scholarly journals THE DIVERSITY OF HERBACEOUS VEGETATION AFTER FOREST FIRE

Author(s):  
Jolita ABRAITIENĖ ◽  
Gerda ŠILINGIENĖ ◽  
Rasa VAITKEVIČIŪTĖ ◽  
Regina VASINAUSKIENĖ

Forest fire is an uncontrolled combustion of flammable materials in forested and non-forested areas. In Lithuania forest fires mainly occur in late spring and summer, mostly in young coniferous forests (Forest ..., 1987). The studies of herbaceous plants in fireplaces were carried out in 2016 in Jurbarkas SFE. Ground-level forest fire increased the projection coverage of herbaceous plants and their species composition in the fireplaces. According to the average data of the survey, 18 herbaceous plant species were ascertained in the fireplace and 14 species in the control stand. During the first year after fire, 9 new species were recorded in the fireplace and 5 species have disappeared, while in the seventh year - 7 new species were recorded and 1 disappeared, as compared with the control stand. Summarizing the obtained data it can be stated that low-intensity ground-level forest fire in pine forest increased the number of herbaceous plant species, however, the number of new and extinct species has been gradually decreasing, suggesting that in the fireplaces the diversity of herbaceous plant species will be like in the control stand.

Safety ◽  
2019 ◽  
Vol 5 (3) ◽  
pp. 56 ◽  
Author(s):  
Nikolay Baranovskiy ◽  
Alena Demikhova

The last few decades have been characterized by an increase in the frequency and burned area of forest fires in many countries of the world. Needles, foliage, branches, and herbaceous plants are involved in burning during forest fires. Most forest fires are surface ones. The purpose of this study was to develop a mathematical model of heat transfer in an element of combustible plant material, namely, in the stem of a herbaceous plant, when exposed to radiation from a surface forest fire. Mathematically, the process of heat transfer in an element of combustible plant material was described by a system of non-stationary partial differential equations with corresponding initial and boundary conditions. The finite difference method was used to solve this system of equations in combination with a locally one-dimensional method for solving multidimensional tasks of mathematical physics. Temperature distributions were obtained as a result of modeling in a structurally inhomogeneous stem of a herbaceous plant for various scenarios of the impact of a forest fire. The results can be used to develop new systems for forest fire forecasting and their environmental impact prediction.


Forests ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 219 ◽  
Author(s):  
Boknam Lee ◽  
Seungwan Cho ◽  
Seung-Kii Lee ◽  
Choongshik Woo ◽  
Joowon Park

Smoke from forest fires is a growing concern in Korea as forest structures have changed and become more vulnerable to fires associated with climate change. In this study, we developed a Korean forest fire smoke dispersion prediction (KFSDP) system to support smoke management in Korea. The KFSDP system integrates modules from different models, including a Korean forest fire growth prediction model, grid-based geographic information system (GIS) fuel loading and consumption maps generated by national forest fuel inventory data, and the Korean Weather Research and Forecasting Model, into a Gaussian plume model to simulate local- and regional-scale smoke dispersion. The forecast system is operated using grid-based fires and simulates a cumulative smoke dispersion of carbon monoxide (CO) and <2.5 µm and <10 µm particulate matter (PM2.5 and PM10, respectively) ground-level concentration contours at 30-min intervals during the fire in concert with weather forecasts. The simulated smoke dispersions were evaluated and agreed well with observed smoke spreads obtained from real forest fires in Korea, and the performance of the KFSDP system was also analyzed using “what-if” scenarios. This is the first study to develop an integrated model for predicting smoke dispersion from forest fires in Korea.


2016 ◽  
Vol 25 (7) ◽  
pp. 797 ◽  
Author(s):  
Michalis Diakakis ◽  
Gavriil Xanthopoulos ◽  
Leontios Gregos

Although forest fires are considered an integral part of forest ecosystems, the abundance of human activities in forested areas has led to a significant number of human casualties and to important effects on properties and infrastructure. Over recent decades, Greece has suffered extensive forest fire disasters, with a significant number of fatalities being recorded. However, there is no coherent inventory of human losses from fires in the country. This work develops and examines a database of 208 fatalities occurring in 78 forest fires in Greece between 1977 and 2013 to provide a better understanding of the circumstances under which fatal incidents occur. Around three-quarters of the victims were civilians; the remainder were firefighters, forest service officials and aircraft crews. Most deaths occurred in July and August, generally under adverse meteorological conditions. Male and older individuals showed an overrepresentation among the victims. A significant number of fatalities occurred in open space, mostly in wildland–urban interface areas and in tall forest vegetation. Late evacuation on foot or in a vehicle and firefighting were the most common activities of victims at the time of the incidents.


