@inproceedings{BorowskiGlowinskiFristeretal.2018, author = {Borowski, Andreas and Glowinski, Ingrid and Frister, Jonas and H{\"o}ttecke, Dietmar and Buth, Katrin and Koenen, Jenna and Masanek, Nicole and Reichwein, Wilko and Scholten, Nina and Sprenger, Sandra and Stender, Peter and W{\"o}hlke, Carina and Komorek, Michael and Freckmann, Janine and Hofmann, Josefine and Niesel, Verena and Richter, Chris and Mehlmann, Nelli and Bikner-Ahsbahs, Angelika and Unverricht, Katja and Schanze, Sascha and Bittorf, Robert Marten and Meier, Monique and Grospietsch, Finja and Mayer, J{\"u}rgen and Gimbel, Katharina and Ziepprecht, Kathrin and Hofmann, Judith and Kramer, Charlotte and M{\"u}ller, Britta-Kornelia and Rohde, Andreas and Z{\"u}hlsdorf, Felix and Winkler, Iris and Laging, Ralf and Peter, Carina and Schween, Michael and H{\"a}rle, Gerhard and Busse, Beatrix and Mahner, Sebastian and K{\"o}stler, Verena and Kufner, Sabrina and M{\"a}gdefrau, Jutta and M{\"u}ller, Christian and Beck, Christina and Kriehuber, Eva and Boch, Florian and Engl, Anna-Teresa and Helzel, Andreas and Pickert, Tina and Reiter, Christian and Blasini, Bettina and Nerdel, Claudia and Lewalter, Doris and Schiffhauer, Silke and Richter-Gebert, J{\"u}rgen and Bannert, Maria and Maahs, Mirjam and Reißner, Maria and Ungar, Patrizia and von Wachter, Jana-Kristin and Hellmann, Katharina and Zaki, Katja and Pohlenz, Philipp}, title = {Koh{\"a}renz in der universit{\"a}ren Lehrerbildung}, editor = {Glowinski, Ingrid and Borowski, Andreas and Gillen, Julia and Schanze, Sascha and von Meien, Joachim}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, isbn = {978-3-86956-438-8}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-414267}, year = {2018}, abstract = {One area that is supported by the project "Qualit{\"a}tsoffensive Lehrerbildung" (funded by BMBF) is the improvement of collaboration and coordination between studies in the discipline, studies in pedagogical content knowledge, and studies in pedagogical knowledge during teacher education at university. Aiming a better coordination among these three parts of teacher education at university, many of the supported projects have designed and realized university-specific approaches. This conference proceedings volume comprises contributions by 15 of these projects. Seven of those were introduced and discussed in workshops on the occasion of two cross-regional project-conferences in Hannover and Potsdam. Overall, the contributions give a theoretically funded as well as a practice-oriented overview of current approaches and concepts to achieve a better connection between study units concerning studies in content knowledge, pedagogical content knowledge and pedagogical knowledge in teacher education. The volume presents university projects, which take effect on different levels (at the level of curriculum and content, at a collegiate level, at the level of structural conditions of universities). The different approaches are described in a way that they can provide a basis for transfer to other subjects or further universities. The contributions are aimed at teacher educators as well as other actors working in the field of teaching- and quality development at universities. All of them can take transferable ideas and impulses from the described concepts and formats.}, language = {de} } @article{SchwiederWesemeyerFrantzetal.2022, author = {Schwieder, Marcel and Wesemeyer, Maximilian and Frantz, David and Pfoch, Kira and Erasmi, Stefan and Pickert, J{\"u}rgen and Nendel, Claas and Hostert, Patrick}, title = {Mapping grassland mowing events across Germany based on combined Sentinel-2 and Landsat 8 time series}, series = {Remote sensing of environment}, volume = {269}, journal = {Remote sensing of environment}, publisher = {Elsevier}, address = {New York}, issn = {0034-4257}, doi = {10.1016/j.rse.2021.112795}, pages = {16}, year = {2022}, abstract = {Spatially explicit knowledge on grassland extent and management is critical to understand and monitor the impact of grassland use intensity on ecosystem services and biodiversity. While regional studies allow detailed insights into land use and ecosystem service interactions, information on a national scale can aid biodiversity assessments. However, for most European countries this information is not yet widely available. We used an analysis-ready-data cube that contains dense time series of co-registered Sentinel-2 and Landsat 8 data, covering the extent of Germany. We propose an algorithm that detects mowing events in the time series based on residuals from an assumed undisturbed phenology, as an indicator of grassland use