Search

Menu
Search
in Ecology

A finely annotated dataset for the automated acoustic identification of European Orthoptera and Cicadidae

62 Views


Abstract

Mounting evidence points to widespread declines in insect abundance and diversity across European terrestrial ecosystems, highlighting an urgent need for effective large-scale monitoring methods. Passive acoustic monitoring enables the monitoring of sound-producing insects at an unprecedented temporal and spatial scale by remotely capturing sounds such as orthopteran stridulations and cicada timbalizations. However, current automated recognition tools for European insect sounds remain limited, and developing algorithms capable of reliably identifying diverse species requires large, ecologically heterogeneous acoustic datasets. Here we present a dataset of 11,224 recordings covering 193 orthopteran and 24 cicada species from North, Central, and temperate Western Europe. It combines coarsely labeled recordings, for which we can only infer the presence, at some point, of their target species (weak labeling), with finely annotated recordings that specify the time and frequency range of each insect sound (strong labeling). This dataset complements existing online resources and supports the advancement of automated acoustic classification for orthopterans and cicadas, aiding biodiversity monitoring efforts across Europe.

Data availability

All data have been deposited in the following Zenodo repository62: https://doi.org/10.5281/zenodo.15043892.

Code availability

All scripts used to generate the figures and tables in this paper, based on the collection of CSV files describing our dataset, are available at: https://github.com/DavidFunosas/ECOSoundSet_database_analysis. The script for retrieving all recordings from the selected online platforms based on GBIF query results is available at: https://github.com/DavidFunosas/GBIF_recording_download. The model used to assess the effect of audio segment duration on automated species recognition performance is available at: https://huggingface.co/AlexanderGbd/insects-base-cnn10-96k-t.

References

  1. Conrad, K. F., Warren, M. S., Fox, R., Parsons, M. S. & Woiwod, I. P. Rapid declines of common, widespread British moths provide evidence of an insect biodiversity crisis. Biological Conservation 132, 279–291 (2006).

    Google Scholar 

  2. Goulson, D., Lye, G. C. & Darvill, B. Decline and Conservation of Bumble Bees. Annual Review of Entomology 53, 191–208 (2008).

    Google Scholar 

  3. Thomas, J. A. Butterfly communities under threat. Science 353, 216–218 (2016).

    Google Scholar 

  4. Hallmann, C. A. et al. More than 75 percent decline over 27 years in total flying insect biomass in protected areas. PLOS ONE 12, e0185809 (2017).

    Google Scholar 

  5. Forister, M. L., Pelton, E. M. & Black, S. H. Declines in insect abundance and diversity: We know enough to act now. Conservation Science and Practice 1, e80 (2019).

    Google Scholar 

  6. Seibold, S. et al. Arthropod decline in grasslands and forests is associated with landscape-level drivers. Nature 574, 671–674 (2019).

    Google Scholar 

  7. Pilotto, F. et al. Meta-analysis of multidecadal biodiversity trends in Europe. Nat Commun 11, 3486 (2020).

    Google Scholar 

  8. van Klink, R. et al. Meta-analysis reveals declines in terrestrial but increases in freshwater insect abundances. Science 368, 417–420 (2020).

    Google Scholar 

  9. Fox, R. et al. The State of Britain’s Larger Moths. Butterfly Conservation https://butterfly-conservation.org/sites/default/files/2021-03/StateofMothsReport2021.pdf (2021).

  10. van Klink, R. et al. Disproportionate declines of formerly abundant species underlie insect loss. Nature 628, 359–364 (2024).

    Google Scholar 

  11. Dirzo, R. et al. Defaunation in the Anthropocene. Science 345, 401–406 (2014).

    Google Scholar 

  12. van Strien, A. J., van Swaay, C. A. M., van Strien-van Liempt, W. T. F. H., Poot, M. J. M. & WallisDeVries, M. F. Over a century of data reveal more than 80% decline in butterflies in the Netherlands. Biological Conservation 234, 116–122 (2019).

    Google Scholar 

  13. Widmer I. Disparition des insectes en Suisse et conséquences éventuelles pour la société et l’économie. Académies Suisses des Sciences https://web.archive.org/web/20190624224701/https://sciencesnaturelles.ch/uuid/59525e50-0606-539e-aa5a-b08adfa8d5cd?r=20190205110021_1554969605_fbc4f2c5-bff4-5035-94ee-709aaffddb7e (2019).

