IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v221y2010i17p2054-2067.html
   My bibliography  Save this article

Different proxies for the reactivity of aquatic sediments towards oxygen: A model assessment

Author

Listed:
  • Van Frausum, Johan
  • Middelburg, Jack J.
  • Soetaert, Karline
  • Meysman, Filip J.R.

Abstract

Information on benthic carbon mineralization rates is often derived from the analysis of oxygen microprofiles in sediments. To enable a direct comparison of different sediment environments, it is often desirable to characterize sediments by a single proxy that expresses their “reactivity” towards oxygen. For this, there are three commonly used proxies: the oxygen penetration depth (OPD), the oxygen flux at the sediment–water interface (DOU), and the maximum volumetric oxygen consumption rate (Rmax). The OPD can be directly determined from the oxygen depth profile, while the DOU is usually obtained by a linear fit to the oxygen gradient either in diffusive boundary layer. The oxygen consumption rate Rmax requires the fitting of a reactive-transport model to the data profile. This article shows that the OPD alone is a suboptimal proxy, because it shows a strong dependence on the half-saturation constant Ks, and secondly, because it is sensitive to the particular re-oxidation conditions right above the oxic–anoxic interface. Similarly, the volumetric oxygen consumption rate Rmax is rather strongly dependent on the kinetic model formulation employed. To show this we fitted three different (Bouldin, Blackman and Monod) kinetics to the same oxygen data profiles. When fitting these models, the Rmax values obtained differed by 20% for exactly the same oxygen profile. Accordingly, if one reports Rmax values, it is crucial to specify the kinetic model alongside. Overall, DOU emerges as sediment reactivity proxy which is the least model dependent.