intensity. A self-adaptive ruleset enabled to account for regional variations in land surface phenology and non-stationary time series on a pixelbasis. We mapped mowing events for the years from 2017 to 2020 for permanent grassland areas in Germany. The results were validated on a pixel level in four of the main natural regions in Germany based on reported mowing events for a total of 92 (2018) and 78 (2019) grassland parcels. Results for 2020 were evaluated with combined time series of Landsat, Sentinel-2 and PlanetScope data. The mean absolute percentage error between detected and reported mowing events was on average 40\% (2018), 36\% (2019) and 35\% (2020). Mowing events were on average detected 11 days (2018), 7 days (2019) and 6 days (2020) after the reported mowing. Performance measures varied between the different regions of Germany, and lower accuracies were found in areas that are revisited less frequently by Sentinel-2. Thus, we assessed the influence of data availability and found that the detection of mowing events was less influenced by data availability when at least 16 cloud-free observations were available in the grassland season. Still, the distribution of available observations throughout the season appeared to be critical. On a national scale our results revealed overall higher shares of less intensively mown grasslands and smaller shares of highly intensively managed grasslands. Hotspots of the latter were identified in the alpine foreland in Southern Germany as well as in the lowlands in the Northwest of Germany. While these patterns were stable throughout the years, the results revealed a tendency to lower management intensity in the extremely dry year 2018. Our results emphasize the ability of the approach to map the intensity of grassland management throughout large areas despite variations in data availability and environmental conditions.}, language = {en} } @article{KamaliStellaBergMohnickeetal.2022, author = {Kamali, Bahareh and Stella, Tommaso and Berg-Mohnicke, Michael and Pickert, J{\"u}rgen and Groh, Jannis and Nendel, Claas}, title = {Improving the simulation of permanent grasslands across Germany by using multi-objective uncertainty-based calibration of plant-water dynamics}, series = {European journal of agronomy}, volume = {134}, journal = {European journal of agronomy}, publisher = {Elsevier}, address = {Amsterdam}, issn = {1161-0301}, doi = {10.1016/j.eja.2022.126464}, pages = {17}, year = {2022}, abstract = {The dynamics of grassland ecosystems are highly complex due to multifaceted interactions among their soil, water, and vegetation components. Precise simulations of grassland productivity therefore rely on accurately estimating a variety of parameters that characterize different processes of these systems. This study applied three calibration schemes - a Single-Objective (SO-SUFI2), a Multi-Objective Pareto (MO-Pareto), and, a novel Uncertainty-Based Multi-Objective (MO-SUFI2) - to estimate the parameters of MONICA (Model for Nitrogen and Carbon Simulation) agro-ecosystem model in grassland ecosystems across Germany. The MO-Pareto model is based on a traditional Pareto optimality concept, while the MO-SUFI2 optimizes multiple target variables considering their level of prediction uncertainty. We used measurements of leaf area index, aboveground biomass, and soil moisture from experimental data at five sites with different intensities of cutting regimes (from two to five cutting events per season) to evaluate model performance. Both MO-Pareto and MO-SUFI2 outperformed SO-SUFI2 during calibration and validation. The comparison of the two MO approaches shows that they do not necessarily conflict with each other, but MO-SUFI2 provides complementary information for better estimations of model parameter uncertainty. We used the obtained parameter ranges to simulate grassland productivity across Germany under different cutting regimes and quantified the uncertainty associated with estimated productivity across regions. The results showed higher uncertainty in intensively managed grasslands compared to extensively managed grasslands, partially due to a lack of high-resolution input information concerning cutting dates. Furthermore, the additional information on the quantified uncertainty provided by our proposed MO-SUFI2 method adds deeper insights on confidence levels of estimated productivity. Benefiting from additional management data collected at high resolution and ground measurements on the composition of grassland species mixtures appear to be promising solutions to reduce uncertainty and increase model reliability.}, language = {en} }