  14. Møller, A. P. Quantifying rapidly declining abundance of insects in Europe using a paired experimental design. Ecol Evol 10, 2446–2451 (2020).

    Google Scholar 

  15. Wagner, D. L., Grames, E. M., Forister, M. L., Berenbaum, M. R. & Stopak, D. Insect decline in the Anthropocene: Death by a thousand cuts. Proceedings of the National Academy of Sciences 118, e2023989118 (2021).

    Google Scholar 

  16. Rumohr, Q. et al. Drivers and pressures behind insect decline in Central and Western Europe based on long-term monitoring data. PLOS ONE 18, e0289565 (2023).

    Google Scholar 

  17. Eisenhauer, N., Bonn, A. & Guerra, C. A. Recognizing the quiet extinction of invertebrates. Nat Commun 10, 50 (2019).

    Google Scholar 

  18. van Klink, R. et al. InsectChange: a global database of temporal changes in insect and arachnid assemblages. Ecology 102, e03354 (2021).

    Google Scholar 

  19. Darras, K. et al. Comparing the sampling performance of sound recorders versus point counts in bird surveys: A meta-analysis. Journal of Applied Ecology 55, 2575–2586 (2018).

    Google Scholar 

  20. Darras, K. et al. Autonomous sound recording outperforms human observation for sampling birds: a systematic map and user guide. Ecol Appl 29, e01954 (2019).

    Google Scholar 

  21. Melo, I., Llusia, D., Bastos, R. P. & Signorelli, L. Active or passive acoustic monitoring? Assessing methods to track anuran communities in tropical savanna wetlands. Ecological Indicators 132, 108305 (2021).

    Google Scholar 

  22. Napier, T., Ahn, E., Allen-Ankins, S., Schwarzkopf, L. & Lee, I. Advancements in preprocessing, detection and classification techniques for ecoacoustic data: A comprehensive review for large-scale Passive Acoustic Monitoring. Expert Systems with Applications 252, 124220 (2024).

    Google Scholar 

  23. Bobay, L. R., Taillie, P. J. & Moorman, C. E. Use of autonomous recording units increased detection of a secretive marsh bird. Journal of Field Ornithology 89, 384–392 (2018).

    Google Scholar 

  24. Barbaro, L. et al. COVID-19 shutdown revealed higher acoustic diversity and vocal activity of flagship birds in old-growth than in production forests. Science of The Total Environment 901, 166328 (2023).

    Google Scholar 

  25. Brunk, K. M. et al. Quail on fire: changing fire regimes may benefit mountain quail in fire-adapted forests. Fire Ecology 19, 19 (2023).

    Google Scholar 

  26. Bielski, L., Cansler, C. A., McGinn, K., Peery, M. Z. & Wood, C. M. Can the Hermit Warbler (Setophaga occidentalis) serve as an old-forest indicator species in the Sierra Nevada? Journal of Field Ornithology 95 (2024).

  27. Claireau, F. et al. Major roads have important negative effects on insectivorous bat activity. Biological Conservation 235, 53–62 (2019).

    Google Scholar 

  28. Hoggatt, M. L., Starbuck, C. A. & O’Keefe, J. M. Acoustic monitoring yields informative bat population density estimates. Ecology and Evolution 14, e11051 (2024).

    Google Scholar 

  29. Chen, Y., Tournayre, O., Tian, H. & Lougheed, S. C. Assessing the breeding phenology of a threatened frog species using eDNA and automatic acoustic monitoring. PeerJ 11, e14679 (2023).

    Google Scholar 

  30. Bota, G. et al. Passive acoustic monitoring and automated detection of the American bullfrog. Biol Invasions 26, 1269–1279 (2024).

    Google Scholar 

  31. Carruthers-Jones, J., Holmes, G. & Norum, R. The Sounds of Silence: Perspectives on Documenting Acoustic Landscapes at the Intersection of Remoteness, Conservation and Tourism. Humanities 14, 41 (2025).

    Google Scholar 

  32. Arend, D. et al. Soundscape-based evaluation of small-scale forest management interventions. Forest Ecology and Management 596, 123067 (2025).

    Google Scholar 

  33. Newson, S. E., Bas, Y., Murray, A. & Gillings, S. Potential for coupling the monitoring of bush-crickets with established large-scale acoustic monitoring of bats. Methods in Ecology and Evolution 8, 1051–1062 (2017).

