Fuel moisture, forest type, and lightning-caused fire in Yellowstone National Park

1992 ◽  
Vol 22 (1) ◽  
pp. 37-45 ◽  
Author(s):  
Roy A. Renkin ◽  
Don G. Despain
Keyword(s):  
Yellowstone National Park ◽  
National Park ◽  
Forest Cover ◽  
Forest Type ◽  
Fire Season ◽  
Fuel Moisture ◽  
Forest Types ◽  
Forest Cover Type ◽  
Fire Activity ◽  
Moisture Conditions

The occurrence and behavior of lightning-caused fires in Yellowstone National Park were summarized for 17 years (1972–1988) during a prescribed natural fire program. Both ignition (occurrence) and spread (stand replacing fire activity) of fires were strongly influenced by fuel moisture and forest cover type. Fuel moisture estimates of 13% for large (>7.6 cm) dead and downed fuels indicated a threshold below which proportionately more fire starts and increased stand replacing fire activity were observed. During periods of suitable fuel moisture conditions, fire occurrence and activity were significantly greater than expected in old-growth, mixed-canopy lodgepole pine (Pinuscontorta Dougl. var. latifolia) and Engelmann spruce–subalpine fir (Piceaengelmannii Parry–Abieslasiocarpa (Hook.) Nutt.) forest types, and significantly less than expected in the successional lodgepole pine forest types. During periods of extended low fuel moisture conditions (drought), sustained high winds significantly reduced the influence of forest cover type on stand replacing fire activity. These extreme weather conditions were observed during the later stages of the 1988 fire season, and to a lesser extent, for a short duration during the 1981 fire season. The Douglas-fir (Pseudotsugamenziesii (Mirb.) Franco) forest type typically supported little stand replacing fire activity, even though a preponderance of fire starts was observed.

scholarly journals The woody flora of Shettihalli Wildlife Sanctuary, central Western Ghats of Karnataka, India - A checklist

2021 ◽  
Vol 13 (13) ◽  
pp. 20033-20055
Author(s):  
Naveen Babu Kanda ◽  
Kurian Ayushi ◽  
Vincy K. Wilson ◽  
Narayanan Ayyappan ◽  
Narayanaswamy Parthasarathy
Keyword(s):  
Western Ghats ◽  
Forest Cover ◽  
Forest Type ◽  
Human Impacts ◽  
Forest Types ◽  
Wildlife Sanctuary ◽  
Peninsular India ◽  
Ecological Features ◽  
Central Western Ghats ◽  
The Western Ghats

Documenting the biodiversity of protected areas and reserve forests is important to researchers, academicians and forest departments in their efforts to establish policies to protect regional biodiversity. Shettihalli Wildlife Sanctuary (SWS) is an important protected area located in the central Western Ghats of Karnataka state known for its diverse flora and fauna with distinct ecological features. For the last four decades the sanctuary has witnessed the loss of forest cover, yet the vegetation in few locations is relatively undisturbed. The current inventory was undertaken during 2019–2020 to provide a checklist of woody species from SWS under-researched earlier. The list comprises 269 species of trees, lianas and shrubs distributed in 207 genera and 68 families. The most diverse families are Fabaceae, Moraceae, Rubiaceae, Rutaceae, Lauraceae, Apocynaceae, Meliaceae, Malvaceae, Phyllanthaceae, and Anacardiaceae, representing 48% of total woody flora. The sanctuary shelters 263 native and six exotic plant species. Thirty-nine species were endemic to the Western Ghats, five species to peninsular India and one species to the Western Ghats and Andaman & Nicobar Islands. Four forest types, i.e., dry deciduous, moist deciduous, semi-evergreen, and evergreen forests, are represented in the sanctuary. Of the total species, only seven occurred in all forest types, while 111 species are exclusive to a single forest type. One-hundred-and-four taxa were assessed for the International Union for Conservation of Nature & Natural Resources (IUCN) Red List. Ten species that fall under Near Threatened, Vulnerable, and Endangered categories were encountered occasionally. The baseline data generated on plant diversity will be useful in highlighting the importance of these forests for species conservation and forest management. Such data form a cornerstone for further research. For instance, to understand the effect of invasive species and human impacts on the diversity of the region. 

