IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v10y2021i8p840-d612404.html
   My bibliography  Save this article

The Exudation of Surplus Products Links Plant Functional Traits and Plant-Microbial Stoichiometry

Author

Listed:
  • Julian Cardenas

    (Faculty of Science, University of South Bohemia, Branišovská 1760, 370 05 České Budějovice, Czech Republic)

  • Fernando Santa

    (Nova Information Management School (NOVA IMS), Universidade Nova de Lisboa, 1070-312 Lisbon, Portugal)

  • Eva Kaštovská

    (Faculty of Science, University of South Bohemia, Branišovská 1760, 370 05 České Budějovice, Czech Republic)

Abstract

The rhizosphere is a hot spot of soil microbial activity and is largely fed by root exudation. The carbon (C) exudation flux, coupled with plant growth, is considered a strategy of plants to facilitate nutrient uptake. C exudation is accompanied by a release of nutrients. Nitrogen (N) and phosphorus (P) co-limit the productivity of the plant-microbial system. Therefore, the C:N:P stoichiometry of exudates should be linked to plant nutrient economies, plant functional traits (PFT) and soil nutrient availability. We aimed to identify the strongest links in C:N:P stoichiometry among all rhizosphere components. A total of eight grass species (from conservative to exploitative) were grown in pots under two different soil C:nutrient conditions for a month. As a result, a wide gradient of plant–microbial–soil interactions were created. A total of 43 variables of plants, exudates, microbial and soil C:N:P stoichiometry, and PFTs were evaluated. The variables were merged into four groups in a network analysis, allowing us to identify the strongest connections among the variables and the biological meaning of these groups. The plant–soil interactions were shaped by soil N availability. Faster-growing plants were associated with lower amounts of mineral N (and P) in the soil solution, inducing a stronger competition for N with microorganisms in the rhizosphere compared to slower-growing plants. The plants responded by enhancing their N use efficiency and root:shoot ratio, and they reduced N losses via exudation. Root growth was supported either by reallocated foliar reserves or by enhanced ammonium uptake, which connected the specific leaf area (SLA) to the mineral N availability in the soil. Rapid plant growth enhanced the exudation flux. The exudates were rich in C and P relative to N compounds and served to release surplus metabolic products. The exudate C:N:P stoichiometry and soil N availability combined to shape the microbial stoichiometry, and N and P mining. In conclusion, the exudate flux and its C:N:P stoichiometry reflected the plant growth rate and nutrient constraints with a high degree of reliability. Furthermore, it mediated the plant–microbial interactions in the rhizosphere.

