Spatial variation in soil inorganic nitrogen across an arid urban ecosystem

We explored variations in inorganic soil nitrogen (N) concentrations across metropolitan Phoenix, Arizona, and the surrounding desert using a probability-based synoptic survey. Data were examined using spatial statistics on the entire region, as well as for the desert and urban sites separately. Concentrations of both NO₃-N and NH₄-N were markedly higher and more heterogeneous amongst urban compared to desert soils. Regional variation in soil NO₃-N concentration was best explained by latitude, land use history, population density, along with percent cover of impervious surfaces and lawn, whereas soil NH₄-N concentrations were related to only latitude and population density. Within the urban area, patterns in both soil NO₃-N and NH₄-N were best predicted by elevation, population density and type of irrigation in the surrounding neighborhood. Spatial autocorrelation of soil NO₃-N concentrations explained 49% of variation among desert sites but was absent between urban sites. We suggest that inorganic soil N concentrations are controlled by a number of ‘local’ or ‘neighborhood’ human-related drivers in the city, rather than factors related to an urban-rural gradient.     

Race and Population Change: A Longitudinal Look at Cleveland Neighborhoods

This paper investigates the relationship of racial composition to neighborhood population change from 1910 to 1990 in the Cleveland metropolitan area. To better understand the long-term dynamics of urban neighborhood change, we focus our analysis upon the longitudinal relationship of race, socioeconomic status, and life cycle stage to changes in neighborhood population densities. First, we find that the more established neighborhoods of the African-American community have experienced dramatic declines in population since 1950, a pattern that represents a clear change from the earlier part of the twentieth century. Second, population loss is experienced through a variety of mechanisms, including the demolition of dwellings, the increase in housing vacancy, and the decline of household size. Third, much of this population loss should be interpreted within the context of high economic distress, occurring most frequently in older African-American communities. Over time, economic distress appears to be more important than race in and of itself in leading to the loss of neighborhood populations.     

Predicting infectious disease outbreak risk via migratory waterfowl vectors

The spread of an emerging infectious disease is a major public health threat. Given the uncertainties associated with vector-borne diseases, in terms of vector dynamics and disease transmission, it is critical to develop statistical models that address how and when such an infectious disease could spread throughout a region such as the USA. This paper considers a spatio-temporal statistical model for how an infectious disease could be carried into the USA by migratory waterfowl vectors during their seasonal migration and, ultimately, the risk of transmission of such a disease to domestic fowl. Modeling spatio-temporal data of this type is inherently difficult given the uncertainty associated with observations, complexity of the dynamics, high dimensionality of the underlying process, and the presence of excessive zeros. In particular, the spatio-temporal dynamics of the waterfowl migration are developed by way of a two-tiered functional temporal and spatial dimension reduction procedure that captures spatial and seasonal trends, as well as regional dynamics. Furthermore, the model relates the migration to a population of poultry farms that are known to be susceptible to such diseases, and is one of the possible avenues toward transmission to domestic poultry and humans. The result is a predictive distribution of those counties containing poultry farms that are at the greatest risk of having the infectious disease infiltrate their flocks assuming that the migratory population was infected. The model naturally fits into the hierarchical Bayesian framework.     

Detecting a changed segment in DNA sequences

Non-coding deoxyribonucleic acid (DNA) can typically be modelled by a sequence of Bernoulli random variables by coding one base, e.g. T, as 1 and other bases as 0. If a segment of a sequence is functionally important, the probability of a 1 will be different in this changed segment from that in the surrounding DNA. It is important to be able to see whether such a segment occurs in a particular DNA sequence and to pin-point it so that a molecular biologist can investigate its possible function. Here we discuss methods for testing the occurrence of such a changed segment and how to estimate the end points of it. Maximum-likelihood-based methods are not very tractable and so a nonparametric method based on the approach of Pettitt has been developed. The problem and its solution are illustrated by a specific DNA example.     

