Predicting long-term development of abandoned subalpine conifer forests in the Swiss National Park

In the past 35 years, various kinds of dynamic models have been used to study vegetation development during primary or secondary succession. Typically, one specific model or models with the same conceptual background were employed. It remains largely unknown to what extent such model-based findings, e.g., on the speed of succession, depend on the specific model approach.To address this issue, we estimated the time elapsing during secondary succession in subalpine conifer forests of the Swiss National Park using three models of different conceptual background: (i) a forest gap model, (ii) a Markov chain model, and (iii) a minimum spanning tree model.Starting from a 95- to 125-year-old mountain pine (Pinus montana Miller) forest, all three models predicted a similar successional development. Even though the forest gap model and the Markov chain model are based on totally different approaches and were calibrated using different data sets, they both forecasted that it would take 500–550 years to reach a late-successional forest stage. The minimum spanning tree model, which only reveals a certain number of time steps yielding a minimum time estimate, showed a development of tree density (stems/ha) that was similar to the results of the forest gap model, but a strict quantitative comparison is not feasible.Our study shows that modeling forest development using three different approaches is quite powerful to obtain a robust estimate of the speed of forest succession. In our case, this estimate is higher than what has been suggested in previous studies that investigated secondary forest succession. The use of several approaches allows for a more comprehensive analysis in terms of variables covered (e.g., relative forest cover in the Markov approach vs. stand-scale species composition in the forest gap model). We recommend that in studies focusing on the speed of succession, several models should be employed simultaneously to identify inconsistencies in our knowledge and to increase confidence in the results.     

Interpreting and using outputs from the Canadian Forest Fire Danger Rating System in research applications

Understanding and being able to predict forest fire occurrence, fire growth and fire intensity are important aspects of forest fire management. In Canada fire management agencies use the Canadian Forest Fire Danger Rating System (CFFDRS) to help predict these elements of forest fire activity. In this paper a review of the CFFDRS is presented with the main focus on understanding and interpreting Canadian Fire Weather Index (FWI) System outputs. The need to interpret the outputs of the FWI System with consideration to regional differences is emphasized and examples are shown of how the relationship between actual fuel moisture and the FWI System’s moisture codes vary from region to region. Examples are then shown of the relationship between fuel moisture and fire occurrence for both human- and lightning-caused fire for regions with different forest composition. The relationship between rate of spread, fuel consumption and the relative fire behaviour indices of the FWI System for different forest types is also discussed. The outputs of the CFFDRS are used every day across Canada by fire managers in every district, regional and provincial fire management office. The purpose of this review is to provide modellers with an understanding of this system and how its outputs can be interpreted. It is hoped that this review will expose statistical modellers and other researchers to some of the models used currently in forest fire management and encourage further research and development of models useful for understanding and managing forest fire activity.

Fuel prices and new vehicle fuel economy—Comparing the United States and Western Europe

Several recent papers have documented an effect of fuel prices on new vehicle fuel economy in the United States. This paper estimates the effect of fuel prices on average new vehicle fuel economy for the eight largest European markets. The analysis spans the years 2002–2007 and uses detailed vehicle registration and specification data to control for policies, consumer preferences, and other potentially confounding factors. We find fuel prices to have a statistically significant effect on average new vehicle fuel economy in Europe. The effect estimated for Europe is much smaller than comparable estimates for the United States.     

Hyperspectral and LiDAR remote sensing of fire fuels in Hawaii Volcanoes National Park.

