Linking 3D spatial models of fuels and fire: Effects of spatial heterogeneity on fire behavior

Treesearch

Russell A. Parsons; William E. Mell; Peter McCauley

2011-01-01

Crownfire endangers fire fighters and can have severe ecological consequences. Prediction of fire behavior in tree crowns is essential to informed decisions in fire management. Current methods used in fire management do not address variability in crown fuels. New mechanistic physics-based fire models address convective heat transfer with computational fluid dynamics (...

Predicting wildfire behavior in black spruce forests in Alaska.

Treesearch

Rodney A. Norum

1982-01-01

The current fire behavior system, when properly adjusted, accurately predicts forward rate of spread and flame length of wildfires in black spruce (Picea mariana (Mill.) B.S.P.) forests in Alaska. After fire behavior was observed and quantified, adjustment factors were calculated and assigned to the selected fuel models to correct the outputs to...

BEHAVE: fire behavior prediction and fuel modeling system--FUEL subsystem

Treesearch

Robert E. Burgan; Richard C. Rothermel

1984-01-01

This manual documents the fuel modeling procedures of BEHAVE--a state-of-the-art wildland fire behavior prediction system. Described are procedures for collecting fuel data, using the data with the program, and testing and adjusting the fuel model.

WRF-Fire: coupled weather-wildland fire modeling with the weather research and forecasting model

Treesearch

Janice L. Coen; Marques Cameron; John Michalakes; Edward G. Patton; Philip J. Riggan; Kara M. Yedinak

2012-01-01

A wildland fire behavior module (WRF-Fire) was integrated into the Weather Research and Forecasting (WRF) public domain numerical weather prediction model. The fire module is a surface fire behavior model that is two-way coupled with the atmospheric model. Near-surface winds from the atmospheric model are interpolated to a finer fire grid and used, with fuel properties...

Validation of behave fire behavior predictions in oak savannas

USGS Publications Warehouse

Grabner, Keith W.; Dwyer, John; Cutter, Bruce E.

1997-01-01

Prescribed fire is a valuable tool in the restoration and management of oak savannas. BEHAVE, a fire behavior prediction system developed by the United States Forest Service, can be a useful tool when managing oak savannas with prescribed fire. BEHAVE predictions of fire rate-of-spread and flame length were validated using four standardized fuel models: Fuel Model 1 (short grass), Fuel Model 2 (timber and grass), Fuel Model 3 (tall grass), and Fuel Model 9 (hardwood litter). Also, a customized oak savanna fuel model (COSFM) was created and validated. Results indicate that standardized fuel model 2 and the COSFM reliably estimate mean rate-of-spread (MROS). The COSFM did not appreciably reduce MROS variation when compared to fuel model 2. Fuel models 1, 3, and 9 did not reliably predict MROS. Neither the standardized fuel models nor the COSFM adequately predicted flame lengths. We concluded that standardized fuel model 2 should be used with BEHAVE when predicting fire rates-of-spread in established oak savannas.

Simulation of quaking aspen potential fire behavior in Northern Utah, USA

Treesearch

R. Justin DeRose; A. Joshua Leffler

2014-01-01

Current understanding of aspen fire ecology in western North America includes the paradoxical characterization that aspen-dominated stands, although often regenerated following fire, are “fire-proof”. We tested this idea by predicting potential fire behavior across a gradient of aspen dominance in northern Utah using the Forest Vegetation Simulator and the Fire and...

Wildland Fire Forecasting: Predicting Wildfire Behavior, Growth, and Feedbacks on Weather

NASA Astrophysics Data System (ADS)

Coen, J. L.

2005-12-01

Recent developments in wildland fire research models have represented more complex of fire behavior. The cost has been to increase the computational requirements. When operational constraints are included, such as the need to produce such forecasts faster than real time, the challenge becomes a balance of how much complexity (with corresponding gains in realism) and accuracy can be achieved in producing the quantities of interest while meeting the specified operational constraints. Current field tools are calculator or Palm-Pilot based algorithms such as BEHAVE and BEHAVE Plus that produce timely estimates of instantaneous fire spread rates, flame length, and fire intensity at a point using readily estimated inputs of fuel model, terrain slope, and atmospheric wind speed at a point. At the cost of requiring a PC and slower calculation, FARSITE represents two-dimensional fire spread and adds capabilities including a parameterized representation of crown fire ignition, This work describes how a coupled atmosphere-fire model previously used as a research tool has been adapted for production of real-time forecasts of fire growth and its interactions with weather over a domain focusing on Colorado during summer 2004. The coupled atmosphere-wildland fire-environment (CAWFE) model composed of a 3-dimensional atmospheric prediction model that has been two-way coupled with an empirical fire spread model. The models are connected in that atmospheric conditions (and fuel conditions influenced by the atmosphere) affect the rate and direction of fire propagation, which releases sensible and latent heat (i.e. thermal and water vapor fluxes) to the atmosphere that in turn alter the winds and atmospheric structure around the fire. Thus, it can represent time and spatially-varying weather and the fire feedbacks on the atmospheric which are at the heart of sudden changes in fire behavior and examples of extreme fire behavior such as blow ups, which are now not predictable with current tools. Thus, although this work shows that is it possible to perform more detailed simulations in real time, fire behavior forecasting remains a challenging problem. This is due to challenges in weather prediction, particularly at fine spatial and temporal scales considered "nowcasting" (0-6 hrs), uncertainties in fire behavior even with known meteorological conditions, limitations in quantitative datasets on fuel properties such as fuel loading, and verification. This work describes efforts to advance these capabilities with input from remote sensing data on fuel characteristics and dynamic steering and object-based verification with remotely sensed fire perimeters.

Toward improving our application and understanding of crown fire behavior

Treesearch

Martin E. Alexander; Miguel G. Cruz; Nicole M. Vaillant

2014-01-01

The suggestion has been made that most wildland fire operations personnel base their expectations of how a fire will behave largely on experience and, to a lesser extent, on guides to predicting fire behavior (Burrows 1984). Experienced judgment is certainly needed in any assessment of wildland fire potential but it does have its limitations. The same can be said for...

Assessment of the FARSITE model for predicting fire behavior in the Southern Appalachian Mountains

Treesearch

Ross J. Phillips; Thomas A. Waldrop; Dean M. Simon

2006-01-01

Fuel reduction treatments are necessary in fire-adapted ecosystems where fire has been excluded for decades and the potential for severe wildfire is high. Using the Fire Area Simulator, FARSITE, we examined the spatial and temporal effects of these treatments on fire behavior in the Southern Appalachian Mountains. With measurements from temperature sensors during...

The effectiveness and limitations of fuel modeling using the fire and fuels extension to the Forest Vegetation Simulator

Treesearch

Erin K. Noonan-Wright; Nicole M. Vaillant; Alicia L. Reiner

2014-01-01

Fuel treatment effectiveness is often evaluated with fire behavior modeling systems that use fuel models to generate fire behavior outputs. How surface fuels are assigned, either using one of the 53 stylized fuel models or developing custom fuel models, can affect predicted fire behavior. We collected surface and canopy fuels data before and 1, 2, 5, and 8 years after...

Fuel model selection for BEHAVE in midwestern oak savannas

USGS Publications Warehouse

Grabner, K.W.; Dwyer, J.P.; Cutter, B.E.

2001-01-01

BEHAVE, a fire behavior prediction system, can be a useful tool for managing areas with prescribed fire. However, the proper choice of fuel models can be critical in developing management scenarios. BEHAVE predictions were evaluated using four standardized fuel models that partially described oak savanna fuel conditions: Fuel Model 1 (Short Grass), 2 (Timber and Grass), 3 (Tall Grass), and 9 (Hardwood Litter). Although all four models yielded regressions with R2 in excess of 0.8, Fuel Model 2 produced the most reliable fire behavior predictions.

Research efforts on fuels, fuel models, and fire behavior in eastern hardwood forests

Treesearch

Thomas A. Waldrop; Lucy Brudnak; Ross J. Phillips; Patrick H. Brose

2006-01-01

Although fire was historically important to most eastern hardwood systems, its reintroduction by prescribed burning programs has been slow. As a result, less information is available on these systems to fire managers. Recent research and nationwide programs are beginning to produce usable products to predict fuel accumulation and fire behavior. We introduce some of...

Moisture dynamics in masticated fuelbeds: A preliminary analysis

Treesearch

Jesse Kreye; J. Morgan Varner

2007-01-01

Mastication has become a popular fuels treatment in the Western United States, but predicting subsequent fire behavior and effects has proven difficult. Fire behavior and effects in masticated fuelbeds have been more intense and erratic in comparison with model predictions. While various particle or fuelbed characteristics in these fuels may contribute to the...

[Fire behavior of ground surface fuels in Pinus koraiensis and Quercus mongolica mixed forest under no wind and zero slope condition: a prediction with extended Rothermel model].

PubMed

Zhang, Ji-Li; Liu, Bo-Fei; Chu, Teng-Fei; Di, Xue-Ying; Jin, Sen

2012-06-01

A laboratory burning experiment was conducted to measure the fire spread speed, residual time, reaction intensity, fireline intensity, and flame length of the ground surface fuels collected from a Korean pine (Pinus koraiensis) and Mongolian oak (Quercus mongolica) mixed stand in Maoer Mountains of Northeast China under the conditions of no wind, zero slope, and different moisture content, load, and mixture ratio of the fuels. The results measured were compared with those predicted by the extended Rothermel model to test the performance of the model, especially for the effects of two different weighting methods on the fire behavior modeling of the mixed fuels. With the prediction of the model, the mean absolute errors of the fire spread speed and reaction intensity of the fuels were 0.04 m X min(-1) and 77 kW X m(-2), their mean relative errors were 16% and 22%, while the mean absolute errors of residual time, fireline intensity and flame length were 15.5 s, 17.3 kW X m(-1), and 9.7 cm, and their mean relative errors were 55.5%, 48.7%, and 24%, respectively, indicating that the predicted values of residual time, fireline intensity, and flame length were lower than the observed ones. These errors could be regarded as the lower limits for the application of the extended Rothermel model in predicting the fire behavior of similar fuel types, and provide valuable information for using the model to predict the fire behavior under the similar field conditions. As a whole, the two different weighting methods did not show significant difference in predicting the fire behavior of the mixed fuels by extended Rothermel model. When the proportion of Korean pine fuels was lower, the predicted values of spread speed and reaction intensity obtained by surface area weighting method and those of fireline intensity and flame length obtained by load weighting method were higher; when the proportion of Korean pine needles was higher, the contrary results were obtained.

On The Usage Of Fire Smoke Emissions In An Air Quality Forecasting System To Reduce Particular Matter Forecasting Error

NASA Astrophysics Data System (ADS)

Huang, H. C.; Pan, L.; McQueen, J.; Lee, P.; ONeill, S. M.; Ruminski, M.; Shafran, P.; DiMego, G.; Huang, J.; Stajner, I.; Upadhayay, S.; Larkin, N. K.

2016-12-01

Wildfires contribute to air quality problems not only towards primary emissions of particular matters (PM) but also emitted ozone precursor gases that can lead to elevated ozone concentration. Wildfires are unpredictable and can be ignited by natural causes such as lightning or accidently by human negligent behavior such as live cigarette. Although wildfire impacts on the air quality can be studied by collecting fire information after events, it is extremely difficult to predict future occurrence and behavior of wildfires for real-time air quality forecasts. Because of the time constraints of operational air quality forecasting, assumption of future day's fire behavior often have to be made based on observed fire information in the past. The United States (U.S.) NOAA/NWS built the National Air Quality Forecast Capability (NAQFC) based on the U.S. EPA CMAQ to provide air quality forecast guidance (prediction) publicly. State and local forecasters use the forecast guidance to issue air quality alerts in their area. The NAQFC fine particulates (PM2.5) prediction includes emissions from anthropogenic and biogenic sources, as well as natural sources such as dust storms and fires. The fire emission input to the NAQFC is derived from the NOAA NESDIS HMS fire and smoke detection product and the emission module of the US Forest Service BlueSky Smoke Modeling Framework. This study focuses on the error estimation of NAQFC PM2.5 predictions resulting from fire emissions. The comparisons between the NAQFC modeled PM2.5 and the EPA AirNow surface observation show that present operational NAQFC fire emissions assumption can lead to a huge error in PM2.5 prediction as fire emissions are sometimes placed at wrong location and time. This PM2.5 prediction error can be propagated from the fire source in the Northwest U.S. to downstream areas as far as the Southeast U.S. From this study, a new procedure has been identified to minimize the aforementioned error. An additional 24 hours reanalysis-run of NAQFC using same-day observed fire emission are being tested. Preliminary results have shown that this procedure greatly improves the PM2.5 predictions at both nearby and downstream areas from fire sources. The 24 hours reanalysis-run is critical and necessary especially during extreme fire events to provide better PM2.5 predictions.

Modeling fire behavior on tropical islands with high-resolution weather data

Treesearch

John W. Benoit; Francis M. Fujioka; David R. Weise

2009-01-01

In this study, we consider fire behavior simulation in tropical island scenarios such as Hawaii and Puerto Rico. The development of a system to provide real-time fire behavior prediction in Hawaii is discussed. This involves obtaining fuels and topography information at a fine scale, as well as supplying daily high-resolution weather forecast data for the area of...

Probability model for analyzing fire management alternatives: theory and structure

Treesearch

Frederick W. Bratten

1982-01-01

A theoretical probability model has been developed for analyzing program alternatives in fire management. It includes submodels or modules for predicting probabilities of fire behavior, fire occurrence, fire suppression, effects of fire on land resources, and financial effects of fire. Generalized "fire management situations" are used to represent actual fire...

Building Fire Behavior Analyst (FBAN) capability and capacity: Lessons learned From Victoria, Australia's Bushfire Behavior Predictive Services Strategy

Treesearch

K. E. Gibos; A. Slijepcevic; T. Wells; L. Fogarty

2015-01-01

Wildland fire managers must frequently make meaning from chaos in order to protect communities and infrastructure from the negative impacts of fire. Fire management personnel are increasingly turning to science to support their experience-based decision-making processes and to provide clear, confident leadership for communities frequently exposed to risk from wildfire...

Predicting behavior and size of crown fires in the northern Rocky Mountains

Treesearch

Richard C. Rothermel

1991-01-01

Describes methods for approximating behavior and size of a wind-driven crown fire in mountainous terrain. Covers estimation of average rate of spread, energy release from tree crowns and surface fuel, fireline intensity, flame length, and unit area power of the fire and ambient wind. Plume-dominated fires, which may produce unexpectedly fast spread rates even with low...

Mastication and prescribed fire influences on tree mortality and predicted fire behavior in ponderosa pine

Treesearch

Alicia L. Reiner; Nicole M. Vaillant; Scott N. Dailey

2012-01-01

The purpose of this study was to provide land managers with information on potential wildfire behavior and tree mortality associated with mastication and masticated/fire treatments in a plantation. Additionally, the effect of pulling fuels away from tree boles before applying fire treatment was studied in relation to tree mortality. Fuel characteristics and tree...

Simulating wildfire spread behavior between two NASA Active Fire data timeframes

NASA Astrophysics Data System (ADS)

Adhikari, B.; Hodza, P.; Xu, C.; Minckley, T. A.

2017-12-01

Although NASA's Active Fire dataset is considered valuable in mapping the spatial distribution and extent of wildfires across the world, the data is only available at approximately 12-hour time intervals, creating uncertainties and risks associated with fire spread and behavior between the two Visible Infrared Imaging Radiometer Satellite (VIIRS) data collection timeframes. Our study seeks to close the information gap for the United States by using the latest Active Fire data collected for instance around 0130 hours as an ignition source and critical inputs to a wildfire model by uniquely incorporating forecasted and real-time weather conditions for predicting fire perimeter at the next 12 hour reporting time (i.e. around 1330 hours). The model ingests highly dynamic variables such as fuel moisture, temperature, relative humidity, wind among others, and prompts a Monte Carlo simulation exercise that uses a varying range of possible values for evaluating all possible wildfire behaviors. The Monte Carlo simulation implemented in this model provides a measure of the relative wildfire risk levels at various locations based on the number of times those sites are intersected by simulated fire perimeters. Model calibration is achieved using data at next reporting time (i.e. after 12 hours) to enhance the predictive quality at further time steps. While initial results indicate that the calibrated model can predict the overall geometry and direction of wildland fire spread, the model seems to over-predict the sizes of most fire perimeters possibly due to unaccounted fire suppression activities. Nonetheless, the results of this study show great promise in aiding wildland fire tracking, fighting and risk management.

Effects of fire on chaparral soils in Arizona and California and postfire management implications

Treesearch

Leonard F. DeBano

1989-01-01

Wildfires and prescribed burns are common throughout Arizona and California chaparral. Predicting fire effects requires understanding fire behavior, estimating soil heating, and predicting changes in soil properties. Substantial quantities of some nutrients, particularly nitrogen and phosphorus, are lost directly during combustion. Highly available nutrients released...

Fire behavior in masticated fuels: a review

Treesearch

Jesse K. Kreye; Nolan W. Brewer; Penelope Morgan; J. Morgan Varner; Alistair M.S. Smith; Chad M. Hoffman; Roger D. Ottmar

2014-01-01

Mastication is an increasingly common fuels treatment that redistributes ‘‘ladder’’ fuels to the forest floor to reduce vertical fuel continuity, crown fire potential, and fireline intensity, but fuel models do not exist for predicting fire behavior in these fuel types. Recent fires burning in masticated fuels have behaved in unexpected and contradictory ways, likely...

Fuels and predicted fire behavior in the southern Appalachian Mountains and fire and fire surrogate treatments

Treesearch

Thomas Waldrop; Ross J. Phillips; Dean A. Simon

2010-01-01

This study tested the success of fuel reduction treatments for mitigating wildfire behavior in an area that has had little previous research on fire, the southern Appalachian Mountains. A secondary objective of treatments was to restore the community to an open woodland condition. Three blocks of four treatments were installed in a mature hardwood forest in western...

Capabilities of current wildfire models when simulating topographical flow

NASA Astrophysics Data System (ADS)

Kochanski, A.; Jenkins, M.; Krueger, S. K.; McDermott, R.; Mell, W.

2009-12-01

Accurate predictions of the growth, spread and suppression of wild fires rely heavily on the correct prediction of the local wind conditions and the interactions between the fire and the local ambient airflow. Resolving local flows, often strongly affected by topographical features like hills, canyons and ridges, is a prerequisite for accurate simulation and prediction of fire behaviors. In this study, we present the results of high-resolution numerical simulations of the flow over a smooth hill, performed using (1) the NIST WFDS (WUI or Wildland-Urban-Interface version of the FDS or Fire Dynamic Simulator), and (2) the LES version of the NCAR Weather Research and Forecasting (WRF-LES) model. The WFDS model is in the initial stages of development for application to wind flow and fire spread over complex terrain. The focus of the talk is to assess how well simple topographical flow is represented by WRF-LES and the current version of WFDS. If sufficient progress has been made prior to the meeting then the importance of the discrepancies between the predicted and measured winds, in terms of simulated fire behavior, will be examined.

Chapter 13 - Conventional fire behavior modeling systems are inadequate for predicting fire behavior in bark beetle-impacted forests (Project INT-EM-F-11-03)

Treesearch

Sharon M. Hood; Robert E. Keane; Helen Y. Smith; Joel Egan; Lisa Holsinger

2018-01-01

Understanding the impacts of mountain pine beetle (MPB; Dendroctonus ponderosae Hopkins) on fire behavior is important from both an ecological and land management viewpoint. However, numerous uncertainties exist in the linkages of MPB-caused treemortality to changes in canopy and surface fuels (e.g., fuel loading, arrangement, and availability) and the...

Fuel treatment longevity in a Sierra Nevada mixed conifer forest

Treesearch

Scott. L. Stephens; Brandon M. Collins; Gary. Roller

2012-01-01

Understanding the longevity of fuel treatments in terms of their ability to maintain fire behavior and effects within a desired range is an important question. The objective of this study was to determine how fuels, forest structure, and predicted fire behavior changed 7-years after initial treatments. Three different treatments: mechanical only, mechanical plus fire,...

Fire interest and antisociality as risk factors in the severity and persistence of juvenile firesetting.

PubMed

MacKay, Sherri; Henderson, Joanna; Del Bove, Giannetta; Marton, Peter; Warling, Diane; Root, Carol

2006-09-01

In the DSM-IV-TR, firesetting is included as a criterion for the diagnoses of conduct disorder and pyromania. The link between firesetting and antisocial behavior is well established in the empirical literature. Although theoretical models of firesetting often include fire interest as a putative risk factor, there is little research on the role of fire interest in firesetting or on the construct of pyromania. The present study evaluated a sample of children and adolescents referred to an outpatient specialty program for juvenile firesetters with firesetting as the primary presenting problem. By assessing fire interest and antisocial behavior concurrently, the contribution of fire interest to firesetting after controlling for the role of conduct problems was evaluated. Results revealed that fire interest and antisocial behavior were significantly and positively correlated. Moreover, variations in fire interest added to the prediction of firesetting severity at assessment and firesetting recidivism at 18-month follow-up above and beyond what was predicted by antisociality alone. These findings have implications for an empirically derived taxonomy of pathological firesetting.

A review of fire interactions and mass fires

Treesearch

Mark A. Finney; Sara S. McAllister

2011-01-01

The character of a wildland fire can change dramatically in the presence of another nearby fire. Understanding and predicting the changes in behavior due to fire-fire interactions cannot only be life-saving to those on the ground, but also be used to better control a prescribed fire to meet objectives. In discontinuous fuel types, such interactions may elicit fire...

Fuel type characterization and potential fire behavior estimation in Sardinia and Corsica islands

NASA Astrophysics Data System (ADS)

Bacciu, V.; Pellizzaro, G.; Santoni, P.; Arca, B.; Ventura, A.; Salis, M.; Barboni, T.; Leroy, V.; Cancellieri, D.; Leoni, E.; Ferrat, L.; Perez, Y.; Duce, P.; Spano, D.

2012-04-01

Wildland fires represent a serious threat to forests and wooded areas of the Mediterranean Basin. As recorded by the European Commission (2009), during the last decade Southern Countries have experienced an annual average of about 50,000 forest fires and about 470,000 burned hectares. The factor that can be directly manipulated in order to minimize fire intensity and reduce other fire impacts, such as three mortality, smoke emission, and soil erosion, is wildland fuel. Fuel characteristics, such as vegetation cover, type, humidity status, and biomass and necromass loading are critical variables in affecting wildland fire occurrence, contributing to the spread, intensity, and severity of fires. Therefore, the availability of accurate fuel data at different spatial and temporal scales is needed for fire management applications, including fire behavior and danger prediction, fire fighting, fire effects simulation, and ecosystem simulation modeling. In this context, the main aims of our work are to describe the vegetation parameters involved in combustion processes and develop fire behavior fuel maps. The overall work plan is based firstly on the identification and description of the different fuel types mainly affected by fire occurrence in Sardinia (Italy) and Corsica (France) Islands, and secondly on the clusterization of the selected fuel types in relation to their potential fire behavior. In the first part of the work, the available time series of fire event perimeters and the land use map data were analyzed with the purpose of identifying the main land use types affected by fires. Thus, field sampling sites were randomly identified on the selected vegetation types and several fuel variables were collected (live and dead fuel load partitioned following Deeming et al., (1977), depth of fuel layer, plant cover, surface area-to-volume ratio, heat content). In the second part of the work, the potential fire behavior for every experimental site was simulated using BEHAVE fire behavior prediction system (Andrews, 1989) and experimental fuel data. Fire behavior was simulated by setting different weather scenarios representing the most frequent summer meteorological conditions. The simulation outputs (fireline intensity, rate of spread, flame length) were then analyzed for clustering the different fuel types in relation to their potential fire behavior. The results of this analysis can be used to produce fire behavior fuel maps that are important tools in evaluating fire hazard and risk for land management planning, locating and rating fuel treatments, and aiding in environmental assessments and fire danger programs modeling. This work is supported by FUME Project FP7-ENV-2009-1, Grant Agreement Number 243888 and Proterina-C Project, EU Italia-Francia Marittimo 2007-2013 Programme.

Stem mortality in surface fires: Part II, experimental methods for characterizing the thermal response of tree stems to heating by fires

Treesearch

D. M. Jimenez; B. W. Butler; J. Reardon

2003-01-01

Current methods for predicting fire-induced plant mortality in shrubs and trees are largely empirical. These methods are not readily linked to duff burning, soil heating, and surface fire behavior models. In response to the need for a physics-based model of this process, a detailed model for predicting the temperature distribution through a tree stem as a function of...

Modeling the effects of vegetation heterogeneity on wildland fire behavior

NASA Astrophysics Data System (ADS)

Atchley, A. L.; Linn, R.; Sieg, C.; Middleton, R. S.

2017-12-01

Vegetation structure and densities are known to drive fire-spread rate and burn severity. Many fire-spread models incorporate an average, homogenous fuel density in the model domain to drive fire behavior. However, vegetation communities are rarely homogenous and instead present significant heterogeneous structure and fuel densities in the fires path. This results in observed patches of varied burn severities and mosaics of disturbed conditions that affect ecological recovery and hydrologic response. Consequently, to understand the interactions of fire and ecosystem functions, representations of spatially heterogeneous conditions need to be incorporated into fire models. Mechanistic models of fire disturbance offer insight into how fuel load characterization and distribution result in varied fire behavior. Here we use a physically-based 3D combustion model—FIRETEC—that solves conservation of mass, momentum, energy, and chemical species to compare fire behavior on homogenous representations to a heterogeneous vegetation distribution. Results demonstrate the impact vegetation heterogeneity has on the spread rate, intensity, and extent of simulated wildfires thus providing valuable insight in predicted wildland fire evolution and enhanced ability to estimate wildland fire inputs into regional and global climate models.

Linking complex forest fuel structure and fire behavior at fine scales

Treesearch

EL Loudermilk; Joseph O' Brien; RJ Mitchell; JK Hiers; WP Cropper; S Grunwald; J Grego; J Fernandez

2012-01-01

Improved fire management of savannas and open woodlands requires better understanding of the fundamental connection between fuel heterogeneity, variation in fire behaviour and the influence of fire variation on vegetation feedbacks. In this study, we introduce a novel approach to predicting fire behaviour at the submetre scale, including measurements of forest...

Value and challenges of conducting rapid response research on wildland fires

Treesearch

L. Lentile; P. Morgan; C. Hardy; A. Hudak; R. Means; R. Ottmar; P. Robichaud; E. Kennedy Sutherland; J. Szymoniak; F. Way; J. Fites-Kaufman; S. Lewis; E. Mathews; H. Shovik; K. Ryan

2007-01-01

Rapid Response Research is conducted during and immediately after wildland fires, in coordination with fire management teams, in order to collect information that can best be garnered in situ and in real-time. This information often includes fire behavior and fire effects data, which can be used to generate practical tools such as predictive fire models for managers....

Predicted fire behavior and societal benefits in three eastern Sierra Nevada vegetation types

Treesearch

C.A. Dicus; K. Delfino; D.R. Weise

2009-01-01

We investigated potential fire behavior and various societal benefits (air pollution removal, carbon sequestration, and carbon storage) provided by woodlands of pinyon pine (Pinus monophylla) and juniper (Juniperus californica), shrublands of Great Basin sagebrush (Artemisia tridentata) and rabbitbrush (Ericameria nauseosa...

Predicting the effect of climate change on wildfire behavior and initial attack success

Treesearch

Jeremy S. Fried; J. Keith Gilless; William J. Riley; Tadashi J. Moody; Clara Simon de Blas; Katharine Hayhoe; Max Mortiz; Scott Stephens; Margaret Torn

2008-01-01

This study focused on how climate change-induced effects on weather will translate into changes in wildland fire severity and outcomes in California, particularly on the effectiveness of initial attack at limiting the number of fires that escape initial attack. The results indicate that subtle shifts in fire behavior of the sort that might be induced by the climate...

An Examination of Extreme Fire Behavior and its Impact on Smoke Injection Altitude using Remote Sensing and Meteorological Data

NASA Astrophysics Data System (ADS)

Peterson, D. A.; Hyer, E. J.; Campbell, J. R.; Fromm, M. D.; Hair, J. W.; Butler, C. F.; Fenn, M. A.

2014-12-01

A variety of regional smoke forecasting applications are currently available to identify air quality, visibility, and societal impacts during large fire events. However, these systems typically assume persistent fire activity, and therefore can have large errors before, during, and after short-term periods of extreme fire behavior. This study employs a wide variety of ground, airborne, and satellite observations, including data collected during a major NASA airborne and field campaign, to examine the conditions required for both extreme spread and pyrocumulonimbus (pyroCb) development. Results highlight the importance of upper-level and nocturnal meteorology, as well as the limitations of traditional fire weather indices. Increasing values of fire radiative power (FRP) at the pixel and sub-pixel level are shown to systematically correspond to higher altitude smoke plumes, and an increased probability of injection above the boundary layer. Lidar data collected during the 2013 Rim Fire, one of the most severe fire events in California's history, show that high FRP observed during extreme spread can facilitate long-distance smoke transport, but fails to loft smoke to the altitude of a large pyroCb. The most extreme fire spread was also observed on days without pyroCb activity or significant regional convection. By incorporating additional fire events across North America, conflicting hypotheses surrounding the primary source of moisture during pyroCb development are examined. The majority of large pyroCbs, and therefore the highest direct injection altitude of smoke particles, is shown to occur with conditions very similar to those that produce dry thunderstorms. The current suite of automated forecasting applications predict only general trends in fire behavior, and specifically do not predict (1) extreme fire spread events and (2) injection of smoke to high altitudes. While (1) and (2) are related, results show that they are not predicted by the same set of conditions and variables. The combination of meteorology from numerical forecast models and satellite observations exhibits great potential for improving regional forecasts of fire behavior and smoke production in automated systems, especially in remote areas where detailed observations are unavailable

Measuring the rate of spread of chaparral prescribed fires in northern California

Treesearch

S. L. Stephens; D. R. Weise; D. L. Fry; R. J. Keiffer; J. Dawson; E. Koo; J. Potts; P. J. Pagni

2008-01-01

Prescribed fire is a common method used to produce desired ecological effects in chaparral by mimicking the natural role of fire. Since prescribed fires are usually conducted in moderate fuel and weather conditions, models that accurately predict fire behavior and effects under these scenarios are important for management. In this study, explosive audio devices and...

How to predict the spread and intensity of forest and range fires

Treesearch

Richard C. Rothermel

1983-01-01

This manual documents procedures for estimating the rate of forward spread, intensity, flame length, and size of fires burning in forests and rangelands. Contains instructions for obtaining fuel and weather data, calculating fire behavior, and interpreting the results for application to actual fire problems. This is a companion publication to "

Developing the U.S. Wildland Fire Decision Support System

Treesearch

Erin Noonan-Wright; Tonja S. Opperman; Mark A. Finney; Tom Zimmerman; Robert C. Seli; Lisa M. Elenz; David E. Calkin; John R. Fiedler

2011-01-01

A new decision support tool, the Wildland Fire Decision Support System (WFDSS) has been developed to support risk-informed decision-making for individual fires in the United States. WFDSS accesses national weather data and forecasts, fire behavior prediction, economic assessment, smoke management assessment, and landscape databases to efficiently formulate and apply...

Reformulation of Rothermel's wildland fire behaviour model for heterogeneous fuelbeds.

Treesearch

David V. Sandberg; Cynthia L. Riccardi; Mark D. Schaaf

2007-01-01

Abstract: The Fuel Characteristic Classification System (FCCS) includes equations that calculate energy release and one-dimensional spread rate in quasi-steady-state fires in heterogeneous but spatially uniform wildland fuelbeds, using a reformulation of the widely used Rothermel fire spread model. This reformulation provides an automated means to predict fire behavior...

Development of Standard Fuel Models in Boreal Forests of Northeast China through Calibration and Validation

PubMed Central

Cai, Longyan; He, Hong S.; Wu, Zhiwei; Lewis, Benard L.; Liang, Yu

2014-01-01

Understanding the fire prediction capabilities of fuel models is vital to forest fire management. Various fuel models have been developed in the Great Xing'an Mountains in Northeast China. However, the performances of these fuel models have not been tested for historical occurrences of wildfires. Consequently, the applicability of these models requires further investigation. Thus, this paper aims to develop standard fuel models. Seven vegetation types were combined into three fuel models according to potential fire behaviors which were clustered using Euclidean distance algorithms. Fuel model parameter sensitivity was analyzed by the Morris screening method. Results showed that the fuel model parameters 1-hour time-lag loading, dead heat content, live heat content, 1-hour time-lag SAV(Surface Area-to-Volume), live shrub SAV, and fuel bed depth have high sensitivity. Two main sensitive fuel parameters: 1-hour time-lag loading and fuel bed depth, were determined as adjustment parameters because of their high spatio-temporal variability. The FARSITE model was then used to test the fire prediction capabilities of the combined fuel models (uncalibrated fuel models). FARSITE was shown to yield an unrealistic prediction of the historical fire. However, the calibrated fuel models significantly improved the capabilities of the fuel models to predict the actual fire with an accuracy of 89%. Validation results also showed that the model can estimate the actual fires with an accuracy exceeding 56% by using the calibrated fuel models. Therefore, these fuel models can be efficiently used to calculate fire behaviors, which can be helpful in forest fire management. PMID:24714164

Using a prescribed fire to test custom and standard fuel models for fire behaviour prediction in a non-native, grass-invaded tropical dry shrubland

Treesearch

Andrew D. Pierce; Sierra McDaniel; Mark Wasser; Alison Ainsworth; Creighton M. Litton; Christian P. Giardina; Susan Cordell; Ralf Ohlemuller

2014-01-01

Questions: Do fuel models developed for North American fuel types accurately represent fuel beds found in grass-invaded tropical shrublands? Do standard or custom fuel models for firebehavior models with in situ or RAWS measured fuel moistures affect the accuracy of predicted fire behavior in grass-invaded tropical shrublands? Location: Hawai’i Volcanoes National...

Winds, Mountains, and Wildland Fire: Improved Understanding of Coupled Atmosphere-Topography-Fire Interactions Through Large-Eddy Simulation

NASA Astrophysics Data System (ADS)

Munoz-Esparza, D.; Sauer, J.; Linn, R.

2015-12-01

Anomalous and unexpected fire behavior in complex terrain continues to result in substantial loss of property and extremely dangerous conditions for firefighting field personnel. We briefly discuss proposed hypotheses of fire interactions with atmospheric flows over complex terrain that can lead to poorly-understood and potentially catastrophic scenarios. Then, our recent results of numerical investigations via large-eddy simulation of coupled atmosphere-topography-fire phenomenology with the Los Alamos National Laboratory, HiGrad-Firetec model are presented as an example of the potential for increased understanding of these complex processes. This investigation focuses on the influence of downslope surface wind enhancement through stably stratified flow over an isolated hill, and the resulting dramatic changes in fire behavior including spread rate, and intensity. Implications with respect to counter-intuitive fire behavior and extreme fire events are discussed. This work demonstrates a tremendous opportunity to immediately create safer and more effective policy for field personnel through improved predictability of atmospheric conditions over complex terrain

The Simulations of Wildland Fire Smoke PM25 in the NWS Air Quality Forecasting Systems

NASA Astrophysics Data System (ADS)

Huang, H. C.; Pan, L.; McQueen, J.; Lee, P.; ONeill, S. M.; Ruminski, M.; Shafran, P.; Huang, J.; Stajner, I.; Upadhayay, S.; Larkin, N. K.

2017-12-01

The increase of wildland fire intensity and frequency in the United States (U.S.) has led to property loss, human fatality, and poor air quality due to elevated particulate matters and surface ozone concentrations. The NOAA/National Weather Service (NWS) built the National Air Quality Forecast Capability (NAQFC) based on the U.S. Environmental Protection Agency (EPA) Community Multi-scale Air Quality (CMAQ) Modeling System driven by the NCEP North American Mesoscale Forecast System meteorology to provide ozone and fine particulate matter (PM2.5) forecast guidance publicly. State and local forecasters use the NWS air quality forecast guidance to issue air quality alerts in their area. The NAQFC PM2.5 predictions include emissions from anthropogenic and biogenic sources, as well as natural sources such as dust storms and wildland fires. The wildland fire emission inputs to the NAQFC is derived from the NOAA National Environmental Satellite, Data, and Information Service Hazard Mapping System fire and smoke detection product and the emission module of the U.S. Forest Service (USFS) BlueSky Smoke Modeling Framework. Wildland fires are unpredictable and can be ignited by natural causes such as lightning or be human-caused. It is extremely difficult to predict future occurrences and behavior of wildland fires, as is the available bio-fuel to be burned for real-time air quality predictions. Assumptions of future day's wildland fire behavior often have to be made from older observed wildland fire information. The comparisons between the NAQFC modeled PM2.5 and the EPA AirNow surface observation show that large errors in PM2.5 prediction can occur if fire smoke emissions are sometimes placed at the wrong location and/or time. A configuration of NAQFC CMAQ-system to re-run previous 24 hours, during which wildland fires were observed from satellites has been included recently. This study focuses on the effort performed to minimize the error in NAQFC PM2.5 predictions resulting from incorporating fire smoke emissions into the NAQFC from a recently updated newer version of USFS BlueSky system. This study will show how new approaches has improved the PM2.5 predictions at both nearby and downstream areas from fire sources. Furthermore, Environment and Climate Change Canada (ECCC) fire emissions data are being tested.

[Fire behavior of Mongolian oak leaves fuel-bed under no-wind and zero-slope conditions. I. Factors affecting fire spread rate and modeling].

PubMed

Jin, Sen; Liu, Bo-Fei; Di, Xue-Ying; Chu, Teng-Fei; Zhang, Ji-Li

2012-01-01

Aimed to understand the fire behavior of Mongolian oak leaves fuel-bed under field condition, the leaves of a secondary Mongolian oak forest in Northeast Forestry University experimental forest farm were collected and brought into laboratory to construct fuel-beds with varied loading, height, and moisture content, and a total of 100 experimental fires were burned under no-wind and zero-slope conditions. It was observed that the fire spread rate of the fuel-beds was less than 0.5 m x min(-1). Fuel-bed loading, height, and moisture contents all had significant effects on the fire spread rate. The effect of fuel-bed moisture content on the fire spread had no significant correlations with fuel-bed loading and height, but the effect of fuel-bed height was related to the fuel-bed loading. The packing ratio of fuel-beds had less effect on the fire spread rate. Taking the fuel-bed loading, height, and moisture content as predictive variables, a prediction model for the fire spread rate of Mongolian oak leaves fuel-bed was established, which could explain 83% of the variance of the fire spread rate, with a mean absolute error 0.04 m x min(-1) and a mean relative error less than 17%.

Modeling tree-level fuel connectivity to evaluate the effectiveness of thinning treatments for reducing crown fire potential

Treesearch

Marco A. Contreras; Russell A. Parsons; Woodam Chung

2012-01-01

Land managers have been using fire behavior and simulation models to assist in several fire management tasks. These widely-used models use average attributes to make stand-level predictions without considering spatial variability of fuels within a stand. Consequently, as the existing models have limitations in adequately modeling crown fire initiation and propagation,...

Predicted fuel consumption in the Burnup model: sensitivity to four user inputs

Treesearch

D. C. Lutes

2013-01-01

Fuelbeds consist of a number of combustible components that are consumed during a fire, including duff, litter, vegetation (herbs, shrub, foliage, and branches) and down dead woody material (DWM). Combustion of DWM during a fire has a well-documented role in determining fire effects and fire behavior impacts such as emissions (Sandberg and others 2002), vegetative...

Modeling moisture content of fine dead wildland fuels: Input to the BEHAVE fire prediction system

Treesearch

Richard C. Rothermel; Ralph A. Wilson; Glen A. Morris; Stephen S. Sackett

1986-01-01

Describes a model for predicting moisture content of fine fuels for use with the BEHAVE fire behavior and fuel modeling system. The model is intended to meet the need for more accurate predictions of fine fuel moisture, particularly in northern conifer stands and on days following rain. The model is based on the Canadian Fine Fuel Moisture Code (FFMC), modified to...

Predicting fire behavior in palmetto-gallberry fuel complexes

Treesearch

W A. Hough; F. A. Albini

1978-01-01

Rate of spread, fireline intensity, and flame length can be predicted with reasonable accuracy for backfires and low-intensity head fires in the palmetto-gallberry fuel complex of the South. This fuel complex was characterized and variables were adjusted for use in Rothermel's (1972) spread model. Age of rough, height of understory, percent of area covered by...

Using relative humidity to predict spotfire probability on prescribed burns

Treesearch

John R. Weir

2007-01-01

Spotfires have and always will be a problem that burn bosses and fire crews will have to contend with on prescribed burns. Weather factors (temperature, wind speed and relative humidity) are the main variables burn bosses can use to predict and monitor prescribed fire behavior. At the Oklahoma State University Research Range, prescribed burns are conducted during...

Characterizing crown fuel distribution for conifers in the interior western United States

Treesearch

Seth Ex; Frederick W. Smith; Tara Keyser

2015-01-01

Canopy fire hazard evaluation is essential for prioritizing fuel treatments and for assessing potential risk to firefighters during suppression activities. Fire hazard is usually expressed as predicted potential fire behavior, which is sensitive to the methodology used to quantitatively describe fuel profiles: methodologies that assume that fuel is distributed...

Using BEHAVEPlus for predicting fire behavior in southern Appalachian hardwood stands subjected to fuel reduction treatments

Treesearch

Helen H. Mohr; Thomas A. Waldrop; Dean M. Simon

2010-01-01

There is a crucial need for fuel reduction in United States forests due to decades of fuel accumulation resulting from fire exclusion. The National Fire and Fire Surrogate Study (FFS) addresses this issue by examining the effects of three fuel reduction treatments on numerous response variables. At an FFS site in the southern Appalachian Mountains, fuels were altered...

Estimated smoldering probability: a new tool for predicting ground fire in the organic soils on the North Carolina Coastal Plain

Treesearch

James Reardon; Gary Curcio

2011-01-01

In the Southeastern United States, fires in pocosin wetlands and other similar vegetation communities with deep organic soils are a serious concern to fire managers. Highly flammable shrubs, such as gallberry and fetterbush, and small evergreen trees, such as red and loblolly bay, create the potential for extreme surface fire behavior. Moreover, deep organic soils...

Dorsomedial Prefrontal Cortex Contribution to Behavioral and Nucleus Accumbens Neuronal Responses to Incentive Cues

PubMed Central

Ishikawa, Akinori; Ambroggi, Frederic; Nicola, Saleem M.; Fields, Howard L.

2008-01-01

Cue-elicited phasic changes in firing of nucleus accumbens (NAc) neurons can facilitate reward-seeking behavior. Here, we test the hypothesis that the medial prefrontal cortex (mPFC), which sends a dense glutamatergic projection to the NAc core, contributes to NAc neuronal firing responses to reward-predictive cues. Rats trained to perform an operant response to a cue for sucrose were implanted with recording electrodes in the core of the NAc and microinjection cannulas in the dorsal mPFC (dmPFC). The cue-evoked firing of NAc neurons was reduced by bilateral injection of GABAA and GABAB agonists into the dmPFC concomitant with loss of behavioral responding to the cue. In addition, unilateral dmPFC inactivation reduced ipsilateral cue excitations and contralateral cue inhibitions. These findings indicate that cue-evoked excitations and inhibitions of NAc core neurons depend on dmPFC projections to the NAc and that these phasic changes contribute to the behavioral response to reward-predictive cues. PMID:18463262

An improved canopy wind model for predicting wind adjustment factors and wildland fire behavior

Treesearch

W. J. Massman; J. M. Forthofer; M. A. Finney

2017-01-01

The ability to rapidly estimate wind speed beneath a forest canopy or near the ground surface in any vegetation is critical to practical wildland fire behavior models. The common metric of this wind speed is the "mid-flame" wind speed, UMF. However, the existing approach for estimating UMF has some significant shortcomings. These include the assumptions that...

Heat transfer and vascular cambium necrosis in the boles of trees during surface fires

Treesearch

M. B. Dickinson

2002-01-01

Heat-transfer and cell-survival models are used to link surface fire behavior with vascular cambium necrosis from heating by flames. Vascular cambium cell survival was predicted with a numerical model based on the kinetics of protein denaturation and parameterized with data from the literature. Cell survival was predicted for vascular cambium temperature regimes...

Numerical modeling of the effects of fire-induced convection and fire-atmosphere interactions on wildfire spread and fire plume dynamics

NASA Astrophysics Data System (ADS)

Sun, Ruiyu

It is possible due to present day computing power to produce a fluid dynamical physically-based numerical solution to wildfire behavior, at least in the research mode. This type of wildfire modeling affords a flexibility and produces details that are not available in either current operational wildfire behavior models or field experiments. However before using these models to study wildfire, validation is necessary, and model results need to be systematically and objectively analyzed and compared to real fires. Plume theory and data from the Meteotron experiment, which was specially designed to provide results from measurements for the theoretical study of a convective plume produced by a high heat source at the ground, are used here to evaluate the fire plume properties simulated by two numerical wildfire models, the Fire Dynamics Simulator or FDS, and the Clark coupled atmosphere-fire model. The study indicates that the FDS produces good agreement with the plume theory and the Meteotron results. The study also suggests that the coupled atmosphere-fire model, a less explicit and ideally less computationally demanding model than the FDS; can produce good agreement, but that the agreement is sensitive to the method of putting the energy released from the fire into the atmosphere. The WFDS (Wildfire and wildland-urban interface FDS), an extension of the FDS to the vegetative fuel, and the Australian grass fire experiments are used to evaluate and improve the UULES-wildfire coupled model. Despite the simple fire parameterization in the UULES-wildfire coupled model, the fireline is fairly well predicted in terms of both shape and location in the simulation of Australian grass fire experiment F19. Finally, the UULES-wildfire coupled model is used to examine how the turbulent flow in the atmospheric boundary layer (ABL) affects the growth of the grass fires. The model fires showed significant randomness in fire growth: Fire spread is not deterministic in the ABL, and a probabilistic prediction method is warranted. Of the two contributors to the variability in fire growth in the grass fire simulations in the ABL, fire-induced convection, as opposed to the turbulent ABL wind, appears to be the more important one. One mechanism associated with enhanced fire-induced flow is the downdraft behind the frontal fireline. The downdraft is the direct result of the random interaction between the fire plume and the large eddies in the ABL. This study indicates a connection between fire variability in rate of spread and area burnt and so-called convective velocity scale, and it may be possible to use this boundary-layer scale parameter to account for the effects of ABL turbulence on fire spread and fire behavior in today's operational fire prediction systems.

Evaluating crown fire rate of spread predictions from physics-based models

Treesearch

C. M. Hoffman; J. Ziegler; J. Canfield; R. R. Linn; W. Mell; C. H. Sieg; F. Pimont

2015-01-01

Modeling the behavior of crown fires is challenging due to the complex set of coupled processes that drive the characteristics of a spreading wildfire and the large range of spatial and temporal scales over which these processes occur. Detailed physics-based modeling approaches such as FIRETEC and the Wildland Urban Interface Fire Dynamics Simulator (WFDS) simulate...

Evaluating fuel complexes for fire hazard mitigation planning in the southeastern United States

Treesearch

Anne G. Andreu; Dan Shea; Bernard R. Parresol; Roger D. Ottmar

2012-01-01

Fire hazard mitigation planning requires an accurate accounting of fuel complexes to predict potential fire behavior and effects of treatment alternatives. In the southeastern United States, rapid vegetation growth coupled with complex land use history and forest management options requires a dynamic approach to fuel characterization. In this study we assessed...

Optimal firing rate estimation

NASA Technical Reports Server (NTRS)

Paulin, M. G.; Hoffman, L. F.

2001-01-01

We define a measure for evaluating the quality of a predictive model of the behavior of a spiking neuron. This measure, information gain per spike (Is), indicates how much more information is provided by the model than if the prediction were made by specifying the neuron's average firing rate over the same time period. We apply a maximum Is criterion to optimize the performance of Gaussian smoothing filters for estimating neural firing rates. With data from bullfrog vestibular semicircular canal neurons and data from simulated integrate-and-fire neurons, the optimal bandwidth for firing rate estimation is typically similar to the average firing rate. Precise timing and average rate models are limiting cases that perform poorly. We estimate that bullfrog semicircular canal sensory neurons transmit in the order of 1 bit of stimulus-related information per spike.

Documenting PyroCb Development on High-Intensity Boreal Fires: Implications for the Arctic Atmosphere

NASA Astrophysics Data System (ADS)

Stocks, B. J.; Fromm, M. D.; Servranckx, R.; Lindsey, D.

2007-12-01

The recent confirmation that smoke from high-intensity boreal forest fires can reach the Upper Troposphere/Lower Stratosphere (UTLS) through pyroconvection and be transported long distances has raised concern over the wider-scale environmental impact of boreal fire smoke. This concern is further elevated as climate change projections indicate a significant increase in the frequency and severity of boreal forest fires over the next century. Smoke in the UTLS is frequently transported to the Arctic and may have important implications for the radiative energy budget in the polar region. Soot deposition from fires may lead to enhanced melting of sea ice and glaciers, and the chemical impact of fire emissions at high altitudes is largely unknown. This knowledge gap will be addressed during the International Polar Year (IPY), as boreal fire emissions will be tracked and documented in detail through aerial, satellite and ground-based measurements, as a key component of the POLARCAT (Polar Study using Aircraft, Remote Sensing, Surface Measurements and Models, of Climate, Chemistry, Aerosols, and Transport) and ARCTAS (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites) projects to be conducted in 2008. A large fire in the Canadian Northwest Territories burned throughout the month of June 2007, in a remote region where forest fires are not actively suppressed, eventually reaching 90,000 hectares in size. This fire was monitored for blowup one week in advance; it erupted into pyroconvection on June 25, 2007. We present an analysis of this event combining satellite data with ground-based measurements to document the development and impact of this classic pyroCb event. Under extreme fire danger conditions, the fire burned close to 20,000 hectares on that day. Fire behavior was consistent with predictions using the Canadian Fire Behavior Prediction System, with the fire spreading at 2.7 km/hr, consuming 33,000 kg of fuel hourly, generating an energy release rate of ~45,000 kW/m. This constitutes a typical high-intensity boreal crown fire, common across northern Canada every summer, and often capable of producing independent pyroconvection. The June 25 blowup was monitored using OMI AI, CALIPSO, Aqua MODIS, AVHRR and GOES satellite imagery, and these measurements validated the predicted fire behavior, including the development of a convection column that rose 10-11 km and injected smoke within the UTLS. Over subsequent days this smoke spread to Arctic latitudes (70-80 degrees N).

Wind adjustment factors for predicting fire behavior in three fuel types in Alaska.

Treesearch

Rodney A. Norum

1983-01-01

Factors for adjusting wind velocities from the 20-foot standard anemometer height down to an average wildfire midflame height (3.5 ft for the fuels studied) are given for exposed, partially sheltered, and sheltered fuels in Alaska. The values are suitable for predicting wildfire behavior.

Juvenile firesetting in Italy: relationship to aggression, psychopathology, personality, self-efficacy, and school functioning.

PubMed

Del Bove, Giannetta; Caprara, Gian Vittorio; Pastorelli, Concetta; Paciello, Marinella

2008-06-01

Despite the fact that juvenile fire involvement is associated with significant injuries and is highly correlated with diverse maladjustment characteristics, firesetting has never been empirically evaluated in Italy. Participants included 567 youth between 11 and 18 years of age. This investigation attempted to address four gaps in the literature. The first objective was to examine how common firesetting behavior is among Italian youth. The second goal was to explore whether in Italy firesetting is associated with other types of psychopathology and later maladjustment. Thirdly, this study sought to extend our knowledge of the personal characteristics of firesetters. Finally, the relationship between firesetting and aggression remains an empirical question. Results suggested that almost one in three Italian youth reported engaging in fire involvement. Moreover, firesetting in Italian youth is associated with significant levels of antisocial behavior and psychopathology. In fact, firesetters-only demonstrated higher levels of most measures of maladjustment than did aggressive-only youth. Finally, the findings of this study suggest that aggressive firesetters are not at higher risk than nonaggressive firesetters. Instead, fire involvement appears to be the most important variable when predicting serious behavioral difficulties and anti-sociality. This highlights the importance of fire involvement in both the assessment and prediction of antisocial behavior and psychosocial adjustment in adolescence.

Multiplexing of Motor Information in the Discharge of a Collision Detecting Neuron during Escape Behaviors

PubMed Central

Fotowat, Haleh; Harrison, Reid R; Gabbiani, Fabrizio

2010-01-01

Locusts possess an identified neuron, the descending contralateral movement detector (DCMD), conveying visual information about impending collision from the brain to thoracic motor centers. We built a telemetry system to simultaneously record, in freely behaving animals, the activity of the DCMD and of motoneurons involved in jump execution. Co-contraction of antagonistic leg muscles, a required preparatory phase, was triggered after the DCMD firing rate crossed a threshold. Thereafter, the number of DCMD spikes predicted precisely motoneuron activity and jump occurrence. Additionally, the time of DCMD peak firing rate predicted that of jump. Ablation experiments suggest that the DCMD, together with a nearly identical ipsilateral descending neuron, is responsible for the timely execution of the escape. Thus, three distinct features that are multiplexed in a single neuron’s sensory response to impending collision – firing rate threshold, peak firing time, and spike count – likely control three distinct motor aspects of escape behaviors. PMID:21220105

Forecasting wildland fire behavior using high-resolution large-eddy simulations

NASA Astrophysics Data System (ADS)

Munoz-Esparza, D.; Kosovic, B.; Jimenez, P. A.; Anderson, A.; DeCastro, A.; Brown, B.

2016-12-01

Wildland fires are responsible for large socio-economic impacts. Fires affect the environment, damage structures, threaten lives, cause health issues, and involve large suppression costs. These impacts can be mitigated via accurate fire spread forecast to inform the incident management team. To this end, the state of Colorado is funding the development of the Colorado Fire Prediction System (CO-FPS). The system is based on the Weather Research and Forecasting (WRF) model enhanced with a fire behavior module (WRF-Fire). Realistic representation of wildland fire behavior requires explicit representation of small scale weather phenomena to properly account for coupled atmosphere-wildfire interactions. Moreover, transport and dispersion of biomass burning emissions from wildfires is controlled by turbulent processes in the atmospheric boundary layer, which are difficult to parameterize and typically lead to large errors when simplified source estimation and injection height methods are used. Therefore, we utilize turbulence-resolving large-eddy simulations at a resolution of 111 m to forecast fire spread and smoke distribution using a coupled atmosphere-wildfire model. This presentation will describe our improvements to the level-set based fire-spread algorithm in WRF-Fire and an evaluation of the operational system using 12 wildfire events that occurred in Colorado in 2016, as well as other historical fires. In addition, the benefits of explicit representation of turbulence for smoke transport and dispersion will be demonstrated.

Forecasting wildland fire behavior using high-resolution large-eddy simulations

NASA Astrophysics Data System (ADS)

Munoz-Esparza, D.; Kosovic, B.; Jimenez, P. A.; Anderson, A.; DeCastro, A.; Brown, B.

2017-12-01

Wildland fires are responsible for large socio-economic impacts. Fires affect the environment, damage structures, threaten lives, cause health issues, and involve large suppression costs. These impacts can be mitigated via accurate fire spread forecast to inform the incident management team. To this end, the state of Colorado is funding the development of the Colorado Fire Prediction System (CO-FPS). The system is based on the Weather Research and Forecasting (WRF) model enhanced with a fire behavior module (WRF-Fire). Realistic representation of wildland fire behavior requires explicit representation of small scale weather phenomena to properly account for coupled atmosphere-wildfire interactions. Moreover, transport and dispersion of biomass burning emissions from wildfires is controlled by turbulent processes in the atmospheric boundary layer, which are difficult to parameterize and typically lead to large errors when simplified source estimation and injection height methods are used. Therefore, we utilize turbulence-resolving large-eddy simulations at a resolution of 111 m to forecast fire spread and smoke distribution using a coupled atmosphere-wildfire model. This presentation will describe our improvements to the level-set based fire-spread algorithm in WRF-Fire and an evaluation of the operational system using 12 wildfire events that occurred in Colorado in 2016, as well as other historical fires. In addition, the benefits of explicit representation of turbulence for smoke transport and dispersion will be demonstrated.

Experimental Study of Fire Hazards of Thermal-Insulation Material in Diesel Locomotive: Aluminum-Polyurethane.

PubMed

Zhang, Taolin; Zhou, Xiaodong; Yang, Lizhong

2016-03-05

This work investigated experimentally and theoretically the fire hazards of thermal-insulation materials used in diesel locomotives under different radiation heat fluxes. Based on the experimental results, the critical heat flux for ignition was determined to be 6.15 kW/m² and 16.39 kW/m² for pure polyurethane and aluminum-polyurethane respectively. A theoretical model was established for both to predict the fire behaviors under different circumstances. The fire behavior of the materials was evaluated based on the flashover and the total heat release rate (HRR). The fire hazards levels were classified based on different experimental results. It was found that the fire resistance performance of aluminum-polyurethane is much better than that of pure-polyurethane under various external heat fluxes. The concentration of toxic pyrolysis volatiles generated from aluminum-polyurethane materials is much higher than that of pure polyurethane materials, especially when the heat flux is below 50 kW/m². The hazard index HI during peak width time was proposed based on the comprehensive impact of time and concentrations. The predicted HI in this model coincides with the existed N-gas and FED models which are generally used to evaluate the fire gas hazard in previous researches. The integrated model named HNF was proposed as well to estimate the fire hazards of materials by interpolation and weighted average calculation.

