.
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Affiliation(s)
- Killian Martin
- PRC, UMR 7247, Ethologie Cognitive et Sociale, CNRS-IFCE-INRAE-Université de Tours, Strasbourg, France
| | | | | | - Olivier Adam
- Institut Jean Le Rond d'Alembert, UMR 7190, CNRS-Sorbonne Université, 75005 Paris, France
- Institut des Neurosciences Paris-Saclay, UMR 9197, CNRS-Université Paris Sud, Orsay, France
| | - Nicolas Obin
- STMS Lab, IRCAM, CNRS-Sorbonne Université, Paris, France
| | - Valérie Dufour
- PRC, UMR 7247, Ethologie Cognitive et Sociale, CNRS-IFCE-INRAE-Université de Tours, Strasbourg, France
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3
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Zhang YJ, Luo Z, Sun Y, Liu J, Chen Z. From beasts to bytes: Revolutionizing zoological research with artificial intelligence. Zool Res 2023; 44:1115-1131. [PMID: 37933101 PMCID: PMC10802096 DOI: 10.24272/j.issn.2095-8137.2023.263] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 10/30/2023] [Indexed: 11/08/2023] Open
Abstract
Since the late 2010s, Artificial Intelligence (AI) including machine learning, boosted through deep learning, has boomed as a vital tool to leverage computer vision, natural language processing and speech recognition in revolutionizing zoological research. This review provides an overview of the primary tasks, core models, datasets, and applications of AI in zoological research, including animal classification, resource conservation, behavior, development, genetics and evolution, breeding and health, disease models, and paleontology. Additionally, we explore the challenges and future directions of integrating AI into this field. Based on numerous case studies, this review outlines various avenues for incorporating AI into zoological research and underscores its potential to enhance our understanding of the intricate relationships that exist within the animal kingdom. As we build a bridge between beast and byte realms, this review serves as a resource for envisioning novel AI applications in zoological research that have not yet been explored.
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Affiliation(s)
- Yu-Juan Zhang
- Chongqing Key Laboratory of Vector Insects
- Chongqing Key Laboratory of Animal Biology
- College of Life Science, Chongqing Normal University, Chongqing 401331, China
| | - Zeyu Luo
- Chongqing Key Laboratory of Vector Insects
- Chongqing Key Laboratory of Animal Biology
- College of Life Science, Chongqing Normal University, Chongqing 401331, China
| | - Yawen Sun
- Chongqing Key Laboratory of Vector Insects
- Chongqing Key Laboratory of Animal Biology
- College of Life Science, Chongqing Normal University, Chongqing 401331, China
| | - Junhao Liu
- Chongqing Key Laboratory of Vector Insects
- Chongqing Key Laboratory of Animal Biology
- College of Life Science, Chongqing Normal University, Chongqing 401331, China
| | - Zongqing Chen
- School of Mathematical Sciences
- National Center for Applied Mathematics in Chongqing, Chongqing Normal University, Chongqing 401331, China. E-mail:
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4
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Fleishman E, Cholewiak D, Gillespie D, Helble T, Klinck H, Nosal EM, Roch MA. Ecological inferences about marine mammals from passive acoustic data. Biol Rev Camb Philos Soc 2023; 98:1633-1647. [PMID: 37142263 DOI: 10.1111/brv.12969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 04/20/2023] [Accepted: 04/24/2023] [Indexed: 05/06/2023]
Abstract
Monitoring on the basis of sound recordings, or passive acoustic monitoring, can complement or serve as an alternative to real-time visual or aural monitoring of marine mammals and other animals by human observers. Passive acoustic data can support the estimation of common, individual-level ecological metrics, such as presence, detection-weighted occupancy, abundance and density, population viability and structure, and behaviour. Passive acoustic data also can support estimation of some community-level metrics, such as species richness and composition. The feasibility of estimation and certainty of estimates is highly context dependent, and understanding the factors that affect the reliability of measurements is useful for those considering whether to use passive acoustic data. Here, we review basic concepts and methods of passive acoustic sampling in marine systems that often are applicable to marine mammal research and conservation. Our ultimate aim is to facilitate collaboration among ecologists, bioacousticians, and data analysts. Ecological applications of passive acoustics require one to make decisions about sampling design, which in turn requires consideration of sound propagation, sampling of signals, and data storage. One also must make decisions about signal detection and classification and evaluation of the performance of algorithms for these tasks. Investment in the research and development of systems that automate detection and classification, including machine learning, are increasing. Passive acoustic monitoring is more reliable for detection of species presence than for estimation of other species-level metrics. Use of passive acoustic monitoring to distinguish among individual animals remains difficult. However, information about detection probability, vocalisation or cue rate, and relations between vocalisations and the number and behaviour of animals increases the feasibility of estimating abundance or density. Most sensor deployments are fixed in space or are sporadic, making temporal turnover in species composition more tractable to estimate than spatial turnover. Collaborations between acousticians and ecologists are most likely to be successful and rewarding when all partners critically examine and share a fundamental understanding of the target variables, sampling process, and analytical methods.
