The role of social capital,personal networks,and emergency responders in post-disaster recovery and resilience: a study of rural communities in Indiana

The factors that explain the speed of recovery after disaster remain contested. While many have argued that physical infrastructure, social capital, and disaster damage influence the arc of recovery, empirical studies that test these various factors within a unified modeling framework are few. We conducted a mail survey to collect data on household recovery in four small towns in southern Indiana that were hit by deadly tornadoes in March 2012. The recovery effort is ongoing; while many of the homes, businesses, and community facilities were rebuilt in 2013, some are still under construction. We investigate how households in these communities are recovering from damage that they experienced and the role of social capital, personal networks, and assistance from emergency responders on the overall recovery experience. We used an ordered probit modeling framework to test the combined as well as relative effects of (a) damage to physical infrastructures (houses, vehicles, etc.); (b) recovery assistance from emergency responders (FEMA) as well as friends and neighbors; (c) personal network characteristics (size, network density, proximity, length of relationship); (d) social capital (civic engagement, contact with neighbors, trust); and (e) household characteristics. Results show that while households with higher levels of damage experienced slower recovery, those with recovery assistance from neighbors, stronger personal networks, and higher levels of social capital experienced faster recovery. The insights gained in this study will enable emergency managers and disaster response personnel to implement targeted strategies in facilitating post-disaster recovery and community resilience.     

How natural hazards impact the social environment for vulnerable groups: an empirical investigation in Japan

Natural Hazards - Much research has demonstrated that vulnerable people fare more poorly than non-vulnerable ones in disasters and crises across a variety of outcomes—including mental and...     

Mapping Soils,Vegetation, and Landforms: An Integrative Physical Geography Field Experience*

Students in a graduate seminar at Michigan State University produced a series of detailed vegetation, soils, and landform maps of a 1.5‐square‐mile (3.9 km²) study area in southwest Lower Michigan. The learning outcomes (maps) and skill development objectives (sampling strategies and various GIS applications) of this field‐intensive mapping experience were driven by the assumption that students learn and understand relationships among physical landscape variables better by mapping them than they would in a classroom‐based experience. The group‐based, problem‐solving format was also intended to foster collaboration and camaraderie. The study area lies within a complex, interlobate moraine. Fieldwork involved mapping in groups of two or three, as well as soil and vegetation sampling. Spatial data products assembled and used in the project included topographic maps, a digital elevation model (DEM), aerial photographs, and NRCS (National Resource Conservation Service) soil maps. Most of the soils are dry and sandy, with the main differentiating characteristic being the amount of, and depth to, subsurface clay bands (lamellae) or gravelly zones. The presettlement (early 1830s) vegetation of the area was oak forest, oak savanna, and black oak “barrens.” Upland sites currently support closed forests of white, black, and red oak, with a red maple, dogwood, and sassafras understory. Ecological data suggest that these oak forests will, barring major disturbance, become increasingly dominated by red maple. This group‐based, problem‐solving approach to physical geography education has several advantages over traditional classroom‐based teaching and could also be successfully applied in other, field‐related disciplines.     

Modelling of hydrocyclone performance based on spray profile analysis

Spray profile measurements can be used to calculate the underflow rate, and consequently, be related to hydrocyclone performance. The flow geometry of the spray discharge is found to arise from velocity patterns at the outlet orifice. Through a videographic example of an industrial hydrocyclone, it is shown that underflow profiles are typically parabolic, a feature which is indicative of the velocity at which the fluid exits. The inclusion of gravity in this model clearly highlights deficiencies in currently used models. Moreover, an intimate knowledge of factors affecting the profiles of the underflow of a cyclone is essential for the correct interpretation of videographic images. Subsequently, image data are used to estimate outlet velocities, which give an excellent insight into various fluid mechanical phenomena that are not appreciated by analysing basic operational variables. The exit velocities are used to calculate underflow rates, which are related to mass recovery in the underflow.     

Social capital as a shield against anxiety among displaced residents from Fukushima

The March 2011 meltdowns at the Fukushima nuclear power plants in Japan resulted in an increased risk of psychological distress among affected residents. We conducted original surveys of Futaba residents, a town in Fukushima where all of the residents were forced to evacuate from their homes due to radioactive contamination, obtaining 585 responses (a response rate of about 20%). Using this original data set, we investigate the role of social capital in maintaining mental health among the residents. First, we found the level of stress captured by the Kessler index (K6) to be unusually high compared both with people across Japan and with those who were displaced because of the earthquake and/or tsunami (but not the nuclear catastrophe). However, having high levels of social capital—captured by the number of neighbors from Futaba after displacement, participation in volunteer work after displacement, and participation in tea parties after displacement—plays an important role in reducing anxiety and distress among Futaba residents. Finally, we provide concrete recommendations for policy makers and NGOs to increase resilience among affected residents by strengthening social ties.     

The power of people: social capital’s role in recovery from the 1995 Kobe earthquake

Despite the regularity of disasters, social science has only begun to generate replicable knowledge about the factors which facilitate post-crisis recovery. Building on the broad variation in recovery rates within disaster-affected cities, I investigate the ability of Kobe’s nine wards to repopulate after the 1995 Kobe earthquake in Japan. This article uses case studies of neighborhoods in Kobe alongside new time-series, cross-sectional data set to test five variables thought to influence recovery along with the relatively untested factor of social capital. Controlling for damage, population density, economic conditions, inequality and other variables thought important in past research, social capital proves to be the strongest and most robust predictor of population recovery after catastrophe. This has important implications both for public policies focused on reconstruction and for social science more generally.     

The Model-Free Analysis of Growth Curves

Abstract.

• 1) An incremental (graphical in this presentation) method for the analysis of growth curves has revealed actual, as opposed to modelled, growth rates. Here, we present data derived from the scallop Pecten maximus (L.). These actual rates exhibit differences in annual environmental conditions and differences between local populations.
• 2) Both first and second derivatives (growth rate and acceleration ? deceleration in growth rate, respectively) can be obtained from plotted size ? age data: here, size is represented by the height of the flat left valve.
• 3) The analysis of age class data from different years allows one to estimate maximum theoretical rates in any given year.
• 4) The analysis of individual data naturally reveals more than the analysis of average data, reinforcing the average nature of population growth parameters.
• 5) The departure of average data from the maxima revealed by the analysis of growth rate and acceleration allows one to identify changes in environmental conditions in different years.
• 6) The Von Bertalanffy growth curve has been used as an example because it is well known and widely used; however, any desired growth curve can be fitted by the method discussed here.