The German Young Geoscientists Group – promoting exchange and information among the next generation of geoscientists

The group „Young geoscientists” of the Senate Commission for Joint Geoscientific Research (Geokommisson, www.geokommission.de) of the German Research Foundation (DFG), is dedicated towards the development of the working environment, workforce and scientific outcome of the next generation of geoscientists in Germany.Geoscientific research – basic as, well as applied – provides crucial contributions for mastering the economic, environmental and societal challenges of the near and medium-term future. Politics and society call for immediate answers, while geoscientific phenomena are complex and act on a large range of temporal and spatial scales.These demands, together with increases mobility requirements, lead to increasing pressure especially on young geoscientists. In this situation the main goals of the group “Young geoscientists” are:Promotion of networking among young geoscientistsInformation about science policy developments, funding opportunities and other relevant mattersRepresenting the interests of young scientists towards (science)-policy makersThe dynamic development of geoscientific research, particularly collaborations across traditional disciplines, as well as in increasing demands from public and policy, calls for a continuous integration of young scientists. We promote this process by organizing round-table discussions, e.g. on “Guaranteeing good scientific praxis” or on “Hot topics and research funding”, by communicating information via the internet and by identifying structural deficiencies that might hinder the advancement of the geosciences and reporting them to decision makers. In this context, we are looking for:European or international collaboratorsYoung geoscientists wishing to participate in / contribute to our activitiesSuggestions on how to improve working conditions of the young and advancing geoscientists</ul

Predominance of methanogens over methanotrophs in rewetted fens characterized by high methane emissions

The rewetting of drained peatlands alters peat geochemistry and often leads to sustained elevated methane emission. Although this methane is produced entirely by microbial activity, the distribution and abundance of methane-cycling microbes in rewetted peatlands, especially in fens, is rarely described. In this study, we compare the community composition and abundance of methane-cycling microbes in relation to peat porewater geochemistry in two rewetted fens in northeastern Germany, a coastal brackish fen and a freshwater riparian fen, with known high methane fluxes. We utilized 16S rRNA high-throughput sequencing and quantitative polymerase chain reaction (qPCR) on 16S rRNA, mcrA, and pmoA genes to determine microbial community composition and the abundance of total bacteria, methanogens, and methanotrophs. Electrical conductivity (EC) was more than 3 times higher in the coastal fen than in the riparian fen, averaging 5.3 and 1.5&thinsp;mS cm−1, respectively. Porewater concentrations of terminal electron acceptors (TEAs) varied within and among the fens. This was also reflected in similarly high intra- and inter-site variations of microbial community composition. Despite these differences in environmental conditions and electron acceptor availability, we found a low abundance of methanotrophs and a high abundance of methanogens, represented in particular by Methanosaetaceae, in both fens. This suggests that rapid (re)establishment of methanogens and slow (re)establishment of methanotrophs contributes to prolonged increased methane emissions following rewetting.</p

Active afforestation of drained peatlands is not a viable option under the EU Nature Restoration Law

The EU Nature Restoration Law (NRL) is critical in restoring degraded ecosystems. However, active afforestation of degraded peatlands has been suggested by some as a restoration measure under the NRL. Here, we discuss the current state of scientific evidence on the climate mitigation effects of peatlands under forestry and its limitations, uncertainties and evidence gaps. Based on this discussion we conclude: Afforestation of drained peatlands, while maintaining their drained state, is not equivalent to ecosystem restoration. This approach will not restore the peatland ecosystem's flora, fauna, and functions. There is insufficient evidence to support the long-term climate change mitigation benefits of active afforestation of drained peatlands. Most studies only focus on the short-term gains in standing biomass and rarely explore the full life cycle emissions associated with afforestation of drained peatlands. Thus, it is unclear whether the CO2 sequestration of a forest on drained peatland can offset the carbon loss from the peat over the long term. In some ecosystems, such as abandoned or certain cutaway peatlands, afforestation may provide short-term benefits for climate change mitigation compared to taking no action. However, this approach violates the concept of sustainability by sacrificing the most space-effective carbon store of the terrestrial biosphere, the long-term peat store, for a shorter-term, less space-effective, and more vulnerable carbon store, namely tree biomass. Consequently, active afforestation of drained peatlands is not a viable option for climate mitigation under the EU Nature Restoration Law and might even impede future rewetting/restoration efforts. To restore degraded peatlands, hydrological conditions must first be improved, primarily through rewetting