scholarly journals Estimates of Down Woody Materials on Fort A.P. Hill, Virginia

2008 ◽  
Vol 32 (2) ◽  
pp. 53-59 ◽  
Author(s):  
Jason R. Applegate
Keyword(s):  
Coarse Woody Debris ◽  
Forest Inventory ◽  
Forest Cover ◽  
Forest Type ◽  
Wildland Fire ◽  
Woody Debris ◽  
Forest Cover Type ◽  
Cover Type ◽  
Forest Cover Types ◽  
Structure Class

Abstract An inventory of down woody materials (DWM) was conducted on Fort A.P. Hill, Virginia, to develop a baseline of DWM abundance and distribution to assist in wildland fire management. Estimates of DWM are necessary to develop accurate assessments of wildfire hazard, model wildland fire behavior, and establish thresholds for retaining DWM, specifically CWD (coarse woody debris), as a structural component of forest ecosystems. DWM were sampled by forest type and structure class using US Forest Service, Forest Inventory and Analysis (FIA) field procedures. DWM averaged 12–16 tn/ac depending on forest cover type and structure class. Coarse woody debris (CWD) averaged 2.7–13.0 tn/ac depending on forest cover type and structure class. CWD comprised more than 70% of DWM across all forest cover types and structure classes. Fine woody debris (FWD) averaged 0.05–3.2 tn/ac depending on fuel hour class, forest cover type, and structure class. DWM was consistently higher in mature (sawtimber) forests than in young (poletimber) forests across all forest cover types, attributed to an increased CWD component of DWM. The variability associated with DWM suggests that obtaining robust estimates of CWD biomass will require a higher sampling intensity than FWD because of its nonuniform distribution in forest systems. FIA field procedures for tallying and quantifying DWM were practical, efficient, and, subsequently, included as permanent metrics in Fort A.P. Hill's Continuous Forest Inventory program.

scholarly journals Bootstrapping Wildfire Selectivity for the Forest Types of Canton Ticino (Switzerland)

2011 ◽  
Vol 15 (19) ◽  
pp. 1-11 ◽  
Author(s):  
Sofia Bajocco ◽  
Gianni Boris Pezzatti ◽  
Antonella De Angelis ◽  
Marco Conedera ◽  
Carlo Ricotta
Keyword(s):  
Resource Selection ◽  
Forest Cover ◽  
Forest Type ◽  
Null Model ◽  
Direct Consequence ◽  
Spatial Arrangement ◽  
Propagation Rate ◽  
Forest Types ◽  
Burnt Area ◽  
Spatially Distributed

Abstract Disturbances spreading through the landscape, like wildfires, are essential processes in modeling landscape structure and dynamics. Like other disturbances, fire may spread from a local epicenter with a propagation rate enhanced or retarded by the spatial arrangement of fuel across the landscape. Therefore, fire ignition and spread are a direct consequence of the presence and arrangement of fire-prone habitats. Generalizing the concept of “habitat selection” to every spatially distributed ecological process, the resource selection functions used in zoology to summarize habitat use by wildlife can be also used to characterize the wildfire’s pattern across the landscape. The aim of this paper is thus to quantify the relationship between forest cover and burnt area in Canton Ticino (Switzerland) during 1980–2007 using a bootstrap test of significance: that is, to identify forest types that burn more (or less) than expected from a random null model based on the regional availability of the resource (forest type). The results show that fires behave selectively for most forest types; whereas chestnut stands and broad-leaved forests display overproportional burnt areas, coniferous forests typically burn less than expected by a random null model.

Fire Regimes on Andesitic Mountain Terrain in Northeastern Yellowstone-National-Park, Wyoming

1994 ◽  
Vol 4 (2) ◽  
pp. 65 ◽  
Author(s):  
SW Barrett
Keyword(s):  
Yellowstone National Park ◽  
National Park ◽  
Fire History ◽  
Forest Type ◽  
Lodgepole Pine ◽  
Fire Suppression ◽  
Short Interval ◽  
Fire Regimes ◽  
High Elevation ◽  
Forest Community

A fire history investigation was conducted for three forest community types in the Absaroka Mountains of Yellowstone National Park, Wyoming. Master fire chronologies were based on fire-initiated age classes and tree fire scars. The area's major forest type, lodgepole pine (Pinus contorta Dougl. var. latifolia) ecosystems, revealed a predominant pattern of stand replacing fires with a 200 year mean interval-nearly half the length estimated in previous studies of lodgepole pine on less productive subalpine plateaus in YNP. High elevation whitebark pine (P. albicaulis Engelm.) forests had primarily stand replacing fires with >350 year mean intervals, but some stands near timberline also occasionally experienced mixed severity- or non-lethal underburns. Before nearly a century of effective fire suppression in Yellowstone's northern range, lower elevation Douglas-fir (Pseudotsuga menziesii [Mirb.] Franco.) communities adjacent to Artemesia tridentata (Nutt.) grasslands experienced primarily non-lethal underburns at 30 year mean intervals. While short interval fire regimes have been altered by longterm fire suppression, fire exclusion apparently had only limited influence on the area's infrequently burned ecosystems prior to widespread stand replacement burning in 1988.

