Threshold Responses of Forest Birds to Landscape Changes around Exurban Development

<div><p>Low-density residential development (i.e., exurban development) is often embedded within a matrix of protected areas and natural amenities, raising concern about its ecological consequences. Forest-dependent species are particularly susceptible to human settlement even at low housing densities typical of exurban areas. However, few studies have examined the response of forest birds to this increasingly common form of land conversion. The aim of this study was to assess whether, how, and at what scale forest birds respond to changes in habitat due to exurban growth. We evaluated changes in habitat composition (amount) and configuration (arrangement) for forest and forest-edge species around North America Breeding Bird Survey (BBS) stops between 1986 and 2009. We used Threshold Indicator Taxa Analysis to detect change points in species occurrence at two spatial extents (400-m and 1-km radius buffer). Our results show that exurban development reduced forest cover and increased habitat fragmentation around BBS stops. Forest birds responded nonlinearly to most measures of habitat loss and fragmentation at both the local and landscape extents. However, the strength and even direction of the response changed with the extent for several of the metrics. The majority of forest birds’ responses could be predicted by their habitat preferences indicating that management practices in exurban areas might target the maintenance of forested habitats, for example through easements or more focused management for birds within existing or new protected areas.</p></div

Performance on the Stroop predicts treatment compliance in cocaine-dependent individuals.

Treatment dropout is a problem of great prevalence and stands as an obstacle to recovery in cocaine-dependent (CD) individuals. Treatment attrition in CD individuals may result from impairments in cognitive control, which can be reliably measured by the Stroop color-word interference task. The present analyses contrasted baseline performance on the color-naming, word-reading, and interference subtests of the Stroop task in CD subjects who completed a cocaine treatment trial (completers: N=50) and those who dropped out of the trial before completion (non-completers: N=24). A logistic regression analysis was used to predict trial completion using three models with the following variables: the Stroop task subscale scores (Stroop model); the Hamilton depression rating scale (HDRS) scores (HDRS model); and both the Stroop task subscale scores and HDRS scores (Stroop and HDRS model). Each model was able to significantly predict group membership (completers vs non-completers) better than a model based on a simple constant (HDRS model p=0.02, Stroop model p=0.006, and Stroop and HDRS model p=0.003). Models using the Stroop preformed better than the HDRS model. These findings suggest that the Stroop task can be used to identify cocaine-dependent subjects at risk for treatment dropout. The Stroop task is a widely available, reliable, and valid instrument that can be easily employed to identify and tailor interventions of at risk individuals in the hope of improving treatment compliance