Author(s):  
Lavanya I

Forest fires are natural hazards defined as movements of fire through unregulated and uncontrolled forested areas. They pose a permanent risk of loss of forest and forest land. The ability to reliably forecast the region that could be involved in a forest fire incident will help to optimize fire prevention efforts. It appears that Portugal may theoretically make better use of the wildfire risk assessment. More than any other region in Europe, it is a country overrun by wildfires. It has a large amount of forest. Forest fires have a long-term impact on the climate because they contribute to deforestation and global warming, which is one of the main causes of the phenomenon. This research employs Back Propagation Neural Network (BPNN) and Recurrent Neural Network (RNN) models with meteorological parameters as inputs to anticipate forest fires as a means of safeguarding forest biodiversity. The results indicate that using meteorological data, it is possible to anticipate the severity of a forest fire at the beginning.


2021 ◽  
Vol 15 (1) ◽  
pp. 67-78
Author(s):  
R. Dmytrakh ◽  

Background. Natural ecosystems of the Ukrainian Carpathians have been signi­ficantly transformed during the last few years due to the impact of climate factors and an increased activity of nature restoration processes. The study of the influence of the external environ­mental factors on populations of the herbaceous plant species is particularly topical for the high-mountain ecosystems. As a result of gradual restoration of native plants, specific changes occur in the structural and spatial organization of populations of many herbaceous plant species. Thus, considering the increased climate changes and regenera­tive activity, the assessment of the present condition of the populations of herbaceous plant species, their regenerative ability, response to changing environmental conditions and individual peculiarities of performance in the altered environmental conditions are important. Methods. The conventional stationary and route-field methods were applied in order to determine changes in the structural organization of high-mountain plant populations and their regenerative ability. The initial diagnostic parameters of the populations’ condition include the individual growth peculiarities and the nature of dynamic trends under the changed environmental conditions. During the ontogenetic development of plants, the most important changes occur within the generative phase that ensures the rege­nera­tion and self-maintenance of populations by means of seeds; those changes are a significant indicative feature. The long-term observations of different types of plant communities were applied; these included the records of the main parameters and characteristic features at permanent test sites. The transects are located in the alpine, subalpine and upper forest belts of the Ukrainian Carpathians within 1000–2000 m a.s.l. altitudinal range. The study comprises such behavioral features of the species populations as phenological (intensity phenophase, flowering rhythmics), demographic (number of individuals, spatial differentiation), reproductive (generative reproduction, seed productivity), etc., which enable the determination of their adaptation and ability to exist under the changed environmental conditions. Results. The continuous monitoring of different high-mountain plant aggregations showed that in some cases the number of species which are distinguished by active regenerative strategy aimed at further extension of the habitat is growing, while in other cases the species demonstrated the opposite trend resulting from their inability to adapt to changing habitat conditions. It has been determined that the vegetative development of the populations of high-mountain plant species is closely related to temperature conditions which influence phenology, dynamics of the numbers of individuals and the nature of their reproduction. A significant influence of warming on the processes of seasonal development of populations and flowering abundance is evidenced by their increased number and migration to much higher hypsometric levels of the high-mountain zone. The increased ability to generative reproduction contributes to the dissemination of seeds and formation of new population loci Valeriana simplicifolia, V. transsilvanica, Silene dioica, Astrantia major, Doronicum carpaticum, Euphorbia carniolica, etc. in favourable micro-habitats at significantly higher hypsometric levels of the high-mountain zone (1600–2000 m a.s.l.). Another natural factor of changes in populations of herbaceous plant species is the impact of restoration succesions in different types of plant communities. These changes are usually accompanied by increased shading and crowding of vegetation due to the spread of more competitive tree and shrub species as well as adventive species of tall herbaceous plants. It refers mostly to grassland species that need open sites for the effective population recruitment. Radical changes can be observed in the structural organization of the populations of herbaceous plants species due to an increased cenotic activity of more competitive species. Such changes reduce the regenerative ability of the populations of herbaceous plants species and trigger their fragmentation. Thus, the change of ecological and cenotic conditions of various plant communities along the elevation gradient of the highlands predetermines different charac­teristic features of the populations of herbaceous plant species and their unequal spatial differentiation. Conclusions. It has been determined that present natural processes occurring in the populations of herbaceous plant species of the high-mountain zone controversially influence their regenerative ability and the nature of changes in their structural organization. The dynamics of populations in each separate case is defined by the influence of natural and climate changes and their association with particular plant communities along the elevation gradient of the high-mountain zone. The multi-year dynamics of the numbers of generative individuals represents their regenerative ability in populations and dependence on weather conditions. The important feature of active regeneration of the populations is the development of their local foci in favorable microhabitats at significantly higher hypsometric levels of the high-mountain zone, in particular, the alpine and the upper margin of the alpine. Occurrence of new populations loci is indicative of their ability to reproduce and survive. In some cases, the dynamic trends in populations are accompanied by an increased number of individuals and extension of their habitats, while in other cases, trends are the opposite, which is caused by a decreased number of individuals and their degradation. The processes which are observed during the regeneration of species populations are related to their ascending extension to various hypsometric levels, as well as the strengthening of the positions of the populations of tree and shrub layer species and adventive representatives of tall herbaceous plants which are peculiar to lower layers. Significant overgrowth processes, which result in gradual exclusion of herbaceous plant species typical of meadow communities aggregations, are observed in the habitats of the populations of many types of herbaceous plants and at the upper margin of the forest and subalpine layers. Thus, the changes in ecological and cenotic conditions of various plant communities along the elevation gradient of the highlands predetermines different characteristic features of the populations of herbaceous plant species and their unequal spatial differentiation.


