Philippa Kaur

AbstractAcid stress is a central environmental factor shaping the structure and function of microbial communities worldwide. However, there is a lack of predictive understanding of how microbial communities respond physiologically and metabolically to acid stress. Here, we find that higher acid stress favors slower-growing species, promoting population growth and coexistence. Our experiments show that acid stress influences the spatial structure of communities, wherein coexistence is ordered over centimeter-length scales and determined by growth-tolerance trade-offs. We find that interspecific interactions are highly dynamic during acid stress changes, with shifts from competition to cooperation, enhancing resilience under high-stress intensities. Slower-growing species may bolster interspecific coexistence through stress-dependent excretion and cross-feeding of public goods. We construct a resource-consumer-based mathematical model to unravel the processes experienced by species in stress-induced coexistence and their distinct physiological states. Finally, our pairwise bacterial-fungal interaction experiments elucidate universalities in stress-induced coexistence between closely related and phylogenetically distant species with complementary phenotypic profiles. Overall, our work provides insights into how acid stress affects physiological and metabolic responses, as well as overall fitness, resilience, and coexistence.

Data availability

All data that support the findings of this study are provided in the Supplementary Information, Source Data file, and databases. Raw mass spectral data is deposited to MassIVE and accessible with the accession code MSV000099939. Source data are provided with this paper, and can also be found at https://doi.org/10.5281/zenodo.1732030972. Source data are provided as a Source Data file. Source data are provided with this paper.
Code availability

Based on the mathematical model provided in the Supplementary Notes, the code can be found at https://zenodo.org/records/17330958.
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Xiaole Xia.Ethics declarations

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Nature Communications thanks Wenping Cui, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

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Reprints and permissionsAbout this articleCite this articleLiao, H., Wu, L., Luo, Y. et al. Slower-growing species promote interspecific cooperation and coexistence under acid stress through cross-feeding.
Nat Commun (2025). https://doi.org/10.1038/s41467-025-67395-zDownload citationReceived: 02 August 2024Accepted: 28 November 2025Published: 14 December 2025DOI: https://doi.org/10.1038/s41467-025-67395-zShare this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy shareable link to clipboard
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AbstractTitan triggerfish (Balistoides viridescens) are among the most territorial reef fishes, known for aggressively defending nests from intruders. In the Maldives’ Fuvahmulah atoll, where tiger sharks (Galeocerdo cuvier) aggregate in high numbers year-round, we opportunistically documented 10 interactions between these species from February to August 2024 during daily diving operations. Video footage from experienced divers was analyzed to identify and categorize aggressive behaviors, defined as bites (rapid, forceful closure of the jaws on the shark’s body) and chases (short pursuits following an aggressive display). All observed aggression was initiated by titan triggerfish, most often targeting the caudal fin of individual tiger sharks. Biting accounted for 70% of interactions, with chases comprising the remainder; over half of bites were immediately followed by a chase. Several interactions occurred near the new moon, coinciding with the species’ nesting period, suggesting that many of these interactions may have been linked to breeding-season territoriality; however, the opportunistic nature of the observations precluded any formal analysis of lunar phase patterns. These behaviors likely function as risk-based defense, exploiting anatomical vulnerabilities to deter much larger predators. The high frequency of these interactions in a location with artificially dense tiger shark populations suggests that provisioning and predator aggregation may increase the likelihood of such cross-trophic encounters. By linking detailed behavioral observations with the ecological context of predator aggregation, this study highlights the defensive capabilities of titan triggerfish and raises questions about how ecotourism-driven changes in predator distribution influence the behavior of non-target reef species.

