Severe Forest Fires Research Articles

Assessing the Relationship between Forest Structure and Fire Severity on the North Rim of the Grand Canyon

While operational fire severity products inform fire management decisions in Grand Canyon National Park (GRCA), managers have expressed the need for better quantification of the consequences of severity, specifically forest structure. In this study we computed metrics related to the forest structure from airborne laser scanning (ALS) data and investigated the influence that fires that burned in the decade previous had on forest structure on the North Rim of the Grand Canyon in Arizona. We found that fire severity best explains the occurrence of structure classes that include canopy cover, vertical fuel distribution, and surface roughness. In general we found that high fire severity resulted in structure types that exhibit lower canopy cover and higher surface roughness. Areas that burned more frequently with lower fire severity in general had a more closed canopy and a lower surface roughness, with less brush and less conifer regeneration. In a random forests modeling exercise to examine the relationship between severity and structure we found mean canopy height to be a powerful explanatory variable, but still proved less informative than the three-component structure classification. We show that fire severity not only impacts forest structure but also brings heterogeneity to vegetation types along the elevation gradient on the Kaibab plateau. This work provides managers with a unique dataset, usable in conjunction with vegetation, fuels and fire history data, to support management decisions at GRCA.

Forest Fire Severity Classification Using Probability Density Function and KOMPSAT-3A

Forest Fire Severity Classification Using Probability Density Function and KOMPSAT-3A

Evaluation of Spectral Indices for Assessing Fire Severity in Australian Temperate Forests

Spectral indices derived from optical remote sensing data have been widely used for fire-severity classification in forests from local to global scales. However, comparative analyses of multiple indices across diverse forest types are few. This represents an information gap for fire management agencies in areas like temperate south-eastern Australia, which is characterised by a diversity of natural forests that vary in structure, and in the fire-regeneration strategies of the dominant trees. We evaluate 10 spectral indices across eight areas burnt by wildfires in 1998, 2006, 2007, and 2009 in south-eastern Australia. These wildfire areas encompass 13 forest types, which represent 86% of the 7.9M ha region’s forest area. Forest types were aggregated into six forest groups based on their fire-regeneration strategies (seeders, resprouters) and structure (tree height and canopy cover). Index performance was evaluated for each forest type and forest group by examining its sensitivity to four fire-severity classes (unburnt, low, moderate, high) using three independent methods (anova, separability, and optimality). For the best-performing indices, we calculated index-specific thresholds (by forest types and groups) to separate between the four severity classes, and evaluated the accuracy of fire-severity classification on independent samples. Our results indicated that the best-performing indices of fire severity varied with forest type and group. Overall accuracy for the best-performing indices ranged from 0.50 to 0.78, and kappa values ranged from 0.33 (fair agreement) to 0.77 (substantial agreement), depending on the forest group and index. Fire severity in resprouter open forests and woodlands was most accurately mapped using the delta Normalised Burnt ratio (dNBR). In contrast, dNDVI (delta Normalised difference vegetation index) performed best for open forests with mixed fire responses (resprouters and seeders), and dNDWI (delta Normalised difference water index) was the most accurate for obligate seeder closed forests. Our analysis highlighted the low sensitivity of all indices to fire impacts in Rainforest. We conclude that the optimal spectral index for quantifying fire severity varies with forest type, but that there is scope to group forests by structure and fire-regeneration strategy to simplify fire-severity classification in heterogeneous forest landscapes.

Mapping Burn Severity of Forest Fires in Small Sample Size Scenarios

Mapping burn severity of forest fires can contribute significantly to understanding, quantifying and monitoring of forest fire severity and its impacts on ecosystems. In recent years, several remote sensing-based methods for mapping burn severity have been reported in the literature, of which the implementations are mainly dependent on several field plots. Therefore, it is a challenge to develop alternative method of mapping burn severity using limited number of field plots. In this study, we proposed a support vector regression based method using multi-temporal satellite data to map the burn severity, evaluated its performance by calculating correlations between the predicted and the observed Composite Burn Index, and compared the performance with that of the regression analysis method (based on dNBR). The results show that the performance of support vector regression based mapping method is more accurate (RMSE = 0.46–0.57) than that of regression analysis method (RMSE = 0.53–0.68). Even with fewer training sets, it can map the detailed distribution of burn severity of forest fires and can achieve relatively better generalization, compared to regression analysis burn severity mapping methods. It could be concluded that the proposed support vector regression based mapping method is an alternative to the regression analysis method in small sample size scenarios. This method with excellent generalization performance should be recommended for future studies on burn severity of forest fires.

