Regional Variability and Driving Forces behind Forest Fires in Sweden

Extreme forest fires have been a historic concern in forests in Canada, the Russian Federation, or the USA, and are now becoming an increasing threat in boreal Europe where recent fire events in 2014 and 2018 caught the attention of those in Sweden. Our study objective was to understand the vulnerability of Swedish forests to fire by spatially analyzing historical burned areas and linking fire events with weather, landscape, and fire-related socioeconomic factors. We developed an extensive database at 1 × 1 km2 homogenous grid, where monthly areas burned in a forest were derived from the MODIS FireCCI51 dataset. Spatial factors, including camping sites, lakes, and roads, topographic features, including aspect, slope, and mean elevation, population density, forest management intensity, and forest stand volume, were collected from various sources and pre-processed. Monthly Fine Fuel Moisture Code (FFMC) values over 2011–2018 were calculated from daily weather data by IIASA’s FLAM model. To include new factors into FLAM, we developed a random forest model to assess the spatial probabilities of burned areas. Due to Sweden’s geographical diversity, the fire dynamics vary between six biogeographical zones. Therefore, the model was applied to each zone separately. As an outcome, we obtained probabilities of burned areas in the forests across Sweden and optimized thresholds. Observed burned areas were well captured by the model. Result accuracy differs with respect to zones; area under the curve (AUC) was 0.875 and 0.94 for zones with a few fires, but above 0.95 for zones with a higher number of fire events. Feature importance analysis and its variability across Sweden provide important information to understand the factors behind forest fires. FFMC, population and road densities, slope and aspect, and forest stand volume were found to be among the key fire-related factors in Sweden. Our modeling approach can be extended to hotspot mapping in other Boreal regions

Sintered glass-ceramic matrix composites made from Latvian silicate wastes

Powder technology and sintering were used to fabricate glass-ceramic matrix composites from Latvian industrial wastes and alumina platelets reinforcement. The optimization of the sintering behaviour of glass-ceramic compositions containing clay and alumina platelets was carried out. Highly crystalline and dense products (> 90 % theoretical density) were fabricated by sintering at temperatures in the range 1040 to 1060 °C, depending on composition. Addition of waste glass to influence the sintering temperature and sintering interval was also investigated. Composites showed higher fracture strength (up to 97 MPa) and hardness than unreinforced glass-ceramics. The "best" composition in terms of density and mechanical properties contained 20 wt% alumina platelets. The matrix exhibited a microstructure composed mainly of elongated crystals of pyroxene type in a residual glassy matrix. These composites are candidates for applications as building materials, such as floor and wall tiles, and for manufacturing machine elements and parts

Regional Variability and Driving Forces behind Forest Fires in Sweden

Extreme forest fires have been a historic concern in the forests of Canada, the Russian Federation, and the USA, and are now an increasing threat in boreal Europe, where recent fire events in 2014 and 2018 drew attention to Sweden. Our study objective was to understand the vulnerability of Swedish forests to fire by spatially analyzing historical burned areas, and to link fire events with weather, landscape, and fire-related socioeconomic factors. We developed an extensive database of 1 × 1 km2 homogenous grids, where monthly burned areas were derived from the MODIS FireCCI51 dataset. The database consists of various socio-economic, topographic-, forest-, and weather-related remote sensing products. To include new factors in the IIASA’s FLAM model, we developed a random forest model to assess the spatial probabilities of burned areas. Due to Sweden’s geographical diversity, fire dynamics vary between six biogeographical zones. Therefore, the model was applied to each zone separately. As an outcome, we obtained probabilities of burned areas in the forests across Sweden and observed burned areas were well captured by the model. The result accuracy differs with respect to zone; the area under the curve (AUC) was 0.875 and 0.94 for zones with few fires, but above 0.95 for zones with a higher number of fire events. Feature importance analysis and their variability across Sweden provide valuable information to understand the reasons behind forest fires. The Fine Fuel Moisture Code, population and road densities, slope and aspect, and forest stand volume were found to be among the key fire-related factors in Sweden. Our modeling approach can be extended to hotspot mapping in other boreal regions and thus is highly policy-relevant. Visualization of our results is available in the Google Earth Engine Application

Modeling risks of climate-driven wildfires in boreal forest: the FLAM approach

Extreme forest fires have been a historic concern in the forests of Canada, the Russian Federation, and the USA,and are now an increasing threat in boreal Europe. We will present approaches to modeling wildfire dynamicsusing the wildFire cLimate impacts and Adaptation Model (FLAM) being developed at the International Instituteof Applied Systems Analysis (IIASA). FLAM operates on a daily time step and uses mechanistic algorithms toparametrize the impacts of climate, human activities, and fuel availability on wildfire probabilities, frequencies,and burned areas. Model validation on historical GIS and remote sensing data and future projections underclimate change scenarios will be discussed at various scales and resolutions for the boreal forest. We willpresent modeling results for the boreal forest, including: (i) simulation of burned areas and adaptation options;(ii) projections of burned areas driven by climate change scenarios until 2100; (iii) regional variability and drivingforces behind forest fires in Sweden. Our results support international analyses that, irrespective of changes inmanagement, it is evident that climate change is very likely to increase the frequency and impact of wildlandfires in the coming decades, also in the boreal forest

Modeling wildfire dynamics and future projections under climate change scenarios: the FLAM approach

We will present approaches to modeling wildfire dynamics using the IIASA’s wildFire cLimate impacts and Adaptation Model (FLAM). FLAM operates with a daily time step and uses mechanistic algorithms to parametrize the impacts of climate, human activities, and fuel availability on wildfire probabilities, frequencies, and burned areas. Validation on historical data and future projections under climate change scenarios will be discussed at various scales and resolutions. We will present results for the following case-studies: (i) projections of global burned areas driven by climate change scenarios until 2100; (ii) modeling burned areas and adaptation options in Europe; (iii) modeling burned areas and their feedback to land-use change in Indonesia with a particular emphasis on extreme fires due the impacts of El Niño southern oscillation using historical data and the delta approach for future scenarios; (iv) regional variability and driving forces behind forest fires in Sweden. Our results support international analyses that, irrespective of changes in management, it is evident that climate change is very likely to increase the frequency and impact of wildland fires in the coming decades

Additional file 2: Figure S1. of Detailed analysis of c-di-GMP mediated regulation of csgD expression in Salmonella typhimurium

Complementation of rdar morphotype and csgD expression by cyclic di-GMP turnover proteins. Figure S2. CsgD levels and rdar morphotype formation of S. typhimurium UMR1 upon expression of the GGDEF-EAL protein STM1703 and its catalytic mutants. Figure S3. STM1827 regulates rdar morphotype and csgD expression by degrading the global pools of c-di-GMP. Figure S4. Enhanced rdar morphotype in STM4264 and STM1703 mutants is dependent on the transcriptional regulators RpoS and OmpR. Figure S5. Effect of c-di-GMP signalling on translation and functionality of CsgD. Figure S6. Schematic representation of GGDEF/EAL proteins and mutants used in the study. (DOCX 1739 kb

Additional file 1: Table S1. of Detailed analysis of c-di-GMP mediated regulation of csgD expression in Salmonella typhimurium

Strains and plasmids, Table S2. Primers and references to supplementary material. (DOCX 40 kb