500 Naturwissenschaften und Mathematik
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The most profound shift in the African hydroclimate of the last 1 million years occurred around 300 thousand years (ka) ago.
This change in African hydroclimate is manifest as an east-west change in moisture balance that cannot be fully explained through linkages to high latitude climate systems.
The east-west shift is, instead, probably driven by a shift in the tropical Walker Circulation related to sea surface temperature change driven by orbital forcing. Comparing records of past vegetation change, and hominin evolution and development, with this breakpoint in the climate system is challenging owing to the paucity of study sites available and uncertainties regarding the dating of records. Notwithstanding these uncertainties we find that, broadly speaking, both vegetation and hominins change around 300 ka.
The vegetative backdrop suggests that relative abundance of vegetative resources shifted from western to eastern Africa, although resources would have persisted across the continent.
The climatic and vegetation changes probably provided challenges for hominins and are broadly coincident with the appearance of Homo sapiens (ca 315 ka) and the emergence of Middle Stone Age technology.
The concomitant changes in climate, vegetation and hominin evolution suggest that these factors are closely intertwined.
This article is part of the theme issue 'Tropical forests in the deep human past'.
In-depth understanding of the reorganization of the hydrological cycle in response to global climate change is crucial in highly sensitive regions like the eastern Mediterranean, where water availability is a major factor for socioeconomic and political development.
The sediments of Lake Lisan provide a unique record of hydroclimatic change during the last glacial to Holocene transition (ca. 24-11 ka) with its tremendous water level drop of similar to 240 m that finally led to its transition into the present hypersaline water body-the Dead Sea.
Here we utilize high-resolution sedimentological analyses from the marginal terraces and deep lake to reconstruct an unprecedented seasonal record of the last millennia of Lake Lisan. Aragonite varve formation in intercalated intervals of our record demonstrates that a stepwise long-term lake level decline was interrupted by almost one millennium of rising or stable water level.
Even periods of pronounced water level drops indicated by gypsum deposition were interrupted by decades of positive water budgets.
Our results thus highlight that even during major climate change at the end of the last glacial, decadal to millennial periods of relatively stable or positive moisture supply occurred which could have been an important premise for human sedentism.
A detailed investigation of the energy levels of perylene-3,4,9,10-tetracarboxylic tetraethylester as a representative compound for the whole family of perylene esters was performed. It was revealed via electrochemical measurements that one oxidation and two reductions take place. The bandgaps determined via the electrochemical approach are in good agreement with the optical bandgap obtained from the absorption spectra via a Tauc plot. In addition, absorption spectra in dependence of the electrochemical potential were the basis for extensive quantum-chemical calculations of the neutral, monoanionic, and dianionic molecules. For this purpose, calculations based on density functional theory were compared with post-Hartree-Fock methods and the CAM-B3LYP functional proved to be the most reliable choice for the calculation of absorption spectra. Furthermore, spectral features found experimentally could be reproduced with vibronic calculations and allowed to understand their origins. In particular, the two lowest energy absorption bands of the anion are not caused by absorption of two distinct electronic states, which might have been expected from vertical excitation calculations, but both states exhibit a strong vibronic progression resulting in contributions to both bands.
Heteromeric HSFA2/HSFA3 complexes drive transcriptional memory after heat stress in Arabidopsis
(2021)
Adaptive plasticity in stress responses is a key element of plant survival strategies. For instance, moderate heat stress (HS) primes a plant to acquire thermotolerance, which allows subsequent survival of more severe HS conditions. Acquired thermotolerance is actively maintained over several days (HS memory) and involves the sustained induction of memory-related genes. Here we show that FORGETTER3/ HEAT SHOCK TRANSCRIPTION FACTOR A3 (FGT3/HSFA3) is specifically required for physiological HS memory and maintaining high memory-gene expression during the days following a HS exposure. HSFA3 mediates HS memory by direct transcriptional activation of memory-related genes after return to normal growth temperatures. HSFA3 binds HSFA2, and in vivo both proteins form heteromeric complexes with additional HSFs. Our results indicate that only complexes containing both HSFA2 and HSFA3 efficiently promote transcriptional memory by positively influencing histone H3 lysine 4 (H3K4) hyper-methylation. In summary, our work defines the major HSF complex controlling transcriptional memory and elucidates the in vivo dynamics of HSF complexes during somatic stress memory. Moderate heat stress primes plants to acquire tolerance to subsequent, more severe heat stress. Here the authors show that the HSFA3 transcription factor forms a heteromeric complex with HSFA2 to sustain activated transcription of genes required for acquired thermotolerance by promoting H3K4 hyper-methylation.
Active matter broadly covers the dynamics of self-propelled particles.
While the onset of collective behavior in homogenous active systems is relatively well understood, the effect of inhomogeneities such as obstacles and traps lacks overall clarity.
Here, we study how interacting, self-propelled particles become trapped and released from a trap.
We have found that captured particles aggregate into an orbiting condensate with a crystalline structure. As more particles are added, the trapped condensates escape as a whole.
Our results shed light on the effects of confinement and quenched disorder in active matter.
Complex networks are abundant in nature and many share an important structural property: they contain a few nodes that are abnormally highly connected (hubs). Some of these hubs are called influencers because they couple strongly to the network and play fundamental dynamical and structural roles. Strikingly, despite the abundance of networks with influencers, little is known about their response to stochastic forcing. Here, for oscillatory dynamics on influencer networks, we show that subjecting influencers to an optimal intensity of noise can result in enhanced network synchronization. This new network dynamical effect, which we call coherence resonance in influencer networks, emerges from a synergy between network structure and stochasticity and is highly nonlinear, vanishing when the noise is too weak or too strong. Our results reveal that the influencer backbone can sharply increase the dynamical response in complex systems of coupled oscillators. Influencer networks include a small set of highly-connected nodes and can reach synchrony only via strong node interaction. Tonjes et al. show that introducing an optimal amount of noise enhances synchronization of such networks, which may be relevant for neuroscience or opinion dynamics applications.
Sporadic E or Es is a transient phenomenon where thin layers of enhanced electron density appear in the ionospheric E region (90-120 km altitude). The neutral wind shear caused by atmospheric tides can lead ions to converge vertically at E-region heights and form the Es layer. This research aims to determine the role of atmospheric solar and lunar tides in Es occurrence. For this purpose, radio occultation data of FORMOSAT-3/COSMIC have been used, which provide complete global coverage of Es events. Moreover, GAIA model simulations have been employed to evaluate the vertical ion convergence induced by solar tides. The results show both migrating and non-migrating solar tidal signatures and the semidiurnal migrating lunar tidal signature mainly in low and mid-latitude Es occurrence. The seasonal variation of the migrating solar tidal components of Es is in good agreement with those in the vertical ion convergence derived from GAIA at higher altitudes. Furthermore, some non-migrating components of solar tides, including semidiurnal westward wavenumbers 1 and 3 and diurnal eastward wavenumbers 2 and 3, also significantly affect the Es occurrence rate.
