Human influence on California fire regimes.

Periodic wildfire maintains the integrity and species composition of many ecosystems, including the mediterranean-climate shrublands of California. However, human activities alter natural fire regimes, which can lead to cascading ecological effects. Increased human ignitions at the wildland-urban interface (WUI) have recently gained attention, but fire activity and risk are typically estimated using only biophysical variables. Our goal was to determine how humans influence fire in California and to examine whether this influence was linear, by relating contemporary (2000) and historic (1960-2000) fire data to both human and biophysical variables. Data for the human variables included fine-resolution maps of the WUI produced using housing density and land cover data. Interface WUI, where development abuts wildland vegetation, was differentiated from intermix WUI, where development intermingles with wildland vegetation. Additional explanatory variables included distance to WUI, population density, road density, vegetation type, and ecoregion. All data were summarized at the county level and analyzed using bivariate and multiple regression methods. We found highly significant relationships between humans and fire on the contemporary landscape, and our models explained fire frequency (R2 = 0.72) better than area burned (R2 = 0.50). Population density, intermix WUI, and distance to WUI explained the most variability in fire frequency, suggesting that the spatial pattern of development may be an important variable to consider when estimating fire risk. We found nonlinear effects such that fire frequency and area burned were highest at intermediate levels of human activity, but declined beyond certain thresholds. Human activities also explained change in fire frequency and area burned (1960-2000), but our models had greater explanatory power during the years 1960-1980, when there was more dramatic change in fire frequency. Understanding wildfire as a function of the spatial arrangement of ignitions and fuels on the landscape, in addition to nonlinear relationships, will be important to fire managers and conservation planners because fire risk may be related to specific levels of housing density that can be accounted for in land use planning. With more fires occurring in close proximity to human infrastructure, there may also be devastating ecological impacts if development continues to grow farther into wildland vegetation.     

Constraints on global fire activity vary across a resource gradient

We provide an empirical, global test of the varying constraints hypothesis, which predicts systematic heterogeneity in the relative importance of biomass resources to burn and atmospheric conditions suitable to burning (weather/climate) across a spatial gradient of long-term resource availability. Analyses were based on relationships between monthly global wildfire activity, soil moisture, and mid-tropospheric circulation data from 2001 to 2007, synthesized across a gradient of long-term averages in resources (net primary productivity), annual temperature, and terrestrial biome. We demonstrate support for the varying constraints hypothesis, showing that, while key biophysical factors must coincide for wildfires to occur, the relative influence of resources to burn and moisture/weather conditions on fire activity shows predictable spatial patterns. In areas where resources are always available for burning during the fire season, such as subtropical/tropical biomes with mid-high annual long-term net primary productivity, fuel moisture conditions exert their strongest constraint on fire activity. In areas where resources are more limiting or variable, such as deserts, xeric shrublands, or grasslands/savannas, fuel moisture has a diminished constraint on wildfire, and metrics indicating availability of burnable fuels produced during the antecedent wet growing seasons reflect a more pronounced constraint on wildfire. This macro-scaled evidence for spatially varying constraints provides a synthesis with studies performed at local and regional scales, enhances our understanding of fire as a global process, and indicates how sensitivity to future changes in temperature and precipitation may differ across the world.     

Mapping lightning/human-caused wildfires occurrence under ignition point location uncertainty

Fire managers need to study fire history in terms of occurrence in order to understand and model the spatial distribution of the causes of ignition. Fire atlases are useful open sources of information, recording each single fire event by means of its geographical position. In such cases the fire event is considered as point-based, rather than area-based data, completely losing its surface nature. Thus, an accurate method is needed to estimate continuous density surfaces from ignition points where location is affected by a certain degree of uncertainty. Recently, the fire scientific community has focused its attention on the kernel density interpolation technique in order to convert point-based data into continuous surface or surface-data. The kernel density technique needs a priori setting of smoothing parameters, such as the bandwidth size. Up to now, the bandwidth size was often based on subjective choices still needing expert knowledge, eventually supported by empirical decisions, thus leading to serious uncertainties. Nonetheless, a geostatistical model able to describe the point concentration and consequently the clustering degree is required. This paper tries to solve such issues by implementing the kernel density adaptive mode. Lightning/human-caused fires occurrence was investigated in the region of Aragón's autonomy over 19 years (1983–2001) using 3428 and 4195 ignition points respectively for the two causes of fire origin. An analytical calibration procedure was implemented to select the most reliable density surfaces to reduce under/over-density estimation, overcoming the current drawbacks to define it by visual inspection or personal interpretation. Besides, ignition point location uncertainty was investigated to check the sensitivity of the proposed model. The different concentration degree and the dissimilar spatial pattern of the two datasets, allow testing the proposed calibration methodology under several conditions. After having discovered the slight sensitivity of the model to the exact point position, the obtained density surfaces for the two causes were combined to discover hotspot areas and spatial patterns of the two causes. Evident differences in spatial location of the origin causes were noted and described. The general trend follows the geographical features and the human activity of the study areas. The proposed technique should be promising to support decision-making in wildfire prevention actions, because of the occurrence map can be used as a response variable in fire risk predicting models.     

