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Individualism in plant populations: Using stochastic differential equations to model individual neighbourhood-dependent plant growth

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  • Lv, Qiming
  • Schneider, Manuel K.
  • Pitchford, Jonathan W.

Abstract

We study individual plant growth and size hierarchy formation in an experimental population of Arabidopsis thaliana, within an integrated analysis that explicitly accounts for size-dependent growth, size- and space-dependent competition, and environmental stochasticity. It is shown that a Gompertz-type stochastic differential equation (SDE) model, involving asymmetric competition kernels and a stochastic term which decreases with the logarithm of plant weight, efficiently describes individual plant growth, competition, and variability in the studied population. The model is evaluated within a Bayesian framework and compared to its deterministic counterpart, and to several simplified stochastic models, using distributional validation. We show that stochasticity is an important determinant of size hierarchy and that SDE models outperform the deterministic model if and only if structural components of competition (asymmetry; size- and space-dependence) are accounted for. Implications of these results are discussed in the context of plant ecology and in more general modelling situations.

Suggested Citation

  • Lv, Qiming & Schneider, Manuel K. & Pitchford, Jonathan W., 2008. "Individualism in plant populations: Using stochastic differential equations to model individual neighbourhood-dependent plant growth," Theoretical Population Biology, Elsevier, vol. 74(1), pages 74-83.
    • Handle: RePEc:eee:thpobi:v:74:y:2008:i:1:p:74-83
    DOI: 10.1016/j.tpb.2008.05.003
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    References listed on IDEAS

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    3. Renate Meyer & Jun Yu, 2000. "BUGS for a Bayesian analysis of stochastic volatility models," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 198-215.
    4. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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