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Can outside interventions foster socio-culturally diverse friendships? We executed a large field experiment that randomized the seating charts of 182 3 rd through 8 th grade classrooms ( N = 2,966 students) for the duration of one semester. We found that being seated next to each other increased the probability of a mutual friendship from 15% to 22% on average. Furthermore, induced proximity increased the latent propensity toward friendship equally for all students, regardless of students’ dyadic similarity with respect to educational achievement, gender, and ethnicity. However, the probability of a manifest friendship increased more among similar than among dissimilar students—a pattern mainly driven by gender. Our findings demonstrate that a scalable light-touch intervention can affect face-to-face networks and foster diverse friendships in groups that already know each other, but they also highlight that transgressing boundaries, especially those defined by gender, remains an uphill battle.

This study examined the long-standing question of whether a person’s position among siblings has a lasting impact on that person’s life course. Empirical research on the relation between birth order and intelligence has convincingly documented that performances on psychometric intelligence tests decline slightly from firstborns to later-borns. By contrast, the search for birth-order effects on personality has not yet resulted in conclusive findings. We used data from three large national panels from the United States (n= 5,240), Great Britain (n= 4,489), and Germany (n= 10,457) to resolve this open research question. This database allowed us to identify even very small effects of birth order on personality with sufficiently high statistical power and to investigate whether effects emerge across different samples. We furthermore used two different analytical strategies by comparing siblings with different birth-order positions (i) within the same family (within-family design) and (ii) between different families (between-family design). In our analyses, we confirmed the expected birth-order effect on intelligence. We also observed a significant decline of a 10th of a SD in self-reported intellect with increasing birth-order position, and this effect persisted after controlling for objectively measured intelligence. Most important, however, we consistently found no birth-order effects on extraversion, emotional stability, agreeableness, conscientiousness, or imagination. On the basis of the high statistical power and the consistent results across samples and analytical designs, we must conclude that birth order does not have a lasting effect on broad personality traits outside of the intellectual domain.

The idea that birth-order position has a lasting impact on personality has been discussed for the past 100 years. Recent large-scale studies have indicated that birth-order effects on the Big Five personality traits are negligible. In the current study, we examined a variety of more narrow personality traits in a large representative sample (n = 6,500-10,500 in between-family analyses; n = 900-1,200 in within-family analyses). We used specification-curve analysis to assess evidence for birth-order effects across a range of models implementing defensible yet arbitrary analytical decisions (e.g., whether to control for age effects or to exclude participants on the basis of sibling spacing). Although specification-curve analysis clearly confirmed the previously reported birth-order effect on intellect, we found no meaningful effects on life satisfaction, locus of control, interpersonal trust, reciprocity, risk taking, patience, impulsivity, or political orientation. The lack of meaningful birth-order effects on self-reports of personality was not limited to broad traits but also held for more narrowly defined characteristics.

Remarkably heavy and devastating rainfalls affected large parts of Peru during the austral summer 2016–2017. These rainfalls favoured widespread land sliding and extensive flooding and generated one of the most severe disasters of Peru since the 1997–1998 El Niño event. The amount of rainfall recorded between January and March 2017 only compares to the biggest El Niño events of the last 40 years (i.e. 1982–1983 and 1997–1998) and exceeded the 90th percentile of available records (1981–2017) over much of the northern and central coasts of Peru, the Andean region and Amazonia. The occurrence of these heavy rainfalls was highly anomalous as it occurred during the first austral summer following the development and decay of a very strong El Niño in 2015–2016. Here, we propose that the likely cause of the anomalous rainfalls is linked to the combination of an especially intense wet spell over the Central Andes related to a deep, long-lasting anticyclone located adjacent to the Chilean coast, and to the unusual development of warm water off the coast of Peru in the nominal El Niño 1 + 2 region. This warming has been related to an anomalous weakening of the mid-upper level subtropical westerly flow, which in turn led to a weakening of the southeasterly trades off the coast, thus hindering the upwelling near the Peruvian coast and favoring the eastern Pacific warming. This development is counter to the usual evolution of sea surface temperature in the eastern equatorial Pacific following very strong El Niño events, such as those occurred in 1982–1983, 1997–1998, and 2015–2016. This paper explores the unusual nature of this event in the observational record and illustrates its consequences.

Climate time series are of major importance for base line studies for climate change impact and adaptation projects. However, for instance, in mountain regions and in developing countries there exist significant gaps in ground based climate records in space and time. Specifically, in the Peruvian Andes spatially and temporally coherent precipitation information is a prerequisite for ongoing climate change adaptation projects in the fields of water resources, disasters and food security. The present work aims at evaluating the ability of Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) to estimate precipitation rates at daily 0.25° × 0.25° scale in the Central Andes and the dependency of the estimate performance on changing spatial and temporal resolution. Comparison of the TMPA product with gauge measurements in the regions of Cuzco, Peru and La Paz, Bolivia were carried out and analysed statistically. Large biases are identified in both investigation areas in the estimation of daily precipitation amounts. The occurrence of strong precipitation events was well assessed, but their intensities were underestimated. TMPA estimates for La Paz show high false alarm ratio. The dependency of the TMPA estimate quality with changing resolution was analysed by comparisons of 1-, 7-, 15- and 30-day sums for Cuzco, Peru. The correlation of TMPA estimates with ground data increases strongly and almost linearly with temporal aggregation. The spatial aggregation to 0.5°, 0.75° and 1° grid box averaged precipitation and its comparison to gauge data of the same areas revealed no significant change in correlation coefficients and estimate performance. In order to profit from the TMPA combination product on a daily basis, a procedure to blend it with daily precipitation gauge measurements is proposed. Different sources of errors and uncertainties introduced by the sensors, sensor-specific algorithm aspects and the TMPA processing scheme are discussed. This study reveals the possibilities and restrictions of the use of TMPA estimates in the Central Andes and should assist other researchers in the choice of the best resolution-accuracy relationship according to requirements of their applications.

