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Cool farm tool water
(2018)
The agricultural sector accounts for 70% of all water consumption and poses great pressure on ground water resources. Therefore, evaluating agricultural water consumption is highly important as it allows supply chain actors to identify practices which are associated with unsustainable water use, which risk depleting current water resources and impacting future production. However, these assessments are often not feasible for crop producers as data, models and experiments are required in order to conduct them. This work introduces a new on-line agricultural water use assessment tool that provides the water footprint and irrigation requirements at field scale based on an enhanced FAO56 approach combined with a global climate, crop and soil databases. This has been included in the Cool Farm Tool - an online tool which already provides metrics for greenhouse gas emissions and biodiversity impacts and therefore allows for a more holistic assessment of environmental sustainability in farming and agricultural supply chains. The model is tested against field scale and state level water footprint data providing good results. The tool provides a practical, reliable way to assess agricultural water use, and offers a means to engage growers and stakeholders in identifying efficient water management practices. (C) 2018 The Authors. Published by Elsevier Ltd.
A catalog of genetic loci associated with kidney function from analyses of a million individuals
(2019)
Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through transancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n = 1,046,070), we identified 264 associated loci (166 new). Of these,147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research.
We utilise multi-epoch MUSE spectroscopy to study binary stars in the core of the Galactic globular cluster NGC 3201. Our sample consists of 3553 stars with 54 883 spectra in total comprising 3200 main-sequence stars up to 4 magnitudes below the turn-off. Each star in our sample has between 3 and 63 (with a median of 14) reliable radial velocity measurements within five years of observations. We introduce a statistical method to determine the probability of a star showing radial velocity variations based on the whole inhomogeneous radial velocity sample. Using HST photometry and an advanced dynamical MOCCA simulation of this specific cluster we overcome observational biases that previous spectroscopic studies had to deal with. This allows us to infer a binary frequency in the MUSE field of view and enables us to deduce the underlying true binary frequency of (6.75 +/- 0.72)% in NGC 3201. The comparison of the MUSE observations with the MOCCA simulation suggests a large portion of primordial binaries. We can also confirm a radial increase in the binary fraction towards the cluster centre due to mass segregation. We discovered that in the core of NGC 3201 at least (57.5 +/- 7.9)% of blue straggler stars are in a binary system. For the first time in a study of globular clusters, we were able to fit Keplerian orbits to a significant sample of 95 binaries. We present the binary system properties of eleven blue straggler stars and the connection to SX Phoenicis-type stars. We show evidence that two blue straggler formation scenarios, the mass transfer in binary (or triple) star systems and the coalescence due to binary-binary interactions, are present in our data. We also describe the binary and spectroscopic properties of four sub-subgiant (or red straggler) stars. Furthermore, we discovered two new black hole candidates with minimum masses (M sin i) of (7.68 +/- 0.50)M-circle dot, (4.4 +/- 2.8)M-circle dot, and refine the minimum mass estimate on the already published black hole to (4.53 +/- 0.21)M-circle dot, These black holes are consistent with an extensive black hole subsystem hosted by NGC 3201.
A nova is a cataclysmic event on the surface of a white dwarf in a binary system that increases the overall brightness by several orders of magnitude. Although binary systems with a white dwarf are expected to be overabundant in globular clusters compared with in the Galaxy, only two novae from Galactic globular clusters have been observed. We present the discovery of an emission nebula in the Galactic globular cluster M 22 (NGC 6656) in observations made with the integral-field spectrograph MUSE. We extracted the spectrum of the nebula and used the radial velocity determined from the emission lines to confirm that the nebula is part of NGC 6656. Emission-line ratios were used to determine the electron temperature and density. It is estimated to have a mass of 1-17 x 10(-5) M-circle dot. This mass and the emission-line ratios indicate that the nebula is a nova remnant. Its position coincides with the reported location of a "guest star", an ancient Chinese term for transients, observed in May 48 BCE. With this discovery, this nova may be one of the oldest confirmed extra-solar events recorded in human history.
