189 research outputs found

    Chromatic Signals Control Proboscis Movements during Hovering Flight in the Hummingbird Hawkmoth Macroglossum stellatarum

    Get PDF
    Most visual systems are more sensitive to luminance than to colour signals. Animals resolve finer spatial detail and temporal changes through achromatic signals than through chromatic ones. Probably, this explains that detection of small, distant, or moving objects is typically mediated through achromatic signals. Macroglossum stellatarum are fast flying nectarivorous hawkmoths that inspect flowers with their long proboscis while hovering. They can visually control this behaviour using floral markings known as nectar guides. Here, we investigate whether this is mediated by chromatic or achromatic cues. We evaluated proboscis placement, foraging efficiency, and inspection learning of naïve moths foraging on flower models with coloured markings that offered either chromatic, achromatic or both contrasts. Hummingbird hawkmoths could use either achromatic or chromatic signals to inspect models while hovering. We identified three, apparently independent, components controlling proboscis placement: After initial contact, 1) moths directed their probing towards the yellow colour irrespectively of luminance signals, suggesting a dominant role of chromatic signals; and 2) moths tended to probe mainly on the brighter areas of models that offered only achromatic signals. 3) During the establishment of the first contact, naïve moths showed a tendency to direct their proboscis towards the small floral marks independent of their colour or luminance. Moths learned to find nectar faster, but their foraging efficiency depended on the flower model they foraged on. Our results imply that M. stellatarum can perceive small patterns through colour vision. We discuss how the different informational contents of chromatic and luminance signals can be significant for the control of flower inspection, and visually guided behaviours in general

    Coagulation and fragmentation dynamics of inertial particles

    Full text link
    Inertial particles suspended in many natural and industrial flows undergo coagulation upon collisions and fragmentation if their size becomes too large or if they experience large shear. Here we study this coagulation-fragmentation process in time-periodic incompressible flows. We find that this process approaches an asymptotic, dynamical steady state where the average number of particles of each size is roughly constant. We compare the steady-state size distributions corresponding to two fragmentation mechanisms and for different flows and find that the steady state is mostly independent of the coagulation process. While collision rates determine the transient behavior, fragmentation determines the steady state. For example, for fragmentation due to shear, flows that have very different local particle concentrations can result in similar particle size distributions if the temporal or spatial variation of shear forces is similar.Comment: 8 pages, 7 figure

    Do Queens of Bumblebee Species Differ In Their Choice Of Flower Colour Morphs Of Corydalis Cava (Fumariaceae)?

    Get PDF
    International audienceAbstractBumblebee queens require a continuous supply of flowering food plants from early spring for the successful development of annual colonies. Early in spring, Corydalis cava provides essential nectar and pollen resources and a choice of flower colour. In this paper, we examine flower colour choice (purple or white) in C. cava and verify the hypothesis that bumblebee queens differ in their choice of flower colour. A total of 10,615 observations of flower visits were made in spring 2011 and spring 2014 near Poznań, western Poland. Our results suggest that Bombus lucorum/cryptarum used purple flowers less, while Bombus terrestris used purple flowers more and Bombus hortorum showed no preference. Therefore, the colour morphs of C. cava are probably co-evolutionary adaptations to the development of another part of the insect community which has different colour preferences

    Mechanistic origins of variability in phytoplankton dynamics. Part II: analysis of mesocosm blooms under climate change scenarios

    Get PDF
    Driving factors of phytoplankton spring blooms have been discussed since long, but rarely analyzed quantitatively. Here, we use a mechanistic size-based ecosystem model to reconstruct observations made during the Kiel mesocosm experiments (2005–2006). The model accurately hindcasts highly variable bloom developments including community shifts in cell size. Under low light, phytoplankton dynamics was mostly controlled by selective mesozooplankton grazing. Selective grazing also explains initial dominance of large diatoms under high light conditions. All blooms were mainly terminated by aggregation and sedimentation. Allometries in nutrient uptake capabilities led to a delayed, post-bloom dominance of small species. In general, biomass and trait dynamics revealed many mutual dependencies, while growth factors decoupled from the respective selective forces. A size shift induced by one factor often changed the growth dependency on other factors. Within climate change scenarios, these indirect effects produced large sensitivities of ecosystem fluxes to the size distribution of winter phytoplankton. These sensitivities exceeded those found for changes in vertical mixing, whereas temperature changes only had minimal impacts

    История развития физической культуры и спорта на Урале в дореволюционный период

    Get PDF
    На сегодняшний день становится чрезвычайно актуальным рассмотрение феномена физической культуры и спорта сквозь призму принципа историзма. Существует еще много неизвестного в истории физической культуры, что требует переоценки событий, фактов с позиции современност

    From ether to acid: a plausible degradation pathway of glycerol dialkyl glycerol tetraethers

