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In this article the authors examine the impact of recent immigration on rates of serious property crime across communities in Austin, Texas. The greater Austin foreign-born population has increased by more than 580 percent since 1980, and Austin is considered a "preemerging" immigrant gateway city to the United States. The changing population dynamics in Austin provide an excellent opportunity to study the effect of recent immigration on crime in a target destination for recent immigrants. Although interest in the relationship between violent crime and immigration to new locales is evidenced by recent studies that show less favorable outcomes for Latinos in new destinations, little attention has been directed to the relationship of recent immigration with serious property crime in new destinations. Negative binomial regression models with corrections for spatial autocorrelation indicate that recent immigration is not associated with an increased rate of burglary, larceny, or motor vehicle theft once important structural predictors of crime are controlled for. © 2013 by Pacific Sociological Association. All rights reserved.

Residential development is one of the most intensive and widespread land uses in the United States, with substantial environmental impacts, including changes in forest cover. However, the relationships between forest cover and residential development are complex. Contemporary forest cover reflects multiple factors, including housing density, time since development, historical land cover, and land management since development. We investigated how forest cover varies with housing density, housing age, and household income over a range of development intensities, in six ecoregions within New York State, Wisconsin, and Colorado. We find areas with residential development do retain important forest resources: across landscapes they are typically more forested than areas that remain undeveloped. However, forest cover consistently had a negative, inverse relationship with housing density, across study areas. Relationships between forest cover and housing age and household income were less common and often restricted to only portions of a given region, according to geographically weighted regression analyses. A better understanding of how forest cover varies with residential development, outside of the typically studied urban areas, will be essential to maintaining ecosystem function and services in residential landscapes., (Published by Elsevier Ltd.)

Public lands are typically established in recognition of their unique ecological value, yet both ecological and social values of public lands change over time, along with human distribution and land use. These transformations are evident even in developed countries with long histories of public land management, such as the United States. The 20th Century saw dramatic changes in the American population, in distribution and in racial and ethnic diversity, leading to new challenges and new roles for public lands. Our goal with this paper is to review changing demographics and implications for terrestrial protected areas in the U.S. We overview the fundamentals of population change and data, review past trends in population change and housing growth and their impacts on public lands, and then analyze the most recent decade of demographic change (2000-2010) relative to public lands. Discussions of demographic change and public lands commonly focus on the rural West, but we show that the South is also experiencing substantial change in rural areas with public lands, including Hispanic population growth. We identify those places, rural and urban, where demographic change (2000-2010), including diversification and housing growth, coincide with public lands. Understanding the current trends and long-term demographic context for recent changes in populations can help land managers and conservation scientists mitigate the effects of residential development near public lands, serve a more diverse population, and anticipate future population changes., (Copyright © 2018. Published by Elsevier Ltd.)

As people encroach increasingly on natural areas, one question is how this affects avian biodiversity. The answer to this is partly scale-dependent. At broad scales, human populations and biodiversity concentrate in the same areas and are positively associated, but at local scales people and biodiversity are negatively associated with biodiversity. We investigated whether there is also a systematic temporal trend in the relationship between bird biodiversity and housing development. We used linear regression to examine associations between forest bird species richness and housing growth in the conterminous United States over 30 years. Our data sources were the North American Breeding Bird Survey and the 2000 decennial U.S. Census. In the 9 largest forested ecoregions, housing density increased continually over time. Across the conterminous United States, the association between bird species richness and housing density was positive for virtually all guilds except ground nesting birds. We found a systematic trajectory of declining bird species richness as housing increased through time. In more recently developed ecoregions, where housing density was still low, the association with bird species richness was neutral or positive. In ecoregions that were developed earlier and where housing density was highest, the association of housing density with bird species richness for most guilds was negative and grew stronger with advancing decades. We propose that in general the relationship between human settlement and biodiversity over time unfolds as a 2-phase process. The first phase is apparently innocuous; associations are positive due to coincidence of low-density housing with high biodiversity. The second phase is highly detrimental to biodiversity, and increases in housing density are associated with biodiversity losses. The long-term effect on biodiversity depends on the final housing density. This general pattern can help unify our understanding of the relationship of human encroachment and biodiversity response., (© 2014 Society for Conservation Biology.)

The wildland urban interface (WUI) delineates the areas where wildland fire hazard most directly impacts human communities and threatens lives and property, and where houses exert the strongest influence on the natural environment. Housing data are a major problem for WUI mapping. When housing data are zonal, the concept of a WUI neighborhood can be captured easily in a density measure, but variations in zone (census block) size and shape introduce bias. Other housing data are points, so zonal issues are avoided, but the neighborhood character of the WUI is lost if houses are evaluated individually. Our goal was to develop a consistent method to map the WUI that is able to determine where neighborhoods (or clusters of houses) exist, using just housing location and wildland fuel data. We used structure and vegetation maps and a moving window analysis, with various window sizes representing neighborhood sizes, to calculate the neighborhood density of both houses and wildland vegetation. Mapping four distinct areas (in WI, MI, CA and CO) the method resulted in amounts of WUI comparable to those of zonal mapping, but with greater precision. We conclude that this hybrid method is a useful alternative to zonal mapping from the neighborhood to the landscape scale, and results in maps that are better suited to operational fire management (e.g., fuels reduction) needs, while maintaining consistency with conceptual and U.S. policy-specific WUI definitions., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

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.

