Modelling and assessing the factors that drive forest fire ignitions is critical for fire prevention and sustainable ecosystem management. In southern Europe, the anthropogenic component of wildland fire ignitions is especially relevant. In the Alps, however, the role of fire as a component of disturbance regimes in forest and grassland ecosystems is poorly known. The aim of this work is to model the probability of fire ignition for an alpine region in Italy using a regional wildfire archive (1995–2009) and MaxEnt modeling. We analyzed separately: i) winter forest fires; ii) winter fires on grasslands and fallow land; iii) summer fires. Predictors were related to morphology, climate, and land use; distance from infrastructures, number of farms, and number of grazing animals were used as proxies for the anthropogenic component; collinearity among predictors was reduced by a Principal Component Analysis. 30 % of ignitions occurred in agricultural areas, 24 % in forests. Ignitions peaked in the late winter–early spring. Negligence from agro-silvicultural activities was the main cause of ignition (64 %); lightning accounted for 9 % of causes across the study timeframe, but increased from 6 % to 10 % between the first and second period of analysis. Models for all groups of fire had a high goodness of-fit (AUC 0.90–0.95). Temperature was proportional to the probability of ignition, and precipitation inverse proportional. Proximity from infrastructures had an effect only on winter fires, while the density of grazing animals had a remarkably different on summer (positive correlation) and winter (negative) fires. Implications are discussed regarding climate change, fire regime changes, and silvicultural prevention. Such spatially explicit approach allows to carry out spatially targeted fire management strategies, and may assist in developing better fire management plans.

Modeling anthropogenic and natural fire ignitions in an inner-alpine valley

Vacchiano, Giorgio;Berretti, Roberta;Motta, Renzo
Last
2017-01-01

Abstract

Modelling and assessing the factors that drive forest fire ignitions is critical for fire prevention and sustainable ecosystem management. In southern Europe, the anthropogenic component of wildland fire ignitions is especially relevant. In the Alps, however, the role of fire as a component of disturbance regimes in forest and grassland ecosystems is poorly known. The aim of this work is to model the probability of fire ignition for an alpine region in Italy using a regional wildfire archive (1995–2009) and MaxEnt modeling. We analyzed separately: i) winter forest fires; ii) winter fires on grasslands and fallow land; iii) summer fires. Predictors were related to morphology, climate, and land use; distance from infrastructures, number of farms, and number of grazing animals were used as proxies for the anthropogenic component; collinearity among predictors was reduced by a Principal Component Analysis. 30 % of ignitions occurred in agricultural areas, 24 % in forests. Ignitions peaked in the late winter–early spring. Negligence from agro-silvicultural activities was the main cause of ignition (64 %); lightning accounted for 9 % of causes across the study timeframe, but increased from 6 % to 10 % between the first and second period of analysis. Models for all groups of fire had a high goodness of-fit (AUC 0.90–0.95). Temperature was proportional to the probability of ignition, and precipitation inverse proportional. Proximity from infrastructures had an effect only on winter fires, while the density of grazing animals had a remarkably different on summer (positive correlation) and winter (negative) fires. Implications are discussed regarding climate change, fire regime changes, and silvicultural prevention. Such spatially explicit approach allows to carry out spatially targeted fire management strategies, and may assist in developing better fire management plans.
2017
1
29
Disturbance regime, Forest fire, MaxEnt, risk model, PCA, ignition
Vacchiano, Giorgio; Foderi, Cristiano; Berretti, Roberta; Marchi, Enrico; Motta, Renzo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1661979
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