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Predicting ecosystem functioning from plant traits: Results from a multi-scale ecophysiological modeling approach

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  • van Wijk, M.T.

Abstract

Ecosystem functioning is the result of processes working at a hierarchy of scales. The representation of these processes in a model that is mathematically tractable and ecologically meaningful is a big challenge. In this paper I describe an individual based model (PLACO—PLAnt COmpetition) that represents the effects that individual plant traits and environmental resources have on the growth of individual plants and, by implementing key interactions of and feedbacks on resource competition and nutrient cycling, also simulates the behaviour of the plant community and the ecosystem as a whole. The model is tested on results obtained in long term fertilization experiments, after which the model is applied to gain insight in questions related to plant diversity and ecosystem functioning. Is there a clear relationship between the diversity of the plant characteristics introduced in the model and overall system level productivity? The model simulations captured the patterns observed in the long term fertilization experiments and correctly predicted the dominance of Betula nana under the fertilization treatment. In the biodiversity simulations at both low and high nutrient inputs, an optimum curve relationship occurred between diversity and system level growth, and between diversity and system level biomass. At low nutrient input, system level productivity showed a curved relationship with an intermediate optimum with Shannon's diversity index, but at high nutrient input single species dominated systems also reached high values of productivity. The model simulations show that individual plant behaviour observed when a plant is growing on its own contains limited information about its behaviour and productivity within a competitive multi-species environment.

Suggested Citation

  • van Wijk, M.T., 2007. "Predicting ecosystem functioning from plant traits: Results from a multi-scale ecophysiological modeling approach," Ecological Modelling, Elsevier, vol. 203(3), pages 453-463.
  • Handle: RePEc:eee:ecomod:v:203:y:2007:i:3:p:453-463
    DOI: 10.1016/j.ecolmodel.2006.12.007
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    1. Michelle C. Mack & Edward A. G. Schuur & M. Syndonia Bret-Harte & Gaius R. Shaver & F. Stuart Chapin, 2004. "Ecosystem carbon storage in arctic tundra reduced by long-term nutrient fertilization," Nature, Nature, vol. 431(7007), pages 440-443, September.
    2. Robert B. McKane & Loretta C. Johnson & Gaius R. Shaver & Knute J. Nadelhoffer & Edward B. Rastetter & Brian Fry & Anne E. Giblin & Knut Kielland & Bonnie L. Kwiatkowski & James A. Laundre & Georgia M, 2002. "Resource-based niches provide a basis for plant species diversity and dominance in arctic tundra," Nature, Nature, vol. 415(6867), pages 68-71, January.
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    1. Soussana, Jean-François & Maire, Vincent & Gross, Nicolas & Bachelet, Bruno & Pagès, Loic & Martin, Raphaël & Hill, David & Wirth, Christian, 2012. "Gemini: A grassland model simulating the role of plant traits for community dynamics and ecosystem functioning. Parameterization and evaluation," Ecological Modelling, Elsevier, vol. 231(C), pages 134-145.

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