scholarly journals Waldbrandmodellierung - Möglichkeiten und Grenzen | Forest fire modeling - limits and possibilities

2010 ◽  
Vol 161 (11) ◽  
pp. 433-441
Author(s):  
Patrick Weibel ◽  
Ché Elkin ◽  
Björn Reineking ◽  
Marco Conedera ◽  
Harald Bugmann
Keyword(s):  
Human Activity ◽  
Forest Fire ◽  
Forest Fires ◽  
Fire Regimes ◽  
Fire Frequency ◽  
Climatic Conditions ◽  
Forest Composition ◽  
General Validity ◽  
Landscape Models ◽  
Dynamic Landscape

Models make it possible to investigate the factors which influence forest fires and to measure their importance. Using various forest fire models, the works presented here examine the influence of weather, forest composition, human activity and changes in legislation on the likelihood of forest fire ignitions in Ticino and Valais. A distinction was made between forest fires started by flash of lightning, and those resulting from human activity. The results show that the weather has the greatest influence where lightning starts, whereas in fires caused by people, the weather takes a subordinate place to human activities. Depending on the ignition causes, different weather indices best represent the danger of forest fires: for those caused by lightning, the Duff Moisture Code (DMC) drought index, and for those started by human activity, the Angstrom Index. In order to test the general validity of forest fire ignition models these were applied to Ticino and to Valais over two different periods of time. Results show that transferability of the models is limited, and that their use for the assessment of the future risk of forest fire is difficult under changing climatic conditions. The landscape model LandClim was used in order to simulate the observed patterns of fire frequency and size in Ticino and in Valais. Thanks to further development of the forest fire module, LandClim achieved a marked improvement of modelquality. Such dynamic landscape models should have an important role to play in assessing future forest fire regimes.

Fire regime shift linked to increased forest density in a piñon–juniper savanna landscape

2014 ◽  
Vol 23 (2) ◽  
pp. 234 ◽  
Author(s):  
Ellis Q. Margolis
Keyword(s):  
Regime Shift ◽  
Fire History ◽  
Fire Regime ◽  
Fire Regimes ◽  
Fire Frequency ◽  
Climatic Conditions ◽  
Tree Density ◽  
High Severity ◽  
Wide Range ◽  
In Fire

Piñon–juniper (PJ) fire regimes are generally characterised as infrequent high-severity. However, PJ ecosystems vary across a large geographic and bio-climatic range and little is known about one of the principal PJ functional types, PJ savannas. It is logical that (1) grass in PJ savannas could support frequent, low-severity fire and (2) exclusion of frequent fire could explain increased tree density in PJ savannas. To assess these hypotheses I used dendroecological methods to reconstruct fire history and forest structure in a PJ-dominated savanna. Evidence of high-severity fire was not observed. From 112 fire-scarred trees I reconstructed 87 fire years (1547–1899). Mean fire interval was 7.8 years for fires recorded at ≥2 sites. Tree establishment was negatively correlated with fire frequency (r=–0.74) and peak PJ establishment was synchronous with dry (unfavourable) conditions and a regime shift (decline) in fire frequency in the late 1800s. The collapse of the grass-fuelled, frequent, surface fire regime in this PJ savanna was likely the primary driver of current high tree density (mean=881treesha–1) that is >600% of the historical estimate. Variability in bio-climatic conditions likely drive variability in fire regimes across the wide range of PJ ecosystems.

scholarly journals Drivers and distribution of forest fires in Sikkim Himalaya: A maximum entropy-based approach to spatial modelling.

2020 ◽  
Author(s):  
Polash Banerjee
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Forest Cover ◽  
Spatial Modelling ◽  
Climatic Conditions ◽  
Mitigation Measures ◽  
Sikkim Himalaya ◽  
Environmental Features ◽  
Validation Criteria ◽  
Forest Fire Model

Abstract The recent episodes of forest fire in Brazil and Australia of 2019 are tragic reminders of the hazards of the forest fire. Globally incidents of forest fire events are in the rise due to human encroachment into wilderness and climate change. Sikkim with a forest cover of more than 47%, suffers seasonal instances of frequent forest fire during the dry winter months. To address this issue, a GIS-aided and MaxEnt machine learning-based forest fire prediction map has been prepared using forest fire inventory database and maps of environmental features. The study indicates that amongst the environmental features, climatic conditions and proximity to roads are the major determinants of the forest fire. Model validation criteria like ROC curve, correlation coefficient and Cohen’s Kappa show a good predictive capability (AUC = 0.95, COR = 0.78, κ = 0.78). The outcomes of this study in the form of a forest fire prediction map can aid the stakeholders of the forest in taking informed mitigation measures.

