julilili42/papers huggingface dataset:
Managing climatic risk in cocoa by designing resilient agroforestry systems based on a functional trait approach
2023-02-26

Climate change projections indicate that significant areas of the current cocoa cultivation areas in West Africa are likely to experience unfavorable climatic conditions by 2050. Water use efficient agroforestry systems are considered to be an important option to adapt cocoa to climate change. Water use efficiency and complementary soil water use between cocoa and shade trees have been reported in previous studies in Indonesia but in our previous study in Ghana, popular native shade tree species Albizia ferruginea and Antiaris toxicaria were found to have a strong competitive water use advantage over cocoa plants during an extreme drought experienced during 2015/16. Cocoa plants under no shade were relatively more resilient with higher survival rate and post drought recovery.While past research studies &amp;#160;&amp;#160;were each limited to few selected shade tree species being investigated despite the huge numbers within cocoa landscapes. To overcome this limitation, an approach based on functional traits of trees in terms of water use is proposed to understand their effect on water use efficiency and drought resilience in cocoa agroforestry systems rather than describing individual species. We apply this concept across temporal and spatial scales in a marginally suitable cocoa climate in Ghana. Shade tree species have been categorized into phenological trait groups (evergreen, deciduous, or brevi-deciduous) under which detailed above- and belowground traits interactions with cocoa plant and effect on water use has been evaluated.The following hypotheses are being tested: (i) shade trees in the three phenological trait groups exhibit significant difference in their root and water uptake depth, and, thus, affect environmental conditions relevant for cocoa, (ii) cocoa plant above- and belowground morphological and physiological traits are influenced by shade tree phenological and morphological traits and their modification by micro-climatic (light, temperature, relative humidity and VPD), and soil (water and nutrients) conditions over different seasons.Replicated plots of 19 shade tree species distributed across the three phenological trait groups have been established for analysis of functional traits interactions in such a multi-species agroforestry system. We determine root specific traits through direct sampling, stable isotope analysis for assessment of water use portioning between the various shade tree groups and cocoa plants. Soil moisture, temperature and relative humidity and light sensors were installed in each plot. Cocoa plants under different micro-climatic impact zones of the shade trees have been monitored for a full production cycle. &amp;#160;The shade trees impact on the cocoa plant productivity (morphology and yield traits) has been evaluated. Complementary and non-complementary shade tree species with respect to their trait interactions and effect on cocoa plant productivity have been identified.
Integrated solar hydrogen production: Impact of the local climate
2023-02-26

Hydrogen as a versatile, greenhouse gas-free energy carrier will play an important role in our future economy. Yet sustainable, competitive production and distribution of hydrogen remains a challenge. Highly integrated solar water splitting systems aim to combine solar energy harvesting and electrolysis in a single device, similar to a photovoltaic module.[1] Such a system can produce hydrogen locally without the requirement to be connected to the electricity grid. Unlike large electrolysis that draws power from the grid, the power density of such a device is reduced so far that it does not require active cooling, but its operating temperature will closely follow outdoor conditions.Here, we present our work on high-efficiency integrated solar water splitting devices based on multi-junction solar absorbers. The light-absorbing component is sensitive to the shape of the solar spectrum and generally becomes more efficient at lower temperatures. Catalysis, on the other hand, benefits from higher temperatures. These conflicting trends wih respect to the temperature impact the design of the solar hydrogen production system. We analyse how the local climate affects production efficiency[2] and show in a lab study that adequate system design allows efficient operation at temperatures as low as -20&amp;#176;C.[3] These insights can help to design small-scale distributed solar hydrogen production for both temperate regions, but also more extreme climatic conditions.[1] M.M. May et al., Nature Communications 6 (2015), 8286.[2] M. K&amp;#246;lbach et al, Sustainable Energy &amp; Fuels 6 (2022), 4062.[3] M. K&amp;#246;lbach, K. Rehfeld, M.M. May, Energy &amp; Environmental Sciences 14 (2021), 4410-4417.
Extreme flood impact on riparian vegetation dynamics in the Ahr catchment, Germany
2023-02-26

