After seeking a “manageable standard” to apply to claims of partisan gerrymandering for over three decades, the Supreme Court has finally given up the chase, ruling that such claims are nonjusticiable. What is to be done? An extended history of successful congressional action suggests that the legislative pathway is more practical than often believed. Statutory requirements also make it possible to consider a broader suite of districting objectives. This paper presents a flexible new software and a framework for evaluating the practical implications of explicit objectives. I apply this approach to the conditions last required by Congress, generating equipopulous, contiguous, and compact districts. Among these conditions, the formal definition of compactness has proven contentious. Does it matter? I contrast the representation of the political parties and of racial and ethnic minorities under plans optimized according to 18 different definitions of compactness. On these grounds, the definitions are markedly consistent. These methods may be extended to alternative districting objectives and criteria.

The environmental bacterium, Burkholderia pseudomallei, is responsible for the potentially fatal disease melioidosis. Factors responsible for the temporospatial distribution of cases are incompletely understood, although a combination of rainfall, groundwater levels and the physicochemical properties of soil are important. The distribution of culture-positive cases of melioidosis from 1996 to 2016 in Far North Queensland, Australia, was investigated to determine the association with different soil types and landforms in Cairns, the region's largest city. Cases were clustered on alluvial fan landforms of strongly bleached gradational textured and yellow massive gradational textured soils indicating these soils are more suitable for B. pseudomallei and risk of melioidosis infection is higher in these areas, cases were less frequent on other soil types on alluvial fan landforms (despite comparable population density) and beach ridges. This indicates that the combination of these soils might be more suitable for B. pseudomallei, increasing the risk of disease in these locations. Sociodemographic characterisics of the population in cluster locations were considered. Knowledge of local soil characteristics may help predict cases of melioidosis and inform public health strategies to prevent the disease. Because melioidosis case clusters were identified, testing for the presence of B. pseudomallei across the study area is a useful target of future research.

Harvest weed seed control (HWSC) techniques have been implemented in Australian cropping systems to target and reduce the number of weed seeds entering the seedbank and thereby reduce the number of problematic weeds emerging in subsequent years to infest subsequent crops. However, the influence of HWSC on ameliorating herbicide-resistance (HR) evolution has not been investigated. This research used integrated spatial modeling to examine how the frequency and efficacy of HWSC affected the evolution of resistance to initially effective herbicides. Herbicides were, in all cases, better protected from future resistance evolution when their use was combined with annual HWSC. Outbreaks of multiple HR were very unlikely to occur and were nearly always eliminated by adding annual, efficient HWSC. The efficacy of the HWSC was important, with greater reductions in the number of resistance genes achieved with higher-efficacy HWSC. Annual HWSC was necessary to protect sequences of lower-efficacy herbicides, but HWSC could still protect herbicides if it was used less often than once per year, when the HWSC and the herbicides were highly effective. Our results highlight the potential benefits of combining HWSC with effective herbicides for controlling weed populations and reducing the future evolution of HR.

Fine resolution spatial variability in pneumonia hospitalization may identify correlates with socioeconomic, demographic and environmental factors. We performed a retrospective study within the Fairview Health System network of Minnesota. Patients 2 months of age and older hospitalized with pneumonia between 2011 and 2015 were geocoded to their census block group, and pneumonia hospitalization risk was analyzed in relation to socioeconomic, demographic and environmental factors. Spatial analyses were performed using Esri's ArcGIS software, and multivariate Poisson regression was used. Hospital encounters of 17 840 patients were included in the analysis. Multivariate Poisson regression identified several significant associations, including a 40% increased risk of pneumonia hospitalization among census block groups with large, compared with small, populations of ⩾65 years, a 56% increased risk among census block groups in the bottom (first) quartile of median household income compared to the top (fourth) quartile, a 44% higher risk in the fourth quartile of average nitrogen dioxide emissions compared with the first quartile, and a 47% higher risk in the fourth quartile of average annual solar insolation compared to the first quartile. After adjusting for income, moving from the first to the second quartile of the race/ethnic diversity index resulted in a 21% significantly increased risk of pneumonia hospitalization. In conclusion, the risk of pneumonia hospitalization at the census-block level is associated with age, income, race/ethnic diversity index, air quality, and solar insolation, and varies by region-specific factors. Identifying correlates using fine spatial analysis provides opportunities for targeted prevention and control.

Several studies have been carried out to evaluate the main drivers behind biological invasions and their ecological consequences. Nevertheless, it is still extremely difficult to acquire a full understanding of the invasion process due to its high level of complexity. The problems that complicate invasion studies are low detection during the early stages of invasion, and the high survey cost of working over large, inaccessible, and rugged areas. The studies that develop efficient tools to reduce costs and time will help to control or mitigate the invaders' damaging effects. Hieracium pilosella is an aggressive invader of grasslands worldwide. The aim of this work was to conduct a regional assessment for the suitability of H. pilosella invasion in the Fuegian Steppe by combining field surveys, spatial modeling, and geographic information system tools. We recorded the invader cover in 167 sample sites and we determined the relationship between environmental variables and the probability of invasion. This was carried out by the selection of alternative generalized linear models. The best model indicates that disturbance and plant community were the main drivers to predict invasion suitability on a regional scale. Therefore, these two variables were used as main inputs to construct a regional invasion suitability map, which identifies the most critical areas for prevention, control, and further monitoring. This approach corresponds to a tool that permits us to evaluate the suitability of invasion even over large and inaccessible areas. The results especially warn about soil disturbance associated with usual management practices in Fuegian rangelands.

This paper extends first-best analysis of anti-sprawl policies, such as development taxes, and examines the welfare effects of development taxes in the presence of urban decline at the city core. We find that anti-sprawl policies generate several important feedbacks within the urban system, generating additional welfare gains and affecting the level of urban decline and suburban sprawl. Further, the optimal development tax exceeds the (first-best) Pigouvian level, irrespective of whether or not revenues are returned lump-sum to all landowners or earmarked for urban decline mitigation.

As many local and state governments in the United States grapple with increasing growth pressures, the need to understand the economic and institutional factors underlying these pressures has taken on added urgency. From an economic perspective, individual land use decisions play a central role in the manifestation of growth pressures, as changes in land use pattern are the cumulative result of numerous individual decisions regarding the use of lands. In this study, the issue of growth management is addressed by developing a spatially disaggregated, microeconomic model of land conversion decisions suitable for describing residential land use change at the rural-urban fringe. The model employs parcel-level data on land use in Calvert County, Maryland, a rapidly growing rural-urban fringe county. A probabilistic model of residential land use change is estimated using a duration model, and the parameter estimates are employed to simulate possible future growth scenarios under alternative growth management scenarios. Results suggest that “smart growth” objectives are best met when policies aimed at concentrating growth in target areas are implemented in tandem with policies designed to preserve rural or open space lands.

This study examines the effectiveness of growth management policies on influencing future patterns of exurban and suburban development. We initially estimate a spatially explicit model of residential development with parcel data in Sonoma County, California. This estimated model is then used to simulate the effect of urban growth boundaries (UGBs) versus allowing municipal sewer service expansion. The UGB policy decreases the amount of suburban development but is less effective in managing exurban development. The downzoning policy in agricultural and resource areas reduces the amount of exurban development, but only partially due to the prevalence of grandfathered lots in rural areas.