Experimental Study of Fire Hazards of Thermal-Insulation Material in Diesel Locomotive: Aluminum-Polyurethane

PubMed Central

Zhang, Taolin; Zhou, Xiaodong; Yang, Lizhong

2016-01-01

This work investigated experimentally and theoretically the fire hazards of thermal-insulation materials used in diesel locomotives under different radiation heat fluxes. Based on the experimental results, the critical heat flux for ignition was determined to be 6.15 kW/m2 and 16.39 kW/m2 for pure polyurethane and aluminum-polyurethane respectively. A theoretical model was established for both to predict the fire behaviors under different circumstances. The fire behavior of the materials was evaluated based on the flashover and the total heat release rate (HRR). The fire hazards levels were classified based on different experimental results. It was found that the fire resistance performance of aluminum-polyurethane is much better than that of pure-polyurethane under various external heat fluxes. The concentration of toxic pyrolysis volatiles generated from aluminum-polyurethane materials is much higher than that of pure polyurethane materials, especially when the heat flux is below 50 kW/m2. The hazard index HI during peak width time was proposed based on the comprehensive impact of time and concentrations. The predicted HI in this model coincides with the existed N-gas and FED models which are generally used to evaluate the fire gas hazard in previous researches. The integrated model named HNF was proposed as well to estimate the fire hazards of materials by interpolation and weighted average calculation. PMID:28773295

Fire control method and analytical model for large liquid hydrocarbon pool fires

NASA Technical Reports Server (NTRS)

Fenton, D. L.

1986-01-01

The dominate parameter governing the behavior of a liquid hydrocarbon (JP-5) pool fire is wind speed. The most effective method of controlling wind speed in the vicinity of a large circular (10 m dia.) pool fire is a set of concentric screens located outside the perimeter. Because detailed behavior of the pool fire structure within one pool fire diameter is unknown, an analytical model supported by careful experiments is under development. As a first step toward this development, a regional pool fire model was constructed for the no-wind condition consisting of three zones -- liquid fuel, combustion, and plume -- where the predicted variables are mass burning rate and characteristic temperatures of the combustion and plume zones. This zone pool fire model can be modified to incorporate plume bending by wind, radiation absorption by soot particles, and a different ambient air flow entrainment rate. Results from the zone model are given for a pool diameter of 1.3 m and are found to reproduce values in the literature.

Influence of vegetation moisture on combustion of pyrolysis gases in wildland fires

Treesearch

S.C. Dover; A.R. Dahale; B. Shotorban; S. Mahalingam; D.R. Weise

2011-01-01

Since wildland fires occur in living vegetation, the fuel moisture content must be considered in order to correctly predict the behavior of the fire. One facet of combustion of pyrolysis gases that has not been considered in previous research is the effect of moisture on the combustion process. This effect is investigated by using CHEMKIN software to study an opposed...

Forest Fire Danger Rating (FFDR) Prediction over the Korean Peninsula

NASA Astrophysics Data System (ADS)

Song, B.; Won, M.; Jang, K.; Yoon, S.; Lim, J.

2016-12-01

Approximately five hundred forest fires occur and inflict the losses of both life and property each year in Korea during the forest fire seasons in the spring and autumn. Thus, an accurate prediction of forest fire is essential for effective forest fire prevention. The meteorology is one of important factors to predict and understand the fire occurrence as well as its behaviors and spread. In this study, we present the Forest Fire Danger Rating Systems (FFDRS) on the Korean Peninsula based on the Daily Weather Index (DWI) which represents the meteorological characteristics related to forest fire. The thematic maps including temperature, humidity, and wind speed produced from Korea Meteorology Administration (KMA) were applied to the forest fire occurrence probability model by logistic regression to analyze the DWI over the Korean Peninsula. The regional data assimilation and prediction system (RDAPS) and the improved digital forecast model were used to verify the sensitivity of DWI. The result of verification test revealed that the improved digital forecast model dataset showed better agreements with the real-time weather data. The forest fire danger rating index (FFDRI) calculated by the improved digital forecast model dataset showed a good agreement with the real-time weather dataset at the 233 administrative districts (R2=0.854). In addition, FFDRI were compared with observation-based FFDRI at 76 national weather stations. The mean difference was 0.5 at the site-level. The results produced in this study indicate that the improved digital forecast model dataset can be useful to predict the FFDRI in the Korean Peninsula successfully.

Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance

PubMed Central

Hong, Ha; Solomon, Ethan A.; DiCarlo, James J.

2015-01-01

To go beyond qualitative models of the biological substrate of object recognition, we ask: can a single ventral stream neuronal linking hypothesis quantitatively account for core object recognition performance over a broad range of tasks? We measured human performance in 64 object recognition tests using thousands of challenging images that explore shape similarity and identity preserving object variation. We then used multielectrode arrays to measure neuronal population responses to those same images in visual areas V4 and inferior temporal (IT) cortex of monkeys and simulated V1 population responses. We tested leading candidate linking hypotheses and control hypotheses, each postulating how ventral stream neuronal responses underlie object recognition behavior. Specifically, for each hypothesis, we computed the predicted performance on the 64 tests and compared it with the measured pattern of human performance. All tested hypotheses based on low- and mid-level visually evoked activity (pixels, V1, and V4) were very poor predictors of the human behavioral pattern. However, simple learned weighted sums of distributed average IT firing rates exactly predicted the behavioral pattern. More elaborate linking hypotheses relying on IT trial-by-trial correlational structure, finer IT temporal codes, or ones that strictly respect the known spatial substructures of IT (“face patches”) did not improve predictive power. Although these results do not reject those more elaborate hypotheses, they suggest a simple, sufficient quantitative model: each object recognition task is learned from the spatially distributed mean firing rates (100 ms) of ∼60,000 IT neurons and is executed as a simple weighted sum of those firing rates. SIGNIFICANCE STATEMENT We sought to go beyond qualitative models of visual object recognition and determine whether a single neuronal linking hypothesis can quantitatively account for core object recognition behavior. To achieve this, we designed a database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior. PMID:26424887

New tendencies in wildland fire simulation for understanding fire phenomena: An overview of the WFDS system capabilities in Mediterranean ecosystems

NASA Astrophysics Data System (ADS)

Pastor, E.; Tarragó, D.; Planas, E.

2012-04-01

Wildfire theoretical modeling endeavors predicting fire behavior characteristics, such as the rate of spread, the flames geometry and the energy released by the fire front by applying the physics and the chemistry laws that govern fire phenomena. Its ultimate aim is to help fire managers to improve fire prevention and suppression and hence reducing damage to population and protecting ecosystems. WFDS is a 3D computational fluid dynamics (CFD) model of a fire-driven flow. It is particularly appropriate for predicting the fire behaviour burning through the wildland-urban interface, since it is able to predict the fire behaviour in the intermix of vegetative and structural fuels that comprise the wildland urban interface. This model is not suitable for operational fire management yet due to computational costs constrains, but given the fact that it is open-source and that it has a detailed description of the fuels and of the combustion and heat transfer mechanisms it is currently a suitable system for research purposes. In this paper we present the most important characteristics of the WFDS simulation tool in terms of the models implemented, the input information required and the outputs that the simulator gives useful for understanding fire phenomena. We briefly discuss its advantages and opportunities through some simulation exercises of Mediterranean ecosystems.

Predictions of fire behavior and resistance to control: for use with photo series for the ponderosa pine type, ponderosa pine and associated species type, and lodgepole pine type.

Treesearch

Franklin R. Ward; David V. Sandberg

1981-01-01

This publication presents tables on the behavior of fire and the resistance of fuels to control. The information is to be used with the publication, "Photo Series for Quantifying Forest Residues in the Ponderosa Pine Type, Ponderosa Pine and Associated Species Type, Lodgepole Pine Type" (Maxwell, Wayne G.; Ward, Franklin R. 1976. Gen. Tech. Rep. PNW-GTR-052....

Predictions of fire behavior and resistance to control: for use with photo series for the sierra mixed conifer type and the sierra true fir type.

Treesearch

Franklin R. Ward; David V. Sandberg

1981-01-01

This publication presents tables on the behavior of fire and the resistance: of fuels to control. The information is to be used with the photos in the publication, "Photo Series for Quantifying Forest Residues in the Sierra Mixed Conifer Type, Sierra True Fir Type" (Maxwell, Wayne G.; Ward, Franklin R. 1979. Gen. Tech. Rep. PNW-GTR-095. Portland, OR: U.S....

A multi-scale conceptual model of fire and disease interactions in North American forests

NASA Astrophysics Data System (ADS)

Varner, J. M.; Kreye, J. K.; Sherriff, R.; Metz, M.

2013-12-01

One aspect of global change with increasing attention is the interactions between irruptive pests and diseases and wildland fire behavior and effects. These pests and diseases affect fire behavior and effects in spatially and temporally complex ways. Models of fire and pathogen interactions have been constructed for individual pests or diseases, but to date, no synthesis of this complexity has been attempted. Here we synthesize North American fire-pathogen interactions into syndromes with similarities in spatial extent and temporal duration. We base our models on fire interactions with three examples: sudden oak death (caused by the pathogen Phytopthora ramorum) and the native tree tanoak (Notholithocarpus densiflorus); mountain pine beetle (Dendroctonus ponderosae) and western Pinus spp.; and hemlock woolly adelgid (Adelges tsugae) on Tsuga spp. We evaluate each across spatial (severity of attack from branch to landscape scale) and temporal scales (from attack to decades after) and link each change to its coincident effects on fuels and potential fire behavior. These syndromes differ in their spatial and temporal severity, differentially affecting windows of increased or decreased community flammability. We evaluate these models with two examples: the recently emergent ambrosia beetle-vectored laurel wilt (caused by the pathogen Raffaelea lauricola) in native members of the Lauraceae and the early 20th century chestnut blight (caused by the pathogen Cryphonectria parasitica) that led to the decline of American chestnut (Castanea dentata). Some changes (e.g., reduced foliar moisture content) have short-term consequences for potential fire behavior while others (functional extirpation) have more complex indirect effects on community flammability. As non-native emergent diseases and pests continue, synthetic models that aid in prediction of fire behavior and effects will enable the research and management community to prioritize mitigation efforts to realized effects.

Development and evaluation of the photoload sampling technique

Treesearch

Robert E. Keane; Laura J. Dickinson

2007-01-01

Wildland fire managers need better estimates of fuel loading so they can accurately predict potential fire behavior and effects of alternative fuel and ecosystem restoration treatments. This report presents the development and evaluation of a new fuel sampling method, called the photoload sampling technique, to quickly and accurately estimate loadings for six common...

Fire danger rating and fire behavior prediction in the United States

Treesearch

Patricia L. Andrews

2005-01-01

For the seven year period from 1998 to 2004, an average of almost 79,000 fires per year on U.S. Federal and State land burned a yearly average of over 22,000 km2. An average of 1 billion US dollars was spent on suppression each year by the Federal agencies alone. Variation in climate, vegetation, and population across the U.S. leads to significant differences in the...

Behavior of Insulated Carbon-FRP-Strengthened RC Beams Exposed to Fire

NASA Astrophysics Data System (ADS)

Sayin, B.

2014-09-01

There are two main approaches to improving the fire resistance of fiber-reinforced polymer (FRP) systems. While the most common method is to protect or insulate the FRP system, an other way is to use fibers and resins with a better fire performance. This paper presents a numerical investigation into the five protection behavior of insulated carbon-fiber-reinforced-polymer (CFRP)-strengthened reinforced concrete (RC) beams. The effects of external loading and thermal expansion of materials at elevated temperatures are taken into consideration in a finite-element model. The validity of the numerical model is demonstrated with results from an existing experimental study on insulated CFRP-strengthened RC beams. Conclusions of this investigation are employed to predict the structural behavior of CFRP-strengthened concrete structures.

Predictions of fire behavior and resistance to control: for use with photo series for the Douglas fir-hemlock type and the coastal Douglas-fir-hardwood type.

Treesearch

David V. SANDBERG; Franklin R. Ward

1981-01-01

This publication presents tables on the behavior of fire and the resistance of fuels to control. The information is to be used with the photos in the publication, "Photo Series for Quantifying Forest Residues in the Coastal Douglas-fir—Hemlock Type, Coastal Douglas-fir—Hardwood Type" (Maxwell, Wayne G.; Ward, Franklin R. 1976. Gen. Tech. Rep. PNW-GTR-051....

FireMap: A Web Tool for Dynamic Data-Driven Predictive Wildfire Modeling Powered by the WIFIRE Cyberinfrastructure

NASA Astrophysics Data System (ADS)

Block, J.; Crawl, D.; Artes, T.; Cowart, C.; de Callafon, R.; DeFanti, T.; Graham, J.; Smarr, L.; Srivas, T.; Altintas, I.

2016-12-01

The NSF-funded WIFIRE project has designed a web-based wildfire modeling simulation and visualization tool called FireMap. The tool executes FARSITE to model fire propagation using dynamic weather and fire data, configuration settings provided by the user, and static topography and fuel datasets already built-in. Using GIS capabilities combined with scalable big data integration and processing, FireMap enables simple execution of the model with options for running ensembles by taking the information uncertainty into account. The results are easily viewable, sharable, repeatable, and can be animated as a time series. From these capabilities, users can model real-time fire behavior, analyze what-if scenarios, and keep a history of model runs over time for sharing with collaborators. Firemap runs FARSITE with national and local sensor networks for real-time weather data ingestion and High-Resolution Rapid Refresh (HRRR) weather for forecasted weather. The HRRR is a NOAA/NCEP operational weather prediction system comprised of a numerical forecast model and an analysis/assimilation system to initialize the model. It is run with a horizontal resolution of 3 km, has 50 vertical levels, and has a temporal resolution of 15 minutes. The HRRR requires an Environmental Data Exchange (EDEX) server to receive the feed and generate secondary products out of it for the modeling. UCSD's EDEX server, funded by NSF, makes high-resolution weather data available to researchers worldwide and enables visualization of weather systems and weather events lasting months or even years. The high-speed server aggregates weather data from the University Consortium for Atmospheric Research by way of a subscription service from the Consortium called the Internet Data Distribution system. These features are part of WIFIRE's long term goals to build an end-to-end cyberinfrastructure for real-time and data-driven simulation, prediction and visualization of wildfire behavior. Although Firemap is a research product of WIFIRE, developed in collaboration with a number of fire departments, the tool is operational in pilot form for providing big data-driven predictive fire spread modeling. Most recently, FireMap was used for situational awareness in the July 2016 Sand Fire by LA City and LA County Fire Departments.

Firing a Weapon and Killing In Combat Are Associated with Suicidal Ideation in OEF/OIF Veterans

PubMed Central

Tripp, Jessica C.; McDevitt-Murphy, Meghan E.; Henschel, Aisling V.

2016-01-01

Objective Combat veterans are at risk for several adverse outcomes such as posttraumatic stress disorder (PTSD), depression, hazardous alcohol use, and most critically, suicidal behaviors. The high rate of suicide in veterans has been understood as a correlate of PTSD and depression, but it is possible that certain specific types of combat experiences may lead to suicidal behaviors. Acts committed by the veteran in the context of war such as killing may evoke a “moral injury,” which leads to thoughts of ending one’s life. Method The present exploratory research examined relationships between combat experiences and suicidal ideation (SI) and PTSD in a sample of 68 OEF/OIF veterans (91% male, mean age = 32.31 years) who had screened positive for alcohol misuse. We examined firing a weapon/killing in combat (Firing/Killing) and killing in combat (Killing) alone as predictors of (SI) and PTSD severity in both the full sample, and in analyses that examined men only. Results Firing/Killing were associated with SI for the full sample and men only, and Killing showed a trend towards significance in predicting SI. Hierarchical regression analyses suggested that Firing/Killing did not predict PTSD for the full sample or men only, but Killing was predictive of PTSD for both samples. Conclusions These results indicate that there may be differences in Firing/Killing and Killing alone in OEF/OIF veterans who screened positive for alcohol misuse. Thorough screening of combat experiences and addressing moral injury in returning combat veterans may help reduce high rates of suicide and PTSD. PMID:26460495

Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance.

PubMed

Majaj, Najib J; Hong, Ha; Solomon, Ethan A; DiCarlo, James J

2015-09-30

To go beyond qualitative models of the biological substrate of object recognition, we ask: can a single ventral stream neuronal linking hypothesis quantitatively account for core object recognition performance over a broad range of tasks? We measured human performance in 64 object recognition tests using thousands of challenging images that explore shape similarity and identity preserving object variation. We then used multielectrode arrays to measure neuronal population responses to those same images in visual areas V4 and inferior temporal (IT) cortex of monkeys and simulated V1 population responses. We tested leading candidate linking hypotheses and control hypotheses, each postulating how ventral stream neuronal responses underlie object recognition behavior. Specifically, for each hypothesis, we computed the predicted performance on the 64 tests and compared it with the measured pattern of human performance. All tested hypotheses based on low- and mid-level visually evoked activity (pixels, V1, and V4) were very poor predictors of the human behavioral pattern. However, simple learned weighted sums of distributed average IT firing rates exactly predicted the behavioral pattern. More elaborate linking hypotheses relying on IT trial-by-trial correlational structure, finer IT temporal codes, or ones that strictly respect the known spatial substructures of IT ("face patches") did not improve predictive power. Although these results do not reject those more elaborate hypotheses, they suggest a simple, sufficient quantitative model: each object recognition task is learned from the spatially distributed mean firing rates (100 ms) of ∼60,000 IT neurons and is executed as a simple weighted sum of those firing rates. Significance statement: We sought to go beyond qualitative models of visual object recognition and determine whether a single neuronal linking hypothesis can quantitatively account for core object recognition behavior. To achieve this, we designed a database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior. Copyright © 2015 the authors 0270-6474/15/3513402-17$15.00/0.

A high-quality fuels database of photos and information

Treesearch

Clinton S. Wright; Paige C. Eagle; Diana L. Olson

2010-01-01

Photo series and their associated data provide a quick and easy way for managers to quantify and describe fuel and vegetation properties, such as loading of dead and down woody material, tree density, or height of understory vegetation. This information is critical for making fuel management decisions and for predicting fire behavior and fire effects. The Digital Photo...

Fuel and fire behavior prediction in big sagebrush

Treesearch

James K. Brown

1982-01-01

Relationships between height of big sagebrush and crown area, fuel loading, bulk density, size distribution of foliage and stemwood, and fraction dead stemwood are presented. Based upon these relationships, modeled rate-of-fire spread and fireline intensity are shown for sagebrush ranging in height from 20 to 120 em and in coverage from 10 to 40 percent. Verification...

A cellular automaton model of wildfire propagation and extinction

Treesearch

Keith C. Clarke; James A. Brass; Phillip J. Riggan

1994-01-01

We propose a new model to predict the spatial and temporal behavior of wildfires. Fire spread and intensity were simulated using a cellular automaton model. Monte Carlo techniques were used to provide fire risk probabilities for areas where fuel loadings and topography are known. The model assumes predetermined or measurable environmental variables such as wind...

Modeling task-specific neuronal ensembles improves decoding of grasp

NASA Astrophysics Data System (ADS)

Smith, Ryan J.; Soares, Alcimar B.; Rouse, Adam G.; Schieber, Marc H.; Thakor, Nitish V.

2018-06-01

Objective. Dexterous movement involves the activation and coordination of networks of neuronal populations across multiple cortical regions. Attempts to model firing of individual neurons commonly treat the firing rate as directly modulating with motor behavior. However, motor behavior may additionally be associated with modulations in the activity and functional connectivity of neurons in a broader ensemble. Accounting for variations in neural ensemble connectivity may provide additional information about the behavior being performed. Approach. In this study, we examined neural ensemble activity in primary motor cortex (M1) and premotor cortex (PM) of two male rhesus monkeys during performance of a center-out reach, grasp and manipulate task. We constructed point process encoding models of neuronal firing that incorporated task-specific variations in the baseline firing rate as well as variations in functional connectivity with the neural ensemble. Models were evaluated both in terms of their encoding capabilities and their ability to properly classify the grasp being performed. Main results. Task-specific ensemble models correctly predicted the performed grasp with over 95% accuracy and were shown to outperform models of neuronal activity that assume only a variable baseline firing rate. Task-specific ensemble models exhibited superior decoding performance in 82% of units in both monkeys (p  <  0.01). Inclusion of ensemble activity also broadly improved the ability of models to describe observed spiking. Encoding performance of task-specific ensemble models, measured by spike timing predictability, improved upon baseline models in 62% of units. Significance. These results suggest that additional discriminative information about motor behavior found in the variations in functional connectivity of neuronal ensembles located in motor-related cortical regions is relevant to decode complex tasks such as grasping objects, and may serve the basis for more reliable and accurate neural prosthesis.

Long-Term Predictive and Feedback Encoding of Motor Signals in the Simple Spike Discharge of Purkinje Cells

PubMed Central

Popa, Laurentiu S.; Streng, Martha L.

2017-01-01

Abstract Most hypotheses of cerebellar function emphasize a role in real-time control of movements. However, the cerebellum’s use of current information to adjust future movements and its involvement in sequencing, working memory, and attention argues for predicting and maintaining information over extended time windows. The present study examines the time course of Purkinje cell discharge modulation in the monkey (Macaca mulatta) during manual, pseudo-random tracking. Analysis of the simple spike firing from 183 Purkinje cells during tracking reveals modulation up to 2 s before and after kinematics and position error. Modulation significance was assessed against trial shuffled firing, which decoupled simple spike activity from behavior and abolished long-range encoding while preserving data statistics. Position, velocity, and position errors have the most frequent and strongest long-range feedforward and feedback modulations, with less common, weaker long-term correlations for speed and radial error. Position, velocity, and position errors can be decoded from the population simple spike firing with considerable accuracy for even the longest predictive (-2000 to -1500 ms) and feedback (1500 to 2000 ms) epochs. Separate analysis of the simple spike firing in the initial hold period preceding tracking shows similar long-range feedforward encoding of the upcoming movement and in the final hold period feedback encoding of the just completed movement, respectively. Complex spike analysis reveals little long-term modulation with behavior. We conclude that Purkinje cell simple spike discharge includes short- and long-range representations of both upcoming and preceding behavior that could underlie cerebellar involvement in error correction, working memory, and sequencing. PMID:28413823

Brazil Fire Characterization and Burn Area Estimation Using the Airborne Infrared Disaster Assessment (AIRDAS) System

NASA Technical Reports Server (NTRS)

Brass, J. A.; Riggan, P. J.; Ambrosia, V. G.; Lockwood, R. N.; Pereira, J. A.; Higgins, R. G.; Peterson, David L. (Technical Monitor)

1995-01-01

Remotely sensed estimations of regional and global emissions from biomass combustion have been used to characterize fire behavior, determine fire intensity, and estimate burn area. Highly temporal, low resolution satellite data have been used to calculate estimates of fire numbers and area burned. These estimates of fire activity and burned area have differed dramatically, resulting in a wide range of predictions on the ecological and environmental impacts of fires. As part of the Brazil/United States Fire Initiative, an aircraft campaign was initiated in 1992 and continued in 1994. This multi-aircraft campaign was designed to assist in the characterization of fire activity, document fire intensity and determine area burned over prescribed, agricultural and wildland fires in the savanna and forests of central Brazil. Using a unique, multispectral scanner (AIRDAS), designed specifically for fire characterization, a variety of fires and burned areas were flown with a high spatial and high thermal resolution scanner. The system was used to measure flame front size, rate of spread, ratio of smoldering to flaming fronts and fire intensity. In addition, long transects were flown to determine the size of burned areas within the cerrado and transitional ecosystems. The authors anticipate that the fire activity and burned area estimates reported here will lead to enhanced information for precise regional trace gas prediction.

Predicting large wildfires across western North America by modeling seasonal variation in soil water balance.

PubMed

Waring, Richard H; Coops, Nicholas C

A lengthening of the fire season, coupled with higher temperatures, increases the probability of fires throughout much of western North America. Although regional variation in the frequency of fires is well established, attempts to predict the occurrence of fire at a spatial resolution <10 km 2 have generally been unsuccessful. We hypothesized that predictions of fires might be improved if depletion of soil water reserves were coupled more directly to maximum leaf area index (LAI max ) and stomatal behavior. In an earlier publication, we used LAI max and a process-based forest growth model to derive and map the maximum available soil water storage capacity (ASW max ) of forested lands in western North America at l km resolution. To map large fires, we used data products acquired from NASA's Moderate Resolution Imaging Spectroradiometers (MODIS) over the period 2000-2009. To establish general relationships that incorporate the major biophysical processes that control evaporation and transpiration as well as the flammability of live and dead trees, we constructed a decision tree model (DT). We analyzed seasonal variation in the relative availability of soil water ( fASW ) for the years 2001, 2004, and 2007, representing respectively, low, moderate, and high rankings of areas burned. For these selected years, the DT predicted where forest fires >1 km occurred and did not occur at ~100,000 randomly located pixels with an average accuracy of 69 %. Extended over the decade, the area predicted burnt varied by as much as 50 %. The DT identified four seasonal combinations, most of which included exhaustion of ASW during the summer as critical; two combinations involving antecedent conditions the previous spring or fall accounted for 86 % of the predicted fires. The approach introduced in this paper can help identify forested areas where management efforts to reduce fire hazards might prove most beneficial.

Thermocouple Probe Orientation Affects Prescribed Fire Behavior Estimation.

PubMed

Coates, T Adam; Chow, Alex T; Hagan, Donald L; Waldrop, Thomas A; Wang, G Geoff; Bridges, William C; Rogers, Mary-Frances; Dozier, James H

2018-01-01

Understanding the relationship between fire intensity and fuel mass is essential information for scientists and forest managers seeking to manage forests using prescribed fires. Peak burning temperature, duration of heating, and area under the temperature profile are fire behavior metrics obtained from thermocouple-datalogger assemblies used to characterize prescribed burns. Despite their recurrent usage in prescribed burn studies, there is no simple protocol established to guide the orientation of thermocouple installation. Our results from dormant and growing season burns in coastal longleaf pine ( Mill.) forests in South Carolina suggest that thermocouples located horizontally at the litter-soil interface record significantly higher estimates of peak burning temperature, duration of heating, and area under the temperature profile than thermocouples extending 28 cm vertically above the litter-soil interface ( < 0.01). Surprisingly, vertical and horizontal estimates of these measures did not show strong correlation with one another ( ≤ 0.14). The horizontal duration of heating values were greater in growing season burns than in dormant season burns ( < 0.01), but the vertical values did not indicate this difference ( = 0.52). Field measures of fuel mass and depth before and after fire showed promise as significant predictive variables ( ≤ 0.05) for the fire behavior metrics. However, all correlation coefficients were less than or equal to = 0.41. Given these findings, we encourage scientists, researchers, and managers to carefully consider thermocouple orientation when investigating fire behavior metrics, as orientation may affect estimates of fire intensity and the distinction of fire treatment effects, particularly in forests with litter-dominated surface fuels. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Detection, Emission Estimation and Risk Prediction of Forest Fires in China Using Satellite Sensors and Simulation Models in the Past Three Decades—An Overview

PubMed Central

Zhang, Jia-Hua; Yao, Feng-Mei; Liu, Cheng; Yang, Li-Min; Boken, Vijendra K.

2011-01-01

Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status. PMID:21909297

Detection, emission estimation and risk prediction of forest fires in China using satellite sensors and simulation models in the past three decades--an overview.

PubMed

Zhang, Jia-Hua; Yao, Feng-Mei; Liu, Cheng; Yang, Li-Min; Boken, Vijendra K

2011-08-01

Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status.

A Role for the Lateral Dorsal Tegmentum in Memory and Decision Neural Circuitry

PubMed Central

Redila, Van; Kinzel, Chantelle; Jo, Yong Sang; Puryear, Corey B.; Mizumori, Sheri J.Y.

2017-01-01

A role for the hippocampus in memory is clear, although the mechanism for its contribution remains a matter of debate. Converging evidence suggests that hippocampus evaluates the extent to which context-defining features of events occur as expected. The consequence of mismatches, or prediction error, signals from hippocampus is discussed in terms of its impact on neural circuitry that evaluates the significance of prediction errors: Ventral tegmental area (VTA) dopamine cells burst fire to rewards or cues that predict rewards (Schultz et al., 1997). Although the lateral dorsal tegmentum (LDTg) importantly controls dopamine cell burst firing (Lodge & Grace, 2006) the behavioral significance of the LDTg control is not known. Therefore, we evaluated LDTg functional activity as rats performed a spatial memory task that generates task-dependent reward codes in VTA (Jo et al., 2013; Puryear et al., 2010) and another VTA afferent, the pedunculopontine nucleus (PPTg, Norton et al., 2011). Reversible inactivation of the LDTg significantly impaired choice accuracy. LDTg neurons coded primarily egocentric information in the form of movement velocity, turning behaviors, and behaviors leading up to expected reward locations. A subset of the velocity-tuned LDTg cells also showed high frequency bursts shortly before or after reward encounters, after which they showed tonic elevated firing during consumption of small, but not large, rewards. Cells that fired before reward encounters showed stronger correlations with velocity as rats moved toward, rather than away from, rewarded sites. LDTg neural activity was more strongly regulated by egocentric behaviors than that observed for PPTg or VTA cells that were recorded by Puryear et al. and Norton et al. While PPTg activity was uniquely sensitive to ongoing sensory input, all three regions encoded reward magnitude (although in different ways), reward expectation, and reward encounters. Only VTA encoded reward prediction errors. LDTg may inform VTA about learned goal-directed movement that reflects the current motivational state, and this in turn may guide VTA determination of expected subjective goal values. When combined it is clear the LDTg and PPTg provide only a portion of the information that dopamine cells need to assess the value of prediction errors, a process that is essential to future adaptive decisions and switches of cognitive (i.e. memorial) strategies and behavioral responses. PMID:24910282

Fire risk in San Diego County, California: A weighted Bayesian model approach

USGS Publications Warehouse

Kolden, Crystal A.; Weigel, Timothy J.

2007-01-01

Fire risk models are widely utilized to mitigate wildfire hazards, but models are often based on expert opinions of less understood fire-ignition and spread processes. In this study, we used an empirically derived weights-of-evidence model to assess what factors produce fire ignitions east of San Diego, California. We created and validated a dynamic model of fire-ignition risk based on land characteristics and existing fire-ignition history data, and predicted ignition risk for a future urbanization scenario. We then combined our empirical ignition-risk model with a fuzzy fire behavior-risk model developed by wildfire experts to create a hybrid model of overall fire risk. We found that roads influence fire ignitions and that future growth will increase risk in new rural development areas. We conclude that empirically derived risk models and hybrid models offer an alternative method to assess current and future fire risk based on management actions.

Effects of using visualization and animation in presentations to communities about forest succession and fire behavior potential

Treesearch

Jane Kapler Smith; Donald E. Zimmerman; Carol Akerelrea; Garrett O' Keefe

2008-01-01

Natural resource managers use a variety of computer-mediated presentation methods to communicate management practices to the public. We explored the effects of using the Stand Visualization System to visualize and animate predictions from the Forest Vegetation Simulator-Fire and Fuels Extension in presentations explaining forest succession (forest growth and change...

The photoload sampling technique: estimating surface fuel loadings from downward-looking photographs of synthetic fuelbeds

Treesearch

Robert E. Keane; Laura J. Dickinson

2007-01-01

Fire managers need better estimates of fuel loading so they can more accurately predict the potential fire behavior and effects of alternative fuel and ecosystem restoration treatments. This report presents a new fuel sampling method, called the photoload sampling technique, to quickly and accurately estimate loadings for six common surface fuel components (1 hr, 10 hr...

Physical characteristics of shrub and conifer fuels for fire behavior models

Treesearch

Jonathan R. Gallacher; Thomas H. Fletcher; Victoria Lansinger; Sydney Hansen; Taylor Ellsworth; David R. Weise

2017-01-01

The physical properties and dimensions of foliage are necessary inputs for some fire spread models. Currently, almost no data exist on these plant characteristics to fill this need. In this report, we measured the physical properties and dimensions of the foliage from 10 live shrub and conifer fuels throughout a 1-year period. We developed models to predict relative...

Jack Pine and Aspen Forest Floors in Northeastern Minnesota

Treesearch

Robert M. Loomis

1977-01-01

Characteristics of upland forest floors under mature jack pine and aspen in northeastern Minnesota were investigated. These fuel measurements were needed as inputs for fire behavior prediction models -- useful for fire management decisions. The forest floor weight averaged 33,955 kg/ha and depth averaged 7.1 cm. Bulk density averaged 17 kg/m3 for the L (litter)...

Prediction and Mitigation of the Effects of Catastrophic Fire on Water Supplies: Science for Risk Reduction and Planning for Future Scenarios

NASA Astrophysics Data System (ADS)

Martin, D. A.; Tindall, J.

2008-12-01

Precipitation falling on forests and grasslands provides much of the water to communities across the United States. The U.S. Forest Service estimates that over 3,400 communities are served by water draining land under its jurisdiction alone. Much of this land is subject to wildland fires, which have been increasing in size and severity in the western United States in response to climatic forcing and increased ignitions from human sources. Runoff from burned landscapes can present a significant risk to municipal and agricultural water supplies from ash, sediment, contaminants from burned structures, and fire-fighting chemicals. Several municipalities, including Denver, Colorado, have experienced both short-term and long-term degradation of their water supplies in the aftermath of fires in watersheds upstream from drinking water reservoirs. Scientific efforts to predict and mitigate the effects of catastrophic fire on water supplies have focused on three areas. The first consists of data collection and carefully designed experiments to understand the change of the hydrologic behavior of burned watersheds in response to rain with different intensities, durations, and trajectories as the watersheds recover. Results from these studies are used to validate models that predict watershed response under different initial conditions constrained by remotely-sensed burn severity, topography, rainfall-intensity recurrence probabilities and other factors. These predictions are the basis for rehabilitation measures applied to the landscape to minimize post-fire runoff and erosion. Efforts are under way to incorporate the chemical effects of ash and fire-fighting compounds in decision-support tools. A second area of scientific focus is the characterization of the chemical and physical properties of ash from wildland fire, including ash from structures consumed by fire. The ash chemistry is correlated to remotely- sensed data, type of vegetation that burned, and the underlying geology. Ash affects the hydraulic properties and behavior of soils in burned watersheds while it still mantles the hillslopes, but it is easily delivered to water bodies by rain and wind as a flush of material that affects water chemistry and properties like turbidity and temperature. A third thrust is to identify watersheds that are critical to the function of municipal water supplies and infrastructure to determine their vulnerability to fire and post-fire effects. This information can be used to prioritize areas for fuel treatments or land management practices to minimize the probability of high severity fire and hence the effects of post-fire runoff. Scientific studies are providing crucial information about such topics as changes in soil erodibility, infiltration and runoff after fire, and the effects of vegetation recovery. Even in watersheds where land management actions are limited by topography or land use designation, such as wilderness areas, knowledge of the potential response of burned areas allows water providers to develop rapid-response and long-term plans based on scientific data and tools. Some climate change models are predicting hotter, drier temperatures in certain areas of the United States and a higher probability of larger, more severe wildfires. These predictions have a direct bearing on the potential risk of impairment of water supplies by post-fire runoff and erosion. In an era when water availability and quality are of utmost importance, careful scientific studies focused on the effects of wildland fire on water supplies will continue to inform public policy and decision making on topics of vulnerability and risk reduction.

Behavior of Steel-Sheathed Shear Walls Subjected to Seismic and Fire Loads.

PubMed

Hoehler, Matthew S; Smith, Christopher M; Hutchinson, Tara C; Wang, Xiang; Meacham, Brian J; Kamath, Praveen

2017-07-01

A series of tests was conducted on six 2.7 m × 3.7 m shear wall specimens consisting of cold-formed steel framing sheathed on one side with sheet steel adhered to gypsum board and on the opposite side with plain gypsum board. The specimens were subjected to various sequences of simulated seismic shear deformation and fire exposure to study the influence of multi-hazard interactions on the lateral load resistance of the walls. The test program was designed to complement a parallel effort at the University of California, San Diego to investigate a six-story building subjected to earthquakes and fires. The test results reported here indicate that the fire exposure caused a shift in the failure mode of the walls from local buckling of the sheet steel in cases without fire exposure, to global buckling of the sheet steel with an accompanying 35 % reduction in lateral load capacity after the wall had been exposed to fire. This behavior appears to be predictable, which is encouraging from the standpoint of residual lateral load capacity under these severe multi-hazard actions.

Analytical approximations of the firing rate of an adaptive exponential integrate-and-fire neuron in the presence of synaptic noise.

PubMed

Hertäg, Loreen; Durstewitz, Daniel; Brunel, Nicolas

2014-01-01

Computational models offer a unique tool for understanding the network-dynamical mechanisms which mediate between physiological and biophysical properties, and behavioral function. A traditional challenge in computational neuroscience is, however, that simple neuronal models which can be studied analytically fail to reproduce the diversity of electrophysiological behaviors seen in real neurons, while detailed neuronal models which do reproduce such diversity are intractable analytically and computationally expensive. A number of intermediate models have been proposed whose aim is to capture the diversity of firing behaviors and spike times of real neurons while entailing the simplest possible mathematical description. One such model is the exponential integrate-and-fire neuron with spike rate adaptation (aEIF) which consists of two differential equations for the membrane potential (V) and an adaptation current (w). Despite its simplicity, it can reproduce a wide variety of physiologically observed spiking patterns, can be fit to physiological recordings quantitatively, and, once done so, is able to predict spike times on traces not used for model fitting. Here we compute the steady-state firing rate of aEIF in the presence of Gaussian synaptic noise, using two approaches. The first approach is based on the 2-dimensional Fokker-Planck equation that describes the (V,w)-probability distribution, which is solved using an expansion in the ratio between the time constants of the two variables. The second is based on the firing rate of the EIF model, which is averaged over the distribution of the w variable. These analytically derived closed-form expressions were tested on simulations from a large variety of model cells quantitatively fitted to in vitro electrophysiological recordings from pyramidal cells and interneurons. Theoretical predictions closely agreed with the firing rate of the simulated cells fed with in-vivo-like synaptic noise.

Irresistible ants: exposure to novel toxic prey increases consumption over multiple temporal scales.

PubMed

Herr, Mark W; Robbins, Travis R; Centi, Alan; Thawley, Christopher J; Langkilde, Tracy

2016-07-01

As species become increasingly exposed to novel challenges, it is critical to understand how evolutionary (i.e., generational) and plastic (i.e., within lifetime) responses work together to determine a species' fate or predict its distribution. The introduction of non-native species imposes novel pressures on the native species that they encounter. Understanding how native species exposed to toxic or distasteful invaders change their feeding behavior can provide insight into their ability to cope with these novel threats as well as broader questions about the evolution of this behavior. We demonstrated that native eastern fence lizards do not avoid consuming invasive fire ants following repeated exposure to this toxic prey. Rather fence lizards increased their consumption of these ants following exposure on three different temporal scales. Lizards ate more fire ants when they were exposed to this toxic prey over successive days. Lizards consumed more fire ants if they had been exposed to fire ants as juveniles 6 months earlier. Finally, lizards from populations exposed to fire ants over multiple generations consumed more fire ants than those from fire ant-free areas. These results suggest that the potentially lethal consumption of fire ants may carry benefits resulting in selection for this behavior, and learning that persists long after initial exposure. Future research on the response of native predators to venomous prey over multiple temporal scales will be valuable in determining the long-term effects of invasion by these novel threats.

High-severity fire: evaluating its key drivers and mapping its probability across western US forests

NASA Astrophysics Data System (ADS)

Parks, Sean A.; Holsinger, Lisa M.; Panunto, Matthew H.; Jolly, W. Matt; Dobrowski, Solomon Z.; Dillon, Gregory K.

2018-04-01

Wildland fire is a critical process in forests of the western United States (US). Variation in fire behavior, which is heavily influenced by fuel loading, terrain, weather, and vegetation type, leads to heterogeneity in fire severity across landscapes. The relative influence of these factors in driving fire severity, however, is poorly understood. Here, we explore the drivers of high-severity fire for forested ecoregions in the western US over the period 2002–2015. Fire severity was quantified using a satellite-inferred index of severity, the relativized burn ratio. For each ecoregion, we used boosted regression trees to model high-severity fire as a function of live fuel, topography, climate, and fire weather. We found that live fuel, on average, was the most important factor driving high-severity fire among ecoregions (average relative influence = 53.1%) and was the most important factor in 14 of 19 ecoregions. Fire weather was the second most important factor among ecoregions (average relative influence = 22.9%) and was the most important factor in five ecoregions. Climate (13.7%) and topography (10.3%) were less influential. We also predicted the probability of high-severity fire, were a fire to occur, using recent (2016) satellite imagery to characterize live fuel for a subset of ecoregions in which the model skill was deemed acceptable (n = 13). These ‘wall-to-wall’ gridded ecoregional maps provide relevant and up-to-date information for scientists and managers who are tasked with managing fuel and wildland fire. Lastly, we provide an example of the predicted likelihood of high-severity fire under moderate and extreme fire weather before and after fuel reduction treatments, thereby demonstrating how our framework and model predictions can potentially serve as a performance metric for land management agencies tasked with reducing hazardous fuel across large landscapes.

Experimental validation of finite element model analysis of a steel frame in simulated post-earthquake fire environments

NASA Astrophysics Data System (ADS)

Huang, Ying; Bevans, W. J.; Xiao, Hai; Zhou, Zhi; Chen, Genda

2012-04-01

During or after an earthquake event, building system often experiences large strains due to shaking effects as observed during recent earthquakes, causing permanent inelastic deformation. In addition to the inelastic deformation induced by the earthquake effect, the post-earthquake fires associated with short fuse of electrical systems and leakage of gas devices can further strain the already damaged structures during the earthquakes, potentially leading to a progressive collapse of buildings. Under these harsh environments, measurements on the involved building by various sensors could only provide limited structural health information. Finite element model analysis, on the other hand, if validated by predesigned experiments, can provide detail structural behavior information of the entire structures. In this paper, a temperature dependent nonlinear 3-D finite element model (FEM) of a one-story steel frame is set up by ABAQUS based on the cited material property of steel from EN 1993-1.2 and AISC manuals. The FEM is validated by testing the modeled steel frame in simulated post-earthquake environments. Comparisons between the FEM analysis and the experimental results show that the FEM predicts the structural behavior of the steel frame in post-earthquake fire conditions reasonably. With experimental validations, the FEM analysis of critical structures could be continuously predicted for structures in these harsh environments for a better assistant to fire fighters in their rescue efforts and save fire victims.

Fire Behavior (FB)

Treesearch

Robert E. Keane

2006-01-01

The Fire Behavior (FB) method is used to describe the behavior of the fire and the ambient weather and fuel conditions that influence the fire behavior. Fire behavior methods are not plot based and are collected by fire event and time-date. In general, the fire behavior data are used to interpret the fire effects documented in the plot-level sampling. Unlike the other...

Quantifying and predicting fuels and the effects of reduction treatments along successional and invasion gradients in sagebrush habitats

USGS Publications Warehouse

Shinneman, Douglas; Pilliod, David S.; Arkle, Robert; Glenn, Nancy F.

2015-01-01

Sagebrush shrubland ecosystems in the Great Basin are prime examples of how altered successional trajectories can create dynamic fuel conditions and, thus, increase uncertainty about fire risk and behavior. Although fire is a natural disturbance in sagebrush, post-fire environments are highly susceptible to conversion to an invasive grass-fire regime (often referred to as a “grass-fire cycle”). After fire, native shrub-steppe plants are often slow to regenerate, whereas nonnative annuals, especially cheatgrass (Bromus tectorum) and medusahead (Taeniatherum caput-medusae), can establish quickly and outcompete native species. Once fire-prone annuals become established, fire occurrences increase, further promoting dominance of nonnative species. The invasive grass-fire regime also alters nutrient and hydrologic cycles, pushing ecosystems beyond ecological thresholds toward steady-state, fire-prone, nonnative communities. These changes affect millions of hectares in the Great Basin and increase fire risk, decrease habitat quality and biodiversity, accelerate soil erosion, and degrade rangeland resources for livestock production. In many sagebrush landscapes, constantly changing plant communities and fuel conditions hinder attempts by land managers to predict and control fire behavior, restore native communities, and provide ecosystem services (e.g., forage production for livestock). We investigated successional and nonnative plant invasion states and associated fuel loads in degraded sagebrush habitat in a focal study area, the Morley Nelson Snake River Birds of Prey National Conservation Area (hereafter the NCA), in the Snake River Plain Ecoregion of southern Idaho. We expanded our inference by comparing our findings to similar data collected throughout seven major land resource areas (MLRAs) across the Great Basin (JFSP Project “Fire Rehabilitation Effectiveness: A Chronosequence Approach for the Great Basin” [09-S-02-1]). 4 We used a combination of field-sampling, experimental treatments, and remotely sensed data to address the following questions: (1) How do fuel loads change along gradients of succession and invasion in sagebrush ecological sites? (2) How do fuel reduction treatments influence fuels in invaded areas formerly dominated by sagebrush? (3) How do fuel loads vary across landscapes and which remote sensing techniques are effective for characterizing them?

Quantifying soil burn severity for hydrologic modeling to assess post-fire effects on sediment delivery

NASA Astrophysics Data System (ADS)

Dobre, Mariana; Brooks, Erin; Lew, Roger; Kolden, Crystal; Quinn, Dylan; Elliot, William; Robichaud, Pete

2017-04-01

Soil erosion is a secondary fire effect with great implications for many ecosystem resources. Depending on the burn severity, topography, and the weather immediately after the fire, soil erosion can impact municipal water supplies, degrade water quality, and reduce reservoirs' storage capacity. Scientists and managers use field and remotely sensed data to quickly assess post-fire burn severity in ecologically-sensitive areas. From these assessments, mitigation activities are implemented to minimize post-fire flood and soil erosion and to facilitate post-fire vegetation recovery. Alternatively, land managers can use fire behavior and spread models (e.g. FlamMap, FARSITE, FOFEM, or CONSUME) to identify sensitive areas a priori, and apply strategies such as fuel reduction treatments to proactively minimize the risk of wildfire spread and increased burn severity. There is a growing interest in linking fire behavior and spread models with hydrology-based soil erosion models to provide site-specific assessment of mitigation treatments on post-fire runoff and erosion. The challenge remains, however, that many burn severity mapping and modeling products quantify vegetation loss rather than measuring soil burn severity. Wildfire burn severity is spatially heterogeneous and depends on the pre-fire vegetation cover, fuel load, topography, and weather. Severities also differ depending on the variable of interest (e.g. soil, vegetation). In the United States, Burned Area Reflectance Classification (BARC) maps, derived from Landsat satellite images, are used as an initial burn severity assessment. BARC maps are classified from either a Normalized Burn Ratio (NBR) or differenced Normalized Burned Ratio (dNBR) scene into four classes (Unburned, Low, Moderate, and High severity). The development of soil burn severity maps requires further manual field validation efforts to transform the BARC maps into a product more applicable for post-fire soil rehabilitation activities. Alternative spectral indices and modeled output approaches may prove better predictors of soil burn severity and hydrologic effects, but these have not yet been assessed in a model framework. In this project we compare field-verified soil burn severity maps to satellite-derived and modeled burn severity maps. We quantify the extent to which there are systematic differences in these mapping products. We then use the Water Erosion Prediction Project (WEPP) hydrologic soil erosion model to assess sediment delivery from these fires using the predicted and observed soil burn severity maps. Finally, we discuss differences in observed and predicted soil burn severity maps and application to watersheds in the Pacific Northwest to estimate post-fire sediment delivery.

Stimulus-Response-Outcome Coding in the Pigeon Nidopallium Caudolaterale

PubMed Central

Starosta, Sarah; Güntürkün, Onur; Stüttgen, Maik C.

2013-01-01

A prerequisite for adaptive goal-directed behavior is that animals constantly evaluate action outcomes and relate them to both their antecedent behavior and to stimuli predictive of reward or non-reward. Here, we investigate whether single neurons in the avian nidopallium caudolaterale (NCL), a multimodal associative forebrain structure and a presumed analogue of mammalian prefrontal cortex, represent information useful for goal-directed behavior. We subjected pigeons to a go-nogo task, in which responding to one visual stimulus (S+) was partially reinforced, responding to another stimulus (S–) was punished, and responding to test stimuli from the same physical dimension (spatial frequency) was inconsequential. The birds responded most intensely to S+, and their response rates decreased monotonically as stimuli became progressively dissimilar to S+; thereby, response rates provided a behavioral index of reward expectancy. We found that many NCL neurons' responses were modulated in the stimulus discrimination phase, the outcome phase, or both. A substantial fraction of neurons increased firing for cues predicting non-reward or decreased firing for cues predicting reward. Interestingly, the same neurons also responded when reward was expected but not delivered, and could thus provide a negative reward prediction error or, alternatively, signal negative value. In addition, many cells showed motor-related response modulation. In summary, NCL neurons represent information about the reward value of specific stimuli, instrumental actions as well as action outcomes, and therefore provide signals useful for adaptive behavior in dynamically changing environments. PMID:23437383

Developing Custom Fire Behavior Fuel Models for Mediterranean Wildland-Urban Interfaces in Southern Italy

NASA Astrophysics Data System (ADS)

Elia, Mario; Lafortezza, Raffaele; Lovreglio, Raffaella; Sanesi, Giovanni

2015-09-01

The dramatic increase of fire hazard in wildland-urban interfaces (WUIs) has required more detailed fuel management programs to preserve ecosystem functions and human settlements. Designing effective fuel treatment strategies allows to achieve goals such as resilient landscapes, fire-adapted communities, and ecosystem response. Therefore, obtaining background information on forest fuel parameters and fuel accumulation patterns has become an important first step in planning fuel management interventions. Site-specific fuel inventory data enhance the accuracy of fuel management planning and help forest managers in fuel management decision-making. We have customized four fuel models for WUIs in southern Italy, starting from forest classes of land-cover use and adopting a hierarchical clustering approach. Furthermore, we provide a prediction of the potential fire behavior of our customized fuel models using FlamMap 5 under different weather conditions. The results suggest that fuel model IIIP (Mediterranean maquis) has the most severe fire potential for the 95th percentile weather conditions and the least severe potential fire behavior for the 85th percentile weather conditions. This study shows that it is possible to create customized fuel models directly from fuel inventory data. This achievement has broad implications for land managers, particularly forest managers of the Mediterranean landscape, an ecosystem that is susceptible not only to wildfires but also to the increasing human population and man-made infrastructures.

Developing Custom Fire Behavior Fuel Models for Mediterranean Wildland-Urban Interfaces in Southern Italy.

PubMed

Elia, Mario; Lafortezza, Raffaele; Lovreglio, Raffaella; Sanesi, Giovanni

2015-09-01

The dramatic increase of fire hazard in wildland-urban interfaces (WUIs) has required more detailed fuel management programs to preserve ecosystem functions and human settlements. Designing effective fuel treatment strategies allows to achieve goals such as resilient landscapes, fire-adapted communities, and ecosystem response. Therefore, obtaining background information on forest fuel parameters and fuel accumulation patterns has become an important first step in planning fuel management interventions. Site-specific fuel inventory data enhance the accuracy of fuel management planning and help forest managers in fuel management decision-making. We have customized four fuel models for WUIs in southern Italy, starting from forest classes of land-cover use and adopting a hierarchical clustering approach. Furthermore, we provide a prediction of the potential fire behavior of our customized fuel models using FlamMap 5 under different weather conditions. The results suggest that fuel model IIIP (Mediterranean maquis) has the most severe fire potential for the 95th percentile weather conditions and the least severe potential fire behavior for the 85th percentile weather conditions. This study shows that it is possible to create customized fuel models directly from fuel inventory data. This achievement has broad implications for land managers, particularly forest managers of the Mediterranean landscape, an ecosystem that is susceptible not only to wildfires but also to the increasing human population and man-made infrastructures.

An instrument for rapid, accurate, determination of fuel moisture content

Treesearch

Stephen S. Sackett

1980-01-01

Moisture contents of dead and living fuels are key variables in fire behavior. Accurate, real-time fuel moisture data are required for prescribed burning and wildfire behavior predictions. The convection oven method has become the standard for direct fuel moisture content determination. Efforts to quantify fuel moisture through indirect methods have not been...

Historical, observed, and modeled wildfire severity in montane forests of the Colorado Front Range.

PubMed

Sherriff, Rosemary L; Platt, Rutherford V; Veblen, Thomas T; Schoennagel, Tania L; Gartner, Meredith H

2014-01-01

Large recent fires in the western U.S. have contributed to a perception that fire exclusion has caused an unprecedented occurrence of uncharacteristically severe fires, particularly in lower elevation dry pine forests. In the absence of long-term fire severity records, it is unknown how short-term trends compare to fire severity prior to 20th century fire exclusion. This study compares historical (i.e. pre-1920) fire severity with observed modern fire severity and modeled potential fire behavior across 564,413 ha of montane forests of the Colorado Front Range. We used forest structure and tree-ring fire history to characterize fire severity at 232 sites and then modeled historical fire-severity across the entire study area using biophysical variables. Eighteen (7.8%) sites were characterized by low-severity fires and 214 (92.2%) by mixed-severity fires (i.e. including moderate- or high-severity fires). Difference in area of historical versus observed low-severity fire within nine recent (post-1999) large fire perimeters was greatest in lower montane forests. Only 16% of the study area recorded a shift from historical low severity to a higher potential for crown fire today. An historical fire regime of more frequent and low-severity fires at low elevations (<2260 m) supports a convergence of management goals of ecological restoration and fire hazard mitigation in those habitats. In contrast, at higher elevations mixed-severity fires were predominant historically and continue to be so today. Thinning treatments at higher elevations of the montane zone will not return the fire regime to an historic low-severity regime, and are of questionable effectiveness in preventing severe wildfires. Based on present-day fuels, predicted fire behavior under extreme fire weather continues to indicate a mixed-severity fire regime throughout most of the montane forest zone. Recent large wildfires in the Front Range are not fundamentally different from similar events that occurred historically under extreme weather conditions.

Historical, Observed, and Modeled Wildfire Severity in Montane Forests of the Colorado Front Range

PubMed Central

Sherriff, Rosemary L.; Platt, Rutherford V.; Veblen, Thomas T.; Schoennagel, Tania L.; Gartner, Meredith H.

2014-01-01

Large recent fires in the western U.S. have contributed to a perception that fire exclusion has caused an unprecedented occurrence of uncharacteristically severe fires, particularly in lower elevation dry pine forests. In the absence of long-term fire severity records, it is unknown how short-term trends compare to fire severity prior to 20th century fire exclusion. This study compares historical (i.e. pre-1920) fire severity with observed modern fire severity and modeled potential fire behavior across 564,413 ha of montane forests of the Colorado Front Range. We used forest structure and tree-ring fire history to characterize fire severity at 232 sites and then modeled historical fire-severity across the entire study area using biophysical variables. Eighteen (7.8%) sites were characterized by low-severity fires and 214 (92.2%) by mixed-severity fires (i.e. including moderate- or high-severity fires). Difference in area of historical versus observed low-severity fire within nine recent (post-1999) large fire perimeters was greatest in lower montane forests. Only 16% of the study area recorded a shift from historical low severity to a higher potential for crown fire today. An historical fire regime of more frequent and low-severity fires at low elevations (<2260 m) supports a convergence of management goals of ecological restoration and fire hazard mitigation in those habitats. In contrast, at higher elevations mixed-severity fires were predominant historically and continue to be so today. Thinning treatments at higher elevations of the montane zone will not return the fire regime to an historic low-severity regime, and are of questionable effectiveness in preventing severe wildfires. Based on present-day fuels, predicted fire behavior under extreme fire weather continues to indicate a mixed-severity fire regime throughout most of the montane forest zone. Recent large wildfires in the Front Range are not fundamentally different from similar events that occurred historically under extreme weather conditions. PMID:25251103

A Simple Model for the Earthquake Cycle Combining Self-Organized Criticality with Critical Point Behavior

NASA Astrophysics Data System (ADS)

Newman, W. I.; Turcotte, D. L.

2002-12-01

We have studied a hybrid model combining the forest-fire model with the site-percolation model in order to better understand the earthquake cycle. We consider a square array of sites. At each time step, a "tree" is dropped on a randomly chosen site and is planted if the site is unoccupied. When a cluster of "trees" spans the site (a percolating cluster), all the trees in the cluster are removed ("burned") in a "fire." The removal of the cluster is analogous to a characteristic earthquake and planting "trees" is analogous to increasing the regional stress. The clusters are analogous to the metastable regions of a fault over which an earthquake rupture can propagate once triggered. We find that the frequency-area statistics of the metastable regions are power-law with a negative exponent of two (as in the forest-fire model). This is analogous to the Gutenberg-Richter distribution of seismicity. This "self-organized critical behavior" can be explained in terms of an inverse cascade of clusters. Individual trees move from small to larger clusters until they are destroyed. This inverse cascade of clusters is self-similar and the power-law distribution of cluster sizes has been shown to have an exponent of two. We have quantified the forecasting of the spanning fires using error diagrams. The assumption that "fires" (earthquakes) are quasi-periodic has moderate predictability. The density of trees gives an improved degree of predictability, while the size of the largest cluster of trees provides a substantial improvement in forecasting a "fire."

Forecasting distribution of numbers of large fires

USGS Publications Warehouse

Eidenshink, Jeffery C.; Preisler, Haiganoush K.; Howard, Stephen; Burgan, Robert E.

2014-01-01

Systems to estimate forest fire potential commonly utilize one or more indexes that relate to expected fire behavior; however they indicate neither the chance that a large fire will occur, nor the expected number of large fires. That is, they do not quantify the probabilistic nature of fire danger. In this work we use large fire occurrence information from the Monitoring Trends in Burn Severity project, and satellite and surface observations of fuel conditions in the form of the Fire Potential Index, to estimate two aspects of fire danger: 1) the probability that a 1 acre ignition will result in a 100+ acre fire, and 2) the probabilities of having at least 1, 2, 3, or 4 large fires within a Predictive Services Area in the forthcoming week. These statistical processes are the main thrust of the paper and are used to produce two daily national forecasts that are available from the U.S. Geological Survey, Earth Resources Observation and Science Center and via the Wildland Fire Assessment System. A validation study of our forecasts for the 2013 fire season demonstrated good agreement between observed and forecasted values.

A model of interval timing by neural integration.

PubMed

Simen, Patrick; Balci, Fuat; de Souza, Laura; Cohen, Jonathan D; Holmes, Philip

2011-06-22

We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes, that correlations among them can be largely cancelled by balancing excitation and inhibition, that neural populations can act as integrators, and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys, and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule's predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior.