Conservation Threats Due to Human-Caused Increases in Fire Frequency in Mediterranean-Climate Ecosystems

Periodic wildfire is an important natural process in Mediterranean-climate ecosystems, but increasing fire recurrence threatens the fragile ecology of these regions. Because most fires are human-caused, we investigated how human population patterns affect fire frequency. Prior research in California suggests the relationship between population density and fire frequency is not linear. There are few human ignitions in areas with low population density, so fire frequency is low. As population density increases, human ignitions and fire frequency also increase, but beyond a density threshold, the relationship becomes negative as fuels become sparser and fire suppression resources are concentrated. We tested whether this hypothesis also applies to the other Mediterranean-climate ecosystems of the world. We used global satellite databases of population, fire activity, and land cover to evaluate the spatial relationship between humans and fire in the world's five Mediterranean-climate ecosystems. Both the mean and median population densities were consistently and substantially higher in areas with than without fire, but fire again peaked at intermediate population densities, which suggests that the spatial relationship is complex and nonlinear. Some land-cover types burned more frequently than expected, but no systematic differences were observed across the five regions. The consistent association between higher population densities and fire suggests that regardless of differences between land-cover types, natural fire regimes, or overall population, the presence of people in Mediterranean-climate regions strongly affects the frequency of fires; thus, population growth in areas now sparsely settled presents a conservation concern. Considering the sensitivity of plant species to repeated burning and the global conservation significance of Mediterranean-climate ecosystems, conservation planning needs to consider the human influence on fire frequency. Fine-scale spatial analysis of relationships between people and fire may help identify areas where increases in fire frequency will threaten ecologically valuable areas.     

Knowing fire incidence through fuel phenology: A remotely sensed approach

Fire is a basic ecological factor that contributes to determine vegetation diversity and dynamics in time and space. Fuel characteristics play an essential role in fire ignition and propagation; at the landscape scale fuel availability and flammability are closely related to the vegetation phenology that directly affects wildfire pattern in time and space. In this view, the annual normalized difference vegetation index (NDVI) profiles derived from high temporal resolution satellites, like SPOT Vegetation, represent an effective tool for monitoring the coarse-scale vegetation seasonal timing. The objective of this study thus consists in quantifying the explanatory power of multitemporal NDVI profiles on the fire regime characteristics of the potential natural vegetation (PNV) types of Sardinia (Italy) over a 5-year period (2000-2004). The results obtained show a good association between the NDVI temporal dynamics of the PNV of Sardinia and the corresponding fire regime characteristics, emphasizing the role of the bioclimatic timing of the vegetation in controlling the coarse-scale wildfire spatio-temporal distribution of Sardinia. By providing a sound phytogeographical framework for describing different wildfire regimes, PNV maps can thus be considered helpful cartographic documents for fire management strategies at the landscape scale.     

Cicada emergence in Southwestern riparian forest: influences of wildfire and vegetation composition.

Annually emerging cicadas are a numerically and ecologically dominant species in Southwestern riparian forests. Humans have altered disturbance regimes that structure these forests such that floods are less common and wildfires occur more frequently than was historically the case. Impacts of these changes on primary consumers such as riparian cicadas are unknown. Because cicadas are consumed by a variety of animal species, disturbances that alter timing of their emergence or abundance could have consequences for species at higher trophic levels. We trapped emerging cicadas (Tibicen dealbatus) in burned and unburned riparian forest plots along the Middle Rio Grande in central New Mexico (USA) to determine effects of wildfire and vegetation structure on their density and phenology. We measured vegetation variables and soil temperature at cicada traps and related these variables to variation in emergence density and phenology. We also experimentally heated soil under emergence traps to examine the relationship between soil temperature and emergence phenology. Emergence density was similar in wildfire and unburned plots, though emergence date averaged earlier in wildfire plots and experimentally heated traps. We identified models containing cottonwood proximity (distance from the nearest cottonwood tree) and cottonwood canopy coverage as the most parsimonious explanations of emergence density at each trap. Model selection results were consistent with the literature and field observations that showed that cottonwood trees are an essential resource for T. dealbatus. Cottonwood canopy was also correlated with low soil temperatures, which are associated with later emergence dates. Failure of cottonwoods to reestablish following wildfire could result in cicadas emerging at lower densities and at earlier dates. For cicadas to emerge at densities and times that provide the greatest benefits to birds and other riparian-obligate secondary consumers, riparian forests should be protected from fire, and native vegetation in wildfire sites should be restored.     