Data availability

Data and data sets are available from the corresponding author upon reasonable request.
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Download referencesAcknowledgementsWe want to extend our sincere gratitude to the individuals who contributed to this study by providing valuable video footage of interactions between titan triggerfish and tiger sharks. This study could not have been completed without the support of Fuvahmulah Dive School and Pelagic Divers Fuvahmulah, and the authors are grateful for their assistance. The authors extend special thanks to Mathieu Noé, Anoos, Sadhar Suresh, Nikita Kornilov, and Ahmed Ashhal Abdulla for capturing and sharing the essential videos that formed the foundation of this research. Their efforts were crucial in documenting the behavioral dynamics observed in this study. We also thank Luca Asshauer and Max Kimble for their assistance with the artistic figures included in this manuscript. Additionally, we thank Gonzalo Araujo for their insightful feedback during the analysis process. This research would not have been possible without the support and contributions of all those involved. The study was conducted following the guidelines and under the research permits issued by the Ministry of Fisheries, Marine Resources and Agriculture, Maldives (annually renewable permit: 30-D/PRIV/2021/190). The methods were non-invasive, ensuring no harm was caused to the animals involved.FundingThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.Author informationAuthor notesThese authors jointly supervised this work: Filippo Bocchi and Nathan Perisic.Authors and AffiliationsNature Friends of Maldives NGO, Fuvahmulah, MaldivesFilippo Bocchi & Ahmed InahFuvahmulah Dream NGO, Fuvahmulah, MaldivesNathan Perisic & Tatiana IvanovaAuthorsFilippo BocchiView author publicationsSearch author on:PubMed Google ScholarNathan PerisicView author publicationsSearch author on:PubMed Google ScholarAhmed InahView author publicationsSearch author on:PubMed Google ScholarTatiana IvanovaView author publicationsSearch author on:PubMed Google ScholarContributionsNathan Perisic and Filippo Bocchi were responsible for the analysis, manuscript writing, and review. Ahmed Inah and Tatiana Ivanova contributed to the study’s inception, preparation of the manuscript, and review.Corresponding authorCorrespondence to
Nathan Perisic.Ethics declarations

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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 permissionsAbout this articleCite this articleBocchi, F., Perisic, N., Inah, A. et al. Defensive responses of titan triggerfish to tiger sharks at a provisioned reef.
Sci Rep (2025). https://doi.org/10.1038/s41598-025-31560-7Download citationReceived: 19 August 2025Accepted: 03 December 2025Published: 14 December 2025DOI: https://doi.org/10.1038/s41598-025-31560-7Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy shareable link to clipboard
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KeywordsSpecies interactionIndian oceanSharksTropical ecologyTriggerfishSupplementary Material 1Supplementary Material 2Supplementary Material 3Supplementary Material 4Supplementary Material 5Supplementary Material 6Supplementary Material 7 More

AbstractBarriers can affect the movement, migratory patterns, and demographic rates of ungulates. Even in highly remote areas with relatively little development, like northwest Alaska, isolated roads can alter the movements of ungulates such as caribou (Rangifer tarandus). Here, a solitary, 80-km long industrial road connecting a large zinc and lead mine to a port affects caribou migrations. Using location and survival data from 366 GPS collared, adult female caribou representing > 850 caribou-years from 2010 to 2023, we assessed whether caribou whose fall movements were altered by the road experienced higher mortality risk compared to those whose movements were unaltered. Of the 101 caribou-years that came within 20 km of the road, 58% displayed altered movements. The survival rate of caribou whose movements were unaltered by the road was 20% higher than those caribou whose movements were altered by it, though difference was not significant (p > 0.05). Increased movements, delayed migration, and/or changes in habitat selection related to altered movements could still have energetic and demographic consequences. Caribou that crossed or circumvented the road had significantly higher survival rates (78.5% survived until calving) than caribou that did not cross or circumvent the road (i.e., it acted as an impermeable barrier and the caribou wintered north of it; 57.9%). Given our results, we posit that enhancing the permeability of roads could improve the survival of caribou in the region.

Data availability

Survival data used for this analysis will be made available in the NPS’ publicly-accessible database (IRMA; https://irma.nps.gov) upon manuscript acceptance.
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Download referencesAcknowledgementsWe thank A. Hansen (Alaska Department of Fish and Game) for his ongoing collaboration that makes our long-term monitoring program possible. We also thank the many people that have helped deploy GPS collars over the years. Funding for this project was provided by the National Park Service, the Alaska Department of Fish and Game, and NSF Navigating the New Arctic grant 212727 (Fate of the Caribou). We thank H. Johnson, A. Hansen, S. Karpovich, and N. Edmison for reviews of a previous draft of this manuscript.Author informationAuthors and AffiliationsArctic Inventory and Monitoring Program, National Park Service, Gates of the Arctic National Park and Preserve, Fairbanks, AK, USAKyle Joly & Matthew D. CameronCollege of Environmental Science and Forestry, State University of New York, Syracuse, NY, USAChloe Beaupré, Nicole Barbour & Eliezer GurarieThe Wilderness Society, Anchorage, AK, USATimothy J. FullmanAuthorsKyle JolyView author publicationsSearch author on:PubMed Google ScholarChloe BeaupréView author publicationsSearch author on:PubMed Google ScholarTimothy J. FullmanView author publicationsSearch author on:PubMed Google ScholarMatthew D. CameronView author publicationsSearch author on:PubMed Google ScholarNicole BarbourView author publicationsSearch author on:PubMed Google ScholarEliezer GurarieView author publicationsSearch author on:PubMed Google ScholarContributionsData acquisition: KJ and MDC. Data management: KJ, MDC, and CB. Conceptualization and data interpretation: all authors. Data Analysis: CB, EG, TJF, KJ, and MDC. Original draft: KJ. Manuscript review, revision, and submission approval: all authors.Corresponding authorCorrespondence to
Eliezer Gurarie.Ethics declarations