AEGIS: a wildfire prevention and management information system

NASA Astrophysics Data System (ADS)

Kalabokidis, Kostas; Ager, Alan; Finney, Mark; Athanasis, Nikos; Palaiologou, Palaiologos; Vasilakos, Christos

2016-03-01

We describe a Web-GIS wildfire prevention and management platform (AEGIS) developed as an integrated and easy-to-use decision support tool to manage wildland fire hazards in Greece (http://aegis.aegean.gr). The AEGIS platform assists with early fire warning, fire planning, fire control and coordination of firefighting forces by providing online access to information that is essential for wildfire management. The system uses a number of spatial and non-spatial data sources to support key system functionalities. Land use/land cover maps were produced by combining field inventory data with high-resolution multispectral satellite images (RapidEye). These data support wildfire simulation tools that allow the users to examine potential fire behavior and hazard with the Minimum Travel Time fire spread algorithm. End-users provide a minimum number of inputs such as fire duration, ignition point and weather information to conduct a fire simulation. AEGIS offers three types of simulations, i.e., single-fire propagation, point-scale calculation of potential fire behavior, and burn probability analysis, similar to the FlamMap fire behavior modeling software. Artificial neural networks (ANNs) were utilized for wildfire ignition risk assessment based on various parameters, training methods, activation functions, pre-processing methods and network structures. The combination of ANNs and expected burned area maps are used to generate integrated output map of fire hazard prediction. The system also incorporates weather information obtained from remote automatic weather stations and weather forecast maps. The system and associated computation algorithms leverage parallel processing techniques (i.e., High Performance Computing and Cloud Computing) that ensure computational power required for real-time application. All AEGIS functionalities are accessible to authorized end-users through a web-based graphical user interface. An innovative smartphone application, AEGIS App, also provides mobile access to the web-based version of the system.

Estimating stand structure using discrete-return lidar: an example from low density, fire prone ponderosa pine forests

USGS Publications Warehouse

Hall, S. A.; Burke, I.C.; Box, D. O.; Kaufmann, M. R.; Stoker, Jason M.

2005-01-01

The ponderosa pine forests of the Colorado Front Range, USA, have historically been subjected to wildfires. Recent large burns have increased public interest in fire behavior and effects, and scientific interest in the carbon consequences of wildfires. Remote sensing techniques can provide spatially explicit estimates of stand structural characteristics. Some of these characteristics can be used as inputs to fire behavior models, increasing our understanding of the effect of fuels on fire behavior. Others provide estimates of carbon stocks, allowing us to quantify the carbon consequences of fire. Our objective was to use discrete-return lidar to estimate such variables, including stand height, total aboveground biomass, foliage biomass, basal area, tree density, canopy base height and canopy bulk density. We developed 39 metrics from the lidar data, and used them in limited combinations in regression models, which we fit to field estimates of the stand structural variables. We used an information–theoretic approach to select the best model for each variable, and to select the subset of lidar metrics with most predictive potential. Observed versus predicted values of stand structure variables were highly correlated, with r2 ranging from 57% to 87%. The most parsimonious linear models for the biomass structure variables, based on a restricted dataset, explained between 35% and 58% of the observed variability. Our results provide us with useful estimates of stand height, total aboveground biomass, foliage biomass and basal area. There is promise for using this sensor to estimate tree density, canopy base height and canopy bulk density, though more research is needed to generate robust relationships. We selected 14 lidar metrics that showed the most potential as predictors of stand structure. We suggest that the focus of future lidar studies should broaden to include low density forests, particularly systems where the vertical structure of the canopy is important, such as fire prone forests.

Development and Validation of a Computational Model for Predicting the Behavior of Plumes from Large Solid Rocket Motors

NASA Technical Reports Server (NTRS)

Wells, Jason E.; Black, David L.; Taylor, Casey L.

2013-01-01

Exhaust plumes from large solid rocket motors fired at ATK's Promontory test site carry particulates to high altitudes and typically produce deposits that fall on regions downwind of the test area. As populations and communities near the test facility grow, ATK has become increasingly concerned about the impact of motor testing on those surrounding communities. To assess the potential impact of motor testing on the community and to identify feasible mitigation strategies, it is essential to have a tool capable of predicting plume behavior downrange of the test stand. A software package, called PlumeTracker, has been developed and validated at ATK for this purpose. The code is a point model that offers a time-dependent, physics-based description of plume transport and precipitation. The code can utilize either measured or forecasted weather data to generate plume predictions. Next-Generation Radar (NEXRAD) data and field observations from twenty-three historical motor test fires at Promontory were collected to test the predictive capability of PlumeTracker. Model predictions for plume trajectories and deposition fields were found to correlate well with the collected dataset.

Fire behavior, fuel treatments, and fire suppression on the Hayman Fire - Part 2: Description and interpretations of fire behavior

Treesearch

Mark A. Finney; Charles W. McHugh; Roberta Bartlette; Kelly Close; Paul Langowski

2003-01-01

This report summarizes the progress of the Hayman Fire, its behavior, and the influence of environmental conditions. Data were obtained from narratives from fire behavior analysts assigned to the fire management teams, discussions with fire management staff, meteorology from local weather stations and Bradshaw and others (2003), photographs, satellite imagery, and...

State of Fire Behavior Models and their Application to Ecosystem and Smoke Management Issues: Special Session Summary Report

DTIC Science & Technology

2013-10-24

advance fire science: (1) fire behavior, (2) ecological effects of fire, (3) carbon accounting , (4) emissions characterization, and (5) fire plume...relates to smoke management. 3) Carbon accounting in forest management and prescribed fire programs (including tradeoffs such as prescribed burning...carbon accounting , 4) emissions characterization and 5) fire plume dispersion. 1) Fire behavior. Better characterization of wildland fire behavior is

Warning signals for eruptive events in spreading fires.

PubMed

Fox, Jerome M; Whitesides, George M

2015-02-24

Spreading fires are noisy (and potentially chaotic) systems in which transitions in dynamics are notoriously difficult to predict. As flames move through spatially heterogeneous environments, sudden shifts in temperature, wind, or topography can generate combustion instabilities, or trigger self-stabilizing feedback loops, that dramatically amplify the intensities and rates with which fires propagate. Such transitions are rarely captured by predictive models of fire behavior and, thus, complicate efforts in fire suppression. This paper describes a simple, remarkably instructive physical model for examining the eruption of small flames into intense, rapidly moving flames stabilized by feedback between wind and fire (i.e., "wind-fire coupling"-a mechanism of feedback particularly relevant to forest fires), and it presents evidence that characteristic patterns in the dynamics of spreading flames indicate when such transitions are likely to occur. In this model system, flames propagate along strips of nitrocellulose with one of two possible modes of propagation: a slow, structured mode, and a fast, unstructured mode sustained by wind-fire coupling. Experimental examination of patterns in dynamics that emerge near bifurcation points suggests that symptoms of critical slowing down (i.e., the slowed recovery of the system from perturbations as it approaches tipping points) warn of impending transitions to the unstructured mode. Findings suggest that slowing responses of spreading flames to sudden changes in environment (e.g., wind, terrain, temperature) may anticipate the onset of intense, feedback-stabilized modes of propagation (e.g., "blowup fires" in forests).

Modeling fire occurrence as a function of landscape

NASA Astrophysics Data System (ADS)

Loboda, T. V.; Carroll, M.; DiMiceli, C.

2011-12-01

Wildland fire is a prominent component of ecosystem functioning worldwide. Nearly all ecosystems experience the impact of naturally occurring or anthropogenically driven fire. Here, we present a spatially explicit and regionally parameterized Fire Occurrence Model (FOM) aimed at developing fire occurrence estimates at landscape and regional scales. The model provides spatially explicit scenarios of fire occurrence based on the available records from fire management agencies, satellite observations, and auxiliary geospatial data sets. Fire occurrence is modeled as a function of the risk of ignition, potential fire behavior, and fire weather using internal regression tree-driven algorithms and empirically established, regionally derived relationships between fire occurrence, fire behavior, and fire weather. The FOM presents a flexible modeling structure with a set of internal globally available default geospatial independent and dependent variables. However, the flexible modeling environment adapts to ingest a variable number, resolution, and content of inputs provided by the user to supplement or replace the default parameters to improve the model's predictive capability. A Southern California FOM instance (SC FOM) was developed using satellite assessments of fire activity from a suite of Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data, Monitoring Trends in Burn Severity fire perimeters, and auxiliary geospatial information including land use and ownership, utilities, transportation routes, and the Remote Automated Weather Station data records. The model was parameterized based on satellite data acquired between 2001 and 2009 and fire management fire perimeters available prior to 2009. SC FOM predictive capabilities were assessed using observed fire occurrence available from the MODIS active fire product during 2010. The results show that SC FOM provides a realistic estimate of fire occurrence at the landscape level: the fraction of area impacted by fire from the total available area within a given value of the Fire Occurrence Index (FOI) increased from 9.e-06 at FOI < 3 to 28.e-06 at 25 < FOI <= 28. Additionally, the model has revealed a new important relationship between fire occurrence, anthropogenic activity, and fire weather. Data analysis has demonstrated that human activity can alter the expected weather/fire occurrence relationships and result in considerable modifications of fire regimes contrary to the assumed ecological parameters. Specifically, between 2001 and 2009 over 50% of total fire impacted area burned during the low fire danger conditions (Canadian Fire Weather Index < 5). These findings and the FOM capabilities offer a new theoretical construct and an advanced tool for assessing the potential impacts of climate changes on fire regimes, particularly within landscapes which are impacted strongly by human activities. Future development of the FOM will focus on ingesting and internal downscaling of climate variables produced by General or Regional Circulation Models to develop scenarios of potential future change in fire occurrence under the influence of projected climate change at the appropriate regional or landscape scales.

[Research progress in post-fire debris flow].

PubMed

Di, Xue-ying; Tao, Yu-zhu

2013-08-01

The occurrence of the secondary disasters of forest fire has significant impacts on the environment quality and human health and safety. Post-fire debris flow is one of the most hazardous secondary disasters of forest fire. To understand the occurrence conditions of post-fire debris flow and to master its occurrence situation are the critical elements in post-fire hazard assessment. From the viewpoints of vegetation, precipitation threshold and debris flow material sources, this paper elaborated the impacts of forest fire on the debris flow, analyzed the geologic and geomorphic conditions, precipitation and slope condition that caused the post-fire debris flow as well as the primary mechanisms of debris-flow initiation caused by shallow landslide or surface runoff, and reviewed the research progress in the prediction and forecast of post-fire debris flow and the related control measures. In the future research, four aspects to be focused on were proposed, i. e., the quantification of the relationships between the fire behaviors and environmental factors and the post-fire debris flow, the quantitative research on the post-fire debris flow initiation and movement processes, the mechanistic model of post-fire debris flow, and the rapid and efficient control countermeasures of post-fire debris flow.

Numerical investigation of aggregated fuel spatial pattern impacts on fire behavior

DOE PAGES

Parsons, Russell A.; Linn, Rodman Ray; Pimont, Francois; ...

2017-06-18

Here, landscape heterogeneity shapes species distributions, interactions, and fluctuations. Historically, in dry forest ecosystems, low canopy cover and heterogeneous fuel patterns often moderated disturbances like fire. Over the last century, however, increases in canopy cover and more homogeneous patterns have contributed to altered fire regimes with higher fire severity. Fire management strategies emphasize increasing within-stand heterogeneity with aggregated fuel patterns to alter potential fire behavior. Yet, little is known about how such patterns may affect fire behavior, or how sensitive fire behavior changes from fuel patterns are to winds and canopy cover. Here, we used a physics-based fire behavior model,more » FIRETEC, to explore the impacts of spatially aggregated fuel patterns on the mean and variability of stand-level fire behavior, and to test sensitivity of these effects to wind and canopy cover. Qualitative and quantitative approaches suggest that spatial fuel patterns can significantly affect fire behavior. Based on our results we propose three hypotheses: (1) aggregated spatial fuel patterns primarily affect fire behavior by increasing variability; (2) this variability should increase with spatial scale of aggregation; and (3) fire behavior sensitivity to spatial pattern effects should be more pronounced under moderate wind and fuel conditions.« less

Numerical investigation of aggregated fuel spatial pattern impacts on fire behavior

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parsons, Russell A.; Linn, Rodman Ray; Pimont, Francois

Here, landscape heterogeneity shapes species distributions, interactions, and fluctuations. Historically, in dry forest ecosystems, low canopy cover and heterogeneous fuel patterns often moderated disturbances like fire. Over the last century, however, increases in canopy cover and more homogeneous patterns have contributed to altered fire regimes with higher fire severity. Fire management strategies emphasize increasing within-stand heterogeneity with aggregated fuel patterns to alter potential fire behavior. Yet, little is known about how such patterns may affect fire behavior, or how sensitive fire behavior changes from fuel patterns are to winds and canopy cover. Here, we used a physics-based fire behavior model,more » FIRETEC, to explore the impacts of spatially aggregated fuel patterns on the mean and variability of stand-level fire behavior, and to test sensitivity of these effects to wind and canopy cover. Qualitative and quantitative approaches suggest that spatial fuel patterns can significantly affect fire behavior. Based on our results we propose three hypotheses: (1) aggregated spatial fuel patterns primarily affect fire behavior by increasing variability; (2) this variability should increase with spatial scale of aggregation; and (3) fire behavior sensitivity to spatial pattern effects should be more pronounced under moderate wind and fuel conditions.« less

How to generate and interpret fire characteristics charts for surface and crown fire behavior

Treesearch

Patricia L. Andrews; Faith Ann Heinsch; Luke Schelvan

2011-01-01

A fire characteristics chart is a graph that presents primary related fire behavior characteristics-rate of spread, flame length, fireline intensity, and heat per unit area. It helps communicate and interpret modeled or observed fire behavior. The Fire Characteristics Chart computer program plots either observed fire behavior or values that have been calculated by...

Potential changes in forest composition could reduce impacts of climate change on boreal wildfires.

PubMed

Terrier, Aurélie; Girardin, Martin P; Périé, Catherine; Legendre, Pierre; Bergeron, Yves

2013-01-01

There is general consensus that wildfires in boreal forests will increase throughout this century in response to more severe and frequent drought conditions induced by climate change. However, prediction models generally assume that the vegetation component will remain static over the next few decades. As deciduous species are less flammable than conifer species, it is reasonable to believe that a potential expansion of deciduous species in boreal forests, either occurring naturally or through landscape management, could offset some of the impacts of climate change on the occurrence of boreal wildfires. The objective of this study was to determine the potential of this offsetting effect through a simulation experiment conducted in eastern boreal North America. Predictions of future fire activity were made using multivariate adaptive regression splines (MARS) with fire behavior indices and ecological niche models as predictor variables so as to take into account the effects of changing climate and tree distribution on fire activity. A regional climate model (RCM) was used for predictions of future fire risk conditions. The experiment was conducted under two tree dispersal scenarios: the status quo scenario, in which the distribution of forest types does not differ from the present one, and the unlimited dispersal scenario, which allows forest types to expand their range to fully occupy their climatic niche. Our results show that future warming will create climate conditions that are more prone to fire occurrence. However, unlimited dispersal of southern restricted deciduous species could reduce the impact of climate change on future fire occurrence. Hence, the use of deciduous species could be a good option for an efficient strategic fire mitigation strategy aimed at reducing fire Propagation in coniferous landscapes and increasing public safety in remote populated areas of eastern boreal Canada under climate change.

Warning signals for eruptive events in spreading fires

PubMed Central

Fox, Jerome M.; Whitesides, George M.

2015-01-01

Spreading fires are noisy (and potentially chaotic) systems in which transitions in dynamics are notoriously difficult to predict. As flames move through spatially heterogeneous environments, sudden shifts in temperature, wind, or topography can generate combustion instabilities, or trigger self-stabilizing feedback loops, that dramatically amplify the intensities and rates with which fires propagate. Such transitions are rarely captured by predictive models of fire behavior and, thus, complicate efforts in fire suppression. This paper describes a simple, remarkably instructive physical model for examining the eruption of small flames into intense, rapidly moving flames stabilized by feedback between wind and fire (i.e., “wind–fire coupling”—a mechanism of feedback particularly relevant to forest fires), and it presents evidence that characteristic patterns in the dynamics of spreading flames indicate when such transitions are likely to occur. In this model system, flames propagate along strips of nitrocellulose with one of two possible modes of propagation: a slow, structured mode, and a fast, unstructured mode sustained by wind–fire coupling. Experimental examination of patterns in dynamics that emerge near bifurcation points suggests that symptoms of critical slowing down (i.e., the slowed recovery of the system from perturbations as it approaches tipping points) warn of impending transitions to the unstructured mode. Findings suggest that slowing responses of spreading flames to sudden changes in environment (e.g., wind, terrain, temperature) may anticipate the onset of intense, feedback-stabilized modes of propagation (e.g., “blowup fires” in forests). PMID:25675491

Web service tools in the era of forest fire management and elimination

NASA Astrophysics Data System (ADS)

Poursanidis, Dimitris; Kochilakis, Giorgos; Chrysoulakis, Nektarios; Varella, Vasiliki; Kotroni, Vassiliki; Eftychidis, Giorgos; Lagouvardos, Kostas

2014-10-01

Wildfires in forests and forested areas in South Europe, North America, Central Asia and Australia are a diachronic threat with crucial ecological, economic and social impacts. Last decade the frequency, the magnitude and the intensity of fires have increased even more because of the climate change. An efficient response to such disasters requires an effective planning, with an early detection system of the ignition area and an accurate prediction of fire propagation to support the rapid response mechanisms. For this reason, information systems able to predict and visualize the behavior of fires, are valuable tools for fire fighting. Such systems, able also to perform simulations that evaluate the fire development scenarios, based on weather conditions, become valuable Decision Support Tools for fire mitigation planning. A Web-based Information System (WIS) developed in the framework of the FLIRE (Floods and fire risk assessment and management) project, a LIFE+ co-funded by the European Commission research, is presented in this study. The FLIRE WIS use forest fuel maps which have been developed by using generalized fuel maps, satellite data and in-situ observations. Furthermore, it leverages data from meteorological stations and weather forecast from numerical models to feed the fire propagation model with the necessary for the simulations inputs and to visualize the model's results for user defined time periods and steps. The user has real-time access to FLIRE WIS via any web browser from any platform (PC, Laptop, Tablet, Smartphone).

A model of interval timing by neural integration

PubMed Central

Simen, Patrick; Balci, Fuat; deSouza, Laura; Cohen, Jonathan D.; Holmes, Philip

2011-01-01

We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes; that correlations among them can be largely cancelled by balancing excitation and inhibition; that neural populations can act as integrators; and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule’s predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior. PMID:21697374

Simulating statistics of lightning-induced and man made fires

NASA Astrophysics Data System (ADS)

Krenn, R.; Hergarten, S.

2009-04-01

The frequency-area distributions of forest fires show power-law behavior with scaling exponents α in a quite narrow range, relating wildfire research to the theoretical framework of self-organized criticality. Examples of self-organized critical behavior can be found in computer simulations of simple cellular automata. The established self-organized critical Drossel-Schwabl forest fire model (DS-FFM) is one of the most widespread models in this context. Despite its qualitative agreement with event-size statistics from nature, its applicability is still questioned. Apart from general concerns that the DS-FFM apparently oversimplifies the complex nature of forest dynamics, it significantly overestimates the frequency of large fires. We present a straightforward modification of the model rules that increases the scaling exponent α by approximately 1•3 and brings the simulated event-size statistics close to those observed in nature. In addition, combined simulations of both the original and the modified model predict a dependence of the overall distribution on the ratio of lightning induced and man made fires as well as a difference between their respective event-size statistics. The increase of the scaling exponent with decreasing lightning probability as well as the splitting of the partial distributions are confirmed by the analysis of the Canadian Large Fire Database. As a consequence, lightning induced and man made forest fires cannot be treated separately in wildfire modeling, hazard assessment and forest management.

Validation of coupled atmosphere-fire behavior models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bossert, J.E.; Reisner, J.M.; Linn, R.R.

1998-12-31

Recent advances in numerical modeling and computer power have made it feasible to simulate the dynamical interaction and feedback between the heat and turbulence induced by wildfires and the local atmospheric wind and temperature fields. At Los Alamos National Laboratory, the authors have developed a modeling system that includes this interaction by coupling a high resolution atmospheric dynamics model, HIGRAD, with a fire behavior model, BEHAVE, to predict the spread of wildfires. The HIGRAD/BEHAVE model is run at very high resolution to properly resolve the fire/atmosphere interaction. At present, these coupled wildfire model simulations are computationally intensive. The additional complexitymore » of these models require sophisticated methods for assuring their reliability in real world applications. With this in mind, a substantial part of the research effort is directed at model validation. Several instrumented prescribed fires have been conducted with multi-agency support and participation from chaparral, marsh, and scrub environments in coastal areas of Florida and inland California. In this paper, the authors first describe the data required to initialize the components of the wildfire modeling system. Then they present results from one of the Florida fires, and discuss a strategy for further testing and improvement of coupled weather/wildfire models.« less

Photo series for quantifying fuels and assessing fire risk in giant sequoia groves. Forest Service general technical report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weise, D.R.; Gelobter, A.; Haase, S.M.

1997-03-01

Fuels and stand inventory data are presented for giant sequoia by using 18 different photos located in giant sequoia/mixed conifer stands in the Sierra Nevada of California. Total fuel loading ranges from 7 to 72 tons/acre. The stands have been subjected to a variety of disturbances including timbers harvesting, wildfire, prescribed fire, and recreational use. Fire behavior predictions were made by using 10th, 50th, and 90th percentile weather conditions and the inventoried fuels information. The long-term visual impacts of the various management activities can also be partially assessed with this photo series.

Compatible above-ground biomass equations and carbon stock estimation for small diameter Turkish pine (Pinus brutia Ten.).

PubMed

Sakici, Oytun Emre; Kucuk, Omer; Ashraf, Muhammad Irfan

2018-04-15

Small trees and saplings are important for forest management, carbon stock estimation, ecological modeling, and fire management planning. Turkish pine (Pinus brutia Ten.) is a common coniferous species and comprises 25.1% of total forest area of Turkey. Turkish pine is also important due to its flammable fuel characteristics. In this study, compatible above-ground biomass equations were developed to predict needle, branch, stem wood, and above-ground total biomass, and carbon stock assessment was also described for Turkish pine which is smaller than 8 cm diameter at breast height or shorter than breast height. Compatible biomass equations are useful for biomass prediction of small diameter individuals of Turkish pine. These equations will also be helpful in determining fire behavior characteristics and calculating their carbon stock. Overall, present study will be useful for developing ecological models, forest management plans, silvicultural plans, and fire management plans.

Early Detection of Lightning Caused Wildfires and Prediction of Wildfire Behavior through Energy Distribution, Atmospherics, Geophysics, the Sun's Azimuth, and Topology

NASA Astrophysics Data System (ADS)

Giesige, C.; Nava, E.

2016-12-01

In the midst of a changing climate we have seen extremes in weather events: lightning, wildfires, hurricanes, tornadoes, and earthquakes. All of these ride on an imbalance of magnetic and electrical distribution about the earth including what goes on from the atmospheric and geophysic levels. There is relevance to the important role the sun plays in developing and feeding of the extreme weather events along with the sun's role helping to create a separation of charges on earth furthering climactic extremes. Focusing attention in North America and on how the sun, atmospheric and geophysic winds come together producing lightning events, there are connections between energy distribution in the environment, lightning caused wildfires, and extreme wildfire behavior. Lightning caused wildfires and extreme fire behavior have become enhanced with the changing climate conditions. Even with strong developments in wildfire science, there remains a lack in full understanding of connections that create a lightning caused wildfire event and lack of monitoring advancements in predicting extreme fire behavior. Several connections have been made in our research allowing us to connect multiple facets of the environment in regards to electric and magnetic influences on wildfires. Among them include: irradiance, winds, pressure systems, humidity, and topology. The connections can be made to develop better detection systems of wildfires, establish with more accuracy areas of highest risk for wildfire and extreme wildfire behavior, and prediction of wildfire behavior. A platform found within the environment can also lead to further understanding and monitoring of other extreme weather events in the future.

Closing the wildland fire heat budget - measurements in the field at intermediate and operational scales

NASA Astrophysics Data System (ADS)

Dickinson, M.; Kremens, R.; Bova, A. S.

2012-12-01

Closing the wildland fire heat budget involves characterizing the heat source and energy dissipation across the range of variability in fuels and fire behavior. Meeting this challenge will lay the foundation for predicting direct ecological effects of fires and fire-atmosphere coupling. Here, we focus on the relationships between the fire radiation field, as measured from the zenith, fuel consumption, and the behavior of spreading flame fronts. Experiments were conducted in 8 m x 8 m outdoor plots using pre-conditioned wildland fuels characteristic of mixed-oak forests of the eastern United States. Using dual-band radiometers with a field of view of about 18.5 m^2 at a height of 4.2 m, we found a near-linear increase in fire radiative energy density (FRED) over a range of fuel consumption between 0.15 kg m^-2 to 3.25 kg m^-2. Using an integrated heat budget, we estimate that the fraction of total theoretical combustion energy density radiated from the plot averaged 0.17, the fraction of latent energy transported in the plume averaged 0.08, and the fraction accounted for by the combination of fire convective energy transport and soil heating averaged 0.72. Future work will require, at minimum, instantaneous and time-integrated estimates of energy transported by radiation, convection, and soil heating across a range of fuels. We introduce the Rx-CADRE project through which such measurements are being made.

Estimation of Scale Deposition in the Water Walls of an Operating Indian Coal Fired Boiler: Predictive Modeling Approach Using Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Kumari, Amrita; Das, Suchandan Kumar; Srivastava, Prem Kumar

2016-04-01

Application of computational intelligence for predicting industrial processes has been in extensive use in various industrial sectors including power sector industry. An ANN model using multi-layer perceptron philosophy has been proposed in this paper to predict the deposition behaviors of oxide scale on waterwall tubes of a coal fired boiler. The input parameters comprises of boiler water chemistry and associated operating parameters, such as, pH, alkalinity, total dissolved solids, specific conductivity, iron and dissolved oxygen concentration of the feed water and local heat flux on boiler tube. An efficient gradient based network optimization algorithm has been employed to minimize neural predictions errors. Effects of heat flux, iron content, pH and the concentrations of total dissolved solids in feed water and other operating variables on the scale deposition behavior have been studied. It has been observed that heat flux, iron content and pH of the feed water have a relatively prime influence on the rate of oxide scale deposition in water walls of an Indian boiler. Reasonably good agreement between ANN model predictions and the measured values of oxide scale deposition rate has been observed which is corroborated by the regression fit between these values.

The role of fuels for understanding fire behavior and fire effects

Treesearch

E. Louise Loudermilk; J. Kevin Hiers; Joseph J. O' Brien

2018-01-01

Fire ecology, which has emerged as a critical discipline, links the complex interactions that occur between fire regimes and ecosystems. The ecology of fuels, a first principle in fire ecology, identifies feedbacks between vegetation and fire behavior-a cyclic process that starts with fuels influencing fire behavior, which in turn governs patterns of postfire...

Warning signals for eruptive events in spreading fires

DOE PAGES

Fox, Jerome M.; Whitesides, George M.

2015-02-09

Spreading fires are noisy (and potentially chaotic) systems in which transitions in dynamics are notoriously difficult to predict. As flames move through spatially heterogeneous environments, sudden shifts in temperature, wind, or topography can generate combustion instabilities, or trigger self-stabilizing feedback loops, that dramatically amplify the intensities and rates with which fires propagate. Such transitions are rarely captured by predictive models of fire behavior and, thus, complicate efforts in fire suppression. This study describes a simple, remarkably instructive physical model for examining the eruption of small flames into intense, rapidly moving flames stabilized by feedback between wind and fire (i.e., “wind–firemore » coupling”—a mechanism of feedback particularly relevant to forest fires), and it presents evidence that characteristic patterns in the dynamics of spreading flames indicate when such transitions are likely to occur. Here, in this model system, flames propagate along strips of nitrocellulose with one of two possible modes of propagation: a slow, structured mode, and a fast, unstructured mode sustained by wind–fire coupling. Experimental examination of patterns in dynamics that emerge near bifurcation points suggests that symptoms of critical slowing down (i.e., the slowed recovery of the system from perturbations as it approaches tipping points) warn of impending transitions to the unstructured mode. Lastly, findings suggest that slowing responses of spreading flames to sudden changes in environment (e.g., wind, terrain, temperature) may anticipate the onset of intense, feedback-stabilized modes of propagation (e.g., “blowup fires” in forests).« less

Warning signals for eruptive events in spreading fires

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fox, Jerome M.; Whitesides, George M.

Spreading fires are noisy (and potentially chaotic) systems in which transitions in dynamics are notoriously difficult to predict. As flames move through spatially heterogeneous environments, sudden shifts in temperature, wind, or topography can generate combustion instabilities, or trigger self-stabilizing feedback loops, that dramatically amplify the intensities and rates with which fires propagate. Such transitions are rarely captured by predictive models of fire behavior and, thus, complicate efforts in fire suppression. This study describes a simple, remarkably instructive physical model for examining the eruption of small flames into intense, rapidly moving flames stabilized by feedback between wind and fire (i.e., “wind–firemore » coupling”—a mechanism of feedback particularly relevant to forest fires), and it presents evidence that characteristic patterns in the dynamics of spreading flames indicate when such transitions are likely to occur. Here, in this model system, flames propagate along strips of nitrocellulose with one of two possible modes of propagation: a slow, structured mode, and a fast, unstructured mode sustained by wind–fire coupling. Experimental examination of patterns in dynamics that emerge near bifurcation points suggests that symptoms of critical slowing down (i.e., the slowed recovery of the system from perturbations as it approaches tipping points) warn of impending transitions to the unstructured mode. Lastly, findings suggest that slowing responses of spreading flames to sudden changes in environment (e.g., wind, terrain, temperature) may anticipate the onset of intense, feedback-stabilized modes of propagation (e.g., “blowup fires” in forests).« less

Aids to determining fuel models for estimating fire behavior

Treesearch

Hal E. Anderson

1982-01-01

Presents photographs of wildland vegetation appropriate for the 13 fuel models used in mathematical models of fire behavior. Fuel model descriptions include fire behavior associated with each fuel and its physical characteristics. A similarity chart cross-references the 13 fire behavior fuel models to the 20 fuel models used in the National Fire Danger Rating System....

Risk of fire occurrence in arid and semi-arid ecosystems of Iran: an investigation using Bayesian belief networks.

PubMed

Bashari, Hossein; Naghipour, Ali Asghar; Khajeddin, Seyed Jamaleddin; Sangoony, Hamed; Tahmasebi, Pejman

2016-09-01

Identifying areas that have a high risk of burning is a main component of fire management planning. Although the available tools can predict the fire risks, these are poor in accommodating uncertainties in their predictions. In this study, we accommodated uncertainty in wildfire prediction using Bayesian belief networks (BBNs). An influence diagram was developed to identify the factors influencing wildfire in arid and semi-arid areas of Iran, and it was populated with probabilities to produce a BBNs model. The behavior of the model was tested using scenario and sensitivity analysis. Land cover/use, mean annual rainfall, mean annual temperature, elevation, and livestock density were recognized as the main variables determining wildfire occurrence. The produced model had good accuracy as its ROC area under the curve was 0.986. The model could be applied in both predictive and diagnostic analysis for answering "what if" and "how" questions. The probabilistic relationships within the model can be updated over time using observation and monitoring data. The wildfire BBN model may be updated as new knowledge emerges; hence, it can be used to support the process of adaptive management.

Climatic and weather factors affecting fire occurrence and behavior

Treesearch

Randall P. Benson; John O. Roads; David R. Weise

2009-01-01

Weather and climate have a profound influence on wildland fire ignition potential, fire behavior, and fire severity. Local weather and climate are affected by large-scale patterns of winds over the hemispheres that predispose wildland fuels to fire. The characteristics of wildland fuels, especially the moisture content, ultimately determine fire behavior and the impact...

Fire Behavior System for the Full Range of Fire Management Needs

Treesearch

Richard C. Rothermel; Patricia L. Andrews

1987-01-01

An "integrated fire behavior/fire danger rating system" should be "seamless" to avoid requiring choices among alternate, independent systems. Descriptions of fuel moisture, fuels, and fire behavior should be standardized, permitting information to flow easily through the spectrum of fire management needs. The level of resolution depends on the...

Integrating remote sensing and terrain data in forest fire modeling

NASA Astrophysics Data System (ADS)

Medler, Michael Johns

Forest fire policies are changing. Managers now face conflicting imperatives to re-establish pre-suppression fire regimes, while simultaneously preventing resource destruction. They must, therefore, understand the spatial patterns of fires. Geographers can facilitate this understanding by developing new techniques for mapping fire behavior. This dissertation develops such techniques for mapping recent fires and using these maps to calibrate models of potential fire hazards. In so doing, it features techniques that strive to address the inherent complexity of modeling the combinations of variables found in most ecological systems. Image processing techniques were used to stratify the elements of terrain, slope, elevation, and aspect. These stratification images were used to assure sample placement considered the role of terrain in fire behavior. Examination of multiple stratification images indicated samples were placed representatively across a controlled range of scales. The incorporation of terrain data also improved preliminary fire hazard classification accuracy by 40%, compared with remotely sensed data alone. A Kauth-Thomas transformation (KT) of pre-fire and post-fire Thematic Mapper (TM) remotely sensed data produced brightness, greenness, and wetness images. Image subtraction indicated fire induced change in brightness, greenness, and wetness. Field data guided a fuzzy classification of these change images. Because fuzzy classification can characterize a continuum of a phenomena where discrete classification may produce artificial borders, fuzzy classification was found to offer a range of fire severity information unavailable with discrete classification. These mapped fire patterns were used to calibrate a model of fire hazards for the entire mountain range. Pre-fire TM, and a digital elevation model produced a set of co-registered images. Training statistics were developed from 30 polygons associated with the previously mapped fire severity. Fuzzy classifications of potential burn patterns were produced from these images. Observed field data values were displayed over the hazard imagery to indicate the effectiveness of the model. Areas that burned without suppression during maximum fire severity are predicted best. Areas with widely spaced trees and grassy understory appear to be misrepresented, perhaps as a consequence of inaccuracies in the initial fire mapping.

Predicting Fire Severity and Hydrogeomorphic Effects for Wildland Fire Decision Support

NASA Astrophysics Data System (ADS)

Hyde, K.; Woods, S. W.; Calkin, D.; Ryan, K.; Keane, R.

2007-12-01

The Wildland Fire Decision Support System (WFDSS) uses the Fire Spread Probability (FSPro) model to predict the spatial extent of fire, and to assess values-at-risk within probable spread zones. This information is used to support Appropriate Management Response (AMR), which involves decision making regarding fire-fighter deployment, fire suppression requirements, and identification of areas where fire may be safely permitted to take its course. Current WFDSS assessments are generally limited to a binary prediction of whether or not a fire will reach a given location and an assessment of the infrastructure which may be damaged or destroyed by fire. However, an emerging challenge is to expand the capabilities of WFDSS so that it also estimates the probable fire severity, and hence the effect on soil, vegetation and on hydrologic and geomorphic processes such as runoff and soil erosion. We present a conceptual framework within which derivatives of predictive fire modelling are used to predict impacts upon vegetation and soil, from which fire severity and probable post-fire watershed response can be inferred, before a fire actually occurs. Fire severity predictions are validated using Burned Area Reflectance Classification imagery. Recent tests indicate that satellite derived BARC images are a simple and effective means to predict post-fire erosion response based on relative vegetation disturbance. A fire severity prediction which reasonably approximates a BARC image may therefore be used to assess post-fire erosion and flood potential before fire reaches an area. This information may provide a new avenue of reliable support for fire management decisions.

Developing custom fire behavior fuel models from ecologically complex fuel structures for upper Atlantic Coastal Plain forests

Treesearch

Bernard R. Parresol; Joe H. Scott; Anne Andreu; Susan Prichard; Laurie Kurth

2012-01-01

Currently geospatial fire behavior analyses are performed with an array of fire behavior modeling systems such as FARSITE, FlamMap, and the Large Fire Simulation System. These systems currently require standard or customized surface fire behavior fuel models as inputs that are often assigned through remote sensing information. The ability to handle hundreds or...

Changing Weather Extremes Call for Early Warning of Potential for Catastrophic Fire

NASA Astrophysics Data System (ADS)

Boer, Matthias M.; Nolan, Rachael H.; Resco De Dios, Víctor; Clarke, Hamish; Price, Owen F.; Bradstock, Ross A.

2017-12-01

Changing frequencies of extreme weather events and shifting fire seasons call for enhanced capability to forecast where and when forested landscapes switch from a nonflammable (i.e., wet fuel) state to the highly flammable (i.e., dry fuel) state required for catastrophic forest fires. Current forest fire danger indices used in Europe, North America, and Australia rate potential fire behavior by combining numerical indices of fuel moisture content, potential rate of fire spread, and fire intensity. These numerical rating systems lack the physical basis required to reliably quantify forest flammability outside the environments of their development or under novel climate conditions. Here, we argue that exceedance of critical forest flammability thresholds is a prerequisite for major forest fires and therefore early warning systems should be based on a reliable prediction of fuel moisture content plus a regionally calibrated model of how forest fire activity responds to variation in fuel moisture content. We demonstrate the potential of this approach through a case study in Portugal. We use a physically based fuel moisture model with historical weather and fire records to identify critical fuel moisture thresholds for forest fire activity and then show that the catastrophic June 2017 forest fires in central Portugal erupted shortly after fuels in the region dried out to historically unprecedented levels.

Modeling the disturbance of vegetation by fire in the boreal forest

NASA Astrophysics Data System (ADS)

Crevoisier, C.; Shevliakova, E.; Gloor, M.; Wirth, C.

2006-12-01

Boreal regions are important for the global carbon cycle because it is the largest forested area on earth and there are large belowground carbon pools (~1000 PgC). It is also a region where largest warming trends on the globe over the last decades have been observed and changes of the land ecosystems have already started. A major factor that determines the structure and carbon dynamics of the boreal forest is fire. As fire frequency depends strongly on climate, increased fire occurrence and related losses to the atmosphere are likely, and have already been reported. In order to predict with more confidence the occurrence and effect of fire on forest ecosystems in the boreal region, we have developed a fire model that takes advantage of the large on-ground, remote sensing and climate data from Canada, Alaska and Siberia. This prognostic model estimates the monthly burned area in a grid cell of 2 by 2.5 degrees, from four climate (air temperature, air relative humidity, precipitation and soil water content) and one human-related (road density) variables. Parameters are estimated using a Markov Chain Monte Carlo method applied to a dataset of observed burned area for Canada. The model is able to reproduce the seasonality of fire, the interannual variability, as well as the location of fire events, not only for Canada (on which data the model is based), but also for Siberia and Alaska, for which the results compare well with remote sensing observation, and are in the range of various current estimations of burned area. The fire model is being implemented in LM3V, the new vegetation model of GFDL earth system model, in order to make prediction of future fire behavior in boreal regions, and the related disturbance of the vegetation and carbon emissions.

Acute ethanol effects on neural encoding of reward size and delay in the nucleus accumbens

PubMed Central

Gutman, Andrea L.

2016-01-01

Acute ethanol administration can cause impulsivity, resulting in increased preference for immediately available rewards over delayed but more valuable alternatives. The manner in which reward size and delay are represented in neural firing is not fully understood, and very little is known about ethanol effects on this encoding. To address this issue, we used in vivo electrophysiology to characterize neural firing in the core of the nucleus accumbens (NAcc) in rats responding for rewards that varied in size or delay after vehicle or ethanol administration. The NAcc is a central element in the circuit that governs decision-making and importantly, promotes choice of delayed rewards. We found that NAcc firing in response to reward-predictive cues encoded anticipated reward value after vehicle administration, but ethanol administration disrupted this encoding, resulting in a loss of discrimination between immediate and delayed rewards in cue-evoked neural responses. In addition, NAcc firing occurring at the time of the operant response (lever pressing) was inversely correlated with behavioral response latency, such that increased firing rates were associated with decreased latencies to lever press. Ethanol administration selectively attenuated this lever press-evoked firing when delayed but not immediate rewards were expected. These effects on neural firing were accompanied by increased behavioral latencies to respond for delayed rewards. Our results suggest that ethanol effects on NAcc cue- and lever press-evoked encoding may contribute to ethanol-induced impulsivity. PMID:27169507

Introduction-2nd Fire Behavior and Fuels Conference: The fire environment-innovations, management, and policy

Treesearch

Wayne Cook; Bret W. Butler

2007-01-01

The 2nd Fire Behavior and Fuels Conference: Fire Environment -- Innovations, Management and Policy was held in Destin, FL, March 26-30, 2007. Following on the success of the 1st Fire Behavior and Fuels Conference, this conference was initiated in response to the needs of the National Wildfire Coordinating Group -- Fire Environment Working Team.

A comparison of geospatially modeled fire behavior and fire management utility of three data sources in the southeastern United States

Treesearch

LaWen T. Hollingsworth; Laurie L. Kurth; Bernard R. Parresol; Roger D. Ottmar; Susan J. Prichard

2012-01-01

Landscape-scale fire behavior analyses are important to inform decisions on resource management projects that meet land management objectives and protect values from adverse consequences of fire. Deterministic and probabilistic geospatial fire behavior analyses are conducted with various modeling systems including FARSITE, FlamMap, FSPro, and Large Fire Simulation...

Wildfire simulation using LES with synthetic-velocity SGS models

NASA Astrophysics Data System (ADS)

McDonough, J. M.; Tang, Tingting

2016-11-01

Wildland fires are becoming more prevalent and intense worldwide as climate change leads to warmer, drier conditions; and large-eddy simulation (LES) is receiving increasing attention for fire spread predictions as computing power continues to improve (see, e.g.,). We report results from wildfire simulations over general terrain employing implicit LES for solution of the incompressible Navier-Stokes (N.-S.) and thermal energy equations with Boussinesq approximation, altered with Darcy, Forchheimer and Brinkman extensions, to represent forested regions as porous media with varying (in both space and time) porosity and permeability. We focus on subgrid-scale (SGS) behaviors computed with a synthetic-velocity model, a discrete dynamical system, based on the poor man's N.-S. equations and investigate the ability of this model to produce fire whirls (tornadoes of fire) at the (unresolved) SGS level. Professor, Mechanical Engineering and Mathematics.

Amygdala inputs to prefrontal cortex guide behavior amid conflicting cues of reward and punishment

PubMed Central

Burgos-Robles, Anthony; Kimchi, Eyal Y.; Izadmehr, Ehsan M.; Porzenheim, Mary Jane; Ramos-Guasp, William A.; Nieh, Edward H.; Felix-Ortiz, Ada C.; Namburi, Praneeth; Leppla, Christopher A.; Presbrey, Kara N.; Anandalingam, Kavitha K.; Pagan-Rivera, Pablo A.; Anahtar, Melodi; Beyeler, Anna; Tye, Kay M.

2017-01-01

Orchestrating appropriate behavioral responses in the face of competing signals that predict either rewards or threats in the environment is crucial for survival. The basolateral amygdala (BLA) and prelimbic (PL) medial prefrontal cortex (mPFC) have been implicated in reward-seeking and fear-related responses, but how information flows between these reciprocally-connected structures to coordinate behavior is unknown. We recorded neuronal activity from the BLA and PL while rats performed a task where in shock- and sucrose-predictive cues were simultaneously presented to induce competition. The correlated firing primarily displayed a BLA→PL directionality during the shock-associated cue. Furthermore, the majority of optogenetically-identified PL-projecting BLA neurons recorded encoded the shock-associated cue, and more accurately predicted behavioral responses during competition than unidentified BLA neurons. Finally, BLA→PL photostimulation increased freezing, whereas both chemogenetic and optogenetic inhibition reduced freezing. The BLA→PL circuit plays a critical role in governing the selection of behavioral responses in the face of competing signals. PMID:28436980

Impact of a community based fire prevention intervention on fire safety knowledge and behavior in elementary school children

PubMed Central

Hwang, V; Duchossois, G P; Garcia‐Espana, J F; Durbin, D R

2006-01-01

The objective of this study was to determine the impact of a community based fire prevention intervention directed only to parents on the fire safety knowledge and behavior in elementary school children. This was a prospective, quasi‐randomized controlled study in which third and fourth grade students from two elementary schools in an urban, poor, minority community completed knowledge/behavior surveys at baseline and following completion of the intervention. The intervention group received an in‐home visit from fire department personnel who installed free lithium smoke detectors and provided a fire escape plan. After accounting for a small difference in baseline summary scores of knowledge and behavior between the control and intervention groups, this study found a modest improvement in fire safety behavior among children whose families received a fire prevention intervention reflecting a change in household fire safety practices. However, there was no significant change in fire safety knowledge. PMID:17018679

In-situ characterization of wildland fire behavior

Treesearch

Bret Butler; D. Jimenez; J. Forthofer; Paul Sopko; K. Shannon; Jim Reardon

2010-01-01

A system consisting of two enclosures has been developed to characterize wildand fire behavior: The first enclosure is a sensor/data logger combination that measures and records convective/radiant energy released by the fire. The second is a digital video camera housed in a fire proof enclosure that records visual images of fire behavior. Together this system provides...

Internally generated preactivation of single neurons in human medial frontal cortex predicts volition

PubMed Central

Fried, Itzhak; Mukamel, Roy; Kreiman, Gabriel

2011-01-01

Understanding how self-initiated behavior is encoded by neuronal circuits in the human brain remains elusive. We recorded the activity of 1019 neurons while twelve subjects performed self-initiated finger movement. We report progressive neuronal recruitment over ~1500 ms before subjects report making the decision to move. We observed progressive increase or decrease in neuronal firing rate, particularly in the supplementary motor area (SMA), as the reported time of decision was approached. A population of 256 SMA neurons is sufficient to predict in single trials the impending decision to move with accuracy greater than 80% already 700 ms prior to subjects’ awareness. Furthermore, we predict, with a precision of a few hundred ms, the actual time point of this voluntary decision to move. We implement a computational model whereby volition emerges once a change in internally generated firing rate of neuronal assemblies crosses a threshold. PMID:21315264

75 FR 58347 - Information Collection; Overcoming Barriers to Wildland Fire Defensible Space Behaviors

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-24

... Information Collection; Overcoming Barriers to Wildland Fire Defensible Space Behaviors AGENCY: Forest Service... new information collection, Overcoming Barriers to Wildland Fire Defensible Space Behaviors. DATES... time, Monday through Friday. SUPPLEMENTARY INFORMATION: Title: Overcoming Barriers to Wildland Fire...

Calibrating a forest landscape model to simulate frequent fire in Mediterranean-type shrublands

USGS Publications Warehouse

Syphard, A.D.; Yang, J.; Franklin, J.; He, H.S.; Keeley, J.E.

2007-01-01

In Mediterranean-type ecosystems (MTEs), fire disturbance influences the distribution of most plant communities, and altered fire regimes may be more important than climate factors in shaping future MTE vegetation dynamics. Models that simulate the high-frequency fire and post-fire response strategies characteristic of these regions will be important tools for evaluating potential landscape change scenarios. However, few existing models have been designed to simulate these properties over long time frames and broad spatial scales. We refined a landscape disturbance and succession (LANDIS) model to operate on an annual time step and to simulate altered fire regimes in a southern California Mediterranean landscape. After developing a comprehensive set of spatial and non-spatial variables and parameters, we calibrated the model to simulate very high fire frequencies and evaluated the simulations under several parameter scenarios representing hypotheses about system dynamics. The goal was to ensure that observed model behavior would simulate the specified fire regime parameters, and that the predictions were reasonable based on current understanding of community dynamics in the region. After calibration, the two dominant plant functional types responded realistically to different fire regime scenarios. Therefore, this model offers a new alternative for simulating altered fire regimes in MTE landscapes. ?? 2007 Elsevier Ltd. All rights reserved.

Stochastic representation of fire behavior in a wildland fire protection planning model for California.

Treesearch

J. Keith Gilless; Jeremy S. Fried

1998-01-01

A fire behavior module was developed for the California Fire Economics Simulator version 2 (CFES2), a stochastic simulation model of initial attack on wildland fire used by the California Department of Forestry and Fire Protection. Fire rate of spread (ROS) and fire dispatch level (FDL) for simulated fires "occurring" on the same day are determined by making...

Fire weather and fire behavior in the 1966 loop fire

Treesearch

C.M. Countryman; M.A. Fosberg; R.C. Rothermel; M.J. Schroeder

1968-01-01

Southern California regularly experiences a wind condition known as the Santa Ana winds. This paper describes the phenomenon and the effects it had on fire behavior during the 1966 Loop Fire in the Angeles National Forest, which claimed the lives of 12 fire fighters.

Fire behavior, fuel treatments, and fire suppression on the Hayman Fire - Part 4: Relation of roads to burn severity

Treesearch

Charles W. McHugh; Mark A. Finney

2003-01-01

Effects of roads on fire behavior intensity and severity can be studied directly or indirectly. A direct study of road effects would include uses by fire suppression, burnout operations, and delay of fire progress at the roadside. Interpretations after the fire burns are easily confounded by the unknown nature of suppression activities and fire arrival time, and fire...

Fire characteristics charts for fire behavior and U.S. fire danger rating

Treesearch

Faith Ann Heinsch; Pat Andrews

2010-01-01

The fire characteristics chart is a graphical method of presenting U.S. National Fire Danger Rating indices or primary surface or crown fire behavior characteristics. A desktop computer application has been developed to produce fire characteristics charts in a format suitable for inclusion in reports and presentations. Many options include change of scales, colors,...

Bald Mountain Fire, Eagle Cap Wilderness Area, Wallowa-Whitman National Forest, FARSITE analysis

Treesearch

LaWen Hollingsworth

2012-01-01

While the Near Term Fire Behavior analysis option in WFDSS is similar to FARSITE, the advantage of using FARSITE lies in the ability to use gridded winds which produces more reliable fire behavior results in complex terrain. A couple of FARSITE simulations were completed to evaluate fire growth and fire behavior in relation to the values, notably Red's Horse Ranch...

Differential roles of ventral pallidum subregions during cocaine self-administration behaviors

PubMed Central

Root, David H.; Ma, Sisi; Barker, David J.; Megehee, Laura; Striano, Brendan M.; Ralston, Carla M.; Fabbricatore, Anthony T.; West, Mark O.

2012-01-01

The ventral pallidum (VP) is necessary for drug-seeking behavior. VP contains ventromedial (VPvm) and dorsolateral (VPdl) subregions which receive projections from the nucleus accumbens shell and core, respectively. To date, no study has investigated the behavioral functions of the VPdl and VPvm subregions. To address this issue, we investigated whether changes in firing rate (FR) differed between VP subregions during four events: approaching toward, responding on, or retreating away from a cocaine-reinforced operandum, and a cocaine-associated cue. Baseline FR and waveform characteristics did not differ between subregions. VPdl neurons exhibited a greater change in FR compared to VPvm neurons during approaches toward, as well as responses on, the cocaine-reinforced operandum. VPdl neurons were more likely to exhibit a similar change in FR (direction and magnitude) during approach and response than VPvm neurons. In contrast, VPvm firing patterns were heterogeneous, changing FRs during approach or response alone, or both. VP neurons did not discriminate cued behaviors from uncued behaviors. No differences were found between subregions during the retreat and no VP neurons exhibited patterned changes in FR in response to the cocaine-associated cue. The stronger, sustained FR changes of VPdl neurons during approach and response may implicate VPdl in the processing of drug-seeking and drug-taking behavior via projections to subthalamic nucleus and substantia nigra pars reticulata. In contrast, heterogeneous firing patterns of VPvm neurons may implicate VPvm in facilitating mesocortical structures with information related to the sequence of behaviors predicting cocaine self-infusions via projections to mediodorsal thalamus and ventral tegmental area. PMID:22806483

Heat Transfer Processes Linking Fire Behavior and Tree Mortality

NASA Astrophysics Data System (ADS)

Michaletz, S. T.; Johnson, E. A.

2004-12-01

Traditional methods for predicting post-fire tree mortality employ statistical models which neglect the processes linking fire behavior to physiological mortality mechanisms. Here we present a physical process approach which predicts tree mortality by linking fireline intensity with lateral (vascular cambium) and apical (vegetative bud) meristem necrosis. We use a linefire plume model with independently validated conduction and lumped capacitance heat transfer analyses to predict lethal meristem temperatures in tree stems, branches, and buds. These models show that meristem necrosis in large diameter (Bi ≥ 0.3) stems/branches is governed by meristem height, bark thickness, and bark water content, while meristem necrosis in small diameter (Bi < 0.3) branches/buds is governed by meristem height, branch/bud size, branch/bud water content, and foliage architecture. To investigate effects of interspecfic variation in these properties, we compare model results for Picea glauca (Moench) Voss and Pinus contorta Loudon var. latifolia Engelm. at fireline intensities from 50 to 3000 kWm-1. Parameters are obtained from allometric models which relate stem/branch diameter to bark thickness and height, as well as bark and bud water content data collected in the southern Canadian Rocky Mountains. Variation in foliage architecture is quantified using forced convection heat transfer coefficients measured in a laminar flow wind tunnel at Re from 100 to 2000, typical for branches/buds in a linefire plume. Results indicate that in unfoliated stems/branches, P. glauca meristems are more protected due to thicker bark, whereas in foliated branches/buds, P. contorta meristems are more protected due to larger bud size and foliage architecture.

Fire Technology Abstracts, volume 4, issue 1, August, 1981

NASA Astrophysics Data System (ADS)

Holtschlag, L. J.; Kuvshinoff, B. W.; Jernigan, J. B.

This bibliography contains over 400 citations with abstracts addressing various aspects of fire technology. Subjects cover the dynamics of fire, behavior and properties of materials, fire modeling and test burns, fire protection, fire safety, fire service organization, apparatus and equipment, fire prevention, suppression, planning, human behavior, medical problems, codes and standards, hazard identification, safe handling of materials, insurance, economics of loss and prevention, and more.

How to generate and interpret fire characteristics charts for the U.S. fire danger rating system

Treesearch

Faith Ann Heinsch; Patricia L. Andrews; Deb Tirmenstein

2017-01-01

The fire characteristics chart is a graphical method of presenting U.S. National Fire Danger Rating System (NFDRS) indexes and components as well as primary surface or crown fire behavior characteristics. Computer software has been developed to produce fire characteristics charts for both fire danger and fire behavior in a format suitable for inclusion in reports and...

Algorithm for Estimating the Plume Centerline Temperature and Ceiling Jet Temperature in the Presence of a Hot Upper Layer

NASA Technical Reports Server (NTRS)

Davis, William D.; Notarianni, Kathy A.; Tapper, Phillip Z.

1998-01-01

The experiments were designed to provide insight into the behavior of jet fuel fires in aircraft hangars and to study the impact of these fires on the design and operation of a variety of fire protection systems. As a result, the test series included small fires designed to investigate the operation of UV/IR detectors and smoke detectors as well as large fires which were used to investigate the operation of ceiling mounted heat detectors and sprinklers. The impact of the presence or absence of draft curtains was also studied in the 15 m hangar. It is shown that in order to predict the plume centerline temperature within experimental uncertainty, the entrainment of the upper layer gas must be modeled. For large fires, the impact of a changing radiation fraction must also be included in the calculation. The dependence of the radial temperature profile of the ceiling jet as a function of layer development is demonstrated and a ceiling jet temperature algorithm which includes the impact of a growing layer is developed.

Introduction: Strengthening the foundation of wildland fire Effects prediction for research and management

Treesearch

Matthew B. Dickinson; Kevin C. Ryan

2010-01-01

As prescribed fire use increases and the options for responding to wildfires continue to expand beyond suppression, the need for improving fire effects prediction capabilities be¬comes increasingly apparent. The papers in this Fire Ecology special issue describe recent advances in fire effects prediction for key classes of direct (first-order) fire effects. Important...

Predicting post-fire tree mortality for 12 western US conifers using the First-Order Fire Effects Model (FOFEM)

Treesearch

Sharon Hood; Duncan Lutes

2017-01-01

Accurate prediction of fire-caused tree mortality is critical for making sound land management decisions such as developing burning prescriptions and post-fire management guidelines. To improve efforts to predict post-fire tree mortality, we developed 3-year post-fire mortality models for 12 Western conifer species - white fir (Abies concolor [Gord. &...

Predicting altered connectivity of patchy forests under group selection silviculture

Treesearch

Seth W. Bigelow; Sean A. Parks

2010-01-01

Group selection silviculture creates canopy openings that can alter connectivity in patchy forests, thereby affecting wildlife movement and fire behavior. We examined effects of group selection silviculture on percolation (presence of continuously forested routes across a landscape) in Sierra Nevada East-side pine forest in northern California, USA. Four ~ 250 ha...

Responses of dead forest fuel moisture to climate change

Treesearch

Yongqiang Liu

2016-01-01

Forest fuel moisture is an important factor for wildland fire behavior. Predicting future wildfire trends and controlled burned conditions is essential to effective natural resource management, but the associated effects of forest fuel moisture remain uncertain. This study investigates the responses of dead forest fuel moisture to climate change in the...

Relative impact of weather vs. fuels on fire regimes in coastal California

Treesearch

Jon E. Keeley

2008-01-01

Extreme fire weather is of over riding importance in determining fire behavior in coastal chaparral and on these landscapes fire suppression policy has not resulted in fire exclusion. There is regional variation in foehn winds, which are most important in southern California. Under these severe fire weather conditions fuel age does not constrain fire behavior. As a...

Assessing crown fire potential by linking models of surface and crown fire behavior

Treesearch

Joe H. Scott; Elizabeth D. Reinhardt

2001-01-01

Fire managers are increasingly concerned about the threat of crown fires, yet only now are quantitative methods for assessing crown fire hazard being developed. Links among existing mathematical models of fire behavior are used to develop two indices of crown fire hazard-the Torching Index and Crowning Index. These indices can be used to ordinate different forest...

