Application of an ecological framework linking scales based on self-thinning.

Ecol Appl

CRC for Greenhouse Accounting, Research School of Biological Sciences, Australian National University, Canberra 0200 Australia.

Published: February 2006

AI Article Synopsis

  • Barnes and Roderick created a theoretical framework for modeling vegetation that connects individual plants to larger-scale populations through a self-thinning mechanism, ensuring mass conservation in the model.* -
  • The framework incorporates the effects of regular and random disturbances, allowing for predictions of dry mass and carbon at the patch and ecosystem levels, with practical examples including pine plantations and mixed forests.* -
  • The model is user-friendly, yielding predictions that align well with data, and it enables the examination of how local data influences broader ecosystem dynamics, all while having a general formulation with an analytical solution for ease of application.*

Article Abstract

Barnes and Roderick developed a generic, theoretical framework for vegetation modeling across scales. Inclusion of a self-thinning mechanism connects the individual to the larger-scale population and, being based on the conservation of mass, all mass flux processes are integral to the formulation. Significantly, disturbance (both regular and stochastic) and its impact at larger scales are included in the formulation. The purpose of this paper is to illustrate how this model can be used to predict patch and ecosystem dry mass, and consequently system carbon. Examples from pine plantations and mixed forests are considered, with these applications requiring estimates of system carrying capacity and the growth rates of individual plants. The results indicate that the model is relatively simple and straightforward to apply, and its predictions compare well with the data. A significant feature of this approach is that the impact of local scale data on the dynamics of larger patch and ecosystem scales can be determined explicitly, as we show by example. Further, the general formulation has an analytic solution based on characteristics of the individual, facilitating practical and predictive application.

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Source
http://dx.doi.org/10.1890/05-0763DOI Listing

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