Rising wildfire risk to houses in the United States, especially in grasslands and shrublands.

Wildfire risks to homes are increasing, especially in the wildland-urban interface (WUI), where wildland vegetation and houses are in close proximity. Notably, we found that more houses are exposed to and destroyed by grassland and shrubland fires than by forest fires in the United States. Destruction was more likely in forest fires, but they burned less WUI. The number of houses within wildfire perimeters has doubled since the 1990s because of both housing growth (47% of additionally exposed houses) and more burned area (53%). Most exposed houses were in the WUI, which grew substantially during the 2010s (2.6 million new WUI houses), albeit not as rapidly as before. Any WUI growth increases wildfire risk to houses though, and more fires increase the risk to existing WUI houses.

The global wildland-urban interface.

The wildland-urban interface (WUI) is where buildings and wildland vegetation meet or intermingle1,2. It is where human-environmental conflicts and risks can be concentrated, including the loss of houses and lives to wildfire, habitat loss and fragmentation and the spread of zoonotic diseases3. However, a global analysis of the WUI has been lacking. Here, we present a global map of the 2020 WUI at 10 m resolution using a globally consistent and validated approach based on remote sensing-derived datasets of building area4 and wildland vegetation5. We show that the WUI is a global phenomenon, identify many previously undocumented WUI hotspots and highlight the wide range of population density, land cover types and biomass levels in different parts of the global WUI. The WUI covers only 4.7% of the land surface but is home to nearly half its population (3.5 billion). The WUI is especially widespread in Europe (15% of the land area) and the temperate broadleaf and mixed forests biome (18%). Of all people living near 2003-2020 wildfires (0.4 billion), two thirds have their home in the WUI, most of them in Africa (150 million). Given that wildfire activity is predicted to increase because of climate change in many regions6, there is a need to understand housing growth and vegetation patterns as drivers of WUI change.

The wildland-urban interface in the United States based on 125 million building locations.

The wildland-urban interface (WUI) is the focus of many important land management issues, such as wildfire, habitat fragmentation, invasive species, and human-wildlife conflicts. Wildfire is an especially critical issue, because housing growth in the WUI increases wildfire ignitions and the number of homes at risk. Identifying the WUI is important for assessing and mitigating impacts of development on wildlands and for protecting homes from natural hazards, but data on housing development for large areas are often coarse. We created new WUI maps for the conterminous United States based on 125 million individual building locations, offering higher spatial precision compared to existing maps based on U.S. census housing data. Building point locations were based on a building footprint data set from Microsoft. We classified WUI across the conterminous United States at 30-m resolution using a circular neighborhood mapping algorithm with a variable radius to determine thresholds of housing density and vegetation cover. We used our maps to (1) determine the total area of the WUI and number of buildings included, (2) assess the sensitivity of WUI area included and spatial pattern of WUI maps to choice of neighborhood size, (3) assess regional differences between building-based WUI maps and census-based WUI maps, and (4) determine how building location accuracy affected WUI map accuracy. Our building-based WUI maps identified 5.6%-18.8% of the conterminous United States as being in the WUI, with larger neighborhoods increasing WUI area but excluding isolated building clusters. Building-based maps identified more WUI area relative to census-based maps for all but the smallest neighborhoods, particularly in the north-central states, and large differences were attributable to high numbers of non-housing structures in rural areas. Overall WUI classification accuracy was 98.0%. For wildfire risk mapping and for general purposes, WUI maps based on the 500-m neighborhood represent the original Federal Register definition of the WUI; these maps include clusters of buildings in and adjacent to wildlands and exclude remote, isolated buildings. Our approach for mapping the WUI offers flexibility and high spatial detail and can be widely applied to take advantage of the growing availability of high-resolution building footprint data sets and classification methods.

Tracking rates of postfire conifer regeneration vs. deciduous vegetation recovery across the western United States.

Postfire shifts in vegetation composition will have broad ecological impacts. However, information characterizing postfire recovery patterns and their drivers are lacking over large spatial extents. In this analysis, we used Landsat imagery collected when snow cover (SCS) was present, in combination with growing season (GS) imagery, to distinguish evergreen vegetation from deciduous vegetation. We sought to (1) characterize patterns in the rate of postfire, dual-season Normalized Difference Vegetation Index (NDVI) across the region, (2) relate remotely sensed patterns to field-measured patterns of re-vegetation, and (3) identify seasonally specific drivers of postfire rates of NDVI recovery. Rates of postfire NDVI recovery were calculated for both the GS and SCS for more than 12,500 burned points across the western United States. Points were partitioned into faster and slower rates of NDVI recovery using thresholds derived from field plot data (n = 230) and their associated rates of NDVI recovery. We found plots with conifer saplings had significantly higher SCS NDVI recovery rates relative to plots without conifer saplings, while plots with ≥50% grass/forbs/shrubs cover had significantly higher GS NDVI recovery rates relative to plots with <50%. GS rates of NDVI recovery were best predicted by burn severity and anomalies in postfire maximum temperature. SCS NDVI recovery rates were best explained by aridity and growing degree days. This study is the most extensive effort, to date, to track postfire forest recovery across the western United States. Isolating patterns and drivers of evergreen recovery from deciduous recovery will enable improved characterization of forest ecological condition across large spatial scales.