Performance of fire behavior fuel models developed for the Rothermel Surface Fire Spread Model

Treesearch

Robert Ziel; W. Matt Jolly

2009-01-01

In 2005, 40 new fire behavior fuel models were published for use with the Rothermel Surface Fire Spread Model. These new models are intended to augment the original 13 developed in 1972 and 1976. As a compiled set of quantitative fuel descriptions that serve as input to the Rothermel model, the selected fire behavior fuel model has always been critical to the resulting...

Standard fire behavior fuel models: a comprehensive set for use with Rothermel's surface fire spread model

Treesearch

Joe H. Scott; Robert E. Burgan

2005-01-01

This report describes a new set of standard fire behavior fuel models for use with Rothermel's surface fire spread model and the relationship of the new set to the original set of 13 fire behavior fuel models. To assist with transition to using the new fuel models, a fuel model selection guide, fuel model crosswalk, and set of fuel model photos are provided.

Estimating fire behavior with FIRECAST: user's manual

Treesearch

Jack D. Cohen

1986-01-01

FIRECAST is a computer program that estimates fire behavior in terms of six fire parameters. Required inputs vary depending on the outputs desired by the fire manager. Fuel model options available to users are these: Northern Forest Fire Laboratory (NFFL), National Fire Danger Rating System (NFDRS), and southern California brushland (SCAL). The program has been...

High-fire-risk behavior in critical fire areas

Treesearch

William S. Folkman

1977-01-01

Observations of fire-related behavior of wildland visitors were made in three types of areas-wilderness, established campground, and built-up commercial and residential areas-within the San Bernardino National Forest, California. Interviews were conducted with all persons so observed. Types of fire-related behavior differed markedly from one area to another, as did the...

Predicting post-fire tree mortality for 14 conifers in the Pacific Northwest, USA: Model evaluation, development, and thresholds

Treesearch

Lindsay M. Grayson; Robert A. Progar; Sharon M. Hood

2017-01-01

Fire is a driving force in the North American landscape and predicting post-fire tree mortality is vital to land management. Post-fire tree mortality can have substantial economic and social impacts, and natural resource managers need reliable predictive methods to anticipate potential mortality following fire events. Current fire mortality models are limited to a few...

Fire and Smoke Model Evaluation Experiment: Coordination of a study to improve smoke modeling for fire operations within the United States

NASA Astrophysics Data System (ADS)

French, N. H. F.; Ottmar, R. D.; Brown, T. J.; Larkin, N. K.

2017-12-01

The Fire and Smoke Model Evaluation Experiment (FASMEE) is an integrative research effort to identify and collect critical measurements to improve operational wildland fire and smoke prediction systems. FASMEE has two active phases and one suggested phase. Phase 1 is the analysis and planning process to assess the current state of fire-plume-smoke modeling and to determine the critical measurements required to evaluate and improve these operational fire and smoke models. As the major deliverable for Phase 1, a study plan has been completed that describes the measurement needs, field campaigns, and command, safety and air space de-confliction plans necessary to complete the FASMEE project. Phase 2 is a set of field campaigns to collect data during 2019-2022. Future Improvements would be a set of analyses and model improvements based on the data collected within Phase 2 that is dependent on identifying future funding sources. In this presentation, we will review the FASMEE Study Plan and detailed measurements and conditions expected for the four to five proposed research burns. The recommended measurements during Phase 2 span the four interrelated disciplines of FASMEE: fuels and consumption, fire behavior and energy, plume dynamics and meteorology, and smoke emissions, chemistry, and transport. Fuel type, condition, and consumption during wildland fire relates to several fire impacts including radiative heating, which provides the energy that drives fire dynamics. Local-scale meteorology is an important factor which relates to atmospheric chemistry, dispersion, and transport. Plume dynamics provide the connection between fire behavior and far-field smoke dispersion, because it determines the vertical distribution of the emissions. Guided by the data needs and science questions generated during Phase 1, three wildland fire campaigns were selected. These included the western wildfire campaign (rapid deployment aimed at western wildfires supporting NOAA, NASA, and NSF smoke flights), southwestern campaign (targeting high intensity prescribed fires), and southeastern campaign (targeting large and higher than average fuel loadings with important smoke management relevancy).

Assessing predictive services' 7-day fire potential outlook

Treesearch

Karin Riley; Crystal Stonesifer; Dave Calkin; Haiganoush Preisler

2015-01-01

The Predictive Services program was created under the National Wildfire Coordinating Group in 2001 to address the need for long- and short-term decision support information for fire managers and operations personnel. The primary mission of Predictive Services is to integrate fire weather, fire danger, and resource availability to enable strategic fire suppression...

Unprecedented remote sensing data over King and Rim megafires in the Sierra Nevada Mountains of California.

PubMed

Stavros, E Natasha; Tane, Zachary; Kane, Van R; Veraverbeke, Sander; McGaughey, Robert J; Lutz, James A; Ramirez, Carlos; Schimel, David

2016-11-01

Megafires have lasting social, ecological, and economic impacts and are increasing in the western contiguous United States. Because of their infrequent nature, there is a limited sample of megafires to investigate their unique behavior, drivers, and relationship to forest management practices. One approach is to characterize critical information pre-, during, and post-fire using remote sensing. In August 2013, the Rim Fire burned 104,131 ha and in September 2014, the King Fire burned 39,545 ha. Both fires occurred in California's Sierra Nevada. The areas burned by these fires were fortuitously surveyed by airborne campaigns, which provided the most recent remote sensing technologies not currently available from satellite. Technologies include an imaging spectrometer spanning the visible to shortwave infrared (0.38-2.5 μm), a multispectral, high-spatial resolution thermal infrared (3.5-13 μm) spectroradiometer, and Light Detection and Ranging that provide spatial resolutions of pixels from 1 × 1 m to 35 × 35 m. Because of the unique information inherently derived from these technologies before the fires, the areas were subsequently surveyed after the fires. We processed and provide free dissemination of these airborne datasets as products of surface reflectance, spectral metrics and forest structural metrics ( http://dx.doi.org/10.3334/ORNLDAAC/1288). These data products provide a unique opportunity to study relationships among and between remote sensing observations and fuel and fire characteristics (e.g., fuel type, condition, structure, and fire severity). The novelty of these data is not only in the unprecedented types of information available from them before, during, and after two megafires, but also in the synergistic use of multiple state of the art technologies for characterizing the environment. The synergy of these data can provide novel information that can improve maps of fuel type, structure, abundance, and condition that may improve predictions of megafire behavior and effects, thus aiding management before, during, and after such events. Key questions that these data could address include: What drives, extinguishes, and results from megafires? How does megafire behavior relate to fire and fuel management? How does the size and severity of a megafire affect the ecological recovery of the system? © 2016 by the Ecological Society of America.

Temporal scaling behavior of forest and urban fires

NASA Astrophysics Data System (ADS)

Wang, J.; Song, W.; Zheng, H.; Telesca, L.

2009-04-01

It has been found that many natural systems are characterized by scaling behavior. In such systems natural factors dominate the event dynamics. Forest fires in different countries have been found to exhibit frequency-size power law over many orders of magnitude and with similar value of parameters. But in countries with high population density such as China and Japan, more than 95% of the forest fire disasters are caused by human activities. Furthermore, with the development of society, the wildland-urban interface (WUI) area is becoming more and more populated, and the forest fire is much connected with urban fire. Therefore exploring the scaling behavior of fires dominated by human-related factors is very challenging. The present paper explores the temporal scaling behavior of forest fires and urban fires in Japan with mathematical methods. Two factors, Allan factor (AF) and Fano factor (FF) are used to investigate time-scaling of fire systems. It is found that the FF for both forest fires and urban fires increases linearly in log-log scales, and this indicates that it behaves as a power-law for all the investigated timescales. From the AF plot a 7 days cycle is found, which indicates a weekly cycle. This may be caused by human activities which has a weekly periodicity because on weekends people usually have more outdoor activities, which may cause more hidden trouble of fire disasters. Our findings point out that although the human factors are the main cause, both the forest fires and urban fires exhibit time-scaling behavior. At the same time, the scaling exponents for urban fires are larger than forest fires, signifying a more intense clustering. The reason may be that fires are affected not only by weather condition, but also by human activities, which play a more important role for urban fires than forest fires and have a power law distribution and scaling behavior. Then some work is done to the relative humidity. Similar distribution law characterizes the relative humidity. The AF plot and FF plot of relative humidity validate the existence of a strong link between weather and fires, and it is very likely that the daily humidity cycle determines the daily fire periodicity.

Ecological forestry in the Southeast: Understanding the ecology of fuels

Treesearch

R.J. Mitchell; J.K. Hiers; J. O’Brien; G. Starr

2009-01-01

Fire is a dominant disturbance within many forested ecosystems worldwide. Understanding the complex feedbacks among vegetation as a fuel for fire, the effects of fuels on fire behavior, and the impact of fire behavior on future vegetation are critical for sustaining biodiversity in fire-dependent forests. Nonetheless, understanding in fire ecology has been limited in...

An Overview of FlamMap Fire Modeling Capabilities

Treesearch

Mark A. Finney

2006-01-01

Computerized and manual systems for modeling wildland fire behavior have long been available (Rothermel 1983, Andrews 1986). These systems focus on one-dimensional behaviors and assume the fire geometry is a spreading line-fire (in contrast with point or area-source fires). Models included in these systems were developed to calculate fire spread rate (Rothermel 1972,...

Fire effects on basal area, tiller production, and mortality of the C4 Bunchgrass, Purple Threeawn

USDA-ARS?s Scientific Manuscript database

Fire behavior associated with wild and prescribed fires is variable, but plays a vital role in how a plant responds to fire. The relationship of fire behavior to rangeland plant community response has not been investigated, with a few exceptions, until recently. Fire is an important ecological pro...

[Lightning-caused fire, its affecting factors and prediction: a review].

PubMed

Zhang, Ji-Li; Bi, Wu; Wang, Xiao-Hong; Wang, Zi-Bo; Li, Di-Fei

2013-09-01

Lightning-caused fire is the most important natural fire source. Its induced forest fire brings enormous losses to human beings and ecological environment. Many countries have paid great attention to the prediction of lightning-caused fire. From the viewpoint of the main factors affecting the formation of lightning-caused fire, this paper emphatically analyzed the effects and action mechanisms of cloud-to-ground lightning, fuel, meteorology, and terrain on the formation and development process of lightning-caused fire, and, on the basis of this, summarized and reviewed the logistic model, K-function, and other mathematical methods widely used in prediction research of lightning-caused fire. The prediction methods and processes of lightning-caused fire in America and Canada were also introduced. The insufficiencies and their possible solutions for the present researches as well as the directions of further studies were proposed, aimed to provide necessary theoretical basis and literature reference for the prediction of lightning-caused fire in China.

Sensitivity of fire behavior simulations to fuel model variations

Treesearch

Lucy A. Salazar

1985-01-01

Stylized fuel models, or numerical descriptions of fuel arrays, are used as inputs to fire behavior simulation models. These fuel models are often chosen on the basis of generalized fuel descriptions, which are related to field observations. Site-specific observations of fuels or fire behavior in the field are not readily available or necessary for most fire management...

Solution Focused Empathy Training Groups for Students with Fire-Setting Behaviors

ERIC Educational Resources Information Center

Froeschle, Janet G.

2006-01-01

Fire-setting students are those who intentionally or unintentionally set one or more fires due to curiosity, stress, a need for attention, or due to criminal delinquency. This article describes the nature of fire-setting behaviors, discusses the profile and risk factors associated with the behavior, and outlines a group program using empathy…

Predicting wildfire ignitions, escapes, and large fire activity using Predictive Service’s 7-Day Fire Potential Outlook in the western USA

Treesearch

Karin L. Riley; Crystal Stonesifer; Haiganoush Preisler; Dave Calkin

2014-01-01

Can fire potential forecasts assist with pre-positioning of fire suppression resources, which could result in a cost savings to the United States government? Here, we present a preliminary assessment of the 7-Day Fire Potential Outlook forecasts made by the Predictive Services program. We utilized historical fire occurrence data and archived forecasts to assess how...

Introduction to fire danger rating and remote sensing - Will remote sensing enhance wildland fire danger prediction?

USGS Publications Warehouse

Allgöwer, Britta; Carlson, J.D.; Van Wagtendonk, Jan W.; Chuvieco, Emilio

2003-01-01

While ‘Fire Danger’ per se cannot be measured, the physical properties of the biotic and abiotic world that relate to fire occurrence and fire behavior can. Today, increasingly sophisticated Remote Sensing methods are being developed to more accurately detect fuel properties such as species composition (fuel types), vegetation structure or plant water content - to name a few. Based on meteorological input data and physical, semi-physical or empirical model calculations, Wildland Fire Danger Rating Systems provide ‘indirect values’ - numerical indices - at different temporal scales (e.g., daily, weekly, monthly) denoting the physical conditions that may lead to fire ignition and support fire propagation. The results can be expressed as fire danger levels, ranging from ‘low’ to ‘very high’, and are commonly used in operational wildland fire management (e.g., the Canadian Fire Weather Index [FWI] System, the Russian Nesterov Index, or the U.S. National Fire Danger Rating System [NFDRS]). Today, fire danger levels are often turned into broad scale maps with the help of Geographical Information Systems (GIS) showing the areas with the different fire danger levels, and are distributed via the World Wide Web.In this chapter we will outline some key issues dealing with Remote Sensing and GIS techniques that are covered in the following chapters, and elaborate how the Fire Danger Rating concepts could be integrated into a framework that enables comprehensive and sustainable wildland fire risk assessment. To do so, we will first raise some general thoughts about wildland fires and suggest how to approach this extremely complex phenomenon. Second, we will outline a possible fire risk analysis framework and third we will give a short overview on existing Fire Danger Rating Systems and the principles behind them.

Human and biophysical influences on fire occurrence in the United States

USGS Publications Warehouse

Hawbaker, Todd J.; Radeloff, Volker C.; Stewart, Susan I.; Hammer, Roger B.; Keuler, Nicholas S.; Clayton, Murray K.

2013-01-01

National-scale analyses of fire occurrence are needed to prioritize fire policy and management activities across the United States. However, the drivers of national-scale patterns of fire occurrence are not well understood, and how the relative importance of human or biophysical factors varies across the country is unclear. Our research goal was to model the drivers of fire occurrence within ecoregions across the conterminous United States. We used generalized linear models to compare the relative influence of human, vegetation, climate, and topographic variables on fire occurrence in the United States, as measured by MODIS active fire detections collected between 2000 and 2006. We constructed models for all fires and for large fires only and generated predictive maps to quantify fire occurrence probabilities. Areas with high fire occurrence probabilities were widespread in the Southeast, and localized in the Mountain West, particularly in southern California, Arizona, and New Mexico. Probabilities for large-fire occurrence were generally lower, but hot spots existed in the western and south-central United States The probability of fire occurrence is a critical component of fire risk assessments, in addition to vegetation type, fire behavior, and the values at risk. Many of the hot spots we identified have extensive development in the wildland–urban interface and are near large metropolitan areas. Our results demonstrated that human variables were important predictors of both all fires and large fires and frequently exhibited nonlinear relationships. However, vegetation, climate, and topography were also significant variables in most ecoregions. If recent housing growth trends and fire occurrence patterns continue, these areas will continue to challenge policies and management efforts seeking to balance the risks generated by wildfires with the ecological benefits of fire.

Numerical Analysis on Tensile Properties of Grout-filled Splice Sleeve Rebars under ISO 834 Standard Fire

NASA Astrophysics Data System (ADS)

Liu, Yong Jun; Li, Chao; Zhou, When Jun

2018-06-01

This paper presents some numerical simulation results of tensile properties of reinforcing bars spliced by grout-filled coupling sleeves under fire conditions to identify the effect of load ratio on fire resistance time of spliced reinforcing bars, which provide a useful base for predicting structural behaviors of pre-cast reinforced concrete buildings in fires. A spliced rebar system investigated in this paper consists of two equal-diameter steel reinforcing bars with 25mm diameter and a straight coupling sleeve with 50mm outer and 45mm inner diameters. As a result, the thickness of grout between steel bars and sleeves are 20mm. Firstly, the temperature distributions in steel bars connected by grout- filled coupling sleeves exposed to ISO 834 standard fire were calculated utilizing finite element analysis software ANSYS. Secondly, the stress changes in heated steel bars connected by grout-filled coupling sleeves under different constant tensile loads were calculated step by step until the rebar system failed due to fire. Thus, the fire resistant time of rebar spliced by grout-filled coupling sleeves under different axial tensile loads can be determined, further, the relationship between fire resistance time and axial tensile loads ratio can could be obtained. Finally, the fire resistant times versus axial tensile load ratios curve of grout-filled splice sleeve rebars exposed to ISO 834 standard fire is presented.

Uncertainty and risk in wildland fire management: A review

Treesearch

Matthew P. Thompson; Dave E. Calkin

2011-01-01

Wildland fire management is subject to manifold sources of uncertainty. Beyond the unpredictability of wildfire behavior, uncertainty stems from inaccurate/missing data, limited resource value measures to guide prioritization across fires and resources at risk, and an incomplete scientific understanding of ecological response to fire, of fire behavior response to...

How did prefire treatments affect the Biscuit Fire?

Treesearch

Crystal Raymond; David L. Peterson

2005-01-01

Most scientific literature supports forest thinning to reduce the severity of wildland fires, but the effectiveness of thinning in modifying fire behavior has not been well documented. The Biscuit Fire of 2002 offered a great opportunity to study the effects of mechanical thinning on fire behavior during a megafire.

FARSITE: Fire Area Simulator-model development and evaluation

Treesearch

Mark A. Finney

1998-01-01

A computer simulation model, FARSITE, includes existing fire behavior models for surface, crown, spotting, point-source fire acceleration, and fuel moisture. The model's components and assumptions are documented. Simulations were run for simple conditions that illustrate the effect of individual fire behavior models on two-dimensional fire growth.

Monthly fire behavior patterns

Treesearch

Mark J. Schroeder; Craig C. Chandler

1966-01-01

From tabulated frequency distributions of fire danger indexes for a nationwide network of 89 stations, the probabilities of four types of fire behavior ranging from 'fire out' to 'critical' were calculated for each month and are shown in map form.

Fire behavior, fuel treatments, and fire suppression on the Hayman Fire - Part 1: Fire weather, meteorology, and climate

Treesearch

Larry Bradshaw; Roberta Bartlette; John McGinely; Karl Zeller

2003-01-01

The Hayman Fire in June 2002 was heavily influenced by antecedent regional weather conditions, culminating in a series of daily weather events that aligned to produce widely varying fire behavior. This review of weather conditions associated with the Hayman Fire consists of two parts: 1) A brief overview of prior conditions as described by a regional climate review and...

Fire technology abstracts, volume 4. Cumulative indexes

NASA Astrophysics Data System (ADS)

1982-03-01

Cumulative subject, author, publisher, and report number indexes referencing articles, books, reports, and patents are provided. The dynamics of fire, behavior and properties of materials, fire modeling and test burns, fire protection, fire safety, fire service organization, apparatus and equipment, fire prevention suppression, planning, human behavior, medical problems, codes and standards, hazard identification, safe handling of materials, and insurance economics of loss and prevention are among the subjects covered.

BehavePlus fire modeling system, version 5.0: Design and Features

Treesearch

Faith Ann Heinsch; Patricia L. Andrews

2010-01-01

The BehavePlus fire modeling system is a computer program that is based on mathematical models that describe wildland fire behavior and effects and the fire environment. It is a flexible system that produces tables, graphs, and simple diagrams. It can be used for a host of fire management applications, including projecting the behavior of an ongoing fire, planning...

Improving satellite-driven PM2.5 models with Moderate Resolution Imaging Spectroradiometer fire counts in the southeastern U.S.

PubMed

Hu, Xuefei; Waller, Lance A; Lyapustin, Alexei; Wang, Yujie; Liu, Yang

2014-10-16

Multiple studies have developed surface PM 2.5 (particle size less than 2.5 µm in aerodynamic diameter) prediction models using satellite-derived aerosol optical depth as the primary predictor and meteorological and land use variables as secondary variables. To our knowledge, satellite-retrieved fire information has not been used for PM 2.5 concentration prediction in statistical models. Fire data could be a useful predictor since fires are significant contributors of PM 2.5 . In this paper, we examined whether remotely sensed fire count data could improve PM 2.5 prediction accuracy in the southeastern U.S. in a spatial statistical model setting. A sensitivity analysis showed that when the radius of the buffer zone centered at each PM 2.5 monitoring site reached 75 km, fire count data generally have the greatest predictive power of PM 2.5 across the models considered. Cross validation (CV) generated an R 2 of 0.69, a mean prediction error of 2.75 µg/m 3 , and root-mean-square prediction errors (RMSPEs) of 4.29 µg/m 3 , indicating a good fit between the dependent and predictor variables. A comparison showed that the prediction accuracy was improved more substantially from the nonfire model to the fire model at sites with higher fire counts. With increasing fire counts, CV RMSPE decreased by values up to 1.5 µg/m 3 , exhibiting a maximum improvement of 13.4% in prediction accuracy. Fire count data were shown to have better performance in southern Georgia and in the spring season due to higher fire occurrence. Our findings indicate that fire count data provide a measurable improvement in PM 2.5 concentration estimation, especially in areas and seasons prone to fire events.

Improving satellite-driven PM2.5 models with Moderate Resolution Imaging Spectroradiometer fire counts in the southeastern U.S

PubMed Central

Hu, Xuefei; Waller, Lance A.; Lyapustin, Alexei; Wang, Yujie; Liu, Yang

2017-01-01

Multiple studies have developed surface PM2.5 (particle size less than 2.5 µm in aerodynamic diameter) prediction models using satellite-derived aerosol optical depth as the primary predictor and meteorological and land use variables as secondary variables. To our knowledge, satellite-retrieved fire information has not been used for PM2.5 concentration prediction in statistical models. Fire data could be a useful predictor since fires are significant contributors of PM2.5. In this paper, we examined whether remotely sensed fire count data could improve PM2.5 prediction accuracy in the southeastern U.S. in a spatial statistical model setting. A sensitivity analysis showed that when the radius of the buffer zone centered at each PM2.5 monitoring site reached 75 km, fire count data generally have the greatest predictive power of PM2.5 across the models considered. Cross validation (CV) generated an R2 of 0.69, a mean prediction error of 2.75 µg/m3, and root-mean-square prediction errors (RMSPEs) of 4.29 µg/m3, indicating a good fit between the dependent and predictor variables. A comparison showed that the prediction accuracy was improved more substantially from the nonfire model to the fire model at sites with higher fire counts. With increasing fire counts, CV RMSPE decreased by values up to 1.5 µg/m3, exhibiting a maximum improvement of 13.4% in prediction accuracy. Fire count data were shown to have better performance in southern Georgia and in the spring season due to higher fire occurrence. Our findings indicate that fire count data provide a measurable improvement in PM2.5 concentration estimation, especially in areas and seasons prone to fire events. PMID:28967648

Fire spread in chaparral – a comparison of laboratory data and model predictions in burning live fuels

Treesearch

David R. Weise; Eunmo Koo; Xiangyang Zhou; Shankar Mahalingam; Frédéric Morandini; Jacques-Henri Balbi

2016-01-01

Fire behaviour data from 240 laboratory fires in high-density live chaparral fuel beds were compared with model predictions. Logistic regression was used to develop a model to predict fire spread success in the fuel beds and linear regression was used to predict rate of spread. Predictions from the Rothermel equation and three proposed changes as well as two physically...

Virtualization of Fuelbeds: Building the Next Generation of Fuels Data for Multiple-Scale Fire Modeling and Ecological Analysis

NASA Astrophysics Data System (ADS)

Rowell, Eric Martin

The primary goal of this research is to advance methods for deriving fine-grained, scalable, wildland fuels attributes in 3-dimensions using terrestrial and airborne laser scanning technology. It is fundamentally a remote sensing research endeavor applied to the problem of fuels characterization. Advancements in laser scanning are beginning to have significant impacts on a range of modeling frameworks in fire research, especially those utilizing 3-dimensional data and benefiting from efficient data scaling. The pairing of laser scanning and fire modeling is enabling advances in understanding how fuels variability modulates fire behavior and effects. This dissertation details the development of methods and techniques to characterize and quantify surface fuelbeds using both terrestrial and airborne laser scanning. The primary study site is Eglin Airforce Base, Florida, USA, which provides a range of fuel types and conditions in a fire-adapted landscape along with the multi-disciplinary expertise, logistical support, and prescribed fire necessary for detailed characterization of fire as a physical process. Chapter 1 provides a research overview and discusses the state of fuels science and the related needs for highly resolved fuels data in the southeastern United States. Chapter 2, describes the use of terrestrial laser scanning for sampling fuels at multiple scales and provides analysis of the spatial accuracy of fuelbed models in 3-D. Chapter 3 describes the development of a voxel-based occupied volume method for predicting fuel mass. Results are used to inform prediction of landscape-scale fuel load using airborne laser scanning metrics as well as to predict post-fire fuel consumption. Chapter 4 introduces a novel fuel simulation approach which produces spatially explicit, statistically-defensible estimates of fuel properties and demonstrates a pathway for resampling observed data. This method also can be directly compared to terrestrial laser scanning data to assess how energy interception of the laser pulse affects characterization of the fuelbed. Chapter 5 discusses the contribution of this work to fire science and describes ongoing and future research derived from this work. Chapters 2 and 4 have been published in International Journal of Wildland Fire and Canadian Journal of Remote Sensing, respectively, and Chapter 3 is in preparation for publication.

An evaluation of The Great Escape: can an interactive computer game improve young children's fire safety knowledge and behaviors?

PubMed

Morrongiello, Barbara A; Schwebel, David C; Bell, Melissa; Stewart, Julia; Davis, Aaron L

2012-07-01

Fire is a leading cause of unintentional injury and, although young children are at particularly increased risk, there are very few evidence-based resources available to teach them fire safety knowledge and behaviors. Using a pre-post randomized design, the current study evaluated the effectiveness of a computer game (The Great Escape) for teaching fire safety information to young children (3.5-6 years). Using behavioral enactment procedures, children's knowledge and behaviors related to fire safety were compared to a control group of children before and after receiving the intervention. The results indicated significant improvements in knowledge and fire safety behaviors in the intervention group but not the control. Using computer games can be an effective way to promote young children's understanding of safety and how to react in different hazardous situations.

A mixed integer program to model spatial wildfire behavior and suppression placement decisions

Treesearch

Erin J. Belval; Yu Wei; Michael Bevers

2015-01-01

Wildfire suppression combines multiple objectives and dynamic fire behavior to form a complex problem for decision makers. This paper presents a mixed integer program designed to explore integrating spatial fire behavior and suppression placement decisions into a mathematical programming framework. Fire behavior and suppression placement decisions are modeled using...

Orbitofrontal Cortex Signals Expected Outcomes with Predictive Codes When Stable Contingencies Promote the Integration of Reward History

PubMed Central

Shapiro, Matthew L.

2017-01-01

Memory can inform goal-directed behavior by linking current opportunities to past outcomes. The orbitofrontal cortex (OFC) may guide value-based responses by integrating the history of stimulus–reward associations into expected outcomes, representations of predicted hedonic value and quality. Alternatively, the OFC may rapidly compute flexible “online” reward predictions by associating stimuli with the latest outcome. OFC neurons develop predictive codes when rats learn to associate arbitrary stimuli with outcomes, but the extent to which predictive coding depends on most recent events and the integrated history of rewards is unclear. To investigate how reward history modulates OFC activity, we recorded OFC ensembles as rats performed spatial discriminations that differed only in the number of rewarded trials between goal reversals. The firing rate of single OFC neurons distinguished identical behaviors guided by different goals. When >20 rewarded trials separated goal switches, OFC ensembles developed stable and anticorrelated population vectors that predicted overall choice accuracy and the goal selected in single trials. When <10 rewarded trials separated goal switches, OFC population vectors decorrelated rapidly after each switch, but did not develop anticorrelated firing patterns or predict choice accuracy. The results show that, whereas OFC signals respond rapidly to contingency changes, they predict choices only when reward history is relatively stable, suggesting that consecutive rewarded episodes are needed for OFC computations that integrate reward history into expected outcomes. SIGNIFICANCE STATEMENT Adapting to changing contingencies and making decisions engages the orbitofrontal cortex (OFC). Previous work shows that OFC function can either improve or impair learning depending on reward stability, suggesting that OFC guides behavior optimally when contingencies apply consistently. The mechanisms that link reward history to OFC computations remain obscure. Here, we examined OFC unit activity as rodents performed tasks controlled by contingencies that varied reward history. When contingencies were stable, OFC neurons signaled past, present, and pending events; when contingencies were unstable, past and present coding persisted, but predictive coding diminished. The results suggest that OFC mechanisms require stable contingencies across consecutive episodes to integrate reward history, represent predicted outcomes, and inform goal-directed choices. PMID:28115481

Prediction of understory vegetation cover with airborne lidar in an interior ponderosa pine forest

Treesearch

Brian M. Wing; Martin W. Ritchie; Kevin Boston; Warren B. Cohen; Alix Gitelman; Michael J. Olsen

2012-01-01

Forest understory communities are important components in forest ecosystems providing wildlife habitat and influencing nutrient cycling, fuel loadings, fire behavior and tree species composition over time. One of the most widely utilized understory component metrics is understory vegetation cover, often used as a measure of vegetation abundance. To date, understory...

Novel fuelbed characteristics associated with mechanical mastication treatments in northern California and south-western Oregon, USA

Treesearch

Jeffrey M. Kane; J. Morgan Varner; Eric E. Knapp

2009-01-01

Mechanically masticated fuelbeds are distinct from natural or logging slash fuelbeds, with different particle size distributions, bulk density, and particle shapes, leading to challenges in predicting fire behavior and effects. Our study quantified some physical properties of fuel particles (e.g. squared quadratic mean diameter, proportion of non-cylindrical particles...

Dimensional analysis of flame angles versus wind speed

Treesearch

Robert E. Martin; Mark A. Finney; Domingo M. Molina; David B. Sapsis; Scott L. Stephens; Joe H. Scott; David R. Weise

1991-01-01

Dimensional analysis has potential to help explain and predict physical phenomena, but has been used very little in studies of wildland fire behavior. By combining variables into dimensionless groups, the number of variables to be handled and the experiments to be run is greatly reduced. A low velocity wind tunnel was constructed, and methyl, ethyl, and isopropyl...

Communicating forest management science and practices through visualized and animated media approaches to community presentations: An exploration and assessment

Treesearch

Donald E. Zimmerman; Carol Akerelrea; Jane Kapler Smith; Garrett J. O' Keefe

2006-01-01

Natural-resource managers have used a variety of computer-mediated presentation methods to communicate management practices to diverse publics. We explored the effects of visualizing and animating predictions from mathematical models in computerized presentations explaining forest succession (forest growth and change through time), fire behavior, and management options...

Current status and future needs of the BehavePlus Fire Modeling System

Treesearch

Patricia L. Andrews

2014-01-01

The BehavePlus Fire Modeling System is among the most widely used systems for wildland fire prediction. It is designed for use in a range of tasks including wildfire behaviour prediction, prescribed fire planning, fire investigation, fuel hazard assessment, fire model understanding, communication and research. BehavePlus is based on mathematical models for fire...

Fire weather and behavior of the Little Sioux fire.

Treesearch

Rodney W. Sando; Donald A. Haines

1972-01-01

In mid-May 1971, a northern Minnesota fire burned almost 15,000 acres of forest land. The extreme fire behavior it exhibited was the product of a number of described features. This paper documents the attendant fuel and weather conditions.

Homeostatic Regulation of Memory Systems and Adaptive Decisions

PubMed Central

Mizumori, Sheri JY; Jo, Yong Sang

2013-01-01

While it is clear that many brain areas process mnemonic information, understanding how their interactions result in continuously adaptive behaviors has been a challenge. A homeostatic-regulated prediction model of memory is presented that considers the existence of a single memory system that is based on a multilevel coordinated and integrated network (from cells to neural systems) that determines the extent to which events and outcomes occur as predicted. The “multiple memory systems of the brain” have in common output that signals errors in the prediction of events and/or their outcomes, although these signals differ in terms of what the error signal represents (e.g., hippocampus: context prediction errors vs. midbrain/striatum: reward prediction errors). The prefrontal cortex likely plays a pivotal role in the coordination of prediction analysis within and across prediction brain areas. By virtue of its widespread control and influence, and intrinsic working memory mechanisms. Thus, the prefrontal cortex supports the flexible processing needed to generate adaptive behaviors and predict future outcomes. It is proposed that prefrontal cortex continually and automatically produces adaptive responses according to homeostatic regulatory principles: prefrontal cortex may serve as a controller that is intrinsically driven to maintain in prediction areas an experience-dependent firing rate set point that ensures adaptive temporally and spatially resolved neural responses to future prediction errors. This same drive by prefrontal cortex may also restore set point firing rates after deviations (i.e. prediction errors) are detected. In this way, prefrontal cortex contributes to reducing uncertainty in prediction systems. An emergent outcome of this homeostatic view may be the flexible and adaptive control that prefrontal cortex is known to implement (i.e. working memory) in the most challenging of situations. Compromise to any of the prediction circuits should result in rigid and suboptimal decision making and memory as seen in addiction and neurological disease. © 2013 The Authors. Hippocampus Published by Wiley Periodicals, Inc. PMID:23929788

Homeostatic regulation of memory systems and adaptive decisions.

PubMed

Mizumori, Sheri J Y; Jo, Yong Sang

2013-11-01

While it is clear that many brain areas process mnemonic information, understanding how their interactions result in continuously adaptive behaviors has been a challenge. A homeostatic-regulated prediction model of memory is presented that considers the existence of a single memory system that is based on a multilevel coordinated and integrated network (from cells to neural systems) that determines the extent to which events and outcomes occur as predicted. The "multiple memory systems of the brain" have in common output that signals errors in the prediction of events and/or their outcomes, although these signals differ in terms of what the error signal represents (e.g., hippocampus: context prediction errors vs. midbrain/striatum: reward prediction errors). The prefrontal cortex likely plays a pivotal role in the coordination of prediction analysis within and across prediction brain areas. By virtue of its widespread control and influence, and intrinsic working memory mechanisms. Thus, the prefrontal cortex supports the flexible processing needed to generate adaptive behaviors and predict future outcomes. It is proposed that prefrontal cortex continually and automatically produces adaptive responses according to homeostatic regulatory principles: prefrontal cortex may serve as a controller that is intrinsically driven to maintain in prediction areas an experience-dependent firing rate set point that ensures adaptive temporally and spatially resolved neural responses to future prediction errors. This same drive by prefrontal cortex may also restore set point firing rates after deviations (i.e. prediction errors) are detected. In this way, prefrontal cortex contributes to reducing uncertainty in prediction systems. An emergent outcome of this homeostatic view may be the flexible and adaptive control that prefrontal cortex is known to implement (i.e. working memory) in the most challenging of situations. Compromise to any of the prediction circuits should result in rigid and suboptimal decision making and memory as seen in addiction and neurological disease. Copyright © 2013 Wiley Periodicals, Inc.

Evaluating potential fire behavior in lodgepole pine-dominated forests after a mountain pine beetle epidemic in north-central Colorado

Treesearch

Jennifer G. Klutsch; Mike A. Battaglia; Daniel R. West; Sheryl L. Costello; Jose F. Negron

2011-01-01

A mountain pine beetle outbreak in Colorado lodgepole pine forests has altered stand and fuel characteristics that affect potential fire behavior. Using the Fire and Fuels Extension to the Forest Vegetation Simulator, potential fire behavior was modeled for uninfested and mountain pine beetle-affected plots 7 years after outbreak initiation and 10 and 80% projected...

Combining turbulent kinetic energy and Haines Index predictions for fire-weather assessments

Treesearch

Warren E. Heilman; Xindi Bian

2007-01-01

The 24- to 72-hour fire-weather predictions for different regions of the United States are now readily available from the regional Fire Consortia for Advanced Modeling of Meteorology and Smoke (FCAMMS) that were established as part of the U.S. National Fire Plan. These predictions are based on daily real-time MM5 model simulations of atmospheric conditions and fire-...

Analysis of Neuronal Spike Trains, Deconstructed

PubMed Central

Aljadeff, Johnatan; Lansdell, Benjamin J.; Fairhall, Adrienne L.; Kleinfeld, David

2016-01-01

As information flows through the brain, neuronal firing progresses from encoding the world as sensed by the animal to driving the motor output of subsequent behavior. One of the more tractable goals of quantitative neuroscience is to develop predictive models that relate the sensory or motor streams with neuronal firing. Here we review and contrast analytical tools used to accomplish this task. We focus on classes of models in which the external variable is compared with one or more feature vectors to extract a low-dimensional representation, the history of spiking and other variables are potentially incorporated, and these factors are nonlinearly transformed to predict the occurrences of spikes. We illustrate these techniques in application to datasets of different degrees of complexity. In particular, we address the fitting of models in the presence of strong correlations in the external variable, as occurs in natural sensory stimuli and in movement. Spectral correlation between predicted and measured spike trains is introduced to contrast the relative success of different methods. PMID:27477016

A computational substrate for incentive salience.

PubMed

McClure, Samuel M; Daw, Nathaniel D; Montague, P Read

2003-08-01

Theories of dopamine function are at a crossroads. Computational models derived from single-unit recordings capture changes in dopaminergic neuron firing rate as a prediction error signal. These models employ the prediction error signal in two roles: learning to predict future rewarding events and biasing action choice. Conversely, pharmacological inhibition or lesion of dopaminergic neuron function diminishes the ability of an animal to motivate behaviors directed at acquiring rewards. These lesion experiments have raised the possibility that dopamine release encodes a measure of the incentive value of a contemplated behavioral act. The most complete psychological idea that captures this notion frames the dopamine signal as carrying 'incentive salience'. On the surface, these two competing accounts of dopamine function seem incommensurate. To the contrary, we demonstrate that both of these functions can be captured in a single computational model of the involvement of dopamine in reward prediction for the purpose of reward seeking.

Disentangling the drivers of coarse woody debris behavior and carbon gas emissions during fire

NASA Astrophysics Data System (ADS)

Zhao, Weiwei; van der Werf, Guido R.; van Logtestijn, Richard S. P.; van Hal, Jurgen R.; Cornelissen, Johannes H. C.

2016-04-01

The turnover of coarse woody debris, a key terrestrial carbon pool, plays fundamental roles in global carbon cycling. Biological decomposition and fire are two main fates for dead wood turnover. Compared to slow decomposition, fire rapidly transfers organic carbon from the earth surface to the atmosphere. Both a-biotic environmental factors and biotic wood properties determine coarse wood combustion and thereby its carbon gas emissions during fire. Moisture is a key inhibitory environmental factor for fire. The properties of dead wood strongly affect how it burns either directly or indirectly through interacting with moisture. Coarse wood properties vary between plant species and between various decay stages. Moreover, if we put a piece of dead wood in the context of a forest fuel bed, the soil and wood contact might also greatly affect their fire behavior. Using controlled laboratory burns, we disentangled the effects of all these driving factors: tree species (one gymnosperms needle-leaf species, three angiosperms broad-leaf species), wood decay stages (freshly dead, middle decayed, very strongly decayed), moisture content (air-dried, 30% moisture content in mass), and soil-wood contact (on versus 3cm above the ground surface) on dead wood flammability and carbon gas efflux (CO2 and CO released in grams) during fire. Wood density was measured for all coarse wood samples used in our experiment. We found that compared to other drivers, wood decay stages have predominant positive effects on coarse wood combustion (for wood mass burned, R2=0.72 when air-dried and R2=0.52 at 30% moisture content) and associated carbon gas emissions (for CO2andCO (g) released, R2=0.55 when air-dried and R2=0.42 at 30% moisture content) during fire. Thus, wood decay accelerates wood combustion and its CO2 and CO emissions during fire, which can be mainly attributed to the decreasing wood density (for wood mass burned, R2=0.91 when air-dried and R2=0.63 at 30% moisture content) as wood becomes more decomposed. Our results provide quantitative experimental evidence for how several key abiotic and biotic factors, especially moisture content and the key underlying trait wood density, as well as their interactions, together drive coarse wood carbon turnover through fire. Our experimental data on coarse wood behavior and gas efflux during fire will help to improve the predictive power of global vegetation climate models on dead wood turnover and its feedback to climate.

Large-Scale Spacecraft Fire Safety Experiments in ISS Resupply Vehicles

NASA Technical Reports Server (NTRS)

Ruff, Gary A.; Urban, David

2013-01-01

Our understanding of the fire safety risk in manned spacecraft has been limited by the small scale of the testing we have been able to conduct in low-gravity. Fire growth and spread cannot be expected to scale linearly with sample size so we cannot make accurate predictions of the behavior of realistic scale fires in spacecraft based on the limited low-g testing to date. As a result, spacecraft fire safety protocols are necessarily very conservative and costly. Future crewed missions are expected to be longer in duration than previous exploration missions outside of low-earth orbit and accordingly, more complex in terms of operations, logistics, and safety. This will increase the challenge of ensuring a fire-safe environment for the crew throughout the mission. Based on our fundamental uncertainty of the behavior of fires in low-gravity, the need for realistic scale testing at reduced gravity has been demonstrated. To address this concern, a spacecraft fire safety research project is underway to reduce the uncertainty and risk in the design of spacecraft fire safety systems by testing at nearly full scale in low-gravity. This project is supported by the NASA Advanced Exploration Systems Program Office in the Human Exploration and Operations Mission Directorate. The activity of this project is supported by an international topical team of fire experts from other space agencies to maximize the utility of the data and to ensure the widest possible scrutiny of the concept. The large-scale space flight experiment will be conducted on three missions; each in an Orbital Sciences Corporation Cygnus vehicle after it has deberthed from the ISS. Although the experiment will need to meet rigorous safety requirements to ensure the carrier vehicle does not sustain damage, the absence of a crew allows the fire products to be released into the cabin. The tests will be fully automated with the data downlinked at the conclusion of the test before the Cygnus vehicle reenters the atmosphere. The international topical team is collaborating with the NASA team in the definition of the experiment requirements and performing supporting analysis, experimentation and technology development.

Fire behavior simulation in Mediterranean forests using the minimum travel time algorithm

Treesearch

Kostas Kalabokidis; Palaiologos Palaiologou; Mark A. Finney

2014-01-01

Recent large wildfires in Greece exemplify the need for pre-fire burn probability assessment and possible landscape fire flow estimation to enhance fire planning and resource allocation. The Minimum Travel Time (MTT) algorithm, incorporated as FlamMap's version five module, provide valuable fire behavior functions, while enabling multi-core utilization for the...

Appraising fuels and flammability in western aspen: a prescribed fire guide

Treesearch

James K. Brown; Dennis G. Simmerman

1986-01-01

Describes a method for appraising fuels and fire behavior potential in aspen forests to guide the use of prescribed fire and the preparation of fire prescriptions. Includes an illustrated classification of aspen fuels; appraisals of fireline intensity, rate of spread, adjective ratings for fire behavior and probability of burn success; and evaluations of seasonal...

Davis Fire: Fire behavior and fire effects analysis

Treesearch

LaWen T. Hollingsworth

2010-01-01

The Davis Fire presents an interesting example of fire behavior in subalpine fir, partially dead lodgepole pine with multiple age classes, and moist site Douglas-fir vegetation types. This has been summer of moderate temperatures and intermittent moisture that has kept live herbaceous and live woody moistures fairly high and dead fuel moistures at a moderate level....

Predicting fire severity using surface fuels and moisture

Treesearch

Pamela G. Sikkink; Robert E. Keane

2012-01-01

Fire severity classifications have been used extensively in fire management over the last 30 years to describe specific environmental or ecological impacts of fire on fuels, vegetation, wildlife, and soils in recently burned areas. New fire severity classifications need to be more objective, predictive, and ultimately more useful to fire management and planning. Our...

Characterization of motor units in behaving adult mice shows a wide primary range

PubMed Central

Ritter, Laura K.; Tresch, Matthew C.; Heckman, C. J.; Manuel, Marin

2014-01-01

The mouse is essential for genetic studies of motor function in both normal and pathological states. Thus it is important to consider whether the structure of motor output from the mouse is in fact analogous to that recorded in other animals. There is a striking difference in the basic electrical properties of mouse motoneurons compared with those in rats, cats, and humans. The firing evoked by injected currents produces a unique frequency-current (F-I) function that emphasizes recruitment of motor units at their maximum force. These F-I functions, however, were measured in anesthetized preparations that lacked two key components of normal synaptic input: high levels of synaptic noise and neuromodulatory inputs. Recent studies suggest that the alterations in the F-I function due to these two components are essential for recreating firing behavior of motor units in human subjects. In this study we provide the first data on firing patterns of motor units in the awake mouse, focusing on steady output in quiet stance. The resulting firing patterns did not match the predictions from the mouse F-I behaviors but instead revealed rate modulation across a remarkably wide range (10–60 Hz). The low end of the firing range may be due to changes in the F-I relation induced by synaptic noise and neuromodulatory inputs. The high end of the range may indicate that, unlike other species, quiet standing in the mouse involves recruitment of relatively fast-twitch motor units. PMID:24805075

Characterization of motor units in behaving adult mice shows a wide primary range.

PubMed

Ritter, Laura K; Tresch, Matthew C; Heckman, C J; Manuel, Marin; Tysseling, Vicki M

2014-08-01

The mouse is essential for genetic studies of motor function in both normal and pathological states. Thus it is important to consider whether the structure of motor output from the mouse is in fact analogous to that recorded in other animals. There is a striking difference in the basic electrical properties of mouse motoneurons compared with those in rats, cats, and humans. The firing evoked by injected currents produces a unique frequency-current (F-I) function that emphasizes recruitment of motor units at their maximum force. These F-I functions, however, were measured in anesthetized preparations that lacked two key components of normal synaptic input: high levels of synaptic noise and neuromodulatory inputs. Recent studies suggest that the alterations in the F-I function due to these two components are essential for recreating firing behavior of motor units in human subjects. In this study we provide the first data on firing patterns of motor units in the awake mouse, focusing on steady output in quiet stance. The resulting firing patterns did not match the predictions from the mouse F-I behaviors but instead revealed rate modulation across a remarkably wide range (10-60 Hz). The low end of the firing range may be due to changes in the F-I relation induced by synaptic noise and neuromodulatory inputs. The high end of the range may indicate that, unlike other species, quiet standing in the mouse involves recruitment of relatively fast-twitch motor units. Copyright © 2014 the American Physiological Society.

Experimental And Numerical Evaluation Of Gaseous Agents For Suppressing Cup-Burner Flames In Low Gravity

NASA Technical Reports Server (NTRS)

Takahashi, Fumiaki; Linteris, Gregory T.; Katta, Viswanath R.

2003-01-01

Longer duration missions to the moon, to Mars, and on the International Space Station (ISS) increase the likelihood of accidental fires. NASA's fire safety program for human-crewed space flight is based largely on removing ignition sources and controlling the flammability of the material on-board. There is ongoing research to improve the flammability characterization of materials in low gravity; however, very little research has been conducted on fire suppression in the low-gravity environment. Although the existing suppression systems aboard the Space Shuttle (halon 1301, CF3Br) and the ISS (CO2 or water-based form) may continue to be used, alternative effective agents or techniques are desirable for long-duration missions. The goal of the present investigation is to: (1) understand the physical and chemical processes of fire suppression in various gravity and O2 levels simulating spacecraft, Mars, and moon missions; (2) provide rigorous testing of analytical models, which include detailed combustion-suppression chemistry and radiation sub-models, so that the model can be used to interpret (and predict) the suppression behavior in low gravity; and (3) provide basic research results useful for advances in space fire safety technology, including new fire-extinguishing agents and approaches.

Differences in human versus lightning fires between urban and rural areas of the boreal forest in interior Alaska

USGS Publications Warehouse

Calef, Monika; Varvak, Anna; McGuire, A. David

2017-01-01

In western North America, the carbon-rich boreal forest is experiencing warmer temperatures, drier conditions and larger and more frequent wildfires. However, the fire regime is also affected by direct human activities through suppression, ignition, and land use changes. Models are important predictive tools for understanding future conditions but they are based on regional generalizations of wildfire behavior and weather that do not adequately account for the complexity of human–fire interactions. To achieve a better understanding of the intensity of human influence on fires in this sparsely populated area and to quantify differences between human and lightning fires, we analyzed fires by both ignition types in regard to human proximity in urban (the Fairbanks subregion) and rural areas of interior Alaska using spatial (Geographic Information Systems) and quantitative analysis methods. We found substantial differences in drivers of wildfire: while increases in fire ignitions and area burned were caused by lightning in rural interior Alaska, in the Fairbanks subregion these increases were due to human fires, especially in the wildland urban interface. Lightning fires are starting earlier and fires are burning longer, which is much more pronounced in the Fairbanks subregion than in rural areas. Human fires differed from lightning fires in several ways: they started closer to settlements and highways, burned for a shorter duration, were concentrated in the Fairbanks subregion, and often occurred outside the brief seasonal window for lightning fires. This study provides important insights that improve our understanding of the direct human influence on recently observed changes in wildfire regime with implications for both fire modeling and fire management.

Daily and 3-hourly Variability in Global Fire Emissions and Consequences for Atmospheric Model Predictions of Carbon Monoxide

NASA Technical Reports Server (NTRS)

Mu, M.; Randerson, J. T.; vanderWerf, G. R.; Giglio, L.; Kasibhatla, P.; Morton, D.; Collatz, G. J.; DeFries, R. S.; Hyer, E. J.; Prins, E. M.;

Posterior cingulate cortex mediates outcome-contingent allocation of behavior

PubMed Central

Hayden, Benjamin Y.; Nair, Amrita C.; McCoy, Allison N.; Platt, Michael L.

2008-01-01

SUMMARY Adaptive decision making requires selecting an action and then monitoring its consequences to improve future decisions. The neuronal mechanisms supporting action evaluation and subsequent behavioral modification, however, remain poorly understood. To investigate the contribution of posterior cingulate cortex (CGp) to these processes, we recorded activity of single neurons in monkeys performing a gambling task in which the reward outcome of each choice strongly influenced subsequent choices. We found that CGp neurons signaled reward outcomes in a nonlinear fashion, and that outcome-contingent modulations in firing rate persisted into subsequent trials. Moreover, firing rate on any one trial predicted switching to the alternative option on the next trial. Finally, microstimulation in CGp following risky choices promoted a preference reversal for the safe option on the following trial. Collectively, these results demonstrate that CGp directly contributes to the evaluative processes that support dynamic changes in decision making in volatile environments. PMID:18940585

Study of thermal and fire behavior of wood fiber/thermoplastic composite materials

NASA Astrophysics Data System (ADS)

Oladipo, Adedejo Bukola

The fire safety characteristics of wood fiber/thermoplastic composite materials were investigated in this study. Composites comprising wood fiber fillers and polymeric binders are known to offer many advantages such as good strength to weight ratio, ease of manufacture, low cost, and the possibility for recycling. In spite of these advantages however, the fire safety question of plastic-based materials is an important one since they can, under certain conditions, drip or run, under fire, thereby potentially spreading fire from one location to the other. It is important therefore to understand the fire behavior of such a composite if the advantages it offers are to be fully utilized. To this end, numerical and experimental studies of opposed flow flame spread over the composite were conducted with emphasis on the influences of gravity, material thermal property variations, and finite-rate chemistry on the rate of spread. The thermal properties of the composite material, needed for opposed flame spread computations, were first determined using a combination of inverse heat conduction and non-linear parameter estimation procedures. The influences of wood fiber mass fraction and temperature on the effective thermal properties of the composite were established. The means for predicting the effective properties from those of the individual constituents were also examined and the results showed that the composite is close to being isotropic. The experimental and numerical methods used to determine the thermal properties of the composite were also adapted for the investigation of various proprietary automobile sound blanket materials to assess their effectiveness as thermal barriers separating the engine compartment from the passenger cabin. The results of opposed flame spread study over the composite suggests that, for opposed flow velocities lower than about 245 cm/s, finite rate chemistry will dominate the spread process when the oxygen mass fraction is 70% or less. Above this limit, heat transfer from the flame to the unburned fuel ahead seems to be the dominant factor. Also, the composite was observed to exhibit wood-like fire behavior when the wood fiber mass fraction is 40% or more.

An uncommon case of random fire-setting behavior associated with Todd paralysis: a case report.

PubMed

Kanehisa, Masayuki; Morinaga, Katsuhiko; Kohno, Hisae; Maruyama, Yoshihiro; Ninomiya, Taiga; Ishitobi, Yoshinobu; Tanaka, Yoshihiro; Tsuru, Jusen; Hanada, Hiroaki; Yoshikawa, Tomoya; Akiyoshi, Jotaro

2012-08-31

The association between fire-setting behavior and psychiatric or medical disorders remains poorly understood. Although a link between fire-setting behavior and various organic brain disorders has been established, associations between fire setting and focal brain lesions have not yet been reported. Here, we describe the case of a 24-year-old first time arsonist who suffered Todd's paralysis prior to the onset of a bizarre and random fire-setting behavior. A case of a 24-year-old man with a sudden onset of a bizarre and random fire-setting behavior is reported. The man, who had been arrested on felony arson charges, complained of difficulties concentrating and of recent memory disturbances with leg weakness. A video-EEG recording demonstrated a close relationship between the focal motor impairment and a clear-cut epileptic ictal discharge involving the bilateral motor cortical areas. The SPECT result was statistically analyzed by comparing with standard SPECT images obtained from our institute (easy Z-score imaging system; eZIS). eZIS revealed hypoperfusion in cingulate cortex, basal ganglia and hyperperfusion in frontal cortex,. A neuropsychological test battery revealed lower than normal scores for executive function, attention, and memory, consistent with frontal lobe dysfunction. The fire-setting behavior and Todd's paralysis, together with an unremarkable performance on tests measuring executive function fifteen months prior, suggested a causal relationship between this organic brain lesion and the fire-setting behavior. The case describes a rare and as yet unreported association between random, impulse-driven fire-setting behavior and damage to the brain and suggests a disconnection of frontal lobe structures as a possible pathogenic mechanism.

Application of wildfire spread and behavior models to assess fire probability and severity in the Mediterranean region

NASA Astrophysics Data System (ADS)

Salis, Michele; Arca, Bachisio; Bacciu, Valentina; Spano, Donatella; Duce, Pierpaolo; Santoni, Paul; Ager, Alan; Finney, Mark

2010-05-01

Characterizing the spatial pattern of large fire occurrence and severity is an important feature of the fire management planning in the Mediterranean region. The spatial characterization of fire probabilities, fire behavior distributions and value changes are key components for quantitative risk assessment and for prioritizing fire suppression resources, fuel treatments and law enforcement. Because of the growing wildfire severity and frequency in recent years (e.g.: Portugal, 2003 and 2005; Italy and Greece, 2007 and 2009), there is an increasing demand for models and tools that can aid in wildfire prediction and prevention. Newer wildfire simulation systems offer promise in this regard, and allow for fine scale modeling of wildfire severity and probability. Several new applications has resulted from the development of a minimum travel time (MTT) fire spread algorithm (Finney, 2002), that models the fire growth searching for the minimum time for fire to travel among nodes in a 2D network. The MTT approach makes computationally feasible to simulate thousands of fires and generate burn probability and fire severity maps over large areas. The MTT algorithm is imbedded in a number of research and fire modeling applications. High performance computers are typically used for MTT simulations, although the algorithm is also implemented in the FlamMap program (www.fire.org). In this work, we described the application of the MTT algorithm to estimate spatial patterns of burn probability and to analyze wildfire severity in three fire prone areas of the Mediterranean Basin, specifically Sardinia (Italy), Sicily (Italy) and Corsica (France) islands. We assembled fuels and topographic data for the simulations in 500 x 500 m grids for the study areas. The simulations were run using 100,000 ignitions under weather conditions that replicated severe and moderate weather conditions (97th and 70th percentile, July and August weather, 1995-2007). We used both random ignition locations and ignition probability grids (1000 x 1000 m) built from historical fire data (1995-2007). The simulation outputs were then examined to understand relationships between burn probability and specific vegetation types and ignition sources. Wildfire threats to specific values of human interest were quantified to map landscape patterns of wildfire risk. The simulation outputs also allowed us to differentiate between areas of the landscape that were progenitors of fires versus "victims" of large fires. The results provided spatially explicit data on wildfire likelihood and intensity that can be used in a variety of strategic and tactical planning forums to mitigate wildfire threats to human and other values in the Mediterranean Basin.

pigk Mutation underlies macho behavior and affects Rohon-Beard cell excitability

PubMed Central

Carmean, V.; Yonkers, M. A.; Tellez, M. B.; Willer, J. R.; Willer, G. B.; Gregg, R. G.; Geisler, R.; Neuhauss, S. C.

2015-01-01

The study of touch-evoked behavior allows investigation of both the cells and circuits that generate a response to tactile stimulation. We investigate a touch-insensitive zebrafish mutant, macho (maco), previously shown to have reduced sodium current amplitude and lack of action potential firing in sensory neurons. In the genomes of mutant but not wild-type embryos, we identify a mutation in the pigk gene. The encoded protein, PigK, functions in attachment of glycophosphatidylinositol anchors to precursor proteins. In wild-type embryos, pigk mRNA is present at times when mutant embryos display behavioral phenotypes. Consistent with the predicted loss of function induced by the mutation, knock-down of PigK phenocopies maco touch insensitivity and leads to reduced sodium current (INa) amplitudes in sensory neurons. We further test whether the genetic defect in pigk underlies the maco phenotype by overexpressing wild-type pigk in mutant embryos. We find that ubiquitous expression of wild-type pigk rescues the touch response in maco mutants. In addition, for maco mutants, expression of wild-type pigk restricted to sensory neurons rescues sodium current amplitudes and action potential firing in sensory neurons. However, expression of wild-type pigk limited to sensory cells of mutant embryos does not allow rescue of the behavioral touch response. Our results demonstrate an essential role for pigk in generation of the touch response beyond that required for maintenance of proper INa density and action potential firing in sensory neurons. PMID:26133798

Seasonal predictions for wildland fire severity

Treesearch

Shyh-Chin Chen; Haiganoush Preisler; Francis Fujioka; John W. Benoit; John O. Roads

2009-01-01

The National Fire Danger Rating System (NFDRS) indices deduced from the monthly to seasonal predictions of a meteorological climate model at 50-km grid space from January 1998 through December 2003 were used in conjunction with a probability model to predict the expected number of fire occurrences and large fires over the U.S. West. The short-term climate forecasts are...

