Prediction and driving factors of forest fire occurrence in Jilin Province,China

Forest fires are natural disasters that can occur suddenly and can be very damaging,burning thousands of square kilometers.Prevention is better than suppression and prediction models of forest fire occurrence have developed from the logistic regression model,the geographical weighted logistic regression model,the Lasso regression model,the random forest model,and the support vector machine model based on historical forest fire data from 2000 to 2019 in Jilin Province.The models,along with a distribution map are presented in this paper to provide a theoretical basis for forest fire management in this area.Existing studies show that the prediction accuracies of the two machine learning models are higher than those of the three generalized linear regression models.The accuracies of the random forest model,the support vector machine model,geographical weighted logistic regression model,the Lasso regression model,and logistic model were 88.7%,87.7%,86.0%,85.0%and 84.6%,respectively.Weather is the main factor affecting forest fires,while the impacts of topography factors,human and social-economic factors on fire occurrence were similar.

A study of emissions and marker gases from smouldering combustion in Larix gmelinii plantations of the Daxing'an Mountains

Underground fires are characterized by smouldering combustion with a slow rate of spread rate and without flames.Although smouldering combustion releases large amounts of gaseous pollutants,it is difficult to discover by today's forest fire monitoring technologies.Carbon monoxide(CO),nitrogen oxides(NO_(x))and sulfur dioxide(SO_(2))were identified as high concentration marker gases of smouldering combustion-easily-be monitored.According to a two-way ANOVA,combustion time had a significant impact on CO and NO_(x) emissions;smoldering-depth also had a significant impact on NO_(x) emissions but not on CO emissions.Gas emission equations were established by multiple linear regression,C_(co)=156.989-16.626 t and C_(NOx)=3.637-0.252 t-0.039 h.

The effects of humus moisture content on underground fires in a Larix gmelinii plantation

Underground fires are a smoldering combustion with a slow spread rate, low temperatures and no flame. They can last from days to several months, and can even become overwintering fires. They are difficult to find, leading to considerable damage to the forests. The moisture content of combustible fuels is an important factor in the occurrence and persistence of underground forest fires. The Daxing’an Mountains are a hot spot for underground fires in China. This paper looks at the influence of different moisture contents on underground fire characteristics using simulation combustion experiments in the laboratory. The study showed that peak temperature and spread rate fluctuation of humus at different moisture levels increased with humus depth. Peak temperature and spread rate fluctuation of humus at different depths decreased with increased moisture;moisture content and depth of humus had a significant effect on peak temperature and spread rate fluctuation;peak temperature at different depths decreased with increased moisture;the spread rate in upper layers increased with moisture content, while the spread rate in the lower layers decreased with increased moisture content.

The distribution patterns and temporal dynamics of carabid beetles(Coleoptera:Carabidae)in the forests of Jiaohe,Jilin Province,China

Carabid beetles,predatory insects,are abundant in forests and sensitive to environmental changes.The distribution patterns and diversity of carabid beetles in several natural forests were studied to provide a basis for evaluating the importance of a forest in the protection of carabid beetle diversity.Carabids were captured by pitfall traps during their seasonal activity from 2012 to 2013 in a poplar-birch forest,ash-walnut forest and broad-leaved Korean pine forest.A total of 5252 individuals,representing 21 species,were collected.Carabid abundance was highest in the broad-leaved Korean pine forest and lowest in the ash-walnut forest.Carabus billbergi Mannerheim and Pterostichus pertinax(Tschitscherine)were the dominant beetle species in each stand.Carabus canaliculatus Adams was dominant in the poplar-birch and ash-walnut forests,and Leistus niger Gebler was dominant in the ash-walnut forest.The carabids were affected differently by stand factors.C.billbergi and P.pertinax was positively correlated with mean DBH.C.canaliculatus and L.niger were not positively correlated with any stand factors.The broad-leaved Korean pine forest with greater age,large DBH and thick leaf litter fostered a high diversity of carabid species.The main yearly activity period for most carabids was during July.Different carabid species responded differently to seasonality,and the activity period of several species was relatively late(August)in the year.

Simulation Analysis on Temperature Field and Temperature Stress of Flexible Pavement in Cold Areas

In order to ensure the service life of pavement in cold areas, this paper simulates the temperature field and stress field of pavement at high temperature of 60˚C and low temperature of -30˚C based on ANSYS software, and analyzes the changing trend of temperature of each layer with time and the temperature stress caused by it using the time-incremental finite element method. The results show that when the temperature is higher than 0˚C, the temperature between layers of the structure and the surface temperature shows an increasing trend. On the contrary, when the temperature is lower than 0˚C, it shows a decreasing trend. The more drastic the temperature change is, the greater the temperature stress of the pavement will be, which is easy to cause road structure diseases. When the temperature difference of pavement reaches 90˚C, the change of temperature stress between layers of road structure has a significant effect on the daily evolution of pavement.