Modeling population and subject-specific growth in a latent trait measured by multiple instruments over time using a hierarchical Bayesian framework

Psychometric growth curve modeling techniques are used to describe a person’s latent ability and how that ability changes over time based on a specific measurement instrument. However, the same instrument cannot always be used over a period of time to measure that latent ability. This is often the case when measuring traits longitudinally in children. Reasons may be that over time some measurement tools that were difficult for young children become too easy as they age resulting in floor effects or ceiling effects or both. We propose a Bayesian hierarchical model for such a scenario. Within the Bayesian model we combine information from multiple instruments used at different age ranges and having different scoring schemes to examine growth in latent ability over time. The model includes between-subject variance and within-subject variance and does not require linking item specific difficulty between the measurement tools. The model’s utility is demonstrated on a study of language ability in children from ages one to ten who are hard of hearing where measurement tool specific growth and subject-specific growth are shown in addition to a group level latent growth curve comparing the hard of hearing children to children with normal hearing.KEYWORDS: Bayesian hierarchical models, psychometric modeling, language ability, growth curve modeling, longitudinal analysis     

Do the Constructs of the FACES IV Change Based on Definitions of “Family?” A Measurement Invariance Test

The Family Adaptability and Cohesion Scale (FACES) IV does not provide instructions about which family members respondents should think about while answering questions. This study examined which family members respondents thought about while completing the FACES IV, and if this changed measurement invariance and population heterogeneity of the measure. Using a sample of n = 511 individuals, a latent class analysis showed three distinct classes: Nuclear Family, Family of Origin, and All of the Above. The FACES IV demonstrated measurement invariance across classes on the majority of subscales; however, population heterogeneity tests suggested that the means and variances of the subscales varied across classes. The findings suggest further examination of how the measure functions with unique family constellations is warranted.     

Growing Pains: The Transformative Journey from a Nascent to a Formal Not-For-Profit Venture

This article examines how a social venture transitions from nascent to formal status and argues that the transformation of the organization set in motion by establishing formal boundaries is a deeply profound one. Drawing from the nonprofit and social entrepreneurship literature on what prompts and energizes individuals to initiate new not-for-profit ventures, and linking it to a notion of revolutionary crisis as organizations emerge and develop, we seek to illuminate and explore the tension, and its consequences, between nonprofit entrepreneurs and the organization they create as the new venture transitions from nascent to formal. We do this by presenting the results from an in-depth case study examining the gestation and boundary-forming phases of Robert’s Place Cooperative, a plucky start-up cooperative in a midsize Midwestern city.     

An examination of the role of online social media in journalists’ source mix

Using telephone surveys of business/financial journalists in the United States (n = 200), this research investigates the agenda-building role of social media content in journalists’ work. Understanding that more non-public relations content from user-generated and social network sites, like YouTube and Twitter, are fast becoming resources for journalists to get story ideas, break scandals, and find sources, we began this scholarly work to determine the frequency of such uses of social media. Overall, findings indicate very little use of social media by these business journalists. Results and implications for public relations practitioners are discussed in detail.     

Negative (But Not Positive) Parenting Interacts with Infant Negative Affect to Predict Infant Approach: Evidence of Diathesis‐Stress

Temperament by parenting interactions may reflect that individuals with greater risk are more likely to experience negative outcomes in adverse contexts (diathesis‐stress) or that these individuals are more susceptible to contextual influences in a “for better or for worse” pattern (differential susceptibility). Although such interactions have been identified for a variety of child outcomes, prior research has not examined approach characteristics—excitement and approach toward pleasurable activities—in the first year of life. Therefore, this study investigated whether 6‐month maternal reported infant negative affect—a phenotypic marker of risk/susceptibility—interacted with 8‐month observed parenting behaviors (positive parenting, negative parenting) to predict 12‐month infant behavioral approach. Based on a sample of mothers and their infants (N = 150), results indicated that negative parenting was inversely associated with subsequent approach for infants with high, but not low, levels of negative affect. Similar results did not occur regarding positive parenting. These findings better fit a diathesis‐stress model rather than a differential susceptibility model. Implications and limitations of these findings are discussed.