Comparing alternative tree canopy cover estimates derived from digital aerial photography and field-based assessments

Treesearch

Tracey S. Frescino; Gretchen G. Moisen

2012-01-01

A spatially-explicit representation of live tree canopy cover, such as the National Land Cover Dataset (NLCD) percent tree canopy cover layer, is a valuable tool for many applications, such as defining forest land, delineating wildlife habitat, estimating carbon, and modeling fire risk and behavior. These layers are generated by predictive models wherein their accuracy...

FireStem2D — A two-dimensional heat transfer model for simulating tree stem injury in fires

Treesearch

Efthalia K. Chatziefstratiou; Gil Bohrer; Anthony S. Bova; Ravishankar Subramanian; Renato P.M. Frasson; Amy Scherzer; Bret W. Butler; Matthew B. Dickinson

2013-01-01

FireStem2D, a software tool for predicting tree stem heating and injury in forest fires, is a physically-based, two-dimensional model of stem thermodynamics that results from heating at the bark surface. It builds on an earlier one-dimensional model (FireStem) and provides improved capabilities for predicting fire-induced mortality and injury before a fire occurs by...

Prevalence and correlates of fire-setting in the United States: results from the National Epidemiological Survey on Alcohol and Related Conditions.

PubMed

Vaughn, Michael G; Fu, Qiang; Delisi, Matt; Wright, John Paul; Beaver, Kevin M; Perron, Brian E; Howard, Matthew O

2010-01-01

Fire-setting is a serious and costly form of antisocial behavior. Our objective in this study was to examine the prevalence and correlates of intentional fire-setting behavior in the United States. Data were derived from a nationally representative sample of US residents 18 years and older. Structured psychiatric interviews (N = 43,093) were completed by trained lay interviewers between 2001 and 2002. Fire-setting as well as mood, anxiety, substance use, and personality disorders of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition were assessed with the Alcohol Use Disorder and Associated Disabilities Interview Schedule (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition) version. The prevalence of lifetime fire-setting in the US population was 1.0%. Respondents who were men, white, 18 to 35 years old, born in the United States, and living in the western region of the United States had significantly higher rates of fire-setting than their counterparts. Fire-setting was significantly associated with a wide range of antisocial behaviors. Multivariate logistic regression analyses identified strong associations between lifetime alcohol and marijuana use disorders, conduct disorder, antisocial and obsessive-compulsive personality disorders, and family history of antisocial behavior. Intentional illicit fire-setting behavior is associated with a broad array of antisocial behaviors and psychiatric comorbidities. Given the substantial personal and social costs related to arson, prevention and treatment interventions targeting fire-setters potentially could save lives and property. 2010 Elsevier Inc. All rights reserved.

Topographic and fire weather controls of fire refugia in forested ecosystems of northwestern North America

USGS Publications Warehouse

Krawchuk, Meg A.; Haire, Sandra L.; Coop, Jonathan D.; Parisien, Marc-Andre; Whitman, Ellen; Chong, Geneva W.; Miller, Carol

2016-01-01

for seven study fires that burned in conifer-dominated forested landscapes of the Western Cordillera of Canada between 2001 and 2014. We fit nine models, each for distinct levels of fire weather and terrain ruggedness. Our framework revealed that the predictability and abundance of fire refugia varied among these environmental settings. We observed highest predictability under moderate fire weather conditions and moderate terrain ruggedness (ROC-AUC = 0.77), and lowest predictability in flatter landscapes and under high fire weather conditions (ROC-AUC = 0.63–0.68). Catchment slope, local aspect, relative position, topographic wetness, topographic convergence, and local slope all contributed to discriminating where refugia occur but the relative importance of these topographic controls differed among environments. Our framework allows us to characterize the predictability of contemporary fire refugia across multiple environmental settings and provides important insights for ecosystem resilience, wildfire management, conservation planning, and climate change adaptation.

Fire behavior sensor package remote trigger design

Treesearch

Dan Jimenez; Jason Forthofer; James Reardon; Bret Butler

2007-01-01

Fire behavior characteristics (such as temperature, radiant and total heat flux, 2- and 3-dimensional velocities, and air flow) are extremely difficult to measure insitu. Although insitu sensor packages are capable of such measurements in realtime, it is also essential to acquire video documentation as a means of better understanding the fire behavior data recorded by...

The simulation of surface fire spread based on Rothermel model in windthrow area of Changbai Mountain (Jilin, China)

NASA Astrophysics Data System (ADS)

Yin, Hang; Jin, Hui; Zhao, Ying; Fan, Yuguang; Qin, Liwu; Chen, Qinghong; Huang, Liya; Jia, Xiang; Liu, Lijie; Dai, Yuhong; Xiao, Ying

2018-03-01

The forest-fire not only brings great loss to natural resources, but also destructs the ecosystem and reduces the soil fertility, causing some natural disasters as soil erosion and debris flow. However, due to the lack of the prognosis for forest fire spreading trend in forest fire fighting, it is difficult to formulate rational and effective fire-fighting scheme. In the event of forest fire, achieving accurate judgment to the fire behavior would greatly improve the fire-fighting efficiency, and reduce heavy losses caused by fire. Researches on forest fire spread simulation can effectively reduce the loss of disasters. The present study focused on the simulation of "29 May 2012" wildfire in windthrow area of Changbai Mountain. Basic data were retrieved from the "29 May 2012" wildfire and field survey. A self-development forest fire behavior simulated program based on Rothermel Model was used in the simulation. Kappa coefficient and Sørensen index were employed to evaluate the simulation accuracy. The results showed that: The perimeter of simulated burned area was 4.66 km, the area was 56.47 hm2 and the overlapped burned area was 33.68 hm2, and the estimated rate of fire spread was 0.259 m/s. Between the simulated fire and actual fire, the Kappa coefficient was 0.7398 and the Sørensen co-efficient was 0.7419. This proved the application of Rothermel model to conduct fire behavior simulation in windthrow meadow was feasible. It can achieve the goal of forecasting for the spread behavior in windthrow area of Changbai Mountain. Thus, our self-development program based on the Rothermel model can provide a effective forecast of fire spread, which will facilitate the fire suppression work.

Report of the Army Scientific Advisory Panel Ad Hoc Group on Fire Suppression

DTIC Science & Technology

1975-07-01

initially should be provided a nucleus of a seven- person technical staff composed of one 0-6 combat arme officer as Director, two senior behavioral ...If the suppressee perceives the fire as being reactive to his own behavior then the personal danger factor will be reinforced,1 Fire...that is not periodic hut also not reactive to his behavior may be like periodic fire in its personal threat except more difficult to

Simulating effects of fire on northern Rocky Mountain landscapes with the ecological process model FIRE-BGC.

PubMed

Keane, R E; Ryan, K C; Running, S W

1996-03-01

A mechanistic, biogeochemical succession model, FIRE-BGC, was used to investigate the role of fire on long-term landscape dynamics in northern Rocky Mountain coniferous forests of Glacier National Park, Montana, USA. FIRE-BGC is an individual-tree model-created by merging the gap-phase process-based model FIRESUM with the mechanistic ecosystem biogeochemical model FOREST-BGC-that has mixed spatial and temporal resolution in its simulation architecture. Ecological processes that act at a landscape level, such as fire and seed dispersal, are simulated annually from stand and topographic information. Stand-level processes, such as tree establishment, growth and mortality, organic matter accumulation and decomposition, and undergrowth plant dynamics are simulated both daily and annually. Tree growth is mechanistically modeled based on the ecosystem process approach of FOREST-BGC where carbon is fixed daily by forest canopy photosynthesis at the stand level. Carbon allocated to the tree stem at the end of the year generates the corresponding diameter and height growth. The model also explicitly simulates fire behavior and effects on landscape characteristics. We simulated the effects of fire on ecosystem characteristics of net primary productivity, evapotranspiration, standing crop biomass, nitrogen cycling and leaf area index over 200 years for the 50,000-ha McDonald Drainage in Glacier National Park. Results show increases in net primary productivity and available nitrogen when fires are included in the simulation. Standing crop biomass and evapotranspiration decrease under a fire regime. Shade-intolerant species dominate the landscape when fires are excluded. Model tree increment predictions compared well with field data.

Differences in Human Versus Lightning Fires with Human Proximity at Two Spatial Scales in Interior Alaska

NASA Astrophysics Data System (ADS)

Calef, M. P.; Varvak, A.; McGuire, A. D.

2017-12-01

The boreal forest contains significant amounts of carbon in its biomass and soils and is currently responding to a rapidly changing climate. This is leading to warmer temperatures, drier conditions and larger and more frequent wildfires in western North America. However, the fire regime is also affected by direct human activities through suppression, ignition, and land use changes. Models are important predictive tools for understanding future conditions but they are based on regional generalizations of wildfire behavior and do not account for the complexity of human-fire interactions. In order to achieve a better understanding of the human influence on fires and how human fires differ from lightning fires, we analyzed both in regard to human proximity at two spatial scales (the Fairbanks subregion and Interior Alaska) using ArcGIS and quantitative analysis methods. We found that area burned is increasing across the region at 3% per year and is driven by increase in area burned by lightning while human-caused area burned has been decreasing recently especially in the WUI near Fairbanks. Human fires differed from lightning fires in several ways: they occurred significantly closer to settlements and highways, burned for a shorter duration, and were not as restricted to a brief seasonal window. The fire regime in the much more populated Fairbanks subregion has been altered by human activity: it experienced substantially more human fire ignitions along with a larger area burned though the human influence decreases with distance. This study provides important insights into spatial patterns of human influences on fires and provides useful information for fire modeling and fire management.

Assessment and Prediction of Natural Hazards from Satellite Imagery

PubMed Central

Gillespie, Thomas W.; Chu, Jasmine; Frankenberg, Elizabeth; Thomas, Duncan

2013-01-01

Since 2000, there have been a number of spaceborne satellites that have changed the way we assess and predict natural hazards. These satellites are able to quantify physical geographic phenomena associated with the movements of the earth’s surface (earthquakes, mass movements), water (floods, tsunamis, storms), and fire (wildfires). Most of these satellites contain active or passive sensors that can be utilized by the scientific community for the remote sensing of natural hazards over a number of spatial and temporal scales. The most useful satellite imagery for the assessment of earthquake damage comes from high-resolution (0.6 m to 1 m pixel size) passive sensors and moderate resolution active sensors that can quantify the vertical and horizontal movement of the earth’s surface. High-resolution passive sensors have been used to successfully assess flood damage while predictive maps of flood vulnerability areas are possible based on physical variables collected from passive and active sensors. Recent moderate resolution sensors are able to provide near real time data on fires and provide quantitative data used in fire behavior models. Limitations currently exist due to atmospheric interference, pixel resolution, and revisit times. However, a number of new microsatellites and constellations of satellites will be launched in the next five years that contain increased resolution (0.5 m to 1 m pixel resolution for active sensors) and revisit times (daily ≤ 2.5 m resolution images from passive sensors) that will significantly improve our ability to assess and predict natural hazards from space. PMID:25170186

Firing patterns transition and desynchronization induced by time delay in neural networks

NASA Astrophysics Data System (ADS)

Huang, Shoufang; Zhang, Jiqian; Wang, Maosheng; Hu, Chin-Kun

2018-06-01

We used the Hindmarsh-Rose (HR) model (Hindmarsh and Rose, 1984) to study the effect of time delay on the transition of firing behaviors and desynchronization in neural networks. As time delay is increased, neural networks exhibit diversity of firing behaviors, including regular spiking or bursting and firing patterns transitions (FPTs). Meanwhile, the desynchronization of firing and unstable bursting with decreasing amplitude in neural system, are also increasingly enhanced with the increase of time delay. Furthermore, we also studied the effect of coupling strength and network randomness on these phenomena. Our results imply that time delays can induce transition and desynchronization of firing behaviors in neural networks. These findings provide new insight into the role of time delay in the firing activities of neural networks, and can help to better understand the firing phenomena in complex systems of neural networks. A possible mechanism in brain that can cause the increase of time delay is discussed.

Optimization of the resources management in fighting wildfires.

PubMed

Martin-Fernández, Susana; Martínez-Falero, Eugenio; Pérez-González, J Manuel

2002-09-01

Wildfires lead to important economic, social, and environmental losses, especially in areas of Mediterranean climate where they are of a high intensity and frequency. Over the past 30 years there has been a dramatic surge in the development and use of fire spread models. However, given the chaotic nature of environmental systems, it is very difficult to develop real-time fire-extinguishing models. This article proposes a method of optimizing the performance of wildfire fighting resources such that losses are kept to a minimum. The optimization procedure includes discrete simulation algorithms and Bayesian optimization methods for discrete and continuous problems (simulated annealing and Bayesian global optimization). Fast calculus algorithms are applied to provide optimization outcomes in short periods of time such that the predictions of the model and the real behavior of the fire, combat resources, and meteorological conditions are similar. In addition, adaptive algorithms take into account the chaotic behavior of wildfire so that the system can be updated with data corresponding to the real situation to obtain a new optimum solution. The application of this method to the Northwest Forest of Madrid (Spain) is also described. This application allowed us to check that it is a helpful tool in the decision-making process.

Optimization of the Resources Management in Fighting Wildfires

NASA Astrophysics Data System (ADS)

Martin-Fernández, Susana; Martínez-Falero, Eugenio; Pérez-González, J. Manuel

2002-09-01

Wildfires lead to important economic, social, and environmental losses, especially in areas of Mediterranean climate where they are of a high intensity and frequency. Over the past 30 years there has been a dramatic surge in the development and use of fire spread models. However, given the chaotic nature of environmental systems, it is very difficult to develop real-time fire-extinguishing models. This article proposes a method of optimizing the performance of wildfire fighting resources such that losses are kept to a minimum. The optimization procedure includes discrete simulation algorithms and Bayesian optimization methods for discrete and continuous problems (simulated annealing and Bayesian global optimization). Fast calculus algorithms are applied to provide optimization outcomes in short periods of time such that the predictions of the model and the real behavior of the fire, combat resources, and meteorological conditions are similar. In addition, adaptive algorithms take into account the chaotic behavior of wildfire so that the system can be updated with data corresponding to the real situation to obtain a new optimum solution. The application of this method to the Northwest Forest of Madrid (Spain) is also described. This application allowed us to check that it is a helpful tool in the decision-making process.

Fire-danger rating and observed wildfire behavior in the Northeastern United States.

Treesearch

Donald A. Haines; William A. Main; Albert J. Simard

1986-01-01

Compares the 1978 National Fire-Danger Rating System and its 20 fuel models, along with other danger rating systems, with observed fire behavior and rates the strengths and weaknesses of models and systems.

Synchronization transition of a coupled system composed of neurons with coexisting behaviors near a Hopf bifurcation

NASA Astrophysics Data System (ADS)

Jia, Bing

2014-05-01

The coexistence of a resting condition and period-1 firing near a subcritical Hopf bifurcation point, lying between the monostable resting condition and period-1 firing, is often observed in neurons of the central nervous systems. Near such a bifurcation point in the Morris—Lecar (ML) model, the attraction domain of the resting condition decreases while that of the coexisting period-1 firing increases as the bifurcation parameter value increases. With the increase of the coupling strength, and parameter and initial value dependent synchronization transition processes from non-synchronization to compete synchronization are simulated in two coupled ML neurons with coexisting behaviors: one neuron chosen as the resting condition and the other the coexisting period-1 firing. The complete synchronization is either a resting condition or period-1 firing dependent on the initial values of period-1 firing when the bifurcation parameter value is small or middle and is period-1 firing when the parameter value is large. As the bifurcation parameter value increases, the probability of the initial values of a period-1 firing neuron that lead to complete synchronization of period-1 firing increases, while that leading to complete synchronization of the resting condition decreases. It shows that the attraction domain of a coexisting behavior is larger, the probability of initial values leading to complete synchronization of this behavior is higher. The bifurcations of the coupled system are investigated and discussed. The results reveal the complex dynamics of synchronization behaviors of the coupled system composed of neurons with the coexisting resting condition and period-1 firing, and are helpful to further identify the dynamics of the spatiotemporal behaviors of the central nervous system.

Validating the Malheur model for predicting ponderosa pine post-fire mortality using 24 fires in the Pacific Northwest, USA

Treesearch

Walter G. Thies; Douglas J. Westlind

2012-01-01

Fires, whether intentionally or accidentally set, commonly occur in western interior forests of the US. Following fire, managers need the ability to predict mortality of individual trees based on easily observed characteristics. Previously, a two-factor model using crown scorch and bole scorch proportions was developed with data from 3415 trees for predicting the...

The Jeffcott equations in nonlinear rotordynamics

NASA Technical Reports Server (NTRS)

Zalik, R. A.

1987-01-01

The Jeffcott equations are a system of coupled differential equations representing the behavior of a rotating shaft. This is a simple model which allows investigation of the basic dynamic behavior of rotating machinery. Nolinearities can be introduced by taking into consideration deadband, side force, and rubbing, among others. The properties of the solutions of the Jeffcott equations with deadband are studied. In particular, it is shown how bounds for the solution of these equations can be obtained from bounds for the solutions of the linearized equations. By studying the behavior of the Fourier transforms of the solutions, we are also able to predict the onset of destructive vibrations. These conclusions are verified by means of numerical solutions of the equations, and of power spectrum density (PSD) plots. This study offers insight into a possible detection method to determine pump stability margins during flight and hot fire tests, and was motivated by the need to explain a phenomenon observed in the development phase of the cryogenic pumps of the Space Shuttle, during hot fire ground testing; namely, the appearance of vibrations at frequencies that could not be accounted for by means of linear models.

1/f neural noise and electrophysiological indices of contextual prediction in aging.

PubMed

Dave, S; Brothers, T A; Swaab, T Y

2018-07-15

Prediction of upcoming words during reading has been suggested to enhance the efficiency of discourse processing. Emerging models have postulated that predictive mechanisms require synchronous firing of neural networks, but to date, this relationship has been investigated primarily through oscillatory activity in narrow frequency bands. A recently-developed measure proposed to reflect broadband neural activity - and thereby synchronous neuronal firing - is 1/f neural noise extracted from EEG spectral power. Previous research has indicated that this measure of 1/f neural noise changes across the lifespan, and these neural changes predict age-related behavioral impairments in visual working memory. Using a cross-sectional sample of young and older adults, we examined age-related changes in 1/f neural noise and whether this measure predicted ERP correlates of successful lexical prediction during discourse comprehension. 1/f neural noise across two different language tasks revealed high within-subject correlations, indicating that this measure can provide a reliable index of individualized patterns of neural activation. In addition to age, 1/f noise was a significant predictor of N400 effects of successful lexical prediction; however, noise did not mediate age-related declines in other ERP effects. We discuss broader implications of these findings for theories of predictive processing, as well as potential applications of 1/f noise across research populations. Copyright © 2018 Elsevier B.V. All rights reserved.

Caudate neuronal recording in freely behaving animals following acute and chronic dose response methylphenidate exposure

PubMed Central

Claussen, Catherine M; Dafny, Nachum

2016-01-01

The misuse and abuse of the psychostimulant, methylphenidate (MPD) the drug of choice in the treatment of attention deficit hyperactivity disorder (ADHD) has seen a sharp uprising in recent years among both youth and adults for its cognitive enhancing effects and for recreational purposes. This uprise in illicit use has lead to many questions concerning the long term consequences of MPD exposure. The objective of this study was to record animal behavior concomitantly with the caudate nucleus (CN) neuronal activity following acute and repetitive (chronic) dose response exposure to methylphenidate (MPD). A saline control and three MPD dose (0.6, 2.5, and 10.0 mg/kg) groups were used. Behaviorally, the same MPD dose in some animals following chronic MPD exposure elicited behavioral sensitization and other animals elicited behavioral tolerance. Based on this finding, the CN neuronal population recorded from animals expressing behavioral sensitization were also evaluated separately from CN neurons recorded from animals expressing behavioral tolerance to chronic MPD exposure, respectively. Significant differences in CN neuronal population responses between the behaviorally sensitized and the behaviorally tolerant animals was observed for the 2.5 and 10.0 mg/kg MPD exposed groups. For 2.5 mg/kg MPD, behaviorally sensitized animals responded by decreasing their firing rates while behaviorally tolerant animals showed mainly an increase in their firing rates. The CN neuronal responses recorded from the behaviorally sensitized animals following 10.0 mg/kg MPD responded by increasing their firing rates whereas the CN neuronal recordings from the behaviorally tolerant animals showed that approximately half decreased their firing rates in response to 10.0 mg/kg MPD exposure. The comparison of percentage change in neuronal firing rates showed that the behaviorally tolerant animals trended to exhibit increases in their neuronal firing rates at ED1 following initial MPD exposure and oppositely at ED10 MPD rechallenge. While the behaviorally sensitized animals in general increased in their percentage change of firing rats were observed following acute 10.0 mg/kg MPD and the behaviorally sensitized 10.0 mg/kg MPD animals and a robust increase in neuronal firing rates at ED1 and ED10 rechallenge. These results suggest the need to first individually analyze animal behavioral activity, and than to evaluate the neuronal responses to the drug based on the animals behavioral response to chronic MPD exposure. PMID:26101057

Climate drives inter-annual variability in probability of high severity fire occurrence in the western United States

NASA Astrophysics Data System (ADS)

Keyser, Alisa; Westerling, Anthony LeRoy

2017-05-01

A long history of fire suppression in the western United States has significantly changed forest structure and ecological function, leading to increasingly uncharacteristic fires in terms of size and severity. Prior analyses of fire severity in California forests showed that time since last fire and fire weather conditions predicted fire severity very well, while a larger regional analysis showed that topography and climate were important predictors of high severity fire. There has not yet been a large-scale study that incorporates topography, vegetation and fire-year climate to determine regional scale high severity fire occurrence. We developed models to predict the probability of high severity fire occurrence for the western US. We predict high severity fire occurrence with some accuracy, and identify the relative importance of predictor classes in determining the probability of high severity fire. The inclusion of both vegetation and fire-year climate predictors was critical for model skill in identifying fires with high fractional fire severity. The inclusion of fire-year climate variables allows this model to forecast inter-annual variability in areas at future risk of high severity fire, beyond what slower-changing fuel conditions alone can accomplish. This allows for more targeted land management, including resource allocation for fuels reduction treatments to decrease the risk of high severity fire.

Fire behavior in northern Rocky Mountain forests

Treesearch

J. S. Barrows

1951-01-01

Knowledge of fire behavior is an essential requirement for firefighters. Successful fire control operations depend, first of all, upon the ability of the protection forces to judge where and when fires will start and how they will behave once ignition takes place. Every member of the firefighting team from ranger to smokechaser must be able to make reliable estimates...

Putting out fire with gasoline: pitfalls in the silvicultural treatment of canopy fuels

Treesearch

Christopher R. Keyes; J. Morgan Varner

2007-01-01

There is little question that forest stand structure is directly related to fire behavior, and that canopy fuel structure may be altered using silvicultural methods to successfully modify forest fire behavior and reduce susceptibility to crown fire initiation and spread. Silvicultural treatments can remediate hazardous stand structures that have developed as a result...

Modeling fuels and fire effects in 3D: Model description and applications

Treesearch

Francois Pimont; Russell Parsons; Eric Rigolot; Francois de Coligny; Jean-Luc Dupuy; Philippe Dreyfus; Rodman R. Linn

2016-01-01

Scientists and managers critically need ways to assess how fuel treatments alter fire behavior, yet few tools currently exist for this purpose.We present a spatially-explicit-fuel-modeling system, FuelManager, which models fuels, vegetation growth, fire behavior (using a physics-based model, FIRETEC), and fire effects. FuelManager's flexible approach facilitates...

Chapter 2: Fire and Fuels Extension: Model description

Treesearch

Sarah J. Beukema; Elizabeth D. Reinhardt; Julee A. Greenough; Donald C. E. Robinson; Werner A. Kurz

2003-01-01

The Fire and Fuels Extension to the Forest Vegetation Simulator is a model that simulates fuel dynamics and potential fire behavior over time, in the context of stand development and management. Existing models are used to represent forest stand development (the Forest Vegetation Simulator, Wykoff and others 1982), fire behavior (Rothermel 1972, Van Wagner 1977, and...

Fire fighting aboard ships. Volume 1: Hazard analysis and behavior of combustible materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stavitskiy, M.G.; Kortunov, M.F.; Sidoryuk, V.M.

1983-01-01

The volume zeros in on fire hazards on ships afloat or under construction/repair. It examines fire hazards peculiar to ships carrying particular cargoes, such as dry-cargo ships, tankers, and factory and fishing vessels. This volume examines specific features of fire-fighting equipment, along with the thermal behavior of materials used in shipbuilding.

Potential fire behavior in pine flatwood forests following three different fuel reduction techniques

Treesearch

Patrick Brose; Dale Wade

2002-01-01

A computer modeling study to determine the potential fire behavior in pine flatwood forests following three fuel hazard reduction treatments: herbicide, prescribed fire and thinning was conducted in Florida following the 1998 wildfire season. Prescribed fire provided immediate protection but this protection quickly disappeared as the rough recovered. Thinning had a...

Measuring fire behavior with photography

Treesearch

Hubert B. Clements; Darold E. Ward; Carl W. Adkins

1983-01-01

Photography is practical for recording and measuring some aspects of forest fire behavior if the scale and perspective can be determined. This paper describes a photogrammetric method for measuring flame height and rate of spread for fires on flat terrain. The flames are photographed at known times with a camera in front of the advancing fire. Scale and perspective of...

Fire frequency in the Interior Columbia River Basin: Building regional models from fire history data

USGS Publications Warehouse

McKenzie, D.; Peterson, D.L.; Agee, James K.

2000-01-01

Fire frequency affects vegetation composition and successional pathways; thus it is essential to understand fire regimes in order to manage natural resources at broad spatial scales. Fire history data are lacking for many regions for which fire management decisions are being made, so models are needed to estimate past fire frequency where local data are not yet available. We developed multiple regression models and tree-based (classification and regression tree, or CART) models to predict fire return intervals across the interior Columbia River basin at 1-km resolution, using georeferenced fire history, potential vegetation, cover type, and precipitation databases. The models combined semiqualitative methods and rigorous statistics. The fire history data are of uneven quality; some estimates are based on only one tree, and many are not cross-dated. Therefore, we weighted the models based on data quality and performed a sensitivity analysis of the effects on the models of estimation errors that are due to lack of cross-dating. The regression models predict fire return intervals from 1 to 375 yr for forested areas, whereas the tree-based models predict a range of 8 to 150 yr. Both types of models predict latitudinal and elevational gradients of increasing fire return intervals. Examination of regional-scale output suggests that, although the tree-based models explain more of the variation in the original data, the regression models are less likely to produce extrapolation errors. Thus, the models serve complementary purposes in elucidating the relationships among fire frequency, the predictor variables, and spatial scale. The models can provide local managers with quantitative information and provide data to initialize coarse-scale fire-effects models, although predictions for individual sites should be treated with caution because of the varying quality and uneven spatial coverage of the fire history database. The models also demonstrate the integration of qualitative and quantitative methods when requisite data for fully quantitative models are unavailable. They can be tested by comparing new, independent fire history reconstructions against their predictions and can be continually updated, as better fire history data become available.

Towards the dynamic prediction of wildfire danger. Modeling temporal scenarios of fire-occurrence in Northeast Spain

NASA Astrophysics Data System (ADS)

Martín, Yago; Rodrigues, Marcos

2017-04-01

Up to date models of human-caused ignition probability have commonly been developed from a static or structural point of view, regardless of the time cycles that drive human behavior or environmental conditions. However, human drivers mostly have a temporal dimension, and fuel conditions are subjected to temporal changes as well, which is why a historical/temporal perspective is often required. Previous studies in the region suggest that human driving factors of wildfires have undergone significant shifts in inter-annual occurrence probability models, thus varying over time. On the other hand, an increasing role of environmental conditions has also been reported. This research comprehensively analyzes the intra-annual dimension of fire occurrence and fire-triggering factors using NW Spain as a test area, moving one-step forward towards achieving more accurate predictions, to ultimately develop dynamic predictive models. To this end, several intra-annual presence-only models have been calibrated, exploring seasonal variations of environmental conditions and short-term cycles of human activity (working- vs non-working days). Models were developed from accurately geolocated fire data in the 2008-2012 period, and GIS and remote sensing (MOD1A2 and MOD16) information . Specifically, 8 occurrence data subsets (scenarios) were constructed by splitting fire records into 4 seasons (winter, spring, summer and autumn) then separating each season into 2 new categories (working and non-working days). This allows analyzing the temporal variation of socioeconomic (urban- and agricultural-interfaces, transport and road networks, and human settlements) and environmental (fuel conditions) factors associated with occurrence. Models were calibrated applying the Maximum Entropy algorithm (MaxEnt). The MaxEnt algorithm was selected as it is the most widespread approach to deal with presence-only data, as may be the case of fire occurrence. The dependent variable for each scenario was created on a conceptual framework which assumed that there were no true cases of fire absence. Model accuracy was assessed using a cross-validation k-fold procedure, whereas variable importance was addressed using a jacknife approach combined with AUC estimation. Results reported model performances around 0.8 AUC in all temporal scenarios. In addition, large variability was observed in the contribution of explanatory factors, with accessibility variables and fuel conditions as key factors along models. Overall, we believe our approach is reliable enough to derive dynamic predictions of human-caused fire occurrence probability. To our knowledge, this is the first attempt to combine presence-only models based on XY located fire data, with remote sensing information and intra-annual scenarios also including cycles of human activity.

Mid-21st-century climate changes increase predicted fire occurrence and fire season length, Northern Rocky Mountains, United States

USGS Publications Warehouse

Riley, Karin L.; Loehman, Rachel A.

2016-01-01

Climate changes are expected to increase fire frequency, fire season length, and cumulative area burned in the western United States. We focus on the potential impact of mid-21st-century climate changes on annual burn probability, fire season length, and large fire characteristics including number and size for a study area in the Northern Rocky Mountains. Although large fires are rare they account for most of the area burned in western North America, burn under extreme weather conditions, and exhibit behaviors that preclude methods of direct control. Allocation of resources, development of management plans, and assessment of fire effects on ecosystems all require an understanding of when and where fires are likely to burn, particularly under altered climate regimes that may increase large fire occurrence. We used the large fire simulation model FSim to model ignition, growth, and containment of wildfires under two climate scenarios: contemporary (based on instrumental weather) and mid-century (based on an ensemble average of global climate models driven by the A1B SRES emissions scenario). Modeled changes in fire patterns include increased annual burn probability, particularly in areas of the study region with relatively short contemporary fire return intervals; increased individual fire size and annual area burned; and fewer years without large fires. High fire danger days, represented by threshold values of Energy Release Component (ERC), are projected to increase in number, especially in spring and fall, lengthening the climatic fire season. For fire managers, ERC is an indicator of fire intensity potential and fire economics, with higher ERC thresholds often associated with larger, more expensive fires. Longer periods of elevated ERC may significantly increase the cost and complexity of fire management activities, requiring new strategies to maintain desired ecological conditions and limit fire risk. Increased fire activity (within the historical range of frequency and severity, and depending on the extent to which ecosystems are adapted) may maintain or restore ecosystem functionality; however, in areas that are highly departed from historical fire regimes or where there is disequilibrium between climate and vegetation, ecosystems may be rapidly and persistently altered by wildfires, especially those that burn under extreme conditions.

Effectiveness Testing and Evaluation of Non-Lethal Weapons for Crowd Management

DTIC Science & Technology

2014-06-01

and Combat Service Support• Program Executive Office Ground Combat Systems • Program Executive Office Soldier TACOM LCMC MG Michael J. Terry Assigned...technologies and explosive ordnance disposal Fire Control: Battlefield digitization; embedded system software; aero ballistics and telemetry ARDEC...influence predictive variables Introduction Crowd Behavior Research at TBRL UNCLASSIFIED 7 Data Measurement • Vicon V8i system • 24 cameras • 120 fps

Fire intensity, fire severity and burn severity: A brief review and suggested usage

USGS Publications Warehouse

Keeley, J.E.

2009-01-01

Several recent papers have suggested replacing the terminology of fire intensity and fire severity. Part of the problem with fire intensity is that it is sometimes used incorrectly to describe fire effects, when in fact it is justifiably restricted to measures of energy output. Increasingly, the term has created confusion because some authors have restricted its usage to a single measure of energy output referred to as fireline intensity. This metric is most useful in understanding fire behavior in forests, but is too narrow to fully capture the multitude of ways fire energy affects ecosystems. Fire intensity represents the energy released during various phases of a fire, and different metrics such as reaction intensity, fireline intensity, temperature, heating duration and radiant energy are useful for different purposes. Fire severity, and the related term burn severity, have created considerable confusion because of recent changes in their usage. Some authors have justified this by contending that fire severity is defined broadly as ecosystem impacts from fire and thus is open to individual interpretation. However, empirical studies have defined fire severity operationally as the loss of or change in organic matter aboveground and belowground, although the precise metric varies with management needs. Confusion arises because fire or burn severity is sometimes defined so that it also includes ecosystem responses. Ecosystem responses include soil erosion, vegetation regeneration, restoration of community structure, faunal recolonization, and a plethora of related response variables. Although some ecosystem responses are correlated with measures of fire or burn severity, many important ecosystem processes have either not been demonstrated to be predicted by severity indices or have been shown in some vegetation types to be unrelated to severity. This is a critical issue because fire or burn severity are readily measurable parameters, both on the ground and with remote sensing, yet ecosystem responses are of most interest to resource managers.

Coupling of Bayesian Networks with GIS for wildfire risk assessment on natural and agricultural areas of the Mediterranean

NASA Astrophysics Data System (ADS)

Scherb, Anke; Papakosta, Panagiota; Straub, Daniel

2014-05-01

Wildfires cause severe damages to ecosystems, socio-economic assets, and human lives in the Mediterranean. To facilitate coping with wildfire risks, an understanding of the factors influencing wildfire occurrence and behavior (e.g. human activity, weather conditions, topography, fuel loads) and their interaction is of importance, as is the implementation of this knowledge in improved wildfire hazard and risk prediction systems. In this project, a probabilistic wildfire risk prediction model is developed, with integrated fire occurrence and fire propagation probability and potential impact prediction on natural and cultivated areas. Bayesian Networks (BNs) are used to facilitate the probabilistic modeling. The final BN model is a spatial-temporal prediction system at the meso scale (1 km2 spatial and 1 day temporal resolution). The modeled consequences account for potential restoration costs and production losses referred to forests, agriculture, and (semi-) natural areas. BNs and a geographic information system (GIS) are coupled within this project to support a semi-automated BN model parameter learning and the spatial-temporal risk prediction. The coupling also enables the visualization of prediction results by means of daily maps. The BN parameters are learnt for Cyprus with data from 2006-2009. Data from 2010 is used as validation data set. A special focus is put on the performance evaluation of the BN for fire occurrence, which is modeled as binary classifier and thus, could be validated by means of Receiver Operator Characteristic (ROC) curves. With the final best models, AUC values of more than 70% for validation could be achieved, which indicates potential for reliable prediction performance via BN. Maps of selected days in 2010 are shown to illustrate final prediction results. The resulting system can be easily expanded to predict additional expected damages in the mesoscale (e.g. building and infrastructure damages). The system can support planning of preventive measures (e.g. state resources allocation for wildfire prevention and preparedness) and assist recuperation plans of damaged areas.

Validation of BlueSky Smoke Prediction System using surface and satellite observations during major wildland fire events in Northern California

Treesearch

Lesley Fusina; Sharon Zhong; Julide Koracin; Tim Brown; Annie Esperanza; Leland Tarney; Haiganoush Preisler

2007-01-01

The BlueSky Smoke Prediction System developed by the U.S. Department of Agriculture, Forest Service, AirFire Team under the National Fire Plan is a modeling framework that integrates tools, knowledge of fuels, moisture, combustion, emissions, plume dynamics, and weather to produce real-time predictions of the cumulative impacts of smoke from wildfires, prescribed fires...

Spatially explicit measurements of forest structure and fire behavior following restoration treatments in dry forests

Treesearch

Justin Paul Ziegler; Chad Hoffman; Michael Battaglia; William Mell

2017-01-01

Restoration treatments in dry forests of the western US often attempt silvicultural practices to restore the historical characteristics of forest structure and fire behavior. However, it is suggested that a reliance on non-spatial metrics of forest stand structure, along with the use of wildland fire behavior models that lack the ability to handle complex structures,...

Identifying the location of fire refuges in wet forest ecosystems.

PubMed

Berry, Laurence E; Driscoll, Don A; Stein, John A; Blanchard, Wade; Banks, Sam C; Bradstock, Ross A; Lindenmayer, David B

2015-12-01

The increasing frequency of large, high-severity fires threatens the survival of old-growth specialist fauna in fire-prone forests. Within topographically diverse montane forests, areas that experience less severe or fewer fires compared with those prevailing in the landscape may present unique resource opportunities enabling old-growth specialist fauna to survive. Statistical landscape models that identify the extent and distribution of potential fire refuges may assist land managers to incorporate these areas into relevant biodiversity conservation strategies. We used a case study in an Australian wet montane forest to establish how predictive fire simulation models can be interpreted as management tools to identify potential fire refuges. We examined the relationship between the probability of fire refuge occurrence as predicted by an existing fire refuge model and fire severity experienced during a large wildfire. We also examined the extent to which local fire severity was influenced by fire severity in the surrounding landscape. We used a combination of statistical approaches, including generalized linear modeling, variogram analysis, and receiver operating characteristics and area under the curve analysis (ROC AUC). We found that the amount of unburned habitat and the factors influencing the retention and location of fire refuges varied with fire conditions. Under extreme fire conditions, the distribution of fire refuges was limited to only extremely sheltered, fire-resistant regions of the landscape. During extreme fire conditions, fire severity patterns were largely determined by stochastic factors that could not be predicted by the model. When fire conditions were moderate, physical landscape properties appeared to mediate fire severity distribution. Our study demonstrates that land managers can employ predictive landscape fire models to identify the broader climatic and spatial domain within which fire refuges are likely to be present. It is essential that within these envelopes, forest is protected from logging, roads, and other developments so that the ecological processes related to the establishment and subsequent use of fire refuges are maintained.

Models for predicting fuel consumption in sagebrush-dominated ecosystems

Treesearch

Clinton S. Wright

2013-01-01

Fuel consumption predictions are necessary to accurately estimate or model fire effects, including pollutant emissions during wildland fires. Fuel and environmental measurements on a series of operational prescribed fires were used to develop empirical models for predicting fuel consumption in big sagebrush (Artemisia tridentate Nutt.) ecosystems....

Calculation of precise firing statistics in a neural network model

NASA Astrophysics Data System (ADS)

Cho, Myoung Won

2017-08-01

A precise prediction of neural firing dynamics is requisite to understand the function of and the learning process in a biological neural network which works depending on exact spike timings. Basically, the prediction of firing statistics is a delicate manybody problem because the firing probability of a neuron at a time is determined by the summation over all effects from past firing states. A neural network model with the Feynman path integral formulation is recently introduced. In this paper, we present several methods to calculate firing statistics in the model. We apply the methods to some cases and compare the theoretical predictions with simulation results.

Detection of Bursts and Pauses in Spike Trains

PubMed Central

Ko, D.; Wilson, C. J.; Lobb, C. J.; Paladini, C. A.

2012-01-01

Midbrain dopaminergic neurons in vivo exhibit a wide range of firing patterns. They normally fire constantly at a low rate, and speed up, firing a phasic burst when reward exceeds prediction, or pause when an expected reward does not occur. Therefore, the detection of bursts and pauses from spike train data is a critical problem when studying the role of phasic dopamine (DA) in reward related learning, and other DA dependent behaviors. However, few statistical methods have been developed that can identify bursts and pauses simultaneously. We propose a new statistical method, the Robust Gaussian Surprise (RGS) method, which performs an exhaustive search of bursts and pauses in spike trains simultaneously. We found that the RGS method is adaptable to various patterns of spike trains recorded in vivo, and is not influenced by baseline firing rate, making it applicable to all in vivo spike trains where baseline firing rates vary over time. We compare the performance of the RGS method to other methods of detecting bursts, such as the Poisson Surprise (PS), Rank Surprise (RS), and Template methods. Analysis of data using the RGS method reveals potential mechanisms underlying how bursts and pauses are controlled in DA neurons. PMID:22939922

Temporal Coupling with Cortex Distinguishes Spontaneous Neuronal Activities in Identified Basal Ganglia-Recipient and Cerebellar-Recipient Zones of the Motor Thalamus

PubMed Central

Nakamura, Kouichi C.; Sharott, Andrew; Magill, Peter J.

2014-01-01

Neurons of the motor thalamus mediate basal ganglia and cerebellar influences on cortical activity. To elucidate the net result of γ-aminobutyric acid-releasing or glutamatergic bombardment of the motor thalamus by basal ganglia or cerebellar afferents, respectively, we recorded the spontaneous activities of thalamocortical neurons in distinct identified “input zones” in anesthetized rats during defined cortical activity states. Unexpectedly, the mean rates and brain state dependencies of the firing of neurons in basal ganglia-recipient zone (BZ) and cerebellar-recipient zone (CZ) were matched during slow-wave activity (SWA) and cortical activation. However, neurons were distinguished during SWA by their firing regularities, low-threshold spike bursts and, more strikingly, by the temporal coupling of their activities to ongoing cortical oscillations. The firing of neurons across the BZ was stronger and more precisely phase-locked to cortical slow (∼1 Hz) oscillations, although both neuron groups preferentially fired at the same phase. In contrast, neurons in BZ and CZ fired at different phases of cortical spindles (7–12 Hz), but with similar strengths of coupled firing. Thus, firing rates do not reflect the predicted inhibitory–excitatory imbalance across the motor thalamus, and input zone-specific temporal coding through oscillatory synchronization with the cortex could partly mediate the different roles of basal ganglia and cerebellum in behavior. PMID:23042738

Resistance is not futile: The response of hardwoods to fire-caused wounding

Treesearch

Elaine Kennedy Sutherland; Kevin Smith

2000-01-01

Fires wound trees; but not all of them, and not always. Specific fire behavior and differences among tree species and individual trees produce variable patterns of wounding and wound response. Our work focuses on the relationships between fire behavior and tree biology to better understand how hardwood trees resist injury to the lower stem and either survive or succumb...

Exposure to fire setting behavior on YouTube.

PubMed

Thomas, Meara; Mackay, Sherri; Salsbury, Debbie

2012-07-01

This study is a preliminary examination of fire setting behaviors on YouTube. Data are based on a 1 day search of YouTube. Results indicate YouTube is replete with inappropriate models of fire setting. The findings have potential implications for intervention with fire setting youth. Copyright © 2012 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Utilization of remote sensing techniques for the quantification of fire behavior in two pine stands

Treesearch

Eric V. Mueller; Nicholas Skowronski; Kenneth Clark; Michael Gallagher; Robert Kremens; Jan C. Thomas; Mohamad El Houssami; Alexander Filkov; Rory M. Hadden; William Mell; Albert Simeoni

2017-01-01

Quantification of field-scale fire behavior is necessary to improve the current scientific understanding of wildland fires and to develop and test relevant, physics-based models. In particular, detailed descriptions of individual fires are required, for which the available literature is limited. In this work, two such field-scale experiments, carried out in pine stands...

A tale of two fires: The relative effectiveness of past wildfires in mitigating wildfire behavior and effects

Treesearch

Robert W. Gray; Susan J. Prichard

2015-01-01

The incidence of large, costly landscape-scale fires in western North America is increasing. To combat these fires, researchers and managers have expressed increased interest in investigating the effectiveness of past, stand-replacing wildfires as bottom-up controls on fire spread and severity. Specifically, how effective are past wildfires in mitigating the behavior...

Effects of Mountain Pine Beetle on Fuels and Expected Fire Behavior in Lodgepole Pine Forests, Colorado, USA

PubMed Central

Schoennagel, Tania; Veblen, Thomas T.; Negron, José F.; Smith, Jeremy M.

2012-01-01

In Colorado and southern Wyoming, mountain pine beetle (MPB) has affected over 1.6 million ha of predominantly lodgepole pine forests, raising concerns about effects of MPB-caused mortality on subsequent wildfire risk and behavior. Using empirical data we modeled potential fire behavior across a gradient of wind speeds and moisture scenarios in Green stands compared three stages since MPB attack (Red [1–3 yrs], Grey [4–10 yrs], and Old-MPB [∼30 yrs]). MPB killed 50% of the trees and 70% of the basal area in Red and Grey stages. Across moisture scenarios, canopy fuel moisture was one-third lower in Red and Grey stages compared to the Green stage, making active crown fire possible at lower wind speeds and less extreme moisture conditions. More-open canopies and high loads of large surface fuels due to treefall in Grey and Old-MPB stages significantly increased surface fireline intensities, facilitating active crown fire at lower wind speeds (>30–55 km/hr) across all moisture scenarios. Not accounting for low foliar moistures in Red and Grey stages, and large surface fuels in Grey and Old-MPB stages, underestimates the occurrence of active crown fire. Under extreme burning conditions, minimum wind speeds for active crown fire were 25–35 km/hr lower for Red, Grey and Old-MPB stands compared to Green. However, if transition to crown fire occurs (outside the stand, or within the stand via ladder fuels or wind gusts >65 km/hr), active crown fire would be sustained at similar wind speeds, suggesting observed fire behavior may not be qualitatively different among MPB stages under extreme burning conditions. Overall, the risk (probability) of active crown fire appears elevated in MPB-affected stands, but the predominant fire hazard (crown fire) is similar across MPB stages and is characteristic of lodgepole pine forests where extremely dry, gusty weather conditions are key factors in determining fire behavior. PMID:22272268

Global vegetation-fire pattern under different land use and climate conditions

NASA Astrophysics Data System (ADS)

Thonicke, K.; Poulter, B.; Heyder, U.; Gumpenberger, M.; Cramer, W.

2008-12-01

Fire is a process of global significance in the Earth System influencing vegetation dynamics, biogeochemical cycling and biophysical feedbacks. Naturally ignited wildfires have long history in the Earth System. Humans have been using fire to shape the landscape for their purposes for many millenia, sometimes influencing the status of the vegetation remarkably as for example in Mediterranean-type ecosystems. Processes and drivers describing fire danger, ignitions, fire spread and effects are relatively well-known for many fire-prone ecosystems. Modeling these has a long tradition in fire-affected regions to predict fire risk and behavior for fire-fighting purposes. On the other hand, the global vegetation community realized the importance of disturbances to be recognized in their global vegetation models with fire being globally most important and so-far best studied. First attempts to simulate fire globally considered a minimal set of drivers, whereas recent developments attempt to consider each fire process separately. The process-based fire model SPITFIRE (SPread and InTensity of FIRE) simulates these processes embedded in the LPJ DGVM. Uncertainties still arise from missing measurements for some parameters in less-studied fire regimes, or from broad PFT classifications which subsume different fire-ecological adaptations and tolerances. Some earth observation data sets as well as fire emission models help to evaluate seasonality and spatial distribution of simulated fire ignitions, area burnt and fire emissions within SPITFIRE. Deforestation fires are a major source of carbon released to the atmosphere in the tropics; in the Amazon basin it is the second-largest contributor to Brazils GHG emissions. How ongoing deforestation affects fire regimes, forest stability and biogeochemical cycling in the Amazon basin under present climate conditions will be presented. Relative importance of fire vs. climate and land use change is analyzed. Emissions resulting from wildfires, agricultural and woodfuel burning will be quantified and drivers identified. Future projections of climate and land use change are applied to the model to investigate joint effects on future changes in fire, deforestation and vegetation dynamics in the Amazon basin.

Using behavioral science to improve fire escape behaviors in response to a smoke alarm.

PubMed

Thompson, N J; Waterman, M B; Sleet, D A

2004-01-01

Although the likelihood of fire-related death in homes with smoke alarms is about one-half that in homes without alarms, alarm effectiveness is limited by behavior. Only 16% of residents of homes with alarms have developed and practiced plans for escape when the alarm sounds. We reviewed literature to identify behavioral constructs that influence smoke alarm use. We then convened experts in the behavioral aspects of smoke alarms who reviewed the constructs and determined that the appropriate areas for behavioral focus were formulating, practicing, and implementing escape plans should an alarm sound. They subsequently identified important behaviors to be addressed by burn-prevention programs and incorporated the constructs into a behavioral model for use in such programs. Finally, we organized the available literature to support this model and make programmatic recommendations. Many gaps remain in behavioral research to improve fire escape planning and practice. Future research must select the target behavior, apply behavioral theories, and distinguish between initiation and maintenance of behaviors associated with planning, practicing, and implementing home fire escape plans.

Probabilistic models to estimate fire-induced cable damage at nuclear power plants

NASA Astrophysics Data System (ADS)

Valbuena, Genebelin R.

Even though numerous PRAs have shown that fire can be a major contributor to nuclear power plant risk, there are some specific areas of knowledge related to this issue, such as the prediction of fire-induced damage to electrical cables and circuits, and their potential effects in the safety of the nuclear power plant, that still constitute a practical enigma, particularly for the lack of approaches/models to perform consistent and objective assessments. This report contains a discussion of three different models to estimate fire-induced cable damage likelihood given a specified fire profile: the kinetic, the heat transfer and the IR "K Factor" model. These models not only are based on statistical analysis of data available in the open literature, but to the greatest extent possible they use physics based principles to describe the underlying mechanism of failures that take place among the electrical cables upon heating due to external fires. The characterization of cable damage, and consequently the loss of functionality of electrical cables in fire is a complex phenomenon that depends on a variety of intrinsic factors such as cable materials and dimensions, and extrinsic factors such as electrical and mechanical loads on the cables, heat flux severity, and exposure time. Some of these factors are difficult to estimate even in a well-characterized fire, not only for the variability related to the unknown material composition and physical arrangements, but also for the lack of objective frameworks and theoretical models to study the behavior of polymeric wire cable insulation under dynamic external thermal insults. The results of this research will (1) help to develop a consistent framework to predict fire-induced cable failure modes likelihood, and (2) develop some guidance to evaluate and/or reduce the risk associated with these failure modes in existing and new power plant facilities. Among the models evaluated, the physics-based heat transfer model takes into account the properties and characteristics of the cables and cable materials, and the characteristics of the thermal insult. This model can be used to estimate the probability of cable damage under different thermal conditions.

A system to evaluate fire impacts from simulated fire behavior in Mediterranean areas of Central Chile.

PubMed

Castillo, Miguel E; Molina, Juan R; Rodríguez Y Silva, Francisco; García-Chevesich, Pablo; Garfias, Roberto

2017-02-01

Wildfires constitute the greatest economic disruption to Mediterranean ecosystems, from a socio-economic and ecological perspective (Molina et al., 2014). This study proposes to classify fire intensity levels based on potential fire behavior in different types of Mediterranean vegetation types, using two geographical scales. The study considered >4 thousand wildfires over a period of 25years, identifying fire behavior on each event, based on simulations using "KITRAL", a model developed in Chile in 1993 and currently used in the entire country. Fire intensity values allowed results to be classified into six fire effects categories (levels), each of them with field indicators linking energy values with damage related to burned vegetation and wildland urban interface zone. These indicators also facilitated a preliminary assessment of wildfire impact on different Mediterranean land uses and, are therefore, a useful tool to prioritize future interventions. Copyright © 2016 Elsevier B.V. All rights reserved.

Predicting fire scars in Ozark timber species following prescribed burning

Treesearch

Aaron P. Stevenson; Richard P. Guyette; Rose-Marie Muzika

2009-01-01

A potential consequence of using prescribed fire is heat-related injury to timber trees. Scars formed following fire injuries are often associated with extensive decay in hardwoods. The ability to predict scarring caused by prescribed fire is important when multiple management goals are incorporated on a single forest site.

Predicting streamflow response to fire-induced landcover change: implications of parameter uncertainty in the MIKE SHE model.

PubMed

McMichael, Christine E; Hope, Allen S

2007-08-01

Fire is a primary agent of landcover transformation in California semi-arid shrubland watersheds, however few studies have examined the impacts of fire and post-fire succession on streamflow dynamics in these basins. While it may seem intuitive that larger fires will have a greater impact on streamflow response than smaller fires in these watersheds, the nature of these relationships has not been determined. The effects of fire size on seasonal and annual streamflow responses were investigated for a medium-sized basin in central California using a modified version of the MIKE SHE model which had been previously calibrated and tested for this watershed using the Generalized Likelihood Uncertainty Estimation methodology. Model simulations were made for two contrasting periods, wet and dry, in order to assess whether fire size effects varied with weather regime. Results indicated that seasonal and annual streamflow response increased nearly linearly with fire size in a given year under both regimes. Annual flow response was generally higher in wetter years for both weather regimes, however a clear trend was confounded by the effect of stand age. These results expand our understanding of the effects of fire size on hydrologic response in chaparral watersheds, but it is important to note that the majority of model predictions were largely indistinguishable from the predictive uncertainty associated with the calibrated model - a key finding that highlights the importance of analyzing hydrologic predictions for altered landcover conditions in the context of model uncertainty. Future work is needed to examine how alternative decisions (e.g., different likelihood measures) may influence GLUE-based MIKE SHE streamflow predictions following different size fires, and how the effect of fire size on streamflow varies with other factors such as fire location.

The use of fuel breaks in landscape fire management

USGS Publications Warehouse

Agee, James K.; Bahro, Berni; Finney, Mark A.; Omi, Philip N.; Sapsis, David B.; Skinner, Carl N.; Van Wagtendonk, Jan W.; Weatherspoon, C. Phillip

2000-01-01

Shaded fuelbreaks and larger landscape fuel treatments, such as prescribed fire, are receiving renewed interest as forest protection strategies in the western United States. The effectiveness of fuelbreaks remains a subject of debate because of differing fuelbreak objectives, prescriptions for creation and maintenance, and their placement in landscapes with differing fire regimes. A well-designed fuelbreak will alter the behavior of wildland fire entering the fuel-altered zone. Both surface and crown fire behavior may be reduced. Shaded fuelbreaks must be created in the context of the landscape within which they are placed. No absolute standards for fuelbreak width or fuel reduction are possible, although recent proposals for forested fuelbreaks suggest 400 m wide bands where surface fuels are reduced and crown fuels are thinned. Landscape-level treatments such as prescribed fire can use shaded fuelbreaks as anchor points, and extend the zone of altered fire behavior to larger proportions of the landscape. Coupling fuelbreaks with area-wide fuel treatments can reduce the size, intensity, and effects of wildland fires.

Fuel loads and simulated fire behavior in "old-stage" beetle-infested ponderosa pine of the Colorado Plateau

Treesearch

E. Matthew Hansen; Morris C. Johnson; Barbara J. Bentz; James C. Vandygriff; A. Steven Munson

2015-01-01

Recent bark beetle outbreaks in western North America have led to concerns regarding changes in fuel profiles and associated changes in fire behavior. Data are lacking for a range of infestation severities and time since outbreak, especially for relatively arid cover types. We surveyed fuel loads and simulated fire behavior for ponderosa pine stands of the...

Relation of weather forecasts to the prediction of dangerous forest fire conditions

Treesearch

R. H. Weidman

1923-01-01

The purpose of predicting dangerous forest-fire conditions, of course, is to reduce the great cost and damage caused by forest fires. In the region of Montana and northern Idaho alone the average cost to the United States Forest Service of fire protection and suppression is over $1,000,000 a year. Although the causes of forest fires will gradually be reduced by...

Analytical modeling of fire growth on fire-resistive wood-based materials with changing conditions

Treesearch

Mark A. Dietenberger

2006-01-01

Our analytical model of fire growth for the ASTM E 84 tunnel, which simultaneously predicts heat release rate, flame-over area, and pyrolysis area as functions of time for constant conditions, was documented in the 2001 BCC Symposium for different treated wood materials. The model was extended to predict ignition and fire growth on exterior fire-resistive structures...

Forest-fire models

Treesearch

Haiganoush Preisler; Alan Ager

2013-01-01

For applied mathematicians forest fire models refer mainly to a non-linear dynamic system often used to simulate spread of fire. For forest managers forest fire models may pertain to any of the three phases of fire management: prefire planning (fire risk models), fire suppression (fire behavior models), and postfire evaluation (fire effects and economic models). In...

Integrating fire behavior models and geospatial analysis for wildland fire risk assessment and fuel management planning

Treesearch

Alan A. Ager; Nicole M. Vaillant; Mark A. Finney

2011-01-01

Wildland fire risk assessment and fuel management planning on federal lands in the US are complex problems that require state-of-the-art fire behavior modeling and intensive geospatial analyses. Fuel management is a particularly complicated process where the benefits and potential impacts of fuel treatments must be demonstrated in the context of land management goals...

Surface fire intensity influences simulated crown fire behavior in lodgepole pine forests with recent mountain pine beetle-caused tree mortality

Treesearch

Chad M. Hoffman; Penelope Morgan; William Mell; Russell Parsons; Eva Strand; Steve Cook

2013-01-01

Recent bark beetle outbreaks have had a significant impact on forests throughout western North America and have generated concerns about interactions and feedbacks between beetle attacks and fire. However, research has been hindered by a lack of experimental studies and the use of fire behavior models incapable of accounting for the heterogeneous fuel complexes. We...

Fuel and fire behavior in high-elevation five-needle pines affected by mountain pine beetle

Treesearch

Michael J. Jenkins

2011-01-01

Bark beetle-caused tree mortality in conifer forests affects the quantity and quality of forest fuels and has long been assumed to increase fire hazard and potential fire behavior. In reality, bark beetles and their effects on fuel accumulation and subsequent fire hazard have only recently been described. We have extensively sampled fuels in three conifer forest types...