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Reprints and permissionsAbout this articleCite this articleJoly, K., Beaupré, C., Fullman, T.J. et al. Barrier impermeability is associated with migratory ungulate survival rates.
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KeywordsAlaskaCaribouMortality riskPermeabilityRangifer tarandusRoads More

AbstractMeasurement is essential for effective adaptation management and operation, and indicators and metrics (I&M) have a pivotal role. Surprisingly, systematic efforts to assess advances in the provision of adaptation I&M are scarce, and those that do exist often lack in-depth analysis of the types, characteristics, and applicability of the collected information. Here, we analyse 137 publications and 901 I&M sourced in the scientific literature (2007–2022) to measure adaptation to climate change in urban areas where governments are increasingly placing efforts to prepare populations and infrastructures. A lack of common terminology, standardisation, and guidelines has resulted in a field that is complex to track and understand. This complexity has led to a fragmented methodological landscape, marked by diverse, context-dependent, and occasionally conflicting approaches to the development of I&M. We argue that conventional approaches to I&M are largely inadequate and must better emphasise quantifiability, long-term assessment, and alignment with policy objectives.

Data availability

Data generated or analysed during this study are included in this published article (and its Supplementary Information) and online repositories. The information available through online repositories includes the dataset of publications and indicators and connected metadata, which can be found online at DOI [10.5281/zenodo.10663610] (https://doi.org/10.5281/zenodo.10663610).
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Turner, S., Moloney, S., Glover, A. & Fünfgeld, H. A Review of the Monitoring and Evaluation Literature for Climate Change Adaptation (RMIT University Centre for Urban Research, 2014).Download referencesAcknowledgementsMO, AM and WL have been funded by the European Union (ERC, IMAGINE adaptation, 101039429). Their research is also supported by the María de Maeztu Excellence Unit 2023-2027 Ref. CEX2021-001201-M, funded by MCIN/AEI/10.13039/501100011033; and by the Basque Government through the BERC 2022-2025 program. MO would like to acknowledge the support of the grant RYC2022-037585-I funded by MCIU/AEI/10.13039/501100011033 and ESF+. LG, AV and MO are members of the SAREN Research Group funded by the Basque Government IT1619-22 and AV is funded by UPV/EHU PIF 2020 grant. This work was originally conceived during discussions of the Cities Committee of the International Platform of Adaptation Metrics (IPAM), led by MO.Author informationAuthors and AffiliationsBasque Centre for Climate Change (BC3), Leioa, SpainMarta Olazabal, Andressa V. Mansur & William LewisIKERBASQUE, Basque Foundation for Science, Bilbao, SpainMarta OlazabalIndependent Researcher, New Delhi, IndiaSamraj SahayIndiana University, O’Neill School of Public and Environmental Affairs, Bloomington, IN, USALaura Helmke-LongUniversity Iuav of Venice, Department of Architecture and Arts, Venice, ItalyMassimiliano Granceri BradaschiaUniversity of the Basque Country (UPV/EHU), School of Engineering, Bilbao, SpainAne Villaverde & Leire GarmendiaNagoya University, Graduate School of Civil and Environmental Engineering, Nagoya, JapanPrince Dacosta AboagyeHiroshima University, The IDEC Institute & Network for Education and Research on Peace and Sustainability (NERPS), Hiroshima, JapanAyyoob SharifiSchool of Architecture and Design, Lebanese American University, Beirut, LebanonAyyoob SharifiIpsos Centre for Development Research and Evaluation, Ipsos, Accra, GhanaObed AsamoahKenyatta University, Department of Spatial and Environmental Planning, Nairobi, KenyaPatricia MwangiUniversity of the Basque Country (UPV/EHU), Bilbao, SpainBorja IzaolaBritish Red Cross, West Point House, Edinburgh, United KingdomEllie MurtaghAdaptation Leader, Washington, DC, USAIra FeldmanAuthorsMarta OlazabalView author publicationsSearch author on:PubMed Google ScholarAndressa V. MansurView author publicationsSearch author on:PubMed Google ScholarSamraj SahayView author publicationsSearch author on:PubMed Google ScholarLaura Helmke-LongView author publicationsSearch author on:PubMed Google ScholarMassimiliano Granceri BradaschiaView author publicationsSearch author on:PubMed Google ScholarAne VillaverdeView author publicationsSearch author on:PubMed Google ScholarLeire GarmendiaView author publicationsSearch author on:PubMed Google ScholarPrince Dacosta AboagyeView author publicationsSearch author on:PubMed Google ScholarAyyoob SharifiView author publicationsSearch author on:PubMed Google ScholarObed AsamoahView author publicationsSearch author on:PubMed Google ScholarPatricia MwangiView author publicationsSearch author on:PubMed Google ScholarWilliam LewisView author publicationsSearch author on:PubMed Google ScholarBorja IzaolaView author publicationsSearch author on:PubMed Google ScholarEllie MurtaghView author publicationsSearch author on:PubMed Google ScholarIra FeldmanView author publicationsSearch author on:PubMed Google ScholarContributionsM.O. Conceptualisation; methodology; data collection stage 1; Data collection stage 2; data curation; formal analysis; writing—original draft; writing—review and editing; visualisation; supervision; funding acquisition. A.M. Data collection stage 2; data curation; formal analysis; visualisation; writing—review and editing. S.S. Methodology; data collection stage 1; data collection stage 2; formal analysis; writing—review and editing; visualisation. L.H.L. Data collection stage 1; Data collection stage 2; formal analysis; writing—review and editing. M.G. Methodology; data collection stage 1; data collection stage 2; visualisation. A.V. Methodology; data collection stage 1; data collection stage 2; writing—review and editing. L.G. Methodology; data collection stage 1; data collection stage 2; writing—review and editing. P.D.A. Data collection stage 1; data collection stage 2; writing—review and editing. A.S. Data collection stage 1; data collection stage 2; writing—review and editing. O.A. Data collection stage 1; data collection stage 2. P.M. Data collection stage 2; writing—review and editing. W.L. Data curation; writing—review and editing. B.I. Data collection stage 1. E.M. Data collection stage 1. I.F. Data collection stage 2.Corresponding authorCorrespondence to
Marta Olazabal.Ethics declarations