Drought and the availability of mineable phosphorus minerals used for fertilization are two of the important issues agriculture is facing in the future. High phosphorus availability in soils is necessary to maintain high agricultural yields. Drought is one of the major threats for terrestrial ecosystem performance and crop production in future. Among the measures proposed to cope with the upcoming challenges of intensifying drought stress and to decrease the need for phosphorus fertilizer application is the fertilization with silica (Si). Here we tested the importance of soil Si fertilization on wheat phosphorus concentration as well as wheat performance during drought at the field scale. Our data clearly showed a higher soil moisture for the Si fertilized plots. This higher soil moisture contributes to a better plant performance in terms of higher photosynthetic activity and later senescence as well as faster stomata responses ensuring higher productivity during drought periods. The plant phosphorus concentration was also higher in Si fertilized compared to control plots. Overall, Si fertilization or management of the soil Si pools seem to be a promising tool to maintain crop production under predicted longer and more serve droughts in the future and reduces phosphorus fertilizer requirements.
Changing climatic conditions and unsustainable land use are major threats to savannas worldwide. Historically, many African savannas were used intensively for livestock grazing, which contributed to widespread patterns of bush encroachment across savanna systems. To reverse bush encroachment, it has been proposed to change the cattle-dominated land use to one dominated by comparatively specialized browsers and usually native herbivores. However, the consequences for ecosystem properties and processes remain largely unclear. We used the ecohydrological, spatially explicit model EcoHyD to assess the impacts of two contrasting, herbivore land-use strategies on a Namibian savanna: grazer- versus browser-dominated herbivore communities. We varied the densities of grazers and browsers and determined the resulting composition and diversity of the plant community, total vegetation cover, soil moisture, and water use by plants. Our results showed that plant types that are less palatable to herbivores were best adapted to grazing or browsing animals in all simulated densities. Also, plant types that had a competitive advantage under limited water availability were among the dominant ones irrespective of land-use scenario. Overall, the results were in line with our expectations: under high grazer densities, we found heavy bush encroachment and the loss of the perennial grass matrix. Importantly, regardless of the density of browsers, grass cover and plant functional diversity were significantly higher in browsing scenarios. Browsing herbivores increased grass cover, and the higher total cover in turn improved water uptake by plants overall. We concluded that, in contrast to grazing-dominated land-use strategies, land-use strategies dominated by browsing herbivores, even at high herbivore densities, sustain diverse vegetation communities with high cover of perennial grasses, resulting in lower erosion risk and bolstering ecosystem services.
Charitable giving
(2023)
We investigate how different levels of information influence the allocation decisions of donors who are entitled to freely distribute a fixed monetary endowment between themselves and a charitable organization in both giving and taking frames. Participants donate significantly higher amounts, when the decision is described as taking rather than giving. This framing effect becomes smaller if more information about the charity is provided.
Forest microclimate can buffer biotic responses to summer heat waves, which are expected to become more extreme under climate warming. Prediction of forest microclimate is limited because meteorological observation standards seldom include situations inside forests.
We use eXtreme Gradient Boosting - a Machine Learning technique - to predict the microclimate of forest sites in Brandenburg, Germany, using seasonal data comprising weather features.
The analysis was amended by applying a SHapley Additive explanation to show the interaction effect of variables and individualised feature attributions.
We evaluate model performance in comparison to artificial neural networks, random forest, support vector machine, and multi-linear regression.
After implementing a feature selection, an ensemble approach was applied to combine individual models for each forest and improve robustness over a given single prediction model.
The resulting model can be applied to translate climate change scenarios into temperatures inside forests to assess temperature-related ecosystem services provided by forests.
Many phenomena of high relevance for economic development such as human capital, geography and climate vary considerably within countries as well as between them. Yet, global data sets of economic output are typically available at the national level only, thereby limiting the accuracy and precision of insights gained through empirical analyses. Recent work has used interpolation and downscaling to yield estimates of sub-national economic output at a global scale, but respective data sets based on official, reported values only are lacking. We here present DOSE — the MCC-PIK Database Of Sub-national Economic Output. DOSE contains harmonised data on reported economic output from 1,661 sub-national regions across 83 countries from 1960 to 2020. To avoid interpolation, values are assembled from numerous statistical agencies, yearbooks and the literature and harmonised for both aggregate and sectoral output. Moreover, we provide temporally- and spatially-consistent data for regional boundaries, enabling matching with geo-spatial data such as climate observations. DOSE provides the opportunity for detailed analyses of economic development at the subnational level, consistent with reported values.
Genetic population structure defines wild boar as an urban exploiter species in Barcelona, Spain
(2022)
Urban wildlife ecology is gaining relevance as metropolitan areas grow throughout the world, reducing natural habitats and creating new ecological niches.
However, knowledge is still scarce about the colonisation processes of such urban niches, the establishment of new communities, populations and/or species, and the related changes in behaviour and life histories of urban wildlife.
Wild boar (Sus scrofa) has successfully colonised urban niches throughout Europe.
The aim of this study is to unveil the processes driving the establishment and maintenance of an urban wild boar population by analysing its genetic structure.
A set of 19 microsatellite loci was used to test whether urban wild boars in Barcelona, Spain, are an isolated population or if gene flow prevents genetic differentiation between rural and urban wild boars.
This knowledge will contribute to the understanding of the effects of synurbisation and the associated management measures on the genetic change of large mammals in urban ecosystems. Despite the unidirectional gene flow from rural to urban areas, the urban wild boars in Barcelona form an island population genotypically differentiated from the surrounding rural ones.
The comparison with previous genetic studies of urban wild boar populations suggests that forest patches act as suitable islands for wild boar genetic differentiation.
Previous results and the genetic structure of the urban wild boar population in Barcelona classify wild boar as an urban exploiter species.
These wild boar peri-urban island populations are responsible for conflict with humans and thus should be managed by reducing the attractiveness of urban areas.
The management of peri-urban wild boar populations should aim at reducing migration into urban areas and preventing phenotypic changes (either genetic or plastic) causing habituation of wild boars to humans and urban environments.
The stability of the Greenland Ice Sheet under global warming is governed by a number of dynamic processes and interacting feedback mechanisms in the ice sheet, atmosphere and solid Earth.
Here we study the long-term effects due to the interplay of the competing melt-elevation and glacial isostatic adjustment (GIA) feedbacks for different temperature step forcing experiments with a coupled ice-sheet and solid-Earth model.
Our model results show that for warming levels above 2 degrees C, Greenland could become essentially ice-free within several millennia, mainly as a result of surface melting and acceleration of ice flow. These ice losses are mitigated, however, in some cases with strong GIA feedback even promoting an incomplete recovery of the Greenland ice volume. We further explore the full-factorial parameter space determining the relative strengths of the two feedbacks: our findings suggest distinct dynamic regimes of the Greenland Ice Sheets on the route to destabilization under global warming - from incomplete recovery, via quasi-periodic oscillations in ice volume to ice-sheet collapse.
In the incomplete recovery regime, the initial ice loss due to warming is essentially reversed within 50 000 years, and the ice volume stabilizes at 61 %-93 % of the present-day volume. For certain combinations of temperature increase, atmospheric lapse rate and mantle viscosity, the interaction of the GIA feedback and the melt-elevation feedback leads to self-sustained, long-term oscillations in ice-sheet volume with oscillation periods between 74 000 and over 300 000 years and oscillation amplitudes between 15 %-70 % of present-day ice volume.
