scholarly journals Modeling of wildfire occurrence by using climate data and effect of temperature increments

2020 ◽  
Author(s):  
Amir Hossein Sadat Razavi ◽  
Majid Shafiepour Motlagh ◽  
Alireza Noorpoor ◽  
Amir Houshang Ehsani
Keyword(s):  
Forest Fires ◽  
Boreal Forests ◽  
Environmental Variables ◽  
Temperate Forests ◽  
Forest Type ◽  
Effect Of Temperature ◽  
Transient Temperature ◽  
Fire Occurrence ◽  
Model Output ◽  
Average Temperature

Abstract. Forest fires are assumed as one of the key natural hazards in the globe since it causes great losses in ecology, economy, and human lives; recent fire cases in US and their vast damages are vivid reasons to study the wildfires more deeply One of the basic requirements to manage the threats and protect wildlife is the ability to predict wildfire spots which is necessary to prioritize forest management. In this study, a 25-year period natural wildfire database and a wide array of environmental variables are used to develop an artificial neural network model with the aim of predicting potential fire spots. This study focuses on non-human reasons of wildfires (natural) to compute global warming effects on wildfires. Among the environmental variables, this study shows the significance of temperature for predicting wildfire cases while other parameters are presented in the next study. The study area of this study includes all forest fire cases in united states from 1992 to 2015 excluding tropical forests. The data of eight days including the day fire occurred and 7 previous days are used as input to the model to forecast fire occurrence probability of that day. The climatic inputs are extracted from ECMWF. The inputs of the model are temperature at 2 meter above surface, relative humidity, Total pressure, evaporation, volumetric soil water layer 1, snow melt, Keetch–Byram drought index, total precipitation, wind speed (along U and V direction), and NDVI. The results show there is a transient temperature span for each forest type which acts like a threshold to predict fire occurrence. In Temperate forests, A 0.1-degree Celsius increase in temperature relative to 7-day average temperature before a fire occurrence results in prediction model output of greater than 0.8 for 4.75 % of fire forest cases. In Boreal forests, the model output for temperature increase of less than 1 degree relative to past 7-day average temperature represents no chance of wildfire. But the non-zero fire forest starts at 2 degrees increase of temperature which ends to 2.62 % of fire forest cases with model output of larger than 0.8. It is concluded that other variables except temperature are more determinant to predict wildfires in temperate forests rather than in boreal forests.

Synoptic climatology of lightning-caused forest fires in subalpine and boreal forests

1996 ◽  
Vol 26 (10) ◽  
pp. 1859-1874 ◽  
Author(s):  
C.H. Nash ◽  
E.A. Johnson
Keyword(s):  
High Pressure ◽  
Forest Fires ◽  
Boreal Forests ◽  
Dry Weight ◽  
Weather Conditions ◽  
Synoptic Climatology ◽  
Fuel Moisture ◽  
Fire Occurrence ◽  
Lightning Strikes ◽  
Lightning Fire

The coupling of synoptic scale weather conditions with local scale weather and fuel conditions was examined for 2551 fires and 1 537 624 lightning strikes for the May through August fire seasons in 1988, 1989, 1992, and 1993 in Alberta and Saskatchewan. The probability of lightning fire occurrence (number of fires/number of strikes) is near zero until the Fine Fuel Moisture Code reaches 87 (moisture content of 14% dry weight), after which the probability increases rapidly. Duff Moisture and Drought Codes show less clear increases. In all cases, the probability of fire occurrence was low (the number of strikes greatly exceeded the number of forest fires), suggesting that lightning fire ignition coupled with early spread to detection was an uncommon event. This low probability of fire occurrence even at low fuel moisture may be a result of the arrangement and continuity of fuels in the boreal and subalpine forests. The literature suggests a higher probability of lightning-ignited fires in qualitatively different fuels, e.g., grasslands. The higher probability of fire at lower fuel moistures occurred primarily when high pressure dominated (positive 50-kPa anomaly) for at least 3 days and less than 1.5 mm precipitation occurred. The highest number of lightning strikes and largest number of fires also occurred when high pressure dominated. The high lightning numbers during high pressure systems were logistically related to increasing atmospheric instability (K-index).