Damage caused by weather- and climate-related disasters have increased over the past decades, and growing exposure and wealth have been identified as main drivers of this increase. Disaster databases are a primary tool for the analysis of disaster characteristics and trends at global or national scales, and they support disaster risk reduction and climate change adaptation. However, the quality, consistency and completeness of different disaster databases are highly variable. Even though such variation critically influences the outcome of any study, comparative analyses of different databases are still rare to date. Furthermore, there is an unequal geographic distribution of current disaster trend studies, with developing countries being underrepresented. Here, we analyze three different disaster databases in the developing-country context of Peru: a global database (Emergency Events Database: EM-DAT), a multinational Latin American database (DesInventar) and a national database (Peruvian National Information System for the Prevention of Disasters: SINPAD). The analysis is performed across three dimensions: (1) spatial scales, from local to regional (provincial) and national scale; (2) timescales, from single events to decadal trends; and (3) disaster categories and metrics, including the number of single disaster event occurrence, or people killed and affected. Results show limited changes in disaster occurrence in the Cusco and ApurÍmac regions in southern Peru over the past four decades but strong positive trends in people affected at the national scale. We furthermore found large variations of the disaster metrics studied over different spatial and temporal scales, depending on the disaster database analyzed. We conclude and recommend that the type, method and source of documentation should be carefully evaluated for any analysis of disaster databases; reporting criteria should be improved and documentation efforts strengthened.

Open-ended questions have routinely been included in large-scale survey and panel studies, yet there is some perplexity about how to actually incorporate the answers to such questions into quantitative social science research. Tools developed recently in the domain of natural language processing offer a wide range of options for the automated analysis of such textual data, but their implementation has lagged behind. In this study, we demonstrate straightforward procedures that can be applied to process and analyze textual data for the purposes of quantitative social science research. Using more than 35,000 textual answers to the question “What else are you worried about?” from participants of the German Socio-economic Panel Study (SOEP), we (1) analyzed characteristics of respondents that determined whether they answered the open-ended question, (2) used the textual data to detect relevant topics that were reported by the respondents, and (3) linked the features of the respondents to the worries they reported in their textual data. The potential uses as well as the limitations of the automated analysis of textual data are discussed.

The role of glaciers as temporal water reservoirs is particularly pronounced in the (outer) tropics because of the very distinct wet/dry seasons. Rapid glacier retreat caused by climatic changes is thus a major concern, and decision makers demand urgently for regional/local glacier evolution trends, ice mass estimates and runoff assessments. However, in remote mountain areas, spatial and temporal data coverage is typically very scarce and this is further complicated by a high spatial and temporal variability in regions with complex topography. Here, we present an approach on how to deal with these constraints. For the Cordillera Vilcanota (southern Peruvian Andes), which is the second largest glacierized cordillera in Peru (after the Cordillera Blanca) and also comprises the Quelccaya Ice Cap, we assimilate a comprehensive multi-decadal collection of available glacier and climate data from multiple sources (satellite images, meteorological station data and climate reanalysis), and analyze them for respective changes in glacier area and volume and related trends in air temperature, precipitation and in a more general manner for specific humidity. While we found only marginal glacier changes between 1962 and 1985, there has been a massive ice loss since 1985 (about 30% of area and about 45% of volume). These high numbers corroborate studies from other glacierized cordilleras in Peru. The climate data show overall a moderate increase in air temperature, mostly weak and not significant trends for precipitation sums and probably cannot in full explain the observed substantial ice loss. Therefore, the likely increase of specific humidity in the upper troposphere, where the glaciers are located, is further discussed and we conclude that it played a major role in the observed massive ice loss of the Cordillera Vilcanota over the past decades.

Connections between interindividual differences and people’s behavior has been widely researched in various contexts, often by using top-down group comparisons to explain interindividual differences. In contrast, in this study, we apply a bottom-up approach in which we identify meaningful clusters in people’s concerns about various areas of life (e.g., their own health, their financial situation, the environment). We apply a novel method, Dirichlet clustering, to large-scale longitudinal data from the German Socioeconomic Panel Study (SOEP) to investigate whether concerns of people living in Germany evaluated in 2010 (t0) cluster participants into robust and separable groups, and whether these groups vary regarding their party identification in 2017 (t0 + 7). Clustering results suggest a range of different groups with specific concern patterns. Some of these notably specific patterns of concerns indicate links to party identification. In particular, some patterns show an increased identification with smaller parties as the ‘Bündnis 90/Die Grünen’ (‘Greens’), the left wing party ‘Die Linke’ (‘The Left’) or the right-wing party ‘Alternative für Deutschland’ (‘Alternative for Germany’, AfD). Considering that we identify as many as 37 clusters in total, among them at least six with clearly different party identification, it can also be concluded that the complexity of political concerns may be larger than has been assumed before.

[This corrects the article DOI: 10.1371/journal.pone.0212944.].