Suggested Citation

  • Julian Cardenas & Fernando Santa & Eva Kaštovská, 2021. "The Exudation of Surplus Products Links Plant Functional Traits and Plant-Microbial Stoichiometry," Land, MDPI, vol. 10(8), pages 1-16, August.
  • Handle: RePEc:gam:jlands:v:10:y:2021:i:8:p:840-:d:612404
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/10/8/840/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/10/8/840/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Robert L. Sinsabaugh & Brian H. Hill & Jennifer J. Follstad Shah, 2009. "Ecoenzymatic stoichiometry of microbial organic nutrient acquisition in soil and sediment," Nature, Nature, vol. 462(7274), pages 795-798, December.
    2. Chavent, Marie & Kuentz-Simonet, Vanessa & Liquet, Benoît & Saracco, Jérôme, 2012. "ClustOfVar: An R Package for the Clustering of Variables," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 50(i13).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhiyuan Hu & Jiating Li & Kangwei Shi & Guangqian Ren & Zhicong Dai & Jianfan Sun & Xiaojun Zheng & Yiwen Zhou & Jiaqi Zhang & Guanlin Li & Daolin Du, 2021. "Effects of Canada Goldenrod Invasion on Soil Extracellular Enzyme Activities and Ecoenzymatic Stoichiometry," Sustainability, MDPI, vol. 13(7), pages 1-13, March.
    2. Luther Elliott & Christopher Keith Haddock & Stephanie Campos & Ellen Benoit, 2019. "Polysubstance use patterns and novel synthetics: A cluster analysis from three U.S. cities," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-17, December.
    3. Jeoffrey Dehez & Sandrine Lyser, 2024. "How ocean beach recreational quality fits with safety issues? An analysis of risky behaviours in France," Post-Print hal-04384330, HAL.
    4. C. Pérez-Brandán & J. Huidobro & M. Galván & S. Vargas-Gil & J.M. Meriles, 2016. "Relationship between microbial functions and community structure following agricultural intensification in South American Chaco," Plant, Soil and Environment, Czech Academy of Agricultural Sciences, vol. 62(7), pages 321-328.
    5. Minyoung Kwon & Guanlin Li & Heejae Jo & Gwang-Jung Kim & Haegeun Chung & Yowhan Son, 2024. "Changes in Soil Microbial Communities Associated with Pinus densiflora and Larix kaempferi Seedlings under Extreme Warming and Precipitation Manipulation," Sustainability, MDPI, vol. 16(11), pages 1-14, May.
    6. Xiaowen Wang & Shanshan Yao & Mengying Wang & Guiying Cao & Zishuo Chen & Ziting Huang & Yao Wu & Ling Han & Beibei Xu & Yonghua Hu, 2020. "Multimorbidity among Two Million Adults in China," IJERPH, MDPI, vol. 17(10), pages 1-13, May.
    7. Meixia Liu & Menglu Wang & Congwei Sun & Hui Wu & Xueqing Zhao & Enke Liu & Wenyi Dong & Meiling Yan, 2023. "Self-Regulation of Soil Enzyme Activity and Stoichiometry under Nitrogen Addition and Plastic Film Mulching in the Loess Plateau Area, Northwest China," Agriculture, MDPI, vol. 13(5), pages 1-11, April.
    8. Lbath, Hanâ & Petersen, Alexander & Meiring, Wendy & Achard, Sophie, 2024. "Clustering-based inter-regional correlation estimation," Computational Statistics & Data Analysis, Elsevier, vol. 191(C).
    9. Vanessa Kuentz-Simonet & Amaury Labenne & Tina Rambonilaza, 2017. "Using ClustOfVar to Construct Quality of Life Indicators for Vulnerability Assessment Municipality Trajectories in Southwest France from 1999 to 2009," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 131(3), pages 973-997, April.
    10. Qing Zhao & Jie Tang & Zhaoyang Li & Wei Yang & Yucong Duan, 2018. "The Influence of Soil Physico-Chemical Properties and Enzyme Activities on Soil Quality of Saline-Alkali Agroecosystems in Western Jilin Province, China," Sustainability, MDPI, vol. 10(5), pages 1-15, May.
    11. Wang, Endong & Alp, Neslihan & Shi, Jonathan & Wang, Chao & Zhang, Xiaodong & Chen, Hong, 2017. "Multi-criteria building energy performance benchmarking through variable clustering based compromise TOPSIS with objective entropy weighting," Energy, Elsevier, vol. 125(C), pages 197-210.
    12. Susheel Bhanu Busi & Massimo Bourquin & Stilianos Fodelianakis & Grégoire Michoud & Tyler J. Kohler & Hannes Peter & Paraskevi Pramateftaki & Michail Styllas & Matteo Tolosano & Vincent Staercke & Mar, 2022. "Genomic and metabolic adaptations of biofilms to ecological windows of opportunity in glacier-fed streams," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    13. Yanyu Song & Changchun Song & Jiusheng Ren & Xiuyan Ma & Wenwen Tan & Xianwei Wang & Jinli Gao & Aixin Hou, 2019. "Short-Term Response of the Soil Microbial Abundances and Enzyme Activities to Experimental Warming in a Boreal Peatland in Northeast China," Sustainability, MDPI, vol. 11(3), pages 1-16, January.
    14. Yao Zhang & Junqi Wang & Lan Chen & Sha Zhou & Lu Zhang & Fazhu Zhao, 2022. "Different Response of Soil Microbial Carbon Use Efficiency in Compound of Feldspathic Sandstone and Sand," Agriculture, MDPI, vol. 13(1), pages 1-9, December.
    15. Gero Szepannek, 2022. "An Overview on the Landscape of R Packages for Open Source Scorecard Modelling," Risks, MDPI, vol. 10(3), pages 1-33, March.
    16. Jörg Schnecker & Birgit Wild & Florian Hofhansl & Ricardo J Eloy Alves & Jiří Bárta & Petr Čapek & Lucia Fuchslueger & Norman Gentsch & Antje Gittel & Georg Guggenberger & Angelika Hofer & Sandra Kien, 2014. "Effects of Soil Organic Matter Properties and Microbial Community Composition on Enzyme Activities in Cryoturbated Arctic Soils," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-10, April.
    17. Yao, Xingzhi & Izzeldin, Marwan & Li, Zhenxiong, 2019. "A novel cluster HAR-type model for forecasting realized volatility," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1318-1331.
    18. Daniela Figueroa & Patricia Ortega-Fernández & Thalita F. Abbruzzini & Anaitzi Rivero-Villlar & Francisco Galindo & Bruno Chavez-Vergara & Jorge D. Etchevers & Julio Campo, 2020. "Effects of Land Use Change from Natural Forest to Livestock on Soil C, N and P Dynamics along a Rainfall Gradient in Mexico," Sustainability, MDPI, vol. 12(20), pages 1-20, October.
    19. Ana Belén Ramos-Guajardo, 2022. "A hierarchical clustering method for random intervals based on a similarity measure," Computational Statistics, Springer, vol. 37(1), pages 229-261, March.
    20. Avijit Ghosh & Suheel Ahmad & Amit K. Singh & Pramod Jha & Rajendra Kumar Yadav & Raimundo Jiménez Ballesta & Sheeraz Saleem Bhatt & Nagaratna Biradar & Nazim Hamid Mir, 2024. "Soil Carbon Storage, Enzymatic Stoichiometry, and Ecosystem Functions in Indian Himalayan Legume-Diversified Pastures," Land, MDPI, vol. 13(4), pages 1-17, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:10:y:2021:i:8:p:840-:d:612404. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.