    Google Scholar 

  34. Riede, K. & Balakrishnan, R. Acoustic monitoring for tropical insect conservation. Philosophical Transactions of the Royal Society B: Biological Sciences 380, 20240046 (2025).

  35. Symes, L. B., Madhusudhana, S., Martinson, S. J., Geipel, I. & ter Hofstede, H. M. Multi-year soundscape recordings and automated call detection reveals varied impact of moonlight on calling activity of neotropical forest katydids. Philosophical Transactions of the Royal Society B: Biological Sciences 379, 20230110 (2024).

    Google Scholar 

  36. Thibault, M., Garnier, L. K. M., Kauffmann, C., Bas, Y. & Kerbiriou, C. Listening to the response of bat and bush-cricket communities to management regimes of powerline clearings. Conservation Science and Practice 6, e13127 (2024).

    Google Scholar 

  37. Bennett, D., Nissen, H., Maschke, M. A., Reck, H. & Diekötter, T. Recent technological developments allow for passive acoustic monitoring of Orthoptera (grasshoppers and crickets) in research and conservation across a broad range of temporal and spatial scales. Basic and Applied Ecology 84, 147–157 (2025).

    Google Scholar 

  38. Gasc, A. et al. Soundscapes reveal disturbance impacts: biophonic response to wildfire in the Sonoran Desert Sky Islands. Landscape Ecol 33, 1399–1415 (2018).

    Google Scholar 

  39. Do Nascimento, L. A., Pérez-Granados, C., Alencar, J. B. R. & Beard, K. H. Time and habitat structure shape insect acoustic activity in the Amazon. Philosophical Transactions of the Royal Society B: Biological Sciences 379, 20230112 (2024).

    Google Scholar 

  40. Attinger, A., Dörfel, T. & Mayer, J. Singzikaden (Cicadoidea) in Baden-Württemberg Erste Ergebnisse einer Erfassung mit automatischen Aufzeichnungsgeräten (AudioMoth). Artenschutz und Biodiversität 6, 1–11 (2025).

    Google Scholar 

  41. Rodríguez Ballesteros, A. et al. Towards acoustic monitoring of bees: wingbeat sounds are related to species and individual traits. Philosophical Transactions of the Royal Society B: Biological Sciences 379, 20230111 (2024).

    Google Scholar 

  42. Sebastián-González, E. et al. Density estimation of sound-producing terrestrial animals using single automatic acoustic recorders and distance sampling. Avian Conservation and Ecology 13, (2018).

  43. Gasc, A., Sueur, J., Pavoine, S., Pellens, R. & Grandcolas, P. Biodiversity Sampling Using a Global Acoustic Approach: Contrasting Sites with Microendemics in New Caledonia. PLOS ONE 8, e65311 (2013).

    Google Scholar 

  44. Towsey, M. et al. Visualization of Long-duration Acoustic Recordings of the Environment. Procedia Computer Science 29, 703–712 (2014).

    Google Scholar 

  45. Kahl, S., Wood, C. M., Eibl, M. & Klinck, H. BirdNET: A deep learning solution for avian diversity monitoring. Ecological Informatics 61, 101236 (2021).

    Google Scholar 

  46. Bas, Y., Bas, D. & Julien, J.-F. Tadarida: A Toolbox for Animal Detection on Acoustic Recordings. Journal of Open Research Software 5, (2017).

  47. A Ecologie. CrickIt. Google Play Store https://play.google.com/store/apps/details?id=com.aquilaecologie.sprinkenapp1 (2024).

  48. Rogers, A. Cicada Hunt. Apple App Store https://apps.apple.com/us/app/cicada-hunt/id648038025 (2018).

  49. Yu, D., Seltzer, M. L., Li, J., Huang, J.-T. & Seide, F. Feature Learning in Deep Neural Networks – Studies on Speech Recognition Tasks. Preprint at https://doi.org/10.48550/arXiv.1301.3605 (2013).

  50. Gong, Z., Zhong, P. & Hu, W. Diversity in Machine Learning. IEEE Access 7, 64323–64350 (2019).

    Google Scholar 

  51. Faiß, M. InsectSet47 & InsectSet66: Expanded datasets for automatic acoustic identification of insects (Orthoptera and Cicadidae). Zenodo, https://doi.org/10.5281/zenodo.8252141 (2023).

  52. Faiß, M., Ghani, B. & Stowell, D. A dataset of insect sounds from 459 species for bioacoustic machine learning. Scientific Data 13, 499 (2026).

