IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v240y2012icp139-155.html
   My bibliography  Save this article

Examination of the effects of nutrient regeneration mechanisms on plankton dynamics using aquatic biogeochemical modeling

Author

Listed:
  • Ramin, Maryam
  • Perhar, Gurbir
  • Shimoda, Yuko
  • Arhonditsis, George B.

Abstract

The prolonged stratification of lakes due to climate warming is expected to increase the dependence of planktonic food webs on internal nutrient regeneration mechanisms (i.e., microbial mineralization, zooplankton excretion). Our current conceptualization of aquatic communities, however, suggests that while the strength of the recycling feedback loop is indeed related to climate forcing, other biotic factors (e.g., zooplankton community composition) along with the system productivity may also be equally important. What do the contemporary operational models predict about the role of recycling rates in different trophic environments? How tight is the relationship between mineralization rates and lake warming? How realistically do modelers describe the mechanisms by which nutrients in non-living organic matter are recycled into inorganic forms? Our study addresses these questions using a complex biogeochemical model that simulates multiple elemental cycles (C, N, P, Si, O), multiple functional phytoplankton (diatoms, green algae and cyanobacteria) and zooplankton (copepods and cladocerans) groups. We relaxed the assumption of strict zooplankton homeostasis by allowing nutrient use efficiency to vary with food quality. Our analysis shows that the nutrient regeneration rates can play a major role in planktonic food webs, but their relative importance is somewhat inconsistent with the existing paradigm. We provide evidence that the recycled material and the associated energy fluxes can be significant drivers in low as well as in high-productivity ecosystems depending on the period of the year examined. Warmer climatic conditions and longer stratification periods will increase the dependence of lakes on nutrient regeneration rates. The lake productivity response, however, is non-linear and non-monotonic and is modulated by the type of nutrient limitation (nitrogen or phosphorus) experienced. Our study concludes by pinpointing some problems of the existing mathematical representation of the recycling rates, and emphasizes the need to improve our understanding of the interplay among microbial metabolism, trophic state, and lake thermal structure.

Suggested Citation

  • Ramin, Maryam & Perhar, Gurbir & Shimoda, Yuko & Arhonditsis, George B., 2012. "Examination of the effects of nutrient regeneration mechanisms on plankton dynamics using aquatic biogeochemical modeling," Ecological Modelling, Elsevier, vol. 240(C), pages 139-155.
  • Handle: RePEc:eee:ecomod:v:240:y:2012:i:c:p:139-155
    DOI: 10.1016/j.ecolmodel.2012.04.018
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380012001913
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2012.04.018?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. Zhao, Jingyang & Ramin, Maryam & Cheng, Vincent & Arhonditsis, George B., 2008. "Plankton community patterns across a trophic gradient: The role of zooplankton functional groups," Ecological Modelling, Elsevier, vol. 213(3), pages 417-436.
    2. Law, Tony & Zhang, Weitao & Zhao, Jingyang & Arhonditsis, George B., 2009. "Structural changes in lake functioning induced from nutrient loading and climate variability," Ecological Modelling, Elsevier, vol. 220(7), pages 979-997.
    3. Mulder, Kenneth & Bowden, William Breck, 2007. "Organismal stoichiometry and the adaptive advantage of variable nutrient use and production efficiency in Daphnia," Ecological Modelling, Elsevier, vol. 202(3), pages 427-440.
    4. Jeff J. Hudson & William D. Taylor & David W. Schindler, 1999. "Planktonic nutrient regeneration and cycling efficiency in temperate lakes," Nature, Nature, vol. 400(6745), pages 659-661, August.
    5. Arhonditsis, George B. & Qian, Song S. & Stow, Craig A. & Lamon, E. Conrad & Reckhow, Kenneth H., 2007. "Eutrophication risk assessment using Bayesian calibration of process-based models: Application to a mesotrophic lake," Ecological Modelling, Elsevier, vol. 208(2), pages 215-229.
    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. Guo, Qing & Wang, Yi & Dai, Chuanjun & Wang, Lijun & Liu, He & Li, Jianbing & Tiwari, Pankaj Kumar & Zhao, Min, 2023. "Dynamics of a stochastic nutrient–plankton model with regime switching," Ecological Modelling, Elsevier, vol. 477(C).
    2. Zou, Rui & Wu, Zhen & Zhao, Lei & Elser, James J. & Yu, Yanhong & Chen, Yihui & Liu, Yong, 2020. "Seasonal algal blooms support sediment release of phosphorus via positive feedback in a eutrophic lake: Insights from a nutrient flux tracking modeling," Ecological Modelling, Elsevier, vol. 416(C).
    3. Perhar, Gurbir & Arhonditsis, George B. & Brett, Michael T., 2013. "Modeling zooplankton growth in Lake Washington: A mechanistic approach to physiology in a eutrophication model," Ecological Modelling, Elsevier, vol. 258(C), pages 101-121.

