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Effectively tuning plant growth models with different spatial complexity: A statistical perspective

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  • Nakagawa, Yoshiaki
  • Yokozawa, Masayuki
  • Ito, Akihiko
  • Hara, Toshihiko

Abstract

Forest gap models (non-spatial, patch- and individual-based models) and size structure models (non-spatial stand models) rely on two assumptions: the mean field assumption (A-I) and the assumption that plants in one patch do not compete with plants in other patches (A-II). These assumptions lead to differences in plant size dynamics between these models and spatially explicit models (or observations of real forests). Therefore, to more accurately replicate dynamics, these models require model tuning by (1) adjusting model parameter values or (2) introducing a correction term into models. However, these model tuning methods have not been systematically and statistically investigated in models using different patch sizes.

Suggested Citation

  • Nakagawa, Yoshiaki & Yokozawa, Masayuki & Ito, Akihiko & Hara, Toshihiko, 2017. "Effectively tuning plant growth models with different spatial complexity: A statistical perspective," Ecological Modelling, Elsevier, vol. 361(C), pages 95-112.
    • Handle: RePEc:eee:ecomod:v:361:y:2017:i:c:p:95-112
    DOI: 10.1016/j.ecolmodel.2017.07.018
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