  53. Hershey, S. et al. The Benefit of Temporally-Strong Labels in Audio Event Classification. in ICASSP 2021 – 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 366–370 (2021).

  54. Otálora, S., Marini, N., Müller, H. & Atzori, M. Combining weakly and strongly supervised learning improves strong supervision in Gleason pattern classification. BMC Medical Imaging 21, 77 (2021).

    Google Scholar 

  55. Das, A., Xian, Y., He, Y., Akata, Z. & Schiele, B. Urban Scene Semantic Segmentation with Low-Cost Coarse Annotation. in 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 5967–5976 (2023).

  56. GBIF.org (11 February 2026) GBIF Occurrence Download https://doi.org/10.15468/dl.7e9p5e (2026).

  57. Hill, A. P. et al. AudioMoth: Evaluation of a smart open acoustic device for monitoring biodiversity and the environment. Methods in Ecology and Evolution 9, 1199–1211 (2018).

    Google Scholar 

  58. Cigliano, M. M., Braun, H., Eades, D.C., Otte, D. Orthoptera Species File Version 5.0/5.0. http://Orthoptera.SpeciesFile.org (2025).

  59. Barataud, J. Identification acoustique des espèces françaises du genre Rhacocleis Fieber 1853 (Orthoptera Tettigoniidae) – Mise à jour 2021 – Plume de Naturalistes 5: 77–100 (2021).

  60. Kong, Q., Cao, Y., Iqbal, T., Wang, Y. & Plumbley, M. PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition. Preprint at https://arxiv.org/abs/1912.10211 (2019).

  61. Gemmeke, J. F. et al. Audio Set: An ontology and human-labeled dataset for audio events. in 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 776–780 (2017).

  62. Funosas, D. ECOSoundSet: a finely annotated dataset for the automated acoustic identification of Orthoptera and Cicadidae in North, Central and temperate Western Europe. Zenodo. https://doi.org/10.5281/zenodo.15043892 (2026).

    Google Scholar 

  63. GBIF.org (05 August 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.xjfeaq (2025).

  64. IUCN. The IUCN Red List of Threatened Species. https://www.iucnredlist.org (2016).

Download references

Acknowledgements

We declare having received funding from the Psi-Biom project (French PIA 3 under grant number 2182D0406-A), from the French National Program (ANR) “Investment for Future-Excellency Equipment” (project TERRA FORMA, with the reference ANR-21-ESRE-0014), from LabEx Tulip and from coauthor MC’s discretionary funding from his Junior Professor Chair position Neo Sensation (ANR-23-CPJ1-0174-01). Acoustic research by coauthor TT was conducted as part of the program “Communities, relationships, and communication in ecosystems” (No. P1-0255), funded by the Slovenian Research and Innovation Agency, and part of the acoustic research by coauthors EM and DF was conducted as part of the SpatialTreeP project funded by French ANR (ANR-21-CE03-0002). We are deeply grateful to Roy Kleukers, Mathieu Pélissié, Jakub Burdzicki, Margaux Charra, Adrien Charbonneau, Daniel Espejo Fraga, Joss Deffarges, Lukasz Cudziło, Daniel Bizet, Ghislain Riou, Marta Celej, Marie-Lilith Patou, Blandine Carre, Antoine Chabrolle, Joan Ventura Linares, Marc Corail, Matija Gogala, Mathieu Sannier, Vincent Milaret, Alexis Laforge, Pere Pons, Joan Estrada Bonell, Florence Matutini, Benjamin Drillat, Berenger Remy, Adeline Pichard, Evgenia Kovalyova, Laura Martin, Remi Jullian, Alexandre Crégu, Aurélie Torres, Christian Kerbiriou, Marlene Massouh, Nicolas Mokuenko, Jérome Allain, Romain Riols, Varvara Vedenina, Benoit Nabholz, Carlos Álvarez-Cros, Elouan Meyniel, Gaëtan Jouvenez, Georges Bedrines, Nicolas Vissyrias, Celine Quelennec, Clement Lemarchand, Clementine Azam, Eric Sardet, Klaus Alix, Rafael Tamajón, Sylvain Grimaud, Julien Cavallo, Leslie Campourcy, Sébastien Merle, Tamás Kiss, Xavier Béjar, Aurélien Grimaud, Fabien Sane, Jocelyn Fonderflick, Justine Przybilski, Marc Anton, Thomas Armand, Cédric Mroczko, Philippe Gayet, Antone Thivolle, Stanislas Wroza and Werner Reitmeier, who granted us permission to incorporate their recordings into our dataset (Supplementary Table 2). We also want to thank Johanna Berger, Maren Teschauer, Benjamin Schmid, Orian Ly, Lutèce Mezzetta, Mathilde Lladó, Eva Blot and Léa Geng for their collaboration in the annotation of recordings, Alexander Teschke and Markus Rubenbauer for their help with maintaining recording sites, Thierry Feuillet for facilitating the collection of mountain orthopteran recordings through the SpatialTreeP project, and the www.ornitho.cat and sonotheque.mnhn.fr (from Muséum National d’Histoire Naturelle) platforms for facilitating the access to some of the recordings in our dataset.