This oscillatory regime reveals a possible mode of internal climatic variability in the Earth system on timescales on the order of 100 000 years that may be excited by or synchronized with orbital forcing or interact with glacial cycles and other slow modes of variability. Our findings are not meant as scenario-based near-term projections of ice losses but rather providing insight into of the feedback loops governing the "deep future" and, thus, long-term resilience of the Greenland Ice Sheet.
Geostatistics as a subfield of statistics accounts for the spatial correlations encountered in many applications of, for example, earth sciences. Valuable information can be extracted from these correlations, also helping to address the often encountered burden of data scarcity. Despite the value of additional data, the use of geostatistics still falls short of its potential. This problem is often connected to the lack of user-friendly software hampering the use and application of geostatistics. We therefore present GSTools, a Python-based software suite for solving a wide range of geostatistical problems. We chose Python due to its unique balance between usability, flexibility, and efficiency and due to its adoption in the scientific community. GSTools provides methods for generating random fields; it can perform kriging, variogram estimation and much more. We demonstrate its abilities by virtue of a series of example applications detailing their use.
Global change is shifting the timing of biological events, leading to temporal mismatches between biological events and resource availability. These temporal mismatches can threaten species' populations. Importantly, temporal mismatches not only exert strong pressures on the population dynamics of the focal species, but can also lead to substantial changes in pairwise species interactions such as host-pathogen systems. We adapted an established individual-based model of host-pathogen dynamics. The model describes a viral agent in a social host, while accounting for the host's explicit movement decisions. We aimed to investigate how temporal mismatches between seasonal resource availability and host life-history events affect host-pathogen coexistence, that is, disease persistence. Seasonal resource fluctuations only increased coexistence probability when in synchrony with the hosts' biological events. However, a temporal mismatch reduced host-pathogen coexistence, but only marginally. In tandem with an increasing temporal mismatch, our model showed a shift in the spatial distribution of infected hosts. It shifted from an even distribution under synchronous conditions toward the formation of disease hotspots, when host life history and resource availability mismatched completely. The spatial restriction of infected hosts to small hotspots in the landscape initially suggested a lower coexistence probability due to the critical loss of susceptible host individuals within those hotspots. However, the surrounding landscape facilitated demographic rescue through habitat-dependent movement. Our work demonstrates that the negative effects of temporal mismatches between host resource availability and host life history on host-pathogen coexistence can be reduced through the formation of temporary disease hotspots and host movement decisions, with implications for disease management under disturbances and global change.
In many species, dispersal is decisive for survival in a changing climate. Simulation models for population dynamics under climate change thus need to account for this factor. Moreover, large numbers of species inhabiting agricultural landscapes are subject to disturbances induced by human land use. We included dispersal in the HiLEG model that we previously developed to study the interaction between climate change and agricultural land use in single populations. Here, the model was parameterized for the large marsh grasshopper (LMG) in cultivated grasslands of North Germany to analyze (1) the species development and dispersal success depending on the severity of climate change in subregions, (2) the additional effect of grassland cover on dispersal success, and (3) the role of dispersal in compensating for detrimental grassland mowing. Our model simulated population dynamics in 60-year periods (2020-2079) on a fine temporal (daily) and high spatial (250 x 250 m(2)) scale in 107 subregions, altogether encompassing a range of different grassland cover, climate change projections, and mowing schedules. We show that climate change alone would allow the LMG to thrive and expand, while grassland cover played a minor role. Some mowing schedules that were harmful to the LMG nevertheless allowed the species to moderately expand its range. Especially under minor climate change, in many subregions dispersal allowed for mowing early in the year, which is economically beneficial for farmers. More severe climate change could facilitate LMG expansion to uninhabited regions but would require suitable mowing schedules along the path. These insights can be transferred to other species, given that the LMG is considered a representative of grassland communities. For more specific predictions on the dynamics of other species affected by climate change and land use, the publicly available HiLEG model can be easily adapted to the characteristics of their life cycle.
To better understand the role of individual and lifestyle factors in human disease, an exposome-wide association study was performed to investigate within a single-study anthropometry measures and lifestyle factors previously associated with B-cell lymphoma (BCL). Within the European Prospective Investigation into Cancer and nutrition study, 2402 incident BCL cases were diagnosed from 475 426 participants that were followed-up on average 14 years. Standard and penalized Cox regression models as well as principal component analysis (PCA) were used to evaluate 84 exposures in relation to BCL risk. Standard and penalized Cox regression models showed a positive association between anthropometric measures and BCL and multiple myeloma/plasma cell neoplasm (MM). The penalized Cox models additionally showed the association between several exposures from categories of physical activity, smoking status, medical history, socioeconomic position, diet and BCL and/or the subtypes. PCAs confirmed the individual associations but also showed additional observations. The PC5 including anthropometry, was positively associated with BCL, diffuse large B-cell lymphoma (DLBCL) and MM. There was a significant positive association between consumption of sugar and confectionary (PC11) and follicular lymphoma risk, and an inverse association between fish and shellfish and Vitamin D (PC15) and DLBCL risk. The PC1 including features of the Mediterranean diet and diet with lower inflammatory score showed an inverse association with BCL risk, while the PC7, including dairy, was positively associated with BCL and DLBCL risk. Physical activity (PC10) was positively associated with DLBCL risk among women. This study provided informative insights on the etiology of BCL.
A path in an edge-colored graph is rainbow if no two edges of it are colored the same, and the graph is rainbow-connected if there is a rainbow path between each pair of its vertices. The minimum number of colors needed to rainbow-connect a graph G is the rainbow connection number of G, denoted by rc(G).& nbsp;A simple way to rainbow-connect a graph G is to color the edges of a spanning tree with distinct colors and then re-use any of these colors to color the remaining edges of G. This proves that rc(G) <= |V (G)|-1. We ask whether there is a stronger connection between tree-like structures and rainbow coloring than that is implied by the above trivial argument. For instance, is it possible to find an upper bound of t(G)-1 for rc(G), where t(G) is the number of vertices in the largest induced tree of G? The answer turns out to be negative, as there are counter-examples that show that even c .t(G) is not an upper bound for rc(G) for any given constant c.& nbsp;In this work we show that if we consider the forest number f(G), the number of vertices in a maximum induced forest of G, instead of t(G), then surprisingly we do get an upper bound. More specifically, we prove that rc(G) <= f(G) + 2. Our result indicates a stronger connection between rainbow connection and tree-like structures than that was suggested by the simple spanning tree based upper bound.
Adverse environmental conditions are detrimental to plant growth and development. Acclimation to abiotic stress conditions involves activation of signaling pathways which often results in changes in gene expression via networks of transcription factors (TFs). Mediator is a highly conserved co-regulator complex and an essential component of the transcriptional machinery in eukaryotes. Some Mediator subunits have been implicated in stress-responsive signaling pathways; however, much remains unknown regarding the role of plant Mediator in abiotic stress responses. Here, we use RNA-seq to analyze the transcriptional response of Arabidopsis thaliana to heat, cold and salt stress conditions. We identify a set of common abiotic stress regulons and describe the sequential and combinatorial nature of TFs involved in their transcriptional regulation. Furthermore, we identify stress-specific roles for the Mediator subunits MED9, MED16, MED18 and CDK8, and putative TFs connecting them to different stress signaling pathways. Our data also indicate different modes of action for subunits or modules of Mediator at the same gene loci, including a co-repressor function for MED16 prior to stress. These results illuminate a poorly understood but important player in the transcriptional response of plants to abiotic stress and identify target genes and mechanisms as a prelude to further biochemical characterization.