Alien invasive grasses threaten to transform Hawaiian ecosystems through the alteration of ecosystem dynamics, especially the creation or intensification of a fire cycle. Across sub-montane ecosystems of Hawaii Volcanoes National Park on Hawaii Island, we quantified fine fuels and fire spread potential of invasive grasses using a combination of airborne hyperspectral and light detection and ranging (LiDAR) measurements. Across a gradient from forest to savanna to shrubland, automated mixture analysis of hyperspectral data provided spatially explicit fractional cover estimates of photosynthetic vegetation, non-photosynthetic vegetation, and bare substrate and shade. Small-footprint LiDAR provided measurements of vegetation height along this gradient of ecosystems. Through the fusion of hyperspectral and LiDAR data, a new fire fuel index (FFI) was developed to model the three-dimensional volume of grass fuels. Regionally, savanna ecosystems had the highest volumes of fire fuels, averaging 20% across the ecosystem and frequently filling all of the three-dimensional space represented by each image pixel. The forest and shrubland ecosystems had lower FFI values, averaging 4.4% and 8.4%, respectively. The results indicate that the fusion of hyperspectral and LiDAR remote sensing can provide unique information on the three-dimensional properties of ecosystems, their flammability, and the potential for fire spread.     

Climatic Change, Wildfire, and Conservation

Abstract:  Climatic variability is a dominant factor affecting large wildfires in the western United States, an observation supported by palaeoecological data on charcoal in lake sediments and reconstructions from fire-scarred trees. Although current fire management focuses on fuel reductions to bring fuel loadings back to their historical ranges, at the regional scale extreme fire weather is still the dominant influence on area burned and fire severity. Current forecasting tools are limited to short-term predictions of fire weather, but increased understanding of large-scale oceanic and atmospheric patterns in the Pacific Ocean (e.g., El Niño Southern Oscillation, Pacific Decadal Oscillation) may improve our ability to predict climatic variability at seasonal to annual leads. Associations between these quasi-periodic patterns and fire occurrence, though evident in some regions, have been difficult to establish in others. Increased temperature in the future will likely extend fire seasons throughout the western United States, with more fires occurring earlier and later than is currently typical, and will increase the total area burned in some regions. If climatic change increases the amplitude and duration of extreme fire weather, we can expect significant changes in the distribution and abundance of dominant plant species in some ecosystems, which would thus affect habitat of some sensitive plant and animal species. Some species that are sensitive to fire may decline, whereas the distribution and abundance of species favored by fire may be enhanced. The effects of climatic change will partially depend on the extent to which resource management modifies vegetation structure and fuels.     

Application of Markov-chain model for vegetation restoration assessment at landslide areas caused by a catastrophic earthquake in Central Taiwan

The 921 earthquake caused a catastrophic disaster in Central Taiwan. Ten years have passed since the earthquake occurred. Vegetation succession is the basis for establishing a restoration reference which plays an important role in vegetation restoration at landslide sites. Generally, growth conditions for grass are easier and the growth rate is faster than that for trees. Therefore, grass can be considered a pioneer species or an important reference for the early vegetation succession stage. This is the reason why grass is required to be extracted from other land covers. Integrating remote sensing, geographic information system and image classification into vegetation succession models is very important. In this study, the Markov chain model was applied for vegetation restoration assessment and discussion. Chiufenershan and Ninety-nine peaks were selected as the study areas. Five SPOT satellite images are used for land cover mapping and vegetation restoration simulations. Four categories of land covers were extracted, including forest, grass, bare land and water, respectively. From the transitive probability matrix (derived from any two land covers), the results show that vegetation restoration at the Chiufenershan and Ninety-nine peaks landslide areas is ongoing, but that has been disturbed by natural disasters.     

