The relationship between annual variation in area burned and seasonal temperatures and precipitation was investigated for the major climate divisions in California. Historical analyses showed marked differences in fires on montane and foothill landscapes. Based on roughly a century of data, there are five important lessons on fire–climate relationships in California: (1) seasonal variations in temperature appear to have had minimal influence on area burned in the lower elevation, mostly non-forested, landscapes; (2) temperature has been a significant factor in controlling fire activity in higher elevation montane forests, but this varied greatly with season – winter and autumn temperatures showed no significant effect, whereas spring and summer temperatures were important determinants of area burned; (3) current season precipitation has been a strong controller of fire activity in forests, with drier years resulting in greater area burned on most United States Forest Service (USFS) lands in the state, but the effect of current-year precipitation was decidedly less on lower elevation California Department of Forestry and Fire Protection lands; (4) in largely grass-dominated foothills and valleys the magnitude of prior-year rainfall was positively tied to area burned in the following year, and we hypothesise that this is tied to greater fuel volume in the year following high rainfall. In the southern part of the state this effect has become stronger in recent decades and this likely is due to accelerated type conversion from shrubland to grassland in the latter part of the 20th century; (5) the strongest fire–climate models were on USFS lands in the Sierra Nevada Mountains, and these explained 42–52% of the variation in area burned; however, the models changed over time, with winter and spring precipitation being the primary drivers in the first half of the 20th century, but replaced by spring and summer temperatures after 1960.
Fire activity has increased in western US aridland ecosystems due to increased human-caused ignitions and the expansion of flammable exotic grasses. Because many desert plants are not adapted to fire, increased fire activity may have long-lasting ecological impacts on native vegetation and the wildlife that depend on it. Given the heterogeneity across aridland ecosystems, it is important to understand how trends and drivers of fire vary, so management can be customized accordingly. We examined historical trends and quantified the relative importance of and interactions among multiple drivers of fire patterns across five aridland ecoregions in southeastern California from 1970 to 2010. Fire frequency increased across all ecoregions for the first couple decades, and declined or plateaued since the 1990s; but area burned continued to increase in some regions. The relative importance of anthropogenic and biophysical drivers varied across ecoregions, with both direct and indirect influences on fire. Anthropogenic variables were equally important as biophysical variables, but some contributed indirectly, presumably via their influence on annual grass distribution and abundance. Grass burned disproportionately more than other cover types, suggesting that addressing exotics may be the key to fire management and conservation in much of the area
Growing human and ecological costs due to increasing wildfire are an urgent concern in policy and management, particularly given projections of worsening fire conditions under climate change. Thus, understanding the relationship between climatic variation and fire activity is a critically important scientific question. Different factors limit fire behavior in different places and times, but most fire-climate analyses are conducted across broad spatial extents that mask geographical variation. This could result in overly broad or inappropriate management and policy decisions that neglect to account for regionally specific or other important factors driving fire activity. We developed statistical models relating seasonal temperature and precipitation variables to historical annual fire activity for 37 different regions across the continental United States and asked whether and how fire-climate relationships vary geographically, and why climate is more important in some regions than in others. Climatic variation played a significant role in explaining annual fire activity in some regions, but the relative importance of seasonal temperature or precipitation, in addition to the overall importance of climate, varied substantially depending on geographical context. Human presence was the primary reason that climate explained less fire activity in some regions than in others. That is, where human presence was more prominent, climate was less important. This means that humans may not only influence fire regimes but their presence can actually override, or swamp out, the effect of climate. Thus, geographical context as well as human influence should be considered alongside climate in national wildfire policy and management.
The low-elevation chaparral shrublands of southern California have long been occupied and modified by humans, but the magnitude and extent of human impact has dramatically increased since the early 1900s. As population growth started to boom in the 1940s, the primary form of habitat conversion transitioned from agriculture to urban and residential development. Now, urban growth is the primary contributor, directly and indirectly, to loss and fragmentation of chaparral landscapes. Different patterns and arrangements of housing development confer different ecological impacts. We found wide variation in the changing extent and pattern of development across the seven counties in the region. Substantial growth in lower-density exurban development has been associated with high frequency of human-caused ignitions as well as the expansion of highly flammable non-native annual grasses. Combined, increases in fire ignitions and the extent of grassland can lead to a positive feedback cycle in which grass promotes fire and shortens the fire-return interval, ultimately extirpating shrub species that are not adapted to short fire intervals. An overlay of a 1930s vegetation map with maps of contemporary vegetation showed a consistent trend of chaparral decline and conversion to sage scrub or grassland. In addition, those areas type-converted to grassland had the highest fire frequency over the latter part of the twentieth century. Thus, a continuing trend of population growth and urban expansion may continue to threaten the extent and intactness of remaining shrubland dominated landscapes. Interactions among housing development, fire ignitions, non-native grasses, roads, and vehicle emissions make fire prevention a complex endeavor. However, land use planning that targets the root cause of conversion, exurban sprawl, could address all of these threats simultaneously.