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Reprints and permissionsAbout this articleCite this articleOlazabal, M., Mansur, A.V., Sahay, S. et al. Conventional approaches to indicators and metrics undermine urban climate adaptation.
npj Urban Sustain (2025). https://doi.org/10.1038/s42949-025-00310-zDownload citationReceived: 23 September 2025Accepted: 17 November 2025Published: 14 December 2025DOI: https://doi.org/10.1038/s42949-025-00310-zShare this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy shareable link to clipboard
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Abstract

Mucilage aggregation is a striking phenomenon in the northern Adriatic Sea, reappearing massively in surface waters on the Istrian coast in 2024 after 20 years. Formed through polymerization of exuded sugars during microphytoplankton blooms, mucilage events are hard to capture with traditional monitoring. Here, we used real-time in situ sensors, satellite data and daily pulse-shape flow cytometry to analyze phytoplankton dynamics during this event. Mucilage formation was linked to rising temperatures and Po River-induced salinity drops. Microphytoplankton species like Cerataulina pelagica, Cylindrotheca closterium, Thalassionema spp., and Gonyaulax fragilis showed as important taxa in each different phase of the phenomenon. Aggregates consisted mainly of single cells. Mucilage periods featured low diversity and thicker, more complex cells, unlike autumn blooms which showed higher diversity, chain-forming colonies, and more pigments. Our findings highlight the key role of microphytoplankton and single cells in mucilage dynamics and the influence of environmental factors like temperature, wind and freshwater inputs on phytoplankton structure and biomass in coastal ecosystems.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Wikner, J., Vikström, K. & Verma, A. Regulation of marine plankton respiration: A test of models. Front Mar. Sci 10–2023, (2023).Download referencesAcknowledgementsThis work was funded by the Croatian Science Foundation (HRZZ) Projects: Life Strategies of Phytoplankton in the Northern Adriatic (UIP-2014-09-6563) and Molecular Life Strategies of Phytoplankton in the Northern Adriatic ADRILife (UIP-2020-02-7868). Lana Grižančić is supported by the HRZZ project DOK-2021-02-5104.The study was also supported by the H2020 program project JERICO-S3 and the Interreg Italy-Croatia projects AdriaClim, Cascade, ALIENA, Marless and BRIGANTINE from the European Union regional development funds. We thank the crew of R/V Vila Velebita and R/V Burin for help during sampling.We are grateful to Denis Škalic and Victor Stinga Perusco for their assistance with data acquisition and sensor maintenance, and to Marija Fornažar for her expert advice on flow cytometry.Author informationAuthors and AffiliationsCenter for Marine Research, Ruđer Bošković Institute, Rovinj, CroatiaIvan Vlašiček, Daniela Marić Pfannkuchen, Mirta Smodlaka Tanković, Ana Baričević, Tjaša Kogovšek, Nataša Kužat, Mia Knjaz, Lana Grižančić, Ivan Podolšak, Ariana Turković & Martin PfannkuchenSeaCras, Zagreb, CroatiaRobert Šulc, Robert Kopal & Mario ŠpadinaAlgebra Bernays University, Zagreb, CroatiaRobert KopalAuthorsIvan VlašičekView author publicationsSearch author on:PubMed Google ScholarDaniela Marić PfannkuchenView author publicationsSearch author on:PubMed Google ScholarMirta Smodlaka TankovićView author publicationsSearch author on:PubMed Google ScholarAna BaričevićView author publicationsSearch author on:PubMed Google ScholarTjaša KogovšekView author publicationsSearch author on:PubMed Google ScholarNataša KužatView author publicationsSearch author on:PubMed Google ScholarMia KnjazView author publicationsSearch author on:PubMed Google ScholarLana GrižančićView author publicationsSearch author on:PubMed Google ScholarIvan PodolšakView author publicationsSearch author on:PubMed Google ScholarAriana TurkovićView author publicationsSearch author on:PubMed Google