Importance of root biomass characterization when simulating forest ecosystems

Abstract

Sensitivity analysis are an important tool to understand ecological models functioning, as well as to identify their most important parameters. In addition, sensitivity analysis can be used to design more effective field sampling regimes to calibrate ecological models. When studying forest ecosystems, quantitative analysis of the underground fraction is much more costly and complicated than studying the aboveground fraction, especially when studying the dynamics of production and decomposition of large and fine tree roots. In this work we show an example of sensitivity analysis of the forest ecosystem model FORECAST to parameters defining biomass, longevity and nitrogen concentration in tree roots. The model was calibrated to simulate two Scots pine (Pinus sylvestris L.) stands in the Pyrenees of Navarre. Results indicate that fine root turnover is the most influential parameter on model's tree growth estimations, followed by fine root N concentration and the root biomass/total tree biomass ratio. Furthermore, the model is more sensitive to root-related parameters when calibrated to simulate poor sites with low productivity capacity and higher nutrient limitation.