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- ItemEEG biomarkers of activation of the lymphatic drainage system of the brain during sleep and opening of the blood-brain barrier(Gotenburg : Research Network of Computational and Structural Biotechnology (RNCSB), 2022) Semyachkina-Glushkovskaya, O.V.; Karavaev, A.S.; Prokhorov, M.D.; Runnova, A.E.; Borovkova, E.I.; Ishbulatov, Yu.M.; Hramkov, A.N.; Kulminskiy, D.D.; Semenova, N.I.; Sergeev, K.S.; Slepnev, A.V.; Sitnikova, E.Yu.; Zhuravlev, M.O.; Fedosov, I.V.; Shirokov, A.A.; Blokhina, I.A.; Dubrovski, A.I.; Terskov, A.V.; Khorovodov, A.P.; Ageev, V.B.; Elovenko, D.A.; Evsukova, A.S.; Adushkina, V.V.; Telnova, V.V.; Postnov, D.E.; Penzel, T.U.; Kurths, J.G.The lymphatic drainage system of the brain (LDSB) is the removal of metabolites and wastes from its tissues. A dysfunction of LDSB is an important sign of aging, brain oncology, the Alzheimer's and Parkinson's diseases. The development of new strategies for diagnosis of LDSB injuries can improve prevention of age-related cerebral amyloid angiopathy, neurodegenerative and cerebrovascular diseases. There are two conditions, such as deep sleep and opening of the blood-brain-barrier (OBBB) associated with the LDSB activation. A promising candidate for measurement of LDSB could be electroencephalography (EEG). In this pilot study on rats, we tested the hypothesis, whether deep sleep and OBBB can be an informative platform for an effective extracting of information about the LDSB functions. Using the nonlinear analysis of EEG dynamics and machine learning technology, we discovered that the LDSB activation during OBBB and sleep is associated with similar changes in the EEG θ-activity. The OBBB causes the higher LDSB activation vs. sleep that is accompanied by specific changes in the low frequency EEG activity extracted by the power spectra analysis of the EEG dynamics combined with the coherence function. Thus, our findings demonstrate a link between neural activity associated with the LDSB activation during sleep and OBBB that is an important informative platform for extraction of the EEG-biomarkers of the LDSB activity. These results open new perspectives for the development of technology for the LDSB diagnostics that would open a novel era in the prognosis of brain diseases caused by the LDSB disorders, including OBBB.
- ItemBiodiversity research: Data without theory-theory without data(Lausanne : Frontiers Media, 2015) Rillig, Matthias C.; Kiessling, Wolfgang; Borsch, Thomas; Gessler, Arthur; Greenwood, Alex D.; Hofer, Heribert; Joshi, Jasmin; Schröder, Boris; Thonicke, Kirsten; Tockner, Klement; Weisshuhn, Karoline; Jeltsch, Florian[No abstract available]
- ItemAvailable and missing data to model impact of climate change on European forests(Amsterdam [u.a.] : Elsevier Science, 2019) Ruiz-Benito, Paloma; Vacchiano, Giorgio; Lines, Emily R.; Reyer, Christopher P.O.; Ratcliffe, Sophia; Morin, Xavier; Hartig, Florian; Mäkelä, Annikki; Yousefpour, Rasoul; Chaves, Jimena E.; Palacios-Orueta, Alicia; Benito-Garzón, Marta; Morales-Molino, Cesar; Camarero, J. Julio; Jump, Alistair S.; Kattge, Jens; Lehtonen, Aleksi; Ibrom, Andreas; Owen, Harry J.F.; Zavala, Miguel A.Climate change is expected to cause major changes in forest ecosystems during the 21st century and beyond. To assess forest impacts from climate change, the existing empirical information must be structured, harmonised and assimilated into a form suitable to develop and test state-of-the-art forest and ecosystem models. The combination of empirical data collected at large spatial and long temporal scales with suitable modelling approaches is key to understand forest dynamics under climate change. To facilitate data and model integration, we identified major climate change impacts observed on European forest functioning and summarised the data available for monitoring and predicting such impacts. Our analysis of c. 120 forest-related databases (including information from remote sensing, vegetation inventories, dendroecology, palaeoecology, eddy-flux sites, common garden experiments and genetic techniques) and 50 databases of environmental drivers highlights a substantial degree of data availability and accessibility. However, some critical variables relevant to predicting European forest responses to climate change are only available at relatively short time frames (up to 10-20 years), including intra-specific trait variability, defoliation patterns, tree mortality and recruitment. Moreover, we identified data gaps or lack of data integration particularly in variables related to local adaptation and phenotypic plasticity, dispersal capabilities and physiological responses. Overall, we conclude that forest data availability across Europe is improving, but further efforts are needed to integrate, harmonise and interpret this data (i.e. making data useable for non-experts). Continuation of existing monitoring and networks schemes together with the establishments of new networks to address data gaps is crucial to rigorously predict climate change impacts on European forests. © 2019 The Author(s)
