Grazia Pellizzaro

Evaluation of FARSITE simulator in Mediterranean maquis

In the last two decades, several models were developed to provide temporal and spatial variations of fire spread and behaviour. The most common models (i.e. BEHAVE and FARSITE) are based on Rothermels original fire spread equation and describe fire spread and behaviour taking into account the influences of fuels, terrain and weather conditions. The use of FARSITE on areas different from those where the simulator was originally developed requires a local calibration to produce reliable results. This is particularly true for Mediterranean ecosystems, where plant communities are characterised by high specific and structural heterogeneity and complexity. To perform FARSITE calibration, an appropriate fuel model or the development of a specific custom fuel model is needed. In this study, FARSITE was employed to simulate three fire events in Mediterranean areas using different fuel models and meteorological input data, and the accuracy of results was analysed. A custom fuel model designed and developed for shrubland vegetation (maquis) provided realistic values of rate of spread, when compared with estimated values obtained using standard fuel models. Our results confirm that the use of both wind field data and appropriate custom fuel models are crucial to obtain reasonable simulations of wildfire events occurring on Mediterranean vegetation during the drought season.

Relationships between seasonal patterns of live fuel moisture and meteorological drought indices for Mediterranean shrubland species

Measurements of seasonal patterns of live fuel moisture content and ignitability (in terms of time to ignition) of four Mediterranean shrub species were performed in North Western Sardinia (Italy). Relationships between the two variables were evaluated. Relationships between live fuel moisture content and environmental conditions (i.e. rainfall, air temperature and soil moisture) were analysed. Two groups of species were identified in relation to the different response of live fuel moisture content to seasonal meteorological conditions. Seasonal patterns of live fuel moisture content were also compared with five meteorological drought indices: Duff Moisture Code and Drought Code of the Canadian Forest Fire Weather Index System, Keetch–Byram Drought Index, Canopy Drought Stress Index and Cumulative Water Balance Index. In addition, the capability of the meteorological drought indices to describe moisture variation for each species was evaluated. Although the Drought Code was formulated to describe changes in the moisture content of dead fuel, it was shown to have a good potential for modelling live fuel moisture variation of a group of shrubland species that are sensitive to meteorological conditions, with a clear and large decrease of moisture content during the drought season.

Seasonal variations of live moisture content and ignitability in shrubs of the Mediterranean basin

The objectives of the present study were (i) to describe the seasonal pattern of ignition delay (ID time) and moisture content of live fine fuel (LFMC) for eight common shrub species of the Western Mediterranean Basin, and (ii) to evaluate the relationships between LFMC and ignitability. The experiment was carried out in a shrubland area located in Sardinia, Italy. LFMC and time to ignition or ID time values were determined monthly or twice a month throughout the year. Ignitability was determined by laboratory tests. Meteorological data were also collected from a weather station located in the study area. Significant linear regression equations of ID time v. LFMC were found for most of the species, with R2 values ranging from 67 to 94%. In general, very low values of ID time were observed when LFMC ranged from 70 to 100%. In addition, two groups of species were identified, depending on seasonal changes of both LFMC and ID time (or ignitability): (i) species with LFMC not greater than 100% and high ignitability values all throughout the year, and (ii) species with large seasonal variability of LFMC and ignitability values that were low in winter and high in summer. Significant differences in ignitability among species were also observed.

Analyzing seasonal patterns of wildfire exposure factors in Sardinia, Italy.

In this paper, we applied landscape scale wildfire simulation modeling to explore the spatiotemporal patterns of wildfire likelihood and intensity in the island of Sardinia (Italy). We also performed wildfire exposure analysis for selected highly valued resources on the island to identify areas characterized by high risk. We observed substantial variation in burn probability, fire size, and flame length among time periods within the fire season, which starts in early June and ends in late September. Peak burn probability and flame length were observed in late July. We found that patterns of wildfire likelihood and intensity were mainly related to spatiotemporal variation in ignition locations, fuel moisture, and wind vectors. Our modeling approach allowed consideration of historical patterns of winds, ignition locations, and live and dead fuel moisture on fire exposure factors. The methodology proposed can be useful for analyzing potential wildfire risk and effects at landscape scale, evaluating historical changes and future trends in wildfire exposure, as well as for addressing and informing fuel management and risk mitigation issues.

