The increasing global concern about wildfires, mostly caused by people, has triggered the development of human-caused fire occurrence models in many countries. The premise is that better knowledge of the underlying factors is critical for many fire management purposes, such as operational decision-making in suppression and strategic prevention planning, or guidance on forest and land-use policies. However, the explanatory and predictive capacity of fire occurrence models is not yet widely applied to the management of forests, fires or emergencies. In this article, we analyse the developments in the field of human-caused fire occurrence modelling with the aim of identifying the most appropriate variables and methods for applications in forest and fire management and civil protection. We stratify our worldwide analysis by temporal dimension (short-term and long-term) and by model output (numeric or binary), and discuss management applications. An attempt to perform a meta-analysis based on published models proved limited because of non-equivalence of the metrics and units of the estimators and outcomes across studies, the diversity of models and the lack of information in published works.

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Human-caused fire occurrence modelling in perspective: a review

As most of the forest fires in South Korea are related to human activity, socio-economic factors are critical in estimating their probability. To estimate and analyze how human activity is influencing forest fire probability, this study considered not only environmental factors such as precipitation, elevation, topographic wetness index, and forest type, but also socio-economic factors such as population density and distance from urban area. The machine learning Maximum Entropy (Maxent) and Random Forest models were used to predict and analyze the spatial distribution of forest fire probability in South Korea. The model performance was evaluated using the receiver operating characteristic (ROC) curve method, and models’ outputs were compared based on the area under the ROC curve (AUC). In addition, a multi-temporal analysis was conducted to determine the relationships between forest fire probability and socio-economic or environmental changes from the 1980s to the 2000s. The analysis revealed that the spatial distribution was concentrated in or around cities, and the probability had a strong correlation with variables related to human activity and accessibility over the decades. The AUC values for validation were higher in the Random Forest result compared to the Maxent result throughout the decades. Our findings can be useful for developing preventive measures for forest fire risk reduction considering socio-economic development and environmental conditions.

https://www.mdpi.com/2072-4292/11/1/86/pdf

Multi-Temporal Analysis of Forest Fire Probability Using Socio-Economic and Environmental Variables

This paper predicts future changes in fire danger and the fire season in the current century for south-western China under two different climate change scenarios. The fire weather index (FWI) system calculated from daily outputs of a regional climate model with a horizontal resolution of 50 × 50 km was used to assess fire danger. Temperature and precipitation demonstrated a gradually increasing trend for the future. Forest fire statistics for 1987-2011 revealed that the FWI, initial spread index and seasonal severity rating were significantly related to the number of forest fires between 100 and 1000 ha in size. Over three future periods, the FWI component indices will increase greatly. The mean FWI value will increase by 0.83-1.85, 1.83-2.91 and 3.33-3.97 in the periods 2011-2040, 2041-2070 and 2071-2100. The regions with predicted FWI increases are mainly in central and south-eastern China. The fire season (including days with high, very high and extreme fire danger ratings) will be prolonged by 9-13, 18-21 and 28-31 days over these periods. This fire season extension will mainly be due to days with an extreme fire danger rating. Considering predicted future changes in the forest fire danger rating and the fire season, it is suggested that climate change adaptation measures be implemented.

Changes in forest fire danger for south-western China in the 21st century

Tropical bamboo species, which have a very rapid growth rate, are considered as a promising non-timber forest product capable of exhibiting new functionality by carbonization technology. This study was conducted to compare the characteristics of carbonized bamboos from Andong (G. pseuudoarundinacea (Steudel) Widjaja), Hitam (G. atrovialacea), Tali (G. apus), Kuning (B. vulgaris Var. striata (Lodd. Ex Lindl)), and Ampel (B. vulgaris Scharad. ex Wendland), and Betung (D. asper). Each bamboo was carbonized at 200, 400, 600, 800, and 1,000 °C, respectively, and their physical and anatomical characteristics were investigated. The result showed that the volume and weight of carbonized bamboo decreased with increasing carbonization temperature and showed the substantial changes of volume and weight between 200 and 400 °C. The highest and the lowest density of carbonized samples were found in Ampel bamboo and Betung bamboo, respectively. The density of all carbonized bamboos tended to decrease after carbonization at 200 and 400 °C and relatively become constant afterwards. The carbonized bamboo prepared at 800 and 1,000 °C showed better refining degree. The results of the anatomical observation showed that the vascular diameter of carbonized bamboo decreased with increasing carbonization temperature, and the shrinkage in radial and tangential direction showed similar tendency. Statistical analysis showed that there was significant correlation between physical contraction and anatomical contraction. Based on the results of this study, comprehensive data about Indonesian bamboo charcoals could be obtained and it will be useful for future application studies.