A stellar census in globular clusters with MUSE: A spectral catalogue of emission-line sources
(2019)
Aims. Globular clusters produce many exotic stars due to a much higher frequency of dynamical interactions in their dense stellar environments. Some of these objects were observed together with several hundred thousand other stars in our MUSE survey of 26 Galactic globular clusters. Assuming that at least a few exotic stars have exotic spectra (i.e. spectra that contain emission lines), we can use this large spectroscopic data set of over a million stellar spectra as a blind survey to detect stellar exotica in globular clusters. Methods. To detect emission lines in each spectrum, we modelled the expected shape of an emission line as a Gaussian curve. This template was used for matched filtering on the di fferences between each observed 1D spectrum and its fitted spectral model. The spectra with the most significant detections of H alpha emission are checked visually and cross-matched with published catalogues. Results. We find 156 stars with H alpha emission, including several known cataclysmic variables (CV) and two new CVs, pulsating variable stars, eclipsing binary stars, the optical counterpart of a known black hole, several probable sub-subgiants and red stragglers, and 21 background emission-line galaxies. We find possible optical counterparts to 39 X-ray sources, as we detected H alpha emission in several spectra of stars that are close to known positions of Chandra X-ray sources. This spectral catalogue can be used to supplement existing or future X-ray or radio observations with spectra of potential optical counterparts to classify the sources.
Proceedings of KogWis 2010 : 10th Biannual Meeting of the German Society for Cognitive Science
(2010)
As the latest biannual meeting of the German Society for Cognitive Science (Gesellschaft für Kognitionswissenschaft, GK), KogWis 2010 at Potsdam University reflects the current trends in a fascinating domain of research concerned with human and artificial cognition and the interaction of mind and brain. The Plenary talks provide a venue for questions of the numerical capacities and human arithmetic (Brian Butterworth), of the theoretical development of cognitive architectures and intelligent virtual agents (Pat Langley), of categorizations induced by linguistic constructions (Claudia Maienborn), and of a cross-level account of the “Self as a complex system“ (Paul Thagard). KogWis 2010 integrates a wealth of experimental research, cognitive modelling, and conceptual analysis in 5 invited symposia, over 150 individual talks, 6 symposia, and more than 40 poster contributions. Some of the invited symposia reflect local and regional strenghts of research in the Berlin-Brandenburg area: the two largests research fields of the university Cognitive Sciences Area of Excellence in Potsdam are represented by an invited symposium on “Information Structure” by the Special Research Area 632 (“Sonderforschungsbereich”, SFB) of the same name, of Potsdam University and Humboldt-University Berlin, and by a satellite conference of the research group “Mind and Brain Dynamics”. The Berlin School of Mind and Brain at Humboldt-University Berlin takes part with an invited symposium on “Decision Making” from a perspective of cognitive neuroscience and philosophy and the DFG Cluster of Excellence “Languages of Emotion” of Free University presents interdisciplinary research results in an invited symposium on “Symbolising Emotions”.
Reproducibility is a defining feature of science, but the extent to which it characterizes current research is unknown. We conducted replications of 100 experimental and correlational studies published in three psychology journals using high-powered designs and original materials when available. Replication effects were half the magnitude of original effects, representing a substantial decline. Ninety-seven percent of original studies had statistically significant results. Thirty-six percent of replications had statistically significant results; 47% of original effect sizes were in the 95% confidence interval of the replication effect size; 39% of effects were subjectively rated to have replicated the original result; and if no bias in original results is assumed, combining original and replication results left 68% with statistically significant effects. Correlational tests suggest that replication success was better predicted by the strength of original evidence than by characteristics of the original and replication teams.