On 14th and 15th July 2021 heavy rainfall in western Germany, Belgium and the Netherlands caused severe floodings. The most affected area in Germany was the 86 km long Ahr river valley, which suffered from severe damage to buildings and infrastructure and where more than 130 people died. The Ahr flood exceeded a return period of at minimum 500 years. The river Ahr drains around 900 km2 of the Rhenish Massif with a dendritic catchment from west to east causing differences in slope properties and covering different land uses. The flood water carried large woody debris that caused clogging in bridges of the main valley and some tributaries, some of which collapsed. This extreme event thus offers the opportunity to explore the spatial impact and characteristics of large wood on channel dynamics. This study aims to find thresholds for the initiation of large wood recruitment, dependent on catchment size, valley slopes, water quantity and land use.The study focuses on the whole catchment area of the Ahr river. Using general vegetation data obtained from the German national forest inventory, we quantified the type and amount of flood-affected vegetation. We adopted an NDVI (normalized differential vegetation index) based change detection approach using Landsat/Sentinel satellite data (Google Earth Engine based Hazmapper) to identify recruited live vegetation and deadwood transport during the flood. We validated this remotely obtained data with field surveys along selected valley sections.Large wood was predominantly recruited from the fluvial corridor in the main Ahr valley and not from the tributaries, even if those experienced heavy precipitation and surface runoff (up to few meters high discharge on the flood plains). Although we have observed transported tree trunks in those tributaries, there was no large pattern. We aspire to identify deposition areas using ortho photos to investigate a wood balance.Including large wood in flood modelling would improve flood hazard assessments. Remote sensing analyses offer an interim solution in this regard by helping to identify potential large wood recruitment areas and inform designing flood hazard prevention measures.
Probabilistic regionalization of soil moisture data measured by Rail-based cosmic ray neutron sensing
2023-02-26

Information about soil water content (SWC) in adequate spatial and temporal resolution is highly desired for a variety of scientific and practical applications. Cosmic-Ray Neutron Sensing (CRNS) has become an established method for passive SWC data collection, providing SWC information over several hectares, either by stationary CRNS sensors (local continuous measurements) or by mobile CRNS roving (expanding the footprint on certain field campaign days). Recent approaches of automatic rail-based CRNS roving (Rail-CRNS) allowed to expand the monitored areas further up to the kilometer scale in high temporal resolution. While a pilot study on Rail-CRNS provided promising results along the railway track, currently in daily resolution, it also raised the question of how transferable these SWC data are for areas not directly adjacent to the footprints along the railway. In this study, we have tested the performance of SWC regionalization by probabilistic predictions based on Rail-CRNS derived SWC data. A Monte Carlo approach was applied in regression random forest, using static (e.g. topographical indices, soil properties) and dynamic (precipitation) predictors and quantified their impact on the prediction accuracy. Using daily SWC values from a ~ 9 km long railway at the Harz mountain, Germany, recorded by the Rail-CRNS between September 2021 and July 2022, we predicted the daily spatial SWC variation for an area of ~ 85 km&amp;#178; and a period of 300 days on a 250 x 250 m grid. The resulting maps of gravimetric soil moisture showed realistic pattern for both, spatial and temporal SWC variation. The maps resolved spatial variation as related to land cover, seasonal SWC dynamics and individual responses of single areas to wetting and drying periods. As the demonstrated data represented the outcome of a relatively narrow area as given by the limited training Rail-CRNS data, the extension of the proposed approach by expanding the railway networks, by future technical improvements and by the automatization of the workflow has the clear potential to offer near real time SWC products for the large scale (&gt; 100 km).&amp;#160;
Microbial community dynamics and utilization of rhizodeposits and synthetic urine in grassland soils.
2023-02-26