ScholarRobert ŠulcView author publicationsSearch author on:PubMed Google ScholarRobert KopalView author publicationsSearch author on:PubMed Google ScholarMario ŠpadinaView author publicationsSearch author on:PubMed Google ScholarMartin PfannkuchenView author publicationsSearch author on:PubMed Google ScholarContributionsI.V. designed the research, analysed samples and *in situ* data and discussed results. D.M.P. contributed to the research design, discussion and approved the manuscript. (M.S.T, A.B., T.K., N.K., M.K., L.G., I.P., and A.T.) contributed to the discussion and approved the manuscript. (R.Š., M.Š. and R.K.) contributed with analysis of satellite derived data and approved the manuscript. M.P. led the research team and helped in designing of the study and discussion of results.Corresponding authorCorrespondence to
Daniela Marić Pfannkuchen.Ethics declarations

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The authors declare no competing interests.

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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 permissionsAbout this articleCite this articleVlašiček, I., Pfannkuchen, D.M., Tanković, M.S. et al. High-frequency observations during Adriatic mucilage event reveal unique phytoplankton traits and diversity response.
Sci Rep (2025). https://doi.org/10.1038/s41598-025-31369-4Download citationReceived: 21 May 2025Accepted: 02 December 2025Published: 14 December 2025DOI: https://doi.org/10.1038/s41598-025-31369-4Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy shareable link to clipboard
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AbstractMarine algae underpin entire ocean ecosystems. Yet algae in culture poorly represent their large environmental diversity, and we have a limited understanding of their convoluted evolution by endosymbiosis. Here, we perform a phylogeny-guided plastid genome-resolved metagenomic survey of Tara Oceans expeditions. We present a curated resource of 660 new non-redundant plastid genomes of environmental marine algae, vastly expanding plastid genome diversity within major algal groups, including many without closely related reference genomes. Notably, we recover four plastid genomes, including one near-complete, forming a deep-branching plastid lineage of nano-size algae that we informally name leptophytes. This group is globally distributed and generally rare, although it can reach relatively high abundance in the Arctic. A near-complete mitochondrial genome showing strong co-occurrence with leptophyte plastids is also recovered and assigned to this group. Leptophytes encompass the enigmatic plastid group DPL2, one of the very few known plastid groups not clearly belonging to major algal groups and previously known only from 16S rDNA sequences. Comparative organellar genomics and phylogenomics indicate that leptophytes are sister to haptophytes, and raise the intriguing possibility that cryptophytes acquired their plastids from haptophytes. Collectively, our study demonstrates that metagenomics can reveal hidden organellar diversity, and improve models of plastid evolution.

Data availability

The 937 metagenomes from Tara Oceans used in the study are publicly available at the EBI under project PRJEB402. Data our study generated has been deposited in an online repository: https://doi.org/10.17044/scilifelab.2821217381. This link provides access to the individual FASTA files from each plastid and mitochondrial genome used in our study (including the 660 non-redundant ptMAGs and 34 mtMAGs), the co-assembly of the top six samples where Lepto-01 was most abundant, individual gene alignments, concatenated and trimmed alignments, and maximum-likelihood and Bayesian tree files for the phylogenomic dataset. Source Data for Fig. 4, Supplementary Figs. 10-12, and Supplementary Fig. 22 can be found on the linked GitHub repository, while source data for Supplementary Figs. 2-6 is provided as Supplementary Data 1.
Code availability

