Treegrass: a 3D, process-based model for simulating plant interactions in tree-grass ecosystems

Citation
G. Simioni et al., Treegrass: a 3D, process-based model for simulating plant interactions in tree-grass ecosystems, ECOL MODEL, 131(1), 2000, pp. 47-63
Citations number
64
Categorie Soggetti
Environment/Ecology
Journal title
ECOLOGICAL MODELLING
ISSN journal
03043800 → ACNP
Volume
131
Issue
1
Year of publication
2000
Pages
47 - 63
Database
ISI
SICI code
0304-3800(20000630)131:1<47:TA3PMF>2.0.ZU;2-O
Abstract
The function and dynamics of savanna ecosystems result from complex interac tions and feedbacks between grasses and trees, involving numerous processes (i.e. competition for light, water and nutrients, fire, and herbivory). Th ese interactions are characterised by strong relationships between vegetati on structure and function. Given the heterogeneous structure of savannas, m odelling appears as a convenient approach to study tree-grass interactions. Most current models that describe carbon and water fluxes are not spatiall y explicit, which restricts their ability to simulate plant interactions at small scales in heterogeneous ecosystems. We present here a new 3D process -based model called TREEGRASS. The model aims at predicting, in heterogeneo us tree-grass systems, plant individual radiation, carbon and water fluxes at a local spatial scale. It is run at a daily time-step over periods rangi ng from one to a few years. The model includes (i) a 3D mechanistic submode l simulating radiation and energy (i.e. transpiration) budgets; (ii) a soil water balance submodel, and (iii) a physiologically based submodel of prim ary production and leaf area development. The ability of TREEGRASS to predi ct the seasonal courses of grass dead and leaf mass, soil water content and light regime as observed in the field has been tested for grassy and shrub by areas of Lamto savannas (Ivory Coast). Simulations showed that the spati al distribution of primary production can be strongly affected by the spati al vegetation structure. Potential applications involve predicting net prim ary production and water balance from the individual to the ecosystem and f rom the day to the annual vegetation cycle (e.g. effects of tree spatial pa tterns on carbon and water fluxes at the ecosystem level). (C) 2000 Elsevie r Science B.V. All rights reserved.