2020 ◽  
Author(s):  
Anda Fescenko ◽  
James A. Downer ◽  
Ilja Fescenko

Boreal plants growing along southern edge of their range on isolated mountains in a hot desert matrix live near the extreme of their physiological tolerance. Such plants are considered to be sensitive to small changes in climate. We coupled field observations (1974, 1993, 2019) about the abundance and vigor of small populations of ten remnant boreal plant species persisting in uppermost elevation spruce-fir forests of the Chiricahua Mountains, together with a theoretical modeling of the species' tolerances to three climate change cues: warming, drought, and forest fire, in order to explore the persistence of frontier boreal plant species in the frame of climate changes. We hypothesized that populations of these cryophilic plants have declined or become locally extinct during an adverse warming period since 1993, enforced by two large forest fires (1994, 2011). We used plant functional traits and principal component analysis to model tolerances of the plants to combined actions of warming, drought, and forest fire. Our model predicted selective sensitivity to warming for two species: Vaccinium myrtillus and Rubus parviflorus, while possible decline of the other species could be explained by drought and/or fire. We surveyed the study area in 2019 and found eight of the ten species still occur in the area. Five species occurred in wet canyons at lower elevations, but three species persisted in low vigor at the uppermost elevation highly affected by fires. Both warming-sensitive species did not show signs of decline: population of R. parviflorus increased in abundance and vigor, while V. myrtillus persists without significant changes since 1993. Despite the recorded increase in temperature in the study area over one degree Celsius between years 1975-1993 and 1994-2019, our study did not find evidence of the direct warming effect on the observed species. We conclude that severe wildfires and multi-decadal decrease in precipitation rather than warming are the main limiting factors of the remnant boreal species remarkable but limited persistence in the Chiricahua Mountains. Our study demonstrates how field observations can be combined with modeling to evaluate species selective responses to different environmental stresses for better environmental management decisions, particularly in light of climate change.


Author(s):  
A. E. Akay ◽  
A. Erdoğan

The forested areas along the coastal zone of the Mediterranean region in Turkey are classified as first-degree fire sensitive areas. Forest fires are major environmental disaster that affects the sustainability of forest ecosystems. Besides, forest fires result in important economic losses and even threaten human lives. Thus, it is critical to determine the forested areas with fire risks and thereby minimize the damages on forest resources by taking necessary precaution measures in these areas. The risk of forest fire can be assessed based on various factors such as forest vegetation structures (tree species, crown closure, tree stage), topographic features (slope and aspect), and climatic parameters (temperature, wind). In this study, GIS-based Multi-Criteria Decision Analysis (MCDA) method was used to generate forest fire risk map. The study was implemented in the forested areas within Yayla Forest Enterprise Chiefs at Dursunbey Forest Enterprise Directorate which is classified as first degree fire sensitive area. In the solution process, "extAhp 2.0" plug-in running Analytic Hierarchy Process (AHP) method in ArcGIS 10.4.1 was used to categorize study area under five fire risk classes: extreme risk, high risk, moderate risk, and low risk. The results indicated that 23.81&amp;thinsp;% of the area was of extreme risk, while 25.81&amp;thinsp;% was of high risk. The result indicated that the most effective criterion was tree species, followed by tree stages. The aspect had the least effective criterion on forest fire risk. It was revealed that GIS techniques integrated with MCDA methods are effective tools to quickly estimate forest fire risk at low cost. The integration of these factors into GIS can be very useful to determine forested areas with high fire risk and also to plan forestry management after fire.


