Passive acoustic monitoring of the diel and annual vocal behavior of the Black and Gold Howler Monkey

Pérez‐Granados, Cristian; Schuchmann, Karl‐Ludwig

doi:10.1002/ajp.23241

Cited by 21 publications

(19 citation statements)

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“…Nocturnal vocalizations from diurnal primates have rarely been studied [1,5,8,10,14]. While previous research on the Guianan red howler monkey described different types of calls in their repertoire [15], a detailed and systematic description of their vocal behavior and howling bouts was lacking.…”

Section: Discussionmentioning

confidence: 99%

“…These loud calls are thought to have multiple functions [2]. For example, loud calls may reduce predation risk, facilitate group cohesion, mediate sexual selection by male-male competition or female choice, and regulate intergroup use of space [2][3][4][5]. Despite the large interest in these remarkable loud calls, several species of howler monkeys still lack acoustic characterization of their calls [2,6,7].…”

Section: Introductionmentioning

confidence: 99%

“…Despite the large interest in these remarkable loud calls, several species of howler monkeys still lack acoustic characterization of their calls [2,6,7]. Even less is known about the nocturnal vocal activity of howlers because most studies focus on their diurnal behaviors [1,2,5].…”

Section: Introductionmentioning

confidence: 99%

“…Anthropoids, except the genus Aotus, are considered diurnal. However, there are reports of several anthropoids, such as mantled howler monkeys (Alouatta palliata), black-and-gold howler monkeys (Alouatta caraya), red-tailed monkeys (Cercopithecus ascanius), chimpanzees (Pan troglodytes), Ugandan red colobus monkeys (Procolobus rufomitratus Diversity 2021, 13, 566 2 of 12 tephrosceles), and Guianan red howler monkeys (Alouatta macconnelli) showing nocturnal activity [5,10,[14][15][16]. Diurnal sample bias [8,9] may preclude appreciation that species thought to be strictly diurnal are active during the full diel cycle [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

“…Emerging new technologies and techniques, such as passive acoustic monitoring (PAM) and automatic acoustic detection of calls [20][21][22], greatly facilitate studying soundproducing animals at night and have the potential to advance both behavioral ecology and conservation practices [23][24][25]. Recently, researchers have used PAM and automatic classifiers to decipher diel and annual vocal cycles of black-and-gold howlers and mantled howlers [5,26] and expanded upon the number of acoustic features analyzed for black howlers (Alouatta pigra) and mantled howlers [6,7]. These studies highlighted the utility of PAM and automatic acoustic detection of calls as promising methods to monitor primates and improve understanding of their vocal behavior.…”

Section: Introductionmentioning

confidence: 99%

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Passive Acoustic Monitoring and Automatic Detection of Diel Patterns and Acoustic Structure of Howler Monkey Roars

2021

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Nighttime studies are underrepresented in ecological research. Even well-known behaviors, such as the loud call of howler monkeys, are rarely studied at night. Our goal was to help fill this knowledge gap by studying the 24 h vocal behavior of the Guianan red howler monkey (Alouatta macconnelli) and to compare the acoustic structures of howling bouts made during the day to those made at night. We used passive acoustic monitoring coupled with automatic acoustic detection to study three groups of howlers over three months in the Viruá National Park, Roraima, Brazil. The automatic classifier we built detected 171 howling bouts with a 42% recall rate and 100% precision. Though primarily diurnal, howlers vocalized mainly at night. Greater vocal activity before nautical twilight might be associated with territorial and resource defense behaviors, with howlers calling from roosting sites before starting their daily routines. We also found that during the day, howling bouts were longer and had lower harmonic-to-noise ratios, lower frequencies, and more symmetric energy distributions than bouts at night. Our study adds to growing evidence that passive acoustic monitoring and automatic acoustic detection can be used to study primates and improve our understanding of their vocal behavior.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Passive Acoustic Monitoring and Automatic Detection of Diel Patterns and Acoustic Structure of Howler Monkey Roars