Context. Galactic globular clusters (GCs) are now known to host multiple populations displaying particular abundance variations. The different populations within a GC can be well distinguished following their position in the pseudo two-colors diagrams, also referred to as "chromosome maps". These maps are constructed using optical and near-UV photometry available from the Hubble Space Telescope (HST) UV survey of GCs. However, the chemical tagging of the various populations in the chromosome maps is hampered by the fact that HST photometry and elemental abundances are both only available for a limited number of stars. Aims. The spectra collected as part of the MUSE survey of globular clusters provide a spectroscopic counterpart to the HST photometric catalogs covering the central regions of GCs. In this paper, we use the MUSE spectra of 1115 red giant branch (RGB) stars in NGC 2808 to characterize the abundance variations seen in the multiple populations of this cluster. Methods. We used the chromosome map of NGC 2808 to divide the RGB stars into their respective populations. We then combined the spectra of all stars belonging to a given population, resulting in one high signal-to-noise ratio spectrum representative of each population. Results. Variations in the spectral lines of O, Na, Mg, and Al are clearly detected among four of the populations. In order to quantify these variations, we measured equivalent width differences and created synthetic populations spectra that were used to determine abundance variations with respect to the primordial population of the cluster. Our results are in good agreement with the values expected from previous studies based on high-resolution spectroscopy. We do not see any significant variations in the spectral lines of Ca, K, and Ba. We also do not detect abundance variations among the stars belonging to the primordial population of NGC 2808. Conclusions. We demonstrate that in spite of their low resolution, the MUSE spectra can be used to investigate abundance variations in the context of multiple populations.
Background
In many species males face a higher predation risk than females because males display elaborate traits that evolved under sexual selection, which may attract not only females but also predators. Females are, therefore, predicted to avoid such conspicuous males under predation risk. The present study was designed to investigate predator-induced changes of female mating preferences in Atlantic mollies (Poecilia mexicana). Males of this species show a pronounced polymorphism in body size and coloration, and females prefer large, colorful males in the absence of predators.
Results
In dichotomous choice tests predator-naïve (lab-reared) females altered their initial preference for larger males in the presence of the cichlid Cichlasoma salvini, a natural predator of P. mexicana, and preferred small males instead. This effect was considerably weaker when females were confronted visually with the non-piscivorous cichlid Vieja bifasciata or the introduced non-piscivorous Nile tilapia (Oreochromis niloticus). In contrast, predator experienced (wild-caught) females did not respond to the same extent to the presence of a predator, most likely due to a learned ability to evaluate their predators' motivation to prey.
Conclusions
Our study highlights that (a) predatory fish can have a profound influence on the expression of mating preferences of their prey (thus potentially affecting the strength of sexual selection), and females may alter their mate choice behavior strategically to reduce their own exposure to predators. (b) Prey species can evolve visual predator recognition mechanisms and alter their mate choice only when a natural predator is present. (c) Finally, experiential effects can play an important role, and prey species may learn to evaluate the motivational state of their predators.
Aus dem Inhalt dieser Ausgabe: BEITRAG: Ralf Pröve: Vom Schmuddelkind zur anerkannten Subdisziplin?1Die „neue Militärgeschichte“ der Frühen Neuzeitund der AMG PROJEKTE: Stefan Kroll: Kursächsische Soldaten im 18. Jahrhundert (1728-1789) Matthias Asche: Neusiedler im verheerten Land –Kriegsfolgenbewältigung, Landeswiederaufbau undMigration in der Mark Brandenburg und in Badennach den Kriegen des 17. Jahrhunderts Anne Heinecke: Wahrnehmung und Darstellungvon Plünderung im 17. Jahrhundertim Spiegel von Selbstzeugnissen Militärangehöriger Mikko Huhtamies: Ersatzsoldaten in Europa in der Frühen Neuzeit Benjamin MarschkeThe Development of the Army Chaplaincy inEarly Eighteenth-Century Prussia Holger Th. Gräf: Valentin Wagner – Zeichnungen aus der Zeit desDreißigjährigen Krieges Torsten F. Reimer: magi-e – integriertes Publizierenin der Geschichtswissenschaft Bernhard Schmitt: Militär und Integration im 19. Jahrhundert –Zur Bedeutung und Funktion der Armeebei der Eingliederung neuer Bevölkerungsgruppenin Preußen und der Habsburgermonarchie 1815-1867 Jörg Muth: Flucht aus dem militärischen AlltagUrsachen und individuelle Ausprägung der Desertionin der Armee Friedrichs des Großen Michael Reiff: Strandgut des Krieges: Die soziale Lage Kriegsversehrterin den deutschen Armeen des Absolutismusund der napoleonischen Zeit ( 1648 – 1815 ) Ralf Gebuhr: Nickel von Minckwitzund der frühneuzeitliche Schlossbauin der Niederlausitz Alexander M. Martin: Die Napoleonische Okkupation Moskaus 1812 Daniel Krebs: Deutsche Kriegsgefangeneim Amerikanischen Unabhängigkeitskrieg BERICHTE: REZENSIONEN:
Agent-based models (ABMs) are widely used to predict how populations respond to changing environments. As the availability of food varies in space and time, individuals should have their own energy budgets, but there is no consensus as to how these should be modelled. Here, we use knowledge of physiological ecology to identify major issues confronting the modeller and to make recommendations about how energy budgets for use in ABMs should be constructed. Our proposal is that modelled animals forage as necessary to supply their energy needs for maintenance, growth and reproduction. If there is sufficient energy intake, an animal allocates the energy obtained in the order: maintenance, growth, reproduction, energy storage, until its energy stores reach an optimal level. If there is a shortfall, the priorities for maintenance and growth/reproduction remain the same until reserves fall to a critical threshold below which all are allocated to maintenance. Rates of ingestion and allocation depend on body mass and temperature. We make suggestions for how each of these processes should be modelled mathematically. Mortality rates vary with body mass and temperature according to known relationships, and these can be used to obtain estimates of background mortality rate. If parameter values cannot be obtained directly, then values may provisionally be obtained by parameter borrowing, pattern-oriented modelling, artificial evolution or from allometric equations. The development of ABMs incorporating individual energy budgets is essential for realistic modelling of populations affected by food availability. Such ABMs are already being used to guide conservation planning of nature reserves and shell fisheries, to assess environmental impacts of building proposals including wind farms and highways and to assess the effects on nontarget organisms of chemicals for the control of agricultural pests.
Serial and parallel processes in eye movement control - current controversies and future directions
(2013)
In this editorial for the Special Issue on Serial and Parallel Processing in Reading we explore the background to the current debate concerning whether the word recognition processes in reading are strictly serialsequential or take place in an overlapping parallel fashion. We consider the history of the controversy and some of the underlying assumptions, together with an analysis of the types of evidence and arguments that have been adduced to both sides of the debate, concluding that both accounts necessarily presuppose some weakening of, or elasticity in, the eyemind assumption. We then consider future directions, both for reading research and for scene viewing, and wrap up the editorial with a brief overview of the following articles and their conclusions.
Background: In many species males face a higher predation risk than females because males display elaborate traits that evolved under sexual selection, which may attract not only females but also predators. Females are, therefore, predicted to avoid such conspicuous males under predation risk. The present study was designed to investigate predator-induced changes of female mating preferences in Atlantic mollies (Poecilia mexicana). Males of this species show a pronounced polymorphism in body size and coloration, and females prefer large, colorful males in the absence of predators.
Results: In dichotomous choice tests predator-naive (lab-reared) females altered their initial preference for larger males in the presence of the cichlid Cichlasoma salvini, a natural predator of P. mexicana, and preferred small males instead. This effect was considerably weaker when females were confronted visually with the non-piscivorous cichlid Vieja bifasciata or the introduced non-piscivorous Nile tilapia (Oreochromis niloticus). In contrast, predator experienced (wild-caught) females did not respond to the same extent to the presence of a predator, most likely due to a learned ability to evaluate their predators' motivation to prey.
Conclusions: Our study highlights that (a) predatory fish can have a profound influence on the expression of mating preferences of their prey (thus potentially affecting the strength of sexual selection), and females may alter their mate choice behavior strategically to reduce their own exposure to predators. (b) Prey species can evolve visual predator recognition mechanisms and alter their mate choice only when a natural predator is present. (c) Finally, experiential effects can play an important role, and prey species may learn to evaluate the motivational state of their predators.