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Affiliation(s)
- Erica Fleishman
- College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR, 97331, USA
| | - Danielle Cholewiak
- Northeast Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Woods Hole, MA, 02543, USA
| | - Douglas Gillespie
- Sea Mammal Research Unit, Scottish Oceans Institute, University of St Andrews, St Andrews, KY16 9XL, UK
| | - Tyler Helble
- Naval Information Warfare Center Pacific, San Diego, CA, 92152, USA
| | - Holger Klinck
- K. Lisa Yang Center for Conservation Bioacoustics, Cornell Lab of Ornithology, Cornell University, Ithaca, NY, 14850, USA
| | - Eva-Marie Nosal
- Department of Ocean and Resources Engineering, University of Hawai'i at Manoa, Honolulu, HI, 96822, USA
| | - Marie A Roch
- Department of Computer Science, San Diego State University, San Diego, CA, 92182, USA
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Jourjine N, Woolfolk ML, Sanguinetti-Scheck JI, Sabatini JE, McFadden S, Lindholm AK, Hoekstra HE. Two pup vocalization types are genetically and functionally separable in deer mice. Curr Biol 2023; 33:1237-1248.e4. [PMID: 36893759 DOI: 10.1016/j.cub.2023.02.045] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Revised: 02/11/2023] [Accepted: 02/14/2023] [Indexed: 03/10/2023]
Abstract
Vocalization is a widespread social behavior in vertebrates that can affect fitness in the wild. Although many vocal behaviors are highly conserved, heritable features of specific vocalization types can vary both within and between species, raising the questions of why and how some vocal behaviors evolve. Here, using new computational tools to automatically detect and cluster vocalizations into distinct acoustic categories, we compare pup isolation calls across neonatal development in eight taxa of deer mice (genus Peromyscus) and compare them with laboratory mice (C57BL6/J strain) and free-living, wild house mice (Mus musculus domesticus). Whereas both Peromyscus and Mus pups produce ultrasonic vocalizations (USVs), Peromyscus pups also produce a second call type with acoustic features, temporal rhythms, and developmental trajectories that are distinct from those of USVs. In deer mice, these lower frequency "cries" are predominantly emitted in postnatal days one through nine, whereas USVs are primarily made after day 9. Using playback assays, we show that cries result in a more rapid approach by Peromyscus mothers than USVs, suggesting a role for cries in eliciting parental care early in neonatal development. Using a genetic cross between two sister species of deer mice exhibiting large, innate differences in the acoustic structure of cries and USVs, we find that variation in vocalization rate, duration, and pitch displays different degrees of genetic dominance and that cry and USV features can be uncoupled in second-generation hybrids. Taken together, this work shows that vocal behavior can evolve quickly between closely related rodent species in which vocalization types, likely serving distinct functions in communication, are controlled by distinct genetic loci.
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Affiliation(s)
- Nicholas Jourjine
- Department of Molecular & Cellular Biology, Department of Organismic & Evolutionary Biology, Center for Brain Science, Museum of Comparative Zoology, Harvard University and the Howard Hughes Medical Institute, 16 Divinity Avenue, Cambridge, MA 02138, USA
| | - Maya L Woolfolk
- Department of Molecular & Cellular Biology, Department of Organismic & Evolutionary Biology, Center for Brain Science, Museum of Comparative Zoology, Harvard University and the Howard Hughes Medical Institute, 16 Divinity Avenue, Cambridge, MA 02138, USA
| | - Juan I Sanguinetti-Scheck
- Department of Molecular & Cellular Biology, Department of Organismic & Evolutionary Biology, Center for Brain Science, Museum of Comparative Zoology, Harvard University and the Howard Hughes Medical Institute, 16 Divinity Avenue, Cambridge, MA 02138, USA
| | - John E Sabatini
- Department of Molecular & Cellular Biology, Department of Organismic & Evolutionary Biology, Center for Brain Science, Museum of Comparative Zoology, Harvard University and the Howard Hughes Medical Institute, 16 Divinity Avenue, Cambridge, MA 02138, USA
| | - Sade McFadden
- Department of Molecular & Cellular Biology, Department of Organismic & Evolutionary Biology, Center for Brain Science, Museum of Comparative Zoology, Harvard University and the Howard Hughes Medical Institute, 16 Divinity Avenue, Cambridge, MA 02138, USA
| | - Anna K Lindholm
- Department of Evolutionary Biology & Environmental Studies, University of Zürich, Winterthurerstrasse, 190 8057 Zürich, Switzerland
| | - Hopi E Hoekstra
- Department of Molecular & Cellular Biology, Department of Organismic & Evolutionary Biology, Center for Brain Science, Museum of Comparative Zoology, Harvard University and the Howard Hughes Medical Institute, 16 Divinity Avenue, Cambridge, MA 02138, USA.
