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Abstract: Substrate-borne vibrational signaling is one of the oldest and taxonomically widespread forms of animal communication. For many animals the natural vibrational environment (vibroscape) is an essential source of information underlying their behavioral decisions; however, the structure and dynamics of vibroscape composition of the natural habitats are largely unexplored. We studied vibroscape composition in a eutrophic lowland hay meadow and a sub-Mediterranean dry karst grassland. The results obtained by simultaneous, multi-channel recordings showed that vibroscape composition changes throughout the day and from day to day, differs between plant species, depends on the spatial position of the plant within the habitat and is also influenced by environmental parameters. The results highlight the unpredictability and high variability of the vibrational environment encountered by plant-dwelling insects, and the complexity in implementing biodiversity monitoring based on vibroscape composition.
Keywords: biotremology, ecotremology, vibroscape, vibrational communication, vibrational community, environmental factors, zoology, ecology
Published in DiRROS: 02.07.2025; Views: 1057; Downloads: 962
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Abstract: The ecological significance of vibroscape has been largely overlooked, excluding an important part of the available information from ecosystem assessment. Insects rely primarily on substrate-borne vibrational signalling in their communication, which is why the majority of terrestrial insects are excluded from passive acoustic monitoring. The ability to monitor the biological component of the natural vibroscape has been limited due to a lack of data and methods to analyse the data. In this paper, we evaluate the use of deep learning models to automatically detect and classify vibrational signals from field recordings obtained with laser vibrometry. We created a dataset of annotated vibroscape recordings of meadow habitats, containing vibrational signals categorized as pulses, harmonic signals, pulse trains, and complex signals. We compared different deep neural network architectures for the detection and classification of vibrational signals, including convolutional and transformer models. The PaSST transformer architecture, which was fine-tuned from a pre-trained checkpoint demonstrated the highest performance on all tasks, achieving an average precision of 0.79 in signal detection. For signals with more than one hour of annotated data, the classification models achieved instance-based F1-scores above 0.8, enabling automatic analysis of activity patterns. In our case study, where 24-hour field recordings were analysed, the trained models (even those with lower precision) revealed interesting activity patterns of different species. The presented study, together with the dataset we publish with this paper, lays the foundation for further analysis of the vibroscape and the development of automated methods for ecotremological monitoring that complement passive acoustic monitoring and provide a comprehensive approach to ecosystem assessment.
Keywords: vibroscape, ecotremology, deep learning, automatic classification, biotremology, insects, zoology, laser vibrometry, ecosystem assessment
Published in DiRROS: 21.01.2025; Views: 1059; Downloads: 626
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Abstract: Our awareness of air-borne sounds in natural and urban habitats has led to the recent recognition of soundscape ecology and ecoacoustics as interdisciplinary fields of research that can help us better understand ecological processes and ecosystem dynamics. Because the vibroscape (i.e., the substrate-borne vibrations occurring in a given environment) is hidden to the human senses, we have largely overlooked its ecological significance. Substrate vibrations provide information crucial to the reproduction and survival of most animals, especially arthropods, which are essential to ecosystem functioning. Thus, vibroscape is an important component of the environment perceived by the majority of animals. Nowadays, when the environment is rapidly changing due to human activities, climate change, and invasive species, this hidden vibratory world is also likely to change without our notice, with potentially crucial effects on arthropod communities. Here, we introduce ecotremology, a discipline that mainly aims at studying substrate-borne vibrations for unraveling ecological processes and biological conservation. As biotremology follows the main research concepts of bioacoustics, ecotremology is consistent with the paradigms of ecoacoustics. We argue that information extracted from substrate vibrations present in the environment can be used to comprehensively assess and reliably predict ecosystem changes. We identify key research questions and discuss the technical challenges associated with ecotremology studies.
Keywords: ecotremology, monitoring, hidden biodiversity, vibroscape, vibrational communication
Published in DiRROS: 16.07.2024; Views: 2274; Downloads: 846
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