scholarly journals Forest Type and Tree Species Classification of Nemoral Forests With Sentinel-1 and 2 Time Series Data

2021 ◽  
Author(s):  
Kristian Skau Bjerreskov ◽  
Thomas Nord-Larsen ◽  
Rasmus Fensholt
Keyword(s):  
Tree Species ◽  
Forest Cover ◽  
Forest Type ◽  
Error Rates ◽  
Sensor Data ◽  
Series Data ◽  
Forest Types ◽  
Multi Temporal ◽  
Species Groups

Mapping forest extent and forest cover classification are important for the assessment of forest resources in socio-economic as well as ecological terms. Novel developments in the availability of remotely sensed data, computational resources, and advances in areas of statistical learning have enabled fusion of multi-sensor data, often yielding superior classification results. Most former studies of nemoral forests fusing multi-sensor and multi-temporal data have been limited in spatial extent and typically to a simple classification of landscapes into major land cover classes. We hypothesize that multi-temporal, multi-censor data will have a specific strength in further classification of nemoral forest landscapes owing to the distinct seasonal patterns of the phenology of broadleaves. This study aimed to classify the Danish landscape into forest/non-forest and further into forest types (broadleaved/coniferous) and species groups, using a cloud-based approach based on multi-temporal Sentinel 1 and 2 data and machine learning (random forest) trained with National Forest Inventory (NFI) data. Mapping of non-forest and forest resulted in producer accuracies of 99% and 90 %, respectively. The mapping of forest types (broadleaf and conifer) within the forested area resulted in producer accuracies of 95% for conifer and 96% for broadleaf forest. Tree species groups were classified with producer accuracies ranging 34-74%. Species groups with coniferous species were the least confused whereas the broadleaf groups, especially Oak, had higher error rates. The results are applied in Danish National accounting of greenhouse gas emissions from forests, resource assessment and assessment of forest biodiversity potentials.

scholarly journals Evaluating Model Predictions of Fire Induced Tree Mortality Using Wildfire-Affected Forest Inventory Measurements

Forests ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 958 ◽  
Author(s):  
Jason S. Barker ◽  
Jeremy S. Fried ◽  
Andrew N. Gray
Keyword(s):  
Wind Speed ◽  
Forest Inventory ◽  
Tree Mortality ◽  
Forest Type ◽  
Flame Length ◽  
Weather Data ◽  
Fuel Moisture ◽  
Forest Types ◽  
Mean Error ◽  
Wide Range

Forest land managers rely on predictions of tree mortality generated from fire behavior models to identify stands for post-fire salvage and to design fuel reduction treatments that reduce mortality. A key challenge in improving the accuracy of these predictions is selecting appropriate wind and fuel moisture inputs. Our objective was to evaluate postfire mortality predictions using the Forest Vegetation Simulator Fire and Fuels Extension (FVS-FFE) to determine if using representative fire-weather data would improve prediction accuracy over two default weather scenarios. We used pre- and post-fire measurements from 342 stands on forest inventory plots, representing a wide range of vegetation types affected by wildfire in California, Oregon, and Washington. Our representative weather scenarios were created by using data from local weather stations for the time each stand was believed to have burned. The accuracy of predicted mortality (percent basal area) with different weather scenarios was evaluated for all stands, by forest type group, and by major tree species using mean error, mean absolute error (MAE), and root mean square error (RMSE). One of the representative weather scenarios, Mean Wind, had the lowest mean error (4%) in predicted mortality, but performed poorly in some forest types, which contributed to a relatively high RMSE of 48% across all stands. Driven in large part by over-prediction of modelled flame length on steeper slopes, the greatest over-prediction mortality errors arose in the scenarios with higher winds and lower fuel moisture. Our results also indicated that fuel moisture was a stronger influence on post-fire mortality than wind speed. Our results suggest that using representative weather can improve accuracy of mortality predictions when attempting to model over a wide range of forest types. Focusing simulations exclusively on extreme conditions, especially with regard to wind speed, may lead to over-prediction of tree mortality from fire.

