Impacts of urban sprawl on species richness of plants,butterflies, gastropods and birds: not only built-up area matters

Urban growth is a major factor of global environmental change and has important impacts on biodiversity, such as changes in species composition and biotic homogenization. Most previous studies have focused on effects of urban area as a general measure of urbanization, and on few or single taxa. Here, we analyzed the impacts of the different components of urban sprawl (i.e., scattered and widespread urban growth) on species richness of a variety of taxonomic groups covering mosses, vascular plants, gastropods, butterflies, and birds at the habitat and landscape scales. Besides urban area, we considered the average age, imperviousness, and dispersion degree of urban area, along with human population density, to disentangle the effects of the different components of urban sprawl on biodiversity. The study was carried out in the Swiss Plateau that has undergone substantial urban sprawl in recent decades.Vascular plants and birds showed the strongest responses to urban sprawl, especially at the landscape scale, with non-native and ruderal plants proliferating and common generalist birds increasing at the expense of specialist birds as urban sprawl grew. Overall, urban area had the greatest contribution on such impacts, but additional effects of urban dispersion (i.e., increase of non-native plants) and human population density (i.e., increases of ruderal plants and common generalist birds) were found. Our findings support the hypothesis that negative impacts of urban sprawl on biodiversity can be reduced by compacting urban growth while still avoiding the formation of very densely populated areas.     

Farmers' Contribution to Agricultural Social Capital: Evidence from Southern Spain

Social capital is the whole set of shared norms, values, attitudes, and beliefs that promote cooperation among individuals within the community and that has proved to be a key factor in explaining development processes. This article aims to provide an analytically reliable notion of social capital within the farming sector and a methodological tool for empirically measuring how social capital is accumulated at the farmer level. The theoretical framework proposed is based on the multidimensionality of the complex concept of social capital. Thus, to develop a comprehensive index for social capital, we identify three dimensions of the concept, structural, relational, and cognitive social capital, each one also comprising several subdimensions. This integrative approach permits creation of a composite indicator of the agricultural social capital accumulated at the farmer level, further identifying socioeconomic factors that influence its accumulation at that level. We empirically apply this methodological approach to farmers in Andalusia in southern Spain as a case study. This research provides an interesting starting point for informing policymakers about social capital and helping them implement the necessary programs to facilitate sustainable development in the agricultural sector.     

An overlook on statistical inference issues for stochastic damping hamiltonian systems under the fluctuation-dissipation condition

ABSTRACT

In this paper, we are interested in nonparametric inference issues for stochastic damping hamiltonian systems under the fluctuation-dissipation condition. This condition relates the magnitude of the dissipative term and the magnitude of the random term. The precise balance between the drift term which removes energy in average and the stochastic term provided by the fluctuation-dissipation relation insures that the canonical measure is preserved by the dynamics. In this framework, it is possible to give an explicit construction of a Lyapunov function and thus to prove exponential ergodicity. Then, we consider various estimation procedures and provide also a numerical section, where simulations are conducted.     

Period Parity Progression Ratios and Birth Intervals in England and Wales, 1941–1971: A Synthetic Life Table Analysis

A method is presented for analysing maternity history data to provide period estimates of parity progression ratios, birth intervals and related indices. This is applied to a sample of the marriage and maternity histories from the Census of England and Wales of 1971 and shows: (a) a general increase through the 1950s and into the 1960s in period estimates of marriage and parity progression ratios, especially in the progression from first to second birth; (b) a general acceleration of fertility with, again, the second birth interval becoming particularly short and compact; and (c) very steep declines in third and fourth birth progression ratios from the mid-1960s. Birth interval distributions altered during the period examined. Decomposition of a progression-based total fertility index shows change in the ratios for lower birth orders to have dominated the fertility upswing and declines in ratios for higher birth orders to have initiated the subsequent decline.     

The Multi-dimensional Characteristics of Wellbeing: How Different Aspects of Wellbeing Interact and Do Not Interact with Each Other

Because wellbeing is a multi-varied and dynamic phenomenon, social scientists need to better understand how different aspects of people’s wellbeing are tied together and how these ties differ between individuals at one point in time and within individuals over time. The paper outlines a general model that considers the multidimensional structure of wellbeing. We utilize the potential of latent variable modelling on a unique Swedish database: the Panel Survey of Ageing and the Elderly (PSAE). An inclusive and flexible model that considers the interactions between semi-autonomous domains (material resources, health, psychosocial factors, lifestyle, etc.) is developed. Our empirical study is based on cross-sectional PSAE data and focuses on people 55 years or older (N = 5,374). The analysis takes advantage of recent developments in statistical theory in the field of latent variable modelling to bring about a more dynamic and theory confirming analysis of a multifaceted phenomenon such as wellbeing.     

A Theory of Macroprudential Policies in the Presence of Nominal Rigidities

We propose a theory of monetary policy and macroprudential interventions in financial markets. We focus on economies with nominal rigidities in goods and labor markets and subject to constraints on monetary policy, such as the zero lower bound or fixed exchange rates. We identify an aggregate demand externality that can be corrected by macroprudential interventions in financial markets. Ex post, the distribution of wealth across agents affects aggregate demand and output. Ex ante, however, these effects are not internalized in private financial decisions. We provide a simple formula for the required financial interventions that depends on a small number of measurable sufficient statistics. We also characterize optimal monetary policy. We extend our framework to incorporate pecuniary externalities, providing a unified approach to both externalities. Finally, we provide a number of applications which illustrate the relevance of our theory.     

Investigating impacts of complex sampling on latent growth curve modelling

We investigate the impacts of complex sampling on point and standard error estimates in latent growth curve modelling of survey data. Methodological issues are illustrated with empirical evidence from the analysis of longitudinal data on life satisfaction trajectories using data from the British Household Panel Survey, a national representative survey in Great Britain. A multi-process second-order latent growth curve model with conditional linear growth is used to study variation in the two perceived life satisfaction latent factors considered. The benefits of accounting for the complex survey design are considered, including obtaining unbiased both point and standard error estimates, and therefore correctly specified confidence intervals and statistical tests. We conclude that, even for the rather elaborated longitudinal data models that were considered, estimation procedures are affected by variance-inflating impacts of complex sampling.