Forest Fire Severity Affects Host Plant Quality and Insect Herbivore Damage

Abstract Climate change models predict increased forest fire occurrence and severity in the near future. Forest fire disturbance affects multiple ecological interactions, but there is little evidence for how naturally-occurring fires affect plant quality and herbivore damage, which is important because plants and herbivorous insects comprise most of the diversity in natural ecosystems and are responsible for a variety of ecosystem services. We surveyed three fires in the Rocky Mountains to investigate the effects of fire severity on wax currant (Ribes cereum), an important source of food and cover for wildlife in Colorado. We measured plant quality and herbivore damage; we found that fire severity had a significant negative effect on both measures. Notably, high severity fires decreased herbivore damage by about 50%. Furthermore, we found that the effect of fire on insect herbivore damage is mostly direct, but that indirect effects mediated through changes in plant quality are also significant. Our results have important implications for the effects of climate-driven increases in fire severity on plant-insect interactions, illustrating strong direct and weaker indirect negative effects of fire severity in a forest ecosystem.

A Probabilistic Method Predicting Forest Fire Occurrence Combining Firebrands and the Weather-Fuel Complex in the Northern Part of the Daxinganling Region, China

The fire danger rating method currently used in the northern part of the Daxinganling Region with the most severe forest fires in China only uses weather variables without considering firebrands. The discrepancy between fire occurrence and fire risk by FFDWR (Forest Fire-Danger Weather Rating, a method issued by the National Meteorological Bureau, that is used to predict forest fire probability through links between forest fire occurrence and weather variables) in the northern part is more obvious than that in the southern part. Great discrepancy has emerged between fire danger predicted by the method and actual fire occurrence in recent years since a strict firebrand prohibition policy has significantly reduced firebrands in the region. A probabilistic method predicting fire probability by introducing an Ignition Component (IC) in the National Fire Danger Rating System (NFDRS) adopted in the United States to depict effects of both firebrand and weather-fuel complex on fire occurrence is developed to solve the problem. The suitability and accuracy of the new method in the region were assessed. Results show that the method is suitable in the region. IC or the modified IC can be adopted to depict the effect of the weather-fuel complex on fire occurrence and to rate fire danger for periods with fewer firebrands. Fire risk classes and corresponding preparedness level can be determined from IC in the region. Methods of the same principle could be established to diminish similar discrepancy between actual fire occurrence and fire danger in other countries.

Fuel Treatments and Potential Fire Behavior in Peri-Urban Forests in Northern Greece

The peri-urban and urban forests in Greece occupy a total area of 105.353 ha. In these vulnerable ecosystems, fire constitutes a natural disaster presenting particular challenges and specific difficulties. These include the high number of visitors as well as the forest characteristics, such as the presence of particularly flammable tree species and the high accumulation of combustible biomass, that make the on-start of fires more likely. The main purpose of the current research is to identify the optimum combination of silvicultural treatments to efficiently reduce potential severity of forest fires and to facilitate their successful suppression by firefighting crews. In order to simulate the basic fire environment of urban forests, two main experimental plots were established and several tree and topographical characteristics were measured. Additionally, a crown fire hazard modelling system (NEXUS) was used to simulate forest fire potential behavior before and after the adoption of the silvicultural treatments that altered critical characteristics of the forest fire environment. The results clearly show that specific silvicultural prescriptions altered the type of forest fire spreading potential, revealing the overall efficiency of preventing actions during forest management.

PERAN CURAH HUJAN TERHADAP PENURUNAN HOTSPOT KEBAKARAN HUTAN DAN LAHAN DI EMPAT PROVINSI DI INDONESIA PADA TAHUN 2015-2016 The Role of Rainfall Towards Forest and Land Fires Hotspot Reduction in Four Districs in Indonesia on 2015-2016

Forest and land fires are not a new phenomenon for some areas in Indonesia, such as Kalimantan andSumatra. Riau, South Sumatra, West Kalimantan and Central Kalimantan are among provinces that havebeen suffered from severe forest and land fires every year. One of the natural factors affecting forest andland fires occurrences in Indonesia is climate. This study analyzes the relationship between hotspots andrainfall in Indonesia on 2015-2016. The results show that a large number of hotspots is found in the dryseason when the rainfall was less, i.e., on July - October 2015 and July - August 2016. Statistically, monthlyrainfall and monthly hotspots has a negative correlation (-) with R2 = 42.5% and P-value = 0.001. Theequation built is y = 3182 - 2.50x, where y denotes hotspots and x for rainfall.Key words: forest and land fires, hotspot, rainfall

