Search

Lesson planning is a core part of teachers' professional competence. Written lesson plans play a significant role in science teacher education as a preparation for demonstration lessons during the final teacher certification exam. However, the few existing scoring rubrics on lesson plans are not particularly theoretically sound and are barely tested for the validity of score interpretations. In response to the demand for transparent and applicable criteria, we developed the rubric to assess science lesson plans (RALP) to assess science teachers' lesson plan quality. We employed a mixed‐methods approach: First, we present multiple sources of validity evidence (based on test content, internal structure, relations to other variables, and consequences of testing) as mainly quantitative indicators for the quality of the RALP. Based upon that, we applied the RALP to lesson plans written by preservice and trainee science teachers (N = 100) and provided a qualitative analysis of six cases to illustrate common patterns in these lesson plans. Results indicate that teacher educators consider the RALP criteria (N = 24) relevant and objectively applicable. Correlation analyses of the scores and two teacher educators' holistic quality assessment of all lesson plans provide convincing evidence that the RALP can discriminate lesson plan quality levels. Moreover, comparisons between preservice science teachers and trainee science teachers reveal that trainee teachers score significantly higher than preservice teachers, indicating that the RALP is sensitive to differences in teaching and planning experience. The application and in‐depth analysis of three criteria of the RALP illustrate these differences in levels of planning quality. We discuss possible applications of the RALP in science teacher education and research in science teaching. [ABSTRACT FROM AUTHOR]

Applications of seismic measurements for the prediction of hazard zones are applied practice in many tunnel drives in rock mass today. Next to a large exploration range and accurate localisation of discontinuities, seismic data provide attributes for a comprehensive characterisation of the ground conditions. A good synchronisation of all technical components is required to obtain optimum data quality and quantity while the tunnel excavation is not obstructed thereby. Firstly, the signal source must feed as much energy as possible into the rock in a very short time. Secondly, continuity of the signal generation with constant quality and its precise timing by means of wireless data transmission also ensure a reliable measurement process. Artificial intelligence is used to determine the quality of the recorded data already in the tunnel and feedback is given to the user keeping the data quality high. From the tunnel site, recorded raw data can be transferred to a cloud, from where an authorised processor collects them, wherever in the world. An immediately started data processing delivers a result within an hour that includes a geological forecast of up to 150 m of heading, depending on the rock mass condition. In addition to data quality, the quality of the results is crucial. Therefore, techniques are currently under development using machine learning to correlate and analyse seismic attributes with geological properties. This should lead to a more objective evaluation of the geological forecast in the future. [ABSTRACT FROM AUTHOR]

Next‐generation sequencing (NGS) has significantly increased knowledge of microbial communities and their distribution. However, it is still not common to apply NGS technology to microbial conservation. We sought to use NGS technologies to evaluate conservation strategies for wood‐inhabiting fungi. Evaluating a deadwood experiment 3 years after it was established, we specifically examined which tree species combinations promoted the highest richness of wood‐inhabiting fungi. Deadwood enrichment was an effective strategy and logs of 6 tree species, either those with the highest wood‐inhabiting fungal α and γ diversity or those with the highest β diversity, maintained >1,000 operational taxonomic units (OTUs) spread over a wide range of taxonomic groups. In comparison, a conservation strategy based only on the results of sporocarp surveys yielded 591 OTUs. This result highlights the need to use NGS approaches to inform microbial conservation strategies. We also determined that 5 tree species with the highest saproxylic beetle γ diversity simultaneously conserved wood‐inhabiting fungi. Apart from deadwood volume, we suggest data on deadwood quality and species also be included as indicators, especially for wood‐inhabiting fungal diversity, and incorporated quickly in forest assessment and monitoring systems in Central Europe. Article impact statement: Enrichment of the species diversity of deadwood is an effective strategy for wood‐inhabiting fungal conservation in temperate forests. [ABSTRACT FROM AUTHOR]

Summary: Nitrogen deposition can strongly affect biodiversity, but its specific effects on terrestrial microbial communities and their roles for ecosystem functions and processes are still unclear. Here, we investigated the impacts of N deposition on wood‐inhabiting fungi (WIF) and their related ecological functions and processes in a highly N‐limited deadwood habitat. Based on high‐throughput sequencing, enzymatic activity assay and measurements of wood decomposition rates, we show that N addition has no significant effect on the overall WIF community composition or on related ecosystem functions and processes in this habitat. Nevertheless, we detected several switches in presence/absence (gain/loss) of wood‐inhabiting fungal OTUs due to the effect of N addition. The responses of WIF differed from previous studies carried out with fungi living in soil and leaf‐litter, which represent less N‐limited fungal habitats. Our results suggest that adaptation at different levels of organization and functional redundancy may explain this buffered response and the resistant microbial‐mediated ecosystem function and processes against N deposition in highly N‐limited habitats. [ABSTRACT FROM AUTHOR]

Microorganisms play a crucial role in the biological decomposition of plant litter in terrestrial ecosystems. Due to the permanently changing litter quality during decomposition, studies of both fungi and bacteria at a fine taxonomic resolution are required during the whole process. Here we investigated microbial community succession in decomposing leaf litter of temperate beech forest using pyrotag sequencing of the bacterial 16S and the fungal internal transcribed spacer ( ITS) rRNA genes. Our results reveal that both communities underwent rapid changes. Proteobacteria, Actinobacteria and Bacteroidetes dominated over the entire study period, but their taxonomic composition and abundances changed markedly among sampling dates. The fungal community also changed dynamically as decomposition progressed, with ascomycete fungi being increasingly replaced by basidiomycetes. We found a consistent and highly significant correlation between bacterial richness and fungal richness ( R = 0.76, P < 0.001) and community structure ( RMantel = 0.85, P < 0.001), providing evidence of coupled dynamics in the fungal and bacterial communities. A network analysis highlighted nonrandom co-occurrences among bacterial and fungal taxa as well as a shift in the cross-kingdom co-occurrence pattern of their communities from the early to the later stages of decomposition. During this process, macronutrients, micronutrients, C:N ratio and pH were significantly correlated with the fungal and bacterial communities, while bacterial richness positively correlated with three hydrolytic enzymes important for C, N and P acquisition. Overall, we provide evidence that the complex litter decay is the result of a dynamic cross-kingdom functional succession. [ABSTRACT FROM AUTHOR]