Determinants of riparian fire severity in two Oregon fires, USA

2008 ◽  
Vol 38 (7) ◽  
pp. 1959-1973 ◽  
Author(s):  
Jessica E. Halofsky ◽  
David E. Hibbs
Keyword(s):  
Random Sampling ◽  
Sampling Design ◽  
Fire Severity ◽  
Mineral Soil ◽  
Basal Area ◽  
Fire Effects ◽  
Forest Stand ◽  
Riparian Areas ◽  
Fuel Component ◽  
Crown Scorch

We sought to understand how vegetation indicators and local topographic factors interact to influence riparian fire severity in two recent fires in Oregon, USA. A stratified random sampling design was used to select points in a range of fire severity classes, forest stand ages, and stream sizes in each fire. At each point, plots were sampled in riparian areas and adjacent uplands. Fire severity was assessed in each plot, and measurements were made of factors that have been found to influence riparian fire severity. Understory fire severity (percent exposed mineral soil and bole char height) was significantly lower in riparian areas compared with adjacent uplands in both fires, suggesting a decoupling in understory fire effects in riparian areas versus uplands. However, overstory fire severity (percent crown scorch and percent basal area mortality) was similar in riparian areas and adjacent uplands in both fires. Fire severity in riparian areas was most strongly associated with upland fire severity. In addition, vegetation indicators, particularly those describing riparian fine fuel component and species composition, were strong predictors of riparian fire severity. Consistency in factors controlling fire severity in the two fires suggests that controls on riparian fire severity may be similar in other regions.

Relationships among indices of fire severity in riparian zones

2009 ◽  
Vol 18 (5) ◽  
pp. 584 ◽  
Author(s):  
Jessica E. Halofsky ◽  
David E. Hibbs
Keyword(s):  
Fire Severity ◽  
Mineral Soil ◽  
Quantitative Measure ◽  
Basal Area ◽  
Remotely Sensed ◽  
Riparian Zones ◽  
Limited Information ◽  
Riparian Areas ◽  
Related Information ◽  
Crown Scorch

There is no standard quantitative measure of fire severity. Although different measures of fire severity are often assumed to be closely related, information on the relationships between these measures of fire severity is limited. Information on the relationship between various fire severity indices is particularly lacking for riparian zones, critical areas of the landscape for both habitat and water quality. The present study explores relationships among several ground-based and remotely sensed indices of fire severity in riparian areas of recent fires in Oregon, including ground-based indices of overstorey fire severity (crown scorch and basal area mortality) and understorey fire severity (height of bole char and exposed mineral soil). There were relatively strong associations between the two overstorey indices of fire severity and also between the two understorey indices of fire severity. However, there were weaker associations between understorey and overstorey fire severity indices, suggesting they are at least partially independent. Results also suggested weak associations between ground-based fire severity indices and remotely sensed fire severity assessments in riparian areas. Overall, we show there are limitations to the interpretation and use of these commonly used fire severity assessments in riparian areas.

Multitemporal LiDAR improves estimates of fire severity in forested landscapes

2018 ◽  
Vol 27 (9) ◽  
pp. 581 ◽  
Author(s):  
Michael S. Hoe ◽  
Christopher J. Dunn ◽  
Hailemariam Temesgen
Keyword(s):  
Spatial Information ◽  
Mean Squared Error ◽  
Fire Severity ◽  
Three Dimensional ◽  
Basal Area ◽  
Point Clouds ◽  
Fire Effects ◽  
Maximum Height ◽  
Ecological Resources ◽  
Change In Mean

Landsat-based fire severity maps have limited ecological resolution, which can hinder assessments of change to specific resources. Therefore, we evaluated the use of pre- and post-fire LiDAR, and combined LiDAR with Landsat-based relative differenced Normalized Burn Ratio (RdNBR) estimates, to increase the accuracy and resolution of basal area mortality estimation. We vertically segmented point clouds and performed model selection on spectral and spatial pre- and post-fire LiDAR metrics and their absolute differences. Our best multitemporal LiDAR model included change in mean intensity values 2–10 m above ground, the sum of proportion of canopy reflection above 10 m, and differences in maximum height. This model significantly reduced root-mean-squared error (RMSE), root-mean-squared prediction error (RMSPE), and bias when compared with models using only RdNBR. Our top combined model integrated RdNBR with LiDAR return proportions <2 m above ground, pre-fire 95% heights and pre-fire return proportions <2 m above ground. This model also significantly reduced RMSE, RMSPE, and bias relative to RdNBR. Our results confirm that three-dimensional spectral and spatial information from multitemporal LiDAR can isolate disturbance effects on specific ecological resources with higher accuracy and ecological resolution than Landsat-based estimates, offering a new frontier in landscape-scale estimates of fire effects.

