Passive monitoring of bat species via acoustics is a growing field and as a result there are various software programs available that allow for species identification. However, accuracy of these programs is variable and creating a local call library is essential when trying to identify acoustically similar species. In Dinosaur Provincial Park, Alberta, Canada, 3 Myotis species are difficult to distinguish acoustically. We created an echolocation call library from known Myotis evotis, M. lucifugus, and M. ciliolabrum flying in open spaces and near clutter to test whether or not recording in the bats' local habitat type improved call library quality and identification accuracy. Bat calls recorded within open spaces (coulees) differed from those recorded near cluttered spaces (tree edges) for M. ciliolabrum and M. lucifugus. Accuracy of species identification also increased when we used models based on bat calls recorded in cluttered habitats. Using a simple model with recordings from different habitat types within a study site, we were able to improve identification accuracy and model performance. © 2019 The Wildlife Society.

中文翻译：

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通过考虑栖息地类型来改进蝙蝠的声学调查

通过声学对蝙蝠物种进行被动监测的领域正在不断发展，因此，有各种软件程序可用于物种识别。但是，这些程序的准确性是可变的，在尝试识别声学上相似的物种时，创建本地调用库至关重要。在加拿大艾伯塔省的恐龙省立公园中，很难区分3种Myotis物种。我们从已知的Myotis evotis，M.lucifugus和M.ciliolabrum创建了一个回声定位调用库在开放空间和近乎混乱的环境中飞行，以测试用蝙蝠的本地栖息地类型记录是否改善了呼叫库的质量和识别准确性。在空旷空间（细小柱）中记录的蝙蝠鸣叫不同于在纤细空间（M. ciliolabrum）和lucifugus的M. lucifugus记录在混乱空间（树边缘）附近的蝙蝠鸣叫。当我们使用基于在混乱的栖息地中记录的蝙蝠鸣叫的模型时，物种识别的准确性也会提高。使用一个简单的模型并结合研究地点不同栖息地类型的记录，我们能够提高识别准确性和模型性能。©2019野生动物协会。