• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Avian research >Identification of vocal individuality in male cuckoos using different analytical techniques
【24h】

Identification of vocal individuality in male cuckoos using different analytical techniques

机译：使用不同分析技术识别雄性杜鹃的声音个性

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

BackgroundIndividuality in vocalizations may provide an effective tool for surveying populations of the Common Cuckoo ( Cuculus canorus ) but there remains few data on which technique to use to identify individuality. In this research, we compared the within- and between-individual variation in cuckoo calls using two different analytical methods, and discuss the feasibility of using call individuality to count male cuckoos within a population. MethodsWe recorded vocalization from 13 males, and measured 15 spectro-temporal variables for each call. The majority of these call variables ( n =?12) have greater variation between individuals than within individual. We first calculated the similarity (Pearson’s R) for each paired calls in order to find a threshold that could distinguish calls emitted from the same or different males, and then counted the number of males based on this distinction. Second, we used the more widely accepted technique of discriminant function analysis (DFA) to identify individual male cuckoos, and compared the correct rate of classifying individuals between the two analytical methods. ResultsSimilarity of paired calls from the same male was significantly higher than from different males. Under a relatively broad threshold interval, we achieved a high (>90%) correct rate to distinguish calls and an accurate estimate of male numbers. Based on banded males ( n =?3), we found the similarity of paired calls from different days was lower when compared with paired calls from the same day, but this change did not obscure individual identification, as similarity values of paired calls from different days were still larger than the threshold used to distinguish calls from the same or different males. DFA also yielded a high rate (91.9%) of correct classification of individuals. ConclusionsOur study suggests that identifying individual vocalizations can form the basis of an appropriate survey method for counting male cuckoos within a population, provided the performance of different analytical techniques are compared.
机译：背景技术发声中的个体性可能为调查杜鹃（Cuculus canorus）的种群提供一种有效的工具，但是关于用于识别个性的技术的数据很少。在这项研究中，我们使用两种不同的分析方法比较了布谷鸟的个体内部和个体之间的差异，并讨论了使用个体个体性对种群中的杜鹃进行计数的可行性。方法我们记录了13位男性的发声情况，并为每次通话测量了15个频谱时间变量。这些调用变量中的大多数（n =？12）在个体之间的变化要大于个体内部的变化。我们首先计算每个配对呼叫的相似度（皮尔逊R），以找到一个可以区分来自相同或不同男性的呼叫的阈值，然后根据此区别计算男性的数量。其次，我们使用了更广泛接受的判别函数分析（DFA）技术来识别个体杜鹃，并比较了两种分析方法之间对个体进行分类的正确率。结果同一男性的配对呼叫的相似性显着高于不同男性的配对呼叫。在相对较宽的阈值间隔内，我们实现了较高的（> 90％）正确率来区分通话和对男性号码的准确估计。基于带状雄性（n =？3），我们发现来自不同日期的配对呼叫的相似性低于同一天的配对呼叫，但是这种变化并未掩盖个人身份，因为来自不同日期的配对呼叫的相似性值天数仍然大于用来区分来自相同或不同男性的来电的阈值。 DFA还可以对个人进行正确分类，因此具有很高的识别率（91.9％）。结论我们的研究表明，如果比较不同分析技术的性能，则识别个体发声可以构成一种适当的调查方法的基础，该方法可以对种群中的杜鹃进行计数。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号