The study arrives at a moment when wildfire has become an inescapable feature of Southern California life. Los Angeles sits in a landscape where fire ecology predates human settlement by a millennium; chaparral ecosystems historically burned roughly every thirty years, with extended droughts allowing dead vegetation to accumulate as fuel. Fire, in turn, rejuvenates chaparral seeds that inhibit germination until after a blaze, returning nutrients to the soil and enabling new growth. That natural cycle now collides with millions of residents, and the catastrophic fires of recent years have pushed questions about disaster and social order into public debate. Popular narratives often assume that disasters unleash looting and lawlessness, but decades of criminological research on hurricanes, floods, and tornadoes tell a more complicated story, and wildfires have remained a conspicuous gap in that literature.

To close that gap, the researchers assembled tract-level data for the City of Los Angeles and identified seven major wildfires that occurred inside the municipal boundaries during the 2016 to 2022 window. Their statistical strategy centered on random-effects negative binomial regression models, a choice tailored to the structure of crime data. Crime counts in small geographic units are overdispersed, meaning their variance exceeds their mean, and a negative binomial framework accommodates that distribution far better than ordinary linear regression. The random-effects specification, meanwhile, accounts for unobserved, stable characteristics of each census tract, such as entrenched disadvantage or built environment features, that could otherwise confound the estimated relationship between fire exposure and crime.

The team measured wildfire exposure in two distinct ways, and that distinction turned out to be analytically decisive. The first measure identified census tracts that experienced direct wildfire damage, that is, tracts where the fire itself burned. The second captured proximity, identifying tracts located within a quarter mile of burned areas even if no fire touched them directly. Separating these two forms of exposure allowed the authors to test whether the crime effects of wildfire are confined to physically damaged neighborhoods or spill over into surrounding communities, a question with direct implications for how police and emergency managers allocate resources after a disaster.

The results paint a nuanced picture. Census tracts that experienced direct wildfire damage reported significantly lower levels of property crime. Violent crime was also marginally lower in those directly burned tracts, though the evidence there was weaker. When the researchers accounted for proximity to wildfire damage, however, the direct-damage effect on property crime was no longer statistically significant. What proved most robust was the proximity effect: tracts within a quarter mile of burned areas reported significantly lower levels of both violent and property crime. In other words, the strongest crime-suppressing signal appeared not in the neighborhoods the flames consumed, but in the neighborhoods standing just outside them.

The authors interpret these findings through the lens of two foundational criminological frameworks. Social disorganization theory holds that neighborhood crime is shaped by the capacity of local communities to exercise informal social control, a capacity rooted in stable networks, shared trust, and collective efficacy. Disasters can disrupt or reorganize those networks in unpredictable ways. Research after Hurricane Katrina, for example, documented both crime displacement and, in some domains, strengthened collective resources among repopulating residents. The routine activities approach offers a complementary mechanism: crime requires a motivated offender, a suitable target, and the absence of a capable guardian converging in time and space. Wildfires radically alter that convergence calculus. Evacuations empty neighborhoods of suitable targets, closed roads and fire-perimeter checkpoints supply guardianship, and burned or damaged structures simply cease to be burglarizable.

The proximity finding fits neatly into this routine-activities logic. A quarter-mile buffer around a burned area is precisely the zone where emergency access controls, evacuation orders, utility shutoffs, and heavy first-responder presence are most intense, even when the homes themselves remain intact. Fewer people on the street, restricted vehicular movement, and a saturated official guardianship presence can suppress both opportunistic property offenses and interpersonal violence. At the same time, the social disorganization perspective suggests that shared threat experiences can galvanize neighborly cohesion, with residents monitoring one another’s properties and coordinating informally during and after evacuations. The study cannot adjudicate between these mechanisms, but the spatial pattern it documents, with effects strongest near rather than within fire perimeters, is consistent with guardianship and mobility explanations operating at the edge of disaster zones.

The findings also connect to a broader and rapidly growing research program on environment, green space, and crime. Recent work has linked urban greenspace to lower crime risk across hundreds of major U.S. cities, examined park size and community safety, and used quasi-experimental designs to test whether urban greenways such as the Atlanta Beltline reduce offending. Related studies have explored how drought conditions relate to violent crime trends in California counties and how natural hazards reshape spatiotemporal crime patterns nationally. The Los Angeles wildfire analysis adds a distinctive dimension to this literature: rather than a gradual environmental amenity, wildfire is an acute, spatially bounded shock, and its crime effects appear to radiate outward from the burn scar in measurable ways.