Evaluating and comparing Sentinel 2A and Landsat-8 Operational Land Imager (OLI) spectral indices for estimating fire severity in a Mediterranean pine ecosystem of Greece

The main purpose of this study is to explore the relationship between three field-based fire severity indices (Composite Burn Index-CBI, Geometrically structure CBI, weighted CBI) and spectral indices derived from Sentinel 2A and Landsat-8 OLI imagery on a recent large fire in Thasos, Greece. We employed remotely sensed indices previously used from the remote sensing fire community (Normalized Difference Vegetation Index (NDVI), Normalized Burn Ratio (NBR), differenced NDVI, differenced NBR, relative differenced NBR, Relativized Burn Ratio) and seven Sentinel 2A-specific indices considering the availability of spectral information recorded in the red-edge spectral region. The statistical correlation indicated a slightly stronger relationship between the differenced NBR and the GeoCBI for both Sentinel 2A (r = 0.872) and Landsat-8 OLI (r = 0.845) imagery. Predictive local thresholds of dNBR values showed slightly higher classification accuracy for Sentinel 2A (73.33%) than Landsat-8 OLI (71.11%), suggesting the adequacy of Sentinel 2A for forest fire severity assessment and mapping in Mediterranean pine ecosystems. The evaluation of the classification thresholds calculated in this study over other fires with similar pre-fire conditions could contribute in the operational mapping and reconstruction of the historical patterns of fire severity over the Eastern Mediterranean region.

Issues and Possible Improvements in Winter Fires Detection by Satellite Radiances Analysis: Lesson Learned in Two Regions of Northern Italy

Lombardy is a region of Northern Italy characterized by an alpine/continental climate, where, in winter, strong dry winds and scarce plants hydration frequently cause surface fires with a relatively low intensity level. In Liguria, a coastal region of Northwestern Italy, climate and vegetation conditions are different from Lombardy; in both winter and summer, severe forest fires frequently occur. This study is based on the investigation of winter fire regimes characterizing the aforementioned regions, using Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) data. In particular, we compare the RST-FIRES and the well-established MOD14/MYD14 fire detection products in order to assess their performance in detecting winter fires in Northern Italy. The study shows as a result that, despite the advantages offered by self-adaptive algorithms like RST-FIRES at local/regional scale, wildfires occurring in Lombardy during the winter season are challenging to identify by satellite. In Liguria region, where morphological and weather conditions favor flame propagation, they seem to be better detectable from space. This study aims at investigating issues affecting satellite monitoring of winter fires by encouraging the usage of a multiplatform observing system, integrating data provided by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard Meteosat Second Generation (MSG) satellites, for better supporting fire management activities.

PENILAIAN DAMPAK KEBAKARAN PADA TEGAKAN AKASIA DI BKPH PARUNG PANJANG KPH BOGOR, PERUM PERHUTANI UNIT III JAWA BARAT DAN BANTEN Fire Severity Assessment on Akasia stand at BKPH Parung Panjang KPH Bogor, Perum Perhutani III West Java and Banten

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

Extrapolating Forest Canopy Fuel Properties in the California Rim Fire by Combining Airborne LiDAR and Landsat OLI Data

Accurate, spatially explicit information about forest canopy fuel properties is essential for ecosystem management strategies for reducing the severity of forest fires. Airborne LiDAR technology has demonstrated its ability to accurately map canopy fuels. However, its geographical and temporal coverage is limited, thus making it difficult to characterize fuel properties over large regions before catastrophic events occur. This study presents a two-step methodology for integrating post-fire airborne LiDAR and pre-fire Landsat OLI (Operational Land Imager) data to estimate important pre-fire canopy fuel properties for crown fire spread, namely canopy fuel load (CFL), canopy cover (CC), and canopy bulk density (CBD). This study focused on a fire prone area affected by the large 2013 Rim fire in the Sierra Nevada Mountains, California, USA. First, LiDAR data was used to estimate CFL, CC, and CBD across an unburned 2 km buffer with similar structural characteristics to the burned area. Second, the LiDAR-based canopy fuel properties were extrapolated over the whole area using Landsat OLI data, which yielded an R2 of 0.8, 0.79, and 0.64 and RMSE of 3.76 Mg·ha−1, 0.09, and 0.02 kg·m−3 for CFL, CC, and CBD, respectively. The uncertainty of the estimates was estimated for each pixel using a bootstrapping approach, and the 95% confidence intervals are reported. The proposed methodology provides a detailed spatial estimation of forest canopy fuel properties along with their uncertainty that can be readily integrated into fire behavior and fire effects models. The methodology could be also integrated into the LANDFIRE program to improve the information on canopy fuels.

