Prediction of fire occurrence from live fuel moisture content measurements in a Mediterranean ecosystem

The present paper presents and discusses the relationships between live Fuel Moisture Content (FMC) measurements and fire occurrence (number of fires and burned area) in a Mediterranean area of central Spain. Grasslands and four shrub species (Cistus ladanifer L., Rosmarinus officinalis L., Erica australis L. and Phillyrea angustifolia L.) were sampled in the field from the spring to the summer season over a 9-year period. Higher seasonal FMC variability was found for the herbaceous species than for shrubs, as grasslands have very low values in summertime. Moisture variations of grasslands were found to be good predictors of number of fires and total burned surface, while moisture variation of two shrubs (C. ladanifer L. and R. officinalis L.) was more sensitive to both the total burned area and the occurrence of large fires. All these species showed significant differences between the FMC of high and low occurrence periods. Three different logistic regression models were built for the 202 periods of analysis: one to predict periods with more and less than seven fires, another to predict periods with and without large fires (>500 ha), and the third to predict periods with more and less than 200 ha burned. The results showed accuracy in predicting periods with a high number of fires (94%), and extensive burned area (85%), with less accuracy in estimating periods with large fires (58%). Finally, empirical functions based on logistic regression analysis were successfully related to fire ignition or potential burned area from FMC data. These models should be useful to integrate FMC measurements with other variables of fire danger (ignition causes, for instance), to provide a more comprehensive assessment of fire danger conditions.