Frontier spaces of vulnerability: Regional change,urbanization, drought and fire hazard in Santarém,Pará, Brazil

Fire hazard is a mounting concern in tropical rainforests of the Brazilian Amazon and has raised awareness within the science community of the links between agricultural fire use, drought and accidental fire. As a result, fire is being addressed as a crisis event with mitigation focused on those who light fires, particularly smallholder agriculturalists. Little attention is paid to the historical and ongoing ways in which Amazon landscapes and peoples have been made more susceptible to fire. Frontier regions of the Brazilian Amazon serve a variety of functions within the larger Brazilian society, including as extractive reserves for economic development, as social safety valves to reduce population pressures, and as areas to support urban regional integration. Each of these functions has impacted frontier environments in ways that create more flammable landscapes and/or shape the vulnerability of people to fire hazard. This paper uses a case study inthe Brazilian Lower Amazon to understand how vulnerability to fire hazard develops. It argues that if fire mitigation remains centered on fire as a crisis event, an understanding of what constitutes frontier spaces of vulnerability, both in landscape and in populations, will be limited.     

Frustration in Infancy: Implications for Emotion Regulation,Physiological Processes,and Temperament

A study sample of 162 six‐month‐old children was selected from a larger sample of 346 infants on the basis of parents' report of their infants' temperament and a laboratory assessment of temperament. Infants were classified as easily frustrated and less easily frustrated and compared on a number of emotion regulation, physiology, and temperament measures. Results indicated that male and female infants were equally likely to be classified as frustrated and less easily frustrated; however, male infants were less able to regulate physiologically. Easily frustrated infants used different emotion regulation strategies and were observed to be less attentive and more active than less easily frustrated infants when observed in the laboratory. These infants were also characterized by their parents as more active, less attentive, and more distressed to novelty. Infants classified as easily frustrated were more reactive physiologically and less able to regulate physiological reactivity than their less easily frustrated counterparts. It is hypothesized that this cluster of characteristics may constitute a unique temperamental type that may have implications for other types of behavioral functioning. Limitations of the study are that observations are based on a single brief assessment of the infant, modest effect sizes were found, and the study is cross‐sectional.     

Editorial

Ohne Zusammenfassung

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Editorial

     

Measuring agreement between two statistics with applications to age standardization

Summary.  We detail a general method for measuring agreement between two statistics. An application is two ratios of directly standardized rates which differ only by the choice of the standard. If the statistics have a high value for the coefficient of agreement then the expected squared difference between the statistics is small relative to the variance of the average of the two statistics, and inferences vary little by changing statistics. The estimation of a coefficient of agreement between two statistics is not straightforward because there is only one pair of observed values, each statistic calculated from the data. We introduce estimators of the coefficient of agreement for two statistics and discuss their use, especially as applied to functions of standardized rates.     

Bayesian analysis of mixture modelling using the multivariate t distribution

A finite mixture model using the multivariate t distribution has been shown as a robust extension of normal mixtures. In this paper, we present a Bayesian approach for inference about parameters of t-mixture models. The specifications of prior distributions are weakly informative to avoid causing nonintegrable posterior distributions. We present two efficient EM-type algorithms for computing the joint posterior mode with the observed data and an incomplete future vector as the sample. Markov chain Monte Carlo sampling schemes are also developed to obtain the target posterior distribution of parameters. The advantages of Bayesian approach over the maximum likelihood method are demonstrated via a set of real data.