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Throughfall, that is, the fraction of rainfall that passes through the forest canopy, is strongly influenced by rainfall and forest stand characteristics which are in turn both subject to seasonal dynamics. Disentangling the complex interplay of these controls is challenging, and only possible with long-term monitoring and a large number of throughfall events measured in parallel at different forest stands. We therefore based our analysis on 346 rainfall events across six different forest stands at the long-term terrestrial environmental observatory TERENO Northeast Germany. These forest stands included pure stands of beech, pine and young pine, and mixed stands of oak-beech, pine-beech and pine-oak-beech. Throughfall was overall relatively low, with 54-68% of incident rainfall in summer. Based on the large number of events it was possible to not only investigate mean or cumulative throughfall but also its statistical distribution. The distributions of throughfall fractions show distinct differences between the three types of forest stands (deciduous, mixed and pine). The distributions of the deciduous stands have a pronounced peak at low throughfall fractions and a secondary peak at high fractions in summer, as well as a pronounced peak at higher throughfall fractions in winter. Interestingly, the mixed stands behave like deciduous stands in summer and like pine stands in winter: their summer distributions are similar to the deciduous stands but the winter peak at high throughfall fractions is much less pronounced. The seasonal comparison further revealed that the wooden components and the leaves behaved differently in their throughfall response to incident rainfall, especially at higher rainfall intensities. These results are of interest for estimating forest water budgets and in the context of hydrological and land surface modelling where poor simulation of throughfall would adversely impact estimates of evaporative recycling and water availability for vegetation and runoff.
Does youth matter?
(2021)
Previous research has mainly concentrated on the study of certain transitions and the influence of economic and socio-structural factors on partnership status. From a life course perspective, it remains unclear how factors anchored in youth are related to the diversity of partnership biographies. Arguing that individuals act and behave based on prior experiences and resources, I analyse how personal and social resources as well as socio-demographic characteristics influence the turbulence of longitudinal partnership trajectories.
Using a longitudinal dataset from the German LifE Study, I examine partnership histories from the ages 16 to 45. The results suggest that in addition to the influence of an individual's socio-demographic placement (for example, religious commitment and regional living conditions), personal and social resources anchored in youth also have a long-term effect on the diversity of partnership trajectories. This article shows that women are influenced by their attitudes towards marriage and family, while men are influenced by their attitudes towards their careers.
Teacher self-efficacy and teacher interest are two key facets of teacher motivation that are important for highquality teaching. Little is known about the relative strength of the effects of teacher self-efficacy and interest on teaching quality when compared with one another. We extend previous research on teacher motivation by examining the relations linking mathematics teacher self-efficacy and interest with several relevant dimensions of teaching quality as perceived by teachers and students. Participants were 84 mathematics teachers (61.2% female) and their students (1718 students; 48.5% girls). Based on doubly latent multilevel models, we found that teacher-reported self-efficacy in instruction was positively related to teacher-reported cognitive activation, classroom management, and emotional support in mathematics classrooms. Teacher-reported educational interest showed positive associations with both student- and teacher-perceived emotional support. Future research is advised to focus more strongly on the unique relations between different teachers' motivational characteristics and relevant dimensions of teaching quality.
Eatomics
(2021)
Quantitative proteomics data are becoming increasingly more available, and as a consequence are being analyzed and interpreted by a larger group of users. However, many of these users have less programming experience. Furthermore, experimental designs and setups are getting more complicated, especially when tissue biopsies are analyzed. Luckily, the proteomics community has already established some best practices on how to conduct quality control, differential abundance analysis and enrichment analysis. However, an easy-to-use application that wraps together all steps for the exploration and flexible analysis of quantitative proteomics data is not yet available. For Eatomics, we utilize the R Shiny framework to implement carefully chosen parts of established analysis workflows to (i) make them accessible in a user-friendly way, (ii) add a multitude of interactive exploration possibilities, and (iii) develop a unique experimental design setup module, which interactively translates a given research hypothesis into a differential abundance and enrichment analysis formula. In this, we aim to fulfill the needs of a growing group of inexperienced quantitative proteomics data analysts. Eatomics may be tested with demo data directly online via https://we.analyzegenomes.com/now/eatomics/or with the user's own data by installation from the Github repository at https://github.com/Millchmaedchen/Eatomics.
Semi-distributed hydrological and water quality models are increasingly used as innovative and scientific-based management tools.
However, their application is usually restricted to the gauging stations where they are originally calibrated, limiting their spatial capability.
In this study, the semi-distributed hydrological water quality model HYPE (HYdrological Predictions for the Environment) was tested spatially to represent nitrate-N (NO3- N) and total phosphorus (TP) concentrations and loads of the nested and heterogeneous Selke catchment (463 km(2)) in central Germany.
First, an automatic calibration procedure and uncertainty analysis were conducted using the DiffeRential Evolution Adaptive Metropolis (DREAM) tool to simulate discharge, NO3--N and TP concentrations. A multi-site and multi-objective calibration approach was applied using three main gauging stations, covering the most important hydro-meteorological and physiographical characteristics of the whole catchment. Second, the model's capability was tested to represent further internal stations, which were not initially considered for calibration. Results showed that discharge was well represented by the model at all three main stations during both calibration (1994-1998) and validation (1999-2014) periods with lowest Nash-Sutcliffe Efficiency (NSE) of 0.71 and maximum Percentage BIAS (PBIAS) of 18.0%.