Influence of Stand Age And Structure on the Epiphytic Lichen Vegetation in the Middle-Boreal Forests of Finland

1992 ◽  
Vol 24 (2) ◽  
pp. 165-180
Author(s):  
M. Hyvärinen ◽  
P. Halonen ◽  
M. Kauppi
Keyword(s):  
Boreal Forests ◽  
Environmental Variables ◽  
Competitive Ability ◽  
Lichen Species ◽  
Tree Canopy ◽  
Stand Age ◽  
Ecological Strategy ◽  
Epiphytic Lichen ◽  
Vertical Location ◽  
Community Variation

Abstract The epiphytic lichen vegetation on the trunks of Pinus sylvestris and Picea abies was studied and analysed by canonical correspondence analysis in relation to a number of environmental variables. The distribution and abundance of epiphytic lichen species proved to be dependent on the age of the stand, showing divergent responses in relation to phorophyte species and environmental variables such as acidity of the bark and vertical location on the trunk. The importance of stand age in the pattern of community variation is concluded to be an outcome of interaction between changes in the structure of the tree canopy, microclimate and properties of the bark. The responses of single lichen species to changes in the environment seem to vary considerably, indicating differences in competitive ability and ecological strategy between the species.

scholarly journals Tendencies of Fire Development in the Forests of Ukraine

2020 ◽  
Vol 3 (1) ◽  
pp. 106
Author(s):  
Yevhen Melnyk ◽  
Vladimir Voron
Keyword(s):  
Forest Management ◽  
Forest Fires ◽  
Necessary Conditions ◽  
Climatic Conditions ◽  
Anthropogenic Factors ◽  
Burned Area ◽  
Fire Occurrence ◽  
Management Zones ◽  
Wildfire Occurrence ◽  
Management Zone

Preservation and increase of forest area are necessary conditions for the biosphere functioning. Forest ecosystems in most parts of the world are affected by fires. According to the latest data, the forest fire situation has become complicated in Ukraine, and this issue requires ongoing investigation. The aim of the study was to analyse the dynamics of wildfires in Ukrainian forests over recent decades and to assess the complex indicator of wildfire occurrence in various forest management zones and administrative regions. The average annual complex indicator of fire occurrence, in terms of wildfire number and burned area, was studied in detail in the forests of various administrative regions and forest management zones in Ukraine from 1998 to 2017. The results show that fire occurrence in both the number and area of fires can vary significantly in various forest management zones. There is a very noticeable difference in these indicators in some administrative regions within a particular forest management zone. The data show that the number of forest fires depends not only on the natural and climatic conditions of such regions, but also on anthropogenic factors.

scholarly journals Evolution of Burned Area in Forest Fires under Climate Change Conditions in Southern Spain Using ANN

2019 ◽  
Vol 9 (19) ◽  
pp. 4155
Author(s):  
Pérez-Sánchez ◽  
Jimeno-Sáez ◽  
Senent-Aparicio ◽  
Díaz-Palmero ◽  
de Dios Cabezas-Cerezo
Keyword(s):  
Climate Change ◽  
Forest Fires ◽  
Southern Spain ◽  
Burned Area ◽  
Change Scenario ◽  
Absolute Deviation ◽  
Average Temperature ◽  
Mediterranean Regions ◽  
Artificial Neural Network Ann ◽  
Absolute Percent Error

Wildfires in Mediterranean regions have become a serious problem, and it is currently the main cause of forest loss. Numerous prediction methods have been applied worldwide to estimate future fire activity and area burned in order to provide a stable basis for future allocation of fire-fighting resources. The present study investigated the performance of an artificial neural network (ANN) in burned area size prediction and to assess the evolution of future wildfires and the area concerned under climate change in southern Spain. The study area comprised 39.41 km2 of land burned from 2000 to 2014. ANNs were used in two subsequential phases: classifying the size of the wildfires and predicting the burned surface for fires larger than 30,000 m2. Matrix of confusion and 10-fold cross-validations were used to evaluate ANN classification and mean absolute deviation, root mean square error, mean absolute percent error and bias, which were the metrics used for burned area prediction. The success rate achieved was above 60–70% depending on the zone. An average temperature increase of 3 °C and a 20% increase in wind speed during 2071–2100 results in a significant increase of the number of fires, up to triple the current figure, resulting in seven times the average yearly burned surface depending on the zone and the climate change scenario.

