Task 2.3

Subtask 2.3.1.

Optimizing landscape configuration and fire management policies to minimize expected losses from EWE (UAEGEAN). For that purpose, it will implement the Landscape Treatment Designer (LTD) to quickly test different management policies for the LL of IA 2.4, with results providing information and data to Task 2.4. Stochastic fire simulations with FSim will utilize information and data developed within Task 2.1 and D1.7 and D1.8 to create the necessary inputs; and simulation outputs will be used to estimate landscape locations with expected community (linked to knowledge gained from IA 2.1 and subtask 2.2.2 and other values-at-risk exposure (informed by the findings of IA 2.7), to be considered by LTD runs (linked to IA 2.4). Afterwards, a new optimization approach will implemented to model the expected losses from EWE that integrates directly fire behavior (IA 2.4). The emphasis is on freeing up computational resources to optimize the spatial distribution of novel fire management practices.

Subtask 2.3.2

Designing strategic networks of managed areas to improve suppression efforts against EWE (CTFC). It will implement an integrated system, including an open access data server (e.g., fuels, climatic data, fire hazard, exposed values, infrastructures, etc..), multi-criteria decision analysis, and mathematical optimization, to define how to allocate fuel breaks to mitigate the impact of large fires and facilitate suppression efforts. The emphasis is on generating a network of well managed forest areas/stands, that while taming the behavior of large fires, provides windows of opportunity to firefighters to better attack fires (IA 2.5).

Subtask 2.3.3

Designing post-fire restoration strategies (CTFC, CIGC). It will implement a spatial multi-criteria decision analysis system to define which areas within a large fire perimeter should be prioritized for restoration actions (IA 2.6). A participatory process with experts and end-users will be used to identify which factors, rules, and data, is necessary to select the areas and actions to implement post-fire restoration actions. Once the data on influencing factors is gathered, a multi-criteria analysis will be applied to spatially identify the restoration priority levels. An assessment of spatial layouts of pre-fire vegetation, severity, ecological conditions, monetary and operational constraints will be combined with novel restoration practices, to define where and which actions should be implemented to ensure post-fire recovery. The emphasis is on creating a consistent methodology to identify where to allocate limited budget resources, to maximize the impact of restoration activities in burned areas.