Avian vocal communication represents one of the most intricate forms of animal language,playing a critical role in behavioral interactions.Both peripheral and central auditory-vocal pathways are essential for precisel...Avian vocal communication represents one of the most intricate forms of animal language,playing a critical role in behavioral interactions.Both peripheral and central auditory-vocal pathways are essential for precisely integrating acoustic signals,ensuring effective communication.Like humans,songbirds exhibit vocal learning behaviors supported by complex neural mechanisms.However,unlike most mammals,songbirds possess the remarkable ability to regenerate damaged auditory cells.These capabilities offer unique opportunities to explore how birds adjust their vocal behavior and auditory processing in response to dynamic environmental conditions.Recent studies have advanced our understanding of the plasticity of avian vocal communication system,yet the vocal diversity and neurophysiological mechanisms underlying vocalization and hearing have often been examined independently.A comprehensive overview of how these systems interact and adapt in birds remains lacking.To address this gap,this review synthesizes the peripheral and central features of avian vocalization and hearing,while also exploring the mechanisms that drive the remarkable plasticity of these systems.Furthermore,it explores seasonal variations in bird vocalization and hearing and adaptations to environmental noise,focusing on how hormonal,neural,and ecological factors together shape vocal behavior and auditory sensitivity.Avian vocal communication systems present an exceptional model for studying the integration of peripheral and central vocal-auditory pathways and their adaptive responses to ever-changing environments.This review underscores the dynamic interactions between avian vocal communication systems and environmental stimuli,offering new insights into broader principles of sensory processing,and neuroplasticity.展开更多
Bird vocalizations are pivotal for ecological monitoring,providing insights into biodiversity and ecosystem health.Traditional recognition methods often neglect phase information,resulting in incomplete feature repres...Bird vocalizations are pivotal for ecological monitoring,providing insights into biodiversity and ecosystem health.Traditional recognition methods often neglect phase information,resulting in incomplete feature representation.In this paper,we introduce a novel approach to bird vocalization recognition(BVR)that integrates both amplitude and phase information,leading to enhanced species identification.We propose MHARes Net,a deep learning(DL)model that employs residual blocks and a multi-head attention mechanism to capture salient features from logarithmic power(POW),Instantaneous Frequency(IF),and Group Delay(GD)extracted from bird vocalizations.Experiments on three bird vocalization datasets demonstrate our method's superior performance,achieving accuracy rates of 94%,98.9%,and 87.1%respectively.These results indicate that our approach provides a more effective representation of bird vocalizations,outperforming existing methods.This integration of phase information in BVR is innovative and significantly advances the field of automatic bird monitoring technology,offering valuable tools for ecological research and conservation efforts.展开更多
Vocal communication plays an important role in survival,reproduction,and animal social association.Birds and mammals produce com-plex vocal sequence to convey context-dependent information.Vocalizations are conspicuou...Vocal communication plays an important role in survival,reproduction,and animal social association.Birds and mammals produce com-plex vocal sequence to convey context-dependent information.Vocalizations are conspicuous features of the behavior of most anuran species(frogs and toads),and males usually alter their calling strategies according to ecological context to improve the attractiveness/competitiveness.However,very few studies have focused on the variation of vocal sequence in anurans.In the present study,we used both conventional method and network analysis to investigate the context-dependent vocal repertoire,vocal sequence,and call network structure in serrate-legged small treefrogs Kurixalus odontotarsus.We found that male K.odontotarsus modified their vocal sequence by switching to different call types and increasing repertoire size in the presence of a competitive rival.Specifically,compared with before and after the playback of advertisement calls,males emited fewer advertisement calls,but more aggressive calls,encounter calls,and compound calls during the playback period.Network analysis revealed that the mean degree,mean closeness,and mean betweenness of the call networks significantly decreased during the playback period,which resulted in lower connectivity.in addition,the increased proportion of one-way motifs and average path length also indicated that the connectivity of the call network decreased in competitive context.However,the vocal sequence of K.odontotarsus did not display a clear small-world network structure,regardless of context.Our study presents a paradigm to apply network analysis to vocal sequence in anurans and has important implications for understanding the evolution and function of sequence patterns.展开更多
Echolocation calls of 10 Chinese rhinolophid species were recorded to investigate the relationship between morphology and echolocation signals. All horseshoe bats use FM-CF-FM calls. Rhinolophus rex calls at 23.7 kHz,...Echolocation calls of 10 Chinese rhinolophid species were recorded to investigate the relationship between morphology and echolocation signals. All horseshoe bats use FM-CF-FM calls. Rhinolophus rex calls at 23.7 kHz, the lowest frequency in this genus. Call frequency was not correlated with body mass (P=0.200, 9 species). Close negative relationships were found between call frequency and ear length (r=-0.942, P<0.001) and also between call frequency and forearm length (r=-0.696, P<0.05). Residual analysis was carried out to remove the influence of other morphological features. After calculating ear length, forearm length residuals were not significantly related to call frequency (r=-0.095, P=0.808). The significance of the correlation between ear length and call frequency was slightly lowered (r=-0.642, P=0.062) after “removing” the influence of forearm length. Ear length, therefore, was a better predictor of call frequency than forearm length [Acta Zoologica Sinica 49(1):128-133,2003].展开更多