Riparian and adjacent upland forests burned synchronously during dry years in eastern Oregon (1650–1900 CE), USA

2020 ◽  
Vol 29 (7) ◽  
pp. 602
Author(s):  
Grant L. Harley ◽  
Emily K. Heyerdahl ◽  
James D. Johnston ◽  
Diana L. Olson
Keyword(s):  
Forest Fires ◽  
Fire History ◽  
Riparian Forest ◽  
Fire Regimes ◽  
Fire Frequency ◽  
Riparian Forests ◽  
Landscape Context ◽  
Blue Mountains ◽  
Study Sites

Riparian forests link terrestrial and freshwater communities and therefore understanding the landscape context of fire regimes in these forests is critical to fully understanding the landscape ecology. However, few direct studies of fire regimes exist for riparian forests, especially in the landscape context of adjacent upland forests or studies of long-term climate drivers of riparian forest fires. We reconstructed a low-severity fire history from tree rings in 38 1-ha riparian plots and combined them with existing fire histories from 104 adjacent upland plots to yield 2633 fire scars sampled on 454 trees. Historically (1650–1900), low-severity fires burned more frequently in upland than in riparian plots, but this difference was not significant (P=0.15). During more than half of the fire years at both sites, fires were extensive and burned synchronously in riparian and upland plots, and climate was significantly dry during these years. However, climate was not significantly dry when fires burned in only one plot type. Historically, entire riparian zones likely burned in these two study sites of the Blue Mountains during dry years. This study suggests that riparian and upland forests could be managed similarly, especially given the projected increases to fire frequency and intensity from impending climate change.

The 2019/20 eastern Australian mega forest fires - a global forest perspective

2020 ◽  
Author(s):  
Matthias Boer ◽  
Víctor Resco De Dios ◽  
Ross Bradstock
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Austral Summer ◽  
Fire Regimes ◽  
Burned Area ◽  
Fire Event ◽  
Data Set ◽  
Broadleaf Forest ◽  
Eastern Australia ◽  
Fire Activity

<p>The 2019/20 forest fires in eastern Australia burned over 5.8 million hectares of mainly temperate broadleaf forest between September 2019 and January 2020. This burned area figure is expected to rise over the remainder of the austral summer, but is already an order of magnitude larger than the mean annual burned area for Australian forest fires over the last 20 years, which is ~0.59 Mha per year. Here we show that this forest fire event is of a record-breaking scale, both nationally and globally, and was pre-conditioned by wide-spread prolonged drought and extreme heat.</p><p>We analysed global remotely sensed burned area data for 2000-2019 to estimate annual burned area fractions of all continental forest biomes. The annual burned area fraction, which is related to the length of fire intervals and other aspects of fire regimes, allows us to compare levels of fire activity across different forest biomes and continents.</p><p>Though very large fires occur in some forest biomes, such as the boreal forests of North-America and Asia, over the 20 years covered by our data set, annual burned area fractions have been very small (<0.03) for nearly all continental forest biomes including Australia’s temperate broadleaf forest biome. These findings provide a global historical reference for the interpretation of the scale of the 2019/20 eastern Australian mega forest fires.</p><p>With fire activity in all forest biomes strongly constrained by the moisture content of the fuels, explanations for the unconstrained burning of millions of hectares of temperate broadleaf forest in a single season must be sought in the extreme drought that has affected eastern Australia for the last two years. We use gridded daily soil moisture predictions for the continent to show how widespread and prolonged dryness set the stage for the unprecedented forest fire event of 2019/20.</p>

scholarly journals Analysis of forest fire and climate variability using Geospatial Technology for the State of Telangana, India

2019 ◽  
Vol 7 (1) ◽  
pp. 24-37 ◽  
Author(s):  
Firoz Ahmad ◽  
Laxmi Goparaju
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Wind Velocity ◽  
Forest Fire ◽  
Forest Fires ◽  
Fire Regime ◽  
Fire Frequency ◽  
The State ◽  
Maximum Temperature ◽  
Hotspot Analysis

