Wildfires are a major ecological disturbance in Mediterranean environments, and affect together natural resources, ecosystem services and human activities. The impact of socioeconomic forces on wildfire regimes is generally less investigated than the effects of biophysical drivers. Being grounded on a multi-model regression analysis of socioeconomic and territorial indicators, the present study identifies relevant factors influencing local-scale wildfires’ regimes in Italy. An economically-disadvantaged context with persistent unemployment, rural poverty, social inequalities and population aging proved to be associated to more frequent fire events. Additionally, our analysis points out that occurrence, average size and density of wildfires reflect different correlation profiles with the local-scale socioeconomic context. Along with the socioeconomic profile of local communities, the empirical outcomes of our study show the importance of landscape structure, land-use and cropping systems in local-scale fire regimes. The empirical results of this study justify a multidimensional analysis of relevant socioeconomic dimensions in fire risk assessment and contribute to an informed approach to wildfire management. Moreover, our study provides basic knowledge advancing research on fire prevention, and informing spatial planning and developmental policies aimed at increasing preparedness to large fires.

Ranking the importance of Wildfires’ human drivers through a multi-model regression approach / Mancini, L. D.; Corona, P.; Salvati, L.. - In: ENVIRONMENTAL IMPACT ASSESSMENT REVIEW. - ISSN 0195-9255. - 72:(2018), pp. 177-186. [10.1016/j.eiar.2018.06.003]

Ranking the importance of Wildfires’ human drivers through a multi-model regression approach

Salvati L.
2018

Abstract

Wildfires are a major ecological disturbance in Mediterranean environments, and affect together natural resources, ecosystem services and human activities. The impact of socioeconomic forces on wildfire regimes is generally less investigated than the effects of biophysical drivers. Being grounded on a multi-model regression analysis of socioeconomic and territorial indicators, the present study identifies relevant factors influencing local-scale wildfires’ regimes in Italy. An economically-disadvantaged context with persistent unemployment, rural poverty, social inequalities and population aging proved to be associated to more frequent fire events. Additionally, our analysis points out that occurrence, average size and density of wildfires reflect different correlation profiles with the local-scale socioeconomic context. Along with the socioeconomic profile of local communities, the empirical outcomes of our study show the importance of landscape structure, land-use and cropping systems in local-scale fire regimes. The empirical results of this study justify a multidimensional analysis of relevant socioeconomic dimensions in fire risk assessment and contribute to an informed approach to wildfire management. Moreover, our study provides basic knowledge advancing research on fire prevention, and informing spatial planning and developmental policies aimed at increasing preparedness to large fires.
2018
Anthropogenic factors; Fire risk; Italy; Logistic regression; Non-linear models
01 Pubblicazione su rivista::01a Articolo in rivista
Ranking the importance of Wildfires’ human drivers through a multi-model regression approach / Mancini, L. D.; Corona, P.; Salvati, L.. - In: ENVIRONMENTAL IMPACT ASSESSMENT REVIEW. - ISSN 0195-9255. - 72:(2018), pp. 177-186. [10.1016/j.eiar.2018.06.003]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1647925
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