- ItemDrought losses in China might double between the 1.5 °C and 2.0 °C warming(Washington, DC : NAS, 2018) Su, Buda; Huang, Jinlong; Fischer, Thomas; Wang, Yanjun; Kundzewicz, Zbigniew W.; Zhai, Jianqing; Sun, Hemin; Wang, Anqian; Zeng, Xiaofan; Wang, Guojie; Tao, Hui; Gemmer, Marco; Li, Xiucang; Jiang, TongWe project drought losses in China under global temperature increase of 1.5 °C and 2.0 °C, based on the Standardized Precipitation Evapotranspiration Index (SPEI) and the Palmer Drought Severity Index (PDSI), a cluster analysis method, and “intensity-loss rate” function. In contrast to earlier studies, to project the drought losses, we predict the regional gross domestic product under shared socioeconomic pathways instead of using a static socioeconomic scenario. We identify increasing precipitation and evapotranspiration pattern for the 1.5 °C and 2.0 °C global warming above the preindustrial at 2020–2039 and 2040–2059, respectively. With increasing drought intensity and areal coverage across China, drought losses will soar. The estimated loss in a sustainable development pathway at the 1.5 °C warming level increases 10-fold in comparison with the reference period 1986–2005 and nearly threefold relative to the interval 2006–2015. However, limiting the temperature increase to 1.5 °C can reduce the annual drought losses in China by several tens of billions of US dollars, compared with the 2.0 °C warming.
- ItemSignificant increase in natural disturbance impacts on European forests since 1950(Oxford [u.a.] : Blackwell Science, 2022) Patacca, Marco; Lindner, Marcus; Lucas‐Borja, Manuel Esteban; Cordonnier, Thomas; Fidej, Gal; Gardiner, Barry; Hauf, Ylva; Jasinevičius, Gediminas; Labonne, Sophie; Linkevičius, Edgaras; Mahnken, Mats; Milanovic, Slobodan; Nabuurs, Gert‐Jan; Nagel, Thomas A.; Nikinmaa, Laura; Panyatov, Momchil; Bercak, Roman; Seidl, Rupert; Ostrogović Sever, Masa Zorana; Socha, Jaroslaw; Thom, Dominik; Vuletic, Dijana; Zudin, Sergey; Schelhaas, Mart‐JanOver the last decades, the natural disturbance is increasingly putting pressure on European forests. Shifts in disturbance regimes may compromise forest functioning and the continuous provisioning of ecosystem services to society, including their climate change mitigation potential. Although forests are central to many European policies, we lack the long-term empirical data needed for thoroughly understanding disturbance dynamics, modeling them, and developing adaptive management strategies. Here, we present a unique database of >170,000 records of ground-based natural disturbance observations in European forests from 1950 to 2019. Reported data confirm a significant increase in forest disturbance in 34 European countries, causing on an average of 43.8 million m3 of disturbed timber volume per year over the 70-year study period. This value is likely a conservative estimate due to under-reporting, especially of small-scale disturbances. We used machine learning techniques for assessing the magnitude of unreported disturbances, which are estimated to be between 8.6 and 18.3 million m3/year. In the last 20 years, disturbances on average accounted for 16% of the mean annual harvest in Europe. Wind was the most important disturbance agent over the study period (46% of total damage), followed by fire (24%) and bark beetles (17%). Bark beetle disturbance doubled its share of the total damage in the last 20 years. Forest disturbances can profoundly impact ecosystem services (e.g., climate change mitigation), affect regional forest resource provisioning and consequently disrupt long-term management planning objectives and timber markets. We conclude that adaptation to changing disturbance regimes must be placed at the core of the European forest management and policy debate. Furthermore, a coherent and homogeneous monitoring system of natural disturbances is urgently needed in Europe, to better observe and respond to the ongoing changes in forest disturbance regimes.
- ItemResponsibility Under Uncertainty: Which Climate Decisions Matter Most?(Amsterdam : Baltzer Science Publ., 2023) Botta, Nicola; Brede, Nuria; Crucifix, Michel; Ionescu, Cezar; Jansson, Patrik; Li, Zheng; Martínez, Marina; Richter, TimWe propose a new method for estimating how much decisions under monadic uncertainty matter. The method is generic and suitable for measuring responsibility in finite horizon sequential decision processes. It fulfills “fairness” requirements and three natural conditions for responsibility measures: agency, avoidance and causal relevance. We apply the method to study how much decisions matter in a stylized greenhouse gas emissions process in which a decision maker repeatedly faces two options: start a “green” transition to a decarbonized society or further delay such a transition. We account for the fact that climate decisions are rarely implemented with certainty and that their consequences on the climate and on the global economy are uncertain. We discover that a “moral” approach towards decision making — doing the right thing even though the probability of success becomes increasingly small — is rational over a wide range of uncertainties.
