Call Characteristic Network Reveal Geographical Patterns of Call Similarity:Applying Network Analysis to Frog’s Call Research

作     者：Ke DENG Yue YANG Jianguo CUI Ke DENG;Yue YANG;Jianguo CUI

作者机构：CAS Key Laboratory of Mountain Ecological Restoration and Bioresource Utilization&Ecological Restoration and Biodiversity Conservation Key Laboratory of Sichuan PrcnnnceChengdu Institute of BiologyChinese Academy of SciencesChengdu 610041SichuanChina 

出 版 物：《Asian Herpetological Research》 (亚洲两栖爬行动物研究（英文版）)

年 卷 期：2021年第12卷第1期

页      面：110-116页

核心收录：

学科分类：071011[理学-生物物理学] 0710[理学-生物学] 07[理学] 

基　　金：National Natural Science Foundation of China(31772464,32000313) CAS“Light of West China”Program(2017XBZGXBQNXZB013) Youth Innovation Promotion Association CAS(2012274) the Biodiversity Survey and Assessment Project of the Ministry of Ecology and Environment,China(2019HJ2096001006) 

主　　题：acoustic feature anurans Chiromantis doriae eigenvector centrality geographical population 

摘      要：Individual’s phenotypic traits are the results of adaptation to ecological ***,different selection pressures caused by heterogeneous environments may result in phenotypic difference,especially for individuals in different geographical ***,we illustrated for the first time to use social network analysis(SNA)for examining whether geographical proximity predicts the similarity patterns in call characteristics among populations of an anuran *** recorded calls from 150 male dorsal-striped opposite-fingered treefrogs(Chiromantis doriae)at 11 populations in Hainan Province and one population in Guangdong Province in China s Mainland,and we measured eight acoustic variables for each *** test didn’t show a correlation between geographical proximity and the similarity in call characteristics among *** addition,we failed to find correlations between a population’s eigenvector centrality and the distance to its nearest neighbor,nor between the coefficient of variation of similarity in call characteristics of a population and the average distance to all other ***,three acoustic clusters were identified by the Girvan-Newman algorithm,and clustering was partially associated with ***,the most central populations were included in the same cluster,but the top betweenness populations were located within different clusters,suggesting that centrality populations are not necessary bridging between *** results demonstrate the potential usefulness of the SNA toolbox and indicate that SNA helps to uncover the patterns that often overlooked in other analytical *** using SNA in frog’s call studies,researchers could further uncover the potential relationship in call characteristics between geographical populations,further reveal the effects of ecological factors on call characteristics,and probably enhance our understanding of the adaptive evolution of acoustic signals.