Microbial community dynamics and utilization of rhizodeposits and synthetic urine in grassland soils.&amp;#160;Manisha Koirala 1, Yang Ding 2, Callum C. Banfield2, Michaela A. Dippold2&amp;#160;1 Biogeochemistry of Agroecosystems, University of G&amp;#246;ttingen, 37077 G&amp;#246;ttingen, Germany&amp;#160;2 Geo-Biosphere Interactions, University of T&amp;#252;bingen, 72076 T&amp;#252;bingen, Germany&amp;#160;Soil microbes thrive in a wide range of nutrient inputs and cope with an imbalanced supply of resources by adjusting their utilization strategies. In grasslands, animal urine and root exudates are essential drivers of C and macronutrient inputs and thus microbial growth and community composition, but little is known about how urine and exudates affect microbial community dynamics and utilization. In a factorial design, synthetic cow urine was applied to a Vertic Cambisol densely rooted by Dactylis glomerata. One day, four days, and 14 days after synthetic cow urine application, root-affected and not-rooted bulk soils were harvested. CFE microbial biomass, phospholipid fatty acids (PLFAs), DNA, and enzymatic activities were quantified to characterize the microbiome and its metabolic response.Shoot biomass increased by 11%, 21%, and 36% at one, four, and 14 days after urine application compared to water application respectively. Root biomass increased by 4% and 9% after four and 14 days of water application, respectively, compared to urine application. In the root-affected soil, the activity of the enzyme acid phosphatase was 26% &amp;#160;higher 14 days after water application compared to that of urine. Conversely, the activity of the &amp;#223;-glucosidase was 10% higher 14 days after cow urine application compared to water application in root-affected soil. Similarly, 14 days after urine application MBC in bulk soil was 84% higher compared to only water application. However, in the root-affected soils, MBC was 18% higher with water compared to urine application. The amount of DNA was also 0.5% higher 14 days after urine application compared to water application in the root-affected soils.This study examined and compared the metabolic response of microbial communities and microbial community dynamics due to synthetic urine and water in bulk and root-affected soil. By approaching the study of soils from chemical as well as biological perspectives, an overview of microbial adaptation and structure can be gained to maintain healthy soil in grassland ecosystems.Keywords: synthetic cow urine, grassland, soil microbial communities, root-affected soil, bulk soil, extracellular enzymes.&amp;#160;&amp;#160;&amp;#160;
Drivers of Topography in Fold-thrust Belts: A Perspective from Central Nepal
2023-02-26

Topography in compressional mountain ranges represents an interface at which tectonic and climatic forces interact. Understanding the relative contribution of these two components to mountain formation has been at the forefront of research over the last two decades. The theory underlying the mechanics that govern these interactions has been built on Coulomb wedge mechanics, i.e., mechanical failure and rock uplift occur everywhere along the wedge and the orogen. Observed rock displacement along single, discrete fault planes, including the translation of uplifted topography laterally, appears to be counter to such mechanics. However, a critically tapered topography across fold-thrust belts still emerges. If a critically tapered topography along an orogenic wedge can be produced by the sequential evolution of the subsurface fault geometry and the associated motion of bedrock over discrete fault planes, then a mechanical failure everywhere is not required. Here, the geomorphic evolution of the fold-thrust belt in central Nepal since the Miocene is investigated using a numerical surface processes model whereby the structural geometry, location and magnitude of fault motion are prescribed and based on observations. In addition, end-member climatic scenarios are adopted, i.e., uniform precipitation and climatic change over geologic time as predicted by atmospheric general circulation models. The experiments reproduce the first-order topography of central Nepal. Our modelling results indicate a dynamic variability of erosional efficacy that promotes the interplay of two modes of orogenic wedge behaviour and are contrary to a mechanical failure everywhere along the wedge: (mode 1) phases of lateral translation of uplifted topography and in-sequence propagation of deformation fronts, and (mode 2) phases of hinterland incision during out-of-sequence fault activity. The successful replication of first-order geomorphic indices in central Nepal in our experiments confirms an unusually long-lasting Miocene to Pliocene activity of the Main Boundary Thrust in central Nepal. This period is followed by Late Pleistocene hinterland incision coeval with out-of-sequence fault activity prior to the onset of rock displacement along the Main Frontal Thrust during a time of increased precipitation relative to today.&amp;#160;&amp;#160; &amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;
Quantification of uncertainty using artificial neural networks for mapping of soil properties in Germany
2023-02-26

