Search

Do countries with less democratic forms of government necessarily have lower literacy rates as a consequence? Using a random sample of more than 9000 individuals from military archives in 20th century Portugal, we show that 20-year old males were 50% more likely to end up literate under a nondemocratic regime than under a more democratic one. Our results are robust to controlling for a host of factors including economic growth, the disease environment, and regional fixed effects. We argue for a political economy and cultural explanation for the relative success of the authoritarian regime in promoting basic education. [ABSTRACT FROM AUTHOR]

Abstract: Mobile phone datasets allow for the analysis of human behavior on an unprecedented scale. The social network, temporal dynamics and mobile behavior of mobile phone users have often been analyzed independently from each other using mobile phone datasets. In this article, we explore the connections between various features of human behavior extracted from a large mobile phone dataset. Our observations are based on the analysis of communication data of 100,000 anonymized and randomly chosen individuals in a dataset of communications in Portugal. We show that clustering and principal component analysis allow for a significant dimension reduction with limited loss of information. The most important features are related to geographical location. In particular, we observe that most people spend most of their time at only a few locations. With the help of clustering methods, we then robustly identify home and office locations and compare the results with official census data. Finally, we analyze the geographic spread of users’ frequent locations and show that commuting distances can be reasonably well explained by a gravity model. [Copyright &y& Elsevier]

Abstract: Bats are often killed in large numbers at wind farms over a wide geographical range. We aimed to predict which areas conferred higher fatality risks to bats at wind farms. In an innovative approach, we combined species distribution modelling with mortality data and the ecological conditions at wind farms located in Portugal. We then generated predictive models to determine areas of probable mortality and which environmental factors were promoting it. Mortality data for four bat species, Hypsugo savii, Nyctalus leisleri, Pipistrellus kuhlii and Pipistrellus pipistrellus, were used. These experienced the highest levels of fatalities at wind farms in Portugal, comprising 290 of the 466 fatalities recorded from 2003 to 2011. The mortality risk models showed robust performances. Wind farms sited at humid areas with mild temperatures, closer than 5km to forested areas and within 600m of steep slopes showed higher probabilities of mortality. High mortality risk areas also overlapped highly with the potential distribution of N. leisleri in Portugal, suggesting that populations of this species may be at high risk due to wind farm fatalities. Moreover, a large extent of the area predicted to be a hotspot for mortality (i.e. areas likely to confer high mortality risk for four species) overlaps with sites highly suitable for wind farm construction. In summary, the approach used in this study could be paradigmatic for the development of important pre-emptive conservation measures for bat populations by identifying mortality risk in areas prior to wind farm installation and determining which conditions promote mortality. [Copyright &y& Elsevier]

Abstract: According to the Water Framework Directive (WFD) transitional waters should be differentiated according to type and, in some cases, divided into different water bodies. This raises a dilemma in trying to define parts of a continuum. In the sequence of WFD several indices have been proposed including the Estuarine Fish Assessment Index, which can be applied taking an estuary as a whole (EFAI – without water bodies division) or divided in water bodies (EFAIWB). The purpose of this work is to analyze the robustness of the Estuarine Fish Assessment Index, based on three different ways of dividing Portuguese estuaries into water bodies according to different criteria (criterion 1 – distance to the estuary mouth, criterion 2 – salinity and criterion 3 – morphology, salinity and human dimension as pressure and state). In this study we evaluated at which degree these three criteria could influence the ecological quality ratio (EQR) results, when the index was applied to water body level (EFAIWB). Also, for each estuary, the EQRWB results for each criterion of EFAIWB were combined and weighted according to the water bodies areas (EFAI overall weighted – EFAIOW). Finally, it was compared if the results obtained for each criterion with the EFAIOW were similar to the results of the index application taking the estuary as a whole (EFAI – without water bodies division). No significant differences were found in both cases, which indicated that this index is a robust method regarding the division of the estuaries in different water bodies, which is an important element of a fish-based multimetric tool for assessing estuarine ecological quality. However, in some cases, different ecological quality statuses were achieved when applying the EFAIOW or the EFAI. This work addressed several aspects regarding the possible division of water bodies at the WFD context. [Copyright &y& Elsevier]

Abstract: Portugal is faced with important challenges concerning the definition of policies to achieve energy and environmental targets, taking also into account the economic and social issues. A multi-sectoral economy–energy–environment model has been developed to perform a prospective analysis of the changes in the economic structure and the energy system, as well as to assess the corresponding environmental impacts, providing decision support in policy making. This model is a multi-objective linear programming model that allows for the explicit consideration of distinct axes of evaluation, generally conflicting and non-commensurate, of the merit of distinct policies. The policy recommendations obtained are subject to the inherent uncertainty associated with the model coefficients and, therefore, they may not be robust in face of changes of the input data. The specification of less energy or carbon-intensive technologies is done by considering pollutant/energy coefficients defined as intervals. This analysis is crucial for understanding the role of technology in carbon mitigation efforts and other energy system planning settings, allowing to explore the effects of distinct policies on the total system costs, the fuel and technology mix, and the levels of greenhouse gases and other emissions. [Copyright &y& Elsevier]