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The number of alien plants escaping from cultivation into native ecosystems is increasing steadily. We provide an overview of the historical, contemporary and potential future roles of ornamental horticulture in plant invasions. We show that currently at least 75% and 93% of the global naturalised alien flora is grown in domestic and botanical gardens, respectively. Species grown in gardens also have a larger naturalised range than those that are not. After the Middle Ages, particularly in the 18th and 19th centuries, a global trade network in plants emerged. Since then, cultivated alien species also started to appear in the wild more frequently than non-cultivated aliens globally, particularly during the 19th century. Horticulture still plays a prominent role in current plant introduction, and the monetary value of live-plant imports in different parts of the world is steadily increasing. Historically, botanical gardens - an important component of horticulture - played a major role in displaying, cultivating and distributing new plant discoveries. While the role of botanical gardens in the horticultural supply chain has declined, they are still a significant link, with one-third of institutions involved in retail-plant sales and horticultural research. However, botanical gardens have also become more dependent on commercial nurseries as plant sources, particularly in North America. Plants selected for ornamental purposes are not a random selection of the global flora, and some of the plant characteristics promoted through horticulture, such as fast growth, also promote invasion. Efforts to breed non-invasive plant cultivars are still rare. Socio-economical, technological, and environmental changes will lead to novel patterns of plant introductions and invasion opportunities for the species that are already cultivated. We describe the role that horticulture could play in mediating these changes. We identify current research challenges, and call for more research efforts on the past and current role of horticulture in plant invasions. This is required to develop science-based regulatory frameworks to prevent further plant invasions.
Pri ha-Pardes (Früchte des Obstgartens) ist eine Reihe der Vereinigung für Jüdische Studien e.V., welche in Verbindung mit dem Institut für Jüdische Studien der Universität Potsdam publiziert wird. Pri ha-Pardes möchte kleineren wissenschaftlichen Studien, Forschungen am Rande der großen Disziplinen und exzellenten Masterarbeiten eine Publikationsplattform bieten. Im dritten Band der Reihe Pri ha-Pardes beleuchtet Christoph Kühn das Leben jüdischer Delinquenten im frühneuzeitlichen Deutschland. Jüdische Delinquenten lebten – in unterschiedlichem Maße – am Rande sowohl der christlichen als auch der jüdischen Gesellschaft. Diese doppelte Marginalisierung wird in dem vorliegenden Band untersucht. Die Frühe Neuzeit ist eine Epoche, in der sich das jüdische Leben meist außerhalb urbaner Zentren abspielte, die Epoche des Landjudentums. Ein Resultat ökonomischer und sozialer Restriktionen waren umherziehende Gruppen von Betteljuden, aus denen sich wiederum Teile der jüdischen Delinquenten rekrutierten. Jüdische Sozialeinrichtungen waren für die oft überregional agierenden delinquenten Juden eine lebensnotwenige Infrastruktur. Jedoch nicht alle Delinquenten gehörten zu den Nichtsesshaften. Die Verbundenheit zur jüdischen Gemeinschaft blieb meist bestehen, auch wenn das „Gaunerleben“ nicht immer von großer Frömmigkeit geprägt war. Für jüdische Gemeinden war es nicht einfach, zwischen ehrbaren und delinquenten Juden zu unterscheiden. Im Falle einer Missetat reichten die Reaktionen von öffentlicher Rüge bis zum großen Bann. Seitens der christlichen Obrigkeit wurden gegen Juden keine spezifischen Strafen verhängt, obgleich negative Vorstellungen von einer „typisch jüdischen“ Delinquenz virulent waren.
MULTILIT
(2015)
This paper presents an overview of the linguistic analyses developed in the MULTILIT project and the processing of the oral and written texts collected. The project investigates the language abilities of multilingual children and adolescents, in particular, those who have Turkish and/or Kurdish as a mother tongue. A further aim of the project is to examine from a psycholinguistic and sociolinguistic perspective the extent to which competence in academic registers is achieved on the basis of the languages spoken by the children, including the language(s) spoken at the home, the language of the country of residence and the first foreign language. To be able to examine these questions using corpus linguistic parameters, we created categories of analysis in MULTILIT.
The data collection comprises texts from bilingual and monolingual children and adolescents in Germany in their first language Turkish, their second language German und their foreign language English. Pupils aged between nine and twenty years of age produced monologue oral and written texts in the two genres of narrative and discursive. On the basis of these samples, we examine linguistic features such as lexical expression (lexical density, lexical diversity), syntactic complexity (syntactic and discursive packaging) as well as phonology in the oral texts and orthography in the written texts, with the aim of investigating the pupils’ growing mastery of these features in academic and informal registers.
To this end the raw data have been transcribed by the use of transcription conventions developed especially for the needs of the MULTILIT data. They are based on the commonly used HIAT and GAT transcription conventions and supplemented with conventions that provide additional information such as features at the graphic level.
The categories of analysis comprise a large number of linguistic categories such as word classes, syntax, noun phrase complexity, complex verbal morphology, direct speech and text structures. We also annotate errors and norm deviations at a wide range of levels (orthographic, morphological, lexical, syntactic and textual). In view of the different language systems, these criteria are considered separately for all languages investigated in the project.
Ultrafast and Energy-Efficient Quenching of Spin Order: Antiferromagnetism Beats Ferromagnetism
(2017)
By comparing femtosecond laser pulse induced ferro- and antiferromagnetic dynamics in one and the same material-metallic dysprosium-we show both to behave fundamentally different. Antiferromagnetic order is considerably faster and much more efficiently reduced by optical excitation than its ferromagnetic counterpart. We assign the fast and extremely efficient process in the antiferromagnet to an interatomic transfer of angular momentum within the spin system. Our findings imply that this angular momentum transfer channel is effective in other magnetic metals with nonparallel spin alignment. They also point out a possible route towards energy-efficient spin manipulation for magnetic devices.
We study prediction problems in which the conditional distribution of the output given the input varies as a function of task variables which, in our applications, represent space and time. In varying-coefficient models, the coefficients of this conditional are allowed to change smoothly in space and time; the strength of the correlations between neighboring points is determined by the data. This is achieved by placing a Gaussian process (GP) prior on the coefficients. Bayesian inference in varying-coefficient models is generally intractable. We show that with an isotropic GP prior, inference in varying-coefficient models resolves to standard inference for a GP that can be solved efficiently. MAP inference in this model resolves to multitask learning using task and instance kernels. We clarify the relationship between varying-coefficient models and the hierarchical Bayesian multitask model and show that inference for hierarchical Bayesian multitask models can be carried out efficiently using graph-Laplacian kernels. We explore the model empirically for the problems of predicting rent and real-estate prices, and predicting the ground motion during seismic events. We find that varying-coefficient models with GP priors excel at predicting rents and real-estate prices. The ground-motion model predicts seismic hazards in the State of California more accurately than the previous state of the art.