2018
DOI: 10.1007/s10071-018-1222-y
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Individuality in coo calls of adult male golden snub-nosed monkeys (Rhinopithecus roxellana) living in a multilevel society

Abstract: Vocal individuality is a prerequisite for individual recognition, especially when visual and chemical cues are not available or effective. Vocalizations encoding information of individual identity have been reported in many social animals and should be particularly adaptive for species living in large and complexly organized societies. Here, we examined the individuality in coo calls of adult male golden snub-nosed monkeys (Rhinopithecus roxellana) living in a large and multilevel society. Coo calls are one of… Show more

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Cited by 8 publications
(7 citation statements)
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References 70 publications
(149 reference statements)
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“…Although this can be done automatically using state of the art deep learning techniques (Stowell et al 2018), acoustic features are often extracted manually, whereby simple summary variables (e.g. min, max and mean) associated with the fundamental frequency and the harmonics are calculated (Fan et al 2019;Ji et al 2013).…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Although this can be done automatically using state of the art deep learning techniques (Stowell et al 2018), acoustic features are often extracted manually, whereby simple summary variables (e.g. min, max and mean) associated with the fundamental frequency and the harmonics are calculated (Fan et al 2019;Ji et al 2013).…”
Section: Introductionmentioning
confidence: 99%
“…The recognition models are assessed based on their ability to classify the 'unseen' calls correctly. Several algorithms have been used for this purpose, including discriminant functions (Blumstein and Munos 2005;Fan et al 2019), artificial neural networks (Mielke and Zuberbühler 2013;Reby et al 1998), gaussian mixture models (Cheng et al 2010) and hidden Markov models (Clemins et al 2005;Ji et al 2013). One of the main issues affecting the classification performance of vocal recognition models is the presence of background noise.…”
Section: Introductionmentioning
confidence: 99%
“…地和食物资源造成严重威胁 (Evers et al, 2018), 导 致 很 多 物 种 处 于 濒 临 灭 绝 的 状 态 (Hui, 2022;Johnson et al, 2017)。为了更好地、有针对性地保护 野生动物, 亟需采用高效的方式开展野生动物的种 群动态、栖息地利用和行为等方面的监测和保护管 理工作 (Grooten & Almond, 2018)。声音信号可以向 多个方向传播, 还可以穿过物理障碍进行远距离传 播 (Ma et al, 2020), 因此基于动物叫声特征开发的 被动声学监测(passive acoustic monitoring, PAM)技 术 已 成 为 生 物 多 样 性 评 估 的 一 项 重 要 手 段 (Rosenstock et al, 2002;Weir & Mossman, 2005)。该 技术指将声音传感器(以下称自动录音机)安装在野 外环境中收集野生动物及其所在环境的声音信号 的监测方法 (Parker, 1991;)。自 动录音机的数量可以是单一的, 也可以是多个的, 录音机矩阵能同步收集声音信号数据 (Blumstein et al, 2011)。PAM技术在野外应用时能够根据需求选 择特定时间段进行声音数据的收集 (Dufourq et al, 2021)。与耗费大量的人力、物力和财力并且会侵扰 动物的传统的距离抽样法 (Buckland et al, 2010; 李 月辉, 2021)和标志重捕法 (Markolf et al, 2022) (Nordeide & Kjellsby, 1999;Hawkins & Amorim, 2000;Lobel, 2002)。20世纪80年代, 随着成本更低、操作更简单 的水下自动录音机的出现, PAM技术开始被用于水 生哺乳动物的定位和研究 (Clark, 1980;Fripp et al, 2005;Mellinger & Heimlich, 2013) (Parker, 1991;Vielliard, 1993) (Charlton et al, 2010;Wyman et al, 2012), 叫声可以传播发声者物种、位置、数量、性别、个 体等信息 (McGregor, 2005;Wilkins et al, 2013;Fan et al, 2019), 能够实现警报危险 (Blumstein & Daniel, 2004)、 防御领域 (Ma et al, 2020)、 吸引配偶 (Milich et al, 2014)…”
Section: 人类社会的发展对野生动物赖以生存的栖息unclassified
“…Alternatively, considering the more uncertain and riskier between-unit relationships, social evolution could have favored vocal communication for cultivating bonds and reassuring a liation when interacting, potentially as replacements for more 'stressful' forms of a liative interactions (e.g., approaching, greeting, grooming). Based on our impression of two decades of longitudinal study and past research (Fan et al, 2018(Fan et al, , 2019, we suspect contact 'coo' calls could serve the above functions.…”
Section: Introductionmentioning
confidence: 99%