All scripts used for genome annotation and phylogenetic analyses are available on GitHub: https://github.com/burki-lab/ptMAGs with the identifier: 10.5281/zenodo.1763560482.
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Download referencesAcknowledgementsWe thank Shinichi Sunagawa for having facilitated the recovery of relevant data from the mOTU metagenomic database maintained by his research group at the Department of Biology at ETH Zürich. We thank A. Roger, H. Baños, and C. McCarthey for discussions, and for kindly providing custom scripts for running the phylogenetic models MEOW and GF-MIX. We thank J.E. Dharamshi for discussions about phylogenetic analyses. Our survey was made possible by the sampling and sequencing efforts of the Tara Oceans Project. Tara Oceans (which includes the Tara Oceans and Tara Oceans Polar Circle expeditions) would not exist without the leadership of the Tara Oceans Foundation and the continuous support of 23 institutes (https://oceans.taraexpeditions.org/). This article is contribution number 164 of Tara Oceans. Phylogenetic analyses were enabled by resources provided by the National Academic Infrastructure for Supercomputing in Sweden (NAISS 2024/5-197), partially funded by the Swedish Research Council through grant agreement no. 2022-06725. M.J. was supported by the Swedish Research Council (International Postdoc grant 2022-00351). FB’s research is supported by grants from the European Research Council (ERC consolidator grant 101044505), the Swedish Research Council VR (2021-04055), and Science for Life Laboratory. TD’s research is supported by a grant from the l’Agence Nationale de la Recherche (ANR-23-CE02-0022). We also thank the commitment of the CNRS and Genoscope/CEA. Some of the computations were performed using the platine, titane and curie HPC machine provided through GENCI grants (t2011076389, t2012076389, t2013036389, t2014036389, t2015036389 and t2016036389).FundingOpen access funding provided by Uppsala University.Author informationAuthor notesEric Pelletier & Tom O. DelmontPresent address: Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOsee, Paris, FranceAuthors and AffiliationsDepartment of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Uppsala, SwedenMahwash JamyDepartment of Organismal Biology, Program in Systematic Biology, Uppsala University, Uppsala, SwedenThomas Huber & Fabien BurkiGénomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, Evry, FranceThibault Antoine, Eric Pelletier & Tom O. DelmontResearch Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOsee, Paris, FranceThibault AntoineDepartment of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Zürich, SwitzerlandHans-Joachim RuscheweyhGlobal Health Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, SwitzerlandLucas PaoliAuthorsMahwash JamyView author publicationsSearch author on:PubMed Google ScholarThomas HuberView author publicationsSearch author on:PubMed Google ScholarThibault AntoineView author publicationsSearch author on:PubMed Google ScholarHans-Joachim RuscheweyhView author publicationsSearch author on:PubMed Google ScholarLucas PaoliView author publicationsSearch author on:PubMed Google ScholarEric PelletierView author publicationsSearch author on:PubMed Google ScholarTom O. DelmontView author publicationsSearch author on:PubMed Google ScholarFabien BurkiView author publicationsSearch author on:PubMed Google ScholarContributionsF.B. and T.O.D. conceived the project. T.O.D. characterised the ptMAGs. M.J., F.B. and T.H., performed phylogenetic analyses. T.A., E.P. and T.O.D. created the plastid genomic database and performed surveys for nucleomorphs. H.J.R. and L.P. retrieved relevant data from mOTUs. M.J. and T.H. annotated the ptMAGs, and E.P. performed mapping analyses. F.B., M.J., and T.O.D. wrote the manuscript with input from all the authors.Corresponding authorsCorrespondence to
Tom O. Delmont or Fabien Burki.Ethics declarations

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Reprints and permissionsAbout this articleCite this articleJamy, M., Huber, T., Antoine, T. et al. Identification of a deep-branching lineage of algae using environmental plastid genomes.
Nat Commun (2025). https://doi.org/10.1038/s41467-025-67401-4Download citationReceived: 06 February 2025Accepted: 28 November 2025Published: 14 December 2025DOI: https://doi.org/10.1038/s41467-025-67401-4Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy shareable link to clipboard
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AbstractThe role of soil microorganisms in supporting multiple ecosystem functions (multifunctionality) remains poorly understood across diverse environmental conditions. Here, we investigate 484 soils from 27 European countries spanning a range of climatic and edaphic contexts. We assess the contribution of climate, soil properties, and soil microbiome traits (i.e., the relative abundance of co-occurring taxa) to explain six key functional proxies related to soil structure, biochemical activity, and productivity. We find the highest multifunctionality values in grasslands, woodlands, loamy and acidic soils, and temperate humid regions, and the lowest in croplands, alkaline soils, and drier regions. Soil properties explain 12–31% of variation in multifunctionality, with microbial biomass and nitrogen content emerging as the strongest predictors. The soil microbiome accounts for 2–14% of unique variance in multifunctionality but explains more than 25% of variation in enzymatic activities and primary productivity in clay-rich soils and soils originating from temperate dry regions. Specific taxa, particularly within Actinobacteria, Acidobacteria, and the fungal genus Mortierella consistently emerge as strong predictors of ecosystem multifunctionality. Our findings highlight that ecosystem multifunctionality is jointly shaped by soil properties and microbial communities. We argue that specific taxa hold potential as context-dependent indicators for multifunctionality monitoring across environmental gradients.

