Much ado about not-very-much? Assessing ten years of German citizenship reform

This article examines the development and impact of German citizenship policy over the past decade. As its point of departure, it takes the 2000 Citizenship Law, which sought to undertake a full-scale reform and liberalisation of access to German membership. The article discusses this law’s content and subsequent amendments, focusing particularly on its quantitative impact, asking why the number of naturalisations has been lower than originally expected. The article outlines current challenges to the law’s structure operation and identifies potential trajectories for its future development

Masonry compressive strength prediction using artificial neural networks

The masonry is not only included among the oldest building materials, but it is also the most widely used material due to its simple construction and low cost compared to the other modern building materials. Nevertheless, there is not yet a robust quantitative method, available in the literature, which can reliably predict its strength, based on the geometrical and mechanical characteristics of its components. This limitation is due to the highly nonlinear relation between the compressive strength of masonry and the geometrical and mechanical properties of the components of the masonry. In this paper, the application of artificial neural networks for predicting the compressive strength of masonry has been investigated. Specifically, back-propagation neural network models have been used for predicting the compressive strength of masonry prism based on experimental data available in the literature. The comparison of the derived results with the experimental findings demonstrates the ability of artificial neural networks to approximate the compressive strength of masonry walls in a reliable and robust manner.- (undefined

Estimates of Particulate Organic Carbon Flowing from the Pelagic Environment to the Benthos through Sponge Assemblages

Despite the importance of trophic interactions between organisms, and the relationship between primary production and benthic diversity, there have been few studies that have quantified the carbon flow from pelagic to benthic environments as a result of the assemblage level activity of suspension-feeding organisms. In this study, we examine the feeding activity of seven common sponge species from the Taputeranga marine reserve on the south coast of Wellington in New Zealand. We analysed the diet composition, feeding efficiency, pumping rates, and the number of food particles (specifically picoplanktonic prokaryotic cells) retained by sponges. We used this information, combined with abundance estimates of the sponges and estimations of the total amount of food available to sponges in a known volume of water (89,821 m3), to estimate: (1) particulate organic carbon (POC) fluxes through sponges as a result of their suspension-feeding activities on picoplankton; and (2) the proportion of the available POC from picoplankton that sponges consume. The most POC acquired by the sponges was from non-photosynthetic bacterial cells (ranging from 0.09 to 4.69 g C d−1 with varying sponge percentage cover from 0.5 to 5%), followed by Prochlorococcus (0.07 to 3.47 g C d−1) and then Synechococcus (0.05 to 2.34 g C d−1) cells. Depending on sponge abundance, the amount of POC that sponges consumed as a proportion of the total POC available was 0.2–12.1% for Bac, 0.4–21.3% for Prochlo, and 0.3–15.8% for Synecho. The flux of POC for the whole sponge assemblage, based on the consumption of prokaryotic picoplankton, ranged from 0.07–3.50 g C m2 d−1. This study is the first to estimate the contribution of a sponge assemblage (rather than focusing on individual sponge species) to POC flow from three groups of picoplankton in a temperate rocky reef through the feeding activity of sponges and demonstrates the importance of sponges to energy flow in rocky reef environments

Data from an International Multi-Centre Study of Statistics and Mathematics Anxieties and Related Variables in University Students (the SMARVUS Dataset)

This large, international dataset contains survey responses from N = 12,570 students from 100 universities in 35 countries, collected in 21 languages. We measured anxieties (statistics, mathematics, test, trait, social interaction, performance, creativity, intolerance of uncertainty, and fear of negative evaluation), self-efficacy, persistence, and the cognitive reflection test, and collected demographics, previous mathematics grades, self-reported and official statistics grades, and statistics module details. Data reuse potential is broad, including testing links between anxieties and statistics/mathematics education factors, and examining instruments’ psychometric properties across different languages and contexts. Data and metadata are stored on the Open Science Framework website [https://osf.io/mhg94/]