Recruitment of Picea mariana, Pinus banksiana, and Populus tremuloides across a burn severity gradient following wildfire in the southern boreal forest of Quebec

2004 ◽  
Vol 34 (9) ◽  
pp. 1845-1857 ◽  
Author(s):  
D F Greene ◽  
J Noël ◽  
Y Bergeron ◽  
M Rousseau ◽  
S Gauthier
Keyword(s):  
Boreal Forest ◽  
Populus Tremuloides ◽  
Pinus Banksiana ◽  
Fire Severity ◽  
Mineral Soil ◽  
Basal Area ◽  
Published Data ◽  
Crown Fire ◽  
Conifer Species ◽  
Seed Supply

Most studies of postfire tree recruitment have occurred in severely burned portions, despite the fact that partial burning is common. In this study we examined regeneration following a 1997 fire in the boreal forest of Quebec. A model of postfire recruitment was elaborated using parameters such as the proportion of trees killed (severity), the proportions of postfire seedbed types and their associated juvenile survivorship, the available seed supply, the available bud supply (for Populus tremuloides Michx.), and the granivory rate. All three species had peak recruitment in the first or second summer, and the recruitment episode was essentially finished after the third year. Mineral soil and surviving Sphagnum were the best seedbeds for both conifer species. Seedbed frequency was essentially independent of crown fire severity except for surviving Sphagnum, which was concentrated primarily where severity was light. Conifer fecundity was much lower in the lightly burned stands, a result we attribute to a higher granivory rate. The fecundity (seedlings/basal area for the conifers or suckers/basal area for Populus) in the severe sites was typical of the few other North American studies of postfire recruitment, where the published data permit us to make the comparison.

When It's Hot, It's Hot... Or Maybe It's Not! (Surface Flaming May Not Portend Extensive Soil Heating)

1992 ◽  
Vol 2 (3) ◽  
pp. 139 ◽  
Author(s):  
RA Hartford ◽  
WH Frandsen
Keyword(s):  
Forest Floor ◽  
Fire Severity ◽  
Mineral Soil ◽  
Soil Surface ◽  
Fire Effects ◽  
Fire Intensity ◽  
Surface Moisture ◽  
Long Duration ◽  
Key Variables ◽  
Duration Of Heating

Fire effects on aplant community, soil, and air are not apparent when judged only by surface fire intensity. The fire severity or fire impact can be described by the temperatures reached within the forest floor and the duration of heating experienced in the vegetation, forest floor, and underlying mineral soil. Temporal distributions of temperatures illustrate heat flow in duff and mineral soil in three instrumented plots: two with slash fuel over moist duff and one with litter fuel over dry duff. Fires in the two slash fuel plots produced substantial flame lengths but minimal heating in the underlying mineral soil. In contrast, smoldering combustion in the dry duff plot produced long duration heating with nearly complete duff consumption and lethal temperatures at the mineral soil surface. Moisture content of duff and soil were key variables for determining f i e impact on the forest floor.

Seedbed variation from the interior through the edge of a large wildfire in Alberta

2005 ◽  
Vol 35 (7) ◽  
pp. 1640-1647 ◽  
Author(s):  
David F Greene ◽  
S Ellen Macdonald ◽  
Steve Cumming ◽  
Lynn Swift
Keyword(s):  
Populus Tremuloides ◽  
Life Histories ◽  
Fire Severity ◽  
Mineral Soil ◽  
Basal Area ◽  
White Spruce ◽  
Forest Composition ◽  
Fire Intensity ◽  
Soil Exposure ◽  
In Fire