Gap regeneration within mature deciduous forests of Interior Alaska: Implications for future forest change

Increased fire severity in boreal forests of Interior Alaska is shifting forest canopy composition from black spruce (Picea mariana) to deciduous species, including trembling aspen (Populus tremuloides) and Alaska paper birch (Betula neoalaskana). Because deciduous trees are less flammable than black spruce, the dominant disturbance regime in deciduous forests could move away from fire to one of gap disturbances. In this study, we quantified forest gap characteristics and vegetation within eight mature (62–119-yr-old) deciduous stands in Interior Alaska. Canopy gaps were generally small (true gap area <50m2), formed by the mortality of 4–16 gap makers (which were always deciduous trees), and occupied ∼17–29% of the forest except in the oldest stand, where gap fraction exceeded 45%, and in one anomalous 84-yr old stand, where gaps were absent. Canopy openness increased linearly with gap area, but density of both deciduous and evergreen tree recruits was generally low and insufficient to create future stands with densities similar to those currently found in mature stands across the landscape. Canopy openness was instead correlated with decreased leaf litter cover and increased cover of moss, lichen, and evergreen shrubs. Given the low recruitment of trees with canopy gaps and the decreased probability of fire, deciduous stands will likely transition to non-forested areas or low density stands once overstory trees reach maturity and die. This could have numerous implications for ecosystem function, including carbon (C), water, and energy balance, and potential feedbacks to future fire occurrence and regional climate.

FIRE SEVERITY ASSESSMENT USING NDVI DERIVED FROM LANDSAT TM/ETM IMAGES AND TERRAIN DATA

The forest fires influence on the plants and soil depends on the fire severity and time of exposure. Fire severity integrates physical, chemical and biological changes occurring in ecosystems on the area as a consequence of fire influence. The purpose of the current investigation was to examine the role of the forest fire severity on the vegetation cover of the area of Svilengrad Municipality, using NDVI (Normalized Difference Vegetation Index) before fire and after fire, derived from LANDSAT 8 TM/ETM images. The comparison of the data from NDVI and that observed on the terrain data was also targeted. The results show that NDVI are changed significantly in fire affected area depending on vegetation cover and type of fire. This index also is very sensitive to changes during time after fire occurrence. One year after fire occurrence the NDVI values increased to +0.305 (0.048) for whole studied area. Through dNDVI could be distinguish the recovery rates of the fire affected areas with different tree species.

Contrasting Effects of Fire Severity on the Regeneration of Pinus halepensis Mill. and Resprouter Species in Recently Thinned Thickets

Many studies have outlined the benefits for growth and reproduction resulting from thinning extremely crowded young forests regenerating after stand replacing wildfires (“thickets”). However, scarce information is available on how thinning may influence fire severity and vegetation regeneration in case a new fire occurs. We investigated the relationship between thinning and fire severity in P. halepensis thickets, and the effects on the establishment of pine seedlings and resprouting vigour in resprouter species the year after the fire. Our results show a positive relationship between forest basal area and fire severity, and thus reserved pines in thinned stands suffered less fire damage than those in un‐thinned sites (respectively, 2.02 ± 0.13 vs. 2.93 ± 0.15 in a scale from 0 to 4). Ultimately, differences in fire severity influenced post‐fire regeneration. Resprouting vigour varied depending on the species and the size of individuals but it was consistently higher in thinned stands. Concerning P. halepensis, the proportion of cones surviving the fire decreased with fire severity. However, this could not compensate the much lower pine density in thinned stands and thus the overall seed crop was higher in un‐thinned areas. Establishment of pine seedlings was negatively affected by the slope and positively driven by the number of cones and thus it was higher in un‐thinned than in thinned stands (respectively, 2581 ± 649 vs. 898 ± 325 seedlings∙ha-1). Thinning decreases fire intensity, and thus it may facilitate fire suppression tasks, but retaining a higher density of pines would be necessary to ensure P. halepensis regeneration after a new fire event.

