The SI compartment model describes embolism spreading in networks of vessels and bordered pits in angiosperm xylem

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This paper presents the SI compartment model, which effectively describes the spread of embolisms throughout interconnected vessel and bordered pit networks found in angiosperm xylem.

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The paper studies how embolism spreads through angiosperm xylem vessel networks connected by bordered pits, using high-level modeling approaches to address limits of prior work that relied on overly parameterized physiology and oversimplified pit membranes. The authors first extend physiological models by representing the pit membrane as a 3D object, then introduce a stochastic susceptible-infected (SI) model to track embolism propagation and fit its spreading probability, after which the SI model reproduces vulnerability curves from both the physiological model and empirical data. They further connect the SI model to a directed percolation interpretation to frame embolism spread as a directed percolation process, but the mapping’s exact form is left to future work. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Plant xylem consists of a network of interconnected vessels, through which water is transported under negative pressure. Filling of vessels with air, or embolism, disturbs this transport process and, in extreme cases, leads to tree mortality. Despite this significance, embolism propagation dynamics are still poorly understood, primarily because xylem is opaque to direct observation. Furthermore, existing models of embolism spreading build excessively on physiological and anatomical parameters, and many misrepresent the inter-vessel pit membrane as a 2D surface. Here, we first extend these physiological models by implementing the pit membrane as a 3D object. Then, we introduce a susceptible-infected (SI) model, a simple stochastic model for tracking spreading through a population, for embolism propagation. After correctly fitting the spreading probability, our SI model reproduces vulnerability curves produced by both the physiological model and empirical data, highlighting that the SI model can address embolism spreading dynamics in plant species, for which detailed physiological data are not available. Furthermore, relating the SI model to the physiological one allows interpreting embolism spreading as a directed percolation process. Elucidating the exact mapping between directed percolation and embolism spreading will likely yield new fundamental insights into the relationships between xylem network architecture and embolism dynamics.
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Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Stochastic spreading models reproduce embolism propagation dynamics in angiosperm xylem networks of vessels connected by bordered pits View ORCID Profile Onerva Korhonen , View ORCID Profile Steven Jansen , Luciano de Melo Silva , View ORCID Profile Petri Kiuru , View ORCID Profile Magdalena Held , View ORCID Profile Anna Lintunen , View ORCID Profile Annamari Laurén doi: https://doi.org/10.1101/2025.10.27.684809 Onerva Korhonen 1 Tampere University; Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Onerva Korhonen For correspondence: onerva.korhonen{at}gmail.com Steven Jansen 2 University of Ulm; Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Steven Jansen Luciano de Melo Silva 3 University of Graz; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Petri Kiuru 4 University of Eastern Finland; Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Petri Kiuru Magdalena Held 5 University of Helsinki; Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Magdalena Held Anna Lintunen 5 University of Helsinki; Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Anna Lintunen Annamari Laurén 6 University of Eastern Finland / University of Helsinki Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Annamari Laurén Abstract Info/History Metrics Preview PDF Abstract Plant xylem consists of a network of interconnected vessels, through which water is transported under negative pressure. Filling of vessels with air, or embolism, disturbs this transport process and, in extreme cases, leads to tree mortality. Despite this significance, embolism propagation dynamics are still poorly understood, primarily because xylem is opaque to direct observation. Furthermore, existing models of embolism spreading build excessively on physiological and anatomical parameters, and many misrepresent the inter-vessel pit membrane as a 2D surface. Here, we first extend these physiological models by implementing the pit membrane as a 3D object. Then, we introduce a susceptible-infected (SI) model, a simple stochastic model for tracking spreading through a population, for embolism propagation. After correctly fitting the spreading probability, our SI model reproduces vulnerability curves produced by both the physiological model and empirical data, highlighting that the SI model can address embolism spreading dynamics in plant species, for which detailed physiological data are not available. Furthermore, relating the SI model to the physiological one allows interpreting embolism spreading as a directed percolation process. Elucidating the exact mapping between directed percolation and embolism spreading will likely yield new fundamental insights into the relationships between xylem network architecture and embolism dynamics. Competing Interest Statement The authors have declared no competing interest. Footnotes This is a major revision of the original manuscript with several modifications and clarifications in all parts, including a complete reorganization of the Discussion section Funder Information Declared Research Council of Finland, https://ror.org/05k73zm37 , 342934 , 355142 , 359340 Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license . View the discussion thread. Back to top Previous Next Posted May 22, 2026. 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Share Stochastic spreading models reproduce embolism propagation dynamics in angiosperm xylem networks of vessels connected by bordered pits Onerva Korhonen , Steven Jansen , Luciano de Melo Silva , Petri Kiuru , Magdalena Held , Anna Lintunen , Annamari Laurén bioRxiv 2025.10.27.684809; doi: https://doi.org/10.1101/2025.10.27.684809 Share This Article: Copy Citation Tools Stochastic spreading models reproduce embolism propagation dynamics in angiosperm xylem networks of vessels connected by bordered pits Onerva Korhonen , Steven Jansen , Luciano de Melo Silva , Petri Kiuru , Magdalena Held , Anna Lintunen , Annamari Laurén bioRxiv 2025.10.27.684809; doi: https://doi.org/10.1101/2025.10.27.684809 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Plant Biology Subject Areas All Articles Animal Behavior and Cognition (7635) Biochemistry (17690) Bioengineering (13892) Bioinformatics (41936) Biophysics (21451) Cancer Biology (18588) Cell Biology (25499) Clinical Trials (138) Developmental Biology (13378) Ecology (19899) Epidemiology (2067) Evolutionary Biology (24320) Genetics (15609) Genomics (22506) Immunology (17736) Microbiology (40394) Molecular Biology (17181) Neuroscience (88603) Paleontology (666) Pathology (2832) Pharmacology and Toxicology (4824) Physiology (7641) Plant Biology (15152) Scientific Communication and Education (2045) Synthetic Biology (4294) Systems Biology (9825) Zoology (2271)

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