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.

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.

Patterns of association between humans and biodiversity typically show positive, negative, or negative quadratic relationships and can be described by 3 hypotheses: biologically rich areas that support high human population densities co-occur with areas of high biodiversity (productivity); biodiversity decreases monotonically with increasing human activities (ecosystem stress); and biodiversity peaks at intermediate levels of human influence (intermediate disturbance). To test these hypotheses, we compared anthropogenic land cover and housing units, as indices of human influence, with bird species richness and abundance across the Midwestern United States. We modeled richness of native birds with 12 candidate models of land cover and housing to evaluate the empirical evidence. To assess which species were responsible for observed variation in richness, we repeated our model-selection analysis with relative abundance of each native species as the response and then asked whether natural-history traits were associated with positive, negative, or mixed responses. Native avian richness was highest where anthropogenic land cover was lowest and housing units were intermediate based on model-averaged predictions among a confidence set of candidate models. Eighty-three of 132 species showed some pattern of association with our measures of human influence. Of these species approximately 40% were negatively associated, approximately 6% were positively associated, and approximately 7% showed evidence of an intermediate relationship with human influence measures. Natural-history traits were not closely related to the direction of the relationship between abundance and human influence. Nevertheless, pooling species that exhibited any relationship with human influence and comparing them with unrelated species indicated they were significantly smaller, nested closer to the ground, had shorter incubation and fledging times, and tended to be altricial. Our results support the ecosystem-stress hypothesis for the majority of individual species and for overall species diversity when focusing on anthropogenic land cover. Nevertheless, the great variability in housing units across the land-cover gradient indicates that an intermediate-disturbance relationship is also supported. Our findings suggest preemptive conservation action should be taken, whereby areas with little anthropogenic land cover are given conservation priority. Nevertheless, conservation action should not be limited to pristine landscapes because our results showed that native avian richness and the relative abundance of many species peaked at intermediate housing densities and levels of anthropogenic land cover.

In the United States, housing density has substantially increased in and adjacent to forests. Our goal in this study was to identify how housing density and human populations are associated with avian diversity. We compared these associations to those between landscape pattern and avian diversity, and we examined how these associations vary across the conterminous forested United States. Using data from the North American Breeding Bird Survey, the U.S. Census, and the National Land Cover Database, we focused on forest and woodland bird communities and conducted our analysis at multiple levels of model specificity, first using a coarse-thematic resolution (basic models), then using a larger number of fine-thematic resolution variables (refined models). We found that housing development was associated with forest bird species richness in all forested ecoregions of the conterminous United States. However, there were important differences among ecoregions. In the basic models, housing density accounted for < 5% of variance in avian species richness. In refined models, 85% of models included housing density and/or residential land cover as significant variables. The strongest guild response was demonstrated in the Adirondack-New England ecoregion, where 29% of variation in richness of the permanent resident guild was associated with housing density. Model improvements due to regional stratification were most pronounced for cavity nesters and short-distance migrants, suggesting that these guilds may be especially sensitive to regional processes. The varying patterns of association between avian richness and attributes associated with landscape structure suggested that landscape context was an important mediating factor affecting how biodiversity responds to landscape changes. Our analysis suggested that simple, broadly applicable, land use recommendations cannot be derived from our results. Rather, anticipating future avian response to land use intensification (or reversion to native vegetation) has to be conditioned on the current landscape context and the species group of interest. Our results show that housing density and residential land cover were significant predictors of forest bird species richness, and their prediction strengths are likely to increase as development continues.

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.

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.

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.

As fertility differences in the United States diminish, population redistribution trends are increasingly dependent on migration. This research used newly developed county-level age-specific net migration estimates for the 1990s, supplemented with longitudinal age-specific migration data spanning the prior 40 years, to ascertain whether there are clear longitudinal trends in age-specific net migration and to determine if there is spatial clustering in the migration patterns. The analysis confirmed the continuation into the 1990s of distinct net migration "signature patterns" for most types of counties, although there was temporal variation in the overall volume of migration across the five decades. A spatial autocorrelation analysis revealed large, geographically contiguous regions of net in-migration (in particular, Florida and the Southwest) and geographically contiguous regions of net out-migration (the Great Plains, in particular) that persisted over time. Yet the patterns of spatial concentration and fragmentation over time in these migration data demonstrate the relevance of this "neighborhood" approach to understanding spatiotemporal change in migration.