Sulfate deprivation triggers high methane production in a disturbed and rewetted coastal peatland

In natural coastal wetlands, high supplies of marine sulfate suppress methanogenesis. Coastal wetlands are, however, often subject to disturbance by diking and drainage for agricultural use and can turn to potent methane sources when rewetted for remediation. This suggests that preceding land use measures can suspend the sulfate-related methane suppressing mechanisms. Here, we unravel the hydrological relocation and biogeochemical S and C transformation processes that induced high methane emissions in a disturbed and rewetted peatland despite former brackish impact. The underlying processes were investigated along a transect of increasing distance to the coastline using a combination of concentration patterns, stable isotope partitioning, and analysis of the microbial community structure. We found that diking and freshwater rewetting caused a distinct freshening and an efficient depletion of the brackish sulfate reservoir by dissimilatory sulfate reduction (DSR). Despite some legacy effects of brackish impact expressed as high amounts of sedimentary S and elevated electrical conductivities, contemporary metabolic processes operated mainly under sulfate-limited conditions. This opened up favorable conditions for the establishment of a prospering methanogenic community in the top 30–40&thinsp;cm of peat, the structure and physiology of which resemble those of terrestrial organic-rich environments. Locally, high amounts of sulfate persisted in deeper peat layers through the inhibition of DSR, probably by competitive electron acceptors of terrestrial origin, for example Fe(III). However, as sulfate occurred only in peat layers below 30–40&thinsp;cm, it did not interfere with high methane emissions on an ecosystem scale. Our results indicate that the climate effect of disturbed and remediated coastal wetlands cannot simply be derived by analogy with their natural counterparts. From a greenhouse gas perspective, the re-exposure of diked wetlands to natural coastal dynamics would literally open up the floodgates for a replenishment of the marine sulfate pool and therefore constitute an efficient measure to reduce methane emissions.</p

Onset dynamics of type A botulinum neurotoxin-induced paralysis

Experimental studies have demonstrated that botulinum neurotoxin serotype A (BoNT/A) causes flaccid paralysis by a multi-step mechanism. Following its binding to specific receptors at peripheral cholinergic nerve endings, BoNT/A is internalized by receptor-mediated endocytosis. Subsequently its zinc-dependent catalytic domain translocates into the neuroplasm where it cleaves a vesicle-docking protein, SNAP-25, to block neurally evoked cholinergic neurotransmission. We tested the hypothesis that mathematical models having a minimal number of reactions and reactants can simulate published data concerning the onset of paralysis of skeletal muscles induced by BoNT/A at the isolated rat neuromuscular junction (NMJ) and in other systems. Experimental data from several laboratories were simulated with two different models that were represented by sets of coupled, first-order differential equations. In this study, the 3-step sequential model developed by Simpson (J Pharmacol Exp Ther 212:16–21,1980) was used to estimate upper limits of the times during which anti-toxins and other impermeable inhibitors of BoNT/A can exert an effect. The experimentally determined binding reaction rate was verified to be consistent with published estimates for the rate constants for BoNT/A binding to and dissociating from its receptors. Because this 3-step model was not designed to reproduce temporal changes in paralysis with different toxin concentrations, a new BoNT/A species and rate (kS) were added at the beginning of the reaction sequence to create a 4-step scheme. This unbound initial species is transformed at a rate determined by kS to a free species that is capable of binding. By systematically adjusting the values of kS, the 4-step model simulated the rapid decline in NMJ function (kS ≥0.01), the less rapid onset of paralysis in mice following i.m. injections (kS = 0.001), and the slow onset of the therapeutic effects of BoNT/A (kS < 0.001) in man. This minimal modeling approach was not only verified by simulating experimental results, it helped to quantitatively define the time available for an inhibitor to have some effect (tinhib) and the relation between this time and the rate of paralysis onset. The 4-step model predicted that as the rate of paralysis becomes slower, the estimated upper limits of (tinhib) for impermeable inhibitors become longer. More generally, this modeling approach may be useful in studying the kinetics of other toxins or viruses that invade host cells by similar mechanisms, e.g., receptor-mediated endocytosis

Gap-filling eddy covariance methane fluxes:Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET)

Benchmarking Ontologies: Bigger or Better?