Anatomical and Physical Properties of Indonesian Bamboos Carbonized at Different Temperatures

Preventing and suppressing forest fires is one of the main tasks of forestry agencies to reduce resource loss and requires a thorough understanding of the importance of factors affecting their occurrence. This study was carried out in forest plantations on Maoer Mountain in order to develop models for predicting the moisture content of dead fine fuel using meteorological and soil variables. Models by Nelson (Can J For Res 14:597–600, 1984) and Van Wagner and Pickett (Can For Service 33, 1985) describing the equilibrium moisture content as a function of relative humidity and temperature were evaluated. A random forest and generalized additive models were built to select the most important meteorological variables affecting fuel moisture content. Nelson's (Can J For Res 14:597–600, 1984) model was accurate for Pinus koraiensis, Pinus sylvestris, Larix gmelinii and mixed Larix gmelinii—Ulmus propinqua fuels. The random forest model showed that temperature and relative humidity were the most important factors affecting fuel moisture content. The generalized additive regression model showed that temperature, relative humidity and rain were the main drivers affecting fuel moisture content. In addition to the combined effects of temperature, rainfall and relative humidity, solar radiation or wind speed were also significant on some sites. In P. koraiensis and P. sylvestris plantations, where soil parameters were measured, rain, soil moisture and temperature were the main factors of fuel moisture content. The accuracies of the random forest model and generalized additive model were similar, however, the random forest model was more accurate but underestimated the effect of rain on fuel moisture.

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Prediction model of moisture content of dead fine fuel in forest plantations on Maoer Mountain, Northeast China

The objective of this study was to evaluate the characteristics of charcoals from juvenile woods of albizia (Paraserianthes falcataria), gmelina (Gmelina arborea), mindi (Melia azedarach), and mangium (Acacia mangium). Carbonization was performed at 400, 600, and 800°C for 10 min with a heating rate of 6°C/min. The physical, bioenergetic, and chemical properties were evaluated. Maximum char yield was obtained at 400°C and the increase of carbonization temperature resulted in a decrease of char yield. At the same carbonization temperature, char yield was higher in wood with greater initial density, i.e. ordered from the highest to the lowest: mangium, mindi, gmelina, and albizia. The heating values in all woods increased after carbonization, with maximum values at 600°C. Maximum energy densification ratio and energy yield were obtained at carbonization temperature of 600°C and 400°C, respectively. Char yield of 23.62-39.03%, heating value of 25.16-33.85 kJ/g, energy densification ratio of 1.45-1.72, energy yield of 39.09-60.10%, ash content of 0.80-3.94%, volatile matter of 14.61-38.69%, and fixed carbon of 58.58-83.27% were obtained in all charcoals from juvenile woods and were comparable with those of mature woods, showing suitability for the production of charcoal fuel.

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Carbonization characteristics of juvenile woods from some tropical trees planted in Indonesia

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Predicting the Potential Impact of Climate Change on People–Caused Forest Fire Occurrence in South Korea

The mitogenome of the Siberian flying squirrel Pteromys volans is a circular molecule of 16,514 bp, consisting of a control region and a conserved set of 37 genes containing 13 protein-coding genes...

Phylogenetic position of the Siberian flying squirrel Pteromys volans based on complete mitochondrial genome sequences.

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Hee Mun Chae

Papers

Carbonization characteristics of juvenile woods from some tropical trees planted in Indonesia

Predicting the Potential Impact of Climate Change on People–Caused Forest Fire Occurrence in South Korea

Phylogenetic position of the Siberian flying squirrel Pteromys volans based on complete mitochondrial genome sequences.

Effects of Weather Factors on Fuel Moisture Contents of Forestland in Chuncheon, South Korea