Estimating burn severity and carbon emissions from a historic megafire in boreal forests of China.

Wildfires, especially those of large size, worsen air quality and alter the carbon cycle through combustion of large quantities of biomass and release of carbon into the atmosphere. The Black Dragon fire, which occurred in 1987 in the boreal forests of China is among the top five of such megafires ever recorded in the world. With over 30 years of accumulation of data and availability of new greenhouse gas emission accounting methods, carbon emissions from this megafire can now be estimated with improved precision and greater spatial resolution. To do this, we combined field and remote sensing data to map four burn severity classes and calculated combustion efficiency in terms of the biomass immediately consumed in the fire. Results of the study showed that 1.30 million hectares burned and 52% of that area burned with high severity. The emitted carbon dioxide equivalents (CO2e), accounted for approximately 10% of total fossil fuel emissions from China in 1987, along with CO (2%-3% of annual anthropogenic CO emissions from China) and non-methane hydrocarbons (NMHC) contributing to the atmospheric pollutants. Our study provides an important basis for carbon emission estimation and understanding the impacts of megafires.

Rapid growth of the US wildland-urban interface raises wildfire risk.

The wildland-urban interface (WUI) is the area where houses and wildland vegetation meet or intermingle, and where wildfire problems are most pronounced. Here we report that the WUI in the United States grew rapidly from 1990 to 2010 in terms of both number of new houses (from 30.8 to 43.4 million; 41% growth) and land area (from 581,000 to 770,000 km2; 33% growth), making it the fastest-growing land use type in the conterminous United States. The vast majority of new WUI areas were the result of new housing (97%), not related to an increase in wildland vegetation. Within the perimeter of recent wildfires (1990-2015), there were 286,000 houses in 2010, compared with 177,000 in 1990. Furthermore, WUI growth often results in more wildfire ignitions, putting more lives and houses at risk. Wildfire problems will not abate if recent housing growth trends continue.

High resolution mapping of development in the wildland-urban interface using object based image extraction.

The wildland-urban interface (WUI), the area where human development encroaches on undeveloped land, is expanding throughout the western United States resulting in increased wildfire risk to homes and communities. Although census based mapping efforts have provided insights into the pattern of development and expansion of the WUI at regional and national scales, these approaches do not provide sufficient detail for fine-scale fire and emergency management planning, which requires maps of individual building locations. Although fine-scale maps of the WUI have been developed, they are often limited in their spatial extent, have unknown accuracies and biases, and are costly to update over time. In this paper we assess a semi-automated Object Based Image Analysis (OBIA) approach that utilizes 4-band multispectral National Aerial Image Program (NAIP) imagery for the detection of individual buildings within the WUI. We evaluate this approach by comparing the accuracy and overall quality of extracted buildings to a building footprint control dataset. In addition, we assessed the effects of buffer distance, topographic conditions, and building characteristics on the accuracy and quality of building extraction. The overall accuracy and quality of our approach was positively related to buffer distance, with accuracies ranging from 50 to 95% for buffer distances from 0 to 100 m. Our results also indicate that building detection was sensitive to building size, with smaller outbuildings (footprints less than 75 m2) having detection rates below 80% and larger residential buildings having detection rates above 90%. These findings demonstrate that this approach can successfully identify buildings in the WUI in diverse landscapes while achieving high accuracies at buffer distances appropriate for most fire management applications while overcoming cost and time constraints associated with traditional approaches. This study is unique in that it evaluates the ability of an OBIA approach to extract highly detailed data on building locations in a WUI setting.

Projecting the spatiotemporal carbon dynamics of the Greater Yellowstone Ecosystem from 2006 to 2050.