Data availability

The data that supports the findings of this study are freely available in figshare with the identifier https://doi.org/10.6084/m9.figshare.28645625. Raw DNA sequences can be accessed through the European Soil Data Centre (ESDAC) portal: https://esdac.jrc.ec.europa.eu/content/soil-biodiversity-dna-bacteria-and-fungi. The raw data (DNA sequences) generated in this study have been deposited in the Sequence Read Archive (SRA) database under BioProject ID PRJNA952168. Detailed information on the taxonomic composition of bacterial and fungal modules is available as Supplementary Dataset 1. Detailed information on Structural Equation Models (SEMs) results is availabel as Supplementary Dataset 2.
Code availability

Code used to perform all analyses described in this study is freely available at https://github.com/fromerob/Multifunctionality.git.
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Download referencesAcknowledgementsF.R. acknowledges funding from the Novo Nordisk Foundation through a Postdoctoral fellowship (grant reference number NNF24OC0094454). The LUCAS Survey is coordinated by Unit E4 of the Statistical Office of the European Union (EUROSTAT). The LUCAS Soil sample collection is supported by the Directorate-General Environment (DG-ENV), Directorate-General Agriculture and Rural Development (DG-AGRI) and Directorate-General Climate Action (DG-CLIMA) of the European Commission. M.D-B. acknowledges support from the Spanish Ministry of Science and Innovation for the I  +  D  + I project PID2020-115813RA-I00 funded by MCIN/AEI/10.13039/501100011033. M.v.d.H and F.R. acknowledge funding from the Swiss National Science Foundation (Switzerland) through grant no. 310030–188799 and from the European Union Horizon 2020 research and innovation program under grant agreement no. 862695 EJP SOIL-MINOTAUR.Author informationAuthors and AffiliationsPlant-Soil Interactions group, Agroscope, Zurich, SwitzerlandFerran Romero, Ido Rog & Marcel G. A. van der HeijdenDepartment of Plant and Microbial Biology, University of Zurich, Zurich, SwitzerlandFerran Romero, Ido Rog & Marcel G. A. van der HeijdenDepartment of Agroecology, Aarhus University, Slagelse, DenmarkFerran Romero & Mohammad BahramEuropean Commission, Joint Research Centre Ispra (JRC), Ispra, ItalyMaëva Labouyrie, Cristiano Ballabio, Panos Panagos & Arwyn JonesEuropean Dynamics, Brussels, BelgiumAlberto OrgiazziMycology and Microbiology Center, University of Tartu, Tartu, EstoniaLeho TedersooDepartment of Botany, Institute of Ecology and Earth Sciences, University of Tartu, Tartu, EstoniaMohammad BahramDepartment of Ecology, Swedish University of Agricultural Sciences, Uppsala, SwedenMohammad BahramGerman Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, GermanyNico Eisenhauer, Marie Sünnemann & Carlos A. GuerraInstitute of Biology, Leipzig University, Leipzig, GermanyNico Eisenhauer & Marie SünnemannDepartment of Geography, University of Coimbra, Coimbra, PortugalCarlos A. GuerraLaboratorio de Biodiversidad y Funcionamiento Ecosistémico, Instituto de Recursos Naturales y Agrobiología de Sevilla (IRNAS), Consejo Superior de Investigaciones Científicas (CSIC), Sevilla, SpainDongxue Tao & Manuel Delgado-BaquerizoSchool of Ecology, Sun Yat-Sen University, Shenzhen, ChinaDongxue TaoState Key Laboratory for Crop Stress Resistance and High-Efficiency Production, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, ChinaShuo JiaoConsiglio per la ricerca in agricoltura e l’analisi dell’economia agraria – Centro di Ricerca Agricoltura e Ambiente (CREA-AA), Firenze, ItalyStefano MocaliFreie Universität Berlin, Institute of Biology, Berlin, GermanyMatthias C. Rillig & Anika LehmannAuthorsFerran RomeroView author publicationsSearch author on:PubMed Google ScholarMaëva LabouyrieView author publicationsSearch author on:PubMed Google ScholarAlberto OrgiazziView author publicationsSearch author on:PubMed Google ScholarCristiano BallabioView author publicationsSearch author on:PubMed Google ScholarPanos PanagosView author publicationsSearch author on:PubMed Google ScholarArwyn JonesView author publicationsSearch author on:PubMed Google ScholarLeho TedersooView author publicationsSearch author on:PubMed Google ScholarMohammad BahramView author publicationsSearch author on:PubMed Google ScholarNico EisenhauerView author publicationsSearch author on:PubMed Google ScholarMarie SünnemannView author publicationsSearch author on:PubMed Google ScholarCarlos A. GuerraView author publicationsSearch author on:PubMed Google ScholarDongxue TaoView author publicationsSearch author on:PubMed Google ScholarIdo RogView author publicationsSearch author on:PubMed Google ScholarShuo JiaoView author publicationsSearch author on:PubMed Google ScholarStefano MocaliView author publicationsSearch author on:PubMed Google ScholarMatthias C. RilligView author publicationsSearch author on:PubMed Google ScholarAnika LehmannView author publicationsSearch author on:PubMed Google ScholarManuel Delgado-BaquerizoView author publicationsSearch author on:PubMed Google ScholarMarcel G. A. van der HeijdenView author publicationsSearch author on:PubMed Google ScholarContributionsF.R. contributed to conceptualization, methodology, formal analysis, investigation, data curation, writing – original draft, writing – review & editing, and visualization. M.L. contributed to conceptualization, methodology, formal analysis, investigation, writing – review & editing, and data curation. A.O. contributed to conceptualization, methodology, resources, writing – review & editing, and data curation. C.B. contributed to methodology and resources. P.P. contributed to conceptualization, methodology, resources, writing – review & editing, project administration, and data curation. A.J. contributed to conceptualization, methodology, resources, writing – review & editing, project administration, and data curation. L.T. and M.B. contributed to resources, writing – review & editing, and data curation. N.E., M.S., and C.A.G. contributed to resources and writing – review & editing. D.T. contributed to methodology. I.R. and S.J. contributed to writing – review & editing. S.M. contributed to project administration and funding acquisition. M.C.R. and A.L. contributed to resources and writing – review & editing. M.D.B. contributed to writing – review & editing. M.v.d.H. contributed to conceptualization, methodology, resources, writing – original draft, writing – review & editing, supervision, project administration, and funding acquisition.Corresponding authorsCorrespondence to
Ferran Romero or Marcel G. A. van der Heijden.Ethics declarations