植被根系及其土壤理化特征在高寒小嵩草草甸退化演替过程中的变化

以野外样地调查和室内分析法研究了不同退化演替阶段高寒小嵩草草甸的植被根系空间变化和土壤环境因子间的关系。结果表明,不同退化演替阶段高寒小嵩草草甸群落植被根系和蕴育植被根系的土壤量发生了明显的变化。特别是0~10 cm土层的植被根系在重度退化阶段显著高于其它退化演替阶段（P〈0.05）,而蕴育植被根系的＂载体＂量在重度退化阶段显著低于其它退化演替阶段（P〈0.05）,根土比（根和土的重量比）明显高于其它退化演替阶段（P〈0.05）;随着退化演替阶段的进行,高寒小嵩草草甸群落物种数、地上部分、植被根系锐减,群落结构和功能明显发生变化;不同退化演替阶段,植被根系（0~40 cm）的垂直分布、根土比与土壤容重、土壤含水量以及土壤中N、P含量存在一定的相关性;不同退化演替阶段高寒小嵩草草甸土壤理化特性的变化影响草地群落地上部分和植被根系;土壤的稳定性是草地生产稳定和恢复的重要因素,在评价与改良退化草地时,要充分了解土壤的退化程度。在高寒草甸地下根系取样方法难以统一,而且土壤表层根系和土壤很难难以分离,加之根系采样破坏性大、工作量大,根土比可能是指示高寒草甸退化程度相对可靠的量化指标。     

Forest Restoration and Fire: Principles in the Context of Place

Abstract:  There is broad consensus that active management through thinning and fire is urgently needed in many forests of the western United States. This consensus stems from physically based models of fire behavior and substantial empirical evidence. But the types of thinning and fire and where they are applied are the subjects of much debate. We propose that low thinning is the most appropriate type of thinning practice. Treating surface fuels, reducing ladder fuels, and opening overstory canopies generally produce fire-safe forest conditions, but large, fire-resistant trees are also important components of fire-safe forests. The context of place is critical in assigning priority for the limited resources that will be available for restoration treatments. Historical low-severity fire regimes, because of their current high hazards and dominance by fire-resistant species, are the highest priority for treatment. Mixed-severity fire regimes are of intermediate priority, and high-severity fire regimes are of lowest priority. Classification systems based on potential vegetation will help identify these fire regimes at a local scale.     

Wildfire, landscape diversity and the Drossel-Schwabl model

How simple can a model be that still captures essential aspects of wildfire ecosystems at large spatial and temporal scales? The Drossel-Schwabl model (DSM) is a metaphorical forest-fire model developed to reproduce only one pattern of real systems: a frequency distribution of fire sizes resembling a power law. Consequently, and because it appears oversimplified, it remains unclear what bearings the DSM has in reality. Here, we test whether the DSM is capable of reproducing a pattern that was not considered in its design, the hump-shaped relation between the diversity of succession stages and average annual area burnt. We found that the model, once reformulated to represent succession, produces realistic landscape diversity patterns. We investigated four succession scenarios of forest-fire ecosystems in the USA and Canada. In all scenarios, landscape diversity is highest at an intermediate average annual area burnt as predicted by the intermediate disturbance hypothesis. These results show that a model based solely on the dynamics of the fuel mosaic has surprisingly high predictive power with regard to observed statistical properties of wildfire systems at large spatial scales. Parsimonious models, such as the DSM can be used as starting points for systematic development of more structurally realistic but tractable wildfire models. Due to their simplicity they allow analytical approaches that further our understanding under increasing complexity.     

Modelling the spatial distribution of montane and subalpine forests in the central Alps using digital elevation models

The analysis of complex interactions between spatial distribution patterns of site factors and vegetation types is crucial for understanding high mountain ecosystems, especially in the view of a changing climate. Therefore, in the present study, a GIS and remote sensing-based approach is followed to produce a vegetation map for a study area in the Western Alps (Switzerland). Two major forest alliances are chosen for analysis: subalpine coniferous forest Vaccinio-Piceion/Larici-Pinetum cembrae and montane oak forest Quercion pubescenti-petraeae. As spatial information on site factors is commonly lacking in mountain areas, the use of a digital elevation model (DEM) is a potential substitute for use in vegetation analyses: it highly correlates with temperature, moisture, geomorphological processes and disturbance factors. Thus, it is important to analyse the capabilities of a DEM for indicating habitat conditions in a landscape characterised by high topodiversity and a patchwork of microclimatic habitats.For the purpose of identifying the potential of landform parameters for the indication of forest habitat structures in the present study, 24 primary and secondary landform parameters have been derived, indicating temperature and moisture distribution, exposure towards wind, snow, etc. Quantitative analyses were performed using statistical means such as contingency correlation coefficients and principal components analysis. The results formed the basis for the development of parallel-epiped-vegetation models (PED) used to simulate the spatial distribution patterns of the subalpine coniferous and the montane oak forest. It can be shown that topographic variables derived from a DEM at a spatial resolution of 25 m are very useful for indicating habitats of large forest types. Additionally potential forest sites in the cultural landscape, removed by human logging, can be reconstructed.Inaccuracies within the simulation results can partly be attributed to the insufficient parameterisation of geomorphologic activity and to poor spatial resolution of the DEM as compared to the vegetation data. Although the lack of information on the human dimension leads to some uncertainties in the interpretation of spatial patterns of vegetation, the exclusive use of topographic variables in vegetation models for the indication of forest habitats is very promising.     

