IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v233y2012icp83-89.html
   My bibliography  Save this article

Bridging the gap between empirical and mechanistic models of aquatic primary production with the metabolic theory of ecology: An example from estuarine ecosystems

Author

Listed:
  • Harris, Lora A.
  • Brush, Mark J.

Abstract

Numerical models typically predict phytoplankton production by calculating an exponential response to water temperature to set maximum rates that are reduced by light and nutrient limitation factors. Formulations based on biomass, irradiance, and photic depth (the “BZI” model) have been suggested as an alternative. Both approaches are rooted in empirical observations even as they include parameters that are variables in equations of the metabolic theory of ecology (MTE). Application of the MTE to phytoplankton is particularly appropriate as these communities span several orders of magnitude in individual size. We present a dimensional analysis of the BZI model that demonstrates its first principles origin. Data from estuaries where the BZI model is applied are used to explore temperature dependency of productivity as formulated by the Boltzman factor used in the MTE. We demonstrate how theory and empirical studies may be combined to provide added insight to the application of predictive models.

Suggested Citation

  • Harris, Lora A. & Brush, Mark J., 2012. "Bridging the gap between empirical and mechanistic models of aquatic primary production with the metabolic theory of ecology: An example from estuarine ecosystems," Ecological Modelling, Elsevier, vol. 233(C), pages 83-89.
    • Handle: RePEc:eee:ecomod:v:233:y:2012:i:c:p:83-89
    DOI: 10.1016/j.ecolmodel.2012.03.024
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380012001408
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2012.03.024?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. Geoffrey B. West & James H. Brown & Brian J. Enquist, 1997. "A General Model for the Origin of Allometric Scaling Laws in Biology," Working Papers 97-03-019, Santa Fe Institute.
    2. Brian J. Enquist & Evan P. Economo & Travis E. Huxman & Andrew P. Allen & Danielle D. Ignace & James F. Gillooly, 2003. "Scaling metabolism from organisms to ecosystems," Nature, Nature, vol. 423(6940), pages 639-642, June.
    3. Brian J. Enquist & James H. Brown & Geoffrey B. West, 1998. "Allometric scaling of plant energetics and population density," Nature, Nature, vol. 395(6698), pages 163-165, September.
    4. Geoffrey B. West & James H. Brown & Brian J. Enquist, 1999. "A general model for the structure and allometry of plant vascular systems," Nature, Nature, vol. 400(6745), pages 664-667, August.
    5. Brian J. Enquist & James H. Brown & Geoffrey B. West, 1998. "Allometric Scaling of Plant Energetics and Population Density," Working Papers 98-11-104, Santa Fe Institute.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sun, Detong & Doering, Peter H. & Phlips, Edward J., 2021. "Modeling primary production: Developing the BZI model from the production-irradiance (P-I) curves," Ecological Modelling, Elsevier, vol. 458(C).

    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. Song, Dong-Ming & Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2009. "Statistical properties of world investment networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(12), pages 2450-2460.
    2. Chen, Yanguang, 2014. "An allometric scaling relation based on logistic growth of cities," Chaos, Solitons & Fractals, Elsevier, vol. 65(C), pages 65-77.
    3. Sorrell, Steve, 2015. "Reducing energy demand: A review of issues, challenges and approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 74-82.
    4. Tao, Yong & Lin, Li & Wang, Hanjie & Hou, Chen, 2023. "Superlinear growth and the fossil fuel energy sustainability dilemma: Evidence from six continents," Structural Change and Economic Dynamics, Elsevier, vol. 66(C), pages 39-51.
    5. Chen, Yanguang, 2017. "Multi-scaling allometric analysis for urban and regional development," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 673-689.
    6. Hendriks, A. Jan, 2007. "The power of size: A meta-analysis reveals consistency of allometric regressions," Ecological Modelling, Elsevier, vol. 205(1), pages 196-208.
    7. Peters, Ronny & Olagoke, Adewole & Berger, Uta, 2018. "A new mechanistic theory of self-thinning: Adaptive behaviour of plants explains the shape and slope of self-thinning trajectories," Ecological Modelling, Elsevier, vol. 390(C), pages 1-9.
    8. Jiang Zhang & Lingfei Wu, 2013. "Allometry and Dissipation of Ecological Flow Networks," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-8, September.
    9. Ogawa, Kazuharu, 2009. "Mathematical analysis of change in forest carbon use efficiency with stand development: A case study on Abies veitchii Lindl," Ecological Modelling, Elsevier, vol. 220(11), pages 1419-1424.
    10. Ma, Ping & Han, Xiao-Hui & Lin, Yue & Moore, John & Guo, Yao-Xin & Yue, Ming, 2019. "Exploring the relative importance of biotic and abiotic factors that alter the self-thinning rule: Insights from individual-based modelling and machine-learning," Ecological Modelling, Elsevier, vol. 397(C), pages 16-24.
    11. Chen, Yanguang & Wang, Yihan & Li, Xijing, 2019. "Fractal dimensions derived from spatial allometric scaling of urban form," Chaos, Solitons & Fractals, Elsevier, vol. 126(C), pages 122-134.
    12. Barnes, Belinda & Mokany, Karel & Roderick, Michael, 2007. "Allocation within a generic scaling framework," Ecological Modelling, Elsevier, vol. 201(2), pages 223-232.
    13. Xu, Meng & Jiang, Mengke & Wang, Hua-Feng, 2021. "Integrating metabolic scaling variation into the maximum entropy theory of ecology explains Taylor's law for individual metabolic rate in tropical forests," Ecological Modelling, Elsevier, vol. 455(C).
    14. Xinjing Ding & Peixi Su & Zijuan Zhou & Rui Shi, 2019. "Belowground Bud Bank Distribution and Aboveground Community Characteristics along Different Moisture Gradients of Alpine Meadow in the Zoige Plateau, China," Sustainability, MDPI, vol. 11(9), pages 1-13, May.
    15. GANIO-MEGO, Joe, 2022. "The instant and historical Preston curves: allometry quarter-power law valid for the humans," SocArXiv y8rbt, Center for Open Science.
    16. John J. Kineman & Krupanidhi Srirama & Jennifer Wilby & Bruce T. Milne, 2017. "Elements of a Holistic Theory to Meet the Sustainability Challenge," Systems Research and Behavioral Science, Wiley Blackwell, vol. 34(5), pages 553-563, September.
    17. Ogawa, Kazuharu, 2018. "Mathematical consideration of the age-related decline in leaf biomass in forest stands under the self-thinning law," Ecological Modelling, Elsevier, vol. 372(C), pages 64-69.
    18. He, Ji-Huan, 2007. "Shrinkage of body size of small insects: A possible link to global warming?," Chaos, Solitons & Fractals, Elsevier, vol. 34(3), pages 727-729.
    19. GANIO-MEGO, Joe, 2022. "Estimating the human equivalent weight by applying the quarter-power law of allometry to humanity," OSF Preprints 7eq6x, Center for Open Science.
    20. Wiegand, Kerstin & Saltz, David & Ward, David & Levin, Simon A., 2008. "The role of size inequality in self-thinning: A pattern-oriented simulation model for arid savannas," Ecological Modelling, Elsevier, vol. 210(4), pages 431-445.

    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:233:y:2012:i:c:p:83-89. 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.