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6
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Xing J, Sainburg T, Taylor H, Gentner TQ. Syntactic modulation of rhythm in Australian pied butcherbird song. ROYAL SOCIETY OPEN SCIENCE 2022; 9:220704. [PMID: 36177196 PMCID: PMC9515642 DOI: 10.1098/rsos.220704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 09/05/2022] [Indexed: 05/04/2023]
Abstract
The acoustic structure of birdsong is spectrally and temporally complex. Temporal complexity is often investigated in a syntactic framework focusing on the statistical features of symbolic song sequences. Alternatively, temporal patterns can be investigated in a rhythmic framework that focuses on the relative timing between song elements. Here, we investigate the merits of combining both frameworks by integrating syntactic and rhythmic analyses of Australian pied butcherbird (Cracticus nigrogularis) songs, which exhibit organized syntax and diverse rhythms. We show that rhythms of the pied butcherbird song bouts in our sample are categorically organized and predictable by the song's first-order sequential syntax. These song rhythms remain categorically distributed and strongly associated with the first-order sequential syntax even after controlling for variance in note length, suggesting that the silent intervals between notes induce a rhythmic structure on note sequences. We discuss the implication of syntactic-rhythmic relations as a relevant feature of song complexity with respect to signals such as human speech and music, and advocate for a broader conception of song complexity that takes into account syntax, rhythm, and their interaction with other acoustic and perceptual features.
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Affiliation(s)
- Jeffrey Xing
- Department of Psychology, University of California San Diego, La Jolla, CA, USA
| | - Tim Sainburg
- Department of Psychology, University of California San Diego, La Jolla, CA, USA
| | - Hollis Taylor
- Sydney Conservatorium of Music, University of Sydney, Sydney, New South Wales, Australia
| | - Timothy Q. Gentner
- Department of Psychology, University of California San Diego, La Jolla, CA, USA
- Neurobiology Section, Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA
- Kavli Institute for Brain and Mind, University of California San Diego, La Jolla, CA, USA
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Xing J, Sainburg T, Taylor H, Gentner TQ. Syntactic modulation of rhythm in Australian pied butcherbird song. ROYAL SOCIETY OPEN SCIENCE 2022; 9:220704. [PMID: 36177196 DOI: 10.6084/m9.figshare.c.6197494] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 09/05/2022] [Indexed: 05/21/2023]
Abstract
The acoustic structure of birdsong is spectrally and temporally complex. Temporal complexity is often investigated in a syntactic framework focusing on the statistical features of symbolic song sequences. Alternatively, temporal patterns can be investigated in a rhythmic framework that focuses on the relative timing between song elements. Here, we investigate the merits of combining both frameworks by integrating syntactic and rhythmic analyses of Australian pied butcherbird (Cracticus nigrogularis) songs, which exhibit organized syntax and diverse rhythms. We show that rhythms of the pied butcherbird song bouts in our sample are categorically organized and predictable by the song's first-order sequential syntax. These song rhythms remain categorically distributed and strongly associated with the first-order sequential syntax even after controlling for variance in note length, suggesting that the silent intervals between notes induce a rhythmic structure on note sequences. We discuss the implication of syntactic-rhythmic relations as a relevant feature of song complexity with respect to signals such as human speech and music, and advocate for a broader conception of song complexity that takes into account syntax, rhythm, and their interaction with other acoustic and perceptual features.
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Affiliation(s)
- Jeffrey Xing
- Department of Psychology, University of California San Diego, La Jolla, CA, USA
| | - Tim Sainburg
- Department of Psychology, University of California San Diego, La Jolla, CA, USA
| | - Hollis Taylor
- Sydney Conservatorium of Music, University of Sydney, Sydney, New South Wales, Australia
| | - Timothy Q Gentner
- Department of Psychology, University of California San Diego, La Jolla, CA, USA
- Neurobiology Section, Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA
- Kavli Institute for Brain and Mind, University of California San Diego, La Jolla, CA, USA
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Simmons AM, Ming C, Kloepper LN. Estimating chorusing activity by quantifying total acoustic energy. JASA EXPRESS LETTERS 2022; 2:081201. [PMID: 35967092 PMCID: PMC9358768 DOI: 10.1121/10.0013351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Accepted: 07/15/2022] [Indexed: 06/15/2023]
Abstract
Passive acoustics provides a powerful method for localizing vocalizing animals and estimating species abundance. A passive acoustics method previously used to census dense populations of flying bats is applied here to estimate chorusing activity of male bullfrogs vocalizing against anthropogenic noise. There are significant links between manual counts of the numbers of advertisement call notes and automatically detected notes and two measures of acoustic energy. These data provide a foundation for the use of acoustic energy measures to census vocal activity in different habitats.
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Affiliation(s)
- Andrea Megela Simmons
- Department of Cognitive, Linguistic, & Psychological Sciences, Brown University, Providence, Rhode Island, 02912, USA
| | - Chen Ming
- Carney Institute for Brain Science, Brown University, Providence, Rhode Island 02912, USA
| | - Laura N Kloepper
- Department of Biological Sciences, College of Life Sciences and Agriculture, University of New Hampshire, Durham, New Hampshire 03824, USA , ,
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