Volker C. Radeloff

The wildland-urban interface in the United States

The wildland-urban interface (WUI) is the area where houses meet or intermingle with undeveloped wildland vegetation. The WUI is thus a focal area for human-environment conflicts, such as the destruction of homes by wildfires, habitat fragmentation, introduction of exotic species, and biodiversity decline. Our goal was to conduct a spatially detailed assessment of the WUI across the United States to provide a framework for scientific inquiries into housing growth effects on the environment and to inform both national policymakers and local land managers about the WUI and associated issues. The WUI in the conterminous United States covers 719 156 km? (9% of land area) and contains 44.8 million housing units (39% of all houses). WUI areas are particularly widespread in the eastern United States, reaching a maximum of 72% of land area in Connecticut. California has the highest number of WUI housing units (5.1 million). The extent of the WUI highlights the need for ecological principles in land-use planning as well as sprawl-limiting policies to adequately address both wildfire threats and conservation problems.

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.

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.

Projected land-use change impacts on ecosystem services in the United States

Significance Land-use change affects the provision of ecosystem services and wildlife habitat. We project land-use change from 2001 to 2051 for the contiguous United States under two scenarios reflecting continuation of 1990s trends and high crop demand more reflective of the recent past. These scenarios result in large differences in land-use trajectories that generate increases in carbon storage, timber production, food production from increased yields (even with declines in cropland area), and >10% decreases in habitat for one-quarter of modeled species. We analyzed three policy alternatives that provide incentives to maintain and expand forest cover, conserve natural habitats, and limit urban sprawl. Policy interventions need to be aggressive to significantly alter underlying land-use trends and shift the trajectory of ecosystem service provision. Providing food, timber, energy, housing, and other goods and services, while maintaining ecosystem functions and biodiversity that underpin their sustainable supply, is one of the great challenges of our time. Understanding the drivers of land-use change and how policies can alter land-use change will be critical to meeting this challenge. Here we project land-use change in the contiguous United States to 2051 under two plausible baseline trajectories of economic conditions to illustrate how differences in underlying market forces can have large impacts on land-use with cascading effects on ecosystem services and wildlife habitat. We project a large increase in croplands (28.2 million ha) under a scenario with high crop demand mirroring conditions starting in 2007, compared with a loss of cropland (11.2 million ha) mirroring conditions in the 1990s. Projected land-use changes result in increases in carbon storage, timber production, food production from increased yields, and >10% decreases in habitat for 25% of modeled species. We also analyze policy alternatives designed to encourage forest cover and natural landscapes and reduce urban expansion. Although these policy scenarios modify baseline land-use patterns, they do not reverse powerful underlying trends. Policy interventions need to be aggressive to significantly alter underlying land-use change trends and shift the trajectory of ecosystem service provision.

Predicting spatial patterns of fire on a southern California landscape

Humans influence the frequency and spatial pattern of fire and contribute to altered fire regimes, but fuel loading is often the only factor considered when planning management activities to reduce fire hazard. Understanding both the human and biophysical landscape characteristics that explain how fire patterns vary should help to identify where fire is most likely to threaten values at risk. We used human and biophysical explanatory variables to model and map the spatial patterns of both fire ignitions and fire frequency in the Santa Monica Mountains, a human-dominated southern California landscape. Most fires in the study area are caused by humans, and our results showed that fire ignition patterns were strongly influenced by human variables. In particular, ignitions were most likely to occur close to roads, trails, and housing development but were also related to vegetation type. In contrast, biophysical variables related to climate and terrain (January temperature, transformed aspect, elevation, and slope) explained most of the variation in fire frequency. Although most ignitions occur close to human infrastructure, fires were more likely to spread when located farther from urban development. How far fires spread was ultimately related to biophysical variables, and the largest fires in southern California occurred as a function of wind speed, topography, and vegetation type. Overlaying predictive maps of fire ignitions and fire frequency may be useful for identifying high-risk areas that can be targeted for fire management actions.

Phenological differences in Tasseled Cap indices improve deciduous forest classification

Remote sensing needs to clarify the strengths of different methods so they can be consistently applied in forest management and ecology. Both the use of phenological information in satellite imagery and the use of vegetation indices have independently improved classifications of north temperate forests. Combining these sources of information in change detection has been effective for land cover classifications at the continental scale based on Advanced Very High Resolution Radiometer (AVHRR) imagery. Our objective is to test if using vegetation indices and change analysis of multiseasonal imagery can also improve the classification accuracy of deciduous forests at the landscape scale. We used Landsat Thematic Mapper (TM) scenes that corresponded to Populus spp. leaf-on and Quercus spp. leaf-off (May), peak summer (August), Acer spp. peak color (September), Acer spp. and Populus spp. leaf-off (October). Input data files derived from the imagery were: (1) TM Bands 3, 4, and 5 from all dates; (2) Normalized Difference Vegetation Index (NDVI) from all dates; (3) Tasseled Cap brightness, greenness, and wetness (BGW) from all dates; (4) difference in TM Bands 3, 4, and 5 from one date to the next; (5) difference in NDVI from one date to the next; and (6) difference in BGW from one date to the next. The overall kappa statistics (KHAT) for the aforementioned classifications of deciduous genera were 0.48, 0.36, 0.33, 0.38, 0.26, 0.43, respectively. The highest accuracies occurred from TM Bands 3, 4, and 5 (61.0% for deciduous genera, 67.8% for all classes) or from the difference in BGW (61.0% for deciduous genera, 67.8% for all classes). However, the difference in Tasseled Cap classification more accurately separated deciduous shrubs and harvested stands from closed canopy forest. Our results indicate that phenological change of forest is most accurately captured by combining image differencing and Tasseled Cap indices.