BACKGROUND: Climate change and the concurrent change in wildfire events and land use comprehensively affect carbon dynamics in both spatial and temporal dimensions. The purpose of this study was to project the spatial and temporal aspects of carbon storage in the Greater Yellowstone Ecosystem (GYE) under these changes from 2006 to 2050. We selected three emission scenarios and produced simulations with the CENTURY model using three General Circulation Models (GCMs) for each scenario. We also incorporated projected land use change and fire occurrence into the carbon accounting. RESULTS: The three GCMs showed increases in maximum and minimum temperature, but precipitation projections varied among GCMs. Total ecosystem carbon increased steadily from 7,942 gC/m2 in 2006 to 10,234 gC/m2 in 2050 with an annual rate increase of 53 gC/m2/year. About 56.6% and 27% of the increasing rate was attributed to total live carbon and total soil carbon, respectively. Net Primary Production (NPP) increased slightly from 260 gC/m2/year in 2006 to 310 gC/m2/year in 2050 with an annual rate increase of 1.22 gC/m2/year. Forest clear-cutting and fires resulted in direct carbon removal; however, the rate was low at 2.44 gC/m2/year during 2006-2050. The area of clear-cutting and wildfires in the GYE would account for 10.87% of total forested area during 2006-2050, but the predictive simulations demonstrated different spatial distributions in national forests and national parks. CONCLUSIONS: The GYE is a carbon sink during 2006-2050. The capability of vegetation is almost double that of soil in terms of sequestering extra carbon. Clear-cutting and wildfires in GYE will affect 10.87% of total forested area, but direct carbon removal from clear-cutting and fires is 109.6 gC/m2, which accounts for only 1.2% of the mean ecosystem carbon level of 9,056 gC/m2, and thus is not significant.

Human and biophysical influences on fire occurrence in the United States.

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

Increasing development in the surroundings of U.S. National Park Service holdings jeopardizes park effectiveness.

Protected areas are cornerstones of biodiversity conservation, but they are in danger of becoming islands in a sea of human dominated landscapes. Our question was if protected areas may even foster development in their surroundings because they provide amenities that attract development, thus causing the isolation of the ecosystems they were designed to protect. Our study analyzed historic aerial photographs and topographical maps to reconstruct road development and building growth within and around Indiana Dunes and Pictured Rocks National Lakeshores in the U.S. Great Lakes region from 1938 to 2005, and to estimate the effects of park creation in 1966 on changes in landscape patterns. Historic U.S. census housing density data were used as a baseline to compare observed changes to. Our results showed that park establishment was effective in reducing and stopping the fragmenting impact of development within park boundaries. However, increased amenity levels following park establishment led to enhanced development in the surroundings of both parks. In the extreme case of Indiana Dunes, building density outside the park increased from 45 to 200buildings/km(2) and road density almost doubled from 3.6 to 6.6km/km(2) from 1938 to 2005. Development rates of change were much higher than in the broader landscape, particularly after park establishment. The potential amenity effect was up to 9500 new buildings in the 3.2-km zone around Indiana Dunes between 1966 and 2005. For Pictured Rocks the absolute effect was smaller but up to 70% of the observed building growth was potentially due to amenity effects. Our findings highlight the need for conservation planning at broader scales, incorporating areas beyond the boundaries of protected areas.

Housing growth in and near United States protected areas limits their conservation value.

Protected areas are crucial for biodiversity conservation because they provide safe havens for species threatened by land-use change and resulting habitat loss. However, protected areas are only effective when they stop habitat loss within their boundaries, and are connected via corridors to other wild areas. The effectiveness of protected areas is threatened by development; however, the extent of this threat is unknown. We compiled spatially-detailed housing growth data from 1940 to 2030, and quantified growth for each wilderness area, national park, and national forest in the conterminous United States. Our findings show that housing development in the United States may severely limit the ability of protected areas to function as a modern "Noah's Ark." Between 1940 and 2000, 28 million housing units were built within 50 km of protected areas, and 940,000 were built within national forests. Housing growth rates during the 1990s within 1 km of protected areas (20% per decade) outpaced the national average (13%). If long-term trends continue, another 17 million housing units will be built within 50 km of protected areas by 2030 (1 million within 1 km), greatly diminishing their conservation value. US protected areas are increasingly isolated, housing development in their surroundings is decreasing their effective size, and national forests are even threatened by habitat loss within their administrative boundaries. Protected areas in the United States are thus threatened similarly to those in developing countries. However, housing growth poses the main threat to protected areas in the United States whereas deforestation is the main threat in developing countries.

Paying the extinction debt in southern Wisconsin forest understories.

The lack of long-term baseline data restricts the ability to measure changes in biological diversity directly and to determine its cause. This hampers conservation efforts and limits testing of basic tenets of ecology and conservation biology. We used a historical baseline survey to track shifts in the abundance and distribution of 296 native understory species across 82 sites over 55 years in the fragmented forests of southern Wisconsin. We resurveyed stands first surveyed in the early 1950s to evaluate the influence of patch size and surrounding land cover on shifts in native plant richness and heterogeneity and to evaluate changes in the relative importance of local site conditions versus the surrounding landscape context as drivers of community composition and structure. Larger forests and those with more surrounding forest cover lost fewer species, were more likely to recruit new species, and had lower rates of homogenization than smaller forests in more fragmented landscapes. Nearby urbanization further reduced both alpha and beta understory diversity. Similarly, understory composition depended strongly on local site conditions in the original survey but only weakly reflected the surrounding landscape composition. By 2005, however, the relative importance of these factors had reversed such that the surrounding landscape structure is now a much better predictor of understory composition than are local site conditions. Collectively, these results strongly support the idea that larger intact habitat patches and landscapes better sustain native species diversity and demonstrate that humans play an increasingly important role in driving patterns of native species diversity and community composition.

