scholarly journals The efficacy of fire and fuels reduction treatments in a Sierra Nevada pine plantation

2009 ◽  
Vol 18 (7) ◽  
pp. 791 ◽  
Author(s):  
Leda N. Kobziar ◽  
Joe R. McBride ◽  
Scott L. Stephens
Keyword(s):  
Sierra Nevada ◽  
Prescribed Fire ◽  
Large Scale ◽  
Structural Characteristics ◽  
Fire Behavior ◽  
Pine Plantation ◽  
Understorey Vegetation ◽  
Fuels Reduction ◽  
Reduction Techniques ◽  
Reducing Potential

Plantations are the most common means of reforestation following stand-replacing wildfires. As wildfires continue to increase in size and severity as a result of fire suppression or climate change, establishment of plantations will likely also increase. Plantations’ structural characteristics, including dense, uniform spacing and abundant ladder fuels, present significant wildfire hazards. Large-scale fuels reduction techniques may be necessary to reduce potential fire behavior in plantations and to protect surrounding forests. In the present study, four different manipulations aimed at reducing potential fire behavior in a Sierra Nevada pine plantation are compared. The treatments include: mechanical shredding, or mastication, of understorey vegetation and small trees; mastication followed by prescribed fire; fire alone; and controls. Fire behavior modeling shows that mastication is detrimental whereas prescribed fire is effective in reducing potential fire behavior at moderate to extreme weather conditions. Predicted fire behavior was compared with actual values from the prescribed burns in an effort to explore the limitations of fire modeling. Fire behavior predictions were similar to field observations in the more structurally homogeneous stands, but differed greatly where mastication created forest openings and patchy fuels distributions. In contrast to natural stands, the homogeneity of pine plantations make the results of the present work applicable to other regions such as the south-eastern US, where similar fuels reduction techniques are used to increase fire-resistance and stand resilience.

Mastication and prescribed fire impacts on fuels in a 25-year old ponderosa pine plantation, southern Sierra Nevada

2009 ◽  
Vol 258 (11) ◽  
pp. 2365-2372 ◽  
Author(s):  
Alicia L. Reiner ◽  
Nicole M. Vaillant ◽  
JoAnn Fites-Kaufman ◽  
Scott N. Dailey
Keyword(s):  
Sierra Nevada ◽  
Prescribed Fire ◽  
Ponderosa Pine ◽  
Pine Plantation

scholarly journals Erosion rates as a potential bottom‐up control of forest structural characteristics in the Sierra Nevada Mountains

Ecology ◽  
2015 ◽  
Vol 96 (1) ◽  
pp. 31-38 ◽  
Author(s):  
David T. Milodowski ◽  
Simon M. Mudd ◽  
Edward T. A. Mitchard
Keyword(s):  
Sierra Nevada ◽  
Structural Characteristics ◽  
Bottom Up ◽  
Erosion Rates ◽  
Sierra Nevada Mountains

scholarly journals Using the Landsat Burned Area Products to Derive Fire History Relevant for Fire Management and Conservation in the State of Florida, Southeastern USA

Fire ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 26
Author(s):  
Casey Teske ◽  
Melanie K. Vanderhoof ◽  
Todd J. Hawbaker ◽  
Joe Noble ◽  
John Kevin Hiers
Keyword(s):  
Prescribed Fire ◽  
Spatial Data ◽  
Fire History ◽  
Fire Management ◽  
Fire Behavior ◽  
Fire Risk ◽  
Behavior Modeling ◽  
Burned Area ◽  
Burned Areas ◽  
Burn Probability

Development of comprehensive spatially explicit fire occurrence data remains one of the most critical needs for fire managers globally, and especially for conservation across the southeastern United States. Not only are many endangered species and ecosystems in that region reliant on frequent fire, but fire risk analysis, prescribed fire planning, and fire behavior modeling are sensitive to fire history due to the long growing season and high vegetation productivity. Spatial data that map burned areas over time provide critical information for evaluating management successes. However, existing fire data have undocumented shortcomings that limit their use when detailing the effectiveness of fire management at state and regional scales. Here, we assessed information in existing fire datasets for Florida and the Landsat Burned Area products based on input from the fire management community. We considered the potential of different datasets to track the spatial extents of fires and derive fire history metrics (e.g., time since last burn, fire frequency, and seasonality). We found that burned areas generated by applying a 90% threshold to the Landsat burn probability product matched patterns recorded and observed by fire managers at three pilot areas. We then created fire history metrics for the entire state from the modified Landsat Burned Area product. Finally, to show their potential application for conservation management, we compared fire history metrics across ownerships for natural pinelands, where prescribed fire is frequently applied. Implications of this effort include increased awareness around conservation and fire management planning efforts and an extension of derivative products regionally or globally.

scholarly journals Fabrication of Ultrathin MoS2 Nanosheets and Application on Adsorption of Organic Pollutants and Heavy Metals

Processes ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 504 ◽  
Author(s):  
Siyi Huang ◽  
Ziyun You ◽  
Yanting Jiang ◽  
Fuxiang Zhang ◽  
Kaiyang Liu ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Electrostatic Interactions ◽  
Large Scale ◽  
Layer Structure ◽  
Structural Characteristics ◽  
Hexagonal Phase ◽  
Two Dimensional ◽  
Mos2 Nanosheets ◽  
Hybrid Strategy ◽  
Ultrathin Mos2 Nanosheets

