The Lund–Potsdam–Jena Dynamic Global Vegetation Model (LPJ) combines process‐based, large‐scale representations of terrestrial vegetation dynamics and land‐atmosphere carbon and water exchanges in a modular framework. Features include feedback through canopy conductance between photosynthesis and transpiration and interactive coupling between these ‘fast’ processes and other ecosystem processes including resource competition, tissue turnover, population dynamics, soil organic matter and litter dynamics and fire disturbance. Ten plants functional types (PFTs) are differentiated by physiological, morphological, phenological, bioclimatic and fire‐response attributes. Resource competition and differential responses to fire between PFTs influence their relative fractional cover from year to year. Photosynthesis, evapotranspiration and soil water dynamics are modelled on a daily time step, while vegetation structure and PFT population densities are updated annually. Simulations have been made over the industrial period both for specific sites where field measurements were available for model evaluation, and globally on a 0.5°° × 0.5°° grid. Modelled vegetation patterns are consistent with observations, including remotely sensed vegetation structure and phenology. Seasonal cycles of net ecosystem exchange and soil moisture compare well with local measurements. Global carbon exchange fields used as input to an atmospheric tracer transport model (TM2) provided a good fit to observed seasonal cycles of CO2 concentration at all latitudes. Simulated inter‐annual variability of the global terrestrial carbon balance is in phase with and comparable in amplitude to observed variability in the growth rate of atmospheric CO2. Global terrestrial carbon and water cycle parameters (pool sizes and fluxes) lie within their accepted ranges. The model is being used to study past, present and future terrestrial ecosystem dynamics, biochemical and biophysical interactions between ecosystems and the atmosphere, and as a component of coupled Earth system models.

No abstract

No abstract

Disturbances from fire, wind‐throw, insects and other herbivores are, besides climate, CO2, and soils, critical factors for composition, structure and dynamics of most vegetation. To simulate the influence of fire on the dynamic equilibrium, as well as on potential change, of vegetation at the global scale, we have developed a fire model, running inside the modular framework of the Lund–Potsdam–Jena Dynamic Global Vegetation Model (LPJ‐DGVM). Estimated litter moisture is the main driver of day‐to‐day fire probability. The length of the fire season is used to estimate the fractional area of a grid cell which is burnt in a given year. This affected area is converted into an average fire return interval which can be compared to observations. When driven by observed climate for the 20th century (at a 0.5° longitude/latitude resolution), the model yielded fire return intervals in good agreement with observations for many regions (except parts of semiarid Africa and boreal Siberia). We suggest that further improvement for these regions must involve additional process descriptions such as permafrost and fuel/fire dynamics.

A new fire model is proposed which estimates areas burnt on a macro‐scale (10–100 km). It consists of three parts: evaluation of fire danger due to climatic conditions, estimation of the number of fires and the extent of the area burnt. The model can operate on three time steps, daily, monthly and yearly, and interacts with a Dynamic Global Vegetation Model (DGVM), thereby providing an important forcing for natural competition. Fire danger is related to number of dry days and amplitude of daily temperature during these days. The number of fires during fire days varies with human population density. Areas burnt are calculated based on average wind speed, available fuel and fire duration. The model has been incorporated into the Lund‐Potsdam‐Jena Dynamic Global Vegetation Model (LPJ‐DGVM) and has been tested for peninsular Spain. LPJ‐DGVM was modified to allow bi‐directional feedback between fire disturbance and vegetation dynamics. The number of fires and areas burnt were simulated for the period 1974–94 and compared against observations. The model produced realistic results, which are well correlated, both spatially and temporally, with the fire statistics. Therefore, a relatively simple mechanistic fire model can be used to reproduce fire regime patterns in human‐ dominated ecosystems over a large region and a long time period.