Abstract The dynamic changes in the regimes of forest fires are due to the severity of climate and weather factors. The aim of the study was to examine the trend of forest fires and to evaluate their relationship with climate parameters for the state of Telangana in India. The climate and forest fire data were used and uploaded to the GIS platform in a specified vector grid (spacing: 0.3° x 0.3°). The data were evaluated spatially and statistical methods were applied to examine any relationships. The study revealed that there was a 78% incidence of forest fires in the months of February and March. The overall forest fire hotspot analysis (January to June) of grids revealed that the seven highest forest fire grids retain fire events greater than 600 were found in the north east of Warangal, east of Khammam and south east of Mahbubnagar districts. The forest fire analysis significantly followed the month wise pattern in grid format. Ten grids (in count) showed a fire frequency greater than 240 in the month of March and of these, three grids (in count) were found to be common where the forest fire frequency was highest in the preceding month. Rapid seasonal climate/weather changes were observed which significantly enhanced the forest fire events in the month of February onwards. The solar radiation increased to 159% in the month of March when compared with the preceding month whereas the relative humidity decreased to 47% in the same month. Furthermore, the wind velocity was found to be highest (3.5 meter/sec.) in the month of February and precipitation was found to be lowest (2.9 mm) in the same month. The analysis of Cramer V coefficient (CVC) values for wind velocity, maximum temperature, solar radiation, relative humidity and precipitation with respect to fire incidence were found to be in increasing order and were in the range of 0.280 to 0.715. The CVC value for precipitation was found to be highest and equivalent to 0.715 and showed its strongest association/relationship with fire events. The significant increase in precipitation not only enhances the moisture in the soil but also in the dry fuel load lying on the forest floor which greatly reduces the fuel burning capacity of the forest. The predicted (2050) temperature anomalies data (RCP-6) for the month of February and March also showed a significant increase in temperature over those areas where forest fire events are found to be notably high in the present scenario which will certainly impact adversely on the future forest fire regime. Findings from this study have their own significance because such analyses/relationships have never be examined at the state level, therefore, it can help to fulfill the knowledge gap for the scientific community and the state forest department, and support fire prevention and control activities. There is a need to replicate this study in future by taking more climate variables which will certainly give a better understanding of forest fire events and their relationships with various parameters. The satellite remote sensing data and GIS have a strong potential to analyze various thematic datasets and in the visualization of spatial/temporal paradigms and thus significantly support the policy making framework.

scholarly journals Le régime des incendies de forêt en Valais: influences climatiques et anthropiques | Forest fire regimes in Valais: climatic and human influences

2010 ◽  
Vol 161 (11) ◽  
pp. 442-449 ◽  
Author(s):  
Thomas Zumbrunnen ◽  
Matthias Bürgi ◽  
Harald Bugmann
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Fire Regime ◽  
Fire Regimes ◽  
Combustible Material ◽  
Determining Factors ◽  
Before And After ◽  
History Of ◽  
The Alps ◽  
In Fire

Forest fire regimes are particularly sensitive to variations in the climate and to human influences. In the Alps both the manner in which the land is used and climatic changes, in particular rises in temperature and the frequency of drought periods, are probably going to bring about considerable modifications in fire regimes. The history of these fires in Valais in the 20th century is however still little known, as is the influence of the different determining factors. From a study of documentary archives we have therefore reconstituted the history of forest fires in Valais from 1904 to 2008. We then tried to establish whether or not the fire regime had evolved during this time by comparing descriptive statistics from the first and the second halves of the period under study. By means of correlation analyses we could then find what factors had a significant influence on the occurrence of fires. What emerges is that forest fire activity moved towards the plain in the course of the 20 century, probably on account of the increase in population density at lower altitudes. The seasonality of the fires also evolved: there was an outbreak of fires in the spring during the second half of the period under study, whereas in the first half fires mostly occurred in summer. On the other hand the frequency of the fires and the surface area burned annually did not differ significantly in the periods before and after 1955. As for the balance between factors determining the frequency of fires and the surface burned annually, there has been a modification in the period under study. Although drought was a decisive factor in the first decades of the 20 century, afterwards it seems to have declined in importance, being supplanted by other factors, notably the availability of combustible material. The fact that at present the forest fire regime is apparently regulated by factors other than the climate means it is possible to envisage concrete measures in order to limit fire risks.

scholarly journals Automatic Forest Fire Detection and Suppression Smart Grid System

2021 ◽  
pp. 666-669
Author(s):  
Gopalakrishnan G ◽  
Arul Mozhi Varman S ◽  
Dinessh T C ◽  
Divayarupa S ◽  
Benazir Begam R
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Fire Detection ◽  
Radical Change ◽  
Climatic Conditions ◽  
Grid System ◽  
The Past ◽  
Initial Stage ◽  
Smart Grid System ◽  
Forest Fire Detection

Over the past years, a radical change in Earth’s temperature has been recorded. It has caused global warming and severe changes in climatic conditions. Naturally, this has resulted in many natural disasters. Forest fire is one such calamity that harms the environment to a great extent. The traditional methods of controlling and suppressing the fires are ineffective as the fires spread too rapidly if it is not contained at the initial stage. Hence this paper proposes a system that aims to automatically detect forest fires and suppress them. This system will suppress and contain the forest fires long enough for the firefighters to arrive.

