Wildfire ignition-distribution modelling: a comparative study in the Huron-Manistee National Forest, Michigan, USA

Abstract. Wildfire ignition distribution models are powerful tools for predicting the probability of ignitions across broad areas, and identifying their drivers. Several approaches have been used for ignition-distribution modelling, yet the performance of different model types has not been compared. This is unfortunate, given that conceptually similar speciesdistribution models exhibit pronounced differences among model types. Therefore, our goal was to compare the predictive performance, variable importance and the spatial patterns of predicted ignition-probabilities of three ignition-distribution model types: one parametric, statistical model (Generalised Linear Models, GLM) and two machine-learning algorithms (Random Forests and Maximum Entropy, Maxent). We parameterised the models using 16 years of ignitions data and environmental data for the Huron-Manistee National Forest in Michigan, USA. Random Forests and Maxent had slightly better prediction accuracies than did GLM, but model fit was similar for all three. Variables related to human population and development were the best predictors of wildfire ignition locations in all models (although variable rankings differed slightly), along with elevation. However, despite similar model performance and variables, the map of ignition probabilities generated by Maxent was markedly different from those of the two other models. We thus suggest that when accurate predictions are desired, the outcomes of different model types should be compared, or alternatively combined, to produce ensemble predictions

Housing Arrangement and Location Determine the Likelihood of Housing Loss Due to Wildfire

Surging wildfires across the globe are contributing to escalating residential losses and have major social, economic, and ecological consequences. The highest losses in the U.S. occur in southern California, where nearly 1000 homes per year have been destroyed by wildfires since 2000. Wildfire risk reduction efforts focus primarily on fuel reduction and, to a lesser degree, on house characteristics and homeowner responsibility. However, the extent to which land use planning could alleviate wildfire risk has been largely missing from the debate despite large numbers of homes being placed in the most hazardous parts of the landscape. Our goal was to examine how housing location and arrangement affects the likelihood that a home will be lost when a wildfire occurs. We developed an extensive geographic dataset of structure locations, including more than 5500 structures that were destroyed or damaged by wildfire since 2001, and identified the main contributors to property loss in two extensive, fire-prone regions in southern California. The arrangement and location of structures strongly affected their susceptibility to wildfire, with property loss most likely at low to intermediate structure densities and in areas with a history of frequent fire. Rates of structure loss were higher when structures were surrounded by wildland vegetation, but were generally higher in herbaceous fuel types than in higher fuel-volume woody types. Empirically based maps developed using housing pattern and location performed better in distinguishing hazardous from non-hazardous areas than maps based on fuel distribution. The strong importance of housing arrangement and location indicate that land use planning may be a critical tool for reducing fire risk, but it will require reliable delineations of the most hazardous locations

Anthromes dispaying evidence of weekly cycles in active fire data cover 70% of the global land surface

Across the globe, human activities have been gaining importance relatively to climate and ecology as the main controls on fire regimes and consequently human activity became an important driver of the frequency, extent and intensity of vegetation burning worldwide. Our objective in the present study is to look for weekly cycles in vegetation fire activity at global scale as evidence of human agency, relying on the original MODIS active fire detections at 1 km spatial resolution (MCD14ML) and using novel statistical methodologies to detect significant periodicities in time series data. We tested the hypotheses that global fire activity displays weekly cycles and that the weekday with the fewest fires is Sunday. We also assessed the effect of land use and land cover on weekly fire cycle significance by testing those hypotheses separately for the Villages, Settlements, Croplands, Rangelands, Seminatural, and Wildlands anthromes. Based on a preliminary data analysis of the daily global active fire counts periodogram, we developed an harmonic regression model for the mean function of daily fire activity and assumed a linear model for the de-seasonalized time series. For inference purposes, we used a Bayesian methodology and constructed a simultaneous 95% credible band for the mean function. The hypothesis of a Sunday weekly minimum was directly investigated by computing the probabilities that the mean functions of every weekday (Monday to Saturday) are inside the credible band corresponding to mean Sunday fire activity. Since these probabilities are small, there is statistical evidence of significantly fewer fires on Sunday than on the other days of the week. Cropland, rangeland, and seminatural anthromes, which cover 70% of the global land area and account for 94% of the active fires analysed, display weekly cycles in fire activity. Due to lower land management intensity and less strict control over fire size and duration, weekly cycles in Rangelands and Seminatural anthromes, which jointly account for 53.46% of all fires, although statistically significant are weaker than those detected in Croplandsinfo:eu-repo/semantics/publishedVersio