- ItemGenome-wide identification of regulatory elements and reconstruction of gene regulatory networks of the green alga Chlamydomonas reinhardtii under carbon deprivation(San Francisco, CA : Public Library of Science (PLoS), 2013) Winck, F.V.; Arvidsson, S.; Riaño-Pachón, D.M.; Hempe, S.; Koseska, A.; Nikoloski, Z.; Gomez, D.A.U.; Rupprecht, J.; Mueller-Roeber, B.The unicellular green alga Chlamydomonas reinhardtii is a long-established model organism for studies on photosynthesis and carbon metabolism-related physiology. Under conditions of air-level carbon dioxide concentration [CO 2], a carbon concentrating mechanism (CCM) is induced to facilitate cellular carbon uptake. CCM increases the availability of carbon dioxide at the site of cellular carbon fixation. To improve our understanding of the transcriptional control of the CCM, we employed FAIRE-seq (formaldehyde-assisted Isolation of Regulatory Elements, followed by deep sequencing) to determine nucleosome-depleted chromatin regions of algal cells subjected to carbon deprivation. Our FAIRE data recapitulated the positions of known regulatory elements in the promoter of the periplasmic carbonic anhydrase (Cah1) gene, which is upregulated during CCM induction, and revealed new candidate regulatory elements at a genome-wide scale. In addition, time series expression patterns of 130 transcription factor (TF) and transcription regulator (TR) genes were obtained for cells cultured under photoautotrophic condition and subjected to a shift from high to low [CO2]. Groups of co-expressed genes were identified and a putative directed gene-regulatory network underlying the CCM was reconstructed from the gene expression data using the recently developed IOTA (inner composition alignment) method. Among the candidate regulatory genes, two members of the MYB-related TF family, Lcr1 (Low-CO2 response regulator 1) and Lcr2 (Low-CO2 response regulator 2 ), may play an important role in down-regulating the expression of a particular set of TF and TR genes in response to low [CO2]. The results obtained provide new insights into the transcriptional control of the CCM and revealed more than 60 new candidate regulatory genes. Deep sequencing of nucleosome-depleted genomic regions indicated the presence of new, previously unknown regulatory elements in the C. reinhardtii genome. Our work can serve as a basis for future functional studies of transcriptional regulator genes and genomic regulatory elements in Chlamydomonas.
- ItemUnraveling gene regulatory networks from time-resolved gene expression data - a measures comparison study(London : BioMed Central, 2011) Hempel, Sabrina; Koseska, Aneta; Nikoloski, Zoran; Kurths, Jürgen; Walther, DirkBackground Inferring regulatory interactions between genes from transcriptomics time-resolved data, yielding reverse engineered gene regulatory networks, is of paramount importance to systems biology and bioinformatics studies. Accurate methods to address this problem can ultimately provide a deeper insight into the complexity, behavior, and functions of the underlying biological systems. However, the large number of interacting genes coupled with short and often noisy time-resolved read-outs of the system renders the reverse engineering a challenging task. Therefore, the development and assessment of methods which are computationally efficient, robust against noise, applicable to short time series data, and preferably capable of reconstructing the directionality of the regulatory interactions remains a pressing research problem with valuable applications. Results Here we perform the largest systematic analysis of a set of similarity measures and scoring schemes within the scope of the relevance network approach which are commonly used for gene regulatory network reconstruction from time series data. In addition, we define and analyze several novel measures and schemes which are particularly suitable for short transcriptomics time series. We also compare the considered 21 measures and 6 scoring schemes according to their ability to correctly reconstruct such networks from short time series data by calculating summary statistics based on the corresponding specificity and sensitivity. Our results demonstrate that rank and symbol based measures have the highest performance in inferring regulatory interactions. In addition, the proposed scoring scheme by asymmetric weighting has shown to be valuable in reducing the number of false positive interactions. On the other hand, Granger causality as well as information-theoretic measures, frequently used in inference of regulatory networks, show low performance on the short time series analyzed in this study. Conclusions Our study is intended to serve as a guide for choosing a particular combination of similarity measures and scoring schemes suitable for reconstruction of gene regulatory networks from short time series data. We show that further improvement of algorithms for reverse engineering can be obtained if one considers measures that are rooted in the study of symbolic dynamics or ranks, in contrast to the application of common similarity measures which do not consider the temporal character of the employed data. Moreover, we establish that the asymmetric weighting scoring scheme together with symbol based measures (for low noise level) and rank based measures (for high noise level) are the most suitable choices.