Life cycle analysis and choice of natural gas-based automotive alternative fuels in Chongqing Municipality, China

Road transport produces significant amounts of emissions by using crude oil as the primary energy source. A reduction of emissions can be achieved by implementing alternative fuel chains. The objective of this study is to carry out an economic, environmental and energy (EEE) life cycle study on natural gas-based automotive fuels with conventional gasoline in an abundant region of China. A set of indices of four fuels/vehicle systems on the basis of life cycle are assessed in terms of impact of EEE, in which natural gas produces compressed natural gas (CNG), methanol, dimethylether (DME) and Fischer Tropsch diesel (FTD). The study included fuel production, vehicle production, vehicle operation, infrastructure and vehicle end of life as a system for each fuel/vehicle system. A generic gasoline fueled car is used as a baseline. Data have been reviewed and modified based on the best knowledge available to Chongqing local sources. Results indicated that when we could not change electric and hydrogen fuel cell vehicles into commercial vehicles on a large scale, direct use of CNG in a dedicated or bi-fuel vehicle is an economical choice for the region which is most energy efficient and more environmental friendly. The study can be used to support decisions on how natural gas resources can best be utilized as a fuel/energy resource for automobiles, and what issues need to be resolved in Chongqing. The models and approaches for this study can be applied to other regions of China as long as all the assumptions are well defined and modified to find a substitute automotive energy source and establish an energy policy in a specific region.     

Development of a framework for fire risk assessment using remote sensing and geographic information system technologies

Forest fires play a critical role in landscape transformation, vegetation succession, soil degradation and air quality. Improvements in fire risk estimation are vital to reduce the negative impacts of fire, either by lessen burn severity or intensity through fuel management, or by aiding the natural vegetation recovery using post-fire treatments. This paper presents the methods to generate the input variables and the risk integration developed within the Firemap project (funded under the Spanish Ministry of Science and Technology) to map wildland fire risk for several regions of Spain. After defining the conceptual scheme for fire risk assessment, the paper describes the methods used to generate the risk parameters, and presents proposals for their integration into synthetic risk indices. The generation of the input variables was based on an extensive use of geographic information system and remote sensing technologies, since the project was intended to provide a spatial and temporal assessment of risk conditions. All variables were mapped at 1 km² spatial resolution, and were integrated into a web-mapping service system. This service was active in the summer of 2007 for semi-operational testing of end-users. The paper also presents the first validation results of the danger index, by comparing temporal trends of different danger components and fire occurrence in the different study regions.     