Current models for molecular electrical doping of organic semiconductors are found to be at odds with other well-established concepts in that field, like polaron formation. Addressing these inconsistencies for prototypical systems, we present experimental and theoretical evidence for intermolecular hybridization of organic semiconductor and dopant frontier molecular orbitals. Common doping-related observations are attributed to this phenomenon, and controlling the degree of hybridization emerges as a strategy for overcoming the present limitations in the yield of doping-induced charge carriers.
The spatial distribution of soil types is controlled by a set of environmental factors such as climate, organisms, parent material and topography as well as time and space. A change of these factors will lead to a change in the spatial distribution of soil types. In this study, we use a digital soil mapping approach to improve our knowledge about major soil type distributing factors in the steppe regions of Inner Mongolia (China) which currently undergo tremendous environmental change, e.g. climate and land use change. We use Random Forests in an effort to map Reference Soil Groups according to the World Reference Base for Soil Resources (WRB) in the Xilin River catchment. We benefit from the superior prediction capabilities of RF and additional interpretive results in order to identify the major environmental factors that control spatial patterns of soil types. The nine WRB soil groups that were identified and spatially predicted for the study area are Arenosol, Calcisol, Cambisol, Chernozem, Cryosol, Gleysol, Kastanozem, Phaeozem and Regosol.
Model and prediction performances of the RF model are high with an Out-of-Bag error of 51.6% for the model and a misclassification error for the predicted map of 28.9%. The main controlling factors of soil type distribution are land use, a set of topographic variables, geology and climate. However, land use and climate are of major importance and topography and geology are of minor importance. The visualizations of the predictions, the variable importance measures as result of RF and the comparisons of these with the spatial distribution of the environmental factors delivered additional, quantitative information of these controlling factors and revealed that intensively grazed areas are subjected to soil degradation. However, most of the area is still governed by natural soil forming processes which are driven by climate, topography and geology. Most importantly though, our study revealed that a shift towards warmer temperatures and lower precipitation regimes will lead to a change of the spatial distribution of RSGs towards steppe soils that store less carbon, i.e. a decrease of spatial extent of Phaeozems and an increase of spatial extent of Chernozems and Kastanozems.
A simplified run time analysis of the univariate marginal distribution algorithm on LeadingOnes
(2021)
With elementary means, we prove a stronger run time guarantee for the univariate marginal distribution algorithm (UMDA) optimizing the LEADINGONES benchmark function in the desirable regime with low genetic drift. If the population size is at least quasilinear, then, with high probability, the UMDA samples the optimum in a number of iterations that is linear in the problem size divided by the logarithm of the UMDA's selection rate. This improves over the previous guarantee, obtained by Dang and Lehre (2015) via the deep level-based population method, both in terms of the run time and by demonstrating further run time gains from small selection rates. Under similar assumptions, we prove a lower bound that matches our upper bound up to constant factors.
Developments of future scenarios of Antarctic ecosystems are still in their infancy, whilst predictions of the physical environment are recognized as being of global relevance and corresponding models are under continuous development. However, in the context of environmental change simulations of the future of the Antarctic biosphere are increasingly demanded by decision makers and the public, and are of fundamental scientific interest. This paper briefly reviews existing predictive models applied to Antarctic ecosystems before providing a conceptual framework for the further development of spatially and temporally explicit ecosystem models. The concept suggests how to improve approaches to relating species' habitat description to the physical environment, for which a case study on sea urchins is presented. In addition, the concept integrates existing and new ideas to consider dynamic components, particularly information on the natural history of key species, from physiological experiments and biomolecular analyses. Thereby, we identify and critically discuss gaps in knowledge and methodological limitations. These refer to process understanding of biological complexity, the need for high spatial resolution oceanographic data from the entire water column, and the use of data from biomolecular analyses in support of such ecological approaches. Our goal is to motivate the research community to contribute data and knowledge to a holistic, Antarctic-specific, macroecological framework. Such a framework will facilitate the integration of theoretical and empirical work in Antarctica, improving our mechanistic understanding of this globally influential ecoregion, and supporting actions to secure this biodiversity hotspot and its ecosystem services.