Despite the importance of seedbeds in the life histories of many plant species, there has been little study of the seedbeds created by wildfire in fire-prone vegetation types such as the boreal forest. Both within the interior and at the edge of a very large (>100 000 ha) 2001 wildfire in the mixedwood boreal region of Alberta, we examined the postfire duff depth and the percent coverage of seedbed types. Minimizing the effect of site and forest composition, we looked only at Picea glauca (Moench) Voss – Populus tremuloides Michx. sites burned during a single day of high fire intensity. Good seedbeds (thin humus and exposed mineral soil, with or without ash) averaged 35% coverage within the interior of the fire but varied enormously among stands. There was a weak but significant positive correlation between prefire percent white spruce basal area and percent mineral soil exposure; that is, there is some tendency for conifer stands to create the seedbeds best suited for their own germinants. Fire severity played a clear role in mineral soil exposure, which was greatest in areas with 100% canopy mortality. Mineral soil exposure was far less at the edges of the fire, averaging only 5% even in areas where all trees had been killed; the burn edge was characterized by superficial flaming combustion with no evidence of substantial duff removal via smoldering combustion. In short, the areas where white spruce seed will be most common after the fire, the edges, are where the worst seedbeds in the burn will be found. Regeneration microsites at fire edges appear to be better suited to regeneration of broadleaf species, via suckering; the persistence of white spruce in fire-prone landscapes continues to be difficult to explain.

scholarly journals Assessing the Effect of Training Sampling Design on the Performance of Machine Learning Classifiers for Land Cover Mapping Using Multi-Temporal Remote Sensing Data and Google Earth Engine

2021 ◽  
Vol 13 (8) ◽  
pp. 1433
Author(s):  
Shobitha Shetty ◽  
Prasun Kumar Gupta ◽  
Mariana Belgiu ◽  
S. K. Srivastav
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Random Sampling ◽  
Sampling Design ◽  
Remote Sensing Data ◽  
Google Earth ◽  
Machine Learning Classifiers ◽  
Learning Classifiers ◽  
Multi Temporal ◽  
Google Earth Engine

Machine learning classifiers are being increasingly used nowadays for Land Use and Land Cover (LULC) mapping from remote sensing images. However, arriving at the right choice of classifier requires understanding the main factors influencing their performance. The present study investigated firstly the effect of training sampling design on the classification results obtained by Random Forest (RF) classifier and, secondly, it compared its performance with other machine learning classifiers for LULC mapping using multi-temporal satellite remote sensing data and the Google Earth Engine (GEE) platform. We evaluated the impact of three sampling methods, namely Stratified Equal Random Sampling (SRS(Eq)), Stratified Proportional Random Sampling (SRS(Prop)), and Stratified Systematic Sampling (SSS) upon the classification results obtained by the RF trained LULC model. Our results showed that the SRS(Prop) method favors major classes while achieving good overall accuracy. The SRS(Eq) method provides good class-level accuracies, even for minority classes, whereas the SSS method performs well for areas with large intra-class variability. Toward evaluating the performance of machine learning classifiers, RF outperformed Classification and Regression Trees (CART), Support Vector Machine (SVM), and Relevance Vector Machine (RVM) with a >95% confidence level. The performance of CART and SVM classifiers were found to be similar. RVM achieved good classification results with a limited number of training samples.

scholarly journals Urban Fire Severity and Vegetation Dynamics in Southern California

2020 ◽  
Vol 13 (1) ◽  
pp. 19
Author(s):  
Lauren E. H. Mathews ◽  
Alicia M. Kinoshita
Keyword(s):  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Current Knowledge ◽  
Fire Severity ◽  
Satellite Image ◽  
Burn Severity ◽  
Native Vegetation ◽  
Riparian Areas ◽  
The Impact

A combination of satellite image indices and in-field observations was used to investigate the impact of fuel conditions, fire behavior, and vegetation regrowth patterns, altered by invasive riparian vegetation. Satellite image metrics, differenced normalized burn severity (dNBR) and differenced normalized difference vegetation index (dNDVI), were approximated for non-native, riparian, or upland vegetation for traditional timeframes (0-, 1-, and 3-years) after eleven urban fires across a spectrum of invasive vegetation cover. Larger burn severity and loss of green canopy (NDVI) was detected for riparian areas compared to the uplands. The presence of invasive vegetation affected the distribution of burn severity and canopy loss detected within each fire. Fires with native vegetation cover had a higher severity and resulted in larger immediate loss of canopy than fires with substantial amounts of non-native vegetation. The lower burn severity observed 1–3 years after the fires with non-native vegetation suggests a rapid regrowth of non-native grasses, resulting in a smaller measured canopy loss relative to native vegetation immediately after fire. This observed fire pattern favors the life cycle and perpetuation of many opportunistic grasses within urban riparian areas. This research builds upon our current knowledge of wildfire recovery processes and highlights the unique challenges of remotely assessing vegetation biophysical status within urban Mediterranean riverine systems.