2021 ◽  
Author(s):  
Tomi Karppinen ◽  
Anu-Maija Sundström ◽  
Hannakaisa Lindqvist ◽  
Johanna Tamminen

&lt;p&gt;&lt;span&gt;Climate change is proceeding fastest in the Arctic region. While human-induced emissions of long-lived greenhouse gases are the main driving factor of global warming, short-lived climate forcers or pollutants emitted from the forest fires are also playing an important role, especially in the Arctic. Forest fire emissions also affect local air quality and photochemical processes in the atmosphere. For example, CO contributes to the formation of tropospheric ozone and affects the abundance of greenhouse gases such as methane and CO2.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;During past years Arctic summers have been warmer and drier elevating the risk for extensive forest fire episodes. Satellite observations show, that during the past three summers (2018-2020) fire detections in Arctic, especially in Arctic Siberia have increased considerably, affecting also local emissions of CO. This work focuses on studying CO concentration and its variation at high latitudes and in the Arctic using satellite and ground-based observations. Satellite observations of CO from TROPOMI are analyzed for the 2018-2020 (NH) summer months. To assess the satellite retrieved columns the satellite measurements are compared to ground-based remote sensing measurements at Sodankyl&amp;#228;. Also, ground-based in-situ measurements are used to see how the total column changes mirror the ground level concentrations. The fire characteristics are analyzed using observations from MODIS instruments onboard Aqua and Terra. Fire effects on seasonal cycle and interannual variability of CO concentrations at Arctic high latitudes are analyzed.&lt;/span&gt;&lt;/p&gt;


Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 768
Author(s):  
Jin Pan ◽  
Xiaoming Ou ◽  
Liang Xu

Forest fires are serious disasters that affect countries all over the world. With the progress of image processing, numerous image-based surveillance systems for fires have been installed in forests. The rapid and accurate detection and grading of fire smoke can provide useful information, which helps humans to quickly control and reduce forest losses. Currently, convolutional neural networks (CNN) have yielded excellent performance in image recognition. Previous studies mostly paid attention to CNN-based image classification for fire detection. However, the research of CNN-based region detection and grading of fire is extremely scarce due to a challenging task which locates and segments fire regions using image-level annotations instead of inaccessible pixel-level labels. This paper presents a novel collaborative region detection and grading framework for fire smoke using a weakly supervised fine segmentation and a lightweight Faster R-CNN. The multi-task framework can simultaneously implement the early-stage alarm, region detection, classification, and grading of fire smoke. To provide an accurate segmentation on image-level, we propose the weakly supervised fine segmentation method, which consists of a segmentation network and a decision network. We aggregate image-level information, instead of expensive pixel-level labels, from all training images into the segmentation network, which simultaneously locates and segments fire smoke regions. To train the segmentation network using only image-level annotations, we propose a two-stage weakly supervised learning strategy, in which a novel weakly supervised loss is proposed to roughly detect the region of fire smoke, and a new region-refining segmentation algorithm is further used to accurately identify this region. The decision network incorporating a residual spatial attention module is utilized to predict the category of forest fire smoke. To reduce the complexity of the Faster R-CNN, we first introduced a knowledge distillation technique to compress the structure of this model. To grade forest fire smoke, we used a 3-input/1-output fuzzy system to evaluate the severity level. We evaluated the proposed approach using a developed fire smoke dataset, which included five different scenes varying by the fire smoke level. The proposed method exhibited competitive performance compared to state-of-the-art methods.


2021 ◽  
Author(s):  
Birgit Nordt ◽  
Isabell Hensen ◽  
Solveig Franziska Bucher ◽  
Martin Freiberg ◽  
Richard B. Primack ◽  
...  

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