327 Modeling of Forest Fire and Evaluation of the Fire Effects on Long Term CO_2 balance in Siberia

2005 ◽  
Vol 2005.15 (0) ◽  
pp. 311-314
Author(s):  
Takemi CHIKAHISA ◽  
Yutaka TABE ◽  
Hajime KAWAGUCHI
Keyword(s):  
Clay Minerals ◽  
2009 ◽  
Vol 44 (2) ◽  
pp. 239-247 ◽  
Author(s):  
P. Nørnberg ◽  
A. L. Vendelboe ◽  
H. P. Gunnlaugsson ◽  
J. P. Merrison ◽  
K. Finster ◽  
...  

AbstractA long-standing unresolved puzzle related to the Danish temperate humid climate is the presence of extended areas with large Fe contents, where goethite and ferrihydrite are present in the topsoil along with hematite and maghemite. Hematite and, particularly, maghemite would normally be interpreted as the result of high temperature as found after forest fires. However, a body of evidence argues against these sites having been exposed to fire. In an attempt to get closer to an explanation of this Fe mineralogy, an experimental forest fire was produced. The results showed a clear mineralogical zonation down to 10 cm depth. This was not observed at the natural sites, which contained a mixture of goethite/ferrihydrite, hematite and maghemite down to 20 cm depth. The experimental forest fire left charcoal and ashes at the topsoil, produced high pH and decreased organic matter content, all of which is in contrast to the natural sites. The conclusion from this work is that the mineralogy of these sites is not consistent with exposure to forest fire, but may instead result from long-term transformation in a reducing environment, possibly involving microbiology.


2017 ◽  
Vol 8 (1) ◽  
pp. 55-62
Author(s):  
Lailan Syaufina ◽  
Vera Linda Purba

Forest fire is one of the problem in forest management. The objectives of the study was to measure the forest fire severity based on soil physical and chemical properties. The forest fire effects were assessed using fire severity method and forest health monitoring plot. The study indicated that the burned areas at BKPH Parung Panjang after two years included in low fire severity. The site properties and growth performance analysis showed that the fire has only affected on pH, Mg and tree diameter significantly, whereas the other parameters such as bulk density, P, N, Na, K, Ca and height were not significantly affected. In addition, both burned and unburned areas are classified as in health condition.Key words : fire severity, forest health monitoring, growth performance, site properties


2017 ◽  
Vol 26 (5) ◽  
pp. 399 ◽  
Author(s):  
Tomaž Šturm ◽  
Tomaž Podobnikar

The aim of this study is to develop a long-term forest fire occurrence probability model in the Karst forest management area of Slovenia. The target area has the greatest forest fire occurrence rates and the largest burned areas in the country. To discover how the forest stand characteristics influence forest fire occurrence, we developed a long-term linear regression model. The geographically weighted regression method was applied to build the model, using forest management plans and land-based datasets as explanatory variables and a past forest fire activity dataset as a predicted variable. The land-based dataset was used to represent human activity as a key component in fire occurrence. Variables representing the natural and the anthropogenic environment used in the model explained 39% of past forest fire occurrences and predicted areas with the highest likelihood of forest fire occurrence. The results show that forest fire occurrence probability in a stand increases with lower wood stock, lower species diversity and lower thickness diversity, and in stands dominated by conifer trees under normal canopy closure. These forests stand characteristics are planned to be used in forest management and silviculture planning to reduce fire damage in Slovenian forests.


2021 ◽  
Author(s):  
Adam F. A. Pellegrini ◽  
Jennifer Harden ◽  
Katerina Georgiou ◽  
Kyle S. Hemes ◽  
Avni Malhotra ◽  
...  

2012 ◽  
Vol 12 (8) ◽  
pp. 2591-2601 ◽  
Author(s):  
H. M. Mäkelä ◽  
M. Laapas ◽  
A. Venäläinen

Abstract. Climate variation and change influence several ecosystem components including forest fires. To examine long-term temporal variations of forest fire danger, a fire danger day (FDD) model was developed. Using mean temperature and total precipitation of the Finnish wildfire season (June–August), the model describes the climatological preconditions of fire occurrence and gives the number of fire danger days during the same time period. The performance of the model varied between different regions in Finland being best in south and west. In the study period 1908–2011, the year-to-year variation of FDD was large and no significant increasing or decreasing tendencies could be found. Negative slopes of linear regression lines for FDD could be explained by the simultaneous, mostly not significant increases in precipitation. Years with the largest wildfires did not stand out from the FDD time series. This indicates that intra-seasonal variations of FDD enable occurrence of large-scale fires, despite the whole season's fire danger is on an average level. Based on available monthly climate data, it is possible to estimate the general fire conditions of a summer. However, more detailed input data about weather conditions, land use, prevailing forestry conventions and socio-economical factors would be needed to gain more specific information about a season's fire risk.


2014 ◽  
Vol 33 (8) ◽  
pp. 827-859
Author(s):  
Shannon L. Swim ◽  
Roger F. Walker ◽  
Dale W. Johnson ◽  
Robert M. Fecko ◽  
Watkins W. Miller

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