基金supported by the National Natural Science Foundation of China(NSFC,32471572)to D.L.the NSFC(32401298)the Hebei Natural Science Foundation(C2023205016)to L.W。
文摘Avian vocal communication represents one of the most intricate forms of animal language,playing a critical role in behavioral interactions.Both peripheral and central auditory-vocal pathways are essential for precisely integrating acoustic signals,ensuring effective communication.Like humans,songbirds exhibit vocal learning behaviors supported by complex neural mechanisms.However,unlike most mammals,songbirds possess the remarkable ability to regenerate damaged auditory cells.These capabilities offer unique opportunities to explore how birds adjust their vocal behavior and auditory processing in response to dynamic environmental conditions.Recent studies have advanced our understanding of the plasticity of avian vocal communication system,yet the vocal diversity and neurophysiological mechanisms underlying vocalization and hearing have often been examined independently.A comprehensive overview of how these systems interact and adapt in birds remains lacking.To address this gap,this review synthesizes the peripheral and central features of avian vocalization and hearing,while also exploring the mechanisms that drive the remarkable plasticity of these systems.Furthermore,it explores seasonal variations in bird vocalization and hearing and adaptations to environmental noise,focusing on how hormonal,neural,and ecological factors together shape vocal behavior and auditory sensitivity.Avian vocal communication systems present an exceptional model for studying the integration of peripheral and central vocal-auditory pathways and their adaptive responses to ever-changing environments.This review underscores the dynamic interactions between avian vocal communication systems and environmental stimuli,offering new insights into broader principles of sensory processing,and neuroplasticity.
基金supported by the Beijing Natural Science Foundation (5252014)the National Natural Science Foundation of China (62303063)。
文摘Bird vocalizations are pivotal for ecological monitoring,providing insights into biodiversity and ecosystem health.Traditional recognition methods often neglect phase information,resulting in incomplete feature representation.In this paper,we introduce a novel approach to bird vocalization recognition(BVR)that integrates both amplitude and phase information,leading to enhanced species identification.We propose MHARes Net,a deep learning(DL)model that employs residual blocks and a multi-head attention mechanism to capture salient features from logarithmic power(POW),Instantaneous Frequency(IF),and Group Delay(GD)extracted from bird vocalizations.Experiments on three bird vocalization datasets demonstrate our method's superior performance,achieving accuracy rates of 94%,98.9%,and 87.1%respectively.These results indicate that our approach provides a more effective representation of bird vocalizations,outperforming existing methods.This integration of phase information in BVR is innovative and significantly advances the field of automatic bird monitoring technology,offering valuable tools for ecological research and conservation efforts.
基金supported by the National Natural Science Foundation of China(31772464,32000313)Youth Innovation Promotion Association CAS(2012274)+2 种基金Sichuan ScienceandTechnology Program1(2022JDTD0026)NaturalScience Foundation of Sichuan Province(2022NSFSC1736)Open Research Program in Ministry of Education Key Laboratory for Ecology of Tropical Islands(HNSF-OP-202002).
文摘Vocal communication plays an important role in survival,reproduction,and animal social association.Birds and mammals produce com-plex vocal sequence to convey context-dependent information.Vocalizations are conspicuous features of the behavior of most anuran species(frogs and toads),and males usually alter their calling strategies according to ecological context to improve the attractiveness/competitiveness.However,very few studies have focused on the variation of vocal sequence in anurans.In the present study,we used both conventional method and network analysis to investigate the context-dependent vocal repertoire,vocal sequence,and call network structure in serrate-legged small treefrogs Kurixalus odontotarsus.We found that male K.odontotarsus modified their vocal sequence by switching to different call types and increasing repertoire size in the presence of a competitive rival.Specifically,compared with before and after the playback of advertisement calls,males emited fewer advertisement calls,but more aggressive calls,encounter calls,and compound calls during the playback period.Network analysis revealed that the mean degree,mean closeness,and mean betweenness of the call networks significantly decreased during the playback period,which resulted in lower connectivity.in addition,the increased proportion of one-way motifs and average path length also indicated that the connectivity of the call network decreased in competitive context.However,the vocal sequence of K.odontotarsus did not display a clear small-world network structure,regardless of context.Our study presents a paradigm to apply network analysis to vocal sequence in anurans and has important implications for understanding the evolution and function of sequence patterns.
文摘Echolocation calls of 10 Chinese rhinolophid species were recorded to investigate the relationship between morphology and echolocation signals. All horseshoe bats use FM-CF-FM calls. Rhinolophus rex calls at 23.7 kHz, the lowest frequency in this genus. Call frequency was not correlated with body mass (P=0.200, 9 species). Close negative relationships were found between call frequency and ear length (r=-0.942, P<0.001) and also between call frequency and forearm length (r=-0.696, P<0.05). Residual analysis was carried out to remove the influence of other morphological features. After calculating ear length, forearm length residuals were not significantly related to call frequency (r=-0.095, P=0.808). The significance of the correlation between ear length and call frequency was slightly lowered (r=-0.642, P=0.062) after “removing” the influence of forearm length. Ear length, therefore, was a better predictor of call frequency than forearm length [Acta Zoologica Sinica 49(1):128-133,2003].