- ItemManagement-induced changes in soil organic carbon on global croplands(Katlenburg-Lindau [u.a.] : Copernicus, 2022) Karstens, Kristine; Bodirsky, Benjamin Leon; Dietrich, Jan Philipp; Dondini, Marta; Heinke, Jens; Kuhnert, Matthias; Müller, Christoph; Rolinski, Susanne; Smith, Pete; Weindl, Isabelle; Lotze-Campen, Hermann; Popp, AlexanderSoil organic carbon (SOC), one of the largest terrestrial carbon (C) stocks on Earth, has been depleted by anthropogenic land cover change and agricultural management. However, the latter has so far not been well represented in global C stock assessments. While SOC models often simulate detailed biochemical processes that lead to the accumulation and decay of SOC, the management decisions driving these biophysical processes are still little investigated at the global scale. Here we develop a spatially explicit data set for agricultural management on cropland, considering crop production levels, residue returning rates, manure application, and the adoption of irrigation and tillage practices. We combine it with a reduced-complexity model based on the Intergovernmental Panel on Climate Change (IPCC) tier 2 method to create a half-degree resolution data set of SOC stocks and SOC stock changes for the first 30 cm of mineral soils. We estimate that, due to arable farming, soils have lost around 34.6 GtC relative to a counterfactual hypothetical natural state in 1975. Within the period 1975-2010, this SOC debt continued to expand by 5 GtC (0.14 GtCyr-1) to around 39.6 GtC. However, accounting for historical management led to 2.1 GtC fewer (0.06 GtCyr-1) emissions than under the assumption of constant management. We also find that management decisions have influenced the historical SOC trajectory most strongly by residue returning, indicating that SOC enhancement by biomass retention may be a promising negative emissions technique. The reduced-complexity SOC model may allow us to simulate management-induced SOC enhancement - also within computationally demanding integrated (land use) assessment modeling.
- ItemImpacts of enhanced weathering on biomass production for negative emission technologies and soil hydrology(Katlenburg-Lindau [u.a.] : Copernicus, 2020) De Oliveira Garcia, Wagner; Amann, Thorben; Hartmann, Jens; Karstens, Kristine; Popp, Alexander; Boysen, Lena R.; Smith, Pete; Goll, DanielLimiting global mean temperature changes to well below 2 °C likely requires a rapid and large-scale deployment of negative emission technologies (NETs). Assessments so far have shown a high potential of biomass-based terrestrial NETs, but only a few assessments have included effects of the commonly found nutrient-deficient soils on biomass production. Here, we investigate the deployment of enhanced weathering (EW) to supply nutrients to areas of afforestation-reforestation and naturally growing forests (AR) and bioenergy grasses (BG) that are deficient in phosphorus (P), besides the impacts on soil hydrology. Using stoichiometric ratios and biomass estimates from two established vegetation models, we calculated the nutrient demand of AR and BG. Insufficient geogenic P supply limits C storage in biomass. For a mean P demand by AR and a lowgeogenic-P-supply scenario, AR would sequester 119 Gt C in biomass; for a high-geogenic-P-supply and low-AR-Pdemand scenario, 187 Gt C would be sequestered in biomass; and for a low geogenic P supply and high AR P demand, only 92 GtC would be accumulated by biomass. An average amount of ∼ 150 Gt basalt powder applied for EW would be needed to close global P gaps and completely sequester projected amounts of 190 Gt C during the years 2006-2099 for the mean AR P demand scenario (2-362 Gt basalt powder for the low-AR-P-demand and for the high-AR-P-demand scenarios would be necessary, respectively). The average potential of carbon sequestration by EW until 2099 is ∼ 12 GtC (∼ 0:2-∼ 27 Gt C) for the specified scenarios (excluding additional carbon sequestration via alkalinity production). For BG, 8 kg basaltm2 a1 might, on average, replenish the exported potassium (K) and P by harvest. Using pedotransfer functions, we show that the impacts of basalt powder application on soil hydraulic conductivity and plant-Available water, to close predicted P gaps, would depend on basalt and soil texture, but in general the impacts are marginal. We show that EW could potentially close the projected P gaps of an AR scenario and nutrients exported by BG harvest, which would decrease or replace the use of industrial fertilizers. Besides that, EW ameliorates the soil's capacity to retain nutrients and soil pH and replenish soil nutrient pools. Lastly, EW application could improve plant-Available-water capacity depending on deployed amounts of rock powder - adding a new dimension to the coupling of land-based biomass NETs with EW. © 2020 Royal Society of Chemistry. All rights reserved.