Evaluation of MM5 model resolution when applied to prediction of national fire danger rating indexes

Treesearch

Jeanne L. Hoadley; Miriam L. Rorig; Larry Bradshaw; Sue A. Ferguson; Kenneth J. Westrick; Scott L. Goodrick; Paul Werth

2006-01-01

Weather predictions from the MM5 mesoscale model were used to compute gridded predictions of National Fire Danger Rating System (NFDRS) indexes. The model output was applied to a case study of the 2000 fire season in Northern Idaho and Western Montana to simulate an extreme event. To determine the preferred resolution for automating NFD RS predictions, model...

Numerical Field Model Simulation of Full Scale Fire Tests in a Closed Spherical/Cylindrical Vessel.

DTIC Science & Technology

1987-12-01

the behavior of an actual fire on board a ship. The computer model will be verified by the experimental data obtained in Fire-l. It is important to... behavior in simulations where convection is important. The upwind differencing scheme takes into account the unsymmetrical phenomenon of convection by using...TANK CELL ON THE NORTH SIDE) FOR A * * PARTICULAR FIRE CELL * * COSUMS (I,J) = THE ARRAY TO STORE THE SIMILIAR VALUE FOR THE FIRE * * CELL TO THE SOUTH

Siberian and North American Biomass Burning Contributions to the Processes that Influenced the 2008 Arctic Aircraft and Satellite Field Campaigns

NASA Astrophysics Data System (ADS)

Soja, A. J.; Stocks, B. J.; Carr, R.; Pierce, R. B.; Natarajan, M.; Fromm, M.

2009-05-01

Current climate change scenarios predict increases in biomass burning in terms of increases in fire frequency, area burned, fire season length and fire season severity, particularly in boreal regions. Climate and weather control fire danger, which strongly influences the severity of fire events, and these in turn, feed back to the climate system through direct and indirect emissions, modifying cloud condensation nuclei and altering albedo (affecting the energy balance) through vegetative land cover change and deposition. Additionally, fire emissions adversely influence air quality and human health downwind of burning. The boreal zone is significant because this region stores the largest reservoir of terrestrial carbon, globally, and will experience climate change impacts earliest. Boreal biomass burning is an integral component to several of the primary goals of the ARCTAS (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites) and ARCPAC (Aerosol, Radiation, and Cloud Processes affecting Arctic Climate) 2008 field campaigns, which include its implication for atmospheric composition and climate, aerosol radiative forcing, and chemical processes with a focus on ozone and aerosols. Both the spring and summer phases of ARCTAS and ARCPAC offered substantial opportunities for sampling fresh and aged biomass burning emissions. However, the extent to which spring biomass burning influenced arctic haze was unexpected, which could inform our knowledge of the formation of arctic haze and the early deposition of black carbon on the icy arctic surface. There is already evidence of increased extreme fire seasons that correlate with warming across the circumboreal zone. In this presentation, we discuss seasonal and annual fire activity and anomalies that relate to the ARCTAS and ARCPAC spring (April 1 - 20) and summer (June 18 - July 13) periods across Siberia and North America, with particular emphasis on fire danger and fire behavior as they relate to smoke emissions. Fire severity and subsequent emission levels are directly related to fire danger conditions, which reflect and incorporate both antecedent and current weather. In this century, it is predicted that fire regime increases will be the catalyst for ecosystem change, which will force ecosystems to move more rapidly towards a new equilibrium with climate. However, the reasons for ecosystem change are often accompanied by social and political drivers of land cover change, which complicate the relationship between fire and weather. For instance, since the collapse of the former Soviet Union, financial support for fire fighting is minimal, communal agricultural lands have been abandoned and a number of species are no longer protected (e.g. Saiga in Kalmykia), and each of these factors strongly influences vegetation cover and fire regimes, leading to a complicated interaction of processes that control fire and its affect on the larger environment.

The compensatory interaction between motor unit firing behavior and muscle force during fatigue

PubMed Central

De Luca, Carlo J.; Kline, Joshua C.

2016-01-01

Throughout the literature, different observations of motor unit firing behavior during muscle fatigue have been reported and explained with varieties of conjectures. The disagreement amongst previous studies has resulted, in part, from the limited number of available motor units and from the misleading practice of grouping motor unit data across different subjects, contractions, and force levels. To establish a more clear understanding of motor unit control during fatigue, we investigated the firing behavior of motor units from the vastus lateralis muscle of individual subjects during a fatigue protocol of repeated voluntary constant force isometric contractions. Surface electromyographic decomposition technology provided the firings of 1,890 motor unit firing trains. These data revealed that to sustain the contraction force as the muscle fatigued, the following occurred: 1) motor unit firing rates increased; 2) new motor units were recruited; and 3) motor unit recruitment thresholds decreased. Although the degree of these adaptations was subject specific, the behavior was consistent in all subjects. When we compared our empirical observations with those obtained from simulation, we found that the fatigue-induced changes in motor unit firing behavior can be explained by increasing excitation to the motoneuron pool that compensates for the fatigue-induced decrease in muscle force twitch reported in empirical studies. Yet, the fundamental motor unit control scheme remains invariant throughout the development of fatigue. These findings indicate that the central nervous system regulates motor unit firing behavior by adjusting the operating point of the excitation to the motoneuron pool to sustain the contraction force as the muscle fatigues. PMID:27385798

The compensatory interaction between motor unit firing behavior and muscle force during fatigue.

PubMed

Contessa, Paola; De Luca, Carlo J; Kline, Joshua C

2016-10-01

Throughout the literature, different observations of motor unit firing behavior during muscle fatigue have been reported and explained with varieties of conjectures. The disagreement amongst previous studies has resulted, in part, from the limited number of available motor units and from the misleading practice of grouping motor unit data across different subjects, contractions, and force levels. To establish a more clear understanding of motor unit control during fatigue, we investigated the firing behavior of motor units from the vastus lateralis muscle of individual subjects during a fatigue protocol of repeated voluntary constant force isometric contractions. Surface electromyographic decomposition technology provided the firings of 1,890 motor unit firing trains. These data revealed that to sustain the contraction force as the muscle fatigued, the following occurred: 1) motor unit firing rates increased; 2) new motor units were recruited; and 3) motor unit recruitment thresholds decreased. Although the degree of these adaptations was subject specific, the behavior was consistent in all subjects. When we compared our empirical observations with those obtained from simulation, we found that the fatigue-induced changes in motor unit firing behavior can be explained by increasing excitation to the motoneuron pool that compensates for the fatigue-induced decrease in muscle force twitch reported in empirical studies. Yet, the fundamental motor unit control scheme remains invariant throughout the development of fatigue. These findings indicate that the central nervous system regulates motor unit firing behavior by adjusting the operating point of the excitation to the motoneuron pool to sustain the contraction force as the muscle fatigues. Copyright © 2016 the American Physiological Society.

Predicting fire frequency with chemistry and climate

Treesearch

Richard P. Guyette; Michael C. Stambaugh; Daniel C. Dey; Rose-Marie Muzika

2012-01-01

A predictive equation for estimating fire frequency was developed from theories and data in physical chemistry, ecosystem ecology, and climatology. We refer to this equation as the Physical Chemistry Fire Frequency Model (PC2FM). The equation was calibrated and validated with North American fire data (170 sites) prior to widespread industrial influences (before ...

Summaries of BFRL fire research in-house projects and grants, 1993

NASA Astrophysics Data System (ADS)

Jason, Nora H.

1993-09-01

The report describes the fire research projects performed in the Building and Fire Research Laboratory (BFRL) and under its extramural grants program during fiscal year 1993. The BFRL Fire Research Program has directed its efforts under three program thrusts. The in-house priority projects, grants, and externally-funded efforts thus form an integrated, focussed ensemble. The publication is organized along those lines: fire risk and hazard prediction - carbon monoxide prediction, turbulent combustion, soot, engineering analysis, fire hazard assessment, and large fires; fire safety of products and materials - materials combustion, furniture flammability, and wall and ceiling fires; and advanced technologies for fire sensing and control - fire detection and fire suppression. For the convenience of the reader, an alphabetical listing of all grants is contained in Part 2.0.

FireStem2D – A Two-Dimensional Heat Transfer Model for Simulating Tree Stem Injury in Fires

PubMed Central

Chatziefstratiou, Efthalia K.; Bohrer, Gil; Bova, Anthony S.; Subramanian, Ravishankar; Frasson, Renato P. M.; Scherzer, Amy; Butler, Bret W.; Dickinson, Matthew B.

2013-01-01

FireStem2D, a software tool for predicting tree stem heating and injury in forest fires, is a physically-based, two-dimensional model of stem thermodynamics that results from heating at the bark surface. It builds on an earlier one-dimensional model (FireStem) and provides improved capabilities for predicting fire-induced mortality and injury before a fire occurs by resolving stem moisture loss, temperatures through the stem, degree of bark charring, and necrotic depth around the stem. We present the results of numerical parameterization and model evaluation experiments for FireStem2D that simulate laboratory stem-heating experiments of 52 tree sections from 25 trees. We also conducted a set of virtual sensitivity analysis experiments to test the effects of unevenness of heating around the stem and with aboveground height using data from two studies: a low-intensity surface fire and a more intense crown fire. The model allows for improved understanding and prediction of the effects of wildland fire on injury and mortality of trees of different species and sizes. PMID:23894599

Emerging technology to measure habitat quality and behavior of grouse: Examples from studies of greater sage-grouse

Treesearch

Jennifer Sorensen Forbey; Gail L. Patricelli; Donna M. Delparte; Alan H. Krakauer; Peter J. Olsoy; Marcella R. Fremgen; Jordan D. Nobler; Lucas P. Spaete; Lisa A. Shipley; Janet L. Rachlow; Amy K. Dirksen; Anna Perry; Bryce A. Richardson; Nancy F. Glenn

2017-01-01

An increasing number of threats, both natural (e.g. fires, drought) and anthropogenic (e.g. agriculture, infrastructure development), are likely to affect both availability and quality of plants that grouse rely on for cover and food. As such, there is an increasing need to monitor plants and their use by grouse over space and time to better predict how changes in...

Developing custom fire behavior fuel models from ecologically complex fuel structures for upper Atlantic Coastal Plain forests.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parresol, Bernard, R.; Scott, Joe, H.; Andreu, Anne

2012-01-01

Currently geospatial fire behavior analyses are performed with an array of fire behavior modeling systems such as FARSITE, FlamMap, and the Large Fire Simulation System. These systems currently require standard or customized surface fire behavior fuel models as inputs that are often assigned through remote sensing information. The ability to handle hundreds or thousands of measured surface fuelbeds representing the fine scale variation in fire behavior on the landscape is constrained in terms of creating compatible custom fire behavior fuel models. In this study, we demonstrate an objective method for taking ecologically complex fuelbeds from inventory observations and converting thosemore » into a set of custom fuel models that can be mapped to the original landscape. We use an original set of 629 fuel inventory plots measured on an 80,000 ha contiguous landscape in the upper Atlantic Coastal Plain of the southeastern United States. From models linking stand conditions to component fuel loads, we impute fuelbeds for over 6000 stands. These imputed fuelbeds were then converted to fire behavior parameters under extreme fuel moisture and wind conditions (97th percentile) using the fuel characteristic classification system (FCCS) to estimate surface fire rate of spread, surface fire flame length, shrub layer reaction intensity (heat load), non-woody layer reaction intensity, woody layer reaction intensity, and litter-lichen-moss layer reaction intensity. We performed hierarchical cluster analysis of the stands based on the values of the fire behavior parameters. The resulting 7 clusters were the basis for the development of 7 custom fire behavior fuel models from the cluster centroids that were calibrated against the FCCS point data for wind and fuel moisture. The latter process resulted in calibration against flame length as it was difficult to obtain a simultaneous calibration against both rate of spread and flame length. The clusters based on FCCS fire behavior parameters represent reasonably identifiable stand conditions, being: (1) pine dominated stands with more litter and down woody debriscomponents than other stands, (2) hardwood and pine stands with no shrubs, (3) hardwood dominated stands with low shrub and high non-woody biomass and high down woody debris, (4) stands with high grass and forb (i.e., non-woody) biomass as well as substantial shrub biomass, (5) stands with both high shrub and litter biomass, (6) pine-mixed hardwood stands with moderate litter biomass and low shrub biomass, and (7) baldcypress-tupelo stands. Models representing these stand clusters generated flame lengths from 0.6 to 2.3 musing a 30 km h{sub 1} wind speed and fireline intensities of 100-1500 kW m{sub 1} that are typical within the range of experience on this landscape. The fuel models ranked 1 < 2 < 7 < 5 < 4 < 3 < 6 in terms of both flame length and fireline intensity. The method allows for ecologically complex data to be utilized in order to create a landscape representative of measured fuel conditions and to create models that interface with geospatial fire models.« less

Analysis of NASA JP-4 fire tests data and development of a simple fire model

NASA Technical Reports Server (NTRS)

Raj, P.

1980-01-01

The temperature, velocity and species concentration data obtained during the NASA fire tests (3m, 7.5m and 15m diameter JP-4 fires) were analyzed. Utilizing the data analysis, a sample theoretical model was formulated to predict the temperature and velocity profiles in JP-4 fires. The theoretical model, which does not take into account the detailed chemistry of combustion, is capable of predicting the extent of necking of the fire near its base.

Fire treatment effects on vegetation structure, fuels, and potential fire severity in western U.S. forests

USGS Publications Warehouse

Stephens, S.L.; Moghaddas, J.J.; Edminster, C.; Fiedler, C.E.; Haase, S.; Harrington, M.; Keeley, J.E.; Knapp, E.E.; Mciver, J.D.; Metlen, K.; Skinner, C.N.; Youngblood, A.

2009-01-01

Abstract. Forest structure and species composition in many western U.S. coniferous forests have been altered through fire exclusion, past and ongoing harvesting practices, and livestock grazing over the 20th century. The effects of these activities have been most pronounced in seasonally dry, low and mid-elevation coniferous forests that once experienced frequent, low to moderate intensity, fire regimes. In this paper, we report the effects of Fire and Fire Surrogate (FFS) forest stand treatments on fuel load profiles, potential fire behavior, and fire severity under three weather scenarios from six western U.S. FFS sites. This replicated, multisite experiment provides a framework for drawing broad generalizations about the effectiveness of prescribed fire and mechanical treatments on surface fuel loads, forest structure, and potential fire severity. Mechanical treatments without fire resulted in combined 1-, 10-, and 100-hour surface fuel loads that were significantly greater than controls at three of five FFS sites. Canopy cover was significantly lower than controls at three of five FFS sites with mechanical-only treatments and at all five FFS sites with the mechanical plus burning treatment; fire-only treatments reduced canopy cover at only one site. For the combined treatment of mechanical plus fire, all five FFS sites with this treatment had a substantially lower likelihood of passive crown fire as indicated by the very high torching indices. FFS sites that experienced significant increases in 1-, 10-, and 100-hour combined surface fuel loads utilized harvest systems that left all activity fuels within experimental units. When mechanical treatments were followed by prescribed burning or pile burning, they were the most effective treatment for reducing crown fire potential and predicted tree mortality because of low surface fuel loads and increased vertical and horizontal canopy separation. Results indicate that mechanical plus fire, fire-only, and mechanical-only treatments using whole-tree harvest systems were all effective at reducing potential fire severity under severe fire weather conditions. Retaining the largest trees within stands also increased fire resistance. ?? 2009 by the Ecological Society of America.

Burning Down the Silos: Integrating new perspectives from the social sciences into human behavior in fire research.

PubMed

Kuligowski, Erica

2017-01-01

The traditional social science disciplines can provide many benefits to the field of human behavior in fire (HBiF). First, the social sciences delve further into insights only marginally examined by HBiF researchers, in turn, expanding the depth of HBiF research. In this paper, I present examples of studies from the fields of social psychology and sociology that would expand HBiF research into non-engineering or "unobservable" aspects of behavior during a fire event. Second, the social sciences can provide insight into new areas of research; in turn, expanding the scope of HBiF research. In this section, I introduce pre- and post-fire studies and explore potential research questions that fall outside of the response period of a fire, the phase upon which most focus is currently placed. Third, the social sciences elucidate the value of research methods available to study human behavior. Qualitative research methods are specifically highlighted. These three benefits will allow HBiF researchers to collect a wider range of data, further develop and expand current behavioral knowledge, and increase the impact of this research for both social and engineering applications. Finally, I end with a discussion on possible ways to better integrate the social sciences within human behavior in fire.

Differential Activation of Fast-Spiking and Regular-Firing Neuron Populations During Movement and Reward in the Dorsal Medial Frontal Cortex

PubMed Central

Insel, Nathan; Barnes, Carol A.

2015-01-01

The medial prefrontal cortex is thought to be important for guiding behavior according to an animal's expectations. Efforts to decode the region have focused not only on the question of what information it computes, but also how distinct circuit components become engaged during behavior. We find that the activity of regular-firing, putative projection neurons contains rich information about behavioral context and firing fields cluster around reward sites, while activity among putative inhibitory and fast-spiking neurons is most associated with movement and accompanying sensory stimulation. These dissociations were observed even between adjacent neurons with apparently reciprocal, inhibitory–excitatory connections. A smaller population of projection neurons with burst-firing patterns did not show clustered firing fields around rewards; these neurons, although heterogeneous, were generally less selective for behavioral context than regular-firing cells. The data suggest a network that tracks an animal's behavioral situation while, at the same time, regulating excitation levels to emphasize high valued positions. In this scenario, the function of fast-spiking inhibitory neurons is to constrain network output relative to incoming sensory flow. This scheme could serve as a bridge between abstract sensorimotor information and single-dimensional codes for value, providing a neural framework to generate expectations from behavioral state. PMID:24700585

Twenty Years After the 1988 Yellowstone Fires: Lessons About Disturbance and Ecosystems

USGS Publications Warehouse

Romme, W.H.; Boyce, M.S.; Gresswell, R.; Merrill, E.H.; Minshall, G.W.; Whitlock, C.; Turner, M.G.

2011-01-01

The 1988 Yellowstone fires were among the first in what has proven to be an upsurge in large severe fires in the western USA during the past 20 years. At the time of the fires, little was known about the impacts of such a large severe disturbance because scientists had had few previous opportunities to study such an event. Ecologists predicted short- and long-term effects of the 1988 fires on vegetation, biogeochemistry, primary productivity, wildlife, and aquatic ecosystems based on scientific understanding of the time. Twenty-plus years of subsequent study allow these early predictions to be evaluated. Most of the original predictions were at least partially supported, but some predictions were refuted, others nuanced, and a few postfire phenomena were entirely unexpected. Post-1988 Yellowstone studies catalyzed advances in ecology focused on the importance of spatial and temporal heterogeneity, contingent influences, and multiple interacting drivers. Post-1988 research in Yellowstone also has changed public perceptions of fire as an ecological process and attitudes towards fire management. Looking ahead to projected climate change and more frequent large fires, the well-documented ecological responses to the 1988 Yellowstone fires provide a foundation for detecting and evaluating potential changes in fire regimes of temperate mountainous regions. ?? 2011 Springer Science+Business Media, LLC.

Bidirectional Modulation of Substantia Nigra Activity by Motivational State

PubMed Central

Rossi, Mark A.; Fan, David; Barter, Joseph W.; Yin, Henry H.

2013-01-01

A major output nucleus of the basal ganglia is the substantia nigra pars reticulata, which sends GABAergic projections to brainstem and thalamic nuclei. The GABAergic (GABA) neurons are reciprocally connected with nearby dopaminergic neurons, which project mainly to the basal ganglia, a set of subcortical nuclei critical for goal-directed behaviors. Here we examined the impact of motivational states on the activity of GABA neurons in the substantia nigra pars reticulata and the neighboring dopaminergic (DA) neurons in the pars compacta. Both types of neurons show short-latency bursts to a cue predicting a food reward. As mice became sated by repeated consumption of food pellets, one class of neurons reduced cue-elicited firing, whereas another class of neurons progressively increased firing. Extinction or pre-feeding just before the test session dramatically reduced the phasic responses and their motivational modulation. These results suggest that signals related to the current motivational state bidirectionally modulate behavior and the magnitude of phasic response of both DA and GABA neurons in the substantia nigra. PMID:23936522

Prefrontal Parvalbumin Neurons in Control of Attention

PubMed Central

Kim, Hoseok; Ährlund-Richter, Sofie; Wang, Xinming; Deisseroth, Karl; Carlén, Marie

2016-01-01

Summary While signatures of attention have been extensively studied in sensory systems, the neural sources and computations responsible for top-down control of attention are largely unknown. Using chronic recordings in mice, we found that fast-spiking parvalbumin (FS-PV) interneurons in medial prefrontal cortex (mPFC) uniformly show increased and sustained firing during goal-driven attentional processing, correlating to the level of attention. Elevated activity of FS-PV neurons on the timescale of seconds predicted successful execution of behavior. Successful allocation of attention was characterized by strong synchronization of FS-PV neurons, increased gamma oscillations, and phase locking of pyramidal firing. Phase-locked pyramidal neurons showed gamma-phase-dependent rate modulation during successful attentional processing. Optogenetic silencing of FS-PV neurons deteriorated attentional processing, while optogenetic synchronization of FS-PV neurons at gamma frequencies had pro-cognitive effects and improved goal-directed behavior. FS-PV neurons thus act as a functional unit coordinating the activity in the local mPFC circuit during goal-driven attentional processing. PMID:26771492

Photochemical model estimated fire impacts on ozone and aerosol evaluated with field studies and routine data sources

NASA Astrophysics Data System (ADS)

Baker, K. R.

2017-12-01

Highly instrumented field studies provide a unique opportunity to evaluate multiple aspects of photochemical grid model representation of fire emissions, dispersion, and chemical evolution. Fuel information and burn area for a specific fire coupled with near-fire and downwind chemical measurements provides information needed to constrain model predicted fire plume transport and chemical evolution of important pollutants such as ozone and particulate matter (PM2.5) that have deleterious health effects. Most local to regional scale field campaigns to date have made relatively few transects through plumes from fires with well characterized fuel type and consumption. While more comprehensive field studies are being planned for 2018 and beyond (WE-CAN, FIREX, FIRE-CHEM, and FASMEE), existing measurement data from multiple field campaigns including 2013 SEAC4RS, satellite data, and routine surface networks are used to assess how a regulatory modeling system captures fire impacts on local to regional scale ozone and PM2.5. Key aspects of the regulatory modeling system include fire location and burn area from SMARTFIRE2, emissions from BlueSky framework, and predictions of ambient O3 and PM2.5 from the Community Multiscale Air Quality (CMAQ) photochemical transport model. A comparison of model estimated O3 from specific fires with routine surface measurements at rural locations in proximity to the 2013 Rim fire, 2011 Wallow fire, and 2011 Flint Hills fires suggest the modeling system over-estimates smoke impacts on hourly ozone. Sensitivity simulations where solar radiation and photolysis rates are more aggressively attenuated by smoke reduced O3 predictions but did not ameliorate the over prediction bias. PM2.5 organic carbon tends to be overpredicted at rural surface sites downwind from the 2011 Flint Hills prescribed fires while results were mixed at rural sites downwind of the 2013 Rim fire and 2011 Wallow fire suggesting differences in fuel characterization (e.g., emission factors, emissions speciation, burn period, etc.) between these areas may contribute to differences in model prediction. Aircraft plume transects made downwind of the 2013 Rim fire and satellite information suggest the model does well at regional scale plume transport.

Firefighter attitudes, norms, beliefs, barriers, and behaviors toward post-fire decontamination processes in an era of increased cancer risk.

PubMed

Harrison, Tyler R; Muhamad, Jessica Wendorf; Yang, Fan; Morgan, Susan E; Talavera, Ed; Caban-Martinez, Alberto; Kobetz, Erin

2018-04-01

Firefighters are exposed to carcinogens such as volatile organic compounds (VOCs) and polycyclic aromatic hydrocarbons (PAHs) during fires and from their personal protective equipment (PPE). Recent research has shown that decontamination processes can reduce contamination on both gear and skin. While firefighter cultures that honor dirty gear are changing, little is known about current attitudes and behaviors toward decontamination in the fire service. Four hundred eighty-five firefighters from four departments completed surveys about their attitudes, beliefs, perceived norms, barriers, and behaviors toward post-fire decontamination processes. Overall, firefighters reported positive attitudes, beliefs, and perceived norms about decontamination, but showering after a fire was the only decontamination process that occurred regularly, with field decontamination, use of cleansing wipes, routine gear cleaning, and other behaviors all occurring less frequently. Firefighters reported time and concerns over wet gear as barriers to decontamination.

Convection and downbursts

Treesearch

Joseph J. Charney; Brian E. Potter

2017-01-01

Convection and downbursts are connected meteorological phenomena with the potential to affect fire behavior and thereby alter the evolution of a wildland fire. Meteorological phenomena related to convection and downbursts are often discussed in the context of fire behavior and smoke. The physical mechanisms that contribute to these phenomena are interrelated, but the...

Who repeats? A follow-up study of state hospital patients' firesetting behavior.

PubMed

Geller, J L; Fisher, W H; Bertsch, G

1992-01-01

The authors report on a population of psychiatric patients who were studied over a 6.75 year period to determine the occurrences of firesetting behavior noted in their psychiatric inpatient records. Two groups of 50 patients each were drawn from an earlier study and were matched by sex, age, and diagnoses. One group of patients had prior firesetting behavior; the other did not. Firesetting behavior was found not only in patients originally identified as having previously engaged in this behavior, but also in those with no documented history of this act prior to the period of the study. Patients having firesetting behavior in their past psychiatric record set more actual fires. Total number of episodes of firesetting behavior, however, was not significantly different between the two groups. Results are discussed in terms of the communicative function of firesetting and the dilemma of clinical prediction.

A way forward for fire-caused tree mortality prediction: Modeling a physiological consequence of fire

Treesearch

Kathleen L. Kavanaugh; Matthew B. Dickinson; Anthony S. Bova

2010-01-01

Current operational methods for predicting tree mortality from fire injury are regression-based models that only indirectly consider underlying causes and, thus, have limited generality. A better understanding of the physiological consequences of tree heating and injury are needed to develop biophysical process models that can make predictions under changing or novel...

[Prediction model of human-caused fire occurrence in the boreal forest of northern China].

PubMed

Guo, Fu-tao; Su, Zhang-wen; Wang, Guang-yu; Wang, Qiang; Sun, Long; Yang, Ting-ting

2015-07-01

The Chinese boreal forest is an important forest resource in China. However, it has been suffering serious disturbances of forest fires, which were caused equally by natural disasters (e.g., lightning) and human activities. The literature on human-caused fires indicates that climate, topography, vegetation, and human infrastructure are significant factors that impact the occurrence and spread of human-caused fires. But the studies on human-caused fires in the boreal forest of northern China are limited and less comprehensive. This paper applied the spatial analysis tools in ArcGIS 10.0 and Logistic regression model to investigate the driving factors of human-caused fires. Our data included the geographic coordinates of human-caused fires, climate factors during year 1974-2009, topographic information, and forest map. The results indicated that distance to railway (x1) and average relative humidity (x2) significantly impacted the occurrence of human-caused fire in the study area. The logistic model for predicting the fire occurrence probability was formulated as P= 1/[11+e-(3.026-0.00011x1-0.047x2)] with an accuracy rate of 80%. The above model was used to predict the monthly fire occurrence during the fire season of 2015 based on the HADCM2 future weather data. The prediction results showed that the high risk of human-caused fire occurrence concentrated in the months of April, May, June and August, while April and May had higher risk of fire occurrence than other months. According to the spatial distribution of possibility of fire occurrence, the high fire risk zones were mainly in the west and southwest of Tahe, where the major railways were located.

Effectiveness of mechanical thinning and prescribed burning on fire behavior in Pinus nigra forests in NE Spain.

PubMed

Piqué, Míriam; Domènech, Rut

2018-03-15

Fuel treatments can mitigate present and future impacts of climate change by reducing fire intensity and severity. In recent years, Pinus nigra forests in the Mediterranean basin have been dramatically affected by the new risk of highly intense and extreme fires and its distribution area has been reduced. New tools are necessary for assessing the management of these forests so they can adapt to the challenges to come. Our main goal was to evaluate the effects of different fuel treatments on Mediterranean Pinus nigra forests. We assessed the forest response, in terms of forest structure and fire behavior, to different intensities of low thinning treatments followed by different slash prescriptions (resulting in: light thinning and lop and scatter; light thinning and burn; heavy thinning and lop and scatter; heavy thinning and burn; and, untreated control). Treatments that used fire to decrease the resulting slash were the most effective for reducing active crown fires decreasing the rate of spread and flame length more than 89%. Low thinning had an effect on torching potential, but there was no difference between intensities of thinning. Only an outcoming crown fire could spread actively if it was sustained by a high-enough constant wind speed and enough surface fuel load. Overall, treatments reduce fire intensity and treated areas have a more homogenous fire behavior response than untreated areas. This provides opportunities to extinguish the fire and reduce the probability of trees dying from the fire. It would be helpful to include ecological principles and fire behavior criteria in silvicultural treatment guidelines in order to perform more efficient management techniques in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

Diurnal variation of marine stratocumulus over San Nicolas Island during the FIRE IFO

NASA Technical Reports Server (NTRS)

Davies, R.; Blaskovic, M.

1990-01-01

Preliminary analysis was made of data collected at San Nicolas Island during the Intensive Field Observation (IFO) phase of the First International Satellite Cloud Climatology Program's Regional Experiment (FIRE). Of particular interest was an examination of a distinct diurnal variation in the cloud properties, despite an apparent absence of diurnal forcing from the surface. Direct or indirect radiative modulation of such clouds, as proposed by Fravalo at el. (1981) and Turton and Nicholls (1987) indeed seems likely. Preliminary observational evidence for diurnal change in the marine stratocumulus adjacent to San Nicolas Island is presented. A comparison is then made between the observed behavior and predictions from theoretical models of the interactive effect of radiation on boundary layer clouds.

Assessing the predictability of fire occurrence and area burned across phytoclimatic regions in Spain

NASA Astrophysics Data System (ADS)

Bedia, J.; Herrera, S.; Gutiérrez, J. M.

2014-01-01

Most fire protection agencies throughout the world have developed forest fire risk forecast systems, usually building upon existing fire danger indices and meteorological forecast data. In this context, the daily predictability of wildfires is of utmost importance in order to allow the fire protection agencies to issue timely fire hazard alerts. In this study, we address the predictability of daily fire occurrence using the components of the Canadian Fire Weather Index (FWI) System and related variables calculated from the latest ECMWF (European Centre for Medium Range Weather Forecasts) reanalysis, ERA-Interim. We develop daily fire occurrence models in peninsular Spain for the period 1990-2008 and, considering different minimum burned area thresholds for fire definition, assess their ability to reproduce the inter-annual fire frequency variability. We based the analysis on a phytoclimatic classification aiming the stratification of the territory into homogeneous units in terms of climatic and fuel type characteristics, allowing to test model performance under different climate/fuel conditions. We then extend the analysis in order to assess the predictability of monthly burned areas. The sensitivity of the models to the level of spatial aggregation of the data is also evaluated. Additionally, we investigate the gain in model performance with the inclusion of socioeconomic and land use/land cover (LULC) covariates in model formulation. Fire occurrence models have attained good performance in most of the phytoclimatic zones considered, being able to faithfully reproduce the inter-annual variability of fire frequency. Total area burned has exhibited some dependence on the meteorological drivers, although model performance was poor in most cases. We identified temperature and some FWI system components as the most important explanatory variables, highlighting the adequacy of the FWI system for fire occurrence prediction in the study area. The results were improved when using aggregated data across regions compared to when data were sampled at the grid-box level. The inclusion of socioeconomic and LULC covariates contributed marginally to the improvement of the models, and in most cases attained no relevant contribution to total explained variance - excepting northern Spain, where anthropogenic factors are known to be the major driver of fires. Models of monthly fire counts performed better in the case of fires larger than 0.1 ha, and for the rest of the thresholds (1, 10 and 100 ha) the daily occurrence models improved the predicted inter-annual variability, indicating the added value of daily models. Fire frequency predictions may provide a preferable basis for past fire history reconstruction, long-term monitoring and the assessment of future climate impacts on fire regimes across regions, posing several advantages over burned area as a response variable. Our results leave the door open to the development a more complex modelling framework based on daily data from numerical climate model outputs based on the FWI system.

Projected changes in daily fire spread across Canada over the next century

NASA Astrophysics Data System (ADS)

Wang, Xianli; Parisien, Marc-André; Taylor, Steve W.; Candau, Jean-Noël; Stralberg, Diana; Marshall, Ginny A.; Little, John M.; Flannigan, Mike D.

2017-02-01

In the face of climate change, predicting and understanding future fire regimes across Canada is a high priority for wildland fire research and management. Due in large part to the difficulties in obtaining future daily fire weather projections, one of the major challenges in predicting future fire activity is to estimate how much of the change in weather potential could translate into on-the-ground fire spread. As a result, past studies have used monthly, annual, or multi-decadal weather projections to predict future fires, thereby sacrificing information relevant to day-to-day fire spread. Using climate projections from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), historical weather observations, MODIS fire detection data, and the national fire database of Canada, this study investigated potential changes in the number of active burning days of wildfires by relating ‘spread days’ to patterns of daily fire-conducive weather. Results suggest that climate change over the next century may have significant impacts on fire spread days in almost all parts of Canada’s forested landmass; the number of fire spread days could experience a 2-to-3-fold increase under a high CO2 forcing scenario in eastern Canada, and a greater than 50% increase in western Canada, where the fire potential is already high. The change in future fire spread is critical in understanding fire regime changes, but is also imminently relevant to fire management operations and in fire risk mitigation.

Simulating Fire Disturbance and Plant Mortality Using Antecedent Eco-hydrological Conditions to Inform a Physically Based Combustion Model

NASA Astrophysics Data System (ADS)

Atchley, A. L.; Linn, R.; Middleton, R. S.; Runde, I.; Coon, E.; Michaletz, S. T.

2016-12-01

Wildfire is a complex agent of change that both affects and depends on eco-hydrological systems, thereby constituting a tightly linked system of disturbances and eco-hydrological conditions. For example, structure, build-up, and moisture content of fuel are dependent on eco-hydrological regimes, which impacts fire spread and intensity. Fire behavior, on the other hand, determines the severity and extent of eco-hydrological disturbance, often resulting in a mosaic of untouched, stressed, damaged, or completely destroyed vegetation within the fire perimeter. This in turn drives new eco-hydrological system behavior. The cycles of disturbance and recovery present a complex evolving system with many unknowns especially in the face of climate change that has implications for fire risk, water supply, and forest composition. Physically-based numerical experiments that attempt to capture the complex linkages between eco-hydrological regimes that affect fire behavior and the echo-hydrological response from those fire disturbances help build the understanding required to project how fire disturbance and eco-hydrological conditions coevolve over time. Here we explore the use of FIRETEC—a physically-based 3D combustion model that solves conservation of mass, momentum, energy, and chemical species—to resolve fire spread over complex terrain and fuel structures. Uniquely, we couple a physically-based plant mortality model with FIRETEC and examine the resultant hydrologic impact. In this proof of concept demonstration we spatially distribute fuel structure and moisture content based on the eco-hydrological condition to use as input for FIRETEC. The fire behavior simulation then produces localized burn severity and heat injures which are used as input to a spatially-informed plant mortality model. Ultimately we demonstrate the applicability of physically-based models to explore integrated disturbance and eco-hydrologic response to wildfire behavior and specifically map how fire spread and intensity is affect by the antecedent eco-hydrological condition, which then affects the resulting tree mortality patterns.

Wildfires

MedlinePlus

... motels Expand sub-navigation Hotel fire safety tips Marijuana grow & extraction facilities Nightclubs and other assembly occupancies ... Fire behavior research Fire loss and injury research Benefits of home fire sprinklers Expand sub-navigation Environmental ...

The Behavioral Relevance of Cortical Neural Ensemble Responses Emerges Suddenly

PubMed Central

Sadacca, Brian F.; Mukherjee, Narendra; Vladusich, Tony; Li, Jennifer X.

2016-01-01

Whereas many laboratory-studied decisions involve a highly trained animal identifying an ambiguous stimulus, many naturalistic decisions do not. Consumption decisions, for instance, involve determining whether to eject or consume an already identified stimulus in the mouth and are decisions that can be made without training. By standard analyses, rodent cortical single-neuron taste responses come to predict such consumption decisions across the 500 ms preceding the consumption or rejection itself; decision-related firing emerges well after stimulus identification. Analyzing single-trial ensemble activity using hidden Markov models, we show these decision-related cortical responses to be part of a reliable sequence of states (each defined by the firing rates within the ensemble) separated by brief state-to-state transitions, the latencies of which vary widely between trials. When we aligned data to the onset of the (late-appearing) state that dominates during the time period in which single-neuron firing is correlated to taste palatability, the apparent ramp in stimulus-aligned choice-related firing was shown to be a much more precipitous coherent jump. This jump in choice-related firing resembled a step function more than it did the output of a standard (ramping) decision-making model, and provided a robust prediction of decision latency in single trials. Together, these results demonstrate that activity related to naturalistic consumption decisions emerges nearly instantaneously in cortical ensembles. SIGNIFICANCE STATEMENT This paper provides a description of how the brain makes evaluative decisions. The majority of work on the neurobiology of decision making deals with “what is it?” decisions; out of this work has emerged a model whereby neurons accumulate information about the stimulus in the form of slowly increasing firing rates and reach a decision when those firing rates reach a threshold. Here, we study a different kind of more naturalistic decision—a decision to evaluate “what shall I do with it?” after the identity of a taste in the mouth has been identified—and show that this decision is not made through the gradual increasing of stimulus-related firing, but rather that this decision appears to be made in a sudden moment of “insight.” PMID:26791199

Fire behavior and risk analysis in spacecraft

NASA Technical Reports Server (NTRS)

Friedman, Robert; Sacksteder, Kurt R.

1988-01-01

Practical risk management for present and future spacecraft, including space stations, involves the optimization of residual risks balanced by the spacecraft operational, technological, and economic limitations. Spacecraft fire safety is approached through three strategies, in order of risk: (1) control of fire-causing elements, through exclusion of flammable materials for example; (2) response to incipient fires through detection and alarm; and (3) recovery of normal conditions through extinguishment and cleanup. Present understanding of combustion in low gravity is that, compared to normal gravity behavior, fire hazards may be reduced by the absence of buoyant gas flows yet at the same time increased by ventilation flows and hot particle expulsion. This paper discusses the application of low-gravity combustion knowledge and appropriate aircraft analogies to fire detection, fire fighting, and fire-safety decisions for eventual fire-risk management and optimization in spacecraft.

Prediction suppression and surprise enhancement in monkey inferotemporal cortex.

PubMed

Ramachandran, Suchitra; Meyer, Travis; Olson, Carl R

2017-07-01

Exposing monkeys, over the course of days and weeks, to pairs of images presented in fixed sequence, so that each leading image becomes a predictor for the corresponding trailing image, affects neuronal visual responsiveness in area TE. At the end of the training period, neurons respond relatively weakly to a trailing image when it appears in a trained sequence and, thus, confirms prediction, whereas they respond relatively strongly to the same image when it appears in an untrained sequence and, thus, violates prediction. This effect could arise from prediction suppression (reduced firing in response to the occurrence of a probable event) or surprise enhancement (elevated firing in response to the omission of a probable event). To identify its cause, we compared firing under the prediction-confirming and prediction-violating conditions to firing under a prediction-neutral condition. The results provide strong evidence for prediction suppression and limited evidence for surprise enhancement. NEW & NOTEWORTHY In predictive coding models of the visual system, neurons carry signed prediction error signals. We show here that monkey inferotemporal neurons exhibit prediction-modulated firing, as posited by these models, but that the signal is unsigned. The response to a prediction-confirming image is suppressed, and the response to a prediction-violating image may be enhanced. These results are better explained by a model in which the visual system emphasizes unpredicted events than by a predictive coding model. Copyright © 2017 the American Physiological Society.

Information-Seeking and Sharing Behaviors among Fire Service Field Staff Instructors: A Qualitative Study

ERIC Educational Resources Information Center

Ruan, Lian J.

2011-01-01

Fire service field staff instructors seek and share information and use information sources during their instructional work of teaching, training and curriculum development. This study is the first attempt to study their information-seeking and sharing behaviors, which have not previously been investigated empirically. Twenty-five fire service…

The drivers of wildfire enlargement do not exhibit scale thresholds in southeastern Australian forests.

PubMed

Price, Owen F; Penman, Trent; Bradstock, Ross; Borah, Rittick

2016-10-01

Wildfires are complex adaptive systems, and have been hypothesized to exhibit scale-dependent transitions in the drivers of fire spread. Among other things, this makes the prediction of final fire size from conditions at the ignition difficult. We test this hypothesis by conducting a multi-scale statistical modelling of the factors determining whether fires reached 10 ha, then 100 ha then 1000 ha and the final size of fires >1000 ha. At each stage, the predictors were measures of weather, fuels, topography and fire suppression. The objectives were to identify differences among the models indicative of scale transitions, assess the accuracy of the multi-step method for predicting fire size (compared to predicting final size from initial conditions) and to quantify the importance of the predictors. The data were 1116 fires that occurred in the eucalypt forests of New South Wales between 1985 and 2010. The models were similar at the different scales, though there were subtle differences. For example, the presence of roads affected whether fires reached 10 ha but not larger scales. Weather was the most important predictor overall, though fuel load, topography and ease of suppression all showed effects. Overall, there was no evidence that fires have scale-dependent transitions in behaviour. The models had a predictive accuracy of 73%, 66%, 72% and 53% accuracy at 10 ha, 100 ha, 1000 ha and final size scales. When these steps were combined, the overall accuracy for predicting the size of fires was 62%, while the accuracy of the one step model was only 20%. Thus, the multi-scale approach was an improvement on the single scale approach, even though the predictive accuracy was probably insufficient for use as an operational tool. The analysis has also provided further evidence of the important role of weather, compared to fuel, suppression and topography in driving fire behaviour. Copyright © 2016. Published by Elsevier Ltd.

Multiscale simulation of a prescribed fire event in the New Jersey Pine Barrens using ARPS-CANOPY

Treesearch

Michael T. Kiefer; Warren E. Heilman; Shiyuan Zhong; Joseph J. Charney; Xindi Bian; Nicholas S. Skowronski; John L. Hom; Kenneth L. Clark; Matthew Patterson; Michael R. Gallagher

2014-01-01

Smoke prediction products are one of the tools used by land management personnel for decision making regarding prescribed fires. This study documents the application to a prescribed fire of a smoke prediction system that employs ARPS-CANOPY, a modified version of the Advanced Regional Prediction System (ARPS) model containing a canopy submodel, as the meteorological...

Error associated with model predictions of wildland fire rate of spread

Treesearch

Miguel G. Cruz; Martin E. Alexander

2015-01-01

How well can we expect to predict the spread rate of wildfires and prescribed fires? The degree of accuracy in model predictions of wildland fire behaviour characteristics are dependent on the model's applicability to a given situation, the validity of the model's relationships, and the reliability of the model input data (Alexander and Cruz 2013b#. We...

Using fire-weather forecasts and local weather observations in predicting burning index for individual fire-danger stations.

Treesearch

Owen P. Cramer

1958-01-01

Any agency engaged in forest-fire control needs accurate weather forecasts and systematic procedures for making the best use of predicted and reported weather information. This study explores the practicability of using several tabular and graphical aids for converting area forecasts and local observations of relative humidity and wind speed into predicted values for...

A review of logistic regression models used to predict post-fire tree mortality of western North American conifers

Treesearch

Travis Woolley; David C. Shaw; Lisa M. Ganio; Stephen Fitzgerald

2012-01-01

Logistic regression models used to predict tree mortality are critical to post-fire management, planning prescribed bums and understanding disturbance ecology. We review literature concerning post-fire mortality prediction using logistic regression models for coniferous tree species in the western USA. We include synthesis and review of: methods to develop, evaluate...

Estimating wildfire risk on a Mojave Desert landscape using remote sensing and field sampling

USGS Publications Warehouse

Van Linn, Peter F.; Nussear, Kenneth E.; Esque, Todd C.; DeFalco, Lesley A.; Inman, Richard D.; Abella, Scott R.

2013-01-01

Predicting wildfires that affect broad landscapes is important for allocating suppression resources and guiding land management. Wildfire prediction in the south-western United States is of specific concern because of the increasing prevalence and severe effects of fire on desert shrublands and the current lack of accurate fire prediction tools. We developed a fire risk model to predict fire occurrence in a north-eastern Mojave Desert landscape. First we developed a spatial model using remote sensing data to predict fuel loads based on field estimates of fuels. We then modelled fire risk (interactions of fuel characteristics and environmental conditions conducive to wildfire) using satellite imagery, our model of fuel loads, and spatial data on ignition potential (lightning strikes and distance to roads), topography (elevation and aspect) and climate (maximum and minimum temperatures). The risk model was developed during a fire year at our study landscape and validated at a nearby landscape; model performance was accurate and similar at both sites. This study demonstrates that remote sensing techniques used in combination with field surveys can accurately predict wildfire risk in the Mojave Desert and may be applicable to other arid and semiarid lands where wildfires are prevalent.

Predicting post-fire change in West Virginia, USA from remotely-sensed data

Treesearch

Michael P. Strager; Melissa Thomas-Van Gundy; Aaron E. Maxwell

2016-01-01

Prescribed burning is used in West Virginia, USA to return the important disturbance process of fire to oak and oak-pine forests. Species composition and structure are often the main goals for re-establishing fire with less emphasis on fuel reduction or reducing catastrophic wildfire. In planning prescribed fires land managers could benefit from the ability to predict...

Brief communication: Reaction to fire by savanna chimpanzees (Pan troglodytes verus) at Fongoli, Senegal: Conceptualization of "fire behavior" and the case for a chimpanzee model.

PubMed

Pruetz, Jill D; LaDuke, Thomas C

2010-04-01

The use and control of fire are uniquely human traits thought to have come about fairly late in the evolution of our lineage, and they are hypothesized to correlate with an increase in intellectual complexity. Given the relatively sophisticated cognitive abilities yet small brain size of living apes compared to humans and even early hominins, observations of wild chimpanzees' reactions to naturally occurring fire can help inform hypotheses about the likely responses of early hominins to fire. We use data on the behavior of savanna chimpanzees (Pan troglodytes verus) at Fongoli, Senegal during two encounters with wildfires to illuminate the similarities between great apes and humans regarding their reaction to fire. Chimpanzees' close relatedness to our lineage makes them phylogenetically relevant to the study of hominid evolution, and the open, hot and dry environment at Fongoli, similar to the savanna mosaic thought to characterize much of hominid evolution, makes these apes ecologically important as a living primate model as well. Chimpanzees at Fongoli calmly monitor wildfires and change their behavior in anticipation of the fire's movement. The ability to conceptualize the "behavior" of fire may be a synapomorphic trait characterizing the human-chimpanzee clade. If the cognitive underpinnings of fire conceptualization are a primitive hominid trait, hypotheses concerning the origins of the control and use of fire may need revision. We argue that our findings exemplify the importance of using living chimpanzees as models for better understanding human evolution despite recently published suggestions to the contrary. (c) 2009 Wiley-Liss, Inc.

Inaja Fire - 1956, Pine Hills Fire - 1967...similar, yet different

Treesearch

Mark J. Schroeder; Bernadine B. Taylor

1968-01-01

Two fires burned in the same area in southern California under nearly similar weather conditions, 11 years apart. Yet the Inaja fire of 1956 was much more disastrous than the Pine Hills fire of 1967. The earlier fire claimed 11 lives, and covered an area five times larger than the 1967 fire. Differences in fuels, topography, fire behavior, fire-control action, and...

Estimation of Wild Fire Risk Area based on Climate and Maximum Entropy in Korean Peninsular

NASA Astrophysics Data System (ADS)

Kim, T.; Lim, C. H.; Song, C.; Lee, W. K.

2015-12-01

The number of forest fires and accompanying human injuries and physical damages has been increased by frequent drought. In this study, forest fire danger zone of Korea is estimated to predict and prepare for future forest fire hazard regions. The MaxEnt (Maximum Entropy) model is used to estimate the forest fire hazard region which estimates the probability distribution of the status. The MaxEnt model is primarily for the analysis of species distribution, but its applicability for various natural disasters is getting recognition. The detailed forest fire occurrence data collected by the MODIS for past 5 years (2010-2014) is used as occurrence data for the model. Also meteorology, topography, vegetation data are used as environmental variable. In particular, various meteorological variables are used to check impact of climate such as annual average temperature, annual precipitation, precipitation of dry season, annual effective humidity, effective humidity of dry season, aridity index. Consequently, the result was valid based on the AUC(Area Under the Curve) value (= 0.805) which is used to predict accuracy in the MaxEnt model. Also predicted forest fire locations were practically corresponded with the actual forest fire distribution map. Meteorological variables such as effective humidity showed the greatest contribution, and topography variables such as TWI (Topographic Wetness Index) and slope also contributed on the forest fire. As a result, the east coast and the south part of Korea peninsula were predicted to have high risk on the forest fire. In contrast, high-altitude mountain area and the west coast appeared to be safe with the forest fire. The result of this study is similar with former studies, which indicates high risks of forest fire in accessible area and reflects climatic characteristics of east and south part in dry season. To sum up, we estimated the forest fire hazard zone with existing forest fire locations and environment variables and had meaningful result with artificial and natural effect. It is expected to predict future forest fire risk with future climate variables as the climate changes.

An unusual case of random fire-setting behavior associated with lacunar stroke.

PubMed

Bosshart, Herbert; Capek, Sonia

2011-06-15

A case of a 47-year-old man with a sudden onset of a bizarre and random fire-setting behavior is reported. The man, who had been arrested on felony arson charges, complained of difficulties concentrating and of recent memory impairment. Axial T1-weighted magnetic resonance imaging showed a low intensity lacunar lesion in the genu and anterior limb of the left internal capsule. A neuropsychological test battery revealed lower than normal scores for executive functions, attention and memory, consistent with frontal lobe dysfunction. The recent onset of fire-setting behavior and the chronic nature of the lacunar lesion, together with an unremarkable performance on tests measuring executive functions two years prior, suggested a causal relationship between this organic brain lesion and the fire-setting behavior. The present case describes a rare and as yet unreported association between random impulse-driven fire-setting behavior and damage to the left internal capsule and suggests a disconnection of frontal lobe structures as a possible pathogenic mechanism. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

FireWorks educational program and its effectiveness

Treesearch

Jane Kapler Smith; Nancy E. McMurray

2004-01-01

FireWorks is an educational program that provides interactive, hands-on activities for studying fire behavior, fire ecology, and human influences on three fire-dependent forest types-ponderosa pine (Pinus ponderosa), interior lodgepolepine (P. contorta var.latifolia), and whitebark pine (P. albicaulis)....

Great apes prefer cooked food.

PubMed

Wobber, Victoria; Hare, Brian; Wrangham, Richard

2008-08-01

The cooking hypothesis proposes that a diet of cooked food was responsible for diverse morphological and behavioral changes in human evolution. However, it does not predict whether a preference for cooked food evolved before or after the control of fire. This question is important because the greater the preference shown by a raw-food-eating hominid for the properties present in cooked food, the more easily cooking should have been adopted following the control of fire. Here we use great apes to model food preferences by Paleolithic hominids. We conducted preference tests with various plant and animal foods to determine whether great apes prefer food items raw or cooked. We found that several populations of captive apes tended to prefer their food cooked, though with important exceptions. These results suggest that Paleolithic hominids would likewise have spontaneously preferred cooked food to raw, exapting a pre-existing preference for high-quality, easily chewed foods onto these cooked items. The results, therefore, challenge the hypothesis that the control of fire preceded cooking by a significant period.

AEGIS: a wildfire prevention and management information system

NASA Astrophysics Data System (ADS)

Kalabokidis, K.; Ager, A.; Finney, M.; Athanasis, N.; Palaiologou, P.; Vasilakos, C.

2015-10-01

A Web-GIS wildfire prevention and management platform (AEGIS) was developed as an integrated and easy-to-use decision support tool (http://aegis.aegean.gr). The AEGIS platform assists with early fire warning, fire planning, fire control and coordination of firefighting forces by providing access to information that is essential for wildfire management. Databases were created with spatial and non-spatial data to support key system functionalities. Updated land use/land cover maps were produced by combining field inventory data with high resolution multispectral satellite images (RapidEye) to be used as inputs in fire propagation modeling with the Minimum Travel Time algorithm. End users provide a minimum number of inputs such as fire duration, ignition point and weather information to conduct a fire simulation. AEGIS offers three types of simulations; i.e. single-fire propagations, conditional burn probabilities and at the landscape-level, similar to the FlamMap fire behavior modeling software. Artificial neural networks (ANN) were utilized for wildfire ignition risk assessment based on various parameters, training methods, activation functions, pre-processing methods and network structures. The combination of ANNs and expected burned area maps produced an integrated output map for fire danger prediction. The system also incorporates weather measurements from remote automatic weather stations and weather forecast maps. The structure of the algorithms relies on parallel processing techniques (i.e. High Performance Computing and Cloud Computing) that ensure computational power and speed. All AEGIS functionalities are accessible to authorized end users through a web-based graphical user interface. An innovative mobile application, AEGIS App, acts as a complementary tool to the web-based version of the system.

Modeling and Analysis of Realistic Fire Scenarios in Spacecraft

NASA Technical Reports Server (NTRS)

Brooker, J. E.; Dietrich, D. L.; Gokoglu, S. A.; Urban, D. L.; Ruff, G. A.

2015-01-01

An accidental fire inside a spacecraft is an unlikely, but very real emergency situation that can easily have dire consequences. While much has been learned over the past 25+ years of dedicated research on flame behavior in microgravity, a quantitative understanding of the initiation, spread, detection and extinguishment of a realistic fire aboard a spacecraft is lacking. Virtually all combustion experiments in microgravity have been small-scale, by necessity (hardware limitations in ground-based facilities and safety concerns in space-based facilities). Large-scale, realistic fire experiments are unlikely for the foreseeable future (unlike in terrestrial situations). Therefore, NASA will have to rely on scale modeling, extrapolation of small-scale experiments and detailed numerical modeling to provide the data necessary for vehicle and safety system design. This paper presents the results of parallel efforts to better model the initiation, spread, detection and extinguishment of fires aboard spacecraft. The first is a detailed numerical model using the freely available Fire Dynamics Simulator (FDS). FDS is a CFD code that numerically solves a large eddy simulation form of the Navier-Stokes equations. FDS provides a detailed treatment of the smoke and energy transport from a fire. The simulations provide a wealth of information, but are computationally intensive and not suitable for parametric studies where the detailed treatment of the mass and energy transport are unnecessary. The second path extends a model previously documented at ICES meetings that attempted to predict maximum survivable fires aboard space-craft. This one-dimensional model implies the heat and mass transfer as well as toxic species production from a fire. These simplifications result in a code that is faster and more suitable for parametric studies (having already been used to help in the hatch design of the Multi-Purpose Crew Vehicle, MPCV).

Intrapsychic dynamics, behavioral manifestations, and related interventions with youthful fire setters.

PubMed

Williams, Dian L; Clements, Paul T

2007-01-01

Fire setting in youth has often been overlooked and misunderstood as a coping skill for expressing rage. The act of deliberate fire setting, if uninterrupted, may continue throughout an individual's lifetime. Forensic examiners, mental health care providers, and criminal justice professionals can help guide referral and treatment through better understanding of behaviors and intrapsychic dynamics.

Nomographs for estimating surface fire behavior characteristics

Treesearch

Joe H. Scott

2007-01-01

A complete set of nomographs for estimating surface fire rate of spread and flame length for the original 13 and new 40 fire behavior fuel models is presented. The nomographs allow calculation of spread rate and flame length for wind in any direction with respect to slope and allow for nonheading spread directions. Basic instructions for use are included.

Invasive grasses change landscape structure and fire behavior in Hawaii

Treesearch

Lisa M. Ellsworth; Creighton M. Litton; Alexander P. Dale; Tomoaki Miura

2014-01-01

How does potential fire behavior differ in grass-invaded non-native forests vs open grasslands? How has land cover changed from 1950–2011 along two grassland/forest ecotones in Hawaii with repeated fires? A study on non-native forest with invasive grass understory and invasive grassland (Megathyrsus maximus) ecosystems on Oahu, Hawaii, USA was...

Use of Video Modeling to Teach Extinguishing of Cooking Related Fires to Individuals with Moderate Intellectual Disabilities

ERIC Educational Resources Information Center

Mechling, Linda C.; Gast, David L.; Gustafson, Melissa R.

2009-01-01

This study evaluated the effectiveness of video modeling to teach fire extinguishing behaviors to three young adults with moderate intellectual disabilities. A multiple probe design across three fire extinguishing behaviors and replicated across three students was used to evaluate the effectiveness of the video-based program. Results indicate that…

Practical tools for assessing potential crown fire behavior and canopy fuel characteristics

Treesearch

Martin E. Alexander; Miguel G. Cruz

2015-01-01

This presentation recapitulates the main points made at a technology and information transfer workshop held in advance of the conference that provided overviews of two software applications, developed by the authors, for use in assessing crown fire behavior and canopy fuel characteristics. These are the Crown Fire Initiation and Spread (CFIS) software system and the...

Establishing Fire Safety Skills Using Behavioral Skills Training

ERIC Educational Resources Information Center

Houvouras, Andrew J., IV; Harvey, Mark T.

2014-01-01

The use of behavioral skills training (BST) to educate 3 adolescent boys on the risks of lighters and fire setting was evaluated using in situ assessment in a school setting. Two participants had a history of fire setting. After training, all participants adhered to established rules: (a) avoid a deactivated lighter, (b) leave the training area,…

Early fire history near Papineau lake, Ontario

Treesearch

Daniel C. Dey; Richard P. Guyette

1996-01-01

Research that defines the role of fire in upland red oak-pine ecosystems in central Ontario is being conducted by the Great Lakes-St. Lawrence Silviculture program. Site-specific fire histories are being developed that document fire frequency, fire behavior, fire effects on forest regeneration and grwoth, and the influnce of human activites on fire disturbances. This...

