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Modeling carbon allocation in trees: a search for principles

Franklin, Oskar; Johansson, Jacob LU ; Dewar, Roderick C.; Dieckmann, Ulf; McMurtrie, Ross E.; Brannstrom, Ake and Dybzinski, Ray (2012) In Tree Physiology 32(6). p.648-666
Abstract
We review approaches to predicting carbon and nitrogen allocation in forest models in terms of their underlying assumptions and their resulting strengths and limitations. Empirical and allometric methods are easily developed and computationally efficient, but lack the power of evolution-based approaches to explain and predict multifaceted effects of environmental variability and climate change. In evolution-based methods, allocation is usually determined by maximization of a fitness proxy, either in a fixed environment, which we call optimal response (OR) models, or including the feedback of an individual's strategy on its environment (game-theoretical optimization, GTO). Optimal response models can predict allocation in single trees and... (More)
We review approaches to predicting carbon and nitrogen allocation in forest models in terms of their underlying assumptions and their resulting strengths and limitations. Empirical and allometric methods are easily developed and computationally efficient, but lack the power of evolution-based approaches to explain and predict multifaceted effects of environmental variability and climate change. In evolution-based methods, allocation is usually determined by maximization of a fitness proxy, either in a fixed environment, which we call optimal response (OR) models, or including the feedback of an individual's strategy on its environment (game-theoretical optimization, GTO). Optimal response models can predict allocation in single trees and stands when there is significant competition only for one resource. Game-theoretical optimization can be used to account for additional dimensions of competition, e.g., when strong root competition boosts root allocation at the expense of wood production. However, we demonstrate that an OR model predicts similar allocation to a GTO model under the root-competitive conditions reported in free-air carbon dioxide enrichment (FACE) experiments. The most evolutionarily realistic approach is adaptive dynamics (AD) where the allocation strategy arises from eco-evolutionary dynamics of populations instead of a fitness proxy. We also discuss emerging entropy-based approaches that offer an alternative thermodynamic perspective on allocation, in which fitness proxies are replaced by entropy or entropy production. To help develop allocation models further, the value of wide-ranging datasets, such as FLUXNET, could be greatly enhanced by ancillary measurements of driving variables, such as water and soil nitrogen availability. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
tree growth, soil depth, plasticity, partitioning, theory, game, functional balance, acclimation, evolutionarily stable strategy
in
Tree Physiology
volume
32
issue
6
pages
648 - 666
publisher
Oxford University Press
external identifiers
  • wos:000305585000003
  • scopus:84862992239
ISSN
1758-4469
DOI
10.1093/treephys/tpr138
project
BECC
language
English
LU publication?
yes
id
0883a26e-b594-46ae-b2a9-89c7702beea6 (old id 2890617)
date added to LUP
2012-07-25 12:00:02
date last changed
2017-11-05 04:04:49
@article{0883a26e-b594-46ae-b2a9-89c7702beea6,
  abstract     = {We review approaches to predicting carbon and nitrogen allocation in forest models in terms of their underlying assumptions and their resulting strengths and limitations. Empirical and allometric methods are easily developed and computationally efficient, but lack the power of evolution-based approaches to explain and predict multifaceted effects of environmental variability and climate change. In evolution-based methods, allocation is usually determined by maximization of a fitness proxy, either in a fixed environment, which we call optimal response (OR) models, or including the feedback of an individual's strategy on its environment (game-theoretical optimization, GTO). Optimal response models can predict allocation in single trees and stands when there is significant competition only for one resource. Game-theoretical optimization can be used to account for additional dimensions of competition, e.g., when strong root competition boosts root allocation at the expense of wood production. However, we demonstrate that an OR model predicts similar allocation to a GTO model under the root-competitive conditions reported in free-air carbon dioxide enrichment (FACE) experiments. The most evolutionarily realistic approach is adaptive dynamics (AD) where the allocation strategy arises from eco-evolutionary dynamics of populations instead of a fitness proxy. We also discuss emerging entropy-based approaches that offer an alternative thermodynamic perspective on allocation, in which fitness proxies are replaced by entropy or entropy production. To help develop allocation models further, the value of wide-ranging datasets, such as FLUXNET, could be greatly enhanced by ancillary measurements of driving variables, such as water and soil nitrogen availability.},
  author       = {Franklin, Oskar and Johansson, Jacob and Dewar, Roderick C. and Dieckmann, Ulf and McMurtrie, Ross E. and Brannstrom, Ake and Dybzinski, Ray},
  issn         = {1758-4469},
  keyword      = {tree growth,soil depth,plasticity,partitioning,theory,game,functional balance,acclimation,evolutionarily stable strategy},
  language     = {eng},
  number       = {6},
  pages        = {648--666},
  publisher    = {Oxford University Press},
  series       = {Tree Physiology},
  title        = {Modeling carbon allocation in trees: a search for principles},
  url          = {http://dx.doi.org/10.1093/treephys/tpr138},
  volume       = {32},
  year         = {2012},
}