Plant optimisation modelling

Inspecting plant growth in the RSB CEF

Description

New tools for global change science

When modelling plant and ecosystem responses to changes in environmental variables (atmospheric CO2 concentration, temperature, nutrient and water availability), a fundamental challenge lies in the vast number of underlying physical and biological processes involved.

Over the last 30 years, global change modellers have responded to this challenge largely by developing complex numerical simulation models which couple together many individual processes, each represented by an empirical relationship. Due to their inherent complexity and empiricism, however, these bottom-up models differ greatly in their predictions of how plants and ecosystems will respond to future environmental change.

Optimisation modelling – based on various expressions of “survival of the fittest” (e.g. maximum photosynthesis, maximum growth rate) – offers an alternative and simpler top-down approach. While optimisation has a long pedigree in biological modelling, to date its impact within the global change modelling community has been limited.

We are helping to develop a new generation of plant optimisation models which, unlike bottom-up models, explain and synthesise many of the leaf- and plant-scale responses observed in recent plant elevated CO2 experiments, environmental gradient studies and global leaf trait analyses. We are also comparing traditional plant optimisation models with the Maximum Entropy Production hypothesis – an alternative thermodynamic approach to plant optimisation modelling.

Our ultimate goal is to integrate plant optimisation models into larger-scale coupled vegetation-climate models, in order to make more robust predictions of how the complex interactions between plants and their environment will play out in the future.

Further reading

  • Dewar RC, Tarvainen L, Parker K, Wallin G, McMurtrie RE. 2012. Why does leaf nitrogen decline within tree canopies less rapidly than light? An explanation from optimization subject to a lower bound on leaf mass per area. Tree Physiology 31, 520-534.
  • McMurtrie RE, Iversen CM, Dewar RC, Medlyn BE, Näsholm T, Pepper DA, Norby RJ. 2012. Plant root distributions and nitrogen uptake predicted by a hypothesis of optimal root foraging. Ecology & Evolution 2(6), 1235-1250.
  • Franklin O, Johansson J, Dewar RC, Dieckmann U, McMurtrie RE, Brännström Å, Dybzinski R. 2012. Modeling carbon allocation in trees: a search for principles. Tree Physiology 32, 648-666.
  • McMurtrie RE, Dewar RC. 2011. Leaf trait variation explained by the hypothesis that plants maximise their canopy carbon export over the lifespan of leaves. Tree Physiology 31, 1007-1023.
  • Dewar RC. 2010. Maximum entropy production and plant optimization theories. Philosophical Transactions of the Royal Society B (Biological Sciences) 365, 1429-1435. Contribution to Theme Issue (eds. Kleidon A, Cox PM, Mahli Y): Maximum entropy production in ecological and environmental systems: applications and implications.
  • Dewar RC, Franklin O, Mäkelä A, McMurtrie RE, Valentine HT. 2009. Optimal function explains forest responses to global change. BioScience 59(2), 127-139.
  • McMurtrie RE, Norby RJ, Medlyn BE, Dewar RC, Pepper DA, Reich PB, Barton CVM. 2008. Why is plant growth response to CO2 amplified when water is limiting, but reduced when nitrogen is limiting? A growth-optimisation hypothesis. Functional Plant Biology 35, 521-534.

Partnerships

Our collaborators include: Ross McMurtrie (University of New South Wales), Remko Duursma & Belinda Medlyn (Macquarie University), Oskar Franklin (IIAASA, Vienna), Anniki Mäkelä (Helsinki University).

Updated:  17 December 2017/Responsible Officer:  Director RSB/Page Contact:  Webmaster RSB