Suggested Citation

  • Van Frausum, Johan & Middelburg, Jack J. & Soetaert, Karline & Meysman, Filip J.R., 2010. "Different proxies for the reactivity of aquatic sediments towards oxygen: A model assessment," Ecological Modelling, Elsevier, vol. 221(17), pages 2054-2067.
  • Handle: RePEc:eee:ecomod:v:221:y:2010:i:17:p:2054-2067
    DOI: 10.1016/j.ecolmodel.2010.06.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380010002668
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2010.06.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Soetaert, Karline & Petzoldt, Thomas, 2010. "Inverse Modelling, Sensitivity and Monte Carlo Analysis in R Using Package FME," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i03).
    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. Zhou, W. & O’Neill, E. & Moncaster, A. & Reiner, D. & Guthrie, P., 2019. "Applying Bayesian Model Averaging to Characterise Urban Residential Stock Turnover Dynamics," Cambridge Working Papers in Economics 1986, Faculty of Economics, University of Cambridge.
    2. Hanson, Paul C. & Stillman, Aviah B. & Jia, Xiaowei & Karpatne, Anuj & Dugan, Hilary A. & Carey, Cayelan C. & Stachelek, Joseph & Ward, Nicole K. & Zhang, Yu & Read, Jordan S. & Kumar, Vipin, 2020. "Predicting lake surface water phosphorus dynamics using process-guided machine learning," Ecological Modelling, Elsevier, vol. 430(C).
    3. Hannah Al Ali & Alireza Daneshkhah & Abdesslam Boutayeb & Zindoga Mukandavire, 2022. "Examining Type 1 Diabetes Mathematical Models Using Experimental Data," IJERPH, MDPI, vol. 19(2), pages 1-20, January.
    4. Taffi, Marianna & Paoletti, Nicola & Liò, Pietro & Pucciarelli, Sandra & Marini, Mauro, 2015. "Bioaccumulation modelling and sensitivity analysis for discovering key players in contaminated food webs: The case study of PCBs in the Adriatic Sea," Ecological Modelling, Elsevier, vol. 306(C), pages 205-215.
    5. Lucash, Melissa S. & Marshall, Adrienne M. & Weiss, Shelby A. & McNabb, John W. & Nicolsky, Dmitry J. & Flerchinger, Gerald N. & Link, Timothy E. & Vogel, Jason G. & Scheller, Robert M. & Abramoff, Ro, 2023. "Burning trees in frozen soil: Simulating fire, vegetation, soil, and hydrology in the boreal forests of Alaska," Ecological Modelling, Elsevier, vol. 481(C).
    6. Meier, Laura & Brauns, Mario & Grimm, Volker & Weitere, Markus & Frank, Karin, 2022. "MASTIFF: A mechanistic model for cross-scale analyses of the functioning of multiple stressed riverine ecosystems," Ecological Modelling, Elsevier, vol. 470(C).
    7. Hussnain Mukhtar & Yu-Pin Lin & Oleg V. Shipin & Joy R. Petway, 2017. "Modeling Nitrogen Dynamics in a Waste Stabilization Pond System Using Flexible Modeling Environment with MCMC," IJERPH, MDPI, vol. 14(7), pages 1-15, July.
    8. Sehjeong Kim & Abdessamad Tridane, 2017. "Thalassemia in the United Arab Emirates: Why it can be prevented but not eradicated," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-13, January.
    9. Lee, Kyoungjae & Lee, Jaeyong & Dass, Sarat C., 2018. "Inference for differential equation models using relaxation via dynamical systems," Computational Statistics & Data Analysis, Elsevier, vol. 127(C), pages 116-134.
    10. Jinyoung Yang & Jeffrey S. Rosenthal, 2017. "Automatically tuned general-purpose MCMC via new adaptive diagnostics," Computational Statistics, Springer, vol. 32(1), pages 315-348, March.
    11. repec:jss:jstsof:33:i09 is not listed on IDEAS
    12. Soetaert, Karline & Petzoldt, Thomas & Setzer, R. Woodrow, 2010. "Solving Differential Equations in R: Package deSolve," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i09).
    13. McCullough, Ian M. & Dugan, Hilary A. & Farrell, Kaitlin J. & Morales-Williams, Ana M. & Ouyang, Zutao & Roberts, Derek & Scordo, Facundo & Bartlett, Sarah L. & Burke, Samantha M. & Doubek, Jonathan P, 2018. "Dynamic modeling of organic carbon fates in lake ecosystems," Ecological Modelling, Elsevier, vol. 386(C), pages 71-82.
    14. Chengyao Jiang & Ke Xu & Jiahui Rao & Jiaming Liu & Yushan Li & Yu Song & Mengyao Li & Yangxia Zheng & Wei Lu, 2024. "Establishment and Solution of a Finite Element Gas Exchange Model in Greenhouse-Grown Tomatoes for Two-Dimensional Porous Media with Light Quantity and Light Direction," Agriculture, MDPI, vol. 14(8), pages 1-19, July.
    15. Venolia, Celeste T. & Lavaud, Romain & Green-Gavrielidis, Lindsay A. & Thornber, Carol & Humphries, Austin T., 2020. "Modeling the Growth of Sugar Kelp (Saccharina latissima) in Aquaculture Systems using Dynamic Energy Budget Theory," Ecological Modelling, Elsevier, vol. 430(C).
    16. Haas, Marcelo B. & Guse, Björn & Pfannerstill, Matthias & Fohrer, Nicola, 2015. "Detection of dominant nitrate processes in ecohydrological modeling with temporal parameter sensitivity analysis," Ecological Modelling, Elsevier, vol. 314(C), pages 62-72.
    17. Keane, Robert E. & McKenzie, Donald & Falk, Donald A. & Smithwick, Erica A.H. & Miller, Carol & Kellogg, Lara-Karena B., 2015. "Representing climate, disturbance, and vegetation interactions in landscape models," Ecological Modelling, Elsevier, vol. 309, pages 33-47.
    18. Shoya Iwanami & Kosaku Kitagawa & Hirofumi Ohashi & Yusuke Asai & Kaho Shionoya & Wakana Saso & Kazane Nishioka & Hisashi Inaba & Shinji Nakaoka & Takaji Wakita & Odo Diekmann & Shingo Iwami & Koichi , 2020. "Should a viral genome stay in the host cell or leave? A quantitative dynamics study of how hepatitis C virus deals with this dilemma," PLOS Biology, Public Library of Science, vol. 18(7), pages 1-17, July.
    19. Krishna, Shubham & Pahlow, Markus & Schartau, Markus, 2019. "Comparison of two carbon-nitrogen regulatory models calibrated with mesocosm data," Ecological Modelling, Elsevier, vol. 411(C).
    20. Raquel Martins Lana & Maíra Moreira Morais & Tiago França Melo de Lima & Tiago Garcia de Senna Carneiro & Lucas Martins Stolerman & Jefferson Pereira Caldas dos Santos & José Joaquín Carvajal Cortés &, 2018. "Assessment of a trap based Aedes aegypti surveillance program using mathematical modeling," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-16, January.
    21. Littfinski, Tobias & Stricker, Max & Nettmann, Edith & Gehring, Tito & Hiegemann, Heinz & Krimmler, Stefan & Lübken, Manfred & Pant, Deepak & Wichern, Marc, 2022. "A generalized whole-cell model for wastewater-fed microbial fuel cells," Applied Energy, Elsevier, vol. 321(C).

    More about this item

    Keywords

    Modelling; Sediment biogeochemistry; O2 penetration; O2 uptake; O2 consumption rates;
    All these keywords.

    JEL classification:

    • O2 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy
    • O2 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy
    • O2 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy

    Statistics

    Access and download statistics

    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:eee:ecomod:v:221:y:2010:i:17:p:2054-2067. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    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.