European Red List of Habitats Part 1. Marine habitats

The European Red List of Habitats provides an overview of the risk of collapse (degree of endangerment) of marine, terrestrial and freshwater habitats in the European Union (EU28) and adjacent regions (EU28+), based on a consistent set of categories and criteria, and detailed data and expert knowledge from involved countries1. A total of 257 benthic marine habitat types were assessed. In total, 19% (EU28) and 18% (EU28+) of the evaluated habitats were assessed as threatened in categories Critically Endangered, Endangered and Vulnerable. An additional 12% were Near Threatened in the EU28 and 11% in the EU28+. These figures are approximately doubled if Data Deficient habitats are excluded. The percentage of threatened habitat types differs across the regional seas. The highest proportion of threatened habitats in the EU28 was found in the Mediterranean Sea (32%), followed by the North-East Atlantic (23%), the Black Sea (13%) and then the Baltic Sea (8%). There was a similar pattern in the EU28+. The most frequently cited pressures and threats were similar across the four regional seas: pollution (eutrophication), biological resource use other than agriculture or forestry (mainly fishing but also aquaculture), natural system modifications (e.g. dredging and sea defence works), urbanisation and climate change. Even for habitats where the assessment outcome was Data Deficient, the Red List assessment process has resulted in the compilation of a substantial body of useful information to support the conservation of marine habitats

Collaborative Database to Track Mass Mortality Events in the Mediterranean Sea

Anthropogenic climate change, and global warming in particular, has strong and increasing impacts on marine ecosystems (Poloczanska et al., 2013; Halpern et al., 2015; Smale et al., 2019). The Mediterranean Sea is considered a marine biodiversity hot-spot contributing to more than 7% of world's marine biodiversity including a high percentage of endemic species (Coll et al., 2010). The Mediterranean region is a climate change hotspot, where the respective impacts of warming are very pronounced and relatively well documented (Cramer et al., 2018). One of the major impacts of sea surface temperature rise in the marine coastal ecosystems is the occurrence of mass mortality events (MMEs). The first evidences of this phenomenon dated from the first half of'80 years affecting the Western Mediterranean and the Aegean Sea (Harmelin, 1984; Bavestrello and Boero, 1986; Gaino and Pronzato, 1989; Voultsiadou et al., 2011). The most impressive phenomenon happened in 1999 when an unprecedented large scale MME impacted populations of more than 30 species from different phyla along the French and Italian coasts (Cerrano et al., 2000; Perez et al., 2000). Following this event, several other large scale MMEs have been reported, along with numerous other minor ones, which are usually more restricted in geographic extend and/or number of affected species (Garrabou et al., 2009; Rivetti et al., 2014; Marbà et al., 2015; Rubio-Portillo et al., 2016, authors' personal observations). These events have generally been associated with strong and recurrent marine heat waves (Crisci et al., 2011; Kersting et al., 2013; Turicchia et al., 2018; Bensoussan et al., 2019) which are becoming more frequent globally (Smale et al., 2019). Both field observations and future projections using Regional Coupled Models (Adloff et al., 2015; Darmaraki et al., 2019) show the increase in Mediterranean sea surface temperature, with more frequent occurrence of extreme ocean warming events. As a result, new MMEs are expected during the coming years. To date, despite the efforts, neither updated nor comprehensive information can support scientific analysis of mortality events at a Mediterranean regional scale. Such information is vital to guide management and conservation strategies that can then inform adaptive management schemes that aim to face the impacts of climate change.MV-L was supported by a postdoctoral contract Juan de la Cierva-Incorporación (IJCI-2016-29329) of Ministerio de Ciencia, Innovación y Universidades. AI was supported by a Technical staff contract (PTA2015-10829-I) Ayudas Personal Técnico de Apoyo of Ministerio de Economía y Competitividad (2015). Interreg Med Programme (grant number Project MPA-Adapt 1MED15_3.2_M2_337) 85% cofunded by the European Regional Development Fund, the MIMOSA project funded by the Foundation Prince Albert II Monaco and the European Union's Horizon 2020 research and innovation programme under grant agreement no 689518 (MERCES). DG-G was supported by an FPU grant (FPU15/05457) from the Spanish Ministry of Education. J-BL was partially supported by the Strategic Funding UID/Multi/04423/2013 through national funds provided by FCT - Foundation for Science and Technology and European Regional Development Fund (ERDF), in the framework of the programme PT2020

Data from an International Multi-Centre Study of Statistics and Mathematics Anxieties and Related Variables in University Students (the SMARVUS Dataset)

This large, international dataset contains survey responses from N = 12,570 students from 100 universities in 35 countries, collected in 21 languages. We measured anxieties (statistics, mathematics, test, trait, social interaction, performance, creativity, intolerance of uncertainty, and fear of negative evaluation), self-efficacy, persistence, and the cognitive reflection test, and collected demographics, previous mathematics grades, self-reported and official statistics grades, and statistics module details. Data reuse potential is broad, including testing links between anxieties and statistics/mathematics education factors, and examining instruments’ psychometric properties across different languages and contexts