Innovatives Lehren und Lernen durch die Integration tiergestützter Pädagogik: Am Beispiel der Studieneinrichtung Event- und Sportmanagement

Der vorliegende Beitrag zeigt ein tiergestütztes Lehr-Lern-Projekt. Neben der Vermittlung der Lernziele gab es im Hinblick auf den Tiereinsatz vor allem eine Herausforderung: es sollten didaktische Möglichkeiten für den Hundeeinsatz im Hochschulbereich gefunden und darauf aufbauend ein hochschuldidaktisches, tiergestütztes Pädagogikkonzept erarbeitet werden. Die didaktischen Instrumente und Einsatzmöglichkeiten sollten den Co-Pädagogen so einbinden, dass er organisatorische und kompetenzvermittelnde Aufgaben übernehmen und die ihm zugeschriebenen Kompetenzen vermitteln konnte. Für die Umsetzung wurden Rituale und Übungen mit dem Therapiehund erarbeitet und Kurzreflexionen sowie eine ausführliche Abschlussevaluation umgesetzt

Differential effects of plant diversity on functional trait variation of grass species

Background and Aims Functional trait differences and trait adjustment in response to influences of the biotic environment could reflect niche partitioning among species. In this study, we tested how variation in above-ground plant traits, chosen as indicators for light and nitrogen acquisition and use, differs among taxonomically closely related species (Poaceae) to assess their potential for niche segregation at increasing plant diversity. Methods Traits of 12 grass species were measured in experimental grasslands (Jena Experiment) of varying species richness (from 1 to 60) and presence of particular functional groups (grasses, legumes, tall herbs and small herbs). Key Results Grass species increased shoot and leaf length, investment into supporting tissue (stem mass fraction) and specific leaf area as well as reduced foliar δ13C values with increasing species richness, indicating higher efforts for light acquisition. These species-richness effects could in part be explained by a higher probability of legume presence in more diverse communities. Leaf nitrogen concentrations increased and biomas s : N ratios in shoots decreased when grasses grew with legumes, indicating an improved nitrogen nutrition. Foliar δ15N values of grasses decreased when growing with legumes suggesting the use of depleted legume-derived N, while decreasing δ15N values with increasing species richness indicated a shift in the uptake of different N sources. However, efforts to optimize light and nitrogen acquisition by plastic adjustment of traits in response to species richness and legume presence, varied significantly among grass species. It was possible to show further that trait adjustment of grass species increased niche segregation in more diverse plant communities but that complementarity through niche separation may differ between light and nutrient acquisition. Conclusions The results suggest that even among closely related species such as grasses different strategies are used to cope with neighbours. This lack in redundancy in turn may facilitate complementary resource use and coexistenc

METAdata and metaDATA

Metadata are a very broad and extremely differentiated subject and ranges from rudimentary catalog data to deeply indexed scientific catalogs (e.g., catalogs of works). In this paper, the concept of metadata in the context of MEI is first examined, before two examples are used to show that metadata are more than just rudimentary descriptions. These examples are also intended to illustrate the extent to which metadata are encoded in the field of music philology and thus represent an attempt to create a little more awareness for the work of the Metadata and Cataloging Interest Group of MEI. The examples deal on the one hand with the encoding of performance resources and on the other hand with watermarks. In both cases, the possibilities of metadata encoding with MEI version 4 are exhausted and it is discussed which steps are useful and necessary to create an even deeper, machine-readable structure so that these sub-fields of the MEI metadata can also be used for larger scientific purposes such as analyses

DigiMOF: A Database of Metal–Organic Framework Synthesis Information Generated via Text Mining