Housing growth, forests, and public lands in Northern Wisconsin from 1940 to 2000.

Rural, forested areas throughout the United States are experiencing strong housing growth with potentially detrimental impacts on the environment. In this paper, we quantify housing growth in Northern Wisconsin over the last sixty years to determine if growth rates were higher near public lands, which may represent an important recreational amenity. We used data from the U.S. Census to produce decadal housing density estimates, "backcasts," from 1940 to 2000 for northern Wisconsin to examine "rural sprawl" in northern Wisconsin and its relationship to forested areas and public lands. We integrated housing density estimates with the 1992/1993 National Land Cover Dataset to examine the relationship between rural sprawl and land cover, especially forests. Between 1940 and 2000, private land with <2 housing units/km(2) decreased from 47% to 21% of the total landscape. Most importantly, housing growth was concentrated along the boundaries of public lands. In 14 of the 19 counties that we studied, housing growth rates within 1 km of a public land boundary exceeded growth rates in the remainder of the county, and three of the five counties that did not exhibit this pattern, were the ones with the least amount of public land. Future growth can be expected in areas with abundant natural amenities, highlighting the critical need for additional research and effective natural resource management and regional planning to address these challenges.

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.

Patterns of houses and habitat loss from 1937 to 1999 in northern Wisconsin, USA.

Rural America is witnessing widespread housing development, which is to the detriment of the environment. It has been suggested to cluster houses so that their disturbance zones overlap and thus cause less habitat loss than is the case for dispersed development. Clustering houses makes intuitive sense, but few empirical studies have quantified the spatial pattern of houses in real landscapes, assessed changes in their patterns over time, and quantified the resulting habitat loss. We addressed three basic questions: (1) What are the spatial patterns of houses and how do they change over time; (2) How much habitat is lost due to houses, and how is this affected by spatial pattern of houses; and (3) What type of habitat is most affected by housing development. We mapped 27 419 houses from aerial photos for five time periods in 17 townships in northern Wisconsin and calculated the terrestrial land area remaining after buffering each house using 100- and 500-m disturbance zones. The number of houses increased by 353% between 1937 and 1999. Ripley's K test showed that houses were significantly clustered at all time periods and at all scales. Due to the clustering, the rate at which habitat was lost (176% and 55% for 100- and 500-m buffers, respectively) was substantially lower than housing growth rates, and most land area was undisturbed (95% and 61% for 100-m and 500-m buffers, respectively). Houses were strongly clustered within 100 m of lakes. Habitat loss was lowest in wetlands but reached up to 60% in deciduous forests. Our results are encouraging in that clustered development is common in northern Wisconsin, and habitat loss is thus limited. However, the concentration of development along lakeshores causes concern, because these may be critical habitats for many species. Conservation goals can only be met if policies promote clustered development and simultaneously steer development away from sensitive ecosystems.

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.

Road development, housing growth, and landscape fragmentation in northern Wisconsin: 1937-1999.

Roads remove habitat, alter adjacent areas, and interrupt and redirect ecological flows. They subdivide wildlife populations, foster invasive species spread, change the hydrologic network, and increase human use of adjacent areas. At broad scales, these impacts cumulate and define landscape patterns. The goal of this study was to improve our understanding of the dynamics of road networks over time, and their effects on landscape patterns, and identify significant relationships between road changes and other land-use changes. We mapped roads from aerial photographs from five dates between 1937 and 1999 in 17 townships in predominantly forested landscapes in northern Wisconsin, U.S.A. Patch-level landscape metrics were calculated on terrestrial area outside of a 15-m road-effect zone. We used generalized least-squares regression models to relate changes in road density and landscape pattern to concurrent changes in housing density. Rates of change and relationships were compared among three ecological regions. Our results showed substantial increases in both road density and landscape fragmentation during the study period. Road density more than doubled, and median, mean, and largest patch size were reduced by a factor of four, while patch shape became more regular. Increases in road density varied significantly among ecological subsections and were positively related to increases in housing density. Fragmentation was largely driven by increases in road density, but housing density had a significantly positive relationship with largest patch area and patch shape. Without protection of roadless areas, our results suggest road development is likely to continue in the future, even in areas where road construction is constrained by the physical environment. Recognizing the dynamic nature of road networks is important for understanding and predicting their ecological impacts over time and understanding where other types of development are likely to occur in the future. Historical perspectives of development can provide guidance in prioritizing management efforts to defragment landscapes and mitigate the ecological impacts of past road development.