Modeling carbon allocation in trees: a search for principles
(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:
https://lup.lub.lu.se/record/2890617
- author
- Franklin, Oskar ; Johansson, Jacob LU ; Dewar, Roderick C. ; Dieckmann, Ulf ; McMurtrie, Ross E. ; Brannstrom, Ake and Dybzinski, Ray
- organization
- publishing date
- 2012
- 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
- pmid:22278378
- ISSN
- 1758-4469
- DOI
- 10.1093/treephys/tpr138
- language
- English
- LU publication?
- yes
- id
- 0883a26e-b594-46ae-b2a9-89c7702beea6 (old id 2890617)
- date added to LUP
- 2016-04-01 14:01:09
- date last changed
- 2022-04-22 00:55:01
@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}},
keywords = {{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}},
doi = {{10.1093/treephys/tpr138}},
volume = {{32}},
year = {{2012}},
}