Classes of protection in urban forest fragments are effectiveless in structuring butterfly assemblages: landscape and forest structure are far better predictors

Urbanization is a major cause of biodiversity loss and disconnection between people and nature. For this reason, the creation and maintenance of green areas as part of the urban landscape is a common practice in cities around the world. These green areas are generally a result of particular public policies regarding how these areas can be accessed, maintained, and how they are connected to other natural fragments in the city. In an effort to investigate aspects of the ecology of such green areas of the city of Curitiba, southern Brazil, the present study measured distinct parameters of the structure of butterfly assemblages from 19 forest fragments of distinct classes of protection, testing the influence of different policies (protection category) on butterfly assemblages. Comparatively, we also tested the predictive power of landscape variables (at distinct scales) and fragment quality (e.g. diameter at breast height, density of vegetation) using Generalized Linear Models (GLMs). Overall, 14,596 individuals belonging to 412 butterfly species were recorded, but values of species diversity and composition are very heterogeneous, indicating that the protection categories do not significantly interfere with the structure of the butterfly assemblages. More important than the protection category is the forest fragment quality and landscape connectivity. Our models showed that degraded fragments tend to present a specific butterfly composition, whereas the more urbanized landscape have poor butterfly species richness. These results reinforce the importance of implementing public policies that prioritize the conservation of the quality of forest fragments in every class of protection, as well as the conservation of forest fragments throughout the urban landscape.

     

“A Second-Chance at Being a Parent”: Grandparent Caregivers’ Reported Communication and Parenting Practices with Co-Residential Grandchildren

ABSTRACT

Grandfamilies, family structures in which grandparent(s) co-reside with and assume a primary caregiving role for at least one grandchild, are increasingly common in the United States. This qualitative, exploratory study, informed by family communication patterns theory (FCPT), illuminated the reported communication beliefs and practices of grandparents who serve as primary caregiver to at least one grandchild. Hybrid thematic analysis, combining FCTP with inductive analysis, was used to analyze 21 semi-structured interviews with grandparents. Results yielded four themes describing grandparents’ reported communicative practices: creating opportunities for listening and dialogue, talking about emotion, emphasizing openness, and allowing questioning; and three themes describing the impact of second-chance parenting: increased resources, acquired wisdom, and matured emotionally. Implications for grandfamily communication research in light of hybrid analyses and FCPT are discussed.     

On intra-annual consumption-poverty in the U.S: Response to SNAP and the importance of within-year variation

We use U.S. quarterly consumption data and decomposable poverty indexes to study consumption-based intra-annual poverty and its relationship to participation in the Supplemental Nutrition Assistance Program (SNAP). Intra-annual spells of consumption-poverty account for half of the incidence and one-third of the severity of all consumption-poverty among U.S. households. Households experiencing consumption-poverty for at least one quarter, but not for the whole year, are more likely to self-select into SNAP than the general population but less likely to do so than those who are poor for the year. SNAP participation, in turn, reduces annual and intra-annual poverty.     

Health Insurance Coverage and Access to Care by Sexual Orientation and Marital/Cohabitation Status: New Evidence from the 2015–2018 National Health Interview Survey

Population Research and Policy Review - Disparities in health insurance coverage and access to care are well documented between sexual minority adults and their heterosexual peers. Much less...     

Period effects on race- and parity-specific birth probabilities of American women, 1917–1976: A new measure of fertility

A new measure of fertility—period coefficients in a prediction of the probability of birth by parity and race—for American women during the period 1917–1976 is explained and displayed. The measure estimates the probability that a next birth will be due to annual conditions, net of age, and is specific to race and parity. We controlled effects of age including a parameter based on an explicit theoretical conception about how age and period influences combine. This refined measure promises greater explained variance, more parsimoniously and more realistically, than has been true of earlier analyses of U.S. fertility trends.     

Prespective from a weather modification experiment

This article provides some views on the statistical design and analysis of weather modification experiments. Perspectives were developed from experience with analyses of the Santa Barbara Phase I experiment summarized in Section 2, Randomization analvses are reported and compared with previously published parametric analyses. The parametric significance levels of tests for a cloud seeding effect agree well with the significance levels of the new corresponding randomization tests, These results, along with similar results of others, suggest that parametric analyses may be used as approximations to randomization analyses in exploratory analyses or reanalyses of weather modification experimental data.     

Efficient estimation of nonparametric spatial models with general correlation structures

Spatially correlated data appear in many environmental studies, and consequently there is an increasing demand for estimation methods that take account of spatial correlation and thereby improve the accuracy of estimation. In this paper we propose an iterative nonparametric procedure for modelling spatial data with general correlation structures. The asymptotic normality of the proposed estimators is established under mild conditions. We demonstrate, using both simulation and case studies, that the proposed estimators are more efficient than the traditional locally linear methods which fail to account for spatial correlation.