Understanding the heterogeneity of social preferences for fire prevention management

Author

Varela, Elsa

Jacobsen, Jette B.

Soliño Millán, Mario

Publication date

2020-11-10T12:29:50Z

2020-11-10T12:29:50Z

2014-08-09



Abstract

The forest area burnt annually in the European Mediterranean region has more than doubled since the 1970s. In these forests, the main preventive action consists of forest compartmentalization by fuel break networks, which entail high costs and sometimes significant negative impacts. While many studies look at public preferences for fire suppression, this study analyses the heterogeneity of social preferences for fire prevention. The visual characteristics of fire prevention structures are very familiar to respondents, but their management is unfamiliar, which raises specific attention in terms of analysing preference heterogeneity. A random parameter logit model revealed large heterogeneity and preference for traditional heavy machinery, maintaining linear unshaded fuel breaks at a high density. A latent class model showed that this may be reflected by a third of the population preferring lighter machinery and shaded irregular fuel breaks; a quarter of the population not treating the budget constraint as limiting, another quarter only being worried about the area burnt and the remaining group being against everything. Finally, a discrete mixture model revealed extreme preference patterns for the density of fuel breaks. These results are important for designing fire prevention policies that are efficient and acceptable by the population.


Funding from the Spanish National Research Council (CSIC) (20060569) is acknowledged.

Document Type

Article
Submitted version

Language

English

Subjects and keywords

Forest fires; Fuel breaks; Choice modelling; Random parameter logit; Latent class model; Discrete mixture model

Publisher

Elsevier

Related items

Versió preprint del document publicat a: https://doi.org/10.1016/j.ecolecon.2014.07.014

Ecological Economics, 2014, vol. 106, p. 91-104

Rights

(c) Elsevier, 2014

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