A numerical model for linking soil organic matter decay and wildfire severity
Revista : Ecological ModellingVolumen : 447
Número : 1
Tipo de publicación : ISI Ir a publicación
Abstract
Wildfires are a critical phenomenon in terrestrial ecosystems, and the intensity and frequency of these events have increased in recent years. High temperatures in the topsoil during wildfires can induce changes in soil physical, chemical, and biological properties due to the loss of soil organic matter (SOM). Therefore, the main objective of this study was to develop a numerical model to predict SOM decay during wildfire events. The model identifies the main parameters controlling SOM decay and predicts its decline by coupling the energy balance for soil heating and species conservation for water and SOM using high temperature-induced vaporization and combustion kinetics. Fluid flow was not included; however, the radiative energy conducted through soil pores was incorporated as a volumetric pore radius function. When the radiative term in the thermal conductivity was not considered, the model predicted the soil thermal evolution with a determination coefficient r2 > 0.91 and with an r2 > 0.98 when the volumetric pore radius was adjusted. The main parameters controlling SOM decay were soil texture, oxygen availability, and initial soil water and SOM contents. SOM decay was also dependent on the wildfire temperature and exposure time. In terms of soil texture, SOM decay increases as sand increases or clay reduces. The main results showed that the soil water content controlled the amount of heat consumed during vaporization, the normalized SOM decay does not depend on the initial SOM content, and the restricted oxidation limited SOM decay. Finally, this study reduces the number of parameters when studying SOM decay and second-order fire effects for post-fire assessment and restoration. Also, because it provides a better under- standing of how wildfires affect SOM, implemented as an additional routine, the model can enhance other existing computer models for describing ecological processes.