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Item Leveraging the NEON Airborne Observation Platform for socio-environmental systems research(Wiley, 2021) Ordway, Elsa M.; Elmore, Andrew J.; Kolstoe, Sonja; Quinn, John E.; Swanwick, Rachel; Cattau, Megan; Taillie, Dylan; Guinn, Steven M.; Chadwick, K. Dana; Atkins, Jeff W.; Blake, Rachael E.; Chapman, Melissa; Cobourn, Kelly; Goulden, Tristan; Helmus, Matthew R.; Hondula, Kelly; Hritz, Carrie; Jensen, Jennifer; Julian, Jason P.; Kuwayama, Yusuke; Lulla, Vijay; O’Leary, Donal; Nelson, Donald R.; Ocón, Jonathan P.; Pau, Stephanie; Ponce-Campos, Guillermo E.; Portillo-Quintero, Carlos; Pricope, Narcisa G.; Rivero, Rosanna G.; Schneider, Laura; Steele, Meredith; Tulbure, Mirela G.; Williamson, Matthew A.; Wilson, Cyril; Geography, School of Liberal ArtsDuring the 21st century, human–environment interactions will increasingly expose both systems to risks, but also yield opportunities for improvement as we gain insight into these complex, coupled systems. Human–environment interactions operate over multiple spatial and temporal scales, requiring large data volumes of multi-resolution information for analysis. Climate change, land-use change, urbanization, and wildfires, for example, can affect regions differently depending on ecological and socioeconomic structures. The relative scarcity of data on both humans and natural systems at the relevant extent can be prohibitive when pursuing inquiries into these complex relationships. We explore the value of multitemporal, high-density, and high-resolution LiDAR, imaging spectroscopy, and digital camera data from the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) for Socio-Environmental Systems (SES) research. In addition to providing an overview of NEON AOP datasets and outlining specific applications for addressing SES questions, we highlight current challenges and provide recommendations for the SES research community to improve and expand its use of this platform for SES research. The coordinated, nationwide AOP remote sensing data, collected annually over the next 30 yr, offer exciting opportunities for cross-site analyses and comparison, upscaling metrics derived from LiDAR and hyperspectral datasets across larger spatial extents, and addressing questions across diverse scales. Integrating AOP data with other SES datasets will allow researchers to investigate complex systems and provide urgently needed policy recommendations for socio-environmental challenges. We urge the SES research community to further explore questions and theories in social and economic disciplines that might leverage NEON AOP data.Item Escalating costs of self-injury mortality in the 21st century United States: an interstate observational study(BMC, 2023-02-08) Rockett, Ian R. H.; Ali, Bina; Caine, Eric D.; Shepard, Donald S.; Banerjee, Aniruddha; Nolte, Kurt B.; Connery, Hilary S.; Larkin, G. Luke; Stack, Steven; White, Franklin M. M.; Jia, Haomiao; Cossman, Jeralynn S.; Feinberg, Judith; Stover, Amanda N.; Miller, Ted R.; Geography, School of Liberal ArtsBackground: Estimating the economic costs of self-injury mortality (SIM) can inform health planning and clinical and public health interventions, serve as a basis for their evaluation, and provide the foundation for broadly disseminating evidence-based policies and practices. SIM is operationalized as a composite of all registered suicides at any age, and 80% of drug overdose (intoxication) deaths medicolegally classified as 'accidents,' and 90% of corresponding undetermined (intent) deaths in the age group 15 years and older. It is the long-term practice of the United States (US) Centers for Disease Control and Prevention (CDC) to subsume poisoning (drug and nondrug) deaths under the injury rubric. This study aimed to estimate magnitude and change in SIM and suicide costs in 2019 dollars for the United States (US), including the 50 states and the District of Columbia. Methods: Cost estimates were generated from underlying cause-of-death data for 1999/2000 and 2018/2019 from the US Centers for Disease Control and Prevention's (CDC's) Wide-ranging ONline Data for Epidemiologic Research (WONDER). Estimation utilized the updated version of Medical and Work Loss Cost Estimation Methods for CDC's Web-based Injury Statistics Query and Reporting System (WISQARS). Exposures were medical expenditures, lost work productivity, and future quality of life loss. Main outcome measures were disaggregated, annual-averaged total and per capita costs of SIM and suicide for the nation and states in 1999/2000 and 2018/2019. Results: 40,834 annual-averaged self-injury deaths in 1999/2000 and 101,325 in 2018/2019 were identified. Estimated national costs of SIM rose by 143% from $0.46 trillion to $1.12 trillion. Ratios of quality of life and work losses to medical spending in 2019 US dollars in 2018/2019 were 1,476 and 526, respectively, versus 1,419 and 526 in 1999/2000. Total national suicide costs increased 58%-from $318.6 billion to $502.7 billion. National per capita costs of SIM doubled from $1,638 to $3,413 over the observation period; costs of the suicide component rose from $1,137 to $1,534. States in the top quintile for per capita SIM, those