Modeling the dynamic habitat and breeding population of Southwestern Willow Flycatcher

To aid in the management and conservation of Southwestern Willow Flycatcher (Empidonax traillii extimus, hereafter “Flycatcher”), we developed numerous models of flycatcher breeding habitat at Roosevelt Lake, AZ. For model development and testing, we compiled 10 years of flycatcher territory data that were obtained from intensive fieldwork between 1996 and 2005. We identified riparian vegetation annually in the project area from Landsat Thematic Mapper images, and extracted floodplain features from a digital elevation model. We created a novel class of temporal (i.e., multiyear) variables by characterizing the stability and variability in breeding habitat over a 6-year time interval. We used logistic regression to determine associations between environmental variables and flycatcher territory occurrence, and to test specific hypotheses. We mapped the probability of territory occurrence with a GIS and determined model accuracies with a classification table and a 10-year population database. Environmental features that were associated with breeding flycatchers included floodplain size, proximity to water, and the density, heterogeneity, age and stability of riparian vegetation. Our best model explained 79% of the variability in the flycatcher breeding population at Roosevelt Lake. The majority of predicted flycatcher habitat formed between 1996 and 2004 on an exposed lakebed ～3 years after water levels receded during a prolonged drought. A high correlation between annual reservoir levels and predicted breeding habitat (r = ?0.82) indicates that we can create and manage habitat for conservation purposes. Our predictive models quantify and assess the relative quality of flycatcher breeding habitat remotely, and can be used to evaluate the effectiveness of habitat restoration activities. Numerous techniques we developed can be used to characterize riparian vegetation and patch dynamics directly off of satellite imagery, thereby increasing its utility for conservation purposes.     

Recovery of Endemic Dragonflies after Removal of Invasive Alien Trees

Abstract:  Because dragonflies are very sensitive to alien trees , we assessed their response to large-scale restoration of riparian corridors. We compared three types of disturbance regime—alien invaded , cleared of alien vegetation , and natural vegetation (control)—and recorded data on 22 environmental variables. The most significant variables in determining dragonfly assemblages were percentage of bank cover and tree canopy cover , which indicates the importance of vegetation architecture for these dragonflies. This finding suggests that it is important to restore appropriate marginal vegetation and sunlight conditions. Recovery of dragonfly assemblages after the clearing of alien trees was substantial. Species richness and abundance at restored sites matched those at control sites. Dragonfly assemblage patterns reflected vegetation succession. Thus , initially eurytopic , widespread species were the main beneficiaries of the removal of alien trees , and stenotopic , endemic species appeared after indigenous vegetation recovered over time. Important indicator species were the two national endemics ( Allocnemis leucosticta and Pseudagrion furcigerum ) , which , along with vegetation type , can be used to monitor return of overall integrity of riparian ecology and to make management decisions. Endemic species as a whole responded positively to restoration , which suggests that indigenous vegetation recovery has major benefits for irreplaceable and widespread generalist species .     

Large-scale effects of a small herbivore on salt-marsh vegetation succession—A comparative study on three Wadden Sea islands

Grazing by livestock is used as a management tool to prevent the dominance of a single tall-growing specises during succession on European salt marshes. The effects of natural small herbivores are often neglected by managers. Long-term exclosure experiments on the island of Schiermonnikoog show that hares retard vegetation succession at the early stages of salt-marsh development. In the present study we test whether we can scale-up these exclosure studies to a whole salt-marsh system. We compared 30 years of undisturbed vegetation succession at the Wadden Sea islands of Schiermonnikoog, Rottumerplaat (both The Netherlands) and Mellum (Germany). Salt-marsh development started at all sites in the early 1970s. Hares have been present only on Schiermonnikoog. At each site an area was selected covering a gradient from high to low salt marsh. Surface elevation and clay thickness were measured and a vegetation map was made on the three islands. The areas showed similar clay thickness at low surface elevation, indicating similar sedimentation ratesand hence nitrogen inputs. Rottumerplaat and Mellum showed a higher dominance of the late successional speciesAtriplex portulacoides in the low marsh andElymus athericus in the high marsh compared to Schiermonnikoog. Typical mid-successional, important food plant species for hares and geese had a higher abundance at Schiermonnikoog. Patterns of vegetation development in the absence of hares followed the observed patterns in the smallscale exclosure experiments at Schiermonnikoog. Without hare grazing, vegetation succession proceeds more rapidly and leads to the dominance of tall-growing species in earlier stages of succession. The present study shows that next to large herbivores, small herbivores potentially have largescale effects on salt-marsh vegetation succession during the early successional stages.     