Stem cells are capable of sensing and processing environmental inputs, converting this information to output a specific cell lineage through signaling cascades. Despite the combinatorial nature of mechanical, thermal, and biochemical signals, these stimuli have typically been decoupled and applied independently, requiring continuous regulation by controlling units. We employ a programmable polymer actuator sheet to autonomously synchronize thermal and mechanical signals applied to mesenchymal stem cells (MSC5). Using a grid on its underside, the shape change of polymer sheet, as well as cell morphology, calcium (Ca2+) influx, and focal adhesion assembly, could be visualized and quantified. This paper gives compelling evidence that the temperature sensing and mechanosensing of MSC5 are interconnected via intracellular Ca2+. Up-regulated Ca2+ levels lead to a remarkable alteration of histone H3K9 acetylation and activation of osteogenic related genes. The interplay of physical, thermal, and biochemical signaling was utilized to accelerate the cell differentiation toward osteogenic lineage. The approach of programmable bioinstructivity provides a fundamental principle for functional biomaterials exhibiting multifaceted stimuli on differentiation programs. Technological impact is expected in the tissue engineering of periosteum for treating bone defects.
Stem cells are capable of sensing and processing environmental inputs, converting this information to output a specific cell lineage through signaling cascades. Despite the combinatorial nature of mechanical, thermal, and biochemical signals, these stimuli have typically been decoupled and applied independently, requiring continuous regulation by controlling units. We employ a programmable polymer actuator sheet to autonomously synchronize thermal and mechanical signals applied to mesenchymal stem cells (MSC5). Using a grid on its underside, the shape change of polymer sheet, as well as cell morphology, calcium (Ca2+) influx, and focal adhesion assembly, could be visualized and quantified. This paper gives compelling evidence that the temperature sensing and mechanosensing of MSC5 are interconnected via intracellular Ca2+. Up-regulated Ca2+ levels lead to a remarkable alteration of histone H3K9 acetylation and activation of osteogenic related genes. The interplay of physical, thermal, and biochemical signaling was utilized to accelerate the cell differentiation toward osteogenic lineage. The approach of programmable bioinstructivity provides a fundamental principle for functional biomaterials exhibiting multifaceted stimuli on differentiation programs. Technological impact is expected in the tissue engineering of periosteum for treating bone defects.
The Ca Mau peninsula (CMP) is a key economic region in southern Vietnam. In recent decades, the high demand for water has increased the exploitation of groundwater, thus lowering the groundwater level and leading to risks of degradation, depletion, and land subsidence, as well as salinity intrusion in the groundwater of the whole Mekong Delta region. By using a finite element groundwater model with boundary expansion to the sea, we updated the latest data on hydrogeological profiles, groundwater levels, and exploitation. The basic model setup covers seven aquifers and seven aquitards. It is determined that the inflow along the coastline to the mainland is 39% of the total inflow. The exploitation of the study area in 2019 was 567,364 m(3)/day. The most exploited aquifers are the upper-middle Pleistocene (qp(2-3)) and the middle Pliocene (n(2)(2)), accounting for 63.7% and 24.6%, respectively; the least exploited aquifers are the upper Pleistocene and the upper Miocene, accounting for 0.35% and 0.02%, respectively. In the deeper aquifers, qp(2-3) and n(2)(2), the change in storage is negative due to the high exploitation rate, leading to a decline in the reserves of these aquifers. These groundwater model results are the calculations of groundwater reserves from the coast to the mainland in the entire system of aquifers in the CMP. This makes groundwater decision managers, stakeholders, and others more efficient in sustainable water resources planning in the CMP and Mekong Delta (MKD).
The mammalian system of energy balance regulation is intrinsically rhythmic with diurnal oscillations of behavioral and metabolic traits according to the 24 h day/night cycle, driven by cellular circadian clocks and synchronized by environmental or internal cues such as metabolites and hormones associated with feeding rhythms. Mitochondria are crucial organelles for cellular energy generation and their biology is largely under the control of the circadian system. Whether mitochondrial status might also feed-back on the circadian system, possibly via mitokines that are induced by mitochondrial stress as endocrine-acting molecules, remains poorly understood. Here, we describe our current understanding of the diurnal regulation of systemic energy balance, with focus on fibroblast growth factor 21 (FGF21) and growth differentiation factor 15 (GDF15), two well-known endocrine-acting metabolic mediators. FGF21 shows a diurnal oscillation and directly affects the output of the brain master clock. Moreover, recent data demonstrated that mitochondrial stress-induced GDF15 promotes a day-time restricted anorexia and systemic metabolic remodeling as shown in UCP1-transgenic mice, where both FGF21 and GDF15 are induced as myomitokines. In this mouse model of slightly uncoupled skeletal muscle mitochondria GDF15 proved responsible for an increased metabolic flexibility and a number of beneficial metabolic adaptations. However, the molecular mechanisms underlying energy balance regulation by mitokines are just starting to emerge, and more data on diurnal patterns in mouse and man are required. This will open new perspectives into the diurnal nature of mitokines and action both in health and disease.
Increasing greenhouse gas emissions are likely to impact not only natural systems but economies worldwide. If these impacts alter future economic development, the financial losses will be significantly higher than the mere direct damages. So far, potentially aggravating investment responses were considered negligible. Here we consistently incorporate an empirically derived temperature-growth relation into the simple integrated assessment model DICE. In this framework we show that, if in the next eight decades varying temperatures impact economic growth as has been observed in the past three decades, income is reduced by similar to 20% compared to an economy unaffected by climate change. Hereof similar to 40% are losses due to growth effects of which similar to 50% result from reduced incentive to invest. This additional income loss arises from a reduced incentive for future investment in anticipation of a reduced return and not from an explicit climate protection policy. Under economically optimal climate-change mitigation, however, optimal investment would only be reduced marginally as mitigation efforts keep returns high.
Closing the emissions gap between Nationally Determined Contributions (NDCs) and the global emissions levels needed to achieve the Paris Agreement’s climate goals will require a comprehensive package of policy measures. National and sectoral policies can help fill the gap, but success stories in one country cannot be automatically replicated in other countries. They need to be adapted to the local context. Here, we develop a new Bridge scenario based on nationally relevant, short-term measures informed by interactions with country experts. These good practice policies are rolled out globally between now and 2030 and combined with carbon pricing thereafter. We implement this scenario with an ensemble of global integrated assessment models. We show that the Bridge scenario closes two-thirds of the emissions gap between NDC and 2 °C scenarios by 2030 and enables a pathway in line with the 2 °C goal when combined with the necessary long-term changes, i.e. more comprehensive pricing measures after 2030. The Bridge scenario leads to a scale-up of renewable energy (reaching 52%–88% of global electricity supply by 2050), electrification of end-uses, efficiency improvements in energy demand sectors, and enhanced afforestation and reforestation. Our analysis suggests that early action via good-practice policies is less costly than a delay in global climate cooperation.
