A solution to the growing problem of catastrophic wildfires in Greece will require a more holistic fuel management strategy that focuses more broadly on landscape fire behavior and risk in relation to suppression tactics and ignition prevention. Current fire protection planning is either non-existent or narrowly focused on reducing fuels in proximity to roads and communities where ignitions are most likely. A more effective strategy would expand the treatment footprint to landscape scales to reduce fire intensity and increase the likelihood of safe and efficient suppression activities. However, expanding fuels treatment programs on Greek landscapes that are highly fragmented in terms of land use and vegetation requires: (1) a better understanding of how diverse land cover types contribute to fire spread and intensity; and (2) case studies, both simulated and empirical, that demonstrate how landscape fuel management strategies can achieve desired outcomes in terms of fire behavior. In this study, we used Lesvos Island, Greece as a study area to characterize how different land cover types and land uses contribute to fire exposure and used wildfire simulation methods to understand how fire spreads among parcels of forests, developed areas, and other land cover types (shrublands, agricultural areas, and grasslands) as a way to identify fire source–sink relationships. We then simulated a spatially coordinated fuel management program that targeted the fire prone conifer forests that generally burn under the highest intensity. The treatment effects were measured in terms of post-treatment fire behavior and transmission. The results demonstrated an optimized method for fuel management planning that accounts for the connectivity of wildfire among different land types. The results also identified the scale of risk and the limitations of relying on small scattered fuel treatment units to manage long-term wildfire risk.

Climate change has the potential to influence many aspects of wildfire behavior and risk. During the last decade, Greece has experienced large-scale wildfire phenomena with unprecedented fire behavior and impacts. In this study, thousands of wildfire events were simulated with the Minimum Travel Time (MTT) fire growth algorithm (called Randig) and resulted in spatial data that describe conditional burn probabilities, potential fire spread and intensity in Messinia, Greece. Present (1961–1990) and future (2071–2100) climate projections were derived from simulations of the KNMI regional climate model RACMO2, under the SRES A1B emission scenario. Data regarding fuel moisture content, wind speed and direction were modified for the different projection time periods to be used as inputs in Randig. Results were used to assess the vulnerability changes for certain values-at-risk of the natural and human-made environment. Differences in wildfire risk were calculated and results revealed that larger wildfires that resist initial control are to be expected in the future, with higher conditional burn probabilities and intensities for extensive parts of the study area. The degree of change in the modeled Canadian Forest Fire Weather Index for the two time periods also revealed an increasing trend in frequencies of higher values for the future.