Fire and biodiversity in the Anthropocene

The workshop leading to this paper was funded by the Centre Tecnològic Forestal de Catalunya and the ARC Centre of Excellence for Environmental Decisions. L.T.K. was supported by a Victorian Postdoctoral Research Fellowship (Victorian Government), a Centenary Fellowship (University of Melbourne), and an Australian Research Council Linkage Project Grant (LP150100765). A.R. was supported by the Xunta de Galicia (Postdoctoral Fellowship ED481B2016/084-0) and the Foundation for Science and Technology under the FirESmart project (PCIF/MOG/0083/2017). A.L.S. was supported by a Marie Skłodowska-Curie Individual Fellowship (746191) under the European Union Horizon 2020 Programme for Research and Innovation. L.R. was supported by the Australian Government’s National Environmental Science Program through the Threatened Species Recovery Hub. L.B. was partially supported by the Spanish Government through the INMODES (CGL2014-59742-C2-2-R) and the ERANET-SUMFORESTS project FutureBioEcon (PCIN-2017-052). This research was supported in part by the U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station.BACKGROUND Fire has shaped the diversity of life on Earth for millions of years. Variation in fire regimes continues to be a source of biodiversity across the globe, and many plants, animals, and ecosystems depend on particular temporal and spatial patterns of fire. Although people have been using fire to modify environments for millennia, the combined effects of human activities are now changing patterns of fire at a global scale—to the detriment of human society, biodiversity, and ecosystems. These changes pose a global challenge for understanding how to sustain biodiversity in a new era of fire. We synthesize how changes in fire activity are threatening species with extinction across the globe, highlight forward-looking methods for predicting the combined effects of human drivers and fire on biodiversity, and foreshadow emerging actions and strategies that could revolutionize how society manages fire for biodiversity in the Anthropocene. ADVANCES Our synthesis shows that interactions with anthropogenic drivers such as global climate change, land use, and biotic invasions are transforming fire activity and its impacts on biodiversity. More than 4400 terrestrial and freshwater species from a wide range of taxa and habitats face threats associated with modified fire regimes. Many species are threatened by an increase in fire frequency or intensity, but exclusion of fire in ecosystems that need it can also be harmful. The prominent role of human activity in shaping global ecosystems is the hallmark of the Anthropocene and sets the context in which models and actions must be developed. Advances in predictive modeling deliver new opportunities to couple fire and biodiversity data and to link them with forecasts of multiple drivers including drought, invasive plants, and urban growth. Making these connections also provides an opportunity for new actions that could revolutionize how society manages fire. Emerging actions include reintroduction of mammals that reduce fuels, green fire breaks comprising low-flammability plants, strategically letting wildfires burn under the right conditions, managed evolution of populations aided by new genomics tools, and deployment of rapid response teams to protect biodiversity assets. Indigenous fire stewardship and reinstatement of cultural burning in a modern context will enhance biodiversity and human well-being in many regions of the world. At the same time, international efforts to reduce greenhouse gas emissions are crucial to reduce the risk of extreme fire events that contribute to declines in biodiversity. OUTLOOK Conservation of Earth’s biological diversity will be achieved only by recognition of and response to the critical role of fire in shaping ecosystems. Global changes in fire regimes will continue to amplify interactions between anthropogenic drivers and create difficult trade-offs between environmental and social objectives. Scientific input will be crucial for navigating major decisions about novel and changing ecosystems. Strategic collection of data on fire, biodiversity, and socioeconomic variables will be essential for developing models to capture the feedbacks, tipping points, and regime shifts characteristic of the Anthropocene. New partnerships are also needed to meet the challenges ahead. At the local and regional scale, getting more of the “right” type of fire in landscapes that need it requires new alliances and networks to build and apply knowledge. At the national and global scale, biodiversity conservation will benefit from greater integration of fire into national biodiversity strategies and action plans and in the implementation of international agreements and initiatives such as the UN Convention on Biological Diversity. Placing the increasingly important role of people at the forefront of efforts to understand and adapt to changes in fire regimes is central to these endeavors.PostprintPeer reviewe