whose cost increases exceeded 152%, concentrated in the Great Lakes, Southeast, Mideast and New England. States in the bottom quintile, those with per capita cost increases below 70%, were located in the Far West, Southwest, Plains, and Rocky Mountain regions. West Virginia exhibited the largest increase at 263% and Nevada the smallest at 22%. Percentage per capita cost increases for suicide were smaller than for SIM. Only the Far West, Southwest and Mideast were not represented in the top quintile, which comprised states with increases of 50% or greater. The bottom quintile comprised states with per capita suicide cost increases below 24%. Regions represented were the Far West, Southeast, Mideast and New England. North Dakota and Nevada occupied the extremes on the cost change continuum at 75% and - 1%, respectively. Conclusion: The scale and surge in the economic costs of SIM to society are large. Federal and state prevention and intervention programs should be financed with a clear understanding of the total costs-fiscal, social, and personal-incurred by deaths due to self-injurious behaviors.Item Association of State Social and Environmental Factors With Rates of Self-injury Mortality and Suicide in the United States(AMA, 2022-02) Rockett, Ian R. H.; Jia, Haomiao; Ali, Bina; Banerjee, Aniruddha; Connery, Hilary S.; Nolte, Kurt B.; Miller, Ted; White, Franklin M. M.; DiGregorio, Bernard D.; Larkin, G. Luke; Stack, Steven; Kõlves, Kairi; McHugh, R. Kathryn; Lulla, Vijay O.; Cossman, Jeralynn; De Leo, Diego; Hendricks, Brian; Nestadt, Paul S.; Berry, James H.; D’Onofrio, Gail; Caine, Eric D.; Geography, School of Liberal ArtsImportance Self-injury mortality (SIM) combines suicides and the preponderance of drug misuse–related overdose fatalities. Identifying social and environmental factors associated with SIM and suicide may inform etiologic understanding and intervention design. Objective To identify factors associated with interstate SIM and suicide rate variation and to assess potential for differential suicide misclassification. Design, Setting, and Participants This cross-sectional study used a partial panel time series with underlying cause-of-death data from 50 US states and the District of Columbia for 1999-2000, 2007-2008, 2013-2014 and 2018-2019. Applying data from the Centers for Disease Control and Prevention, SIM includes all suicides and the preponderance of unintentional and undetermined drug intoxication deaths, reflecting self-harm behaviors. Data were analyzed from February to June 2021. Exposures Exposures included inequity, isolation, demographic characteristics, injury mechanism, health care access, and medicolegal death investigation system type. Main Outcomes and Measures The main outcome, SIM, was assessed using unstandardized regression coefficients of interstate variation associations, identified by the least absolute shrinkage and selection operator; ratios of crude SIM to suicide rates per 100 000 population were assessed for potential differential suicide misclassification. Results A total of 101 325 SIMs were identified, including 74 506 (73.5%) among males and 26 819 (26.5%) among females. SIM to suicide rate ratios trended upwards, with an accelerating increase in overdose fatalities classified as unintentional or undetermined (SIM to suicide rate ratio, 1999-2000: 1.39; 95% CI, 1.38-1.41; 2018-2019: 2.12; 95% CI, 2.11-2.14). Eight states recorded a SIM to suicide rate ratio less than 1.50 in 2018-2019 vs 39 states in 1999-2000. Northeastern states concentrated in the highest category (range, 2.10-6.00); only the West remained unrepresented. Least absolute shrinkage and selection operator identified 8 factors associated with the SIM rate in 2018-2019: centralized medical examiner system (β = 4.362), labor underutilization rate (β = 0.728), manufacturing employment (β = −0.056), homelessness rate (β = −0.125), percentage nonreligious (β = 0.041), non-Hispanic White race and ethnicity (β = 0.087), prescribed opioids for 30 days or more (β = 0.117), and percentage without health insurance (β = −0.013) and 5 factors associated with the suicide rate: percentage male (β = 1.046), military veteran (β = 0.747), rural (β = 0.031), firearm ownership (β = 0.030), and pain reliever misuse (β = 1.131). Conclusions and Relevance These findings suggest that SIM rates were associated with modifiable, upstream factors. Although embedded in SIM, suicide unexpectedly deviated in proposed social and environmental determinants. Heterogeneity in medicolegal death investigation processes and data assurance needs further characterization, with the goal of providing the highest-quality reports for developing and tracking public health policies and practices.Item Landsat zooms in on cities’ hottest neighborhoods to help combat the urban heat island effect(Indiana University, 2022) Johnson, Daniel P.; Geography, School of Liberal ArtsItem La fascia trasformata siciliana: Il territorio tra crisi socioecologica e vulnerabilità(Società Di Studi Geografici, 2022) Petino, Gianni; Wilson, Jeffrey S.; Torre, Salvo; Geography, School of Liberal ArtsThe Sicilian transformed belt: territory between socio-ecological crisis and vulnerability. The term “transformed