    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. Law, Tony & Zhang, Weitao & Zhao, Jingyang & Arhonditsis, George B., 2009. "Structural changes in lake functioning induced from nutrient loading and climate variability," Ecological Modelling, Elsevier, vol. 220(7), pages 979-997.
    2. McDonald, C.P. & Bennington, V. & Urban, N.R. & McKinley, G.A., 2012. "1-D test-bed calibration of a 3-D Lake Superior biogeochemical model," Ecological Modelling, Elsevier, vol. 225(C), pages 115-126.
    3. Perhar, Gurbir & Arhonditsis, George B., 2009. "The effects of seston food quality on planktonic food web patterns," Ecological Modelling, Elsevier, vol. 220(6), pages 805-820.
    4. Ramin, Maryam & Labencki, Tanya & Boyd, Duncan & Trolle, Dennis & Arhonditsis, George B., 2012. "A Bayesian synthesis of predictions from different models for setting water quality criteria," Ecological Modelling, Elsevier, vol. 242(C), pages 127-145.
    5. Li, Yuzhao & Liu, Yong & Zhao, Lei & Hastings, Alan & Guo, Huaicheng, 2015. "Exploring change of internal nutrients cycling in a shallow lake: A dynamic nutrient driven phytoplankton model," Ecological Modelling, Elsevier, vol. 313(C), pages 137-148.
    6. Perhar, Gurbir & Arhonditsis, George B. & Brett, Michael T., 2013. "Modeling zooplankton growth in Lake Washington: A mechanistic approach to physiology in a eutrophication model," Ecological Modelling, Elsevier, vol. 258(C), pages 101-121.
    7. Eisenhauer, L. & Carlotti, F. & Baklouti, M. & Diaz, F., 2009. "Zooplankton population model coupled to a biogeochemical model of the North Western Mediterranean Sea ecosystem," Ecological Modelling, Elsevier, vol. 220(21), pages 2865-2876.
    8. Lindim, C. & Pinho, J.L. & Vieira, J.M.P., 2011. "Analysis of spatial and temporal patterns in a large reservoir using water quality and hydrodynamic modeling," Ecological Modelling, Elsevier, vol. 222(14), pages 2485-2494.
    9. Wang, Hao & Lu, Zexian & Raghavan, Aditya, 2018. "Weak dynamical threshold for the “strict homeostasis” assumption in ecological stoichiometry," Ecological Modelling, Elsevier, vol. 384(C), pages 233-240.
    10. Strauss, Tido & Gabsi, Faten & Hammers-Wirtz, Monika & Thorbek, Pernille & Preuss, Thomas G., 2017. "The power of hybrid modelling: An example from aquatic ecosystems," Ecological Modelling, Elsevier, vol. 364(C), pages 77-88.
    11. Xu, Yanhong & Peng, Hong & Yang, Yinqun & Zhang, Wanshun & Wang, Shuangling, 2014. "A cumulative eutrophication risk evaluation method based on a bioaccumulation model," Ecological Modelling, Elsevier, vol. 289(C), pages 77-85.
    12. Mulderij, Gabi & Van Nes, Egbert H. & Van Donk, Ellen, 2007. "Macrophyte–phytoplankton interactions: The relative importance of allelopathy versus other factors," Ecological Modelling, Elsevier, vol. 204(1), pages 85-92.
    13. Chen, Fei & Taylor, William D., 2011. "A model of phosphorus cycling in the epilimnion of oligotrophic and mesotrophic lakes," Ecological Modelling, Elsevier, vol. 222(5), pages 1103-1111.
    14. Kim, Dong-Kyun & Zhang, Weitao & Rao, Yerubandi R. & Watson, Sue & Mugalingam, Shan & Labencki, Tanya & Dittrich, Maria & Morley, Andrew & Arhonditsis, George B., 2013. "Improving the representation of internal nutrient recycling with phosphorus mass balance models: A case study in the Bay of Quinte, Ontario, Canada," Ecological Modelling, Elsevier, vol. 256(C), pages 53-68.
    15. Islam, Md. Nazrul & Kitazawa, Daisuke & Kokuryo, Naoki & Tabeta, Shigeru & Honma, Takamitsu & Komatsu, Nobuyuki, 2012. "Numerical modeling on transition of dominant algae in Lake Kitaura, Japan," Ecological Modelling, Elsevier, vol. 242(C), pages 146-163.
    16. Zhang, Weitao & Arhonditsis, George B., 2009. "A Bayesian hierarchical framework for calibrating aquatic biogeochemical models," Ecological Modelling, Elsevier, vol. 220(18), pages 2142-2161.
    17. Wang, Hao & Sterner, Robert W. & Elser, James J., 2012. "On the “strict homeostasis” assumption in ecological stoichiometry," Ecological Modelling, Elsevier, vol. 243(C), pages 81-88.
    18. Mulder, Kenneth, 2007. "Modeling the dynamics of nutrient limited consumer populations using constant elasticity production functions," Ecological Modelling, Elsevier, vol. 207(2), pages 319-326.
    19. Yang, Likun & Zhao, Xinhua & Peng, Sen & Li, Xia, 2016. "Water quality assessment analysis by using combination of Bayesian and genetic algorithm approach in an urban lake, China," Ecological Modelling, Elsevier, vol. 339(C), pages 77-88.
    20. Tanioka, Tatsuro & Matsumoto, Katsumi, 2018. "Effects of incorporating age-specific traits of zooplankton into a marine ecosystem model," Ecological Modelling, Elsevier, vol. 368(C), pages 257-264.

    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:240:y:2012:i:c:p:139-155. 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.