scholarly journals Predicting wildfire impacts on the prehistoric archaeological record of the Jemez Mountains, New Mexico, USA

Fire Ecology ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Megan M. Friggens ◽  
Rachel A. Loehman ◽  
Connie I. Constan ◽  
Rebekah R. Kneifel
Keyword(s):  
New Mexico ◽  
Fire Severity ◽  
Fire Effects ◽  
Burn Severity ◽  
Fire Season ◽  
Archaeological Sites ◽  
Archaeological Record ◽  
Human Environment ◽  
Jemez Mountains ◽  
Archaeological Materials

Abstract Background Wildfires of uncharacteristic severity, a consequence of climate changes and accumulated fuels, can cause amplified or novel impacts to archaeological resources. The archaeological record includes physical features associated with human activity; these exist within ecological landscapes and provide a unique long-term perspective on human–environment interactions. The potential for fire-caused damage to archaeological materials is of major concern because these resources are irreplaceable and non-renewable, have social or religious significance for living peoples, and are protected by an extensive body of legislation. Although previous studies have modeled ecological burn severity as a function of environmental setting and climate, the fidelity of these variables as predictors of archaeological fire effects has not been evaluated. This study, focused on prehistoric archaeological sites in a fire-prone and archaeologically rich landscape in the Jemez Mountains of New Mexico, USA, identified the environmental and climate variables that best predict observed fire severity and fire effects to archaeological features and artifacts. Results Machine learning models (Random Forest) indicate that topography and variables related to pre-fire weather and fuel condition are important predictors of fire effects and severity at archaeological sites. Fire effects were more likely to be present when fire-season weather was warmer and drier than average and within sites located in sloped, treed settings. Topographic predictors were highly important for distinguishing unburned, moderate, and high site burn severity as classified in post-fire archaeological assessments. High-severity impacts were more likely at archaeological sites with southern orientation or on warmer, steeper, slopes with less accumulated surface moisture, likely associated with lower fuel moistures and high potential for spreading fire. Conclusions Models for predicting where and when fires may negatively affect the archaeological record can be used to prioritize fuel treatments, inform fire management plans, and guide post-fire rehabilitation efforts, thus aiding in cultural resource preservation.

Post-fire survival and flushing in three Sierra Nevada conifers with high initial crown scorch

2009 ◽  
Vol 18 (7) ◽  
pp. 857 ◽  
Author(s):  
Chad T. Hanson ◽  
Malcolm P. North
Keyword(s):  
Sierra Nevada ◽  
Pinus Ponderosa ◽  
Fire Severity ◽  
Conifer Species ◽  
Mature Trees ◽  
Salvage Logging ◽  
Abies Magnifica ◽  
Crown Scorch ◽  
Tree Survival ◽  
Large Trees

With growing debate over the impacts of post-fire salvage logging in conifer forests of the western USA, managers need accurate assessments of tree survival when significant proportions of the crown have been scorched. The accuracy of fire severity measurements will be affected if trees that initially appear to be fire-killed prove to be viable after longer observation. Our goal was to quantify the extent to which three common Sierra Nevada conifer species may ‘flush’ (produce new foliage in the year following a fire from scorched portions of the crown) and survive after fire, and to identify tree or burn characteristics associated with survival. We found that, among ponderosa pines (Pinus ponderosa Dougl. ex. Laws) and Jeffrey pines (Pinus jeffreyi Grev. & Balf) with 100% initial crown scorch (no green foliage following the fire), the majority of mature trees flushed, and survived. Red fir (Abies magnifica A. Murr.) with high crown scorch (mean = 90%) also flushed, and most large trees survived. Our results indicate that, if flushing is not taken into account, fire severity assessments will tend to overestimate mortality and post-fire salvage could remove many large trees that appear dead but are not.

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

2017 ◽  
Vol 8 (1) ◽  
pp. 55-62
Author(s):  
Lailan Syaufina ◽  
Vera Linda Purba
Keyword(s):  
Growth Performance ◽  
Forest Fire ◽  
Health Monitoring ◽  
Fire Severity ◽  
Forest Health ◽  
Chemical Properties ◽  
Fire Effects ◽  
Burned Areas ◽  
Forest Health Monitoring ◽  
Physical And Chemical

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

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