In the context of ecological risk assessment of chemicals, individual-based population models hold great potential to increase the ecological realism of current regulatory risk assessment procedures. However, developing and parameterizing such models is time-consuming and often ad hoc. Using standardized, tested submodels of individual organisms would make individual-based modelling more efficient and coherent. In this thesis, I explored whether Dynamic Energy Budget (DEB) theory is suitable for being used as a standard submodel in individual-based models, both for ecological risk assessment and theoretical population ecology. First, I developed a generic implementation of DEB theory in an individual-based modeling (IBM) context: DEB-IBM. Using the DEB-IBM framework I tested the ability of the DEB theory to predict population-level dynamics from the properties of individuals. We used Daphnia magna as a model species, where data at the individual level was available to parameterize the model, and population-level predictions were compared against independent data from controlled population experiments. We found that DEB theory successfully predicted population growth rates and peak densities of experimental Daphnia populations in multiple experimental settings, but failed to capture the decline phase, when the available food per Daphnia was low. Further assumptions on food-dependent mortality of juveniles were needed to capture the population dynamics after the initial population peak. The resulting model then predicted, without further calibration, characteristic switches between small- and large-amplitude cycles, which have been observed for Daphnia. We conclude that cross-level tests help detecting gaps in current individual-level theories and ultimately will lead to theory development and the establishment of a generic basis for individual-based models and ecology. In addition to theoretical explorations, we tested the potential of DEB theory combined with IBMs to extrapolate effects of chemical stress from the individual to population level. For this we used information at the individual level on the effect of 3,4-dichloroanailine on Daphnia. The individual data suggested direct effects on reproduction but no significant effects on growth. Assuming such direct effects on reproduction, the model was able to accurately predict the population response to increasing concentrations of 3,4-dichloroaniline. We conclude that DEB theory combined with IBMs holds great potential for standardized ecological risk assessment based on ecological models.
Individual-based models (IBMs) predict how dynamics at higher levels of biological organization emerge from individual-level processes. This makes them a particularly useful tool for ecotoxicology, where the effects of toxicants are measured at the individual level but protection goals are often aimed at the population level or higher. However, one drawback of IBMs is that they require significant effort and data to design for each species. A solution would be to develop IBMs for chemical risk assessment that are based on generic individual-level models and theory. Here we show how one generic theory, Dynamic Energy Budget (DEB) theory, can be used to extrapolate the effect of toxicants measured at the individual level to effects on population dynamics. DEB is based on first principles in bioenergetics and uses a common model structure to model all species. Parameterization for a certain species is done at the individual level and allows to predict population-level effects of toxicants for a wide range of environmental conditions and toxicant concentrations. We present the general approach, which in principle can be used for all animal species, and give an example using Daphnia magna exposed to 3,4-dichloroaniline. We conclude that our generic approach holds great potential for standardized ecological risk assessment based on ecological models. Currently, available data from standard tests can directly be used for parameterization under certain circumstances, but with limited extra effort standard tests at the individual would deliver data that could considerably improve the applicability and precision of extrapolation to the population level. Specifically, the measurement of a toxicant's effect on growth in addition to reproduction, and presenting data over time as opposed to reporting a single EC50 or dose response curve at one time point.
Individual-based models (IBMs) are increasingly used to link the dynamics of individuals to higher levels of biological organization. Still, many IBMs are data hungry, species specific, and time-consuming to develop and analyze. Many of these issues would be resolved by using general theories of individual dynamics as the basis for IBMs. While such theories have frequently been examined at the individual level, few cross-level tests exist that also try to predict population dynamics. Here we performed a cross-level test of dynamic energy budget (DEB) theory by parameterizing an individual-based model using individual-level data of the water flea, Daphnia magna, and comparing the emerging population dynamics to independent data from population experiments. We found that DEB theory successfully predicted population growth rates and peak densities but failed to capture the decline phase. Further assumptions on food-dependent mortality of juveniles were needed to capture the population dynamics after the initial population peak. The resulting model then predicted, without further calibration, characteristic switches between small-and large-amplitude cycles, which have been observed for Daphnia. We conclude that cross-level tests help detect gaps in current individual-level theories and ultimately will lead to theory development and the establishment of a generic basis for individual-based models and ecology.