Abstract

To effectively conserve biodiversity, first we must know where it is distributed. Bats are an important component of biodiversity; they comprise a fifth of all mammal species and provide essential ecosystem services such as insect regulation, pollination and seed dispersal. However, they are challenging to survey using conventional trapping and visual sampling methods as they are small, nocturnal and many are difficult to catch and identify. Given that all European bats use echolocation to navigate and find prey, acoustic methods are a promising alternative method of generating distribution data. However distinguishing between the calls of different bat species can be difficult due to the similarity in temporal and spectral structures of calls of different species and the flexibility and intraspecific variability in calls. An objective statistical method of identification is required in order to give a robust classification of echolocation calls. Here I present work on developing algorithms to distinguish between the echolocation calls of 33 European bat species, as an acoustic identification tool. This will aid the collection of bat distribution data in Europe, which can then be entered into spatial models of bat distributions.