scholarly journals Effects of habitat disturbance and hunting on the density and the biomass of the endemic Hose’s leaf monkey Presbytis hosei (Thomas, 1889) (Mammalia: Primates: Cercopithecidae) in east Borneo

2004 ◽  
Vol 73 (4) ◽  
pp. 283-291 ◽  
Author(s):  
Vincent Nijman
Keyword(s):  
National Park ◽  
Forest Cover ◽  
Secondary Forest ◽  
Tree Height ◽  
Habitat Disturbance ◽  
Forest Types ◽  
Crop Raiding ◽  
Single Male ◽  
Leaf Monkey ◽  
Leaf Monkeys

Hose’s leaf monkey Presbytis hosei is endemic to Borneo and occurs only in tall forest. In recent decades Borneo has lost a large part of its forest cover, mostly in low-lying coastal regions. Large intact tracts of forest remain in the interior, but these are by and large inhabited by tribes that subsist in part by hunting. The combined effects of habitat disturbance and hunting on the densities and biomass of Hose’s leaf monkey were studied in Kayan Mentarang National Park in Borneo’s far interior. Over four months, data on densities and hunting were collected by transect walks in four forest types. Hose’s leaf monkeys were hunted to deter crop-raiding, for their meat, and to obtain bezoar stones (visceral secretions used in traditional medicine). Hose’s leaf monkeys occurred in single male groups of 7-8 individuals in densities from 0.8 to 2.3 groups km-2. Densities of Hose’s leaf monkeys were positively correlated with certain vegetation characteristics, e.g. tree height and height of first bough, and negatively correlated with distance to the nearest village. Biomass of Hose’s leaf monkeys declined considerably as a result of habitat disturbance and hunting from 92 kg km-2 in primary hill forest inside the reserve to 38 kg km-2 in old secondary forest and 31 kg km-2 in young secondary forest near villages. A review of the few studies conducted on the effects of habitat disturbance and hunting on Hose’s leaf monkeys reveal inconsistent trends in biomass and density responses.

scholarly journals Climate changes and wildfire alter vegetation of Yellowstone National Park, but forest cover persists

Ecosphere ◽  
2017 ◽  
Vol 8 (1) ◽  
pp. e01636 ◽  
Author(s):  
Jason A. Clark ◽  
Rachel A. Loehman ◽  
Robert E. Keane
Keyword(s):  
Yellowstone National Park ◽  
National Park ◽  
Climate Changes ◽  
Forest Cover

scholarly journals Empirical Models for Spatio-Temporal Live Fuel Moisture Content Estimation in Mixed Mediterranean Vegetation Areas Using Sentinel-2 Indices and Meteorological Data

2021 ◽  
Vol 13 (18) ◽  
pp. 3726
Author(s):  
José M. Costa-Saura ◽  
Ángel Balaguer-Beser ◽  
Luis A. Ruiz ◽  
Josep E. Pardo-Pascual ◽  
José L. Soriano-Sancho
Keyword(s):  
Moisture Content ◽  
Forest Cover ◽  
Meteorological Variables ◽  
Fire Season ◽  
Fuel Moisture ◽  
Spectral Indices ◽  
Live Fuel Moisture ◽  
Spatio Temporal ◽  
Fuel Moisture Content ◽  
Sentinel 2

Live fuel moisture content (LFMC) is an input factor in fire behavior simulation models highly contributing to fire ignition and propagation. Developing models capable of accurately estimating spatio-temporal changes of LFMC in different forest species is needed for wildfire risk assessment. In this paper, an empirical model based on multivariate linear regression was constructed for the forest cover classified as shrublands in the central part of the Valencian region in the Eastern Mediterranean of Spain in the fire season. A sample of 15 non-monospecific shrubland sites was used to obtain a spatial representation of this type of forest cover in that area. A prediction model was created by combining spectral indices and meteorological variables. This study demonstrates that the Normalized Difference Moisture Index (NDMI) extracted from Sentinel-2 images and meteorological variables (mean surface temperature and mean wind speed) are a promising combination to derive cost-effective LFMC estimation models. The relationships between LFMC and spectral indices for all sites improved after using an additive site-specific index based on satellite information, reaching a R2adj = 0.70, RMSE = 8.13%, and MAE = 6.33% when predicting the average of LFMC weighted by the canopy cover fraction of each species of all shrub species present in each sampling plot.

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