scholarly journals Postglacial fire history and interactions with vegetation and climate in southwestern Yunnan Province of China based on charcoal and pollen records

2016 ◽  
Author(s):  
Xiayun Xiao ◽  
Simon G. Haberle ◽  
Ji Shen ◽  
Bin Xue ◽  
Sumin Wang
Keyword(s):  
Yunnan Province ◽  
Fire History ◽  
Fire Regimes ◽  
Fire Frequency ◽  
Climatic Conditions ◽  
Qinghai Lake ◽  
Pollen Record ◽  
Disturbance Factor ◽  
Fire Activity ◽  
Evergreen Oaks

Abstract. A high-resolution, continuous 18.5 ka-long (1 ka=1000 cal yr BP) macroscopic charcoal record from Qinghai Lake in southwestern Yunnan Province, China reveals the postglacial fire frequency and variability history. The results show that three periods with high fire frequency and intensity occurred during the periods 18.5–15.0 ka, 13.0–11.5 ka, and 4.3–~1.0 ka, respectively. This record was compared with the pollen record from the same core, and tentatively correlated with the regional climate proxy records with the aim to separate climate- from human-induced fire activity, and discuss vegetation-fire-climate interactions. The results suggest that fire was mainly controlled by climate before 4.3 ka and by combined action of climate and humans after 4.3 ka. Before 4.3 ka, high fire activity corresponded to cold and dry climatic conditions, while warm and humid climatic conditions brought infrequent and weak fires. Fire was an important disturbance factor and played an important role in forest dynamics around the study area. Vegetation responses to fire before 4.3 ka are not consistent with that after 4.3 ka, suggesting that human influence on vegetation and fire regimes may have become more prevalent after 4.3 ka. The correlations between fire activity and vegetation reveal that evergreen oaks and Alnus are flammable plants. Evergreen oaks are fire-tolerant taxa and Alnus is a fire-adapted taxon. The forests dominated by Lithocarpus/Castanopsis and/or tropical arbors are not easy to ignite, but Lithocarpus/Castanopsis and tropical arbors are fire-sensitive taxa in the study area.

scholarly journals Effects of Climate Change on Canadian Forest Fires

2017 ◽  
Vol 3 (2) ◽  
pp. 1-6 ◽  
Author(s):  
Curtis Chong ◽  
Emily Huang ◽  
Leon Chen
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Forest Fire ◽  
Forest Fires ◽  
Wind Farms ◽  
Weather Conditions ◽  
Fire Frequency ◽  
Cloud Seeding ◽  
Wind Speeds ◽  
Harmful Effects

This study aimed to determine the effects of climate change on forest fire trends in Canada by measuring correlations between weather conditions, and the frequencies and sizes of forest fires. Upon identifying the correlations, a model was created to understand future forest fire trends in order to prevent the increasing occurrences of forest fires, and to devise solutions to reduce their damages. The data obtained from the Canadian National Fire Database was modeled with a linear regression to predict and correlate weather conditions with future forest fire trends. It was concluded that temperature and wind speed correlated positively with forest fire frequency and size, while precipitation presented a negative correlation. To reduce the harmful effects of forest fires, cloud seeding can be used to create more precipitation, and wind farms can be built to lower wind speeds and attract lightning. However, more research and stricter policies directly targeting climate change is a necessity when it comes to decreasing forest fire trends and improving longterm security.

scholarly journals Maximum entropy-based forest fire likelihood mapping: analysing the trends, distribution, and drivers of forest fires in Sikkim Himalaya.

2021 ◽  
Author(s):  
Polash Banerjee
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Forest Cover ◽  
Predictive Ability ◽  
Climatic Conditions ◽  
Mitigation Measures ◽  
Sikkim Himalaya ◽  
Environmental Features ◽  
Validation Criteria ◽  
Likelihood Mapping

Abstract The recent episodes of forest fires in Brazil and Australia of 2019 are tragic reminders of the hazards of forest fire. Globally incidents of forest fire events are on the rise due to human encroachment into the wilderness and climate change. Sikkim with a forest cover of more than 47%, suffers seasonal instances of frequent forest fire during the dry winter months. To address this issue, a GIS-aided and MaxEnt machine learning-based forest fire prediction map has been prepared using a forest fire inventory database and maps of environmental features. The study indicates that amongst the environmental features, climatic conditions and proximity to roads are the major determinants of forest fires. Model validation criteria like ROC curve, correlation coefficient, and Cohen’s Kappa show a good predictive ability (AUC = 0.95, COR = 0.81, κ = 0.78). The outcomes of this study in the form of a forest fire prediction map can aid the stakeholders of the forest in taking informed mitigation measures.

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