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| Main Authors: | , , , , , , |
|---|---|
| Format: | Recurso digital |
| Language: | English |
| Published: |
Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.15746810 |
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Table of Contents:
- <p>Here you can find three files:</p> <p>Soniferous Species Review: This dataset combines NBN Atlas species occurrence data with Global Library of Underwater Biological Sounds (GLUBS) inventories and literature-based sound characteristics. It includes records of species in the area surrounding the study sites (10 km2 radius).</p> <p>Complete Dataset: This dataset contains all the processed data needed to produce the results in the primary paper, i.e. De Clippele et al (2025) Expanding the use of Passive Acoustic Monitoring (PAM) to assess benthic communities in sedimentary habitats associated with offshore wind farms. </p> <p>Script: This script contains the code needed to conduct the statistical analysis, generate the figures in De Clippele et al (2025), and to calculate the acoustic indices. </p> <p>Please cite both the Zenodo DOI: 10.5281/zenodo.15746810 and the primary paper if used for further analysis or modifications. </p> <p>Abstract</p> <p>Understanding biodiversity in offshore benthic ecosystems is crucial as anthropogenic pressures like offshore wind development increasingly alter marine environments. Passive Acoustic Monitoring (PAM), widely used for marine mammal research, offers a promising yet underexplored tool for assessing broader faunal communities. Here, we investigate whether PAM data, collected initially for marine mammal monitoring, can reveal spatial variation in benthic biodiversity along Scotland’s east coast. We analysed bio- and ecoacoustic data from eight offshore sedimentary habitats, identifying 16 distinct biological sound types produced by fish and invertebrates. Phonic richness and acoustic community structure were quantified across diel periods. Acoustic indices were also calculated and compared with environmental variables and benthic richness derived from biodiversity databases. Our results show that key habitat variables, including substrate type, current velocity, and spawning suitability, drive variation in acoustic communities. Several acoustic indices correlated with phonic richness and benthic diversity, suggesting potential for scalable acoustic proxies in ecosystem monitoring. These findings demonstrate that PAM can be used to detect biologically meaningful patterns in benthic assemblages, offering a cost-effective tool for long-term biodiversity monitoring. This study highlights the ecological value of existing acoustic datasets and advances our understanding of soundscape ecology and species-habitat relationships in changing marine environments.</p>