The vastness of materials space, particularly that which is concerned with metal–organic frameworks (MOFs), creates the critical problem of performing efficient identification of promising materials for specific applications. Although high-throughput computational approaches, including the use of machine learning, have been useful in rapid screening and rational design of MOFs, they tend to neglect descriptors related to their synthesis. One way to improve the efficiency of MOF discovery is to data-mine published MOF papers to extract the materials informatics knowledge contained within journal articles. Here, by adapting the chemistry-aware natural language processing tool, ChemDataExtractor (CDE), we generated an open-source database of MOFs focused on their synthetic properties: the DigiMOF database. Using the CDE web scraping package alongside the Cambridge Structural Database (CSD) MOF subset, we automatically downloaded 43,281 unique MOF journal articles, extracted 15,501 unique MOF materials, and text-mined over 52,680 associated properties including the synthesis method, solvent, organic linker, metal precursor, and topology. Additionally, we developed an alternative data extraction technique to obtain and transform the chemical names assigned to each CSD entry in order to determine linker types for each structure in the CSD MOF subset. This data enabled us to match MOFs to a list of known linkers provided by Tokyo Chemical Industry UK Ltd. (TCI) and analyze the cost of these important chemicals. This centralized, structured database reveals the MOF synthetic data embedded within thousands of MOF publications and contains further topology, metal type, accessible surface area, largest cavity diameter, pore limiting diameter, open metal sites, and density calculations for all 3D MOFs in the CSD MOF subset. The DigiMOF database and associated software are publicly available for other researchers to rapidly search for MOFs with specific properties, conduct further analysis of alternative MOF production pathways, and create additional parsers to search for additional desirable properties

Trait means, trait plasticity and trait differences to other species jointly explain species performances in grasslands of varying diversity

Functional traits may help to explain the great variety of species performances in plant communities, but it is not clear whether the magnitude of trait values of a focal species or trait differences to co‐occurring species are key for trait‐based predictions. In addition, trait expression within species is often plastic, but this variation has been widely neglected in trait‐based analyses. We studied functional traits and plant biomass of 59 species in 66 experimental grassland mixtures of varying species richness (Jena Experiment). We related mean species performances (species biomass and relative yield RY) and their plasticities along the diversity gradient to trait‐based pedictors involving mean species traits (Tmean), trait plasticities along the diversity gradient (Tslope), extents of trait variation across communities (TCV; coefficient of variation) and hierarchical differences (Tdiff) and trait distances (absolute values of trait differences Tdist) between focal and co‐occurring species. Tmean (30–55%) and Tdiff (30–33%) explained most variation in mean species performances and their plasticities, but Tslope (20–25%) was also important in explaining mean species performances. The mean species traits and the trait differences between focal species and neighbors with the greatest explanatory power were related to plant size and stature (shoot length, mass:height ratios) and leaf photosynthetic capacity (specific leaf area, stable carbon isotopes and leaf nitrogen concentration). The contribution of trait plasticities in explaining species performances varied in direction (positive or negative) and involved traits related to photosynthetic capacity, nitrogen acquisition (nitrogen concentrations and stable isotopes) as well as structural stability (shoot carbon concentrations). Our results suggest that incorporating plasticity in trait expression as well as trait differences to co‐occurring species is critical for extending trait‐based analyses to understand the assembly of plant communities and the contribution of individual species in structuring plant communities

DigiMOF: a database of metal–organic framework synthesis information generated via text mining

The vastness of materials space, particularly that which is concerned with metal-organic frameworks (MOFs), creates the critical problem of performing efficient identification of promising materials for specific applications. Although high-throughput computational approaches, including the use of machine learning, have been useful in rapid screening and rational design of MOFs, they tend to neglect descriptors related to their synthesis. One way to improve the efficiency of MOF discovery is to data-mine published MOF papers to extract the materials informatics knowledge contained within journal articles. Here, by adapting the chemistry-aware natural language processing tool, ChemDataExtractor (CDE), we generated an open-source database of MOFs focused on their synthetic properties: the DigiMOF database. Using the CDE web scraping package alongside the Cambridge Structural Database (CSD) MOF subset, we automatically downloaded 43,281 unique MOF journal articles, extracted 15,501 unique MOF materials, and text-mined over 52,680 associated properties including the synthesis method, solvent, organic linker, metal precursor, and topology. Additionally, we developed an alternative data extraction technique to obtain and transform the chemical names assigned to each CSD entry in order to determine linker types for each structure in the CSD MOF subset. This data enabled us to match MOFs to a list of known linkers provided by Tokyo Chemical Industry UK Ltd. (TCI) and analyze the cost of these important chemicals. This centralized, structured database reveals the MOF synthetic data embedded within thousands of MOF publications and contains further topology, metal type, accessible surface area, largest cavity diameter, pore limiting diameter, open metal sites, and density calculations for all 3D MOFs in the CSD MOF subset. The DigiMOF database and associated software are publicly available for other researchers to rapidly search for MOFs with specific properties, conduct further analysis of alternative MOF production pathways, and create additional parsers to search for additional desirable properties

Origin context of trait data matters for predictions of community performance in a grassland biodiversity experiment