For practitioners, the implications are concrete. If crime genuinely declines in and around burned neighborhoods, then post-fire policing strategies premised on looting panics may be misdirected, diverting officers from communities where they are actually needed and potentially exposing evacuated areas to over-policing. Emergency response planning, similarly, could incorporate the finding that a quarter-mile buffer around fire perimeters functions as a distinct criminological zone, one where the priorities may be public safety and recovery support rather than crime suppression. For neighborhood recovery, the results hint that the social fabric of fire-adjacent communities may be more resilient than disaster folklore assumes, though the authors caution that their analysis captures associations over a defined study period rather than the full arc of long-term recovery.

The authors are explicit about the limits of their design and the directions it opens. Their data cover seven wildfires within one city over seven years, and census tracts, while useful units of neighborhood analysis, aggregate individual behavior into coarse spatial bins. The proximity threshold of a quarter mile is one plausible buffer among many, and future work could test whether the effect decays smoothly with distance or exhibits spatial spillovers of the kind modeled in wildfire risk mitigation research. Longer follow-up periods could reveal whether suppressed crime rebounds as neighborhoods rebuild, whether reconstruction and gentrification dynamics, of the kind documented after the 1994 Northridge earthquake in Los Angeles, reshape local crime trajectories, and whether the patterns hold in other fire-prone regions. As climate change intensifies fire regimes across the American West, understanding how wildfires reshape not only landscapes but also the social order of the neighborhoods that survive them is becoming an urgent scientific question, and this study provides one of the clearest spatial maps yet of where that reshaping begins.

Subject of Research: The association between neighborhood wildfire exposure and violent and property crime patterns in Los Angeles

Article Title: We Didn’t Start the Fire: How Neighborhood Crime Patterns in the City of Los Angeles Were Associated with Wildfires

Article References: Barton, M. S., Valasik, M., LaPointe, R., & Lopez, S. (2026). We Didn’t Start the Fire: How Neighborhood Crime Patterns in the City of Los Angeles Were Associated with Wildfires. American Journal of Criminal Justice. https://doi.org/10.1007/s12103-026-09955-7

Image Credits: AI Generated

DOI: 10.1007/s12103-026-09955-7

Keywords: wildfires, crime, Los Angeles, violent crime, property crime, social disorganization theory, routine activities approach, disasters, criminology, neighborhoods, negative binomial regression, emergency response

Xiaoshuang Iris Luo of the University of Akron analyzed official violent and property crime data from 297,199 street segments across 12 U.S. cities between 2010 and 2018, drawing on the National Incident Crime Study compiled by the Irvine Laboratory for the Study of Space and Crime. The cities—ranging from Los Angeles and Seattle to Scottsdale, Akron, and Diamond Bar—were selected through stratified random sampling to form a balanced design across three dimensions: city size, population growth, and employment presence. This deliberate variation is the study’s methodological heart. Where nearly all prior micro-place research examined a single large city, Luo’s design allows the effects of neighborhood characteristics to be compared systematically across urban environments rather than inferred from convenience-selected cases.

The analytical engine of the study is group-based trajectory modeling, a statistical technique that clusters individual units—in this case, street segments—into groups sharing similar longitudinal patterns of crime. Rather than assigning segments to groups and then modeling the assignments separately, a common two-step practice that treats group membership as known and understates uncertainty, Luo estimated trajectory parameters and predictors of group membership jointly in a single likelihood. Each segment’s contribution is weighted by its full posterior probability distribution across groups, so classification uncertainty propagates into the estimated effects. Violent crime was modeled with a logit specification because roughly 90 percent of segments recorded no incidents, while property crime used a censored normal specification to handle skewed distributions.

The trajectory solutions revealed five distinct patterns for each crime type. For violent crime, 54.4 percent of street segments were crime-free throughout the nine-year period, 33.4 percent followed a low stable path, and only small minorities followed medium-high decreasing, medium decreasing-increasing, or high stable-decreasing trajectories. Property crime was more widely dispersed: 28.3 percent of segments were crime-free, 37.5 percent showed minimal stable activity, and 1.4 percent sat on a high stable trajectory. The low-crime groups dominate both outcomes, echoing the well-established law of crime concentration at places, yet the aggregate stability conceals substantial street-to-street heterogeneity even among adjacent segments.