Forecasting distribution of numbers of large fires

Treesearch

Haiganoush K. Preisler; Jeff Eidenshink; Stephen Howard; Robert E. Burgan

2015-01-01

Systems to estimate forest fire potential commonly utilize one or more indexes that relate to expected fire behavior; however they indicate neither the chance that a large fire will occur, nor the expected number of large fires. That is, they do not quantify the probabilistic nature of fire danger. In this work we use large fire occurrence information from the...

Electric ants: A cross-disciplinary approach to understanding insect behavior

DOE Office of Scientific and Technical Information (OSTI.GOV)

Slowik, T.J.; Thorvilson, H.G.; Green, B.L.

1996-12-31

The response and attraction of the red imported fire ant, Solenopsis invicta, to electrical equipment was examined using an interdisciplinary approach. Entomologists specializing in fire ant behavior combined expertise with electrical engineers to investigate the economically damaging interaction of fire ants with electrical circuitry. Knowledge from the realms of physics, engineering, and biology were integrated in experimentation to test for a fire ant response to electric fields and magnetic fields associated with electrical equipment. It was determined that fire ants react to electrified conductive material and the alternating-current magnetic fields associated with electricity.

Fire hazards at the urban-wildland interface: What the public expects

NASA Astrophysics Data System (ADS)

Cortner, Hanna J.; Gardner, Philip D.; Taylor, Jonathan G.

1990-01-01

Urban-wildland issues have become among the most contentious and problematic issues for forest managers. Using data drawn from surveys conducted by the authors and others, this article discusses how public knowledge and perceptions of fire policies and fire hazards change over time, the kinds of policy responses homeowners prefer as a way of preventing fire hazards at the urban-wildland interface, and how citizens view their own obligations as participants in interface issues. These data show that public attitudes toward fire have changed significantly over the past two decades and that educating the public about fire and the managers' use of fire can have positive effects on behavior. Yet, modifying the individual's behavior in regard to interface fire risks must also deal with important issues of individual incentives, the distribution of costs, and unanticipated policy impacts.

Fire hazards at the urban-wildland interface: what the public expects

USGS Publications Warehouse

Cortner, Hanna J.; Gardner, Philip D.; Taylor, Jonathan G.

1990-01-01

Urban-wildland issues have become among the most contentious and problematic issues for forest managers. Using data drawn from surveys conducted by the authors and others, this article discusses how public knowledge and perceptions of fire policies and fire hazards change over time, the kinds of policy responses homeowners prefer as a way of preventing fire hazards at the urban-wildland interface, and how citizens view their own obligations as participants in interface issues. These data show that public attitudes toward fire have changed significantly over the past two decades and that educating the public about fire and the managers' use of fire can have positive effects on behavior. Yet, modifying the individual's behavior in regard to interface fire risks must also deal with important issues of individual incentives, the distribution of costs, and unanticipated policy impacts.

Prevalence and correlates of fire-setting in the United States: results from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC).

PubMed

Blanco, Carlos; Alegría, Analucía A; Petry, Nancy M; Grant, Jon E; Simpson, H Blair; Liu, Shang-Min; Grant, Bridget F; Hasin, Deborah S

2010-09-01

To estimate the prevalence, sociodemographic correlates, comorbidity, and rates of mental health service utilization of fire-setters in the general population. A face-to-face survey of more than 43,000 adults aged 18 years and older residing in households was conducted during the 2001-2002 period. Diagnoses of mood, anxiety, substance use disorders, and personality disorders were based on the Alcohol Use Disorder and Associated Disabilities Interview Schedule-DSM-IV Version (AUDADIS-IV). The prevalence of lifetime fire-setting in the US population was 1.13 (95% CI, 1.0-1.3). Being male, never married, and US-born and having a yearly income over $70,000 were risk factors for lifetime fire-setting, while being Asian or Hispanic and older than 30 years were protective factors for lifetime fire-setting. The strongest associations with fire-setting were with disorders often associated with deficits in impulse control, such as antisocial personality disorder (ASPD) (odds ratio [OR] = 21.8; CI, 6.6-28.5), drug dependence (OR = 7.6; 95% CI, 5.2-10.9), bipolar disorder (OR = 5.6; 95% CI, 4.0-7.9), and pathological gambling (OR = 4.8; 95% CI, 2.4-9.5). Associations between fire-setting and all antisocial behaviors were positive and significant. A lifetime history of fire-setting, even in the absence of an ASPD diagnosis, was strongly associated with substantial rates of Axis I comorbidity, a history of antisocial behavior, a family history of other antisocial behaviors, decreased functioning, and higher treatment-seeking rates. Our findings suggest that fire-setting may be better understood as a behavioral manifestation of a broader impaired control syndrome and part of the externalizing spectrum. Fire-setting and other antisocial behaviors tend to be strongly associated with each other and increase the risk of lifetime and current psychiatric disorders, even in the absence of a DSM-IV diagnosis of ASPD. © Copyright 2010 Physicians Postgraduate Press, Inc.

Development of a model to predict ash transport and water pollution risk in fire-affected environments

NASA Astrophysics Data System (ADS)

Neris, Jonay; Elliot, William J.; Doerr, Stefan H.; Robichaud, Peter R.

2017-04-01

An estimated that 15% of the world's population lives in volcanic areas. Recent catastrophic erosion events following wildfires in volcanic terrain have highlighted the geomorphological instability of this soil type under disturbed conditions and steep slopes. Predicting the hydrological and erosional response of this soils in the post-fire period is the first step to design and develop adequate actions to minimize risks in the post-fire period. In this work we apply, for the first time, the Water Erosion Prediction Project model for predicting erosion and runoff events in fire-affected volcanic soils in Europe. Two areas affected by wildfires in 2015 were selected in Tenerife (Spain) representative of different fire behaviour (downhill surface fire with long residence time vs uphill crown fire with short residence time), severity (moderate soil burn severity vs light soil burn severity) and climatic conditions (average annual precipitation of 750 and 210 mm respectively). The actual erosion processes were monitored in the field using silt fences. Rainfall and rill simulations were conducted to determine hydrologic, interrill and rill erosion parameters. The soils were sampled and key properties used as model input, evaluated. During the first 18 months after the fire 7 storms produced runoff and erosion in the selected areas. Sediment delivery reached 5.4 and 2.5 Mg ha-1 respectively in the first rainfall event monitored after the fire, figures comparable to those reported for fire-affected areas of the western USA with similar climatic conditions but lower than those showed by wetter environments. The validation of the WEPP model using field data showed reasonable estimates of hillslope sediment delivery in the post-fire period and, therefore, it is suggested that this model can support land managers in volcanic areas in Europe in predicting post-fire hydrological and erosional risks and designing suitable mitigation treatments.

First application of the WEPP model to predict runoff and erosion risk in fire-affected volcanic areas in Europe

NASA Astrophysics Data System (ADS)

Neris, Jonay; Robichaud, Peter R.; Elliot, William J.; Doerr, Stefan H.; Notario del Pino, Jesús S.; Lado, Marcos

2017-04-01

An estimated that 15% of the world's population lives in volcanic areas. Recent catastrophic erosion events following wildfires in volcanic terrain have highlighted the geomorphological instability of this soil type under disturbed conditions and steep slopes. Predicting the hydrological and erosional response of this soils in the post-fire period is the first step to design and develop adequate actions to minimize risks in the post-fire period. In this work we apply, for the first time, the Water Erosion Prediction Project model for predicting erosion and runoff events in fire-affected volcanic soils in Europe. Two areas affected by wildfires in 2015 were selected in Tenerife (Spain) representative of different fire behaviour (downhill surface fire with long residence time vs uphill crown fire with short residence time), severity (moderate soil burn severity vs light soil burn severity) and climatic conditions (average annual precipitation of 750 and 210 mm respectively). The actual erosion processes were monitored in the field using silt fences. Rainfall and rill simulations were conducted to determine hydrologic, interrill and rill erosion parameters. The soils were sampled and key properties used as model input, evaluated. During the first 18 months after the fire 7 storms produced runoff and erosion in the selected areas. Sediment delivery reached 5.4 and 2.5 Mg ha-1 respectively in the first rainfall event monitored after the fire, figures comparable to those reported for fire-affected areas of the western USA with similar climatic conditions but lower than those showed by wetter environments. The validation of the WEPP model using field data showed reasonable estimates of hillslope sediment delivery in the post-fire period and, therefore, it is suggested that this model can support land managers in volcanic areas in Europe in predicting post-fire hydrological and erosional risks and designing suitable mitigation treatments.

A method for mapping fire hazard and risk across multiple scales and its application in fire management

Treesearch

Robert E. Keane; Stacy A. Drury; Eva C. Karau; Paul F. Hessburg; Keith M. Reynolds

2010-01-01

This paper presents modeling methods for mapping fire hazard and fire risk using a research model called FIREHARM (FIRE Hazard and Risk Model) that computes common measures of fire behavior, fire danger, and fire effects to spatially portray fire hazard over space. FIREHARM can compute a measure of risk associated with the distribution of these measures over time using...

The Cooney Ridge Fire Experiment: An early operation to relate pre-, active, and post-fire field and remotely sensed measurements

Treesearch

Andrew T. Hudak; Patrick H. Freeborn; Sarah A. Lewis; Sharon M. Hood; Helen Y. Smith; Colin C. Hardy; Robert J. Kremens; Bret W. Butler; Casey Teske; Robert G. Tissell; Lloyd P. Queen; Bryce L. Nordgren; Benjamin C. Bright; Penelope Morgan; Philip J. Riggan; Lee Macholz; Leigh B. Lentile; James P. Riddering; Edward E. Mathews

2018-01-01

The Cooney Ridge Fire Experiment conducted by fire scientists in 2003 was a burnout operation supported by a fire suppression crew on the active Cooney Ridge wildfire incident. The fire experiment included measurements of pre-fire fuels, active fire behavior, and immediate post-fire effects. Heat flux measurements collected at multiple scales with multiple ground and...

Relationship of surface fuels to fire radiative energy as estimated from airborne lidar and thermal infrared imaging

NASA Astrophysics Data System (ADS)

Hudak, A. T.; Dickinson, M. B.; Kremens, R.; Loudermilk, L.; O'Brien, J.; Satterberg, K.; Strand, E. K.; Ottmar, R. D.

2013-12-01

Longleaf pine stand structure and function are dependent on frequent fires, so fire managers maintain healthy longleaf pine ecosystems by frequently burning surface fuels with prescribed fires. Eglin Air Force Base (AFB) in the Florida panhandle boasts the largest remnant of longleaf pine forest, providing a productive setting for fire scientists to make multi-scale measurements of fuels, fire behavior, and fire effects in collaboration with Eglin AFB fire managers. Data considered in this analysis were collected in five prescribed burn units: two forested units burned in 2011 and a forested unit and two grassland units burned in 2012. Our objective was to demonstrate the linear relationship between biomass and fire energy that has been shown in the laboratory, but using two independent remotely sensed airborne datasets collected at the unit level: 1) airborne lidar flown over the burn units immediately prior to the burns, and 2) thermal infrared image time series flown over the burn units at 2-3 minute intervals. Airborne lidar point cloud data were reduced to 3 m raster metrics of surface vegetation height and cover, which were in turn used to map surface fuel loads at 3 m resolution. Plot-based measures of prefire surface fuels were used for calibration/validation. Preliminary results based on 2011 data indicate airborne lidar can explain ~30% of variation in surface fuel loads. Multi-temporal thermal infrared imagery (WASP) collected at 3 m resolution were calibrated to units of fire radiative power (FRP), using simultaneous FRP measures from ground-based radiometers, and then temporally integrated to estimate fire radiative energy (FRE) release at the unit level. Prior to AGU, FRP and FRE will be compared to estimates of the same variables derived from ground-based FLIR thermal infrared imaging cameras, each deployed with a nadir view from a tripod, at three sites per burn unit. A preliminary proof-of-concept, comparing FRE derived from a tripod-based FLIR (3.2 MW), to another FLIR deployed with an oblique view from atop a 36 m boom lift (2.1 MW), demonstrated reasonable agreement. Unit-level estimates of FRE will also be compared to estimates of surface fuel consumption (~5 Mg/ha) that were summarized at the unit level from pre- and post-fire clip plots of surface fuel biomass. At AGU, we will also compare predictions of surface fuel loads to estimates of energy release, as mapped at 3 m resolution from these independent remotely sensed data sources. These results will serve to demonstrate our ability to remotely measure and relate fuel loads to fire behavior at a landscape level.

A cost effective FBG-based security fence with fire alarm function

NASA Astrophysics Data System (ADS)

Wu, H. J.; Li, S. S.; Lu, X. L.; Wu, Y.; Rao, Y. J.

2012-02-01

Fiber Bragg Grating (FBG) is sensitive to the temperature as well when it is measuring the strain change, which is always avoided in most measurement applications. However, in this paper strain/temperature dual sensitivity is utilized to construct a special security fence with a second function of fire threat prediction. In an FBG-based fiber fence configuration, only by characteristics analysis and identification method, it can intelligently distinguish the different effects of personal threats and fires from their different trends of the wavelength drifts. Thus without any additional temperature sensing fittings or other fire alarm systems integrated, a normal perimeter security system can possess a second function of fire prediction, which can not only monitor the intrusion induced by personal actions but also predict fire threats in advance. The experimental results show the effectiveness of the method.

Fire behavior modeling-a decision tool

Treesearch

Jack Cohen; Bill Bradshaw

1986-01-01

The usefulness of an analytical model as a fire management decision tool is determined by the correspondence of its descriptive capability to the specific decision context. Fire managers must determine the usefulness of fire models as a decision tool when applied to varied situations. Because the wildland fire phenomenon is complex, analytical fire spread models will...

Domains of Risk in the Developmental Continuity of Fire Setting

ERIC Educational Resources Information Center

McCarty, Carolyn A.; McMahon, Robert J.

2005-01-01

Juvenile fire setting is a serious, dangerous, and costly behavior. The majority of research examining youth fire setting has been cross-sectional. We sought to examine early risk attributes that could differentiate fire setters from non-fire setters, in addition to examining their association with the developmental continuity of fire-setting…

Fire growth maps for the 1988 Greater Yellowstone Area Fires

Treesearch

Richard C. Rothermel; Roberta A Hartford; Carolyn H. Chase

1994-01-01

Daily fire growth maps display the growth of the 1988 fires in the Greater Yellowstone Area. Information and data sources included daily infrared photography flights, satellite imagery, ground and aerial reconnaissance, command center intelligence, and the personal recollections of fire behavior observers. Fire position was digitized from topographic maps using GRASS...

Little Bear Fire Summary Report

Treesearch

Sarah McCaffrey; Melanie Stidham; Hannah. Brenkert-Smith

2013-01-01

In June 2012, immediately after the Little Bear Fire burned outside Ruidoso, New Mexico, a team of researchers interviewed fire managers, local personnel, and residents to understand perceptions of the event itself, communication, evacuation, and pre-fire preparedness. The intensity of fire behavior and resulting loss of 242 homes made this a complex fire with a...

Laboratory fire behavior measurements of chaparral crown fire

Treesearch

C. Sanpakit; S. Omodan; D. Weise; M Princevac

2015-01-01

In 2013, there was an estimated 9,900 wildland fires that claimed more than 577,000 acres of land. That same year, about 542 prescribed fires were used to treat 48,554 acres by several agencies in California. Being able to understand fires using laboratory models can better prepare individuals to combat or use fires. Our research focused on chaparral crown fires....

Fire and Smoke Model Evaluation Experiment (FASMEE): Modeling gaps and data needs

Treesearch

Yongqiang Liu; Adam Kochanski; Kirk Baker; Ruddy Mell; Rodman Linn; Ronan Paugam; Jan Mandel; Aime Fournier; Mary Ann Jenkins; Scott Goodrick; Gary Achtemeier; Andrew Hudak; Matthew Dickson; Brian Potter; Craig Clements; Shawn Urbanski; Roger Ottmar; Narasimhan Larkin; Timothy Brown; Nancy French; Susan Prichard; Adam Watts; Derek McNamara

2017-01-01

Fire and smoke models are numerical tools for simulating fire behavior, smoke dynamics, and air quality impacts of wildland fires. Fire models are developed based on the fundamental chemistry and physics of combustion and fire spread or statistical analysis of experimental data (Sullivan 2009). They provide information on fire spread and fuel consumption for safe and...

Response of Bighead Carp and Silver Carp to repeated water gun operation in an enclosed shallow pond

USGS Publications Warehouse

Romine, Jason G.; Jensen, Nathan; Parsley, Michael J.; Gaugush, Robert F.; Severson, Todd J.; Hatton, Tyson W.; Adams, Ryan F.; Gaikowski, Mark P.

2015-01-01

The Bighead Carp Hypophthalmichthys nobilis and Silver Carp H. molitrix are nonnative species that pose a threat to Great Lakes ecosystems should they advance into those areas. Thus, technologies to impede Asian carp movement into the Great Lakes are needed; one potential technology is the seismic water gun. We evaluated the efficacy of a water gun array as a behavioral deterrent to the movement of acoustic-tagged Bighead Carp and Silver Carp in an experimental pond. Behavioral responses were evaluated by using four metrics: (1) fish distance from the water guns (D); (2) spatial area of the fish's utilization distribution (UD); (3) persistence velocity (Vp); and (4) number of times a fish transited the water gun array. For both species, average D increased by 10 m during the firing period relative to the pre-firing period. During the firing period, the spatial area of use within the pond decreased. Carp were located throughout the pond during the pre-firing period but were concentrated in the north end of the pond during the firing period, thus reducing their UDs by roughly 50%. Overall, Vp decreased during the firing period relative to the pre-firing period, as fish movement became more tortuous and confined, suggesting that the firing of the guns elicited a change in carp behavior. The water gun array was partially successful at impeding carp movement, but some fish did transit the array. Bighead Carp moved past the guns a total of 78 times during the pre-firing period and 15 times during the firing period; Silver Carp moved past the guns 96 times during the pre-firing period and 13 times during the firing period. Although the water guns did alter carp behavior, causing the fish to move away from the guns, this method was not 100% effective as a passage deterrent.

A tilting wind tunnel for fire behavior studies

Treesearch

David R. Weise

1994-01-01

The combined effects of wind velocity and slope on wildland fire behavior can be studied in the laboratory using a tilting wind tunnel. The tilting wind tunnel requires a commercially available fan to induce wind and can be positioned to simulate heading and backing fires spreading up and down slope. The tunnel is portable and can be disassembled for transport using a...

Photo guide for estimating fuel loading and fire behavior in mixed-oak forests of the Mid-Atlantic Region

Treesearch

Patrick H. Brose

2009-01-01

A field guide of 45 pairs of photographs depicting ericaceous shrub, leaf litter, and logging slash fuel types of eastern oak forests and observed fire behavior of these fuel types during prescribed burning. The guide contains instructions on how to use the photo guide to choose appropriate fuel models for prescribed fire planning.

A simplified test for adhesive behavior in wood sections exposed to fire

Treesearch

E. L. Schaffer

1968-01-01

A relatively simple test procedure was developed to evaluate the behavior of various adhesives near fire-exposed surfaces in laminated constructions. A number of sections cut from laminated blocks were exposed to fire on one surface. After this exposure, the sections were transversely cut, and the gluelines were examined for separation depth. In addition, the cool...

1st Fire Behavior and Fuels Conference: Fuels Management-How to Measure Success

Treesearch

Patricia L. Andrews

2006-01-01

The 1st Fire Behavior and Fuels Conference: Fuels Management -- How to Measure Success was held in Portland, Oregon, March 28-30, 2006. The International Association of Wildland Fire (IAWF) initiated a conference on this timely topic primarily in response to the needs of the U.S. National Interagency Fuels Coordinating Group (http://www.nifc.gov/).

Investigation of firebrand generation from an experimental fire: Development of a reliable data collection methodology

Treesearch

Jan C. Thomas; Eric V. Mueller; Simon Santamaria; Michael Gallagher; Mohamad El Houssami; Alexander Filkov; Kenneth Clark; Nicholas Skowronski; Rory M. Hadden; William Mell; Albert Simeoni

2017-01-01

An experimental approach has been developed to quantify the characteristics and flux of firebrands during a management-scale wildfire in a pine-dominated ecosystem. By characterizing the local fire behavior and measuring the temporal and spatial variation in firebrand collection, the flux of firebrands has been related to the fire behavior for the first time. This...

Photo Series for Estimating Post-Hurricane Residues and Fire Behavior in Southern Pine

Treesearch

Dale D. Wade; James K. Forbus; James M. Saveland

1993-01-01

Following Hurricane Hugo, fuels were sampled on nine 2-acre blocks which were then burned during the spring wildfire season. The study was superimposed on dormant-season fire-interval research plots established in 1958 on the Francis Marion National Forest near Charleston, SC. Photographs of preburn fuel loads, fire behavior, and postburn fuel loads were taken to...

Evaluating potential changes in fire risk from Eucalyptus plantings in the Southern United States

Treesearch

Scott L. Goodrick; John A. Stanturf

2012-01-01

Renewed interest in short-rotation woody crops for bioenergy and bioproducts has prompted a reevaluation of the Eucalyptus species for the southern United States. One question that arises about the potential effects of introducing a nonnative species is what effect will there be on fire behavior. Our approximate answer based on modeling fire behavior...

The potential predictability of fire danger provided by ECMWF forecast

NASA Astrophysics Data System (ADS)

Di Giuseppe, Francesca

2017-04-01

The European Forest Fire Information System (EFFIS), is currently being developed in the framework of the Copernicus Emergency Management Services to monitor and forecast fire danger in Europe. The system provides timely information to civil protection authorities in 38 nations across Europe and mostly concentrates on flagging regions which might be at high danger of spontaneous ignition due to persistent drought. The daily predictions of fire danger conditions are based on the US Forest Service National Fire Danger Rating System (NFDRS), the Canadian forest service Fire Weather Index Rating System (FWI) and the Australian McArthur (MARK-5) rating systems. Weather forcings are provided in real time by the European Centre for Medium range Weather Forecasts (ECMWF) forecasting system. The global system's potential predictability is assessed using re-analysis fields as weather forcings. The Global Fire Emissions Database (GFED4) provides 11 years of observed burned areas from satellite measurements and is used as a validation dataset. The fire indices implemented are good predictors to highlight dangerous conditions. High values are correlated with observed fire and low values correspond to non observed events. A more quantitative skill evaluation was performed using the Extremal Dependency Index which is a skill score specifically designed for rare events. It revealed that the three indices were more skilful on a global scale than the random forecast to detect large fires. The performance peaks in the boreal forests, in the Mediterranean, the Amazon rain-forests and southeast Asia. The skill-scores were then aggregated at country level to reveal which nations could potentiallty benefit from the system information in aid of decision making and fire control support. Overall we found that fire danger modelling based on weather forecasts, can provide reasonable predictability over large parts of the global landmass.

Local and regional smoke impacts from prescribed fires

NASA Astrophysics Data System (ADS)

Price, Owen F.; Horsey, Bronwyn; Jiang, Ningbo

2016-10-01

Smoke from wildfires poses a significant threat to affected communities. Prescribed burning is conducted to reduce the extent and potential damage of wildfires, but produces its own smoke threat. Planners of prescribed fires model the likely dispersion of smoke to help manage the impacts on local communities. Significant uncertainty remains about the actual smoke impact from prescribed fires, especially near the fire, and the accuracy of smoke dispersal models. To address this uncertainty, a detailed study of smoke dispersal was conducted for one small (52 ha) and one large (700 ha) prescribed fire near Appin in New South Wales, Australia, through the use of stationary and handheld pollution monitors, visual observations and rain radar data, and by comparing observations to predictions from an atmospheric dispersion model. The 52 ha fire produced a smoke plume about 800 m high and 9 km long. Particle concentrations (PM2.5) reached very high peak values (> 400 µg m-3) and high 24 h average values (> 100 µg m-3) at several locations next to or within ˜ 500 m downwind from the fire, but low levels elsewhere. The 700 ha fire produced a much larger plume, peaking at ˜ 2000 m altitude and affecting downwind areas up to 14 km away. Both peak and 24 h average PM2.5 values near the fire were lower than for the 52 ha fire, but this may be because the monitoring locations were further away from the fire. Some lofted smoke spread north against the ground-level wind direction. Smoke from this fire collapsed to the ground during the night at different times in different locations. Although it is hard to attribute particle concentrations definitively to smoke, it seems that the collapsed plume affected a huge area including the towns of Wollongong, Bargo, Oakdale, Camden and Campbelltown (˜ 1200 km2). PM2.5 concentrations up to 169 µg m-3 were recorded on the morning following the fire. The atmospheric dispersion model accurately predicted the general behaviour of both plumes in the early phases of the fires, but was poor at predicting fine-scale variation in particulate concentrations (e.g. places 500 m from the fire). The correlation between predicted and observed varied between 0 and 0.87 depending on location. The model also completely failed to predict the night-time collapse of the plume from the 700 ha fire. This study provides a preliminary insight into the potential for large impacts from prescribed fire smoke to NSW communities and the need for increased accuracy in smoke dispersion modelling. More research is needed to better understand when and why such impacts might occur and provide better predictions of pollution risk.

Forest fuels and predicted fire behavior in the first 5 years after a bark beetle outbreak with and without timber harvest (Project INT-EM-F-11-04) [Chapter 12

Treesearch

Carolyn Sieg; Kurt Allen; Chad Hoffman; Joel McMillin

2016-01-01

Unprecedented levels of tree mortality from native bark beetle species have occurred in a variety of forest types in Western United States and Canada in recent decades in response to beetle-favorable forest and climatic conditions (Bentz 2009, Meddens and others 2012). Previous studies suggest that bark beetle outbreaks alter stand structural attributes and fuel...

Smoke Alarms for People Who Are Deaf or Hard-of-Hearing

MedlinePlus

... motels Expand sub-navigation Hotel fire safety tips Marijuana grow & extraction facilities Nightclubs and other assembly occupancies ... Fire behavior research Fire loss and injury research Benefits of home fire sprinklers Expand sub-navigation Environmental ...

A Drone Remote Sensing for Virtual Reality Simulation System for Forest Fires: Semantic Neural Network Approach

NASA Astrophysics Data System (ADS)

Narasimha Rao, Gudikandhula; Jagadeeswara Rao, Peddada; Duvvuru, Rajesh

2016-09-01

Wild fires have significant impact on atmosphere and lives. The demand of predicting exact fire area in forest may help fire management team by using drone as a robot. These are flexible, inexpensive and elevated-motion remote sensing systems that use drones as platforms are important for substantial data gaps and supplementing the capabilities of manned aircraft and satellite remote sensing systems. In addition, powerful computational tools are essential for predicting certain burned area in the duration of a forest fire. The reason of this study is to built up a smart system based on semantic neural networking for the forecast of burned areas. The usage of virtual reality simulator is used to support the instruction process of fire fighters and all users for saving of surrounded wild lives by using a naive method Semantic Neural Network System (SNNS). Semantics are valuable initially to have a enhanced representation of the burned area prediction and better alteration of simulation situation to the users. In meticulous, consequences obtained with geometric semantic neural networking is extensively superior to other methods. This learning suggests that deeper investigation of neural networking in the field of forest fires prediction could be productive.

WIFIRE: A Scalable Data-Driven Monitoring, Dynamic Prediction and Resilience Cyberinfrastructure for Wildfires

NASA Astrophysics Data System (ADS)

Altintas, I.; Block, J.; Braun, H.; de Callafon, R. A.; Gollner, M. J.; Smarr, L.; Trouve, A.

2013-12-01

Recent studies confirm that climate change will cause wildfires to increase in frequency and severity in the coming decades especially for California and in much of the North American West. The most critical sustainability issue in the midst of these ever-changing dynamics is how to achieve a new social-ecological equilibrium of this fire ecology. Wildfire wind speeds and directions change in an instant, and first responders can only be effective when they take action as quickly as the conditions change. To deliver information needed for sustainable policy and management in this dynamically changing fire regime, we must capture these details to understand the environmental processes. We are building an end-to-end cyberinfrastructure (CI), called WIFIRE, for real-time and data-driven simulation, prediction and visualization of wildfire behavior. The WIFIRE integrated CI system supports social-ecological resilience to the changing fire ecology regime in the face of urban dynamics and climate change. Networked observations, e.g., heterogeneous satellite data and real-time remote sensor data is integrated with computational techniques in signal processing, visualization, modeling and data assimilation to provide a scalable, technological, and educational solution to monitor weather patterns to predict a wildfire's Rate of Spread. Our collaborative WIFIRE team of scientists, engineers, technologists, government policy managers, private industry, and firefighters architects implement CI pathways that enable joint innovation for wildfire management. Scientific workflows are used as an integrative distributed programming model and simplify the implementation of engineering modules for data-driven simulation, prediction and visualization while allowing integration with large-scale computing facilities. WIFIRE will be scalable to users with different skill-levels via specialized web interfaces and user-specified alerts for environmental events broadcasted to receivers before, during and after a wildfire. Scalability of the WIFIRE approach allows many sensors to be subjected to user-specified data processing algorithms to generate threshold alerts within seconds. Integration of this sensor data into both rapidly available fire image data and models will better enable situational awareness, responses and decision support at local, state, national, and international levels. The products of WIFIRE will be initially disseminated to our collaborators (SDG&E, CAL FIRE, USFS), covering academic, private, and government laboratories while generating values to emergency officials, and consequently to the general public. WIFIRE may be used by government agencies in the future to save lives and property during wildfire events, test the effectiveness of response and evacuation scenarios before they occur and assess the effectiveness of high-density sensor networks in improving fire and weather predictions. WIFIRE's high-density network, therefore, will serve as a testbed for future applications worldwide.

A Comparative Analysis on the Temporal and Spatial Distribution of Fire Characteristics in the Amazon and Equatorial Southern Africa Using Observations from Space

NASA Astrophysics Data System (ADS)

Tang, Wenfu; Arellano, Avelino. F.; Raman, Aishwarya

2015-04-01

Tropical forest fires significantly impact atmospheric composition and regional and global climate. In particular, fires in Equatorial Southern Africa (ESA) and Amazon comprise the two largest contributors to fire emissions of chemically and radiatively-active atmospheric constituents (such as CO, BC, CO2) across the globe. Here, we investigate the spatiotemporal trends in fire characteristics between these regions using combustion signatures observed from space. Our main goals are: 1) To identify key relationships between the trends in co-emitted constituents across these regions, and, 2) To explore linkages of the observed trends in fire characteristics with the main drivers of change such as meteorology, fire practice, development patterns, and ecosystem feedbacks. We take advantage of the similarity in latitude and land area between these regions in understanding some of these drivers. Our approach begins with a multi-species analysis of trends in the observed abundance of CO, NO2, and aerosols over these regions and across the time period 2004 to 2014. We use multi-spectral retrievals of CO from Measurements Of Pollution In The Troposphere (MOPITT), tropospheric column retrievals of NO2 from Ozone Monitoring Instrument (OMI), and aerosol optical depth retrievals from Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. The long records from these retrievals provide a unique opportunity to study atmospheric composition across the most recent decade. While several studies in the past have reported trends over these regions, most of these studies have focused on a particular constituent. A unique aspect of this work involves understanding covariations in co-emitted constituents to provide a more comprehensive look at fire characteristics and behavior, which are yet to be fully understood. Our initial results show that the annual average of CO for ESA (~115 ppbv) is greater than that of Amazon (110 ppbv). This pattern is also seen in NO2 (ESA : ~215 pptv ; Amazon : ~155 pptv). The standard deviation of CO is higher in Amazon (50 ppbv) when compared to ESA (35 ppbv) whereas NO2 shows similar standard deviation in Amazon and ESA (70-90 pptv). We also find changes in the timing patterns of the large fire events across these regions. Since this has important implications to changes in fire behavior (smoldering and flaming phase), we also investigated retrievals of fire radiative power (FRP) from MODIS and information on land cover change and deforestation. We find FRP patterns consistent with our results. Finally, we will explore other measurements available during this period (aircraft field campaigns and in-situ observations) and compare with current fire emission models, such as the Global Fire Emission Database (GFED) to test the robustness of our findings. We note that this exploratory work provides a unique perspective of fire characteristics that will be useful to improve predictive capability of fire emission and atmospheric models for the Amazon and ESA.

Restoring and managing low-severity fire in dry-forest landscapes of the western USA.

PubMed

Baker, William L

2017-01-01

Low-severity fires that killed few canopy trees played a significant historical role in dry forests of the western USA and warrant restoration and management, but historical rates of burning remain uncertain. Past reconstructions focused on on dating fire years, not measuring historical rates of burning. Past statistics, including mean composite fire interval (mean CFI) and individual-tree fire interval (mean ITFI) have biases and inaccuracies if used as estimators of rates. In this study, I used regression, with a calibration dataset of 96 cases, to test whether these statistics could accurately predict two equivalent historical rates, population mean fire interval (PMFI) and fire rotation (FR). The best model, using Weibull mean ITFI, had low prediction error and R2adj = 0.972. I used this model to predict historical PMFI/FR at 252 sites spanning dry forests. Historical PMFI/FR for a pool of 342 calibration and predicted sites had a mean of 39 years and median of 30 years. Short (< 25 years) mean PMFI/FRs were in Arizona and New Mexico and scattered in other states. Long (> 55 years) mean PMFI/FRs were mainly from northern New Mexico to South Dakota. Mountain sites often had a large range in PMFI/FR. Nearly all 342 estimates are for old forests with a history of primarily low-severity fire, found across only about 34% of historical dry-forest area. Frequent fire (PMFI/FR < 25 years) was found across only about 14% of historical dry-forest area, with 86% having multidecadal rates of low-severity fire. Historical fuels (e.g., understory shrubs and small trees) could fully recover between multidecadal fires, allowing some denser forests and some ecosystem processes and wildlife habitat to be less limited by fire. Lower historical rates mean less restoration treatment is needed before beginning managed fire for resource benefits, where feasible. Mimicking patterns of variability in historical low-severity fire regimes would likely benefit biological diversity and ecosystem functioning.

Climate change and future fire regimes: Examples from California

USGS Publications Warehouse

Keeley, Jon E.; Syphard, Alexandra D.

2016-01-01

Climate and weather have long been noted as playing key roles in wildfire activity, and global warming is expected to exacerbate fire impacts on natural and urban ecosystems. Predicting future fire regimes requires an understanding of how temperature and precipitation interact to control fire activity. Inevitably this requires historical analyses that relate annual burning to climate variation. Fuel structure plays a critical role in determining which climatic parameters are most influential on fire activity, and here, by focusing on the diversity of ecosystems in California, we illustrate some principles that need to be recognized in predicting future fire regimes. Spatial scale of analysis is important in that large heterogeneous landscapes may not fully capture accurate relationships between climate and fires. Within climatically homogeneous subregions, montane forested landscapes show strong relationships between annual fluctuations in temperature and precipitation with area burned; however, this is strongly seasonal dependent; e.g., winter temperatures have very little or no effect but spring and summer temperatures are critical. Climate models that predict future seasonal temperature changes are needed to improve fire regime projections. Climate does not appear to be a major determinant of fire activity on all landscapes. Lower elevations and lower latitudes show little or no increase in fire activity with hotter and drier conditions. On these landscapes climate is not usually limiting to fires but these vegetation types are ignition-limited. Moreover, because they are closely juxtaposed with human habitations, fire regimes are more strongly controlled by other direct anthropogenic impacts. Predicting future fire regimes is not rocket science; it is far more complicated than that. Climate change is not relevant to some landscapes, but where climate is relevant, the relationship will change due to direct climate effects on vegetation trajectories, as well as by feedback processes of fire effects on vegetation distribution, plus policy changes in how we manage ecosystems.

Restoring and managing low-severity fire in dry-forest landscapes of the western USA

PubMed Central

2017-01-01

Low-severity fires that killed few canopy trees played a significant historical role in dry forests of the western USA and warrant restoration and management, but historical rates of burning remain uncertain. Past reconstructions focused on on dating fire years, not measuring historical rates of burning. Past statistics, including mean composite fire interval (mean CFI) and individual-tree fire interval (mean ITFI) have biases and inaccuracies if used as estimators of rates. In this study, I used regression, with a calibration dataset of 96 cases, to test whether these statistics could accurately predict two equivalent historical rates, population mean fire interval (PMFI) and fire rotation (FR). The best model, using Weibull mean ITFI, had low prediction error and R2adj = 0.972. I used this model to predict historical PMFI/FR at 252 sites spanning dry forests. Historical PMFI/FR for a pool of 342 calibration and predicted sites had a mean of 39 years and median of 30 years. Short (< 25 years) mean PMFI/FRs were in Arizona and New Mexico and scattered in other states. Long (> 55 years) mean PMFI/FRs were mainly from northern New Mexico to South Dakota. Mountain sites often had a large range in PMFI/FR. Nearly all 342 estimates are for old forests with a history of primarily low-severity fire, found across only about 34% of historical dry-forest area. Frequent fire (PMFI/FR < 25 years) was found across only about 14% of historical dry-forest area, with 86% having multidecadal rates of low-severity fire. Historical fuels (e.g., understory shrubs and small trees) could fully recover between multidecadal fires, allowing some denser forests and some ecosystem processes and wildlife habitat to be less limited by fire. Lower historical rates mean less restoration treatment is needed before beginning managed fire for resource benefits, where feasible. Mimicking patterns of variability in historical low-severity fire regimes would likely benefit biological diversity and ecosystem functioning. PMID:28199416

Comparison of crown fire modeling systems used in three fire management applications

Treesearch

Joe H. Scott

2006-01-01

The relative behavior of surface-crown fire spread rate modeling systems used in three fire management applications-CFIS (Crown Fire Initiation and Spread), FlamMap and NEXUS- is compared using fire environment characteristics derived from a dataset of destructively measured canopy fuel and associated stand characteristics. Although the surface-crown modeling systems...

Simulating spatial and temporally related fire weather

Treesearch

Isaac C. Grenfell; Mark Finney; Matt Jolly

2010-01-01

Use of fire behavior models has assumed an increasingly important role for managers of wildfire incidents to make strategic decisions. For fire risk assessments and danger rating at very large spatial scales, these models depend on fire weather variables or fire danger indices. Here, we describe a method to simulate fire weather at a national scale that captures the...

Decision making under uncertainty: Recommendations for the Wildland Fire Decision Support System (WFDSS)

Treesearch

Matthew P. Thompson

2015-01-01

The management of wildfire is a dynamic, complex, and fundamentally uncertain enterprise. Fire managers face uncertainties regarding fire weather and subsequent influence on fire behavior, the effects of fire on socioeconomic and ecological resources, and the efficacy of alternative suppression actions on fire outcomes. In these types of difficult decision environments...

Atmospheric turbulence observations in the vicinity of surface fires in forested environments

Treesearch

Warren E. Heilman; Xindi Bian; Kenneth L. Clark; Nicholas S. Skowronski; John L. Hom; Michael R. Gallagher

2017-01-01

Ambient and fire-induced atmospheric turbulence in the vicinity of wildland fires can affect the behavior of those fires and the dispersion of smoke. The presence of forest overstory vegetation can further complicate the evolution of local turbulence regimes and their interaction with spreading fires and smoke plumes. Previous observational studies of wildland fire...

Decision modeling for analyzing fire action outcomes

Treesearch

Donald MacGregor; Armando Gonzalez-Caban

2008-01-01

A methodology for incident decomposition and reconstruction is developed based on the concept of an "event-frame model." The event-frame model characterizes a fire incident in terms of (a) environmental events that pertain to the fire and the fire context (e.g., fire behavior, weather, fuels) and (b) management events that represent responses to the fire...

Shift in fire-ecosystems and weather changes

Treesearch

Bongani Finiza

2013-01-01

During recent decades too much focus fell on fire suppression and fire engineering methods. Little attention has been given to understanding the shift in the changing fire weather resulting from the global change in weather patterns. Weather change have gradually changed the way vegetation cover respond to fire occurrence and brought about changes in fire behavior and...

Fire occurrence prediction in the Mediterranean: Application to Southern France

NASA Astrophysics Data System (ADS)

Papakosta, Panagiota; Öster, Jan; Scherb, Anke; Straub, Daniel

2013-04-01

The areas that extend in the Mediterranean basin have a long fire history. The climatic conditions of wet winters and long hot drying summers support seasonal fire events, mainly ignited by humans. Extended land fragmentation hinders fire spread, but seasonal winds (e.g. Mistral in South France or Meltemia in Greece) can drive fire events to become uncontrollable fires with severe impacts to humans and the environment [1]. Prediction models in these areas should incorporate both natural and anthropogenic factors. Several indices have been developed worldwide to express fire weather conditions. The Canadian Fire Weather Index (FWI) is currently adapted by many countries in Europe due to the easily observable input weather parameters (temperature, wind speed, relative humidity, precipitation) and the easy-to-implement algorithms of the Canadian formulation describing fuel moisture relations [2],[3]. Human influence can be expressed directly by human presence (e.g. population density) or indirectly by proxy indicators (e.g. street density [4], land cover type). The random nature of fire occurrences and the uncertainties associated with the influencing factors motivate probabilistic prediction models. The aim of this study is to develop a prediction model of fire occurrence probability under natural and anthropogenic influence in Southern France and to compare it with earlier developed predictions in other Mediterranean areas [5]. Fire occurrence is modeled as a Poisson process. Two interpolation methods (Kriging and Inverse Distance Weighting) are used to interpolate daily weather observations from weather stations to a 1 km² spatial grid and their results are compared. Poisson regression estimates the parameters of the model and the resulting daily predictions are provided in terms of maps displaying fire occurrence rates. The model is applied to the regions Provence-Alpes-Côtes D'Azur und Languedoc-Roussillon in the South of France. Weather data are obtained from the German and French Weather Services (Deutscher Wetterdienst and Météo-France). Historical fire events are taken from Prométhée database. Time series 2000-2010 are used as learning data and data from 2011 is used as the validation data. The resulting model can support real-time fire risk estimation for improved allocation of firefighting resources and planning of other mitigation actions. [1] Keeley, J.E.; Bond, W.J.; Bradstock, R.A.; Pausas, J.G.; Rundel, P.W. (2012): Fire in Mediterranean ecosystems: ecology, evolution and management. Cambridge University Press, New York, USA, pp.515 [2] Lawson, B.D.; Armitage, O.B. (2008): Weather Guide for the Canadian Forest Fire Danger Rating System. Natural Resources Canada, Canadian Forest Service, Northern Forestry Centre, Edmonton, Alberta, Canada. [3] Van Wagner, C.E.; Pickett, T.L. (1985): Equations and FORTRAN Program for the Canadian Forest Fire Weather Index System. Forestry Technical Report 33. Canadian Forestry Service, Government of Canada, Ottawa, Ontario, Canada [4] Syphard, A.D.; Radeloff, V.C.; Keuler, N.S.; Taylor, R.S.; Hawbaker, T.J.; Stewart, S.I.; Clayton, M.K. (2008): Predicting spatial patterns of fire on a southern California landscape. International Journal of Wildland Fire, 17, pp.602-613 [5] Papakosta, P.; Klein, F.; König, S.; Straub, D. (2012): Linking spatio-temporal data to the Fire Weather Index to estimate the probability of wildfire in the Mediterranean. Geophysical Research Abstracts, Vol.14, EGU2012-12737, EGU General Assembly 2012

Prediction of forest fires occurrences with area-level Poisson mixed models.

PubMed

Boubeta, Miguel; Lombardía, María José; Marey-Pérez, Manuel Francisco; Morales, Domingo

2015-05-01

The number of fires in forest areas of Galicia (north-west of Spain) during the summer period is quite high. Local authorities are interested in analyzing the factors that explain this phenomenon. Poisson regression models are good tools for describing and predicting the number of fires per forest areas. This work employs area-level Poisson mixed models for treating real data about fires in forest areas. A parametric bootstrap method is applied for estimating the mean squared errors of fires predictors. The developed methodology and software are applied to a real data set of fires in forest areas of Galicia. Copyright © 2015 Elsevier Ltd. All rights reserved.

On the temperature prediction in a fire escape passage

NASA Astrophysics Data System (ADS)

Casano, G.; Piva, S.

2017-11-01

Fire safety engineering requires a detailed understanding of fire behaviour and of its effects on structures and people. Many factors may condition the fire scenario, as for example, heat transfer between the flame and the boundary structures. Currently advanced numerical codes for the prediction of the fire behaviour are available. However, these solutions often require heavy calculations and long times. In this context analytical solutions can be useful for a fast analysis of simplified schematizations. After that, it is more effective the final utilization of the advanced fire codes. In this contribution, the temperature in a fire escape passage, separated with a thermally resistant wall from a fire room, is analysed. The escape space is included in a building where the neighbouring rooms are at a constant undisturbed temperature. The presence of the neighbouring rooms is considered with an equivalent heat transfer coefficient, in a boundary condition of the third type. An analytical solution is used to predict the temperature distribution during the fire. It allows to obtain useful information on the temperature reached in the escape area in contact with a burning room; it is useful also for a fast choice of the thermal characteristics of a firewall.

Fuels planning: science synthesis and integration; forest structure and fire hazard fact sheet 02: fire hazard

Treesearch

Rocky Mountain Research Station USDA Forest Service

2004-01-01

Fire hazard reflects the potential fire behavior and magnitude of effects as a function of fuel conditions. This fact sheet discusses crown fuels, surface fuels, and ground fuels and their contribution and involvement in wildland fire.Other publications in this series...

The fire environment--innovations, management, and policy; conference proceedings

Treesearch

Bret W. Butler; Wayne Cook

2007-01-01

The International Association of Wildland Fire sponsored the second Fire Behavior and Fuels conference in Destin, Florida. The conference theme was "Fire Environment--Innovations, Management, and Policy." Over 450 attendees participated in presentations on the latest innovations in wildland fire management, examples of successful and maybe not so successful...

Resource allocation for wildland fire suppression planning using a stochastic program

Treesearch

Alex Taylor Masarie

2011-01-01

Resource allocation for wildland fire suppression problems, referred to here as Fire-S problems, have been studied for over a century. Not only have the many variants of the base Fire-S problem made it such a durable one to study, but advances in suppression technology and our ever-expanding knowledge of and experience with wildland fire behavior have required almost...

Effectiveness of Fire and Fire Surrogate Treatments For Controlling Wildfire Behavior in Piedmont Forests: A Simulation Study

Treesearch

Helen H. Mohr; Thomas A. Waldrop; Sandra Rideout; Ross J. Phillips; Charles T. Flint

2004-01-01

The need for fuel reduction has increased in United States forests due to decades of fire exclusion. Excessive fuel buildup has led to uncharacteristically severe fires in areas with historically short-interval, low-to-moderate-intensity fire regimes. The National Fire and Fire Surrogate (NFFS) Study compared the impacts of three fuel-reduction treatments on numerous...

Fire and forest history at Mount Rushmore.

PubMed

Brown, Peter M; Wienk, Cody L; Symstad, Amy J

2008-12-01

Mount Rushmore National Memorial in the Black Hills of South Dakota is known worldwide for its massive sculpture of four of the United States' most respected presidents. The Memorial landscape also is covered by extensive ponderosa pine (Pinus ponderosa) forest that has not burned in over a century. We compiled dendroecological and forest structural data from 29 plots across the 517-ha Memorial and used fire behavior modeling to reconstruct the historical fire regime and forest structure and compare them to current conditions. The historical fire regime is best characterized as one of low-severity surface fires with occasional (> 100 years) patches (< 100 ha) of passive crown fire. We estimate that only approximately 3.3% of the landscape burned as crown fire during 22 landscape fire years (recorded at > or = 25% of plots) between 1529 and 1893. The last landscape fire was in 1893. Mean fire intervals before 1893 varied depending on spatial scale, from 34 years based on scar-to-scar intervals on individual trees to 16 years between landscape fire years. Modal fire intervals were 11-15 years and did not vary with scale. Fire rotation (the time to burn an area the size of the study area) was estimated to be 30 years for surface fire and 800+ years for crown fire. The current forest is denser and contains more small trees, fewer large trees, lower canopy base heights, and greater canopy bulk density than a reconstructed historical (1870) forest. Fire behavior modeling using the NEXUS program suggests that surface fires would have dominated fire behavior in the 1870 forest during both moderate and severe weather conditions, while crown fire would dominate in the current forest especially under severe weather. Changes in the fire regime and forest structure at Mount Rushmore parallel those seen in ponderosa pine forests from the southwestern United States. Shifts from historical to current forest structure and the increased likelihood of crown fire justify the need for forest restoration before a catastrophic wildfire occurs and adversely impacts the ecological and aesthetic setting of the Mount Rushmore sculpture.

Using NASA Satellite Observations to Map Wildfire Risk in the United States for Allocation of Fire Management Resources

NASA Astrophysics Data System (ADS)

Farahmand, A.; Reager, J. T., II; Behrangi, A.; Stavros, E. N.; Randerson, J. T.

2017-12-01

Fires are a key disturbance globally acting as a catalyst for terrestrial ecosystem change and contributing significantly to both carbon emissions and changes in surface albedo. The socioeconomic impacts of wildfire activities are also significant with wildfire activity results in billions of dollars of losses every year. Fire size, area burned and frequency are increasing, thus the likelihood of fire danger, defined by United States National Interagency Fire Center (NFIC) as the demand of fire management resources as a function of how flammable fuels (a function of ignitability, consumability and availability) are from normal, is an important step toward reducing costs associated with wildfires. Numerous studies have aimed to predict the likelihood of fire danger, but few studies use remote sensing data to map fire danger at scales commensurate with regional management decisions (e.g., deployment of resources nationally throughout fire season with seasonal and monthly prediction). Here, we use NASA Gravity Recovery And Climate Experiment (GRACE) assimilated surface soil moisture, NASA Atmospheric Infrared Sounder (AIRS) vapor pressure deficit, NASA Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index products and landcover products, along with US Forest Service historical fire activity data to generate probabilistic monthly fire potential maps in the United States. These maps can be useful in not only government operational allocation of fire management resources, but also improving understanding of the Earth System and how it is changing in order to refine predictions of fire extremes.

Ecological effects of the Hayman Fire - Part 1: Historical (pre-1860) and current (1860-2002) fire regimes

Treesearch

William H. Romme; Thomas T. Veblen; Merrill R. Kaufmann; Rosemary Sherriff; Claudia M. Regan

2003-01-01

To address historical and current fire regimes in the Hayman landscape, we first present the concepts of “historical range of variability” and ”fire regime” to provide the necessary conceptual tools for evaluating fire occurrence, fire behavior, and fire effects. Next we summarize historical (pre-1860) fire frequency and fire effects for the major forest types of the...

The influence of an incomplete fuels treatment on fire behavior and effects in the 2007 Tin Cup Fire, Bitterroot National Forest, Montana

Treesearch

Michael Harrington; Erin Noonan-Wright

2010-01-01

Extensive forested areas have received fuels treatments in recent decades and significant funding is available for additional treatments in an attempt to mitigate undesirable high wildfire intensities and impacts. Fuel treatment successes and failures in moderating fire behavior and effects can be found in quantified and anecdotal reports. Questions remain about the...

Use of models to study forest fire behavior

Treesearch

Wallace L. Fons

1961-01-01

The U.S. Forest Service has started a laboratory study with the ultimate objective of determining model laws for fire behavior. The study includes an examination of the effect of such variables as species of wood, density of wood, moisture content, size of fuel particle, spacing, dimensions of fuel bed, wind, and slope on the rate of spread of fire and the partition of...

Wild Fire Computer Model Helps Firefighters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Canfield, Jesse

2012-09-04

A high-tech computer model called HIGRAD/FIRETEC, the cornerstone of a collaborative effort between U.S. Forest Service Rocky Mountain Research Station and Los Alamos National Laboratory, provides insights that are essential for front-line fire fighters. The science team is looking into levels of bark beetle-induced conditions that lead to drastic changes in fire behavior and how variable or erratic the behavior is likely to be.

Wild Fire Computer Model Helps Firefighters

ScienceCinema

Canfield, Jesse

2018-02-14

A high-tech computer model called HIGRAD/FIRETEC, the cornerstone of a collaborative effort between U.S. Forest Service Rocky Mountain Research Station and Los Alamos National Laboratory, provides insights that are essential for front-line fire fighters. The science team is looking into levels of bark beetle-induced conditions that lead to drastic changes in fire behavior and how variable or erratic the behavior is likely to be.

Strategic Placement of Treatments (SPOTS): Maximizing the Effectiveness of Fuel and Vegetation Treatments on Problem Fire Behavior and Effects

Treesearch

Diane M. Gercke; Susan A. Stewart

2006-01-01

In 2005, eight U.S. Forest Service and Bureau of Land Management interdisciplinary teams participated in a test of strategic placement of treatments (SPOTS) techniques to maximize the effectiveness of fuel treatments in reducing problem fire behavior, adverse fire effects, and suppression costs. This interagency approach to standardizing the assessment of risks and...

Predicting fire spread in Arizona's oak chaparral

Treesearch

A. W. Lindenmuth; James R. Davis

1973-01-01

Five existing fire models, both experimental and theoretical, did not adequately predict rate-of-spread (ROS) when tested on single- and multiclump fires in oak chaparral in Arizona. A statistical model developed using essentially the same input variables but weighted differently accounted for 81 percent ofthe variation in ROS. A chemical coefficient that accounts for...

Fuel consumption models for pine flatwoods fuel types in the southeastern United States

Treesearch

Clinton S. Wright

2013-01-01

Modeling fire effects, including terrestrial and atmospheric carbon fluxes and pollutant emissions during wildland fires, requires accurate predictions of fuel consumption. Empirical models were developed for predicting fuel consumption from fuel and environmental measurements on a series of operational prescribed fires in pine flatwoods ecosystems in the southeastern...

Impacts of single and recurrent wildfires on topsoil moisture regime

NASA Astrophysics Data System (ADS)

González-Pelayo, Oscar; Malvar, Maruxa; van den Elsen, Erik; Hosseini, Mohammadreza; Coelho, Celeste; Ritsema, Coen; Bautista, Susana; Keizer, Jacob

2017-04-01

The increasing fire recurrence on forest in the Mediterranean basin is well-established by future climate scenarios due to land use changes and climate predictions. By this, shifts on mature pine woodlands to shrub rangelands are of major importance on forest ecosystems buffer functions, since historical patterns of established vegetation help to recover from fire disturbances. This fact, together with the predicted expansion of the drought periods, will affect feedback processes of vegetation patterns since water availability on these seasons are driven by post-fire local soil properties. Although fire impacts of soil properties and water availability has been widely studied using the fire severity as the main factor, little research is developed on post-fire soil moisture patterns, including the fire recurrence as a key explanatory variable. The following research investigated, in pine woodlands of north central Portugal, the short-term consequences (one year after a fire) of wildfire recurrence on the surface soil moisture content (SMC) and on effective soil water (SWEFF, parameter that includes actual daily soil moisture, soil field capacity-FC and permanent wilting point-PWP). The study set-up includes analyses at two fire recurrence scenarios (1x- and 4x-burnt since 1975), at a patch level (shrub patch/interpatch) and at two soil depths (2.5 and 7.5 cm) in a nested approach. Understanding how fire recurrence affects water in soil over space and time is the main goal of this research. The use of soil moisture sensors in a nested approach, the rainfall features and analyses on basic soil properties as soil organic matter, texture, bulk density, pF curves, soil water repellency and soil surface components will establish which factors has the largest role in controlling soil moisture behavior. Main results displayed, in a seasonal and yearly basis, no differences on SMC as increasing fire recurrence (1x- vs 4x-burnt) neither between patch/interpatch microsites at both two soil depths. Otherwise, in a yearly basis and during soil drying cycles, it was found less effective water on soil at the surface layers of the 4x-burnt and between shrub interpatches, based on the worst soil hydrological conditions (PWP) and the increasing percentage of abiotic soil surface components as increasing fire recurrence. Our results suggest that the inclusion of soil hydrological properties, as pF-curves, on the soil water effectiveness calculation seems to be a better indicator of water availability that volumetric SM per se. Otherwise, the use of a nested approach methodology, stresses how fire recurrence, expected increases in the summer drought spells and, the increasing dominance of abiotic soil surface components, are the factors that much influence soil eco-hydrological functioning in fire prone ecosystems. Furthermore, this research point out how post-fire soil structural quality into plant interpatches could provoke looping feedback processes triggering desertification situations also in humid Mediterranean forestlands.

Friendly fire: Longitudinal effects of exposure to violent video games on aggressive behavior in adolescent friendship dyads.

PubMed

Verheijen, Geert P; Burk, William J; Stoltz, Sabine E M J; van den Berg, Yvonne H M; Cillessen, Antonius H N

2018-05-01

Research on gaming effects has focused on adolescence, a developmental period in which peer relationships become increasingly salient. However, the impact of peers on the effects of violent gaming on adolescents has been understudied. This study examined whether adolescents' exposure to violent video games predicted their own and their friend's aggression one year later. Among 705 gaming adolescents, 141 dyads were identified based on reciprocated best friend nominations (73.8% male, M age  = 13.98). Actor-Partner Interdependence Models indicated that adolescent males' (but not females') exposure to violent games positively predicted the aggression of their best friend 1 year later. This effect appeared regardless of whether the friends played video games together or not. The study illustrates the importance of peers in the association between violent gaming and aggression. © 2018 The Authors. Aggressive Behavior Published by Wiley Periodicals, Inc.