The model was able to reproduce the seasonal dynamics of NO3--N and TP concentrations with low predictive uncertainty at the three main stations, reflected by PBIAS values in the ranges from 16.1% to 6.4% and from 20.0% to 11.5% for NO3--N and TP load simulations, respectively.
At internal stations, the model could represent reasonably well the seasonal variation of nutrient concentrations with PBIAS values in the ranges from 9.0% to 14.2% for NO3--N and from 25.3% to 34.3% for TP concentration simulations.
Overall, results suggested that the spatial validation of a nutrient transport model can be better ensured when a multi-site and multi-objective calibration approach using archetypical gauging stations is implemented.
Further, results revealed that the delineation of sub-catchments should put more focus on hydro-meteorological conditions than on land-use features.
The H alpha spectral line is a well-studied absorption line revealing properties of the highly structured and dynamic solar chromosphere. Typical features with distinct spectral signatures in H alpha include filaments and prominences, bright active-region plages, superpenumbrae around sunspots, surges, flares, Ellerman bombs, filigree, and mottles and rosettes, among others. This study is based on high-spectral resolution H alpha spectra obtained with the Echelle spectrograph of the Vacuum Tower Telescope (VTT) located at Observatorio del Teide, Tenerife, Spain. The t-distributed stochastic neighbor embedding (t-SNE) is a machine-learning algorithm, which is used for nonlinear dimensionality reduction. In this application, it projects H alpha spectra onto a two-dimensional map, where it becomes possible to classify the spectra according to results of cloud model (CM) inversions. The CM parameters optical depth, Doppler width, line-of-sight velocity, and source function describe properties of the cloud material. Initial results of t-SNE indicate its strong discriminatory power to separate quiet-Sun and plage profiles from those that are suitable for CM inversions. In addition, a detailed study of various t-SNE parameters is conducted, the impact of seeing conditions on the classification is assessed, results for various types of input data are compared, and the identified clusters are linked to chromospheric features. Although t-SNE proves to be efficient in clustering high-dimensional data, human inference is required at each step to interpret the results. This exploratory study provides a framework and ideas on how to tailor a classification scheme toward specific spectral data and science questions.
The sharing economy
(2020)
Purpose Quantitative bibliometric approaches were used to statistically and objectively explore patterns in the sharing economy literature. Design/methodology/approach Journal (co-)citation analysis, author (co-)citation analysis, institution citation and co-operation analysis, keyword co-occurrence analysis, document (co-)citation analysis and burst detection analysis were conducted based on a bibliometric data set relating to sharing economy publications. Findings Sharing economy research is multi- and interdisciplinary. Journals focused upon products liability, organizing framework, profile characteristics, diverse economies, consumption system and everyday life themes. Authors focused upon profile characteristics, sharing economy organization, social connections, first principle and diverse economy themes. No institution dominated the research field. Keyword co-occurrence analysis identified organizing framework, tourism industry, consumer behavior, food waste, generous exchange and quality cue as research themes. Document co-citation analysis found research themes relating to the tourism industry, exploring public acceptability, agri-food system, commercial orientation, products liability and social connection. Most cited authors, institutions and documents are reported. Research limitations/implications The study did not exclusively focus on publications in top-tier journals. Future studies could run analyses relating to top-tier journals alone, and then run analyses relating to less renowned journals alone. To address the potential fuzzy results concern, reviews could focus on business and/or management research alone. Longitudinal reviews conducted over several points in time are warranted. Future reviews could combine qualitative and quantitative approaches. Originality/value We contribute by analyzing information relating to the population of all sharing economy articles. In addition, we contribute by employing several quantitative bibliometric approaches that enable the identification of trends relating to the themes and patterns in the growing literature.
The literature contains a sizable number of publications where weather types are used to decompose climate shifts or trends into contributions of frequency and mean of those types. They are all based on the product rule, that is, a transformation of a product of sums into a sum of products, the latter providing the decomposition. While there is nothing to argue about the transformation itself, its interpretation as a climate shift or trend decomposition is bound to fail. While the case of a climate shift may be viewed as an incomplete description of a more complex behaviour, trend decomposition indeed produces bogus trends, as demonstrated by a synthetic counterexample with well-defined trends in type frequency and mean. Consequently, decompositions based on that transformation, be it for climate shifts or trends, must not be used.
A numerical framework is developed to study the hysteresis of elastic properties of porous ceramics as a function of temperature. The developed numerical model is capable of employing experimentally measured crystallographic orientation distribution and coefficient of thermal expansion values. For realistic modeling of the microstructure, Voronoi polygons are used to generate polycrystalline grains. Some grains are considered as voids, to simulate the material porosity. To model intercrystalline cracking, cohesive elements are inserted along grain boundaries. Crack healing (recovery of the initial properties) upon closure is taken into account with special cohesive elements implemented in the commercial code ABAQUS. The numerical model can be used to estimate fracture properties governing the cohesive behavior through inverse analysis procedure. The model is applied to a porous cordierite ceramic. The obtained fracture properties are further used to successfully simulate general non-linear macroscopic stress-strain curves of cordierite, thereby validating the model.
A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.