belt” indicates a predominantly coastal area of Southeastern Sicily in which greenhouse cultivation of products mainly intended for large-scale distribution has intensifed. The case study is indicative of the profound social crisis that has been triggered by the transformation of the primary sector in Southern Europe and can also be considered indicative of the processes of territorial change and of the dynamics of production of socio-ecological crises. The almost exclusive use of migrant labour overlaps with land consumption and damage to local biomes, in an overall process that has also resulted in a situation of social marginality. The impact of the production system is very high, and the modest amount of public and private remediation interventions aggravated the situation. The intervention intends to focus on some experiences of conversion of production practices that have presupposed a reflection on the connection between food production, value chains and new life practices.Item Efficacy of Low-Cost Sensor Networks at Detecting Fine-Scale Variations in Particulate Matter in Urban Environments(MDPI, 2023-01) Heintzelman, Asrah; Filippelli, Gabriel M.; Moreno-Madriñan, Max J.; Wilson, Jeffrey S.; Wang, Lixin; Druschel, Gregory K.; Lulla, Vijay O.; Geography, School of Liberal ArtsThe negative health impacts of air pollution are well documented. Not as well-documented, however, is how particulate matter varies at the hyper-local scale, and the role that proximal sources play in influencing neighborhood-scale patterns. We examined PM2.5 variations in one airshed within Indianapolis (Indianapolis, IN, USA) by utilizing data from 25 active PurpleAir (PA) sensors involving citizen scientists who hosted all but one unit (the control), as well as one EPA monitor. PA sensors report live measurements of PM2.5 on a crowd sourced map. After calibrating the data utilizing relative humidity and testing it against a mobile air-quality unit and an EPA monitor, we analyzed PM2.5 with meteorological data, tree canopy coverage, land use, and various census variables. Greater proximal tree canopy coverage was related to lower PM2.5 concentrations, which translates to greater health benefits. A 1% increase in tree canopy at the census tract level, a boundary delineated by the US Census Bureau, results in a ~0.12 µg/m3 decrease in PM2.5, and a 1% increase in “heavy industry” results in a 0.07 µg/m3 increase in PM2.5 concentrations. Although the overall results from these 25 sites are within the annual ranges established by the EPA, they reveal substantial variations that reinforce the value of hyper-local sensing technologies as a powerful surveillance tool.Item Impacts of confounding roadway characteristics on estimates of associations between alcohol outlet densities and alcohol-related motor vehicle crashes(Wiley, 2021) Lipton, Robert; Banerjee, Aniruddha; Ponicki, William R.; Gruenewald, Paul J.; Morrison, Christopher; Geography, School of Liberal ArtsIntroduction and aims: Previous research on alcohol-related motor vehicle crashes (AMVC) share a substantial limitation: sources of geographic variations in background crash risks may confound estimated spatial relationships between alcohol outlets and AMVCs. The aim of this study was to address this concern by examining, spatial-temporally, relationships between alcohol outlets and AMVCs adjusting for a set of six roadway characteristics that may be, independently, related to crash risks. While most similar studies focus on one metropolitan area, we use a unique sample of 50 cities. Design and methods: The spatial sample for this study consisted of 8726 Census 2000 block groups representing 50 mid-sized California cities. Dependent measures were counts of crashes located within Census block groups. Independent measures included socio-demographics, social disadvantage, alcohol outlets and roadway characteristics. We assessed relationships of crashes to independent measures using hierarchical generalised linear models. Results: Greater roadway length, greater percentage of highways, greater average speeds, fewer T-intersections, greater curviness and less fragmentation were related to greater numbers of crashes as was alcohol outlet density. Discussion: Above and beyond alcohol outlet type and density, we found that roadway characteristics were related to AMVC risks across a sample of 50 mid-sized cities. Measures of roadway characteristics are an essential component of any model of motor vehicle crashes that attempts to assess impacts of alcohol outlets on motor vehicle crashes risks.Item Intact landscape promotes gene flow and low genetic structuring in the threatened Eastern Massasauga Rattlesnake(Wiley, 2021-06) Kudla, Nathan; McCluskey, Eric M.; Lulla, Vijay; Grundel, Ralph; Moore, Jennifer A.; Geography, School of Liberal ArtsGenetic structuring of wild populations is dependent on environmental, ecological, and life-history factors. The specific role environmental context plays in genetic structuring is important to conservation practitioners working with rare species across areas with varying degrees of fragmentation. We investigated fine-scale genetic patterns of the federally threatened Eastern Massasauga Rattlesnake (Sistrurus