Using Remote Sensing to Evaluate Environmental Institutional Designs: A Habitat Conservation Planning Example

Objective. Satellite-based remote-sensing analysis is a beneficial, yet underused, tool for environmental policy, planning, and evaluation. We identify its benefits and costs to encourage social scientists to consider the use of remote sensing as a tool for planning and evaluating environmental institutions. Methods. We analyze two multispectral Landsat Thematic Mapper satellite images to evaluate a habitat conservation plan (HCP) implemented pursuant to the Endangered Species Act. Results. Image analysis provides useful broad spatial scale information on HCP performance that is not discernible to the naked eye or through other methodologies. Conclusions. Satellite image analysis should be considered as a tool for planning and evaluating environmental institutional designs—despite the financial costs and requisite technical training. These images provide ecological and land cover change information that may not be available elsewhere. We provide lessons learned to help make analysts cognizant of some important issues surrounding the use of satellite-based imagery for environmental institutional analysis.     

Nonparametric M-regression with free knot splines

Many problems of practical interest can be formulated as the nonparametric estimation of a certain function such as a regression function, logistic or other generalized regression function, density function, conditional density function, hazard function, or conditional hazard function. Extended linear modeling provides a convenient theoretical framework for using polynomial splines and their selected tensor products in such function estimation problems and especially for obtaining rates of convergence of the resulting estimates in a unified manner. For a long time the theoretical results were restricted to fixed knot splines and to log-likelihood functions that were twice continuously differentiable. Recently, Stone and Huang extended the theory to handle free knot splines. In the present paper, the theory is further extended to handle contexts in which the log-likelihood function may not be differentiable. Specifically, we establish rates of convergence for estimation based on free knot splines in the context of nonparametric regression corresponding to M-estimates, which includes least absolute deviations (LAD) regression, quantile regression, and robust regression as special cases.     

符号正义与公共行政 ——基于语言游戏的正义视角

公共行政是正义研究的重要领域。传统理论多采用罗尔斯、诺齐克和沃尔泽等人为正义提供的客观标准。但这些标准不仅在理论上相互冲突,而且在公共行政的实践中也常常会导致模棱两可的判断。本研究旨在提出一种符号正义的观念,来指导当代公共行政的理论与实践。这种观念认为正义并不存在中立客观的标准,而是被群体共享的信念和实践所建构。研究者只有将正义置于特定语言游戏的背景中,才能真正理解其发生和运作。因为和正义相关的不同语言游戏之间只存在家族相似性,所以公共行政必须面对相互冲突的复杂环境。符号正义的观念能够为这种公共行政问题的复杂性提供必不可少的分析框架。     

The Obese Smoker's Wage Penalty*

Objective. Smoking and obesity are associated with significant wage penalties when considered separately. We assess the combined effects of those behaviors. Methods. We estimate the effects of smoking and obesity on wages using multivariate regression analysis with 1979 National Longitudinal Survey of Youth data. Results. The raw data indicate that obese smokers experience large earnings penalties. However, these penalties are not found to be interactive or directly causal for most of the demographic subgroups we examine. One exception is the wage penalty associated with obesity for females, which remains significant throughout the analysis. Conclusions. In the absence of a demonstrable direct causal effect of those behaviors on wages, associated individual‐specific socioeconomic factors appear to be the driving forces behind the obese smoker wage penalty. Not included, but potentially significant, are the effects of employer and customer discrimination against obese smokers and the possible labor policy implications of such discrimination.     

Animal behavior in urban ecosystems: Modifications due to human-induced stress

Wildlife-human interactions are increasing in prevalence as urban sprawl continues to encroach into rural areas. Once considered to be unsuitable habitat for most wildlife species, urban/suburban areas now host an array of wildlife populations, many of which were previously restricted to rural or pristine habitats. The presence of some wildlife species in close proximity to dense human populations can create conflict, forcing resource managers to address issues relating to urban wildlife. However, evidence suggests that wildlife residing in urban areas may not exhibit the same life history traits as their rural counterparts because of adaptation to human-induced stresses. This creates difficulty for biologists or managers that must address problems associated with urban wildlife. Population control or mitigation efforts aimed at urban wildlife require detailed knowledge of the habits of wildlife populations in urban areas. This paper describes the history of wildlife in urban areas, provides examples of wildlife populations that have modified their behavior as an adaptation to urban stresses, and discusses the challenges that resource managers face when dealing with urban wildlife.     

Neural Correlates of Human and Monkey Face Processing in 9‐Month‐Old Infants

Behavioral and electrophysiological evidence suggests a gradual, experience‐dependent specialization of cortical face processing systems that takes place largely in the 1st year of life. To further investigate these findings, event‐related potentials (ERPs) were collected from typically developing 9‐month‐old infants presented with pictures of familiar and unfamiliar monkey or human faces in 2 different orientations. Analyses revealed differential processing across changes in monkey and human faces. The N290 was greater for familiar compared to unfamiliar faces, regardless of species or orientation. In contrast, the P400 to unfamiliar faces was greater than to familiar faces, but only for the monkey condition. The P400 to human faces differentiated the orientation of both familiar and unfamiliar faces. These results suggest more specific processing of human compared to monkey faces in 9‐month‐olds.