Obligatory barrier crossing and adaptive fuel management in migratory birds: the case of the Atlantic crossing in Northern Wheatears (<Emphasis Type="Italic">Oenanthe oenanthe</Emphasis>)

Behaviour on migration was often suggested to be selected for time-minimising strategies. Current optimality models predict that optimal fuel loads at departure from stopover sites should increase with increasing fuel deposition rates. We modified such models for the special case of the east Atlantic crossing of the Northern Wheatear (Oenanthe oenanthe). From optimality theory, we predict that optimal time-minimising behaviour in front of such a barrier should result in a positive correlation between fuel deposition rates and departure fuel loads only above a certain threshold, which is the minimum fuel load (f _min) required for the barrier crossing. Using a robust range equation, we calculated the minimum fuel loads for different barrier crossings and predict that time-minimising wheatears should deposit a minimum of 24% fuel in relation to lean body mass (m ₀ ) for the sea crossing between Iceland and Scotland. Fuel loads of departing birds in autumn in Iceland reached this value only marginally but showed positive correlation between fuel deposition rate (FDR) and departure fuel load (DFL). Birds at Fair Isle (Scotland) in spring, which were heading towards Iceland or Greenland, were significantly heavier and even showed signs of overloading with fuel loads up to 50% of lean body mass. Departure decisions of Icelandic birds correlated significantly with favourable wind situations when assuming a migration direction towards Spain; however, the low departure fuel loads contradict a direct non-stop flight.     

Vegetation succession of low estuarine marshes is affected by distance to navigation channel and changes in water level

Climate change and engineering activities have modified the hydrology and morphology of estuaries. However, the potential effects of these modifications on vegetation succession in estuarine marshes are still poorly understood. Therefore, we studied temporal changes in tidal habitats of the Elbe estuary over a period of 30 years. We compared vegetation maps from 1980 to 2010 and calculated the change in area of habitats with respect to three salinity and three elevational zones. To analyze the direction of the temporal change, we differentiated between progressive and regressive succession. By using regression tree models (conditional inference trees), we identified the most influential factors determining progressive or regressive succession of low marshes. The total area of the estuarine tidal marshes at the Elbe increased by 2 % from 1980 to 2010, but changes were unequal among the salinity zones. In the salt and brackish zones, the area covered by high marshes increased substantially but decreased in the tidal freshwater zone, while that covered by low marshes decreased in all the salinity zones. Additionally, we determined high persistence of tidal flats and high marshes, whereas only 19 to 28 % of the low marshes found in 1980 remained in 2010. In salt and brackish marshes, more than two-thirds of the area that had been identified as low marshes in 1980 had progressively developed into high marshes. In contrast, 44 % of the area of low marshes in tidal freshwater marshes showed regressive succession back into tidal flats. The distance to the navigation channel was the main factor determining successional direction in salt and brackish marshes. Here, greater proximity to the channel was correlated with higher risk of regressive succession. In tidal freshwater marshes, we identified both the distance to the navigation channel and the situation on the river shore (i.e. inner bank, outer bank or straight bank) as the main factors for marsh succession. Here, considerable engineering activities in the channel had simultaneously decreased the mean low water level and increased the mean high water level between 1980 and 2010, which led to an increase in tidal amplitude. It is quite likely that these changes negatively modified marsh distribution, increased regressive succession and, thus, lowered the quality of tidal freshwater marshes.     

