Data

Supplementary to Acoustic differentiation of soil-surface-dwelling invertebrates under controlled conditions

Flinders University
Alex Taylor (Aggregated by) Amy Annells (Aggregated by) Jake Robinson (Aggregated by) Martin Breed (Aggregated by) Martin F. Breed (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25451/flinders.31991418.v1&rft.title=Supplementary to Acoustic differentiation of soil-surface-dwelling invertebrates under controlled conditions&rft.identifier=10.25451/flinders.31991418.v1&rft.publisher=Flinders University&rft.description=Soil degradation threatens food security, climate regulation, biodiversity and human wellbeing worldwide. Up to 75% of the world’s soils are degraded, , prompting rapid upscaling of global restoration efforts to meet international targets. Moreover, many soil management practices (e.g., conservation agriculture, cover cropping, reforestation) create litter/mulch habitats that support soil-surface-dwelling microbial and invertebrate functions. However, monitoring soil and leaf-litter biodiversity remains a major barrier to tracking restoration success, particularly for invertebrates that underpin key processes such as nutrient cycling and soil aggregation. Traditional sampling methods are labour-intensive, destructive and poorly suited to long-term or landscape-scale monitoring. Soil ecoacoustics is emerging as a promising non-destructive tool for monitoring soil biodiversity. However, its capacity for taxonomic resolution of invertebrate groups remains untested. Here, we present a proof-of-concept study demonstrating the potential of a soil-surface-dwelling invertebrate acoustic classifier. Using a low-cost, sound-attenuated recording system, we quantified 19 spectral and temporal audio features from six morphologically and behaviourally distinct invertebrate species under controlled conditions. Acoustic profiles differed among taxa and generally clustered into podous and apodous groups, suggesting that acoustic signatures capture taxon-specific traits. This work provides a foundation for developing automated acoustic classifiers that could enable scalable, non-destructive monitoring of soil biodiversity.&rft.creator=Alex Taylor&rft.creator=Amy Annells&rft.creator=Jake Robinson&rft.creator=Martin Breed&rft.creator=Martin F. Breed&rft.creator=Riley Hodgson&rft.creator=Sofie Costin&rft.creator=Tarryn Davies&rft.creator=Timothy Cavagnaro&rft.creator=Timothy Cavagnaro&rft.date=2026&rft_rights= https://creativecommons.org/licenses/by/4.0/&rft_subject=Ecological applications not elsewhere classified&rft_subject=Acoustic feature analysis&rft_subject=Ecosystem monitoring&rft_subject=Invertebrate identification&rft_subject=Soil biodiversity&rft_subject=Soil ecoacoustics&rft.type=dataset&rft.language=English Access the data

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Soil degradation threatens food security, climate regulation, biodiversity and human wellbeing worldwide. Up to 75% of the world’s soils are degraded, , prompting rapid upscaling of global restoration efforts to meet international targets. Moreover, many soil management practices (e.g., conservation agriculture, cover cropping, reforestation) create litter/mulch habitats that support soil-surface-dwelling microbial and invertebrate functions. However, monitoring soil and leaf-litter biodiversity remains a major barrier to tracking restoration success, particularly for invertebrates that underpin key processes such as nutrient cycling and soil aggregation. Traditional sampling methods are labour-intensive, destructive and poorly suited to long-term or landscape-scale monitoring. Soil ecoacoustics is emerging as a promising non-destructive tool for monitoring soil biodiversity. However, its capacity for taxonomic resolution of invertebrate groups remains untested. Here, we present a proof-of-concept study demonstrating the potential of a soil-surface-dwelling invertebrate acoustic classifier. Using a low-cost, sound-attenuated recording system, we quantified 19 spectral and temporal audio features from six morphologically and behaviourally distinct invertebrate species under controlled conditions. Acoustic profiles differed among taxa and generally clustered into podous and apodous groups, suggesting that acoustic signatures capture taxon-specific traits. This work provides a foundation for developing automated acoustic classifiers that could enable scalable, non-destructive monitoring of soil biodiversity.

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ACN 633 798 857