Land use planning and wildfire: Development policies influence future probability of housing loss

Abstract Increasing numbers of homes are being destroyed by wildfire in the wildland-urban interface. With projections of climate change and housing growth potentially exacerbating the threat of wildfire to homes and property, effective fire-risk reduction alternatives are needed as part of a comprehensive fire management plan. Land use planning represents a shift in traditional thinking from trying to eliminate wildfires, or even increasing resilience to them, toward avoiding exposure to them through the informed placement of new residential structures. For land use planning to be effective, it needs to be based on solid understanding of where and how to locate and arrange new homes. We simulated three scenarios of future residential development and projected landscape-level wildfire risk to residential structures in a rapidly urbanizing, fireprone region in southern California. We based all future development on an econometric subdivision model, but we varied the emphasis of subdivision decision-making based on three broad and common growth types: infill, expansion, and leapfrog. Simulation results showed that decision-making based on these growth types, when applied locally for subdivision of individual parcels, produced substantial landscape-level differences in pattern, location, and extent of development. These differences in development, in turn, affected the area and proportion of structures at risk from burning in wildfires. Scenarios with lower housing density and larger numbers of small, isolated clusters of development, i.e., resulting from leapfrog development, were generally predicted to have the highest predicted fire risk to the largest proportion of structures in the study area, and infill development was predicted to have the lowest risk. These results suggest that land use planning should be considered an important component to fire risk management and that consistently applied policies based on residential pattern may provide substantial benefits for future risk reduction

HAXPES study of Sn core levels and their plasmon loss features

Hard X-ray Photoelectron spectra have been recorded for elemental Sn. Electron loss features, prominent in all core level spectra of the metal, are analyzed at several photo energies for the 3p core level. For higher photoelectron kinetic energies the intensity of the plasmonic features follows a simple exponential law. The data and models presented here will aid the modeling of spectra where tin is present and especially if its spectrum overlaps with those from other sources

The impact of antecedent fire area on burned area in southern California coastal ecosystems

Frequent wildfire disasters in southern California highlight the need for risk reduction strategies for the region, of which fuel reduction via prescribed burning is one option. However, there is no consensus about the effectiveness of prescribed fire in reducing the area of wildfire. Here, we use 29 years of historical fire mapping to quantify the relationship between annual wildfire area and antecedent fire area in predominantly shrub and grassland fuels in seven southern California counties, controlling for annual variation in weather patterns. This method has been used elsewhere to measure leverage: the reduction in wildfire area resulting from one unit of prescribed fire treatment. We found little evidence for a leverage effect (leverage = zero). Specifically our results showed no evidence that wildfire area was negatively influenced by previous fires, and only weak relationships with weather variables rainfall and Santa Ana wind occurrences, which were variables included to control for inter-annual variation. We conclude that this is because only 2% of the vegetation burns each year and so wildfires rarely encounter burned patches and chaparral shrublands can carry a fire within 1 or 2 years after previous fire. Prescribed burning is unlikely to have much influence on fire regimes in this area, though targeted treatment at the urban interface may be effective at providing defensible space for protecting assets. These results fit an emerging global model of fire leverage which position California at the bottom end of a continuum, with tropical savannas at the top (leverage = 1: direct replacement of wildfire by prescribed fire) and Australian eucalypt forests in the middle (leverage ∼ 0.25)