Author information

Authors and Affiliations

  1. Station d’Écologie Théorique et Expérimentale (SETE, CNRS), Moulis, France

    David Funosas, Jose M. Montoya & Maxime Cauchoix

  2. Université Paul Sabatier – Toulouse III, UPS, Toulouse, France

    David Funosas & Elodie Massol

  3. Centre de Recherche sur la Biodiversité et l’Environnement – UMR 5300 CNRS-INPT-IRD-UT, Toulouse, France

    David Funosas, Elodie Massol & Laurent Pelozuelo

  4. Centre d’Ecologie et des Sciences de la Conservation (CESCO, MNHN), Centre National de la Recherche Scientifique, Sorbonne Université, Paris, France

    Yves Bas

  5. PatriNat (OFB, MNHN), 75005, Paris, France

    Yves Bas

  6. University of Freiburg, Faculty of Biology, Geobotany, Schaenzlestr. 1, D-79104, Freiburg, Germany

    Svenja Schmidt, Dominik Arend, Sandra Mueller & Björn Schuller

  7. Kiel University, Institute of Natural Resource Conservation, Landscape Ecology, Olshausenstr. 75, 24118, Kiel, Germany

    David Bennett

  8. Brandenburgische Technische Universität Cottbus – Senftenburg, Fachgebiet Umweltplanung, Erich-Weinert-Str. 1, 03046, Cottbus, Germany

    David Bennett

  9. CHI – Chair of Health Informatics, MRI, Technical University of Munich, Munich, Germany

    Alexander Gebhard, Sebastian König & Andreas Triantafyllopoulos

  10. Dynafor, INRAE-INPT, University of Toulouse, Castanet-Tolosan, Toulouse, France

    Luc Barbaro

  11. Institució Catalana d’Història Natural (ICHN), Barcelona, Spain

    Rafael Carbonell Font

  12. Bestioles et Compagnie, Le village, 09240, Montseron, France

    David Sannier

  13. Nashvert Naturophonia, Val Maravel, France

    Fernand Deroussen

  14. Institut de Systématique, Evolution, Biodiversité (ISYEB), Muséum national d’Histoire Naturelle (MNHN), CNRS, Sorbonne Université, Ecole Pratique des Hautes Etudes – PSL, Université des Antilles, Paris, France