Understanding where and how fire patterns may change is critical for management and policy decision-making. To map future fire patterns, statistical correlative models are typically developed, which associate observed fire locations with recent climate maps, and are then applied to maps of future climate projections. A potential source of uncertainty is the common omission of static or dynamic vegetation as predictor variables. We therefore assessed the sensitivity of future fire projections to different combinations of vegetation maps used as explanatory variables in a statistically based fire modeling framework. We compared models without vegetation to models that incorporated static vegetation maps and that included output from a dynamic vegetation model that imposed three scenarios of fire and one scenario of land use change. We mapped projected future probability of all and large fires (> = 40 ha) under two climate scenarios in a heterogeneous study area spanning a large elevational gradient in the Sierra Nevada, California, USA. Results showed high model sensitivity to the treatment of vegetation as a predictor variable, particularly for models of large fire probability and for models accounting for wildfire effects on vegetation, which lowered future fire probability. Some scenarios resulted in opposite directional trends in the extent and probability of future fire, which could have serious implications for policy and management resource allocation. Model sensitivity resulted from high relative importance of vegetation variables in the baseline models and from large predicted changes in vegetation, particularly when simulating wildfire. Although statistical fire models often omit vegetation due to uncertainty, model sensitivity demonstrated here suggests a need to account for that uncertainty. Coupling statistical and processed based models may be a promising approach to reflect a more plausible range of scenarios.
To develop effective long-term strategies, natural resource managers need to account for the projected effects of climate change as well as the uncertainty inherent in those projec- tions. Vegetation models are one important source of projected climate effects. We explore results and associated uncertainties from the MC2 Dynamic Global Vegetation Model for the Pacific Northwest west of the Cascade crest. We compare model results for vegetation cover and carbon dynamics over the period 1895–2100 assuming: 1) unlimited wildfire igni- tions versus stochastic ignitions, 2) no fire, and 3) a moderate CO2 fertilization effect versus no CO2 fertilization effect. Carbon stocks decline in all scenarios, except without fire and with a moderate CO2 fertilization effect. The greatest carbon stock loss, approximately 23% of historical levels, occurs with unlimited ignitions and no CO2 fertilization effect. With sto- chastic ignitions and a CO2 fertilization effect, carbon stocks are more stable than with unlimited ignitions. For all scenarios, the dominant vegetation type shifts from pure conifer to mixed forest, indicating that vegetation cover change is driven solely by climate and that significant mortality and vegetation shifts are likely through the 21st century regardless of fire regime changes.
Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, either using well-founded empirical relationships or process-based models with good predictive skill. A large variety of models exist today and it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project – FireMIP, an international project to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we summarise the current state-of-the-art in fire regime modelling and model evaluation, and outline what lessons may be learned from FireMIP.
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.
Wildfire is globally an important ecological disturbance affecting biochemical cycles and vegetation composition, but also puts people and their homes at risk. Suppressing wildfires has detrimental ecological effects and can promote larger and more intense wildfires when fuels accumulate, which increases the threat to buildings in the wildland–urban interface (WUI). Yet, when wildfires occur, typically only a small proportion of the buildings within the fire perimeter are lost, and the question is what determines which buildings burn. Our goal was to examine which factors are related to building loss when awildfire occurs throughout the United States. We were particularly interested in the relative roles of vegetation, topography, and the spatial arrangement of buildings, and how their respective roles vary among ecoregions. We analyzed all fires that occurred within the conterminous United States from 2000 to 2010 and digitized which buildings were lost and which survived according to Google Earth historical imagery. We modeled the occurrence as well as the percentage of buildings lost within clusters using logistic and linear regression. Overall, variables related to topography and the spatial arrangement of buildings were more frequently present in the best 20 regression models than vegetation-related variables. In other words, specific locations in the landscape have a higher fire risk, and certain development patterns can exacerbate that risk. Fire policies and prevention efforts focused on vegetation management are important, but insufficient to solve current wildfire problems. Furthermore, the factors associated with building loss varied considerably among ecoregions suggesting that fire policy applied uniformly across the United States will not work equally well in all regions and that efforts to adapt communities to wildfires must be regionally tailored.
Although wildfire plays an important role in maintaining biodiversity in many ecosystems, fire management to protect human assets is often carried out by different agencies than those tasked for conserving biodiversity. In fact, fire risk reduction and biodiversity conservation are often viewed as competing objectives. Here we explored the role of management through private land conservation and asked whether we could identify private land acquisition strategies that fulfill the mutual objectives of biodiversity conservation and fire risk reduction, or whether the maximization of one objective comes at a detriment to the other. Using a fixed budget and number of homes slated for development, we simulated 20 years of housing growth under alternative conservation selection strategies, and then projected the mean risk of fires destroying structures and the area and configuration of important habitat types in San Diego County, California, USA. We found clear differences in both fire risk projections and biodiversity impacts based on the way conservation lands are prioritized for selection, but these differences were split between two distinct groupings. If no conservation lands were purchased, or if purchases were prioritized based on cost or likelihood of development, both the projected fire risk and biodiversity impacts were much higher than if conservation lands were purchased in areas with high fire hazard or high species richness. Thus, conserving land focused on either of the two objectives resulted in nearly equivalent mutual benefits for both. These benefits not only resulted from preventing development in sensitive areas, but they were also due to the different housing patterns and arrangements that occurred as development was displaced from those areas. Although biodiversity conflicts may still arise using other fire management strategies, this study shows that mutual objectives can be attained through land-use planning in this region. These results likely generalize to any place where high species richness overlaps with hazardous wildland vegetation.