Mapping prescribed fire severity in south-east Australian eucalypt forests using modelling and satellite imagery: a case study

Accurate fire severity maps are fundamental to the management of flammable landscapes. Severity mapping methods have been developed and tested for wildfire, but need further refinement for prescribed fire. We evaluated the accuracy of two severity mapping methods for a low-intensity, patchy prescribed fire in a south-eastern Australian eucalypt forest: (1) the Normalised Difference Vegetation Index (NDVI) derived from RapidEye satellite imagery, and (2) PHOENIX RapidFire, a fire-spread simulation model. We used each method to generate a fire severity map (four-category: unburnt, low, moderate and severe), and then validated the maps against field-based data. We used error matrices and the Kappa statistic to assess mapping accuracy. Overall, the satellite-based map was more accurate (75%; Kappa±95% confidence interval 0.54±0.06) than the modelled map (67%; Kappa 0.40±0.06). Both methods overestimated the area of unburnt forest; however, the satellite-based map better represented moderately burnt areas. Satellite- and model-based methods both provide viable approaches for mapping prescribed fire severity, but refinements could further improve map accuracy. Appropriate severity mapping methods are essential given the increasing use of prescribed fire as a forest management tool.

Recognising the value of all ‘restorative’ contributions

Recognising the value of all ‘restorative’ contributions

Effects of wind and tree density on forest fire patterns in a mixed-tree species forest

ABSTRACTIt is well known that global climate change causes an increase in forest fire frequency and severity. Thus, understanding fire dynamics is necessary to comprehend the mitigation of the negative effects of forest fires. Our objective was to inform how fire spreads in a simulated two-species forest with varying wind strengths. The forest in this study was comprised of two different tree species with varying probabilities of transferring fire that was randomly distributed in space at densities (Ctot) ranging from 0.0 (low) to 1.0 (high). We studied the distribution pattern of burnt trees by using local rules of the two-dimensional model. This model incorporated wind blowing from south to north with strength (Pw) ranging from 0.0 (low) to 1.0 (high). Simulation results showed that when Ctot > 0.45 the fire covered the entire forest, but when Ctot ≤ 0.45 the fire did not spread. The wind effect on the variation of the amount of the burnt tree was maximized at the critical density and dramatically decreased with increasing Ctot. Additionally, we found that the term of Ctot and Pw plays an important role in determining the distribution.

Spatially modeling wildland fire severity in pine forests of Galicia, Spain

Fire is a major disturbance in forests and one of the most important carbon emissions sources, which contributes to climate change. Carbon emissions are directly correlated with the degree of organic matter consumption or fire severity. Gaining knowledge about the relative strength of the various explanatory variables is essential to mitigate its environmental impact. We tested an approach that combines wind modeling, light detection and ranging (LiDAR), remotely sensed vegetation indices and topography data for assessing the occurrence of high-severity fire using the random forests ensemble learning method. Data from four wildfires that occurred in Galicia (northwestern Spain) were used to exemplify the application of this approach. The models predicted high-severity occurrence with a classification accuracy ranging from 77 to 94%. High-severity fire occurred more frequently in areas of high simulated wind speed, and more pronouncedly, for cases reported as wind-driven fires. High severity also occurred more frequently in areas of high terrain roughness, on sunny slopes and in low canopy base height stands. This approach allowed predicting spatially explicit fire severity at a mean scale level (resolution of 25 m) with accuracy rates from 80 to 95%. This approach may be helpful for fire managers when delimiting and planning fuel treatments for severity mitigation or during fire suppression, and for post hoc case studies.

Torpor and basking after a severe wildfire: mammalian survival strategies in a scorched landscape.

Wildfires can completely obliterate above-ground vegetation, yet some small terrestrial mammals survive during and after fires. As knowledge about the physiological and behavioural adaptations that are crucial for post-wildfire survival is scant, we investigated the thermal biology of a small insectivorous marsupial (Antechinus flavipes) after a severe forest fire. Some populations of antechinus survived the fire in situ probably by hiding deep in rocky crevices, the only fire-proof sites near where they were trapped. We hypothesised that survival in the post-fire landscape was achieved by decreasing daytime activity and using torpor frequently to save energy. Indeed, daytime activity was less common and torpor expression was substantially higher (≥2-fold) at the post-fire site than observed in an unburnt control site and also in comparison to a laboratory study, both when food was provided ad libitum and withheld. Basking in the post-fire site was also recorded, which was likely used to further reduce energy expenditure. Our data suggest that torpor and basking are used by this terrestrial mammal to reduce energy and foraging requirements, which is important in a landscape where food and shelter are limited and predation pressure typically is increased.