Microbial immigration across the Mediterranean via airborne dust.

Dust particles lifting and discharge from Africa to Europe is a recurring phenomenon linked to air circulation conditions. The possibility that microorganisms are conveyed across distances entails important consequences in terms of biosafety and pathogens spread. Using culture independent DNA-based analyses via next generation sequencing of the 16 S genes from the airborne metagenome, the atmospheric microbial community was characterized and the hypothesis was tested that shifts in species diversity could be recorded in relation to dust discharge. As sampling ground the island of Sardinia was chosen, being an ideal cornerstone within the Mediterranean and a crossroad of wind circulation amidst Europe and Africa. Samples were collected in two opposite coastal sites and in two different weather conditions comparing dust-conveying winds from Africa with a control situation with winds from Europe. A major conserved core microbiome was evidenced but increases in species richness and presence of specific taxa were nevertheless observed in relation to each wind regime. Taxa which can feature strains with clinical implications were also detected. The approach is reported as a recommended model monitoring procedure for early warning alerts in frameworks of biosafety against natural spread of clinical microbiota across countries as well as to prevent bacteriological warfare.

Pollen emission from olive trees and concentrations of airborne pollen in an urban area of North Sardinia

In this study the seasonal and daily variations in olive airborne pollen concentrations were measured in the atmosphere of Sassari (Italy) and the olive pollen emission was monitored in the countryside during the flowering period in 1995 and 1996, in order to detect the patterns of change in the atmosphere. The intensity and the timing of pollination was also studied in relation to phenological stages occurrence. In addition, the influence of the main meteorological parameters on pollen emission and airborne pollen dispersal in the city was assessed. Airborne pollen reached its highest concentration a few days before the peak of pollen emission in 1995 but several days after it in 1996 (6 days). Analysis of hourly concentrations shows that the maximum emission and dispersion recorded during the observation period occurred in the middle of the day. Significant regressions were found between hourly temperature and air humidity values and hourly pollen concentrations recorded in the olive grove for almost every day studied, indicating a negative correlation between humidity and pollen concentration and a positive correlation between pollen concentration and temperature. On the other hand, no significant correlation was observed between the meteorological parameters and pollen concentration recorded in the urban area.

An optimal Cellular Automata algorithm for simulating wildfire spread

Abstract Raster-based methods for simulating wildfire spread are computationally more efficient than vector-based approaches. In spite of this, their success has been limited by the distortions that affect the fire shapes. This work presents a Cellular Automata (CA) approach that is able to mitigate the problem of distorted fire shapes thanks to a redefinition of the spread velocity, where the equations generally used in vector-based approaches are modified by means of some correction factors. A numerical optimization approach is used to find the optimal values for the correction factors. The results are compared to the ones given by two Cellular Automata simulators from the literature under homogeneous conditions. According to this work, the proposed approach provides better results, in terms of accuracy, at a comparable computational cost. The proposed approach has then been compared to Farsite, a vector-based fire-spread simulator, under realistic slope and wind conditions, producing equivalent results in a reduced computational time.

An Improved Cellular Automata for Wildfire Spread

Despite being computationally more efficient than vector-based approaches, the use of raster-based techniques for simulating wildfire spread has been limited by the distortions that affect the fire shapes. This work presents a Cellular Automata approach that is able to mitigate this problem with a redefinition of the spread velocity, where the equations generally used in vector-based approaches are modified by means of a number of correction factors. A numerical optimization approach is used to find the optimal values for the correction factors. The results are compared to the ones given by two well-known Cellular Automata simulators. According to this work, the proposed approach provides better results, at a comparable computational cost.