catenatus) on a relatively undisturbed island in northern Michigan, USA. This species often persists in habitat islands throughout much of its distribution due to extensive habitat loss and distance-limited dispersal. We found that the entire island population exhibited weak genetic structuring with spatially segregated variation in effective migration and genetic diversity. The low level of genetic structuring contrasts with previous studies in the southern part of the species' range at comparable fine scales (~7 km), in which much higher levels of structuring were documented. The island population's genetic structuring more closely resembles that of populations from Ontario, Canada, that occupy similarly intact habitats. Intrapopulation variation in effective migration and genetic diversity likely corresponds to the presence of large inland lakes acting as barriers and more human activity in the southern portion of the island. The observed genetic structuring in this intact landscape suggests that the Eastern Massasauga is capable of sufficient interpatch movements to reduce overall genetic structuring and colonize new habitats. Landscape mosaics with multiple habitat patches and localized barriers (e.g., large water bodies or roads) will promote gene flow and natural colonization for this declining species.Item Predicting COVID-19 community infection relative risk with a Dynamic Bayesian Network(Frontiers, 2022) Johnson, Daniel P.; Lulla, Vijay; Geography, School of Liberal ArtsAs COVID-19 continues to impact the United States and the world at large it is becoming increasingly necessary to develop methods which predict local scale spread of the disease. This is especially important as newer variants of the virus are likely to emerge and threaten community spread. We develop a Dynamic Bayesian Network (DBN) to predict community-level relative risk of COVID-19 infection at the census tract scale in the U.S. state of Indiana. The model incorporates measures of social and environmental vulnerability—including environmental determinants of COVID-19 infection—into a spatial temporal prediction of infection relative risk 1-month into the future. The DBN significantly outperforms five other modeling techniques used for comparison and which are typically applied in spatial epidemiological applications. The logic behind the DBN also makes it very well-suited for spatial-temporal prediction and for “what-if” analysis. The research results also highlight the need for further research using DBN-type approaches that incorporate methods of artificial intelligence into modeling dynamic processes, especially prominent within spatial epidemiologic applications.Item Population-Based Disparities in U.S. Urban Heat Exposure from 2003 to 2018(MDPI, 2022) Johnson, Daniel P.; Geography, School of Liberal ArtsPrevious studies have shown, in the United States (U.S.), that communities of color are exposed to significantly higher temperatures in urban environments than complementary White populations. Studies highlighting this disparity have generally been cross-sectional and are therefore “snapshots” in time. Using surface urban heat island (SUHI) intensity data, U.S. Census 2020 population counts, and a measure of residential segregation, this study performs a comparative analysis between census tracts identified as prevalent for White, Black, Hispanic and Asian populations and their thermal exposure from 2003 to 2018. The analysis concentrates on the top 200 most populous U.S. cities. SUHI intensity is shown to be increasing on average through time for the examined tracts. However, based on raw observations the increase is only statistically significant for White and Black prevalent census tracts. There is a 1.25 K to ~2.00 K higher degree of thermal exposure on average for communities of color relative to White prevalent areas. When examined on an inter-city basis, White and Black prevalent tracts had the largest disparity, as measured by SUHI intensity, in New Orleans, LA, by <6.00 K. Hispanic (>7.00 K) and Asian (<6.75 K) prevalent tracts were greatest in intensity in San Jose, CA. To further explore temporal patterns, two models were developed using a Bayesian hierarchical spatial temporal framework. One models the effect of varying the percentages of each population group relative to SUHI intensity within all examined tracts. Increases in percentages of Black, Hispanic, and Asian populations contributed to statistically significant increases in SUHI intensity. White increases in population percentage witnessed a lowering of SUHI intensity. Throughout all modeled tracts, there is a statistically significant 0.01 K per year average increase in SUHI intensity. A second model tests the effect of residential segregation on thermal inequity across all examined cities. Residential segregation, indeed, has a statistically significant positive association with SUHI intensity based on this portion of the analysis. Similarly, there is a statistically significant 0.01 K increase in average SUHI intensity per year for all cities. Results from this study can be used to guide and prioritize intervention strategies and further urgency related to social, climatic, and environmental justice concerns.