Causasilty among wildfire,ENSO, timber harvest,and urban sprawl: The vector autoregression approach

This article demonstrates the applicability of vector autoregression (VAR) modeling in probing the causality relationships among wildfire, El Niño/Southern Oscillation (ENSO), timber harvest, and urban sprawl in the U.S. The VAR approach allows for the multi-directional, multi-faceted interactions among the variables concerned and enables us to portray the temporal impacts of ENSO, the volume of timber harvested, and urban sprawl on wildfire. The empirical analysis, though intended mainly for illustration, reveals that an individual factor may not affect wildfire activity (number of fires and area burned) when acting alone, but can significantly influence fire activity when coupled with other factors, and that wildfire activity has feedback effects on other variables. The impact of a change in ENSO, the volume of timber harvested, and urban population density on wildfire activity could last two decades with the most noticeable impact occurring in the initial 5–10 years. Though ENSO, timber harvest, and urban sprawl all Granger-cause wildfire activity, the impulse response functions show that wildfire activity is more responsive to urban population density than to the volume of timber harvested or ENSO. Thus, controlling urban sprawl represents another option for wildfire mitigation; and integrative wildfire management is essential.     

Bandwidth determination for kernel density analysis of wildfire events at forest sub-district scale

Forest fire is regarded as one of the most significant factors leading to land degradation. While evaluating fire hazard or producing fire risk zone maps, quantitative analyses using historic fire data is often required, and during all these modeling and multi-criteria analysis processes, the fire event itself is taken as the dependent variable. However, there are two main problematic issues in analyzing historic fire data. The first difficulty arises from the fact that it is in point format, whereas a continuous surface is frequently needed for statistically analyzing the relationship of fire events with other factors, such as anthropogenic, topographic and climatic conditions. Another, and probably the most bothersome challenge is to overcome inaccuracy inherent in historic fire data in point format, since the exact coordinates of ignition points are mostly unknown. In this study, kernel density mapping, a widely used method for converting discrete point data into a continuous raster surface, was used to map the historic fire data in Mumcular Forest Sub-district in Mu?la, Turkey. The historic fire data was transferred onto the digital forest stand map of the study area, where the exact locations of ignition points are unknown; however, the exact number of ignition points in each compartment of the forest stand map is known. Different random distributions of ignition points were produced, and for each random distribution, kernel density maps were produced by applying two distinct kernel functions with several smoothing parameter options. The obtained maps were compared through correlation analysis in order to illustrate the effect of randomness, choice of kernel function and smoothing parameter. The proposed method gives a range of values rather than a single bandwidth value; however, it provides a more reliable way than comparing the maps with different bandwidths subjectively by eye.     

Shapes of simulated fires in discrete fuels

Simulation models are used to examine the possible effects of discrete fuel distributions and of several fire-spread mechanisms on fire shapes. Two postulated fire spread mechanisms —heat accumulation and flame contact—are shown to yield near-ellipses in continuous fuels, but a wide range of shapes in discrete and very patchy fuels. The alternative shapes include ovoids, “tear-drop” (with the ignition point at varying positions on the major axis), and straight lines. Simulated fires in discrete, patchy fuels are less regular in shape than in uniform and continuous fuels and show little or no backburning. The results may explain certain observed differences between wildfire shapes that occur in different environments and at different burning intensities.     

Fighting fire with fire: estimating the efficacy of wildfire mitigation programs using propensity scores

This paper examines the effect wildfire mitigation has on broad-scale wildfire behavior. Each year, hundreds of million of dollars are spent on fire suppression and fuels management applications, yet little is known, quantitatively, of the returns to these programs in terms of their impact on wildfire extent and intensity. This is especially true when considering that wildfire management influences and reacts to several, often times confounding factors, including socioeconomic characteristics, values at risk, heterogeneous landscapes, and climate. Due to the endogenous nature of suppression effort and fuels management intensity and placement with wildfire behavior, traditional regression models may prove inadequate. Instead, I examine the applicability of propensity score matching (PSM) techniques in modeling wildfire. This research makes several significant contributions including: (1) applying techniques developed in labor economics and in epidemiology to evaluate the effects of natural resource policies on landscapes, rather than on individuals; (2) providing a better understanding of the relationship between wildfire mitigation strategies and their influence on broad-scale wildfire patterns; (3) quantifying the returns to suppression and fuels management on wildfire behavior.