2021

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Performance of autonomous recorders to detect a cryptic and endangered primate species, the black lion‐tamarin (Leontopithecus chrysopygus)

Zambolli

Manzano

Honda

et al. 2022

American J Primatol

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Information about species distribution is important for conservation but the monitoring of populations can demand a high sampling effort with traditional methods (e.g., line transects, sound playback) that are poorly efficient for cryptic primates, such as the black lion tamarin (Leontopithecus chrysopygus). Here we investigated the effectiveness of passive acoustic monitoring (PAM) as an alternative method to identify the presence of vocalizing lion tamarins in the wild. We aimed to: (1) determine the maximum distance at which autonomous recorders (Song Meter 3) and Raven Pro acoustic software can respectively detect and identify lion tamarin long calls emitted by two captive subjects (ex situ study); and (2) determine the sampling effort required to confirm the presence of the species in the wild (in situ study). In captive settings, we recorded lion tamarin long calls with one to two autonomous recorders operating at increasing distances from the animals' enclosure (8−202 m). In a 515 ha forest fragment, we deployed 12 recorders in a grid, 300 m apart from each other, within the estimated 100 ha home range of one group, and let them record for 10 consecutive days, totaling 985 h. In the ex situ study, hand‐browsing of spectrograms yielded 298 long calls emitted from 8 to 194 m, and Raven's Template Detector identified 54.6% of them, also emitted from 8 to 194 m. In the in situ study, we manually counted 1115 long calls, and the Raven's Template Detector identified 44.75% of them. Furthermore, the presence of lion tamarins was confirmed within 1 day using four randomly sorted recorders, whereas 5 days on average were necessary with only one device. While specific protocols still need to be developed to determine primate population size using this technology, we concluded that PAM is a promising tool when considering long term costs and benefits.

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Pairing a user‐friendly machine‐learning animal sound detector with passive acoustic surveys for occupancy modeling of an endangered primate

Wood

Cruz

Kahl

2023

American J Primatol

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Population declines and range contractions due to habitat loss are pervasive among nonhuman primates, with 60% of species threatened with extinction.However, the extensive vocal activity displayed by many primates makes them excellent candidates for passive acoustic surveys. Passive acoustic survey data is increasingly being used to support occupancy models, which have proven to be an efficient means of estimating both population trends and distributions.Passive acoustic surveys can be conducted relatively quickly and at broad scales, but efficient audio data processing has long proven elusive. The machine learning algorithm BirdNET was originally developed for birds but was recently expanded to include nonavian taxa. We demonstrate that BirdNET can accurately and efficiently identify an endangered primate, the Yucatán black howler monkey (Alouatta pigra), by sound in passive acoustic survey data (collected in southeastern Chiapas, Mexico), enabling us to use a single-season occupancy model to inform further survey efforts. Importantly, we also generated data on up to 286 co-occurring bird species, demonstrating the value of integrated animal sound classification tools for biodiversity surveys.BirdNET is freely available, requires no computer science expertise to use, and can readily be expanded to include more species (e.g., its species list recently tripled to >3000), suggesting that passive acoustic surveys, and thus occupancy modeling, for primate conservation could rapidly become much more accessible.Importantly, the long history of bioacoustics in primate research has yielded a wealth of information about their vocal behavior, which can facilitate appropriate survey design and data interpretation.

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Passive acoustic monitoring of the diel and annual vocal behavior of the Black and Gold Howler Monkey

Cited by 21 publications

References 55 publications

Passive Acoustic Monitoring and Automatic Detection of Diel Patterns and Acoustic Structure of Howler Monkey Roars

Passive Acoustic Monitoring and Automatic Detection of Diel Patterns and Acoustic Structure of Howler Monkey Roars

Performance of autonomous recorders to detect a cryptic and endangered primate species, the black lion‐tamarin (Leontopithecus chrysopygus)

Pairing a user‐friendly machine‐learning animal sound detector with passive acoustic surveys for occupancy modeling of an endangered primate

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