Aviation and shipping currently contribute approximately 8% of total anthropogenic CO2 emissions, with growth in tourism and global trade projected to increase this contribution further(1-3). Carbon-neutral transportation is feasible with electric motors powered by rechargeable batteries, but is challenging, if not impossible, for long-haul commercial travel, particularly airtravel(4). A promising solution are drop-in fuels (synthetic alternatives for petroleum-derived liquid hydrocarbon fuels such as kerosene, gasoline or diesel) made from H2O and CO2 by solar-driven processes(5-7).Among the many possible approaches, the thermochemical path using concentrated solar radiation as the source of high-temperature process heat offers potentially high production rates and efficiencies(8), and can deliver truly carbon-neutral fuels if the required CO2 is obtained directly from atmospheric air(9) . If H2O is also extracted from air(10), feedstock sourcing and fuel production can be colocated in desert regions with high solar irradiation and limited accessto water resources. While individual steps of such a scheme have been implemented, here we demonstrate the operation of the entire thermochemical solar fuel production chain, from H2O and CO2 captured directly from ambient air to the synthesis of drop-in transportation fuels (for example, methanol and kerosene), with a modular 5 kW(thermal) pilot-scale solar system operated under field conditions. We further identify the research and development efforts and discuss the economic viability and policies required to bring these solar fuels to market.
The degree of completeness of large-scale floristic inventories is often difficult to judge. We compared prior vascular plant species inventories of the Mediterranean island of Limnos (North Aegean, Greece) with 231 recent records from 2016-2021. Together with the recent records, the known number of vascular plant species on the island is 960 native taxa, 63 established neophytes, and 27 species of as yet casual status for a total of 1050 taxa. We looked at a number of traits (plant family, size, flower color, perceptibility, habitat, reproduction period, rarity, and status) to investigate whether they were overrepresented in the dataset of the newly found taxa. Overrepresentation was found in some plant families (e.g., Poaceae and Chenopodiaceae) and for traits such as hydrophytic life form, unobtrusive flower color, coastal as well as agricultural and ruderal habitats, and late (summer/autumn) reproduction period. Apart from the well-known fact of esthetic bias, we found evidence for ecological and perceptibility biases. Plant species inventories based on prior piecemeal collated data should focus on regionally specific species groups and underrepresented and rare habitats.
When new covalent organic frameworks (COFs) are designed, the main efforts are typically focused on selecting specific building blocks with certain geometries and properties to control the structure and function of the final COFs. The nature of the linkage (imine, boroxine, vinyl, etc.) between these building blocks naturally also defines their properties. However, besides the linkage type, the orientation, i.e., the constitutional isomerism of these linkages, has rarely been considered so far as an essential aspect. In this work, three pairs of constitutionally isomeric imine-linked donor-acceptor (D-A) COFs are synthesized, which are different in the orientation of the imine bonds (D-C=N-A (DCNA) and D-N=C-A (DNCA)). The constitutional isomers show substantial differences in their photophysical properties and consequently in their photocatalytic performance. Indeed, all DCNA COFs show enhanced photocatalytic H2 evolution performance than the corresponding DNCA COFs. Besides the imine COFs shown here, it can be concluded that the proposed concept of constitutional isomerism of linkages in COFs is quite universal and should be considered when designing and tuning the properties of COFs.
Plants use photoperiodism to activate flowering in response to a particular daylength. In rice, flowering is accelerated in short-day conditions, and even a brief exposure to light during the dark period (night-break) is sufficient to delay flowering. Although many of the genes involved in controlling flowering in rice have been uncovered, how the long- and short-day flowering pathways are integrated, and the mechanism of photoperiod perception is not understood. While many of the signaling components controlling photoperiod-activated flowering are conserved between Arabidopsis and rice, flowering in these two systems is activated by opposite photoperiods. Here we establish that photoperiodism in rice is controlled by the evening complex (EC). We show that mutants in the EC genes LUX ARRYTHMO (LUX) and EARLY FLOWERING3 (ELF3) paralogs abolish rice flowering. We also show that the EC directly binds and suppresses the expression of flowering repressors, including PRR37 and Ghd7. We further demonstrate that light acts via phyB to cause a rapid and sustained posttranslational modification of ELF3-1. Our results suggest a mechanism by which the EC is able to control both long- and short-day flowering pathways.
The European river lamprey Lampetra fluviatilis and the European brook lamprey Lampetra planeri (Block 1784) are classified as a paired species, characterized by notably different life histories but morphological similarities. Previous work has further shown limited genetic differentiation between these two species at the mitochondrial DNA level. Here, we expand on this previous work, which focused on lamprey species from the Iberian Peninsula in the south and mainland Europe in the north, by sequencing three mitochondrial marker regions of Lampetra individuals from five river systems in Ireland and five in southern Italy. Our results corroborate the previously identified pattern of genetic diversity for the species pair. We also show significant genetic differentiation between Irish and mainland European lamprey populations, suggesting another ichthyogeographic district distinct from those previously defined. Finally, our results stress the importance of southern Italian L. planeri populations, which maintain several private alleles and notable genetic diversity.
Due to climate change the frequency and character of precipitation are changing as the hydrological cycle intensifies. With regards to snowfall, global warming has two opposing influences; increasing humidity enables intense snowfall, whereas higher temperatures decrease the likelihood of snowfall. Here we show an intensification of extreme snowfall across large areas of the Northern Hemisphere under future warming. This is robust across an ensemble of global climate models when they are bias-corrected with observational data. While mean daily snowfall decreases, both the 99th and the 99.9th percentiles of daily snowfall increase in many regions in the next decades, especially for Northern America and Asia. Additionally, the average intensity of snowfall events exceeding these percentiles as experienced historically increases in many regions. This is likely to pose a challenge to municipalities in mid to high latitudes. Overall, extreme snowfall events are likely to become an increasingly important impact of climate change in the next decades, even if they will become rarer, but not necessarily less intense, in the second half of the century.
Purpose
The objective of the investigation was to determine the concomitant effects of upper arm blood flow restriction (BFR) and inversion on elbow flexors neuromuscular responses.
Methods
Randomly allocated, 13 volunteers performed four conditions in a within-subject design: rest (control, 1-min upright position without BFR), control (1-min upright with BFR), 1-min inverted (without BFR), and 1-min inverted with BFR. Evoked and voluntary contractile properties, before, during and after a 30-s maximum voluntary contraction (MVC) exercise intervention were examined as well as pain scale.
Results
Inversion induced significant pre-exercise intervention decreases in elbow flexors MVC (21.1%, Z2p = 0.48, p = 0.02) and resting evoked twitch forces (29.4%, Z2p = 0.34, p = 0.03). The 30-s MVC induced significantly greater pre- to post-test decreases in potentiated twitch force (Z2p = 0.61, p = 0.0009) during inversion (75%) than upright (65.3%) conditions. Overall, BFR decreased MVC force 4.8% (Z2p = 0.37, p = 0.05). For upright position, BFR induced 21.0% reductions in M-wave amplitude (Z2p = 0.44, p = 0.04). There were no significant differences for electromyographic activity or voluntary activation as measured with the interpolated twitch technique. For all conditions, there was a significant increase in pain scale between the 40-60 s intervals and post-30-s MVC (upright< inversion, and without BFR< BFR).
