LPJ-GUESS Ecosystem Model
We adopted LPJ-GUESS (Smith et al. 2001; other refs), a dynamic vegetation model (DVM) optimised for
regional to global applications, as the ecosystem model for our study. Vegetation dynamics are simulated as
the emergent outcome of growth and competition for light, space and soil resources among woody plant
individuals and a herbaceous understorey in each of a number (NN in this study) of replicate patches
representing ‘random samples’ of each simulated locality or grid cell. Multiple patches are simulated to
account for the distribution within a landscape representative of the grid cell as a whole of vegetation stands
differing in their histories of disturbance and stand development (succession). The simulated plants are
classified into one of a number of plant functional types (PFTs) discriminated by growth form, phenology,
photosynthetic pathway (C3 or C4), bioclimatic limits for establishment and survival and, for woody PFTs,
allometry and life history strategy (see Table NN). The simulations of this study were carried out in ‘cohort
mode,’ in which, for woody PFTs, cohorts of individuals recruited in the same patch in a given year are
represented by a single average individual, and are thus assumed to retain the same size and form as they
grow.
Primary production and plant growth follow the approach of LPJ-DGVM (Sitch et al. 2003). Canopy fluxes
of carbon dioxide and water vapour are calculated by a coupled photosynthesis and stomatal conductance
scheme based on the approach of BIOME3 (Haxeltine & Prentice 1996). The net primary production (NPP)
accrued by an average individual plant each simulation year is allocated to leaves, fine roots and, for woody
PFTs, sapwood, following a set of prescribed allometric relationships for each PFT, resulting in biomass,
height and diameter growth (Sitch et al. 2003). Population dynamics (recruitment and mortality) are
represented as stochastic processes, influenced by current resource status, demography and the life history
characteristics of each PFT (Hickler et al. 2004). Biomass-destroying disturbances are simulated as a
stochastic process, affecting individual patches with an expectation of 0.01 yr−1. In addition, wildfires are
modelled prognostically based on temperature, fuel (litter) load and moisture (Thonicke et al. 2001). Litter
arising from phenological turnover, mortality and disturbances enters the soil decomposition cycle.
Decomposition rates of litter and two soil organic matter (SOM) pools depend on soil temperature and
moisture (Sitch et al. 2003). Soil hydrology follows Gerten et al. (2004).
A detailed description of LPJ-GUESS is available in Smith et al. (2001). We used LPJ-GUESS version 2.1
which includes the PFT set and modifications described in Ahlström et al. (2012).
Cited references
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