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What ecosystems really are—Physicochemical or biological entities?

Author

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  • Schizas, Dimitrios
  • Stamou, George

Abstract

Classical systems ecology in the style of Howard Odum wasn’t genuinely holistic. Odum reduced ecological phenomena to storages, fluxes and transformations of energy and by doing so he undermined the autonomy of ecological science. To surmount this situation, Patten and coworkers offer an alternative framework, namely environ analysis. Resulting in novel ontological perspectives, environ analysis attempts to represent phenomena that are characteristically biological in nature, rather than purely physical or chemical. However, Patten and coworkers do not assign autonomy to ecosystem processes related to these phenomena and lead themselves to the “reductionist trap”. In an effort to escape this trap they throw off the traditional ecosystem models and proceed to methodological reforms. This way, they finally achieve to partly outmatch the reductionism associated traditionally with Systems Ecology, although the holding to a framework which overrates prediction probably jeopardizes the whole enterprise.

Suggested Citation

  • Schizas, Dimitrios & Stamou, George, 2007. "What ecosystems really are—Physicochemical or biological entities?," Ecological Modelling, Elsevier, vol. 200(1), pages 178-182.
    • Handle: RePEc:eee:ecomod:v:200:y:2007:i:1:p:178-182
    DOI: 10.1016/j.ecolmodel.2006.07.014
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    Cited by:

    1. Schizas, Dimitrios & Stamou, George, 2010. "Beyond identity crisis: The challenge of recontextualizing ecosystem delimitation," Ecological Modelling, Elsevier, vol. 221(12), pages 1630-1635.
    2. Ginzburg, Lev R. & Jensen, Christopher X.J. & Yule, Jeffrey V., 2007. "Aiming the “unreasonable effectiveness of mathematics” at ecological theory," Ecological Modelling, Elsevier, vol. 207(2), pages 356-362.
    3. Santos, Mário & Bastos, Rita & Cabral, João Alexandre, 2013. "Converting conventional ecological datasets in dynamic and dynamic spatially explicit simulations: Current advances and future applications of the Stochastic Dynamic Methodology (StDM)," Ecological Modelling, Elsevier, vol. 258(C), pages 91-100.

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