scholarly journals Seasonality is more important than forest type in regulating the pool size and composition of soil soluble N in temperate forests

2020 ◽  
Vol 150 (3) ◽  
pp. 279-295
Author(s):  
Lei Gao ◽  
Paul W. Hill ◽  
Davey L. Jones ◽  
Yafen Guo ◽  
Fei Gao ◽  
...  
Keyword(s):  
Temperate Forests ◽  
Forest Type ◽  
Pool Size

scholarly journals The Effect of Temperature and Humidity May Reduce the Growth Rate of the Coronavirus Disease 2019 Epidemic

2020 ◽  
Author(s):  
Lei Qin ◽  
Qiang Sun ◽  
Jiani Shao ◽  
Yang Chen ◽  
Xiaomei Zhang ◽  
...  
Keyword(s):  
Growth Rate ◽  
Relative Humidity ◽  
Effect Of Temperature ◽  
Average Temperature ◽  
Temperature And Humidity ◽  
Scatter Plots ◽  
Low Humidity ◽  
Average Relative Humidity ◽  
Effects Of Temperature ◽  
The Relationship

Abstract Background: The effects of temperature and humidity on the epidemic growth of coronavirus disease 2019 (COVID-19)remains unclear.Methods: Daily scatter plots between the epidemic growth rate (GR) and average temperature (AT) or average relative humidity (ARH) were presented with curve fitting through the “loess” method. The heterogeneity across days and provinces were calculated to assess the necessity of using a longitudinal model. Fixed effect models with polynomial terms were developed to quantify the relationship between variations in the GR and AT or ARH.Results: An increased AT dramatically reduced the GR when the AT was lower than −5°C, the GR was moderately reduced when the AT ranged from −5°C to 15°C, and the GR increased when the AT exceeded 15°C. An increasedARH increased theGR when the ARH was lower than 72% and reduced theGR when the ARH exceeded 72%.Conclusions: High temperatures and low humidity may reduce the GR of the COVID-19 epidemic. The temperature and humidity curves were not linearly associated with the COVID-19 GR.

Effect of temperature and relative humidity on the milk production of dairy cows

2021 ◽  
Vol 13 (2) ◽  
pp. 22-27
Author(s):  
Ivan Imrich ◽  
Róbert Toman ◽  
Martina Pšenková ◽  
Eva Mlyneková ◽  
Tomáš Kanka ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Milk Production ◽  
Milk Yield ◽  
Effect Of Temperature ◽  
Winter Period ◽  
Summer Period ◽  
Average Temperature ◽  
Holstein Friesian ◽  
Humidity Index ◽  
Index Value

The aim of this study was to evaluate the influence of environmental housing conditions on the milk yield of dairy cows. Measurements were taken in the summer period from June to September 2020 and in the winter period during January 2021 on a large-capacity farm of Holstein Friesian cattle. Cows were housed in free stall barn with the lying boxes and selected during the second or third lactations, in the summer period from the 51st day to the 135th day and in the winter period from the 64th day to the 120th day of lactation. The average temperature in the housing was 23 °C in summer, and 7.05 °C in winter. The average THI (thermal humidity index) value in summer was 70.43, but during the day the THI values sometimes reached 75. The dairy cows were therefore exposed to heat stress during summer. Increasing THI and temperature values negatively affected the milk yield, as there was a negative correlation between both THI and milk yield (r = -0.641; p <0.01) and temperature and milk yield (r = -0.637; p <0.01). Milk production in winter was at 58.77 kg per day and in summer at 49.55 kg per day. In the summer, the milk had a significantly lower content of fat (p <0.05), proteins (p <0.001), lactose (p <0.001), minerals (p <0.001) and conversely, a higher number of somatic cells (p <0.01). These results show that worse environmental conditions during the summer negatively affected the level of milk yield and the composition of the cows’ milk.