Conclusion
The concomitant application of inversion with elbow flexors BFR only amplified neuromuscular performance impairments to a small degree. Individuals who execute forceful contractions when inverted or with BFR should be cognizant that force output may be impaired.
Objective
For an effective control of the SARS-CoV-2 pandemic with vaccines, most people in a population need to be vaccinated. It is thus important to know how to inform the public with reference to individual preferences–while also acknowledging the societal preference to encourage vaccinations. According to the health care standard of informed decision-making, a comparison of the benefits and harms of (not) having the vaccination would be required to inform undecided and skeptical people. To test evidence-based fact boxes, an established risk communication format, and to inform their development, we investigated their contribution to knowledge and evaluations of COVID-19 vaccines.
Methods
We conducted four studies (1, 2, and 4 were population-wide surveys with N = 1,942 to N = 6,056): Study 1 assessed the relationship between vaccination knowledge and intentions in Germany over three months. Study 2 assessed respective information gaps and needs of the population in Germany. In parallel, an experiment (Study 3) with a mixed design (presentation formats; pre-post-comparison) assessed the effect of fact boxes on risk perceptions and fear, using a convenience sample (N = 719). Study 4 examined how effective two fact box formats are for informing vaccination intentions, with a mixed experimental design: between-subjects (presentation formats) and within-subjects (pre-post-comparison).
Results
Study 1 showed that vaccination knowledge and vaccination intentions increased between November 2020 and February 2021. Study 2 revealed objective information requirements and subjective information needs. Study 3 showed that the fact box format is effective in adjusting risk perceptions concerning COVID-19. Based on those results, fact boxes were revised and implemented with the help of a national health authority in Germany. Study 4 showed that simple fact boxes increase vaccination knowledge and positive evaluations in skeptics and undecideds.
Conclusion
Fact boxes can inform COVID-19 vaccination intentions of undecided and skeptical people without threatening societal vaccination goals of the population
Given the increasing interest in keeping global warming below 1.5°C, a key question is what this would mean for China’s emission pathway, energy restructuring, and decarbonization. By conducting a multimodel study, we find that the 1.5°C-consistent goal would require China to reduce its carbon emissions and energy consumption by more than 90 and 39%, respectively, compared with the “no policy” case. Negative emission technologies play an important role in achieving near-zero emissions, with captured carbon accounting on average for 20% of the total reductions in 2050. Our multimodel comparisons reveal large differences in necessary emission reductions across sectors, whereas what is consistent is that the power sector is required to achieve full decarbonization by 2050. The cross-model averages indicate that China’s accumulated policy costs may amount to 2.8 to 5.7% of its gross domestic product by 2050, given the 1.5°C warming limit.
The large majority of climate change mitigation scenarios that hold warming below 2 °C show high deployment of carbon dioxide removal (CDR), resulting in a peak-and-decline behavior in global temperature. This is driven by the assumption of an exponentially increasing carbon price trajectory which is perceived to be economically optimal for meeting a carbon budget. However, this optimality relies on the assumption that a finite carbon budget associated with a temperature target is filled up steadily over time. The availability of net carbon removals invalidates this assumption and therefore a different carbon price trajectory should be chosen. We show how the optimal carbon price path for remaining well below 2 °C limits CDR demand and analyze requirements for constructing alternatives, which may be easier to implement in reality. We show that warming can be held at well below 2 °C at much lower long-term economic effort and lower CDR deployment and therefore lower risks if carbon prices are high enough in the beginning to ensure target compliance, but increase at a lower rate after carbon neutrality has been reached.
Agriculture in India accounts for 18% of greenhouse gas (GHG) emissions and uses significant land and water. Various socioeconomic factors and food subsidies influence diets in India. Indian food systems face the challenge of sustainably nourishing the 1.3 billion population. However, existing studies focus on a few food system components, and holistic analysis is still missing. We identify Indian food systems covering six food system components: food consumption, production, processing, policy, environmental footprints, and socioeconomic factors from the latest Indian household consumer expenditure survey. We identify 10 Indian food systems using k-means cluster analysis on 15 food system indicators belonging to the six components. Based on the major source of calorie intake, we classify the ten food systems into production-based (3), subsidy-based (3), and market-based (4) food systems. Home-produced and subsidized food contribute up to 2000 kcal/consumer unit (CU)/day and 1651 kcal/CU/day, respectively, in these food systems. The calorie intake of 2158 to 3530 kcal/CU/day in the food systems reveals issues of malnutrition in India. Environmental footprints are commensurate with calorie intake in the food systems. Embodied GHG, land footprint, and water footprint estimates range from 1.30 to 2.19 kg CO(2)eq/CU/day, 3.89 to 6.04 m(2)/CU/day, and 2.02 to 3.16 m(3)/CU/day, respectively. Our study provides a holistic understanding of Indian food systems for targeted nutritional interventions on household malnutrition in India while also protecting planetary health.
From an active labor market policy perspective, start-up subsidies for unemployed individuals are very effective in improving long-term labor market outcomes for participants. From a business perspective, however, the assessment of these public programs is less clear since they might attract individuals with low entrepreneurial abilities and produce businesses with low survival rates and little contribution to job creation, economic growth, and innovation. In this paper, we use a rich data set to compare participants of a German start-up subsidy program for unemployed individuals to a group of regular founders who started from non-unemployment and did not receive the subsidy. The data allows us to analyze their business performance up until 40 months after business formation. We find that formerly subsidized founders lag behind not only in survival and job creation, but especially also in innovation activities. The gaps in these business outcomes are relatively constant or even widening over time. Hence, we do not see any indication of catching up in the longer run. While the gap in survival can be entirely explained by initial differences in observable start-up characteristics, the gap in business development remains and seems to be the result of restricted access to capital as well as differential business strategies and dynamics. Considering these conflicting results for the assessment of the subsidy program from an ALMP and business perspective, policy makers need to carefully weigh the costs and benefits of such a strategy to find the right policy mix.
Genome-scale metabolic networks for model plants and crops in combination with approaches from the constraint-based modelling framework have been used to predict metabolic traits and design metabolic engineering strategies for their manipulation. With the advances in technologies to generate large-scale genotyping data from natural diversity panels and other populations, genome-wide association and genomic selection have emerged as statistical approaches to determine genetic variants associated with and predictive of traits. Here, we review recent advances in constraint-based approaches that integrate genetic variants in genome-scale metabolic models to characterize their effects on reaction fluxes. Since some of these approaches have been applied in organisms other than plants, we provide a critical assessment of their applicability particularly in crops. In addition, we further dissect the inferred effects of genetic variants with respect to reaction rate constants, abundances of enzymes, and concentrations of metabolites, as main determinants of reaction fluxes and relate them with their combined effects on complex traits, like growth. Through this systematic review, we also provide a roadmap for future research to increase the predictive power of statistical approaches by coupling them with mechanistic models of metabolism.