Assessing the performance of theoretical and empirical tree mortality models using tree-ring series of Norway spruce

Successional dynamics of forests under current and changed climate are often investigated using gap models, a subset of forest succession models that simulate establishment, growth, and mortality of trees. However, the mortality submodels of gap models are largely based on theoretical assumptions, and have not been tested in detail.In the present study, we compared the performance of a range of theoretical mortality functions (TMFs) that are commonly used in gap models with several empirical mortality functions (EMFs) that were derived using logistic regression from growth patterns of tree-ring series as predictor variables. Data from dead and living Norway spruce (Picea abies (L.) Karst.) trees from subalpine forests at three study sites in Switzerland were used to this end.Three of the four EMFs consistently performed better at all three sites, while three of the four TMFs performed worse than the remaining mortality functions. At one site, these three EMFs correctly classified 71–78% of the dead trees (48–72% for the three TMFs) and 73% (49–64%) of the living trees. 44–54% (21–25%) of the dead trees were predicted to die within 15 years prior to death. 0–2% (7–10%) of the dead trees and 5% (19–31%) of the living trees were predicted to die more than 60 years prior to the last measured year.We conclude that, unless the parameters of the TMFs are optimized for individual species, the TMFs are not appropriate to predict the time of tree death, in spite of their widespread use. A substantial change in simulated forest succession is to be expected if the currently implemented TMFs in gap models are replaced by species-specific EMFs.     

Evaluating the ecological benefits of wildfire by integrating fire and ecosystem simulation models

Fire managers are now realizing that wildfires can be beneficial because they can reduce hazardous fuels and restore fire-dominated ecosystems. A software tool that assesses potential beneficial and detrimental ecological effects from wildfire would be helpful to fire management. This paper presents a simulation platform called FLEAT (Fire and Landscape Ecology Assessment Tool) that integrates several existing landscape- and stand-level simulation models to compute an ecologically based measure that describes if a wildfire is moving the burning landscape towards or away from the historical range and variation of vegetation composition. FLEAT uses a fire effects model to simulate fire severity, which is then used to predict vegetation development for 1, 10, and 100 years into the future using a landscape simulation model. The landscape is then simulated for 5000 years using parameters derived from historical data to create an historical time series that is compared to the predicted landscape composition at year 1, 10, and 100 to compute a metric that describes their similarity to the simulated historical conditions. This tool is designed to be used in operational wildfire management using the LANDFIRE spatial database so that fire managers can decide how aggressively to suppress wildfires. Validation of fire severity predictions using field data from six wildfires revealed that while accuracy is moderate (30-60%), it is mostly dictated by the quality of GIS layers input to FLEAT. Predicted 1-year landscape compositions were only 8% accurate but this was because the LANDFIRE mapped pre-fire composition accuracy was low (21%). This platform can be integrated into current readily available software products to produce an operational tool for balancing benefits of wildfire with potential dangers.     

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

Crown fire 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 (CFD) and can be used to model fire in heterogeneous crown fuels. However, the potential impacts of variability in crown fuels on fire behavior have not yet been explored. In this study we describe a new model, FUEL3D, which incorporates the pipe model theory (PMT) and a simple 3D recursive branching approach to model the distribution of fuel within individual tree crowns. FUEL3D uses forest inventory data as inputs, and stochastically retains geometric variability observed in field data. We investigate the effects of crown fuel heterogeneity on fire behavior with a CFD fire model by simulating fire under a homogeneous tree crown and a heterogeneous tree crown modeled with FUEL3D, using two different levels of surface fire intensity. Model output is used to estimate the probability of tree mortality, linking fire behavior and fire effects at the scale of an individual tree. We discovered that variability within a tree crown altered the timing, magnitude and dynamics of how fire burned through the crown; effects varied with surface fire intensity. In the lower surface fire intensity case, the heterogeneous tree crown barely ignited and would likely survive, while the homogeneous tree had nearly 80% fuel consumption and an order of magnitude difference in total net radiative heat transfer. In the higher surface fire intensity case, both cases burned readily. Differences for the homogeneous tree between the two surface fire intensity cases were minimal but were dramatic for the heterogeneous tree. These results suggest that heterogeneity within the crown causes more conditional, threshold-like interactions with fire. We conclude with discussion of implications for fire behavior modeling and fire ecology.