The objective of ModelEco is to develop a biosphere-atmosphere (B-A) model to predict the impacts of large-scale disturbances on the gross primary production (GPP) and evapotranspiration (ET) of forests on the basis of widely available data, i.e. vegetation indices (VI) from satellite imagery and meteorological data. The focus will be on the impacts of wildfires, as wildfire regimes have intensified in many Mediterranean regions, where climate conditions are particularly propitious to fire ignition and spread, and have been spreading to more temperate regions of the planet.
This model will be an important tool for improving climate change predictions. Even though some state-of-the-art climate change models include the impacts of direct CO2 emissions during wildfires, the incorporation of the indirect impacts of wildfires on C fluxes continues to be a major challenge. This can be explained by the complexity of post-fire C fluxes, as post-fire ecosystem recovery depend on a large number of factors related to fire conditions (timing, severity) as well as biotic and abiotic site conditions, including energy and heat balances. For example, recurrent or particularly severe fires can induce regime shifts even in fire-adapted Mediterranean forest ecosystems, compromising spontaneous tree regeneration directly (seedbanks) or indirectly (soil fertility) and promoting their permanent conversion to shrublands. At the same time, however, wildfire impacts on the C cycle have mainly been studied by biometric methods as changes in C pools, while studies of the underlying fluxes have largely focused on 1 process – soil respiration – and typically extrapolated midday point-scale measurements in time and space. Only a handful of studies across the world have assessed post-fire C fluxes at the field/ecosystem scale over 30-min to multi-annual periods, using the eddy-covariance technique. Even fewer studies have monitored eddy-covariance fluxes in a continuous manner from immediately after fire, asis being done by the precursor project FIRE-C-BUDs (PTDC/AGR-FOR/4143/2014 – POCI01-0145-FEDER 016780). The eddy-covariance technique has the additional advantage of simultaneously monitoring ET, thereby allowing to improve our – still limited – understanding of the interactions of C and H2O cycles in burnt areas.
B-A models as envisaged by ModelEco are designed to develop and test competing hypotheses about ecosystem functioning against observations and, if validated, to predict ecosystem responses to novel conditions, in particular due to climate change but also due to changes in management operations.
