Probabilistic Wildfire Risk Assessment and Modernization Transitions: The Case of Greece

Abstract

Wildfire is the primary cause of deforestation in fire-prone environments, disrupting the forest transition process generated by multiple social-ecological drivers of modernization. Given the positive feedback between climate change and wildfire-driven deforestation, it seems necessary to abstract the primary- or micro-characteristics of wildfire event(s) and focus on the general behavior of the phenomenon across time and space. This paper intends to couple wildfire self-organizing criticality theory (SOC) and modernization statistics to propose a verisimilar explanation of the phenomenon’s evolution in the past decades and a prediction of its trends in Greece. We use power law distributions of the fire frequency–magnitude relationship to estimate the basic SOC parameters and the Weibull reliability method to calculate large-size wildfires’ conditional probability as a time function. We use automatic linear modeling to search for the most accurate relationship between wildfire metrics and the best subset of modernization predictors. The discussion concentrates on reframing the political debate on fire prevention vs. suppression, its flaws and limitations, and the core challenges for adopting more efficient wildfire management policies in Greece.