Hierarchical space-time models for fire ignition and percentage of land burned by wildfires

Policy responses for local and global fire management as well as international green-gas inventories depend heavily on the proper understanding of the annual fire extend as well as its spatial variation across any given study area. Proper statistical models are important tools in quantifying these fire risks. We propose Bayesian methods to model jointly the probability of ignition and fire sizes in Australia and New Zeland. The data set on which we base our model and results consists of annual observations of several meteorological and topographical explanatory variables, together with the percentage of land burned over a grid with resolution of 1° across Austalia and New Zealand. Our model and conclusions bring improvements on the results reported by Russell-Smith et al. in Int J Wildland Fire, 16:361–377 (2007) based on a similar data set.     

Wildfire smoke and health impacts: A closer look at fire attributes and their marginal effects

Existing studies on the economic impact of wildfire smoke have focused on single fire events or entire seasons without considering the marginal effect of daily fire progression on downwind communities. Neither approach allows for an examination of the impact of even the most basic fire attributes, such as distance and fuel type, on air quality and health outcomes. Improved knowledge of these effects can provide important guidance for efficient wildfire management strategies. This study aims to bridge this gap using detailed information on 24 large-scale wildfires that sent smoke plumes to the Reno/Sparks area of Northern Nevada over a 4-year period. We relate the daily acreage burned by these fires to daily data on air pollutants and local hospital admissions. Using information on medical expenses, we compute the per-acre health cost of wildfires of different attributes. We find that patient counts can be causally linked to fires as far as 200–300 miles from the impact area. As expected, the marginal impact per acre burned generally diminishes with distance and for fires with lighter fuel loads. Our results also highlight the importance of allowing for temporal lags between fire occurrence and pollutant levels.     

Responses of pond-breeding amphibians to wildfire: short-term patterns in occupancy and colonization.

Wildland fires are expected to become more frequent and severe in many ecosystems, potentially posing a threat to many sensitive species. We evaluated the effects of a large, stand-replacement wildfire on three species of pond-breeding amphibians by estimating changes in occupancy of breeding sites during the three years before and after the fire burned 42 of 83 previously surveyed wetlands. Annual occupancy and colonization for each species was estimated using recently developed models that incorporate detection probabilities to provide unbiased parameter estimates. We did not find negative effects of the fire on the occupancy or colonization rates of the long-toed salamander (Ambystoma macrodactylum). Instead, its occupancy was higher across the study area after the fire, possibly in response to a large snowpack that may have facilitated colonization of unoccupied wetlands. Naive data (uncorrected for detection probability) for the Columbia spotted frog (Rana luteiventris) initially led to the conclusion of increased occupancy and colonization in wetlands that burned. After accounting for temporal and spatial variation in detection probabilities, however, it was evident that these parameters were relatively stable in both areas before and after the fire. We found a similar discrepancy between naive and estimated occupancy of A. macrodactylum that resulted from different detection probabilities in burned and control wetlands. The boreal toad (Bufo boreas) was not found breeding in the area prior to the fire but colonized several wetlands the year after they burned. Occupancy by B. boreas then declined during years 2 and 3 following the fire. Our study suggests that the amphibian populations we studied are resistant to wildfire and that B. boreas may experience short-term benefits from wildfire. Our data also illustrate how naive presence-non-detection data can provide misleading results.     

Conservation Threat of Increasing Fire Frequencies in the Western Ghats, India

Abstract:  The acceleration of processes such as forest fragmentation and forest fires in landscapes under intense human pressures makes it imperative to quantify and understand the effects of these processes on the conservation of biodiversity in these landscapes. We combined information from remote-sensing imagery and ground maps of all fires in the Mudumalai Wildlife Sanctuary (MWLS) in the Western Ghats of India over 14 years (1989–2002). These spatial data on fire occurrence were integrated with maps of vegetation types found in the MWLS to examine fire conditions in each. We calculated the average fire-return interval for each of the vegetation types individually and for the MWLS as a whole. Using vegetation data from the larger Nilgiri Biosphere Reserve and the entire Western Ghats region, we conservatively estimated fire-frequency information for these larger regions. Because the MWLS does not contain tropical evergreen or montane forests, we were unable to estimate fire conditions in these forest types, which represent 31% of all Western Ghats vegetation cover. For the MWLS, all vegetation types had average fire-return intervals of <7 years, and the sanctuary as a whole had a fire-return interval of 3.3 years. Compared with a 13-year MWLS fire data set from 1909–1921, this represents a threefold increase in fire frequency over the last 80 years. We estimated average fire-return intervals of roughly 5 years for both the larger Nilgiri Biosphere Reserve and the entire Western Ghats region. Given other recent reports, the estimated fire frequencies for the Western Ghats forests outside protected reserves are conservative. We conclude that the current fire regime of the Western Ghats poses a severe and persistent conservation threat to forests both within and outside protected reserves.     

