Mitigating land degradation caused by wildfire: Application of the PESERA model to fire-affected sites in central Portugal

Wildfires represent an important agent of land degradation in temperate sub-humid ecosystems, including southern European Mediterranean countries. Identification of integrated conservation approaches that can reduce or prevent degradational impacts is the aim of the EU-funded DESIRE research program, part of which is concerned with quantifying the likely benefit of acceptable alternative conservation strategies to wildfire. The overall aim of this paper is to apply a modification of the Pan-European Soil Erosion Risk Assessment (PESERA) model in order to compare predicted soil erosion rates of one possible conservation strategy, the regular application of prescribed fire, with that of wildfire. The model is applied to two fire-prone study areas in central Portugal (Góis and Mação) and predicts runoff and erosion at much larger spatial (regional) and temporal (decadal) scales than is usually possible with field monitoring. Simulation using the model was carried out for 50 years based on a historical climate time-series. Even assuming very frequent management burns (every 2 years) and infrequent wildfires (100 years), the model suggests that this conservation measure can generally reduce soil erosion relative to infrequent wildfires, although the predicted soil losses for both types of fire are large compared even with those obtained from small-scale field monitoring. The benefits, limitations, scope for improvement and application to future climatic scenarios of the model in a fire context are discussed.

► Post-fire main modelled effects: loss of vegetation, increasing soil erodibility.
► Modelling of forest fire dynamics and post-fire recovery is still exploratory.
► Further analysis of field data for the study sites is still needed.
► PESERA appears to over-estimate post-fire soil erosion of thin stony soils.
► Promising alternative route for assessing medium- to long-term impacts of wildfires.