Machine learning models have been widely used in digital soil mapping to predict the spatial distribution of soil properties across the landscape. However, due to the unpredictable behavior of soil properties, insufficient training sample size, input data error, uncertainty in model parameters and structure, uncertainty inherently exists in machine learning predictions. Therefore, knowledge of prediction uncertainty is vital for decision-makers and end-users. This study quantifies the overall uncertainty of digital soil maps of Germany for soil acidity, organic carbon, cation exchange capacity, and clay using quantile regression forest (QRF) and artificial neural network (ANN) models. Here, we propose the use of a novel ANN model that directly estimates the lower and upper bounds of a prediction interval by using an architecture with two output neurons. A multi-objective evolutionary algorithm (i.e., non-dominated sorting genetic algorithm II) was employed to parameterize the ANN weights. The results of the modeling indicated that ANN performed better than the QRF for predicting soil properties. Additionally, the ANNs produced narrower prediction intervals in comparison to the QRF. Most importantly, ANN yielded prediction interval coverage probabilities that were more closely aligned to their associated confidence levels in comparison to the QRF. In general, the ANNs were not only effective in predicting soil properties, but they were also effective in constructing reasonable prediction intervals for soil characteristics; and therefore, it is recommended to be used for predicting soil properties and quantifying their uncertainty in digital soil mapping.Keywords: uncertainty estimation, prediction interval, multi-objective optimization, artificial neural networks, machine learning, Germany
Long-term hydrologic connectivity on the Australian dryland margins: evidence from the Willandra Lakes World Heritage Area over the last 60 ky
2023-02-26

The recent catastrophic flooding across the world&amp;#8217;s driest inhabited continent &amp;#8211; Australia &amp;#8211; has highlighted an urgent need to understand the climatic (atmospheric) and hydrological (land surface) mechanisms comprising hydroclimate. Records of past hydrologic change may help in this endeavor by informing us about different hydroclimate states and their manifestation on the land surface. By virtue of its antiquity, aridity and relative paucity of available sediment, however, the Australian continent preserves few records of long-term hydroclimate. As a result, we know little about long-term water availability and the drivers of surface hydrology and climate circulation, particularly for the dry inland regions where water resources and sensitive land surfaces need to be carefully managed.&amp;#160;One of the few areas in dryland Australia which preserves semi-continuous deposition of hydrologic change is the Willandra Lakes system. The Willandra Lakes are located on the semi-arid desert margin of southeastern Australia, yet its headwaters lie in the temperate eastern highlands. Long-term lake filling and drying is consequently driven by rainfall in the headwaters and hydrologic connectivity both across the catchment and between the lakes. These environmental changes &amp;#8211; both long and short in duration &amp;#8211; are recorded in the sediments of the downwind transverse dunes (lunettes). In this study we investigate long-term hydrologic connectivity across the catchment and between the lakes. Our approach uses a novel integration of both classical lake-level reconstruction based on lunette sedimentology, stratigraphy and luminescence geochronology, with hydrologic modelling of key event time slices over the last 60 ky, fed into a palaeoclimate model. We characterize the land-surface response to various hydroclimate states, so improving our understanding of dryland atmosphere-hydrosphere interactions.&amp;#160;
Concepts of geodiversity and biodiversity interactions across different scales
2023-02-26