    Jérôme Sueur

  15. Slovenian Museum of Natural History (PMSL), Ljubljana, Slovenia

    Tomi Trilar

  16. Department of Ornithology, Max Planck Institute for Biological Intelligence, Seewiesen, Germany

    Wolfgang Forstmeier

  17. INRAE, Université de Bordeaux, BIOGECO, Pessac, France

    Lucas Roger

  18. Plante & Cité, Angers, France

    Lucas Roger

  19. Museu de Ciències Naturals de Barcelona (MCNB), Barcelona, Spain

    Eloïsa Matheu

  20. Murowaniec 44, 38-455, Niżna Łąka, Poland

    Piotr Guzik

  21. 117 rue Jean Carou – 19330 Chanteix, Paris, France

    Julien Barataud

  22. Muséum d’Histoire Naturelle, Dijon, France

    Stéphane Puissant

  23. Group on Language, Audio, & Music (GLAM), Imperial College London, London, UK

    Björn Schuller

Authors

  1. David Funosas
    View author publications

    Search author on:PubMed Google Scholar

  2. Elodie Massol
    View author publications

    Search author on:PubMed Google Scholar

  3. Yves Bas
    View author publications

    Search author on:PubMed Google Scholar

  4. Svenja Schmidt
    View author publications

    Search author on:PubMed Google Scholar

  5. David Bennett
    View author publications

    Search author on:PubMed Google Scholar

  6. Dominik Arend
    View author publications

    Search author on:PubMed Google Scholar

  7. Alexander Gebhard
    View author publications

    Search author on:PubMed Google Scholar

  8. Luc Barbaro
    View author publications

    Search author on:PubMed Google Scholar

  9. Sebastian König
    View author publications

    Search author on:PubMed Google Scholar

  10. Rafael Carbonell Font
    View author publications

    Search author on:PubMed Google Scholar

  11. David Sannier
    View author publications

    Search author on:PubMed Google Scholar

  12. Fernand Deroussen
    View author publications

    Search author on:PubMed Google Scholar

  13. Jérôme Sueur
    View author publications

    Search author on:PubMed Google Scholar

  14. Tomi Trilar
    View author publications

    Search author on:PubMed Google Scholar

  15. Wolfgang Forstmeier
    View author publications

    Search author on:PubMed Google Scholar

  16. Lucas Roger
    View author publications

    Search author on:PubMed Google Scholar

  17. Eloïsa Matheu
    View author publications

    Search author on:PubMed Google Scholar

  18. Piotr Guzik
    View author publications

    Search author on:PubMed Google Scholar

  19. Julien Barataud
    View author publications

    Search author on:PubMed Google Scholar

  20. Laurent Pelozuelo
    View author publications

    Search author on:PubMed Google Scholar

  21. Stéphane Puissant
    View author publications

    Search author on:PubMed Google Scholar

  22. Sandra Mueller
    View author publications

    Search author on:PubMed Google Scholar

  23. Björn Schuller
    View author publications

    Search author on:PubMed Google Scholar

  24. Jose M. Montoya
    View author publications

    Search author on:PubMed Google Scholar

  25. Andreas Triantafyllopoulos
    View author publications

    Search author on:PubMed Google Scholar

  26. Maxime Cauchoix
    View author publications

    Search author on:PubMed Google Scholar

Contributions

David Funosas: Writing – original draft, Visualization, Software, Methodology, Investigation, Formal analysis, Data curation. Elodie Massol: Writing – Review & Editing, Methodology, Investigation, Data curation. Yves Bas: Writing – Review & Editing, Investigation, Data curation. Svenja Schmidt: Writing – Review & Editing, Investigation, Data curation. David Bennett: Investigation, Data curation. Dominik Arend: Writing – Review & Editing, Investigation, Data curation. Alexander Gebhard: Writing – Review & Editing, Software, Validation. Luc Barbaro: Writing – Review & Editing. Sebastian König: Investigation, Data curation. Rafael Carbonell Font: Investigation, Data curation. David Sannier: Investigation, Data curation. Fernand Deroussen: Investigation, Data curation. Jérôme Sueur: Investigation, Data curation. Tomi Trilar: Investigation, Data curation. Wolfgang Forstmeier: Investigation, Data curation. Lucas Roger: Investigation, Data curation. Eloïsa Matheu: Investigation, Data curation. Piotr Guzik: Investigation, Data curation. Julien Barataud: Investigation, Data curation. Laurent Pelozuelo: Investigation, Data curation. Stéphane Puissant: Investigation, Data curation. Sandra Mueller: Writing – Review & Editing. Björn Schuller: Writing – Review & Editing. José Montoya: Writing – Review & Editing. Andreas Triantafyllopoulos: Software. Maxime Cauchoix: Writing – Review & Editing, Validation, Supervision, Resources, Project Administration, Methodology, Funding Acquisition, Conceptualization.

Corresponding author

Correspondence to
David Funosas.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary information (download DOCX )

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Cite this article

Funosas, D., Massol, E., Bas, Y. et al. A finely annotated dataset for the automated acoustic identification of European Orthoptera and Cicadidae.
Sci Data (2026). https://doi.org/10.1038/s41597-026-07150-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41597-026-07150-1

Source: Ecology - nature.com

Lignocellulose-mediated selection of potential halophilic PET-degrading enzymes from mangrove soil

Behavioral heterogeneity in host seeking and post-feeding suppression among disease vector mosquitoes

This portal is not a newspaper as it is updated without periodicity. It cannot be considered an editorial product pursuant to law n. 62 of 7.03.2001. The author of the portal is not responsible for the content of comments to posts, the content of the linked sites. Some texts or images included in this portal are taken from the internet and, therefore, considered to be in the public domain; if their publication is violated, the copyright will be promptly communicated via e-mail. They will be immediately removed.

Back to Top
Close