Plant functional traits may explain the positive relationship between species richness and ecosystem functioning, but species‐level trait variation in response to growth conditions is often ignored in trait‐based predictions of community performance. In a large grassland biodiversity experiment (Jena Experiment), we measured traits on plants grown as solitary individuals, in monocultures or in mixtures. We calculated two measures of community‐level trait composition, i.e., community‐weighted mean traits (CWM) and trait diversity (Rao's quadratic entropy; FD) based on different contexts in which traits were measured (trait origins). CWM and FD values of the different measurement origins were then compared regarding their power to predict community biomass production and biodiversity effects quantified with the additive partitioning method. Irrespective of trait origin, models combining CWM and FD values as predictors best explained community biomass and biodiversity effects. CWM values based on monoculture, mixture‐mean or community‐specific trait data were similarly powerful predictors, but predictions became worse when trait values originated from solitary‐grown individuals. FD values based on monoculture traits were the best predictors of community biomass and net biodiversity effects, while FD values based on community‐specific traits were the best predictors for complementarity and selection effects. Traits chosen as best CWM predictors were not strongly affected by trait origin but traits chosen as best FD predictors varied strongly dependent on trait origin and altered the predictability of community performance. We conclude that by adjusting their functional traits to species richness and even specific community compositions, plants can change community‐level trait compositions, thereby also changing community biomass production and biodiversity effects. Incorporation of these plastic trait adjustments of plants in trait‐based ecology can improve its predictive power in explaining biodiversity–ecosystem functioning relationships

Watermarks and Where to Find Them: Digitisation, Recognition, and Automated Clustering of Watermarks in the Music Manuscripts of Franz Schubert

Our project focuses on watermarks found in the music manuscripts of Franz Schubert. The endeavour incorporates thermography, machine learning and signal processing to produce digitized watermarks for databases and manuscript descriptions as well as to curtail the approximate dating of some undated autographs. By applying fingerprint recognition software to the acquired thermographic watermark images, a new method for automatic clustering will be established. MEI will be used as the system’s foundation for data presentation online and to guarantee long-term archiving and open source access. As MEI currently does not provide a best practice for encoding watermark information, a standardized form will be developed in collaboration with the community

Drought reduces floral resources for pollinators

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record.Climate change is predicted to result in increased occurrence and intensity of drought in many regions worldwide. By increasing plant physiological stress, drought is likely to affect the floral resources (flowers, nectar and pollen) that are available to pollinators. However, little is known about impacts of drought at the community level, nor whether plant community functional composition influences these impacts. To address these knowledge gaps, we investigated the impacts of drought on floral resources in calcareous grassland. Drought was simulated using rain shelters and the impacts were explored at multiple scales and on four different experimental plant communities varying in functional trait composition. First, we investigated the effects of drought on nectar production of three common wildflower species (Lathyrus pratensis, Onobrychis viciifolia and Prunella vulgaris). In the drought treatment, L. pratensis and P. vulgaris had a lower proportion of flowers containing nectar and O. viciifolia had fewer flowers per raceme. Second, we measured the effects of drought on the diversity and abundance of floral resources across plant communities. Drought reduced the abundance of floral units for all plant communities, irrespective of functional composition, and reduced floral species richness for two of the communities. Functional diversity did not confer greater resistance to drought in terms of maintaining floral resources, probably because the effects of drought were ubiquitous across component plant communities. The findings indicate that drought has a substantial impact on the availability of floral resources in calcareous grassland, which will have consequences for pollinator behaviour and populations. We would like to thank Nigel Follett for use of the site, and Victoria Mallott, Rachel McDonald and Joanna Savage for assistance with fieldwork. BP would like to thank The Access & Achievement Foundation and the Haberdashers’ Educational Foundation for personal financial support. An earlier draft was greatly improved by comments from two anonymous reviewers. This study was part of the Wessex Biodiversity and Ecosystem Service Sustainability (BESS) project, funded under the BESS programme, and supported by the Natural Environment Research Council (Wessex BESS, ref. NE/J014680/1)

Towards MerMEId 2.0

The “Metadata Editor and Repository for MEI Data” (MerMEId) is a web-based tool to capture and enrich data in the MEI header. This tool was originally developed by Axel Teich Geertinger and Sigfrid Lundberg at the “Danish Centre for Music Editing”, under an open-source license. This poster describes the transfer of this project to community-based releases by members of the MerMEId community with a formal governance structure, towards a true open-source community venture