Spatial Optimization and Tradeoffs of Alternative Forest Management Scenarios in Macedonia, Greece

Abstract

Managing forests has been demonstrated to be an efficient strategy for fragmenting fuels and for reducing fire spread rates and severity. However, large-scale analyses to examine operational aspects of implementing different forest management scenarios to meet fire governance objectives are nonexistent for many Mediterranean countries. In this study we described an optimization framework to build forest management scenarios that leverages fire simulation, forest management, and tradeoff analyses for forest areas in Macedonia, Greece. We demonstrated the framework to evaluate five forest management priorities aimed at (1) protection of developed areas, (2) optimized commercial timber harvests, (3) protection of ecosystem services, (4) fire resilience, and (5) reducing suppression difficulty. Results revealed that by managing approximately 33,000 ha across all lands in different allocations of 100 projects, the area that accounted for 16% of the wildfire exposure to developed areas was treated while harvesting 2.5% of total wood volume. The treatments also reduced fuels on the area that are responsible for 3% of the potential fire impacts to sites with important ecosystem services, while suppression difficulty and wildfire transmission to protected areas attainment was 4.5% and 16%, respectively. We also tested the performance of multiple forest district management priorities when applying a proposed four-year fuel treatment plan that targeted achieving high levels of attainment by treating less area but strategically selected lands. Sharp management tradeoffs were observed among all management priorities, especially for harvest production compared with suppression difficulty, the protection of developed areas, and wildfire exposure to protected areas.

Assessing Wildfire Exposure to Communities and Protected Areas in Portugal

“…As with the wildfire exposure in communities (Figure 6A), cumulative exposure charts highlighted the high concentration of most exposure in a reduced portion of the landscape. Previous works conducted in other fire-prone Mediterranean areas also found that most exposure was concentrated in a reduced part of the landscape [48,65]. Interestingly, most exposed areas were manageable land classes, while less than 10% corresponded to non-manageable protected land (Figure 8B).…”

“…Then, the fire spread is predicted using Rothermel's surface fire spread model [43], and fire intensity (kW m −1 ) is converted to flame length (FL) using Byram's equation [44]. The FConstMTT program has been extensively described and widely used in several fire-prone areas worldwide to model wildfire spread and behavior in large landscapes and assess wildfire exposure, transmission, and risk to valued resources and assets [26,[45][46][47][48].…”

Meteorological Analysis of the 2021 Extreme Wildfires in Greece: Lessons Learned and Implications for Early Warning of the Potential for Pyroconvection

“…The temperate forests of southern Greece are mainly composed of species adapted to hot and dry environments, such as Pinus halepensis, Pinus brutia, and most of the evergreen broadleaves [35]. In general, plant biomass is abundant enough to sustain fire spread, mainly due to the unbalanced policy adopted by the Greek state, which heavily promotes fire suppression over sustainable forest management [36]. Therefore, the main factor limiting the extent and severity of wildfires is the moisture content of available fuels.…”

Assessing the effects of alternative fuel treatments to reduce wildfire exposure

“…Simulation modelling has been used for evaluating wildfire exposure and wildfire risk-mitigation strategies from the forest stand scale to the landscape, regional, and national levels (Collins et al 2011;Ager et al 2020). Fire simulation models such as FlamMap (Finney 2006) are increasingly used in the European Union to assess wildfire hazard and risk (Xofis et al 2020;Palaiologou et al 2021;Salis et al 2013), as well as the effects of fuel treatment on wildfire spread and behavior at a landscape scale (Cortes-Molino et al 2020;Molina et al 2021). FlamMap requires gridded geospatial input data on topography and fire behavior prediction (FBP) fuel types, along with weather streams.…”