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AbstractThe universality of the allometric model for describing the length–weight relationship in marine species has been questioned, particularly for some invertebrates such as sea urchins, clams, and barnacles. In such cases, nonparametric regression models may offer improved flexibility and capture specific patterns-such as inflection points in growth curves-not identified by standard parametric models. These features can support the identification of biologically meaningful thresholds relevant to fisheries, including size-dependent yield. Nonparametric quantile regression further enhances inference by characterizing variability across the entire distribution of body condition. Here, we assess the comparative performance of parametric and nonparametric regression models for the Atlantic surfclam, Spisula solidissima, using data collected from three regions along the U.S. Atlantic coast (Virginia, Delaware/Maryland, and New Jersey). First, we compare two mean regression approaches —a classic allometric model and a kernel-based nonparametric alternative— using a bootstrap-based procedure. Second, we apply quantile regression to both parametric and nonparametric frameworks to investigate size-dependent variation in growth patterns. Model selection for mean regressions was based on a hypothesis test contrasting the allometric model versus a general nonparametric alternative, while the quantile regressions were evaluated using a goodness-of-fit test derived from the cumulative sum of the gradient vector. Our results indicate that the allometric model provides a better fit in the mean regression context, while the nonparametric model proves more effective for quantile regression, particularly in detecting condition-dependent deviations and regional variability. Other long-lived marine bivalves, such as Arctica islandica and Mercenaria mercenaria, which show environmentally driven variation in growth and condition, may similarly benefit from modeling approaches that distinguish central from marginal populations.

Data availability

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. The code used to estimate the models and perform the goodness-of-fit testing procedure is publicly available on GitHub at: https://github.com/sestelo/surfclam_length_weight_code.
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KeywordsBivalvesGrowth modellingBootstrap methodsNonparametric smoothing More