[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-272094-105":3,"detail-sidebar-cat-0-en-105":81,"doc-detail-272094-en":131},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":74,"head_meta":76,"extra_data":78,"updated_unix":80},105,"en","in-silico-analysis-of-carbon-and-water-dynamics-in-the-rhizosphere-under-drought-conditions","In silico analysis of carbon and water dynamics in the rhizosphere under drought conditions","","A plant’s development depends on coordinated water and carbon flows across the soil–plant–atmosphere continuum, and climate change shifts these cycles while altering plant phenotypes. The work presents the equations and software implementation of a rhizosphere–soil model in the CPlantBox framework to mechanistically simulate feedback loops between water and carbon fluxes. The model updates multi-scale plant–rhizosphere–soil coupling, evaluates dry spells at different growth stages, and tests microbial kinetic parameterisations. Results show that dry spell timing and microbial reactivity strongly change cumulative plant carbon release, soil carbon inputs, and CO2 emissions. This enables insight into plant-scale C and water flows and soil-plant interaction effects on soil carbon cycling.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & Report",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/in-silico-analysis-of-carbon-and-water-dynamics-in-the-rhizosphere-under-drought-conditions/272094/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/in-silico-analysis-of-carbon-and-water-dynamics-in-the-rhizosphere-under-drought-conditions/272094.png","ImageObject",300,407,{"name":42,"@type":43},"Jasmine","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-29","2026-09-15",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",15,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What is the main goal of the study?","Question",{"text":63,"@type":64},"To develop and implement a rhizosphere–soil model within CPlantBox that mechanistically simulates feedback loops between water and carbon fluxes under drought conditions.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"How does the timing of dry spells affect model outputs?",{"text":68,"@type":64},"Earlier dry spells (days 11–18) lead to lower cumulative plant carbon release, while later dry spells (days 18–25) increase carbon input to the soil.",{"name":70,"@type":61,"acceptedAnswer":71},"Why do microbial parameterisations change CO2 emissions?",{"text":72,"@type":64},"More reactive microbial communities increase CO2 emissions because the higher carbon input to soil accelerates microbial carbon uptake and turnover; less reactive communities yield lower microbial CO2 emissions under the same weather scenario.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},272094,1789463185,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,106,111,115,120,123,127],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":97,"doc_module":4,"doc_module_name":25,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":102,"doc_module":4,"doc_module_name":25,"category_name":103,"show_sort_weight":104,"slug":105},6,"Technology",50,"technology",{"id":107,"doc_module":4,"doc_module_name":25,"category_name":108,"show_sort_weight":109,"slug":110},7,"Healthcare",40,"healthcare",{"id":112,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":113,"slug":114},8,30,"research-report",{"id":116,"doc_module":4,"doc_module_name":25,"category_name":117,"show_sort_weight":118,"slug":119},9,"Religion & Spirituality",20,"religion-spirituality",{"id":118,"doc_module":4,"doc_module_name":25,"category_name":121,"show_sort_weight":118,"slug":122},"World Cup","world-cup",{"id":124,"doc_module":4,"doc_module_name":25,"category_name":125,"show_sort_weight":124,"slug":126},10,"Lifestyle","lifestyle",{"id":128,"doc_module":4,"doc_module_name":25,"category_name":129,"show_sort_weight":97,"slug":130},19,"General","general",{"code":4,"msg":82,"data":132},{"doc_id":79,"user_id":133,"nickname":42,"user_avatar":134,"doc_module":4,"category_id":112,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":140,"language":141,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":142,"faqs":143,"seo_title":144,"seo_description":12,"update_tm":80,"read_time":145,"preview_page_count":4},2336478487870,"https://ap-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45","SOIL, 12, 371–419, 2026  \n[https://doi.org/10.5194/soil-12-371-2026](https://doi.org/10.5194/soil-12-371-2026)[ ](https://doi.org/10.5194/soil-12-371-2026)© Author(s) 2026 . This work is distributed under the Creative Commons Attribution 4 .0 License.  \nSOIL  \nIn silico analysis of carbon and water dynamics in therhizosphere under drought conditions  \nMona Giraud 1,2 ;􀀔 , Ahmet Kür¸sad Sırcan3 ;􀀔 , Thilo Streck3 , Daniel Leitner 1 , Guillaume Lobet4 ,  \nHolger Pagel 1,2 ;􀀔 , and Andrea Schnepf1,2 ;􀀔  \n1Institute of Bio-and Geosciences (IBG-3), Forschungszentrum Jülich, 52428, Jülich, Germany  \n2Institute of Crop Science and Resource Conservation, University of Bonn, 53115 Bonn, Germany  \n3Institute of Soil Science and Land Evaluation, Department of Biogeophysics, University of Hohenheim, Stuttgart, Germany  \n4Earth and Life Institute, Université catholique de Louvain, is Louvain-la-Neuve, Belgium  \n􀀔 These authors contributed equally to this work.  \nCorrespondence: Mona Giraud ([m.giraud@fz-juelich.de](m.giraud@fz-juelich.de))  \nReceived: 7 February 2025 – Discussion started: 7 March 2025  \nRevised: 6 March 2026 – Accepted: 16 March 2026 – Published: 2 April 2026  \nAbstract. A plant's development is strongly linked to the water and carbon (C) flows in the soil-plantatmosphere continuum. Ongoing climate shifts will alter the water and C cycles and affect plant phenotypes. Comprehensive models that simulate mechanistically and dynamically the feedback loops between water and C fluxes in the soil-plant system are useful tools to evaluate the sustainability of genotype-environmentmanagement combinations that do not yet exist. In this study, we present the equations and implementation of a rhizosphere-soil model within the CPlantBox framework, a functional-structural plant model that represents plant processes and plant-soil interactions. The multi-scale plant-rhizosphere-soil coupling scheme previously used for CPlantBox was likewise updated, among others to increase the accuracy and stability of the model outputs. The model was implemented to simulate the effect of dry spells occurring at different plant development stages, and for different soil kinetic parameterisations of microbial dynamics in soil. We could observe diverging results according to the date of occurrence of the dry spells and soil parameterisations. For instance, earlier dry spells (from 11th to the 18th day of growth) led to a lower cumulative plant C release, while later dry spells (from 18th to the 25th day of growth) led to higher C input to the soil. For more reactive microbial communities (higher maximum C uptake rate and (de)activation rates), this higher C input caused a strong increase in CO 2 emissions. For the same weather scenario, we observed lower microbial CO 2 emissions with less reactive communities. This model can be used to gain insight into C and water flows at the plant scale, and the influence of soil-plant interactions on C cycling in soils.  \n1 Introduction  \nUnderstanding the dynamics driving the water and carbon (C) balances in the soil-plant-atmosphere continuum is key to predict, mitigate, and adapt agroecosystems to climate change (Silva and Lambers, 2021 ; George et al., 2024) .  \nPlants link the water and C balances in the soil and atmosphere via plant-related processes, such as coupled stomatal regulation-photosynthesis-transpiration (De Swaef et al.,  \n2022 ; Lacointe and Minchin, 2019 ; Silva and Lambers, 2021); the topology of its shoot (de la Fuente Cantó et al., 2020) and root system (Galindo-Castañeda et al., 2023 ; George et al., 2024 ; de la Fuente Cantó et al., 2020); as well as plant anatomical characteristics – e.g., number and size of the phloem and xylem vessels (Lynch et al., 2021 ; GalindoCastañeda et al., 2023) .  \nPlant-soil exchanges lead to the creation of the rhizosphere, i.e., root-affected soil with characteristics distinctive  \nPublished by Copernicus Publications on behalf of the European Geosciences Union.  \n3","cbCaiabV0b0u1Dbf","https://ap.wps.com/l/cbCaiabV0b0u1Dbf","pdf",8179577,49,"English","# Abstract\n# Introduction\n## Soil–plant–atmosphere water and carbon coupling\n## Rhizosphere formation and microbial control\n## Mechanistic biogeochemical modelling and FSPMs","[{\"question\":\"What is the main goal of the study?\",\"answer\":\"To develop and implement a rhizosphere–soil model within CPlantBox that mechanistically simulates feedback loops between water and carbon fluxes under drought conditions.\"},{\"question\":\"How does the timing of dry spells affect model outputs?\",\"answer\":\"Earlier dry spells (days 11–18) lead to lower cumulative plant carbon release, while later dry spells (days 18–25) increase carbon input to the soil.\"},{\"question\":\"Why do microbial parameterisations change CO2 emissions?\",\"answer\":\"More reactive microbial communities increase CO2 emissions because the higher carbon input to soil accelerates microbial carbon uptake and turnover; less reactive communities yield lower microbial CO2 emissions under the same weather scenario.\"}]","In silico analysis of carbon and water dynamics in the rhizosphere under drought conditions | PDF",123]