&amp;lt;p&amp;gt;It has been proposed that geodiversity (the diversity of geological, geomorphological and pedological features) is positively correlated with biodiversity. This suggests that by preserving geodiversity, we can also preserve biodiversity and the associated ecosystem functions. However, a significant correlation between geodiversity and biodiversity measures does not mean causation and does not distinguish spatial and temporal scale dependencies of the processes involved. In fact, such a correlation could also imply that biodiversity estimates can predict geodiversity. These aspects have, nonetheless, rarely been considered in geo- and biodiversity studies, which constrains the applicability of these analyses in, for example, models of geo- and biodiversity distribution that rely on explicit processes. We aim to explore the interactions between geo- and biodiversity across different scales, identifying the key mechanisms that link them.&amp;lt;/p&amp;gt; &amp;lt;p&amp;gt;The feedbacks between geodiversity and biodiversity start at the microscale during the process of soil aggregation and formation, driven by microbial diversity such as fungi and biological soil crusts, as well as by plant roots. On the other hand, soil texture defines microsites for microbial life, and surface types and quality shape their colonization process. At intermediate landform or catchment scales, the spatial variability of topographical, lithological and soil features benefits the formation of diverse habitats and resources for biota (e.g. plants, vertebrates and invertebrates), which, at the same time, will affect radiation distribution, erosion and nutrient availability. At even larger scales, processes like mantle dynamics and the number of plate boundaries can determine regional-scale shifts in ecosystems, isolation processes and the evolution of biota. Similarly, temporal variability determined by, e.g. microclimate, catchment scale meteorology or orographic effects, induces niche variability within a spatial scale. Finally, based on these process-related relationships at variable scales, we suggest a list of geodiversity parameters to be used when assessing geo- and biodiversity interactions.&amp;lt;/p&amp;gt;
Diagnosis and management of complications from the treatment of primary central nervous system tumors in adults
2023-02-27

Abstract Central nervous system (CNS) tumor patients commonly undergo multimodality treatment in the course of their disease. Adverse effects and complications from these interventions have not been systematically studied, but pose significant challenges in clinical practice and impact function and quality of life, especially in the management of long-term brain tumor survivors. Here, the European Association of Neuro-Oncology (EANO) has developed recommendations to prevent, diagnose, and manage adverse effects and complications in the adult primary brain CNS tumor (except lymphomas) patient population with a specific focus on surgery, radiotherapy, and pharmacotherapy. Specifically, we also provide recommendations for dose adaptations, interruptions, and reexposure for pharmacotherapy that may serve as a reference for the management of standard of care in clinical trials. We also summarize which interventions are unnecessary, inactive or contraindicated. This consensus paper should serve as a reference for the conduct of standard therapy within and outside of clinical trials.
Synthesize of pluronic-based nanovesicular formulation loaded with Pistacia atlantica extract for improved antimicrobial efficiency
2023-02-27

One of the current concerns to human health is antibiotic resistance, which promotes the use of antibiotics that are more harmful, expensive, and ineffective. In this condition, researchers are turning to innovative options to combat this alarming situation. Combining herbal medicine with nanotechnology has created a new strategy to increase the effectiveness of phytochemical compounds in overcoming antimicrobial resistance. Pistacia atlantica is one of the promising herbs with medicinal benefits, but its poor solubility in biological fluids is challenging. In this regard, we seek to evaluate the antibacterial efficacy of Pistacia atlantica extract-loaded nanovesicle. Cholesterol, Span 40, and Pluronic F127 modified nanoformulation was developed using an environmentally friendly improved heating technique, and it was evaluated for size distribution, zeta potential, morphology, entrapment efficiency (EE%), release behavior, stability, and antimicrobial performance. By using DLS, spherical nanovesicles were identified with a size distribution of 50–150 nm and a zeta potential of −43 mV. The extract's encapsulation efficiency was 72.03%. The developed loaded nanovesicles demonstrated controlled extract release in the tested 96 h and storage stability of at least 12 months at 25 °C. Also, Comparing the two samples, the encapsulated extract had greater antibacterial activity against Candida albicans, Staphylococcus aureus, and Pseudomonas plecoglossicida with MIC of 1320, 570, and 1100 μg/mL, respectively. Besides reducing the misuse of antibiotics by allowing for the controlled release of drugs made from natural sources, we expect the findings described here to help provide alternative plant-based formulations with greater stability and antibacterial activity.