In this paper we examine the effect of uncertainty on readers' predictions about meaning. In particular, we were interested in how uncertainty might influence the likelihood of committing to a specific sentence meaning. We conducted two event-related potential (ERP) experiments using particle verbs such as turn down and manipulated uncertainty by constraining the context such that readers could be either highly certain about the identity of a distant verb particle, such as turn the bed [...] down, or less certain due to competing particles, such as turn the music [...] up/down. The study was conducted in German, where verb particles appear clause-finally and may be separated from the verb by a large amount of material. We hypothesised that this separation would encourage readers to predict the particle, and that high certainty would make prediction of a specific particle more likely than lower certainty. If a specific particle was predicted, this would reflect a strong commitment to sentence meaning that should incur a higher processing cost if the prediction is wrong. If a specific particle was less likely to be predicted, commitment should be weaker and the processing cost of a wrong prediction lower. If true, this could suggest that uncertainty discourages predictions via an unacceptable cost-benefit ratio. However, given the clear predictions made by the literature, it was surprisingly unclear whether the uncertainty manipulation affected the two ERP components studied, the N400 and the PNP. Bayes factor analyses showed that evidence for our a priori hypothesised effect sizes was inconclusive, although there was decisive evidence against a priori hypothesised effect sizes larger than 1 mu Vfor the N400 and larger than 3 mu V for the PNP. We attribute the inconclusive finding to the properties of verb-particle dependencies that differ from the verb-noun dependencies in which the N400 and PNP are often studied.
Monitoring the response of volcanic CO2 emissions to changes in the Los Humeros hydrothermal system
(2021)
Carbon dioxide is the most abundant, non-condensable gas in volcanic systems, released into the atmosphere through either diffuse or advective fluid flow. The emission of substantial amounts of CO2 at Earth's surface is not only controlled by volcanic plumes during periods of eruptive activity or fumaroles, but also by soil degassing along permeable structures in the subsurface. Monitoring of these processes is of utmost importance for volcanic hazard analyses, and is also relevant for managing geothermal resources. Fluid-bearing faults are key elements of economic value for geothermal power generation. Here, we describe for the first time how sensitively and quickly natural gas emissions react to changes within a deep hydrothermal system due to geothermal fluid reinjection. For this purpose, we deployed an automated, multi-chamber CO2 flux monitoring system within the damage zone of a deep-rooted major normal fault in the Los Humeros Volcanic Complex (LHVC) in Mexico and recorded data over a period of five months. After removing the atmospheric effects on variations in CO2 flux, we calculated correlation coefficients between residual CO2 emissions and reinjection rates, identifying an inverse correlation of rho = - 0.51 to - 0.66. Our results indicate that gas emissions respond to changes in reinjection rates within 24 h, proving an active hydraulic communication between the hydrothermal system and Earth's surface. This finding is a promising indication not only for geothermal reservoir monitoring but also for advanced long-term volcanic risk analysis. Response times allow for estimation of fluid migration velocities, which is a key constraint for conceptual and numerical modelling of fluid flow in fracture-dominated systems.
Movement behavior is an essential element of fundamental ecological processes such as competition and predation. Although intraspecific trait variation (ITV) in movement behaviors is pervasive, its consequences for ecological community dynamics are still not fully understood. Using a newly developed individual-based model, we analyzed how given and constant ITVs in foraging movement affect differences in foraging efficiencies between species competing for common resources under various resource distributions. Further, we analyzed how the effect of ITV on emerging differences in competitive abilities ultimately affects species coexistence. The model is generic but mimics observed patterns of among-individual covariation between personality, movement and space use in ground-dwelling rodents. Interacting species differed in their mean behavioral types along a slow-fast continuum, integrating consistent individual variation in average behavioral expression and responsiveness (i.e. behavioral reaction norms). We found that ITV reduced interspecific differences in competitive abilities by 5-35% and thereby promoted coexistence via an equalizing mechanism. The emergent relationships between behavioral types and foraging efficiency are characteristic for specific environmental contexts of resource distribution and population density. As these relationships are asymmetric, species that were either 'too fast' or 'too slow' benefited differently from ITV. Thus, ITV in movement behavior has consequences for species coexistence but to predict its effect in a given system requires intimate knowledge on how variation in movement traits relates to fitness components along an environmental gradient.
The near-Earth space environment is a highly complex system comprised of several regions and particle populations hazardous to satellite operations. The trapped particles in the radiation belts and ring current can cause significant damage to satellites during space weather events, due to deep dielectric and surface charging. Closer to Earth is another important region, the ionosphere, which delays the propagation of radio signals and can adversely affect navigation and positioning. In response to fluctuations in solar and geomagnetic activity, both the inner-magnetospheric and ionospheric populations can undergo drastic and sudden changes within minutes to hours, which creates a challenge for predicting their behavior. Given the increasing reliance of our society on satellite technology, improving our understanding and modeling of these populations is a matter of paramount importance.
In recent years, numerous spacecraft have been launched to study the dynamics of particle populations in the near-Earth space, transforming it into a data-rich environment. To extract valuable insights from the abundance of available observations, it is crucial to employ advanced modeling techniques, and machine learning methods are among the most powerful approaches available. This dissertation employs long-term satellite observations to analyze the processes that drive particle dynamics, and builds interdisciplinary links between space physics and machine learning by developing new state-of-the-art models of the inner-magnetospheric and ionospheric particle dynamics.
The first aim of this thesis is to investigate the behavior of electrons in Earth's radiation belts and ring current. Using ~18 years of electron flux observations from the Global Positioning System (GPS), we developed the first machine learning model of hundreds-of-keV electron flux at Medium Earth Orbit (MEO) that is driven solely by solar wind and geomagnetic indices and does not require auxiliary flux measurements as inputs. We then proceeded to analyze the directional distributions of electrons, and for the first time, used Fourier sine series to fit electron pitch angle distributions (PADs) in Earth's inner magnetosphere. We performed a superposed epoch analysis of 129 geomagnetic storms during the Van Allen Probes era and demonstrated that electron PADs have a strong energy-dependent response to geomagnetic activity. Additionally, we showed that the solar wind dynamic pressure could be used as a good predictor of the PAD dynamics. Using the observed dependencies, we created the first PAD model with a continuous dependence on L, magnetic local time (MLT) and activity, and developed two techniques to reconstruct near-equatorial electron flux observations from low-PA data using this model.
The second objective of this thesis is to develop a novel model of the topside ionosphere. To achieve this goal, we collected observations from five of the most widely used ionospheric missions and intercalibrated these data sets. This allowed us to use these data jointly for model development, validation, and comparison with other existing empirical models. We demonstrated, for the first time, that ion density observations by Swarm Langmuir Probes exhibit overestimation (up to ~40-50%) at low and mid-latitudes on the night side, and suggested that the influence of light ions could be a potential cause of this overestimation. To develop the topside model, we used 19 years of radio occultation (RO) electron density profiles, which were fitted with a Chapman function with a linear dependence of scale height on altitude. This approximation yields 4 parameters, namely the peak density and height of the F2-layer and the slope and intercept of the linear scale height trend, which were modeled using feedforward neural networks (NNs). The model was extensively validated against both RO and in-situ observations and was found to outperform the International Reference Ionosphere (IRI) model by up to an order of magnitude. Our analysis showed that the most substantial deviations of the IRI model from the data occur at altitudes of 100-200 km above the F2-layer peak. The developed NN-based ionospheric model reproduces the effects of various physical mechanisms observed in the topside ionosphere and provides highly accurate electron density predictions.
