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Traditional visual surveys often miss broader effects on soundscape conditions. This study applies Passive Acoustic Monitoring in Seychelles to compare a restoration site with healthy and degraded reference reefs using manual detection of fish sounds and machine learning via Uniform Manifold Approximation and Projection. Results differ by method and indicate recovery is recovery-time and soundscape-scale dependent.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/coral-restoration-alters-reef-soundscapes-but-machine-learning-and-manual-analyses-suggest-different-recovery-rates-research-article/291142/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/coral-restoration-alters-reef-soundscapes-but-machine-learning-and-manual-analyses-suggest-different-recovery-rates-research-article/291142.png","ImageObject",300,407,{"name":92,"@type":93},"Theodora","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-17","2026-09-17",true,{"@type":102,"interactionType":103,"userInteractionCount":44},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What monitoring challenge does the study target in coral restoration projects?","Question",{"text":112,"@type":113},"Traditional visual surveys may not capture the full impact of restoration on reef function, especially aspects reflected in the soundscape.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How did the researchers assess changes in reef soundscapes?",{"text":117,"@type":113},"They used Passive Acoustic Monitoring and analyzed recordings with two approaches: manual detection of fish sounds and a machine learning method using Uniform Manifold Approximation and Projection.",{"name":119,"@type":110,"acceptedAnswer":120},"What did the study find about recovery after coral restoration?",{"text":121,"@type":113},"The recovery signals differed by analysis method: manual analysis emphasized similarity in fish calls between restoration and healthy reefs, while machine learning identified broader soundscape patterns clustering the restoration site with degraded references.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},291142,1789643548,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":44,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":129,"read_time":144,"preview_page_count":4},687197207919,"https://ap-avatar.wpscdn.com/avatar/a000253d6f5f7c60be?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779446848396160552","OPEN ACCESS  \nCitation: Croasdale EM, Saponari L, Dale C, Shah N, Williams B, Lamont TAC (2026) Coral restoration alters reef soundscapes but machine learning and manual analyses suggest different recovery rates. PLoS One 21(5): e0347307. [https://doi.org/10.1371/journal](https://doi.org/10.1371/journal). pone.0347307  \nEditor: Parviz Tavakoli-Kolour, University of the Ryukyus, JAPAN  \nReceived: May 14, 2025  \nAccepted: March 31, 2026  \nPublished: May 27, 2026  \nPeer Review History: PLOS recognizes the benefits of transparency in the peer review process; therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. The editorial history of this article is available here: [https://doi.org/10.1371/journal](https://doi.org/10.1371/journal). pone.0347307  \nCopyright: © 2026 Croasdale et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution,  \nRESEARCH ARTICLE  \nCoral restoration alters reef soundscapes but machine learning and manual analyses suggest different recovery rates  \nEmily Maria Croasdale1,2*, Luca Saponari3, Charlotte Dale3, Nirmal Shah3, Ben Williams4,5, Timothy A. C. Lamont6*  \n1 Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The Netherlands, 2 MARE, Laboratorio Maritimo da Guia, Faculdade de Ciencias da Universidade de Lisboa, Cascais, Portugal, 3 Nature Seychelles, The Centre for Environment & Education Roche Caiman, Mahe, Republic of Seychelles, 4 Division of Biosciences, University College London, London, United Kingdom, 5 Zoological Society of London, London, United Kingdom, 6 Lancaster Environment Centre, University of Lancaster, Lancaster, United Kingdom  \n* [emcroasdale@fc.ul.pt](emcroasdale@fc.ul.pt) (EMC); [tim.lamont@lancaster.ac.uk](tim.lamont@lancaster.ac.uk) (TL)  \nAbstract  \nCoral restoration is recognised as a critical tool to mitigate pantropical degradation of reef ecosystems. Robust monitoring of restoration progress is crucial for projects to evaluate their success, improve practice, and share knowledge. However, traditional visual surveys often fail to capture the full impact of coral restoration on reef function. Therefore, we employed Passive Acoustic Monitoring (PAM) to assess whether the soundscape of a coral restoration site in the Seychelles differs from adjacent healthy and degraded reference reefs. We applied two methods of soundscape analysis: manual detection of unidentified fish sounds; and machine learning-based Uniform Manifold Approximation and Projection analysis. Results were approach-specific: the manual approach highlighted similarities in fish calls between the restoration site and the healthy reference reef, while the machine learning approach extracted broader soundscape patterns, clustering the restoration site alongside the degraded reference reef. Although this is a single-site study, these findings suggest that a) coral restoration alters reef soundscapes, though recovery time may be taxon-specific, and b) multiple metrics are needed to bridge single-taxon and broad soundscape scales. This study contributes to the evolving field of soundscape ecology in coral reef ecosystems, highlighting the utility of PAM in monitoring changes to reef function through coral restoration.  \nIntroduction  \nOver the past decade, coral restoration efforts around the world have dramatically increased as part of an attempt to mitigate global degradation of reef habitat [ 1] . Despite increased effort to restore coral ecosystems, very few programmes have  \nPLOS One | [https://doi.org/10.1371/journal.pone.0347307](https://doi.org/10.1371/journal.pone.0347307) May 27, 2026 1 / 13  \nand reproduction in any medium, provided the original author and source are credited.  \nData availability statement: All relevant data for this study are publicly available from the Zenodo repository ([https://doi.","cbCaicqt2hFbWEYQ","https://ap.wps.com/l/cbCaicqt2hFbWEYQ","pdf",1366125,13,"English","# Abstract\n# Introduction\n## Monitoring challenges in coral restoration\n## Passive acoustic monitoring in coral reef ecology\n# Data availability statement\n# Funding and competing interests","[{\"question\":\"What monitoring challenge does the study target in coral restoration projects?\",\"answer\":\"Traditional visual surveys may not capture the full impact of restoration on reef function, especially aspects reflected in the soundscape.\"},{\"question\":\"How did the researchers assess changes in reef soundscapes?\",\"answer\":\"They used Passive Acoustic Monitoring and analyzed recordings with two approaches: manual detection of fish sounds and a machine learning method using Uniform Manifold Approximation and Projection.\"},{\"question\":\"What did the study find about recovery after coral restoration?\",\"answer\":\"The recovery signals differed by analysis method: manual analysis emphasized similarity in fish calls between restoration and healthy reefs, while machine learning identified broader soundscape patterns clustering the restoration site with degraded references.\"}]","Coral restoration alters reef soundscapes but machine learning and manual analyses suggest different recovery rates - research article | PDF",33]