Chapter 4. Predicting post-fire erosion and sedimentation risk on a landscape scale

USGS Publications Warehouse

MacDonald, L.H.; Sampson, R.; Brady, D.; Juarros, L.; Martin, Deborah

2000-01-01

Historic fire suppression efforts have increased the likelihood of large wildfires in much of the western U.S. Post-fire soil erosion and sedimentation risks are important concerns to resource managers. In this paper we develop and apply procedures to predict post-fire erosion and sedimentation risks on a pixel-, catchment-, and landscape-scale in central and western Colorado.Our model for predicting post-fire surface erosion risk is conceptually similar to the Revised Universal Soil Loss Equation (RUSLE). One key addition is the incorporation of a hydrophobicity risk index (HY-RISK) based on vegetation type, predicted fire severity, and soil texture. Post-fire surface erosion risk was assessed for each 90-m pixel by combining HYRISK, slope, soil erodibility, and a factor representing the likely increase in soil wetness due to removal of the vegetation. Sedimentation risk was a simple function of stream gradient. Composite surface erosion and sedimentation risk indices were calculated and compared across the 72 catchments in the study area.When evaluated on a catchment scale, two-thirds of the catchments had relatively little post-fire erosion risk. Steeper catchments with higher fuel loadings typically had the highest post-fire surface erosion risk. These were generally located along the major north-south mountain chains and, to a lesser extent, in west-central Colorado. Sedimentation risks were usually highest in the eastern part of the study area where a higher proportion of streams had lower gradients. While data to validate the predicted erosion and sedimentation risks are lacking, the results appear reasonable and are consistent with our limited field observations. The models and analytic procedures can be readily adapted to other locations and should provide useful tools for planning and management at both the catchment and landscape scale.

Fires and fuels: Vegetation change over time in the Zuni Mountains, New Mexico

NASA Astrophysics Data System (ADS)

Wylie, Luke Anthony

The Zuni Mountains are a region that has been dramatically changed by human interference. Anthropogenically, fire suppression practices have allowed a buildup of fuels and caused a change in the fire-adapted ponderosa pine ecosystem such that the new ecosystem now incorporates many fire-intolerant species. As a result, the low-severity fires that the ecosystem once depended on to regenerate the forest are much reduced, and these low-severity fires are now replaced by crown-level infernos that threaten the forest and nearby towns. In order to combat these effects, land managers are implementing fuel reduction practices and are striving to better understand the local ecosystem. In this study, a predictive fire spread model (FARSITE) was implemented to predict spatio-temporal distribution of fire in the Zuni Mountains based on change in vegetation types that are most prone to fire. Using Landsat imagery and historical fire spread data from 2001 to 2014, the following research questions were investigated: (1) What variables are responsible for fire spread in the Zuni Mountains, New Mexico? (2) Which areas are prone to destructive and canopy level fires? and (3) How have the fuel model types that are most conducive to fire spread changed in the past twenty years? The utilization of spatial modeling and remote sensing to understand the interaction of meteorological variables and vegetation in predicting fire spread in this region is a novel approach. This study showed that (i) fires are more likely to occur in the valleys and high elevation grassland areas of the Zuni Mountains, (ii) certain vegetation types including grass and shrub lands in the area present a greater danger to canopy fire than others, and (iii) that these vegetation types have changed in the past sixteen years.

Predicting Fire Season Severity in the Pacific Northwest

Treesearch

Paul Werth

2006-01-01

Projections of fire season severity that integrate historical weather and fire information can be used by fire managers when making decisions about allocating and prioritizing firefighting resources. They enable fire managers to anticipate fire activity and pre-position resources to maximize public and firefighter safety, reduce environmental impacts, and lower...

Landslides, forest fires, and earthquakes: examples of self-organized critical behavior

NASA Astrophysics Data System (ADS)

Turcotte, Donald L.; Malamud, Bruce D.

2004-09-01

Per Bak conceived self-organized criticality as an explanation for the behavior of the sandpile model. Subsequently, many cellular automata models were found to exhibit similar behavior. Two examples are the forest-fire and slider-block models. Each of these models can be associated with a serious natural hazard: the sandpile model with landslides, the forest-fire model with actual forest fires, and the slider-block model with earthquakes. We examine the noncumulative frequency-area statistics for each natural hazard, and show that each has a robust power-law (fractal) distribution. We propose an inverse-cascade model as a general explanation for the power-law frequency-area statistics of the three cellular-automata models and their ‘associated’ natural hazards.

Fire behavior of transformer dielectric insulating fluids

DOT National Transportation Integrated Search

1980-01-31

This report presents results for the fire behavior of pure and askarel-contaminated fluids which are candidates for use as railroad transformer dielectric insulating fluids. In the study a hydrocarbon and a dimethyl-siloxane fluid were examined. The ...

Analysis of the ability of large-scale reanalysis data to define Siberian fire danger in preparation for future fire prediction

NASA Astrophysics Data System (ADS)

Soja, Amber; Westberg, David; Stackhouse, Paul, Jr.; McRae, Douglas; Jin, Ji-Zhong; Sukhinin, Anatoly

2010-05-01

Fire is the dominant disturbance that precipitates ecosystem change in boreal regions, and fire is largely under the control of weather and climate. Fire frequency, fire severity, area burned and fire season length are predicted to increase in boreal regions under current climate change scenarios. Therefore, changes in fire regimes have the potential to compel ecological change, moving ecosystems more quickly towards equilibrium with a new climate. The ultimate goal of this research is to assess the viability of large-scale (1°) data to be used to define fire weather danger and fire regimes, so that large-scale data can be confidently used to predict future fire regimes using large-scale fire weather data, like that available from current Intergovernmental Panel on Climate Change (IPCC) climate change scenarios. In this talk, we intent to: (1) evaluate Fire Weather Indices (FWI) derived using reanalysis and interpolated station data; (2) discuss the advantages and disadvantages of using these distinct data sources; and (3) highlight established relationships between large-scale fire weather data, area burned, active fires and ecosystems burned. Specifically, the Canadian Forestry Service (CFS) Fire Weather Index (FWI) will be derived using: (1) NASA Goddard Earth Observing System version 4 (GEOS-4) large-scale reanalysis and NASA Global Precipitation Climatology Project (GPCP) data; and National Climatic Data Center (NCDC) surface station-interpolated data. Requirements of the FWI are local noon surface-level air temperature, relative humidity, wind speed, and daily (noon-noon) rainfall. GEOS-4 reanalysis and NCDC station-interpolated fire weather indices are generally consistent spatially, temporally and quantitatively. Additionally, increased fire activity coincides with increased FWI ratings in both data products. Relationships have been established between large-scale FWI to area burned, fire frequency, ecosystem types, and these can be use to estimate historic and future fire regimes.

Interactions across spatial scales among forest dieback, fire, and erosion in northern New Mexico landscapes

USGS Publications Warehouse

Allen, Craig D.

2007-01-01

Ecosystem patterns and disturbance processes at one spatial scale often interact with processes at another scale, and the result of such cross-scale interactions can be nonlinear dynamics with thresholds. Examples of cross-scale pattern-process relationships and interactions among forest dieback, fire, and erosion are illustrated from northern New Mexico (USA) landscapes, where long-term studies have recently documented all of these disturbance processes. For example, environmental stress, operating on individual trees, can cause tree death that is amplified by insect mortality agents to propagate to patch and then landscape or even regional-scale forest dieback. Severe drought and unusual warmth in the southwestern USA since the late 1990s apparently exceeded species-specific physiological thresholds for multiple tree species, resulting in substantial vegetation mortality across millions of hectares of woodlands and forests in recent years. Predictions of forest dieback across spatial scales are constrained by uncertainties associated with: limited knowledge of species-specific physiological thresholds; individual and site-specific variation in these mortality thresholds; and positive feedback loops between rapidly-responding insect herbivore populations and their stressed plant hosts, sometimes resulting in nonlinear “pest” outbreak dynamics. Fire behavior also exhibits nonlinearities across spatial scales, illustrated by changes in historic fire regimes where patch-scale grazing disturbance led to regional-scale collapse of surface fire activity and subsequent recent increases in the scale of extreme fire events in New Mexico. Vegetation dieback interacts with fire activity by modifying fuel amounts and configurations at multiple spatial scales. Runoff and erosion processes are also subject to scale-dependent threshold behaviors, exemplified by ecohydrological work in semiarid New Mexico watersheds showing how declines in ground surface cover lead to non-linear increases in bare patch connectivity and thereby accelerated runoff and erosion at hillslope and watershed scales. Vegetation dieback, grazing, and fire can change land surface properties and cross-scale hydrologic connectivities, directly altering ecohydrological patterns of runoff and erosion. The interactions among disturbance processes across spatial scales can be key drivers in ecosystem dynamics, as illustrated by these studies of recent landscape changes in northern New Mexico. To better anticipate and mitigate accelerating human impacts to the planetary ecosystem at all spatial scales, improvements are needed in our conceptual and quantitative understanding of cross-scale interactions among disturbance processes.

Comparison of Fire Model Predictions with Experiments Conducted in a Hangar With a 15 Meter Ceiling

NASA Technical Reports Server (NTRS)

Davis, W. D.; Notarianni, K. A.; McGrattan, K. B.

1996-01-01

The purpose of this study is to examine the predictive capabilities of fire models using the results of a series of fire experiments conducted in an aircraft hangar with a ceiling height of about 15 m. This study is designed to investigate model applicability at a ceiling height where only a limited amount of experimental data is available. This analysis deals primarily with temperature comparisons as a function of distance from the fire center and depth beneath the ceiling. Only limited velocity measurements in the ceiling jet were available but these are also compared with those models with a velocity predictive capability.

Variability of fire behavior, fire effects, and emissions in Scotch pine forests of central Siberia

Treesearch

D. J. McRae; Susan Conard; G. A. Ivanova; A. I. Sukhinin; Steve Baker; Y. N. Samsonov; T. W. Blake; V. A. Ivanov; A. V. Ivanov; T. V. Churkina; WeiMin Hao; K. P. Koutzenogij; Nataly Kovaleva

2006-01-01

As part of the Russian FIRE BEAR (Fire Effects in the Boreal Eurasia Region) Project, replicated 4-ha experimental fires were conducted on a dry Scotch pine (Pinus sylvestris)/lichen (Cladonia sp.)/feathermoss (Pleurozeum schreberi) forest site in central Siberia. Observations from the initial seven surface fires (2000-2001) ignited under a range of burning...

Effectiveness of Prescribed Fire as a Fuel Treatment in Californian Coniferous Forests

Treesearch

Nicole M. Vaillant; JoAnn Fites-Kaufman; Scott L. Stephens

2006-01-01

Effective fire suppression for the past century has altered forest structure and increased fuel loads. Prescribed fire as a fuels treatment can reduce wildfire size and severity. This study investigates how prescribed fire affects fuel loads, forest structure, potential fire behavior, and modeled tree mortality at 80th, 90th, and 97.5th percentile fire weather...

Continental-scale simulation of burn probabilities, flame lengths, and fire size distribution for the United States

Treesearch

Mark A. Finney; Charles W. McHugh; Isaac Grenfell; Karin L. Riley

2010-01-01

Components of a quantitative risk assessment were produced by simulation of burn probabilities and fire behavior variation for 134 fire planning units (FPUs) across the continental U.S. The system uses fire growth simulation of ignitions modeled from relationships between large fire occurrence and the fire danger index Energy Release Component (ERC). Simulations of 10,...

Progression and Behavior of the Canoe Fire in Coast Redwood

Treesearch

Hugh Scanlon

2007-01-01

Lightning caused fires occur in coast redwood forests, but large fires have been rare since the 1930s. Coast redwood (Sequoia sempervirens) is considered fire resistant. In 2003, the Canoe Fire, a lightning fire started in an old-growth redwood stand in Humboldt Redwoods State Park, burned 5,554 hectares (13,774 acres) before it was contained. Fuel...

Wilderness fire science: A state of knowledge review

Treesearch

James K. Agee

2000-01-01

Wilderness fire science has progressed since the last major review of the topic, but it was significantly affected by the large fire events of 1988. Strides have been made in both fire behavior and fire effects, and in the issues of scaling, yet much of the progress has not been specifically tied to wilderness areas or funding. Although the management of fire in...

Space station internal environmental and safety concerns

NASA Technical Reports Server (NTRS)

Cole, Matthew B.

1987-01-01

Space station environmental and safety concerns, especially those involving fires, are discussed. Several types of space station modules and the particular hazards associated with each are briefly surveyed. A brief history of fire detection and suppression aboard spacecraft is given. Microgravity fire behavior, spacecraft fire detector systems, space station fire suppression equipment and procedures, and fire safety in hyperbaric chambers are discussed.

BehavePlus fire modeling system, version 4.0: User's Guide

Treesearch

Patricia L. Andrews; Collin D. Bevins; Robert C. Seli

2005-01-01

The BehavePlus fire modeling system is a program for personal computers that is a collection of mathematical models that describe fire and the fire environment. It is a flexible system that produces tables, graphs, and simple diagrams. It can be used for a multitude of fire management applications including projecting the behavior of an ongoing fire, planning...

Previous fires moderate burn severity of subsequent wildland fires in two large western US wilderness areas

Treesearch

Sean A. Parks; Carol Miller; Cara R. Nelson; Zachary A. Holden

2014-01-01

Wildland fire is an important natural process in many ecosystems. However, fire exclusion has reduced frequency of fire and area burned in many dry forest types, which may affect vegetation structure and composition, and potential fire behavior. In forests of the western U.S., these effects pose a challenge for fire and land managers who seek to restore the ecological...

Short- and long-term effects on fuels, forest structure, and wildfire potential from prescribed fire and resource benefit fire in southwestern forests, USA

Treesearch

Molly E. Hunter; Jose M. Iniguez; Leigh B. Lentile

2011-01-01

Prescribed and resource benefit fires are used to manage fuels in fire-prone landscapes in the Southwest. These practices, however, typically occur under different conditions, potentially leading to differences in fire behavior and effects. The objectives of this study were to investigate the effects of recent prescribed fires, resource benefit fires, and repeated...

[Forest lighting fire forecasting for Daxing'anling Mountains based on MAXENT model].

PubMed

Sun, Yu; Shi, Ming-Chang; Peng, Huan; Zhu, Pei-Lin; Liu, Si-Lin; Wu, Shi-Lei; He, Cheng; Chen, Feng

2014-04-01

Daxing'anling Mountains is one of the areas with the highest occurrence of forest lighting fire in Heilongjiang Province, and developing a lightning fire forecast model to accurately predict the forest fires in this area is of importance. Based on the data of forest lightning fires and environment variables, the MAXENT model was used to predict the lightning fire in Daxing' anling region. Firstly, we studied the collinear diagnostic of each environment variable, evaluated the importance of the environmental variables using training gain and the Jackknife method, and then evaluated the prediction accuracy of the MAXENT model using the max Kappa value and the AUC value. The results showed that the variance inflation factor (VIF) values of lightning energy and neutralized charge were 5.012 and 6.230, respectively. They were collinear with the other variables, so the model could not be used for training. Daily rainfall, the number of cloud-to-ground lightning, and current intensity of cloud-to-ground lightning were the three most important factors affecting the lightning fires in the forest, while the daily average wind speed and the slope was of less importance. With the increase of the proportion of test data, the max Kappa and AUC values were increased. The max Kappa values were above 0.75 and the average value was 0.772, while all of the AUC values were above 0.5 and the average value was 0. 859. With a moderate level of prediction accuracy being achieved, the MAXENT model could be used to predict forest lightning fire in Daxing'anling Mountains.

Interactions among livestock grazing, vegetation type, and fire behavior in the Murphy Wildland Fire Complex in Idaho and Nevada, July 2007

USGS Publications Warehouse

Launchbaugh, Karen; Brammer, Bob; Brooks, Matthew L.; Bunting, Stephen C.; Clark, Patrick; Davison, Jay; Fleming, Mark; Kay, Ron; Pellant, Mike; Pyke, David A.

2008-01-01

A series of wildland fires were ignited by lightning in sagebrush and grassland communities near the Idaho-Nevada border southwest of Twin Falls, Idaho in July 2007. The fires burned for over two weeks and encompassed more than 650,000 acres. A team of scientists, habitat specialists, and land managers was called together by Tom Dyer, Idaho BLM State Director, to examine initial information from the Murphy Wildland Fire Complex in relation to plant communities and patterns of livestock grazing. Three approaches were used to examine this topic: (1) identify potential for livestock grazing to modify fuel loads and affect fire behavior using fire models applied to various vegetation types, fuel loads, and fire conditions; (2) compare levels of fuel consumed within and among major vegetation types; and (3) examine several observed lines of difference and discontinuity in fuel consumed to determine what factors created these contrasts. The team found that much of the Murphy Wildland Fire Complex burned under extreme fuel and weather conditions that likely overshadowed livestock grazing as a factor influencing fire extent and fuel consumption in many areas where these fires burned. Differences and abrupt contrast lines in the level of fuels consumed were affected mostly by the plant communities that existed on a site before fire. A few abrupt contrasts in burn severity coincided with apparent differences in grazing patterns of livestock, observed as fence-line contrasts. Fire modeling revealed that grazing in grassland vegetation can reduce surface rate of spread and fire-line intensity to a greater extent than in shrubland types. Under extreme fire conditions (low fuel moisture, high temperatures, and gusty winds), grazing applied at moderate utilization levels has limited or negligible effects on fire behavior. However, when weather and fuel-moisture conditions are less extreme, grazing may reduce the rate of spread and intensity of fires allowing for patchy burns with low levels of fuel consumption. The team suggested that targeted grazing to accomplish fuel objectives holds promise but requires detailed planning that includes clearly defined goals for fuel modification and appropriate monitoring to assess effectiveness. It was recommended that a pilot plan be devised to strategically place grazed blocks across a landscape to create fuel-reduction bands capable of influencing fire behavior. Also suggested was the development of a general technical report that highlights information and examples of how livestock grazing influences fire extent, severity, and intensity. Finally, the team encouraged continued research and monitoring of the effects of the Murphy Wildland Fire Complex. Much more can be learned from the effects of this extensive fire complex that may offer insight for future management decisions.

Post-fire vegetation and fuel development influences fire severity patterns in reburns.

PubMed

Coppoletta, Michelle; Merriam, Kyle E; Collins, Brandon M

2016-04-01

In areas where fire regimes and forest structure have been dramatically altered, there is increasing concern that contemporary fires have the potential to set forests on a positive feedback trajectory with successive reburns, one in which extensive stand-replacing fire could promote more stand-replacing fire. Our study utilized an extensive set of field plots established following four fires that occurred between 2000 and 2010 in the northern Sierra Nevada, California, USA that were subsequently reburned in 2012. The information obtained from these field plots allowed for a unique set of analyses investigating the effect of vegetation, fuels, topography, fire weather, and forest management on reburn severity. We also examined the influence of initial fire severity and time since initial fire on influential predictors of reburn severity. Our results suggest that high- to moderate-severity fire in the initial fires led to an increase in standing snags and shrub vegetation, which in combination with severe fire weather promoted high-severity fire effects in the subsequent reburn. Although fire behavior is largely driven by weather, our study demonstrates that post-fire vegetation composition and structure are also important drivers of reburn severity. In the face of changing climatic regimes and increases in extreme fire weather, these results may provide managers with options to create more fire-resilient ecosystems. In areas where frequent high-severity fire is undesirable, management activities such as thinning, prescribed fire, or managed wildland fire can be used to moderate fire behavior not only prior to initial fires, but also before subsequent reburns.

Fire safety

Treesearch

Robert H. White; Mark A. Dietenberger

1999-01-01

Fire safety is an important concern in all types of construction. The high level of national concern for fire safety is reflected in limitations and design requirements in building codes. These code requirements are discussed in the context of fire safety design and evaluation in the initial section of this chapter. Since basic data on fire behavior of wood products...

Benefits of hindsight: reestablishing fire on the landscape.

Treesearch

Sally Duncan

2001-01-01

Well-intentioned fire suppression efforts during the last 80 to 100 years have altered the structure of low-elevation forests in the interior Northwest. Historically, nondestructive, frequent, low-intensity fires have given way to larger, infrequent, severe, high-intensity fires. Because of altered fire behavior, forests now have increased fuel, and consequently, are...

Fire in southern forest landscapes

Treesearch

John A. Stanturf; Dale D. Wade; Thomas A. Waldrop; Deborah K. Kennard; Gary L. Achtemeier

2002-01-01

Other than land clearing for urban development (Wear and others 1998), no disturbance is more common in southern forests than fire. The pervasive role of fire predates human activity in the South (Komarek 1964, 1974), and humans magnified that role. Repeating patterns of fire behavior lead to recognizable fire regimes, with temporal and spatial dimensions....

Soil shapes community structure through fire.

PubMed

Ojeda, Fernando; Pausas, Juli G; Verdú, Miguel

2010-07-01

Recurrent wildfires constitute a major selecting force in shaping the structure of plant communities. At the regional scale, fire favours phenotypic and phylogenetic clustering in Mediterranean woody plant communities. Nevertheless, the incidence of fire within a fire-prone region may present strong variations at the local, landscape scale. This study tests the prediction that woody communities on acid, nutrient-poor soils should exhibit more pronounced phenotypic and phylogenetic clustering patterns than woody communities on fertile soils, as a consequence of their higher flammability and, hence, presumably higher propensity to recurrent fire. Results confirm the predictions and show that habitat filtering driven by fire may be detected even in local communities from an already fire-filtered regional flora. They also provide a new perspective from which to consider a preponderant role of fire as a key evolutionary force in acid, infertile Mediterranean heathlands.

Contrasting fire responses to climate and management: insights from two Australian ecosystems.

PubMed

King, Karen J; Cary, Geoffrey J; Bradstock, Ross A; Marsden-Smedley, Jonathan B

2013-04-01

This study explores effects of climate change and fuel management on unplanned fire activity in ecosystems representing contrasting extremes of the moisture availability spectrum (mesic and arid). Simulation modelling examined unplanned fire activity (fire incidence and area burned, and the area burned by large fires) for alternate climate scenarios and prescribed burning levels in: (i) a cool, moist temperate forest and wet moorland ecosystem in south-west Tasmania (mesic); and (ii) a spinifex and mulga ecosystem in central Australia (arid). Contemporary fire activity in these case study systems is limited, respectively, by fuel availability and fuel amount. For future climates, unplanned fire incidence and area burned increased in the mesic landscape, but decreased in the arid landscape in accordance with predictions based on these limiting factors. Area burned by large fires (greater than the 95th percentile of historical, unplanned fire size) increased with future climates in the mesic landscape. Simulated prescribed burning was more effective in reducing unplanned fire activity in the mesic landscape. However, the inhibitory effects of prescribed burning are predicted to be outweighed by climate change in the mesic landscape, whereas in the arid landscape prescribed burning reinforced a predicted decline in fire under climate change. The potentially contrasting direction of future changes to fire will have fundamentally different consequences for biodiversity in these contrasting ecosystems, and these will need to be accommodated through contrasting, innovative management solutions. © 2012 Blackwell Publishing Ltd.

Seasonal forecasting of fire over Kalimantan, Indonesia

NASA Astrophysics Data System (ADS)

Spessa, A. C.; Field, R. D.; Pappenberger, F.; Langner, A.; Englhart, S.; Weber, U.; Stockdale, T.; Siegert, F.; Kaiser, J. W.; Moore, J.

2015-03-01

Large-scale fires occur frequently across Indonesia, particularly in the southern region of Kalimantan and eastern Sumatra. They have considerable impacts on carbon emissions, haze production, biodiversity, health, and economic activities. In this study, we demonstrate that severe fire and haze events in Indonesia can generally be predicted months in advance using predictions of seasonal rainfall from the ECMWF System 4 coupled ocean-atmosphere model. Based on analyses of long, up-to-date series observations on burnt area, rainfall, and tree cover, we demonstrate that fire activity is negatively correlated with rainfall and is positively associated with deforestation in Indonesia. There is a contrast between the southern region of Kalimantan (high fire activity, high tree cover loss, and strong non-linear correlation between observed rainfall and fire) and the central region of Kalimantan (low fire activity, low tree cover loss, and weak, non-linear correlation between observed rainfall and fire). The ECMWF seasonal forecast provides skilled forecasts of burnt and fire-affected area with several months lead time explaining at least 70% of the variance between rainfall and burnt and fire-affected area. Results are strongly influenced by El Niño years which show a consistent positive bias. Overall, our findings point to a high potential for using a more physical-based method for predicting fires with several months lead time in the tropics rather than one based on indexes only. We argue that seasonal precipitation forecasts should be central to Indonesia's evolving fire management policy.

Effects of experimental fuel additions on fire intensity and severity: unexpected carbon resilience of a neotropical forest.

PubMed

Brando, Paulo M; Oliveria-Santos, Claudinei; Rocha, Wanderley; Cury, Roberta; Coe, Michael T

2016-07-01

Global changes and associated droughts, heat waves, logging activities, and forest fragmentation may intensify fires in Amazonia by altering forest microclimate and fuel dynamics. To isolate the effects of fuel loads on fire behavior and fire-induced changes in forest carbon cycling, we manipulated fine fuel loads in a fire experiment located in southeast Amazonia. We predicted that a 50% increase in fine fuel loads would disproportionally increase fire intensity and severity (i.e., tree mortality and losses in carbon stocks) due to multiplicative effects of fine fuel loads on the rate of fire spread, fuel consumption, and burned area. The experiment followed a fully replicated randomized block design (N = 6) comprised of unburned control plots and burned plots that were treated with and without fine fuel additions. The fuel addition treatment significantly increased burned area (+22%) and consequently canopy openness (+10%), fine fuel combustion (+5%), and mortality of individuals ≥5 cm in diameter at breast height (dbh; +37%). Surprisingly, we observed nonsignificant effects of the fuel addition treatment on fireline intensity, and no significant differences among the three treatments for (i) mortality of large trees (≥30 cm dbh), (ii) aboveground forest carbon stocks, and (iii) soil respiration. It was also surprising that postfire tree growth and wood increment were higher in the burned plots treated with fuels than in the unburned control. These results suggest that (i) fine fuel load accumulation increases the likelihood of larger understory fires and (ii) single, low-intensity fires weakly influence carbon cycling of this primary neotropical forest, although delayed postfire mortality of large trees may lower carbon stocks over the long term. Overall, our findings indicate that increased fine fuel loads alone are unlikely to create threshold conditions for high-intensity, catastrophic fires during nondrought years. © 2016 John Wiley & Sons Ltd.

Use of spatially refined satellite remote sensing fire detection data to initialize and evaluate coupled weather-wildfire growth model simulations

NASA Astrophysics Data System (ADS)

Schroeder, W.; Coen, J.; Oliva, P.

2013-12-01

Availability of spatially refined satellite active fire detection data is gradually increasing. For example, the new 375 m Visible Infrared Imaging Radiometer Suite (VIIRS) data show improved active fire detection performance for both small and large size fires. The VIIRS data have proved superior to MODIS for mapping of wildfires events spanning several days to weeks of either continued or intermittent activity, delivering 12-h active fire data of improved spatial fidelity. The VIIRS active fire data are complemented by other satellite active fire data sets of similar or higher spatial resolution, including the new 30 m Landsat-8. Additional assets should include the upcoming 20 m Sentinel-2 Landsat-class satellite program by the European Space Agency to be launched in 2014-15. These improved active fire data sets are fostering new applications that rely on higher resolution input fire data. In this study, we describe the characteristics of the new VIIRS and Landsat-8 data and demonstrate one such new application of satellite active fire data in support of fire behavior modeling. We present results for a wildfire observed in June 2012 in New Mexico using an innovative approach to improving the simulation of large, long-duration wildfires, either for retrospective studies or forecasting in a number of geophysical applications. The approach uses (1) the Coupled Atmosphere-Wildland Fire Environment (CAWFE) Model, a numerical weather prediction model two-way coupled with a module representing the rate of spread of a wildfire's flaming front, its rate of consumption of different wildland fuels, and the feedback of this heat release upon the atmosphere - i.e. 'how a fire creates its own weather', combined with (2) spatially refined 375 m VIIRS active fire data, which is used for initialization of a wildfire already in progress in the model and evaluation of its simulated progression at the time of the next pass. Results show that initializing a fire that is 'in progress' with VIIRS data and a weather simulation based on more recent atmospheric analyses can overcome several issues and improve the simulation of late-developing fires and of later periods (particularly those with growth periods separated by lulls) in a long-lived fire.

Fire behavior modeling to assess net benefits of forest treatments on fire hazard mitigation and bioenergy production in Northeastern California

Treesearch

David J. Ganz; David S. Saah; Klaus Barber; Mark Nechodom

2007-01-01

The fire behavior modeling described here, conducted as part of the Biomass to Energy (B2E) life cycle assessment, is funded by the California Energy Commission to evaluate the potential net benefits associated with treating and utilizing forest biomass. The B2E project facilitates economic, environmental, energy, and effectiveness assessments of the potential public...

Remote sensing for prediction of 1-year post-fire ecosystem condition

Treesearch

Leigh B. Lentile; Alistair M. S. Smith; Andrew T. Hudak; Penelope Morgan; Michael J. Bobbitt; Sarah A. Lewis; Peter R. Robichaud

2009-01-01

Appropriate use of satellite data in predicting >1 year post-fire effects requires remote measurement of surface properties that can be mechanistically related to ground measures of post-fire condition. The present study of burned ponderosa pine (Pinus ponderosa) forests in the Black Hills of South Dakota evaluates whether immediate fractional cover estimates of...

Fire spread probabilities for experimental beds composed of mixedwood boreal forest fuels

Treesearch

M.B. Dickinson; E.A. Johnson; R. Artiaga

2013-01-01

Although fuel characteristics are assumed to have an important impact on fire regimes through their effects on extinction dynamics, limited capabilities exist for predicting whether a fire will spread in mixedwood boreal forest surface fuels. To improve predictive capabilities, we conducted 347 no-wind, laboratory test burns in surface fuels collected from the mixed-...

Predicting the effect of fire on large-scale vegetation patterns in North America.

Treesearch

Donald McKenzie; David L. Peterson; Ernesto. Alvarado

1996-01-01

Changes in fire regimes are expected across North America in response to anticipated global climatic changes. Potential changes in large-scale vegetation patterns are predicted as a result of altered fire frequencies. A new vegetation classification was developed by condensing Kuchler potential natural vegetation types into aggregated types that are relatively...

Predicting duff and woody fuel consumed by prescribed fire in the Northern Rocky Mountains

Treesearch

James K. Brown; Michael A. Marsden; Kevin C. Ryan; Elizabeth D. Reinhardt

1985-01-01

Relationships for predicting duff reduction, mineral soil exposure, and consumption of downed woody fuel were determined to assist in planning prescribed fires. Independent variables included lower and entire duff moisture contents, loadings of downed woody fuels, duff depth, National Fire-Danger Rating System 1,000-hour moisture content, and Canadian Duff Moisture...

Acoustic cavity technology for high performance injectors

NASA Technical Reports Server (NTRS)

1976-01-01

The feasibility of damping more than one mode of rocket engine combustion instability by means of differently tuned acoustic cavities sharing a common entrance was shown. Analytical procedures and acoustic modeling techniques for predicting the stability behavior of acoustic cavity designs in hot firings were developed. Full scale testing of various common entrance, dual cavity configurations, and subscale testing for the purpose of obtaining motion pictures of the cavity entrance region, to aid in determining the mechanism of cavity damping were the two major aspects of the program.

Using Earth Observations to Assess the Socioeconomic Impact of Human Decision Making during the Suppression of a Wildland Fire

NASA Astrophysics Data System (ADS)

Miller, V. V.; Kochanski, A.; Mandel, J.; Herr, V.; Schranz, S.

2016-12-01

This presentation will discuss the fire simulation system based on WRF-SFIRE and assimilation of satellite Active Fires detection to estimate the socio-economic impact of Earth observations and fire behavior modeling for the 2011 Las Conchas fire in New Mexico. Multiple scenarios will be developed with the WRF-SFIRE simulation based on value of information (VOI) provided by retired incident commanders, whose decision inputs will steer scenario development and simulation. The scenarios will differ according to the Earth observations available through NASA and then deemed useful to incident commanders. Each scenario will be evaluated in terms of its socio-economic impact as specified by NASA (2012) for its wildland fire program. This presentation is a proposed supplement to NASA grant NNX13AH59G Wildland Fire Behavior and Risk Forecasting, Sher Schranz, PI.

Catching fire? Social interactions, beliefs, and wildfire risk mitigation behaviors

Treesearch

Katherine Dickinson; Hannah Brenkert-Smith; Patricia Champ; Nicholas Flores

2015-01-01

Social interactions are widely recognized as a potential influence on risk-related behaviors. We present a mediation model in which social interactions (classified as formal/informal and generic-fire-specific) are associated with beliefs about wildfire risk and mitigation options, which in turn shape wildfire mitigation behaviors. We test this model using survey data...

Predicting Fire Susceptibility in the Forests of Amazonia

NASA Technical Reports Server (NTRS)

Nepstad, Daniel C.; Brown, I. Foster; Setzer, Alberto

2000-01-01

Although fire is the single greatest threat to the ecological integrity of Amazon forests, our ability to predict the occurrence of Amazon forest fires is rudimentary. Part of the difficulty encountered in making such predictions is the remarkable capacity of Amazon forests to tolerate drought by tapping moisture stored in deep soil. These forests can avoid drought-induced leaf shedding by withdrawing moisture to depths of 8 meters and more. Hence, the absorption of deep soil moisture allows these forests to maintain their leaf canopies following droughts of several months duration, thereby maintaining the deep shade and high relative humidity of the forest interior that prevents these ecosystems from burning. But the drought- and fire-avoidance that is conferred by this deep-rooting phenomenon is not unlimited. During successive years of drought, such as those provoked by El Nino episodes, deep soil moisture can be depleted, and drought-induced leaf shedding begins. The goal of this project was to incorporate this knowledge of Amazon forest fire ecology into a predictive model of forest flammability.

Evaluation of a post-fire tree mortality model for western US conifers

Treesearch

Sharon M. Hood; Charles W McHugh; Kevin C. Ryan; Elizabeth Reinhardt; Sheri L. Smith

2007-01-01

Accurately predicting fire-caused mortality is essential to developing prescribed fire burn plans and post-fire salvage marking guidelines. The mortality model included in the commonly used USA fire behaviour and effects models, the First Order Fire Effects Model (FOFEM), BehavePlus, and the Fire and Fuels Extension to the Forest Vegetation Simulator (FFE-FVS), has not...

Avian community responses to post-fire forest structure: implications for fire management in mixed conifer forests

Treesearch

Angela White; Patricia Manley; Gina Tarbill; T. W. Richardson; R. E. Russell; H. D. Safford; S. Z. Dobrowski

2016-01-01

Fire is a natural process and the dominant disturbance shaping plant and animal communities in many coniferous forests of the western US. Given that fire size and severity are predicted to increase in the future, it has become increasingly important to understand how wildlife responds to fire and post-fire management. The Angora Fire...

Near real-time wildfire mapping using spatially-refined satellite data: The rim fire case study

Treesearch

Patricia Oliva; Wilfrid Schroeder

2015-01-01

Fire incident teams depend on accurate fire diagnostics and predictive data to guide daily positioning and tactics of fire crews. Currently, the U.S. Department of Agriculture - Forest Service National Infrared Operations (NIROPs) nighttime airborne data provides daily information about the fire front and total fire affected area of priority fires to the incident teams...

Fossils and fire: a study on the effects of fire on paleontological resources at Badlands National Park

Treesearch

Rachel Benton; James Reardon

2006-01-01

National Park Service policies stipulate that each park with vegetation capable of burning will prepare a fire management plan. Badlands National Park completed its fire management plan in 2004. Fossils are a principle resource of the park and the fire sensitivity of fossils is the focus of this study. The surface temperatures of fossil specimens and fire behavior...

Challenges and a checklist for biodiversity conservation in fire-prone forests: perspecitves from the Pacific Northwest of USA and Southeastern Australia

Treesearch

Thomas A. Spies; David B. Lindenmayer; A. Malcolm Gill; Scott L. Stephens; James K. Agee

2012-01-01

Conserving biodiversity in fire-prone forest ecosystems is challenging for several reasons including differing and incomplete conceptual models of fire-related ecological processes, major gaps in ecological and management knowledge, high variability in fire behavior and ecological responses to fires, altered fire regimes as a result of land-use history and climate...

Simulation and thermal imaging of the 2006 Esperanza Wildfire in southern California: application of a coupled weather-wildland fire model

Treesearch

Janice L. Coen; Philip J Riggan

2014-01-01

The 2006 Esperanza Fire in Riverside County, California, was simulated with the Coupled Atmosphere-Wildland Fire Environment (CAWFE) model to examine how dynamic interactions of the atmosphere with large-scale fire spread and energy release may affect observed patterns of fire behavior as mapped using the FireMapper thermal imaging radiometer. CAWFE simulated the...

Fire behavior, fuel treatments, and fire suppression on the Hayman Fire - Part 5: Fire suppression activities

Treesearch

Charles W. McHugh; Paul Gleason

2003-01-01

The purpose of this report is to document the suppression actions taken during the Hayman Fire. The long duration of suppression activities (June 8 through July 18), and multiple incident management teams assigned to the fire, makes this a challenging task. Original records and reports produced independently by the various teams assigned to different portions of the...

Post-fire logging reduces surface woody fuels up to four decades following wildfire

Treesearch

David W. Peterson; Erich Kyle Dodson; Richy J. Harrod

2015-01-01

Severe wildfires create pulses of dead trees that influence future fuel loads, fire behavior, and fire effects as they decay and deposit surface woody fuels. Harvesting fire-killed trees may reduce future surface woody fuels and related fire hazards, but the magnitude and timing of post-fire logging effects on woody fuels have not been fully assessed. To address this...

A Simple Network Architecture Accounts for Diverse Reward Time Responses in Primary Visual Cortex

PubMed Central

Hussain Shuler, Marshall G.; Shouval, Harel Z.

2015-01-01

Many actions performed by animals and humans depend on an ability to learn, estimate, and produce temporal intervals of behavioral relevance. Exemplifying such learning of cued expectancies is the observation of reward-timing activity in the primary visual cortex (V1) of rodents, wherein neural responses to visual cues come to predict the time of future reward as behaviorally experienced in the past. These reward-timing responses exhibit significant heterogeneity in at least three qualitatively distinct classes: sustained increase or sustained decrease in firing rate until the time of expected reward, and a class of cells that reach a peak in firing at the expected delay. We elaborate upon our existing model by including inhibitory and excitatory units while imposing simple connectivity rules to demonstrate what role these inhibitory elements and the simple architectures play in sculpting the response dynamics of the network. We find that simply adding inhibition is not sufficient for obtaining the different distinct response classes, and that a broad distribution of inhibitory projections is necessary for obtaining peak-type responses. Furthermore, although changes in connection strength that modulate the effects of inhibition onto excitatory units have a strong impact on the firing rate profile of these peaked responses, the network exhibits robustness in its overall ability to predict the expected time of reward. Finally, we demonstrate how the magnitude of expected reward can be encoded at the expected delay in the network and how peaked responses express this reward expectancy. SIGNIFICANCE STATEMENT Heterogeneity in single-neuron responses is a common feature of neuronal systems, although sometimes, in theoretical approaches, it is treated as a nuisance and seldom considered as conveying a different aspect of a signal. In this study, we focus on the heterogeneous responses in the primary visual cortex of rodents trained with a predictable delayed reward time. We describe under what conditions this heterogeneity can arise by self-organization, and what information it can convey. This study, while focusing on a specific system, provides insight onto how heterogeneity can arise in general while also shedding light onto mechanisms of reinforcement learning using realistic biological assumptions. PMID:26377457

What Fraction of Global Fire Activity Can Be Forecast Using Sea Surface Temperatures?

NASA Astrophysics Data System (ADS)

Chen, Y.; Randerson, J. T.; Morton, D. C.; Andela, N.; Giglio, L.

2015-12-01

Variations in sea surface temperatures (SSTs) can influence climate dynamics in local and remote land areas, and thus influence fire-climate interactions that govern burned area. SST information has been recently used in statistical models to create seasonal outlooks of fire season severity in South America and as the initial condition for dynamical model predictions of fire activity in Indonesia. However, the degree to which large-scale ocean-atmosphere interactions can influence burned area in other continental regions has not been systematically explored. Here we quantified the amount of global burned area that can be predicted using SSTs in 14 different oceans regions as statistical predictors. We first examined lagged correlations between GFED4s burned area and the 14 ocean climate indices (OCIs) individually. The maximum correlations from different OCIs were used to construct a global map of fire predictability. About half of the global burned area can be forecast by this approach 3 months before the peak burning month (with a Pearson's r of 0.5 or higher), with the highest levels of predictability in Central America and Equatorial Asia. Several hotspots of predictability were identified using k-means cluster analysis. Within these regions, we tested the improvements of the forecast by using two OCIs from different oceans. Our forecast models were based on near-real-time SST data and may therefore support the development of new seasonal outlooks for fire activity that can aid the sustainable management of these fire-prone ecosystems.

Inhibitory neurons promote robust critical firing dynamics in networks of integrate-and-fire neurons.

PubMed

Lu, Zhixin; Squires, Shane; Ott, Edward; Girvan, Michelle

2016-12-01

We study the firing dynamics of a discrete-state and discrete-time version of an integrate-and-fire neuronal network model with both excitatory and inhibitory neurons. When the integer-valued state of a neuron exceeds a threshold value, the neuron fires, sends out state-changing signals to its connected neurons, and returns to the resting state. In this model, a continuous phase transition from non-ceaseless firing to ceaseless firing is observed. At criticality, power-law distributions of avalanche size and duration with the previously derived exponents, -3/2 and -2, respectively, are observed. Using a mean-field approach, we show analytically how the critical point depends on model parameters. Our main result is that the combined presence of both inhibitory neurons and integrate-and-fire dynamics greatly enhances the robustness of critical power-law behavior (i.e., there is an increased range of parameters, including both sub- and supercritical values, for which several decades of power-law behavior occurs).

Simulation of air quality impacts from prescribed fires on an urban area.

PubMed

Hu, Yongtao; Odman, M Talat; Chang, Michael E; Jackson, William; Lee, Sangil; Edgerton, Eric S; Baumann, Karsten; Russell, Armistead G

2008-05-15

On February 28, 2007, a severe smoke event caused by prescribed forest fires occurred in Atlanta, GA. Later smoke events in the southeastern metropolitan areas of the United States caused by the Georgia-Florida wild forest fires further magnified the significance of forest fire emissions and the benefits of being able to accurately predict such occurrences. By using preburning information, we utilize an operational forecasting system to simulate the potential air quality impacts from two large February 28th fires. Our "forecast" predicts that the scheduled prescribed fires would have resulted in over 1 million Atlanta residents being potentially exposed to fine particle matter (PM2.5) levels of 35 microg m(-3) or higher from 4 p.m. to midnight. The simulated peak 1 h PM2.5 concentration is about 121 microg m(-3). Our study suggests that the current air quality forecasting technology can be a useful tool for helping the management of fire activities to protect public health. With postburning information, our "hindcast" predictions improved significantly on timing and location and slightly on peak values. "Hindcast" simulations also indicated that additional isoprenoid emissions from pine species temporarily triggered by the fire could induce rapid ozone and secondary organic aerosol formation during late winter. Results from this study suggest that fire induced biogenic volatile organic compounds emissions missing from current fire emissions estimate should be included in the future.

Partial synchronization of relaxation oscillators with repulsive coupling in autocatalytic integrate-and-fire model and electrochemical experiments

NASA Astrophysics Data System (ADS)

Kori, Hiroshi; Kiss, István Z.; Jain, Swati; Hudson, John L.

2018-04-01

Experiments and supporting theoretical analysis are presented to describe the synchronization patterns that can be observed with a population of globally coupled electrochemical oscillators close to a homoclinic, saddle-loop bifurcation, where the coupling is repulsive in the electrode potential. While attractive coupling generates phase clusters and desynchronized states, repulsive coupling results in synchronized oscillations. The experiments are interpreted with a phenomenological model that captures the waveform of the oscillations (exponential increase) followed by a refractory period. The globally coupled autocatalytic integrate-and-fire model predicts the development of partially synchronized states that occur through attracting heteroclinic cycles between out-of-phase two-cluster states. Similar behavior can be expected in many other systems where the oscillations occur close to a saddle-loop bifurcation, e.g., with Morris-Lecar neurons.

A population model of chaparral vegetation response to frequent wildfires.

PubMed

Lucas, Timothy A; Johns, Garrett; Jiang, Wancen; Yang, Lucie

2013-12-01

The recent increase in wildfire frequency in the Santa Monica Mountains (SMM) may substantially impact plant community structure. Species of Chaparral shrubs represent the dominant vegetation type in the SMM. These species can be divided into three life history types according to their response to wildfires. Nonsprouting species are completely killed by fire and reproduce by seeds that germinate in response to a fire cue, obligate sprouting species survive by resprouting from dormant buds in a root crown because their seeds are destroyed by fire, and facultative sprouting species recover after fire both by seeds and resprouts. Based on these assumptions, we developed a set of nonlinear difference equations to model each life history type. These models can be used to predict species survivorship under varying fire return intervals. For example, frequent fires can lead to localized extinction of nonsprouting species such as Ceanothus megacarpus while several facultative sprouting species such as Ceanothus spinosus and Malosma (Rhus) laurina will persist as documented by a longitudinal study in a biological preserve in the SMM. We estimated appropriate parameter values for several chaparral species using 25 years of data and explored parameter relationships that lead to equilibrium populations. We conclude by looking at the survival strategies of these three species of chaparral shrubs under varying fire return intervals and predict changes in plant community structure under fire intervals of short return. In particular, our model predicts that an average fire return interval of greater than 12 years is required for 50 % of the initial Ceanothus megacarpus population and 25 % of the initial Ceanothus spinosus population to survive. In contrast, we predict that the Malosma laurina population will have 90 % survivorship for an average fire return interval of at least 6 years.

Review of vortices in wildland fire

Treesearch

Jason M. Forthofer; Scott L. Goodrick

2011-01-01

Vortices are almost always present in the wildland fire environment and can sometimes interact with the fire in unpredictable ways, causing extreme fire behavior and safety concerns. In this paper, the current state of knowledge of the interaction of wildland fire and vortices is examined and reviewed. A basic introduction to vorticity is given, and the two common...

Use of prescribed fire to reduce wildfire potential

Treesearch

Robert E. Martin; J. Boone Kauffman

1989-01-01

Fires were a part of our wildlands prehistorically. Prescribed burning reduces fire hazard and potential fire behavior primarily by reducing fuel quantity and continuity. Fuel continuity should be considered on the micro scale within stands, the mid-scale among, and the macro-scale among watersheds or entire forests. Prescribed fire is only one of the tools which can...

A simulation of wildfire behavior in piedmont forests

Treesearch

Helen H. Mohr; Thomas A. Waldrop

2006-01-01

Decades of fire exclusion have increased the need for fuel reduction in U.S. forests. The buildup of excessive fuels has led to uncharacteristically severe fires in areas with historically short-interval, low to moderate intensity fire regimes. The National Fire and Fire Surrogate Study compares the impacts of three fuel reduction treatments on numerous response...

Fire on the mountain: birds and burns in the Rocky Mountains

Treesearch

Natasha B. Kotliar; Victoria A. Saab; Richard L. Hutto

2005-01-01

The diversity of climate and topography across the Rocky Mountains has resulted in a broad spectrum of fire regimes ranging from frequent, low-severity fires to infrequent stand-replacement events. Such variation in fire history contributes to landscape structure and dynamics, and in turn can influence subsequent fire behavior (Allen et al. 2002). In essence,...

Invasive plant species and the Joint Fire Science Program.

Treesearch

Heather E. Erickson; Rachel White

2007-01-01

Invasive nonnative plants may be responsible for serious, long-term ecological impacts, including altering fire behavior and fire regimes. Therefore, knowing how to successfully manage invasive plants and their impacts on natural resources is crucial. We present a summary of research on invasive plants and fire that has been generated through the Joint Fire Science...

Fire Prevention in California's Riverside County Headstart Project: An Evaluation.

ERIC Educational Resources Information Center

Folkman, William S.; Taylor, Jean

Results of evaluation are reported for a safety program devised by Head Start teachers and California Division of Forestry personnel to teach fire prevention education to Head Start children. Chapters describe the place of fire prevention in Head Start and causes of fire starting behavior in children. The Head Start Fire Prevention Kit is also…

FireWorks curriculum featuring ponderosa, lodgepole, and whitebark pine forests

Treesearch

Jane Kapler Smith; Nancy E. McMurray

2000-01-01

FireWorks is an educational program for students in grades 1-10. The program consists of the curriculum in this report and a trunk of laboratory materials, specimens, and reference materials. It provides interactive, hands-on activities for studying fire ecology, fire behavior, and the influences of people on three fire-dependent forest types - Pinus ponderosa...

Massachusetts Public Fire and Safety Education Curriculum Planning Guidebook. Second Version.

ERIC Educational Resources Information Center

Massachusetts Department of Fire Services, Stow.

This updated curriculum planning guidebook is a resource for fire educators throughout the state of Massachusetts. It is designed to be a tool in efforts to: identify fire problems in the community; select appropriate behaviors and lessons to correct the fire problems; design fire education programs; and implement and evaluate the programs. The…

Modeling impacts of fire severity on successional trajectories and future fire behavior in Alaskan boreal forests

Treesearch

Jill F. Johnstone; T. Scott Rupp; Mark Olson; David. Verbyla

2011-01-01

Much of the boreal forest in western North America and Alaska experiences frequent, stand-replacing wildfires. Secondary succession after fire initiates most forest stands and variations in fire characteristics can have strong effects on pathways of succession. Variations in surface fire severity that influence whether regenerating forests are dominated by coniferous...

Economic efficiency and risk character of fire management programs, Northern Rocky Mountains

Treesearch

Thomas J. Mills; Frederick W. Bratten

1988-01-01

Economic efficiency and risk have long been considered during the selection of fire management programs and the design of fire management polices. The risk considerations was largely subjective, however, and efficiency has only recently been calculated for selected portions of the fire management program. The highly stochastic behavior of the fire system and the high...

Enhanced Risk of Wildfire Resulting from the Interactions between Pyro-Cumulus and Mountain Waves: Implications for Fire Research and Management

NASA Astrophysics Data System (ADS)

Kim, Y. J.; Linn, R.; Sauer, J.; Canfield, J.; Costigan, K. R.; Munoz-Esparza, D.

2014-12-01

The Los Alamos National Laboratory is conducting a research project to understand the physical mechanisms behind the Las Conchas Fire that occurred in Santa Fe National Forest near Los Alamos, New Mexico on June 26, 2011. Between 8 pm on June 26 and 3 am on June 27, the fire grew from 8,000 to 43,000 acres, spreading downhill in sparse fuels and lighter winds than were present during the first several hours of the fire. Fire behavior experts and fire management officers expected the fire to reach 9,000 to 12,000 acres by sunrise due to the anticipated burning conditions, but it actually increased 440% in size before 3 am, surprising everyone. One viable hypothesis was suggested for this baffling fire behavior: a partial collapse of the soot-laden pyrocumulus column (pyro-cu) that towered above the fire, causing a sustained density current carrying fire at high speed. Moreover, another mechanism has been suggested recently that could have significantly affected the fire characteristics around mountainous regions, such as Jemez Mountains near Los Alamos: the drastic changes in the speed, direction, and gustiness of the winds due to the development of mountain waves. The present research tests these hypotheses and attempts to decipher the combination of environmental conditions, due to pyro-cu and mountain wave interactions, and fire behavior dynamics associated with this anomalous wildfire event. Preliminary results from WRF (Weather Research and Forecasting model) and HIGRAD (High-GRADient model developed at LANL) simulations suggest that these two mechanisms may need to be taken into account in order to fully understand and prepare for atypical wildfire behavior in regions with complex topography. It is possible that the Las Conchas Fire could have directly affected the nearby Los Alamos National Laboratory if the fire broke out concurrently with both pyro-cu and strong mountain waves along the upstream of the Laboratory. This research also addresses its implications for the management as well as the research of wildfire in that, in order to prepare for potential wildfire, the topography of the surrounding region as well as the region of importance itself should be taken into account.

Evaluating Fire Risk in the Northeastern United States in the Past, Present, and Future

NASA Astrophysics Data System (ADS)

Miller, D.; Bradley, R. S.

2017-12-01

One poorly understood consequence of climate change is its effects on extreme events such as wildfires. Robust associations between wildfire frequency and climatic variability have been shown to exist, indicating that future climate change may continue to have a significant effect on wildfire activity. The Northeastern United States (NEUS) has seen some of the most infamous and largest historic fires in North America, such as the Miramichi Fire of 1825 and the fires of 1947. Although return intervals for large fires in the NEUS are long (hundreds of years), wildfires have played a critical role in ecosystem development and forest structure in the region. Understanding and predicting fire occurrence and vulnerability in the NEUS, especially in a changing climate, is economically and culturally important yet remains difficult due to human impacts (i.e. fire suppression activities and human disturbance). Thus, an alternative method for investigating fire risk in the NEUS is needed. Here, we present a compilation of meteorological data collected from Automated Surface Observing Systems (ASOS) from the NEUS throughout the 20th century through present day. We use these data to compute fifteen common "fire danger indices" employed in the USA and Canada to investigate changes in the region's fire risk over time, as well as the skill of each of these indices at predicting wildfire activity relative to the historical record of fires in the NEUS. We use dynamically-downscaled regional climate model output for the 21st century to project future wildfire activity based on the fire danger indices capable of capturing historical fire activity in the NEUS. These projections will aid in predicting how fire risk in the NEUS will evolve with anticipated climate change.

Prefrontal Cortex HCN1 Channels Enable Intrinsic Persistent Neural Firing and Executive Memory Function

PubMed Central

Thuault, Sébastien J.; Malleret, Gaël; Constantinople, Christine M.; Nicholls, Russell; Chen, Irene; Zhu, Judy; Panteleyev, Andrey; Vronskaya, Svetlana; Nolan, Matthew F.; Bruno, Randy

2013-01-01

In many cortical neurons, HCN1 channels are the major contributors to Ih, the hyperpolarization-activated current, which regulates the intrinsic properties of neurons and shapes their integration of synaptic inputs, paces rhythmic activity, and regulates synaptic plasticity. Here, we examine the physiological role of Ih in deep layer pyramidal neurons in mouse prefrontal cortex (PFC), focusing on persistent activity, a form of sustained firing thought to be important for the behavioral function of the PFC during working memory tasks. We find that HCN1 contributes to the intrinsic persistent firing that is induced by a brief depolarizing current stimulus in the presence of muscarinic agonists. Deletion of HCN1 or acute pharmacological blockade of Ih decreases the fraction of neurons capable of generating persistent firing. The reduction in persistent firing is caused by the membrane hyperpolarization that results from the deletion of HCN1 or Ih blockade, rather than a specific role of the hyperpolarization-activated current in generating persistent activity. In vivo recordings show that deletion of HCN1 has no effect on up states, periods of enhanced synaptic network activity. Parallel behavioral studies demonstrate that HCN1 contributes to the PFC-dependent resolution of proactive interference during working memory. These results thus provide genetic evidence demonstrating the importance of HCN1 to intrinsic persistent firing and the behavioral output of the PFC. The causal role of intrinsic persistent firing in PFC-mediated behavior remains an open question. PMID:23966682

[Fire behavior of Quercus mongolica leaf litter fuelbed under zero-slope and no-wind conditions. II. Analysis and modelling of fireline intensity, fuel consumption, and combustion efficiency].

PubMed

Zhang, Ji-Li; Liu, Bo-Fei; Di, Xue-Ying; Chu, Teng-Fei; Jin, Sen

2013-12-01

Mongolian oak (Quercus mongolica) is an important constructive and accompanying species in mixed broadleaf-conifer forest in Northeast China, In this paper, a laboratory burning experiment was conducted under zero-slope and no-wind conditions to study the effects of fuel moisture content, loading, and thickness on the fireline intensity, fuel consumption, and combustion efficiency of the Mongolian oak leaf litter fuelbed. The fuel moisture content, loading, and thickness all had significant effects on the three fire behavior indices, and there existed interactions between these three affecting factors. Among the known models, the Byram model could be suitable for the prediction of local leaf litter fire intensity only after re-parameterization. The re-estimated alpha and beta parameters of the re-parameterized Byram model were 98.009 and 1.099, with an adjusted determination coefficient of 0.745, the rooted mean square error (RMSE) of 8.676 kW x m(-1), and the mean relative error (MRE) of 21%, respectively (R2 = 0.745). The re-estimated a and b by the burning efficiency method proposed by Albini were 0.069 and 0.169, and the re-estimated values were all higher than 93%, being mostly overestimated. The Consume model had a stronger suitability for the fuel. The R2 of the general linear models established for fireline intensity, fuel consumption, and burning efficiency was 0.82, 0.73 and 0.53, and the RMSE was 8.266 kW x m(-1) 0.081 kg x m(-2), and 0.203, respectively. In low intensity surface fires, the fine fuels could not be completely consumed, and thus, to consider the leaf litter and fine fuel in some forest ecosystems being completely consumed would overestimate the carbon release from forest fires.

Global Change Impacts on Future Fire Regimes: Distinguishing Between Climate-limited vs Ignition-Limited Landscapes

NASA Astrophysics Data System (ADS)

Keeley, J. E.; Syphard, A. D.

2016-12-01

Global warming is expected to exacerbate fire impacts. Predicting how climates will impact future fire regimes requires an understanding of how temperature and precipitation interact to control fire activity. Inevitably this requires historical analyses that relate annual burning to climate variation. Within climatically homogeneous subregions, montane forested landscapes show strong relationships between annual fluctuations in temperature and precipitation with area burned, however, this is strongly seasonal dependent; e.g., winter temperatures have very little or no effect but spring and summer temperatures are critical. Climate models are needed that predict future seasonal temperature changes if we are to forecast future fire regimes in these forests. Climate does not appear to be a major determinant of fire activity on all landscapes. Lower elevations and lower latitudes show little or no increase in fire activity with hotter and drier conditions. On these landscapes climate is not usually limiting to fires but these vegetation types are ignition-limited, and because they are closely juxtaposed with human habitations fire regimes are more strongly controlled by other direct anthropogenic impacts. Predicting future fire regimes is not rocket science, it is far more complicated than that. Climate change is not relevant on some landscapes, but where climate is relevant the relationship will change due to direct climate effects on vegetation trajectories, as well as by feedback processes of fire effects on vegetation distribution, plus policy changes in how we manage ecosystems.