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 worlds 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.

Detecting Jack Pine Budworm Defoliation Using Spectral Mixture Analysis: Separating Effects from Determinants

Abstract Insect defoliation is a major disturbance force in forested ecosystems. Monitoring outbreaks, and estimating the areas affected, is therefore important for both forest managers and forest ecologists. The objective of our study was to classify jack pine budworm defoliation levels in Landsat TM imagery recorded previous to and during the 1990–1995 outbreak in our 450,000 ha study area in northwestern Wisconsin (USA). Many previous studies correlated insect defoliation and remotely sensed imagery with moderate to good success, but it often remained unclear if actual defoliation effects or other forest attributes correlated with defoliation were detected. For example, a larger deciduous component in mixed jack pine stands will limit budworm populations and thereby defoliation. The deciduous component in stands is a determining factor for insect defoliation, whereas needle discoloration and tree mortality are their effect. We used pre-outbreak Landsat TM data (1987) to identify determining factors for jack pine budworm population levels and peak-outbreak imagery (1993) for detecting actual defoliation. Our satellite data were atmospherically corrected using a radiative transfer model (5S). Spectral mixture analysis was performed using spectrometer measurements of jack pine needles and bark as representations of surface materials (“endmembers”). The explanatory power of the resulting fraction images was evaluated using jack pine budworm population data collected at 33 sampling points. Near-infrared reflectance (NIR) increased in defoliated stands between 1987 and 1993, but single date NIR in each year was negatively correlated with budworm levels in 1993 ( r =−0.69 and −0.47). This was because hardwood trees within jack pine stands caused higher NIR reflectance but limited jack pine budworm populations. The 10% NIR difference between pure and mixed jack pine stands outweighed the 3–5% increase in NIR due to defoliation and necessitated stratification of the satellite data by tree species. Spectral mixture analysis performed on pure jack pine stands resulted in a strong negative correlation between the 1993 green needle fraction and the 1993 budworm population data ( r =−0.94). This study was, to our knowledge, the first that applied spectral mixture analysis for forest damage detection, and also the first to use insect population measurements as independent field data. These methods, and the separation of determinants and effects of jack pine budworm defoliation, enabled us to detect actual defoliation with high accuracy.

Wildland-urban interface housing growth during the 1990s in California, Oregon, and Washington

In the present study, we examine housing growth in California, Oregon, and Washington in the wildland-urban interface (WUI), the area where homes and other structures abut or intermingle with wildland vegetation. We combine housing density information from the 1990 and 2000 USA censuses with land cover information from the 1992/93 National Land Cover Dataset to demarcate the location and extent of the WUI and its growth, both in terms of area and number of housing units during the 1990s. We overlay the WUI with coarse-scale fire regime condition class information to evaluate implications for wildland fire management. During the 1990s, WUI area in the three-state region increased by 5218 km 2 (10.9%) to nearly 53 000 km 2 and the number of housing units in the WUI increased over 1 million units (17.6%) and in 2000 encompassed 6.9 million units, 43% of all housing in the region. Over a million new homes were constructed in the WUI, comprising 61% of the new homes constructed in the region. By 2000, there was far more intermix WUI (75% of the WUI area and 64% of the WUI housing units) than interface WUI. Expansion of the WUI accounted for only 13% of WUI housing unit growth and WUI that existed in 1990 encompassed 98% of WUI housing units in 2000. In 2000, there were nearly 1.5 million WUI housing units in areas with 0-35-year fire return intervals and 3.4 million in areas with 35-100+ year fire return intervals. In both these fire regimes, the majority of WUI housing units (66% and 90% respectively) are in areas with a current condition outside the historic range of variability. Housing growth patterns in this three-state region are exacerbating wildland fire problems in the WUI. Any long-term solution to wildland fire issues in the western United States will have to address housing growth patterns. Using a consistent, nationally applicable assessment protocol, the present study reveals the vast extent of WUI in the west coast states and its growth in the 1990s, and provides a foundation for consistent monitoring efforts.

Housing is positively associated with invasive exotic plant species richness in New England, USA.

Understanding the factors related to invasive exotic species distributions at broad spatial scales has important theoretical and management implications, because biological invasions are detrimental to many ecosystem functions and processes. Housing development facilitates invasions by disturbing land cover, introducing nonnative landscaping plants, and facilitating dispersal of propagules along roads. To evaluate relationships between housing and the distribution of invasive exotic plants, we asked (1) how strongly is housing associated with the spatial distribution of invasive exotic plants compared to other anthropogenic and environmental factors; (2) what type of housing pattern is related to the richness of invasive exotic plants; and (3) do invasive plants represent ecological traits associated with specific housing patterns? Using two types of regression analysis (best subset analysis and hierarchical partitioning analysis), we found that invasive exotic plant richness was equally or more strongly related to housing variables than to other human (e.g., mean income and roads) and environmental (e.g., topography and forest cover) variables at the county level across New England. Richness of invasive exotic plants was positively related to area of wildland-urban interface (WUI), low-density residential areas, change in number of housing units between 1940 and 2000, mean income, plant productivity (NDVI), and altitudinal range and rainfall; it was negatively related to forest area and connectivity. Plant life history traits were not strongly related to housing patterns. We expect the number of invasive exotic plants to increase as a result of future housing growth and suggest that housing development be considered a primary factor in plans to manage and monitor invasive exotic plant species.