Deciphering EcoFitness of Marine Ecosystems through eDNA Cross-trophic Interactions

Deciphering EcoFitness of Marine Ecosystems through eDNA Cross-trophic Interactions | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Deciphering EcoFitness of Marine Ecosystems through eDNA Cross-trophic Interactions Weiye Huang, Wanqing Tai, Xiaoming Shen, Matteo Convertino This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8750751/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 7 You are reading this latest preprint version Abstract Effective assessment of marine ecosystems increasingly requires approaches that go beyond static biodiversity indices to capture cross-trophic organization and dynamic stability based on network topology. In this study, we applied a multi-marker (12S, 18S, COI) eDNA metabarcoding approach to compare the ecological organization of two subtropical ecosystems, Mirs Bay and Daya Bay nearshore and marine habitats, representing contrasting environmental settings. Species co-occurrence networks were reconstructed to examine topological features such as degree distribution, modularity, centrality, and species-pair rank, and to relate those to ecological fitness. Two ecological allometric laws were then evaluated: (1) Taylor’s Power Law (TPL), which quantifies species aggregation; and (2) the Network Kleiber's Law (NKL) attributing relative species abundance (RSA) variance to network hyperconnectivity. Correlations among these ecological indicators and environmental factors were used to explore potential causal determinants of ecological organization. The two ecosystems exhibited strikingly different network architectures. Daya Bay supported higher biodiversity and a larger, more densely connected homogeneous network, while Mirs Bay showed lower diversity and richness but a more hierarchical and compartmentalized structure. TPL described both systems well ($R^2 >$ 0.86), with Mirs Bay showing stronger aggregation (nu=1.697) than Daya Bay (nu=1.460), and a more organized NKL pattern. The TPL exponent nu's sensitivity to several environmental is higher for more organized ecosystems, and increases with depth and average species biomass, suggesting its potential as a systemic ecofitness indicator of multitrophic organization. In contrast, no significant scaling relationship was found between RSA variance and network hyperconnectivity. Biological sciences/Ecology Earth and environmental sciences/Ecology Earth and environmental sciences/Environmental sciences EcoFitness Cross-trophic Networks Envirome Marine Ecosystems Allometry Taylor’s Law eDNA Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 18 May, 2026 Reviews received at journal 11 Mar, 2026 Reviewers agreed at journal 11 Feb, 2026 Reviewers invited by journal 11 Feb, 2026 Editor assigned by journal 06 Feb, 2026 Submission checks completed at journal 05 Feb, 2026 First submitted to journal 31 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8750751","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":589763142,"identity":"3f624c26-99ed-4d0d-b8fe-cc6ce2d6a608","order_by":0,"name":"Weiye Huang","email":"","orcid":"","institution":"Tsinghua University","correspondingAuthor":false,"prefix":"","firstName":"Weiye","middleName":"","lastName":"Huang","suffix":""},{"id":589763143,"identity":"31be60e6-23eb-4463-8b36-b633660f7055","order_by":1,"name":"Wanqing Tai","email":"","orcid":"","institution":"Tsinghua University","correspondingAuthor":false,"prefix":"","firstName":"Wanqing","middleName":"","lastName":"Tai","suffix":""},{"id":589763144,"identity":"4598e6f0-ee37-44e1-b148-ac553b4cdfc2","order_by":2,"name":"Xiaoming Shen","email":"","orcid":"","institution":"Shenzhen Dapeng Peninsula Marine Library","correspondingAuthor":false,"prefix":"","firstName":"Xiaoming","middleName":"","lastName":"Shen","suffix":""},{"id":589763145,"identity":"f0367b5b-42c3-483e-883c-f1176025405c","order_by":3,"name":"Matteo Convertino","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCklEQVRIiWNgGAWjYPACGwiVAEZAwINXNTNjAwNDGohBmpbDEC0MxGjRbT9//MGHivP28g38hz883FGbZ3D8AOODt20M8uY4tJidSWZsnHHmdmJjAzObROKZ48UGZxKYDee2MRjubMCh5UAyYzNv2+0EZgZmNobEtmOJGw4ksEnztjEkGBzAoeX8Y8bmv23n7NkYmJk/gLWcf8D+G6+WG0BbGNsOMPYAvS+R2FaTuOFGAhszfi2PDWf2nElOnMHMbAbUciBx5o2HzZJzzkkYbsDpsMQHH35U2NnLtzc+/vizrS6x73zywQ9vymzkcdmCAJBoAUUQKKIYJAiph4M6olWOglEwCkbByAEAuMdgPVRpYSsAAAAASUVORK5CYII=","orcid":"","institution":"Tsinghua University","correspondingAuthor":true,"prefix":"","firstName":"Matteo","middleName":"","lastName":"Convertino","suffix":""}],"badges":[],"createdAt":"2026-01-31 14:53:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8750751/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8750751/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102963554,"identity":"19833bf0-078b-4203-880a-085a4a869fca","added_by":"auto","created_at":"2026-02-19 04:18:59","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":28317014,"visible":true,"origin":"","legend":"","description":"","filename":"eDNApaperConvertino.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8750751/v1_covered_a335f736-76a8-49ec-bc81-c9fc8d5c7e1e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eDeciphering EcoFitness of Marine Ecosystems through eDNA Cross-trophic Interactions\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-biodiversity","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"npjbiodivers","sideBox":"Learn more about [npj Biodiversity](https://www.nature.com/npjbiodivers/)","snPcode":"44185","submissionUrl":"https://mts-npjbiodivers.nature.com/cgi-bin/main.plex","title":"npj Biodiversity","twitterHandle":"@npjbiodiversity","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"npj","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"EcoFitness, Cross-trophic Networks, Envirome, Marine Ecosystems, Allometry, Taylor’s Law, eDNA","lastPublishedDoi":"10.21203/rs.3.rs-8750751/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8750751/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEffective assessment of marine ecosystems increasingly requires approaches that go beyond static biodiversity indices to capture cross-trophic organization and dynamic stability based on network topology. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn this study, we applied a multi-marker (12S, 18S, COI) eDNA metabarcoding approach to compare the ecological organization of two subtropical ecosystems, Mirs Bay and Daya Bay nearshore and marine habitats, representing contrasting environmental settings. 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