Turning to explanations, the study confirms the central prediction of social disorganization theory: concentrated disadvantage—a composite of poverty, unemployment, single-parent households, and the absence of educational and economic resources—is strongly associated with elevated crime trajectories. A one standard deviation increase in disadvantage nearly doubles the odds that a street segment follows a low stable violent crime trajectory rather than remaining crime free, and more than triples the odds of following the highest violent crime trajectory. Consumer-facing employment, capturing the retail and service establishments that generate routine activity and draw visitors, showed among the strongest and most consistent gradients of all, with the odds of high crime membership rising dramatically as consumer-facing employment increased.

But the study’s most striking findings emerge when city context enters the picture. The criminogenic effect of disadvantage is not uniform across urban environments. For violent crime, a one standard deviation increase in disadvantage roughly doubles the odds of high crime trajectory membership in small cities, but increases those odds more than fivefold in medium cities and more than threefold in large ones. For property crime the contrast is sharper still: the association actually reverses direction in small cities, where greater disadvantage is modestly associated with lower odds of crime-active trajectories, while remaining clearly criminogenic in medium and large cities. Disadvantage, in other words, is not a fixed risk factor but one whose consequences depend on the scale of the surrounding urban environment.

Residential stability tells an equally context-dependent story. In small cities, stability is strongly protective: higher stability substantially reduces the odds that street segments fall into any crime-active violent crime trajectory, with the protective effect growing stronger as trajectories become more severe. In medium and large cities, this protective association is largely absent, and for property crime it reverses, with stability positively associated with membership in the lower crime trajectories. City growth conditions these relationships as well. Concentrated disadvantage predicts severe violent crime trajectories more strongly in stagnant cities than in growing ones, while residential stability is more protective against medium and high violent crime trajectories in growing cities. Growing cities may benefit from economic prosperity, new investment, and an influx of residents and businesses that curb violent crime, whereas stagnant cities face persistent disinvestment, declining municipal capacity, and limited resources for prevention.

These results carry a substantial implication: the neighborhood-crime relationships documented in the large-city literature may describe a special case rather than a general process. Social disorganization theory holds that structural disadvantage weakens informal social control, but the capacity for such control also depends on the density of local institutions, the responsiveness of municipal services, and the stability of the surrounding economy—all of which vary across cities. In a small city with an intact institutional fabric, disadvantage may carry different consequences than the same level of disadvantage in a large city where residents are more anonymous and criminal opportunities more abundant. Similarly, residential stability in a large city may reflect immobility and constrained housing options rather than the attachment and investment that generate protective social ties.

The study is candid about its limitations. The 12 cities were drawn through stratified random sampling from 108 eligible cities in the NICS database, ensuring balanced variation across the dimensions of interest but not constituting a simple random sample of U.S. cities, and the sample skews somewhat toward Southern California. Neighborhood measures are drawn from 2010 and treated as static over the nine-year observation period, so the design captures the association between baseline conditions and subsequent trajectories but cannot speak to whether changing neighborhood conditions produce changing crime patterns. Spatial dependence among nearby segments is not explicitly modeled, and collective efficacy—the shared willingness of residents to intervene that is central to contemporary social disorganization theory—requires survey data unavailable at the street-segment level across 12 cities, leaving the connecting mechanism unobserved.

Even with those caveats, the findings point toward a clear policy conclusion: one-size-fits-all crime prevention is unlikely to work. Efforts to reduce concentrated disadvantage may yield larger returns in medium and large cities, while programs that sustain residential stability appear most consequential in smaller and growing ones. Place-based interventions calibrated to a single metropolitan context cannot simply be transplanted elsewhere. As micro-level crime research moves beyond its traditional focus on large, well-resourced cities, the message of this study is that the street corner and the city around it form a single interacting system—and understanding crime where most Americans actually live requires studying both at once.

Subject of Research: Longitudinal trajectories of violent and property crime at street segments across varied U.S. city contexts

Article Title: Micro-Level Crime Trajectories Across Urban Contexts: A Multi-City Longitudinal Study in the U.S.

Article References: Luo, X. I. (2026). Micro-Level Crime Trajectories Across Urban Contexts: A Multi-City Longitudinal Study in the U.S.. American Journal of Criminal Justice. https://doi.org/10.1007/s12103-026-09952-w

Image Credits: AI Generated

DOI: 10.1007/s12103-026-09952-w

Keywords: crime trajectories, street segments, social disorganization theory, concentrated disadvantage, residential stability, city context, group-based trajectory modeling, crime concentration, urban criminology, property crime, violent crime, crime prevention