Dynamic Global Vegetation Models: Searching for the balance between demographic process representation and computational tractability

• Published in: PLOS climate Vol. 1; no. 9; p. e0000068
• Main Authors: Argles, Arthur P. K., Moore, Jonathan R., Cox, Peter M.
• Format: Journal Article
• Language: English
• Published: San Francisco Public Library of Science 01.09.2022
• Subjects: Atmospheric composition; Atmospheric models; Biodiversity; Biogeography; Biomass; Boxes; Carbon; Carbon sequestration; Carbon sinks; Climate change; Competition; Complexity; Computer applications; Demographics; Demography; Disturbances; Ecosystems; Forests; Land use; Precipitation; Representations; Structure-function relationships; Vegetation; Vegetation type
• DOI: 10.1371/journal.pclm.0000068
• ISSN: 2767-3200

Vegetation is subject to multiple pressures in the 21st century, including changes in climate, atmospheric composition and human land-use. Changes in vegetation type, structure, and function also feed back to the climate through their impact on the surface-atmosphere fluxes of carbon and water. Dynamic Global Vegetation Models (DGVMs), are therefore key component of the latest Earth System Models (ESMs). Model projections for the future land carbon sink still span a wide range, in part due to the difficulty of representing complex ecosystem and biogeochemical processes at large scales (i.e. grid lengths ≈ 100km). The challenge for developers of DGVMs is therefore to find an optimal balance between detailed process representation and the ability to scale-up. We categorise DGVMs into four groups; Individual, Average Area, Two Dimensional Cohort and One Dimensional Cohort models. From this we review popular methods used to represent dynamic vegetation within the context of Earth System modelling. We argue that the minimum level of complexity required to effectively model changes in carbon storage under changing climate and disturbance regimes, requires a representation of tree size distributions within forests. Furthermore, we find that observed size distributions are consistent with Demographic Equilibrium Theory, suggesting that One Dimensional Cohort models with a focus on tree size, offer the best balance between computational tractability and realism for ESM applications.