Abstract
Bat-pollinated flowers have to attract their pollinators in absence of light and therefore some species developed specialized echoic floral parts. These parts are usually concave shaped and act like acoustic retroreflectors making the flowers acoustically conspicuous to the bats. Acoustic plant specializations only have been described for two bat-pollinated species in the Neotropics and one other bat-dependent plant in South East Asia. However, it remains unclear whether other bat-pollinated plant species also show acoustic adaptations. Moreover, acoustic traits have never been compared between bat-pollinated flowers and flowers belonging to other pollination syndromes. To investigate acoustic traits of bat-pollinated flowers we recorded a dataset of 32320 flower echoes, collected from 168 individual flowers belonging to 12 different species. 6 of these species were pollinated by bats and 6 species were pollinated by insects or hummingbirds. We analyzed the spectral target strength of the flowers and trained a convolutional neural network (CNN) on the spectrograms of the flower echoes. We found that bat-pollinated flowers have a significantly higher echo target strength, independent of their size, and differ in their morphology, specifically in the lower variance of their morphological features. We found that a good classification accuracy by our CNN (up to 84%) can be achieved with only one echo/spectrogram to classify the 12 different plant species, both bat-pollinated and otherwise, with bat-pollinated flowers being easier to classify. The higher classification performance of bat-pollinated flowers can be explained by the lower variance of their morphology.
Highlights
The more relevant information about the environment an animal can extract from the continuous sensory information flow, the better and more efficiently it can navigate, and the more resources it may access [1]
Some plant species that are pollinated by bats evolved echo acoustic signals to attract their nocturnal pollinators
Few of the more than 400 bat-pollinated neotropical plants have been studied in this regard and it remained unclear if bat-pollinated flowers share general echo acoustic adaptations and differ acoustically from flowers that are pollinated by other animals
Summary
The more relevant information about the environment an animal can extract from the continuous sensory information flow, the better and more efficiently it can navigate, and the more resources it may access [1]. In order to obtain relevant information, the stream of information is filtered, evaluated and compared with known sensory templates This is commonly referred to as a classification task [2]. In the case of a nectar-feeding bat searching for flowers, this stream of information will consist of visual [3] and olfactory information [4] and of echo acoustic information. The latter is important for detection and during the approach of flowers [5,6,7,8]. It has been debated to which extent plant and flower echoes contain information about the physical form [9,10] and whether echolocating bats can identify and classify plants and flowers by their echoes alone [9,11,12]
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