Owing to their peculiar structural characteristics and potential applications in various fields, the ultrathin MoS2 nanosheets, a typical two-dimensional material, have attracted numerous attentions. In this paper, a hybrid strategy with combination of quenching process and liquid-based exfoliation was employed to fabricate the ultrathin MoS2 nanosheets (MoS2 NS). The obtained MoS2 NS still maintained hexagonal phase (2H-MoS2) and exhibited evident thin layer-structure (1–2 layers) with inconspicuous wrinkle. Besides, the MoS2 NS dispersion showed excellent stability (over 60 days) and high concentration (0.65 ± 0.04 mg mL−1). The MoS2 NS dispersion also displayed evident optical properties, with two characteristic peaks at 615 and 670 nm, and could be quantitatively analyzed with the absorbance at 615 nm in the range of 0.01–0.5 mg mL−1. The adsorption experiments showed that the as-prepared MoS2 NS also exhibited remarkable adsorption performance on the dyes (344.8 and 123.5 mg g−1 of qm for methylene blue and methyl orange, respectively) and heavy metals (185.2, 169.5, and 70.4 mg g−1 of qm for Cd2+, Cu2+, and Ag+). During the adsorption, the main adsorption mechanisms involved the synergism of physical hole-filling effects and electrostatic interactions. This work provided an effective way for the large-scale fabrication of the two-dimensional nanosheets of transition metal dichalcogenides (TMDs) by liquid exfoliation.

scholarly journals Parallel Framework for Dimensionality Reduction of Large-Scale Datasets

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Sai Kiranmayee Samudrala ◽  
Jaroslaw Zola ◽  
Srinivas Aluru ◽  
Baskar Ganapathysubramanian
Keyword(s):  
Dimensionality Reduction ◽  
Organic Solar Cells ◽  
Large Scale ◽  
Parallel Implementation ◽  
High Dimensional Data ◽  
Real Life ◽  
Processing Parameters ◽  
High Dimensional ◽  
Morphology Evolution ◽  
Reduction Techniques

Dimensionality reduction refers to a set of mathematical techniques used to reduce complexity of the original high-dimensional data, while preserving its selected properties. Improvements in simulation strategies and experimental data collection methods are resulting in a deluge of heterogeneous and high-dimensional data, which often makes dimensionality reduction the only viable way to gain qualitative and quantitative understanding of the data. However, existing dimensionality reduction software often does not scale to datasets arising in real-life applications, which may consist of thousands of points with millions of dimensions. In this paper, we propose a parallel framework for dimensionality reduction of large-scale data. We identify key components underlying the spectral dimensionality reduction techniques, and propose their efficient parallel implementation. We show that the resulting framework can be used to process datasets consisting of millions of points when executed on a 16,000-core cluster, which is beyond the reach of currently available methods. To further demonstrate applicability of our framework we perform dimensionality reduction of 75,000 images representing morphology evolution during manufacturing of organic solar cells in order to identify how processing parameters affect morphology evolution.

Application of projection-based model reduction to finite-element plate models for two-dimensional traveling waves

2016 ◽  
Vol 28 (14) ◽  
pp. 1886-1904 ◽  
Author(s):  
Vijaya VN Sriram Malladi ◽  
Mohammad I Albakri ◽  
Serkan Gugercin ◽  
Pablo A Tarazaga
Keyword(s):  
Finite Element ◽  
Model Reduction ◽  
Traveling Waves ◽  
Large Scale ◽  
Fe Model ◽  
Plate Model ◽  
Reduction Techniques ◽  
State Frequency ◽  
Scale Down ◽  
The Stability

A finite element (FE) model simulates an unconstrained aluminum thin plate to which four macro-fiber composites are bonded. This plate model is experimentally validated for single and multiple inputs. While a single input excitation results in the frequency response functions and operational deflection shapes, two input excitations under prescribed conditions result in tailored traveling waves. The emphasis of this article is the application of projection-based model reduction techniques to scale-down the large-scale FE plate model. Four model reduction techniques are applied and their performances are studied. This article also discusses the stability issues associated with the rigid-body modes. Furthermore, the reduced-order models are utilized to simulate the steady-state frequency and time response of the plate. The results are in agreement with the experimental and the full-scale FE model results.

Experimental study of large-scale fire behavior under low pressure at high altitude

2013 ◽  
Vol 31 (6) ◽  
pp. 481-494 ◽  
Author(s):  
Wei Yao ◽  
Xiaokang Hu ◽  
Jianzhong Rong ◽  
Jian Wang ◽  
Hui Zhang
Keyword(s):  
Experimental Study ◽  
High Altitude ◽  
Large Scale ◽  
Fire Behavior ◽  
Low Pressure

Structural characteristics of a developing turbulent planar jet

1986 ◽  
Vol 163 ◽  
pp. 227-256 ◽  
Author(s):  
F. O. Thomas ◽  
V. W. Goldschmidt
Keyword(s):  
Large Scale ◽  
Structural Characteristics ◽  
Energy Spectra ◽  
Two Dimensional ◽  
Structural Pattern ◽  
Potential Core ◽  
Planar Jet ◽  
Fluctuation Phase ◽  
Oriented Parallel ◽  
Phase Angles

An experimental study of the developing structural characteristics of a two-dimensional jet in an extremely quiet environment was performed. The jet, at an exit Reynolds number of 6000 and with fluctuation intensity under 0.2% at the mouth, was operated within a large anechoic room. Measurements of energy spectra, fluctuation phase angles and two-dimensionality led to the inference of structural patterns in the flow. These patterns are initially characterized by relatively strong symmetric modes exhibiting limited two-dimensionality and oriented parallel to the mouth of the jet. Subsequent downstream evolution led to the formation of an antisymmetric pattern beyond the jet potential core and the associated development of extended structures possessing a definite large lateral inclination. The results of this work suggest a developing large-scale structural pattern more complicated than previously supposed.

Sign in / Sign up

Export Citation Format

Share Document