A scientific ontology is a formal representation of knowledge within a domain, typically including central concepts, their properties, and relations. With the rise of computers and high-throughput data collection, ontologies have become essential to data mining and sharing across communities in the biomedical sciences. Powerful approaches exist for testing the internal consistency of an ontology, but not for assessing the fidelity of its domain representation. We introduce a family of metrics that describe the breadth and depth with which an ontology represents its knowledge domain. We then test these metrics using (1) four of the most common medical ontologies with respect to a corpus of medical documents and (2) seven of the most popular English thesauri with respect to three corpora that sample language from medicine, news, and novels. Here we show that our approach captures the quality of ontological representation and guides efforts to narrow the breach between ontology and collective discourse within a domain. Our results also demonstrate key features of medical ontologies, English thesauri, and discourse from different domains. Medical ontologies have a small intersection, as do English thesauri. Moreover, dialects characteristic of distinct domains vary strikingly as many of the same words are used quite differently in medicine, news, and novels. As ontologies are intended to mirror the state of knowledge, our methods to tighten the fit between ontology and domain will increase their relevance for new areas of biomedical science and improve the accuracy and power of inferences computed across them

Treibhausgasemissionen aus organischen Böden im deutschen Treibhausgasinventar: Methodenentwicklung und Ergebnisse

Entwässerte organische Böden sind in vielen Ländern, darunter auch in Deutschland, eine starke Quelle anthropogener Treibhausgase (THG). Daher müssen sie bei der Berichterstattung gemäß UNFCCC und Kyoto-Protokoll angemessen berücksichtigt werden. Hier beschreiben wir die Methodik, Daten und Ergebnisse der deutschen detaillierten Tier-3-Methodik zur Berichterstattung anthropogener Treibhausgasemissionen aus entwässerten organischen Böden, die für das deutsche Treibhausgasinventar entwickelt und angewandt wurden. Der Ansatz basiert auf nationalen Daten und bietet das Potenzial, Änderungen der Landnutzung und des Wassermanagements zu verfolgen, falls Zeitreihen zu relevanten Aktivitätsdaten vorliegen. Die Aktivitätsdaten umfassen hochauflösende Karten zu Klima, Landnutzung, organischen Böden und vom mittleren jährlichen Grundwasserflurabstand. Die Grundwasserkarte wurde durch ein statistisches Modell aus Daten von &gt; 1000 Standorten abgeleitet. Die THG-Emissionen beruhen auf einem einzigartigen Datensatz mit mehr als 200 THG-Bilanzen für fast alle Kombinationen von Landnutzungskategorien und Typen organischer Böden. Die Messungen wurden mit vollständig harmonisierten Protokollen durchgeführt. Nicht-lineare Funktionen beschreiben die Abhängigkeit der Kohlendioxid- und Methan-Flüsse vom mittleren jährlichen Grundwasserstand und, wenn erforderlich, von der Landnutzung. Die daraus resultierenden "angewandten Emissionsfaktoren" für jede Landnutzungskategorie berücksichtigen sowohl die Unsicherheit der nicht-linearen Funktionen als auch die Verteilung der Grundwasserstände in jeder Landnutzungskategorie. Da keine einfachen funktionellen Zusammenhänge für die Lachgasemissionen gefunden wurden, wurden die entsprechenden Emissionsfaktoren daher als Mittelwerte der Messwerte jeder Landnutzungskategorie berechnet. Für kleinere THG-Quellen wie Methanemissionen aus Gräben und Austräge von gelöstem organischem Kohlenstoff wurden IPCC-Standard-Emissionsfaktoren verwendet