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.     

Assessing the risk of ignition in the Russian far east within a modeling framework of fire threat.

The forests of high biological importance in the Russian Far East (RFE) have been experiencing increasing pressure from growing demands for natural resources under the changing economy of post-Soviet Russia. This pressure is further amplified by the rising threat of large and catastrophic fire occurrence, which threatens both the resources and the economic potential of the region. In this paper we introduce a conceptual Fire Threat Model (FTM) and use it to provide quantitative assessment of the risk of ignition in the Russian Far East. The remotely sensed data driven FTM is aimed at evaluating potential wildland fire occurrence and its impact and recovery potential for a given resource. This model is intended for use by resource managers to assist in assessing current levels of fire threat to a given resource, projecting the changes in fire threat under changing climate and land use, and evaluating the efficiency of various management approaches aimed at minimizing the fire impact. Risk of ignition (one of the major uncertainties within fire threat modeling) was analyzed using the MODIS active fire product. The risk of ignition in the RFE is shown to be highly variable in spatial and temporal domains. However, the number of ignition points is not directly proportional to the amount of fire occurrence in the area. Fire ignitions in the RFE are strongly linked to anthropogenic activity (transportation routes, settlements, and land use). An increase in the number of fire ignitions during summer months could be attributed to (1) disruption of the summer monsoons and subsequent changes in fire weather and (2) an increase in natural sources of fire ignitions.     

Modeling mammal response to fire based on species’ traits

Fire has shaped ecological communities worldwide for millennia, but impacts of fire on individual species are often poorly understood. We performed a meta-analysis to predict which traits, habitat, or study variables and fire characteristics affect how mammal species respond to fire. We modeled effect sizes of measures of population abundance or occupancy as a function of various combinations of these traits and variables with phylogenetic least squares regression. Nine of 115 modeled species (7.83%) returned statistically significant effect sizes, suggesting most mammals are resilient to fire. The top-ranked model predicted a negative impact of fire on species with lower reproductive rates, regardless of fire type (estimate = –0.68), a positive impact of burrowing in prescribed fires (estimate = 1.46) but not wildfires, and a positive impact of average fire return interval for wildfires (estimate = 0.93) but not prescribed fires. If a species’ International Union for Conservation of Nature Red List assessment includes fire as a known or possible threat, the species was predicted to respond negatively to wildfire relative to prescribed fire (estimate = –2.84). These findings provide evidence of experts’ abilities to predict whether fire is a threat to a mammal species and the ability of managers to meet the needs of fire-threatened species through prescribed fire. Where empirical data are lacking, our methods provide a basis for predicting mammal responses to fire and thus can guide conservation actions or interventions in species or communities.     

Assessing spatial uncertainty of the Portuguese fire risk through direct sequential simulation

Forest fires have a significant economic, social, and environmental impact in Portugal. For that its fire risk was assessed through Bayes Formalism, where the main component of the risk of fire was assessed by the conditional probability of fire I(u,t) given a class of the daily severity rating (DSR) for a specific period of time—P[I(u,t)|R(u,t)]. The evaluation of this a posterior probability, P[I(u,t)|R(u,t)], was based on the update of marginal local probability of fire in each chosen region u (Durão, 2006).DSR values were used to calculate fire's risk, taking into account historical data, I(s,t), in a given region s, and also to define DSR's local thresholds in order to have P [I(u,t)|R(u,t)] ≥ 0.65.In this paper we characterize these posterior probabilities using direct sequential simulation models (DSS models) to obtain the spatial distribution of these probabilities over the entire Portugal, in order to assess the risk of fire and associated spatial uncertainty. Local probability density functions (pdfs) and spatial uncertainty are evaluated by a set of equiprobable simulated images of these posterior probabilities.Results are presented and discussed for the Portuguese fire seasons of the 2-year period, 2003-2004. The conditional probabilities reproduced reasonably well what was officially published for the studied fire seasons. We expect that a better understanding of both spatial and temporal patterns of fire in Portugal together with uncertainty measures constitutes an important tool for managers, helping to improve the effectiveness of fire prevention, detection and fire fighting resources allocation in critical social and environmental areas.