Temperate Forests of the Southern Andean Region

2007 ◽  
Author(s):  
Thomas T. Veblen
Keyword(s):  
South America ◽  
Southern Hemisphere ◽  
Northern Hemisphere ◽  
Boreal Forests ◽  
Temperate Forests ◽  
High Latitudes ◽  
Andean Region ◽  
Southern South America ◽  
The Andes ◽  
Evergreen Conifers

Although most of the continent of South America is characterized by tropical vegetation, south of the tropic of Capricorn there is a full range of temperate-latitude vegetation types including Mediterranean-type sclerophyll shrublands, grasslands, steppe, xeric woodlands, deciduous forests, and temperate rain forests. Southward along the west coast of South America the vast Atacama desert gives way to the Mediterranean-type shrublands and woodlands of central Chile, and then to increasingly wet forests all the way to Tierra del Fuego at 55°S. To the east of the Andes, these forests are bordered by the vast Patagonian steppe of bunch grasses and short shrubs. The focus of this chapter is on the region of temperate forests occurring along the western side of the southernmost part of South America, south of 33°S. The forests of the southern Andean region, including the coastal mountains as well as the Andes, are presently surrounded by physiognomically and taxonomically distinct vegetation types and have long been isolated from other forest regions. Although small in comparison with the extent of temperate forests of the Northern Hemisphere, this region is one of the largest areas of temperate forest in the Southern Hemisphere and is rich in endemic species. For readers familiar with temperate forests of the Northern Hemisphere, it is difficult to place the temper temperate forests of southern South America into a comparable ecological framework owing both to important differences in the histories of the biotas and to contrasts between the broad climatic patterns of the two hemispheres. There is no forest biome in the Southern Hemisphere that is comparable to the boreal forests of the high latitudes of the Northern Hemisphere. The boreal forests of the latter are dominated by evergreen conifers of needle-leaved trees, mostly in the Pinaceae family, and occur in an extremely continental climate. In contrast, at high latitudes in southern South America, forests are dominated mostly by broadleaved trees such as the southern beech genus (Nothofagus). Evergreen conifers with needle or scaleleaves (from families other than the Pinaceae) are a relatively minor component of these forests.

scholarly journals Designing a Model to Display the Relation between Social Vulnerability and Anthropogenic Risk of Wildfires in Galicia, Spain

Urban Science ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 32 ◽  
Author(s):  
Jaime de Diego ◽  
Antonio Rúa ◽  
Mercedes Fernández
Keyword(s):  
Population Structure ◽  
Forest Fires ◽  
Social Vulnerability ◽  
Academic Research ◽  
Northern Region ◽  
Fire Occurrence ◽  
Socioeconomic Variables ◽  
Structure Density ◽  
The Relationship ◽  
Selection Of

Since the beginning of the 21st century, most of the forest fires that have occured in Spain have taken place in the northern region of Galicia. This area represents 5.8% of the Spanish territory, but compromises, in certain years, up to 50% of the total number of wildfires. Current research on forest fires is focused mostly on physical or meteorological characteristics, post-fire situations, and their potential destructive capacities (main areas burnt, type of vegetation, economic loses, etc.). However, the academic research to date has not delved into other socioeconomic factors (population structure, density, livestock farms, education, among others), which compromise the existing pre-fire situation in the affected territories, and subsequently reflect the prevailing vulnerability of the population. Indeed, these socioeconomic variables can influence fire occurrence, whether positively or negatively. To fill in this knowledge gap, this article analyzes the relationship between wildfire events and the socioeconomic variables that characterize the Galician municipalities affected. To that effect, first, a thorough examination and selection of the most relevant socioeconomic variables, and their subsequent justification will be carried out. Then, using IBM SPSS statistics 24, a linear regression is executed using the data of wildfires that occurred in Galicia between 2001–2015. The resulting model allows a better knowledge of the importance of the socioeconomic situation in Galician municipalities when wildfires occur. Therefore, this result identifies the existing relationship between the socioeconomic variables and wildfire events, and consequently will help to optimize the interventions that must be done. This may be the best way to carry out prevention actions in order to reduce vulnerability to forest fires.

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