This dissertation provides an extensive study of geospace dynamics, and the main results of this work contribute to the improvement of models of plasma populations in the near-Earth space environment.
Seed traits matter
(2021)
Although many plants are dispersed by wind and seeds can travel long distances across unsuitable matrix areas, a large proportion relies on co-evolved zoochorous seed dispersal to connect populations in isolated habitat islands. Particularly in agricultural landscapes, where remaining habitat patches are often very small and highly isolated, mobile linkers as zoochorous seed dispersers are critical for the population dynamics of numerous plant species. However, knowledge about the quali- or quantification of such mobile link processes, especially in agricultural landscapes, is still limited. In a controlled feeding experiment, we recorded the seed intake and germination success after complete digestion by the European brown hare (Lepus europaeus) and explored its mobile link potential as an endozoochoric seed disperser. Utilizing a suite of common, rare, and potentially invasive plant species, we disentangled the effects of seed morphological traits on germination success while controlling for phylogenetic relatedness. Further, we measured the landscape connectivity via hares in two contrasting agricultural landscapes (simple: few natural and semi-natural structures, large fields; complex: high amount of natural and semi-natural structures, small fields) using GPS-based movement data. With 34,710 seeds of 44 plant species fed, one of 200 seeds (0.51%) with seedlings of 33 species germinated from feces. Germination after complete digestion was positively related to denser seeds with comparatively small surface area and a relatively slender and elongated shape, suggesting that, for hares, the most critical seed characteristics for successful endozoochorous seed dispersal minimize exposure of the seed to the stomach and the associated digestive system. Furthermore, we could show that a hare's retention time is long enough to interconnect different habitats, especially grasslands and fields. Thus, besides other seed dispersal mechanisms, this most likely allows hares to act as effective mobile linkers contributing to ecosystem stability in times of agricultural intensification, not only in complex but also in simple landscapes.
During reading or listening, people can generate predictions about the lexical and morphosyntactic properties of upcoming input based on available context. Psycholinguistic experiments that study predictability or control for it conventionally rely on a human-based approach and estimate predictability via the cloze task. Our study investigated an alternative corpus-based approach for estimating predictability via language predictability models. We obtained cloze and corpus-based probabilities for all words in 144 Russian sentences, correlated the two measures, and found a strong correlation between them. Importantly, we estimated how much variance in eye movements registered while reading the same sentences was explained by each of the two probabilities and whether the two probabilities explain the same variance. Along with lexical predictability (the activation of a particular word form), we analyzed morphosyntactic predictability (the activation of morphological features of words) and its effect on reading times over and above lexical predictability. We found that for predicting reading times, cloze and corpus-based measures of both lexical and morphosyntactic predictability explained the same amount of variance. However, cloze and corpus-based lexical probabilities both independently contributed to a better model fit, whereas for morphosyntactic probabilities, the contributions of cloze and corpus-based measures were interchangeable. Therefore, morphosyntactic but not lexical corpus-based probabilities can substitute for cloze probabilities in reading experiments. Our results also indicate that in languages with rich inflectional morphology, such as Russian, when people engage in prediction, they are much more successful in predicting isolated morphosyntactic features than predicting the particular lexeme and its full morphosyntactic markup.
Soil structure, the complex arrangement of soil into aggregates and pore spaces, is a key feature of soils and soil biota. Among them, filamentous saprobic fungi have well-documented effects on soil aggregation. However, it is unclear what properties, or traits, determine the overall positive effect of fungi on soil aggregation. To achieve progress, it would be helpful to systematically investigate a broad suite of fungal species for their trait expression and the relation of these traits to soil aggregation. Here, we apply a trait-based approach to a set of 15 traits measured under standardized conditions on 31 fungal strains including Ascomycota, Basidiomycota, and Mucoromycota, all isolated from the same soil. We find large differences among these fungi in their ability to aggregate soil, including neutral to positive effects, and we document large differences in trait expression among strains. We identify biomass density, i.e., the density with which a mycelium grows (positive effects), leucine aminopeptidase activity (negative effects) and phylogeny as important factors explaining differences in soil aggregate formation (SAF) among fungal strains; importantly, growth rate was not among the important traits. Our results point to a typical suite of traits characterizing fungi that are good soil aggregators, and our findings illustrate the power of employing a trait-based approach to unravel biological mechanisms underpinning soil aggregation. Such an approach could now be extended also to other soil biota groups. In an applied context of restoration and agriculture, such trait information can inform management, for example to prioritize practices that favor the expression of more desirable fungal traits.
Globally, cardiovascular diseases are the leading cause of death in the aging population. While the clinical pathology of the aging heart is thoroughly characterized, underlying molecular mechanisms are still insufficiently clarified. The aim of the present study was to establish an in vitro model system of cardiomyocyte premature senescence, culturing heart muscle cells derived from neonatal C57Bl/6J mice for 21 days. Premature senescence of neonatal cardiac myocytes was induced by prolonged culture time in an oxygen-rich postnatal environment. Age-related changes in cellular function were determined by senescence-associated beta-galactosidase activity, increasing presence of cell cycle regulators, such as p16, p53, and p21, accumulation of protein aggregates, and restricted proteolysis in terms of decreasing (macro-)autophagy. Furthermore, the culture system was functionally characterized for alterations in cell morphology and contractility. An increase in cellular size associated with induced expression of atrial natriuretic peptides demonstrated a stress-induced hypertrophic phenotype in neonatal cardiomyocytes. Using the recently developed analytical software tool Myocyter, we were able to show a spatiotemporal constraint in spontaneous contraction behavior during cultivation. Within the present study, the 21-day culture of neonatal cardiomyocytes was defined as a functional model system of premature cardiac senescence to study age-related changes in cardiomyocyte contractility and autophagy.
In this report we describe Cy5-dUTP labelling of recombinase-polymerase-amplification (RPA) products directly during the amplification process for the first time. Nucleic acid amplification techniques, especially polymerase-chain-reaction as well as various isothermal amplification methods such as RPA, becomes a promising tool in the detection of pathogens and target specific genes. Actually, RPA even provides more advantages. This isothermal method got popular in point of care diagnostics because of its speed and sensitivity but requires pre-labelled primer or probes for a following detection of the amplicons. To overcome this disadvantages, we performed an labelling of RPA-amplicons with Cy5-dUTP without the need of pre-labelled primers. The amplification results of various multiple antibiotic resistance genes indicating great potential as a flexible and promising tool with high specific and sensitive detection capabilities of the target genes. After the determination of an appropriate rate of 1% Cy5-dUTP and 99% unlabelled dTTP we were able to detect the bla(CTX-M15) gene in less than 1.6E-03 ng genomic DNA corresponding to approximately 200 cfu of Escherichia coli cells in only 40 min amplification time.