    Get PDF
    Glycerol dialkyl glycerol tetraethers (GDGTs) are ubiquitous microbial lipids with extensive demonstrated and potential roles as paleoenvironmental proxies. Despite the great attention they receive, comparatively little is known regarding their diagenetic fate. Putative degradation products of GDGTs, identified as hydroxyl and carboxyl derivatives, were detected in lipid extracts of marine sediment, seep carbonate, hot spring sediment and cells of the marine thaumarchaeon Nitrosopumilus maritimus. The distribution of GDGT degradation products in environmental samples suggests that both biotic and abiotic processes act as sinks for GDGTs. More than a hundred newly recognized degradation products afford a view of the stepwise degradation of GDGT via (1) ether bond hydrolysis yielding hydroxyl isoprenoids, namely, GDGTol (glycerol dialkyl glycerol triether alcohol), GMGD (glycerol monobiphytanyl glycerol diether), GDD (glycerol dibiphytanol diether), GMM (glycerol monobiphytanol monoether) and bpdiol (biphytanic diol); (2) oxidation of isoprenoidal alcohols into corresponding carboxyl derivatives and (3) chain shortening to yield C39and smaller isoprenoids. This plausible GDGT degradation pathway from glycerol ethers to isoprenoidal fatty acids provides the link to commonly detected head-to-head linked long chain isoprenoidal hydrocarbons in petroleum and sediment samples. The problematic C80to C82tetraacids that cause naphthenate deposits in some oil production facilities can be generated from H-shaped glycerol monoalkyl glycerol tetraethers (GMGTs) following the same process, as indicated by the distribution of related derivatives in hydrothermally influenced sediments.Seventh Framework Programme (European Commission) (ERC Grant 247153

    Geophysical monitoring and reactive transport modeling of ureolytically-driven calcium carbonate precipitation

    Get PDF
    Ureolytically-driven calcium carbonate precipitation is the basis for a promising in-situ remediation method for sequestration of divalent radionuclide and trace metal ions. It has also been proposed for use in geotechnical engineering for soil strengthening applications. Monitoring the occurrence, spatial distribution, and temporal evolution of calcium carbonate precipitation in the subsurface is critical for evaluating the performance of this technology and for developing the predictive models needed for engineering application. In this study, we conducted laboratory column experiments using natural sediment and groundwater to evaluate the utility of geophysical (complex resistivity and seismic) sensing methods, dynamic synchrotron x-ray computed tomography (micro-CT), and reactive transport modeling for tracking ureolytically-driven calcium carbonate precipitation processes under site relevant conditions. Reactive transport modeling with TOUGHREACT successfully simulated the changes of the major chemical components during urea hydrolysis. Even at the relatively low level of urea hydrolysis observed in the experiments, the simulations predicted an enhanced calcium carbonate precipitation rate that was 3-4 times greater than the baseline level. Reactive transport modeling results, geophysical monitoring data and micro-CT imaging correlated well with reaction processes validated by geochemical data. In particular, increases in ionic strength of the pore fluid during urea hydrolysis predicted by geochemical modeling were successfully captured by electrical conductivity measurements and confirmed by geochemical data. The low level of urea hydrolysis and calcium carbonate precipitation suggested by the model and geochemical data was corroborated by minor changes in seismic P-wave velocity measurements and micro-CT imaging; the latter provided direct evidence of sparsely distributed calcium carbonate precipitation. Ion exchange processes promoted through NH4+ production during urea hydrolysis were incorporated in the model and captured critical changes in the major metal species. The electrical phase increases were potentially due to ion exchange processes that modified charge structure at mineral/water interfaces. Our study revealed the potential of geophysical monitoring for geochemical changes during urea hydrolysis and the advantages of combining multiple approaches to understand complex biogeochemical processes in the subsurface

    Meneco, a Topology-Based Gap-Filling Tool Applicable to Degraded Genome-Wide Metabolic Networks

    Get PDF
    International audienceIncreasing amounts of sequence data are becoming available for a wide range of non-model organisms. Investigating and modelling the metabolic behaviour of those organisms is highly relevant to understand their biology and ecology. As sequences are often incomplete and poorly annotated, draft networks of their metabolism largely suffer from incompleteness. Appropriate gap-filling methods to identify and add missing reactions are therefore required to address this issue. However, current tools rely on phenotypic or taxonomic information, or are very sensitive to the stoichiometric balance of metabolic reactions, especially concerning the co-factors. This type of information is often not available or at least prone to errors for newly-explored organisms. Here we introduce Meneco, a tool dedicated to the topological gap-filling of genome-scale draft metabolic networks. Meneco reformulates gap-filling as a qualitative combinatorial optimization problem, omitting constraints raised by the stoichiometry of a metabolic network considered in other methods, and solves this problem using Answer Set Programming. Run on several artificial test sets gathering 10,800 degraded Escherichia coli networks Meneco was able to efficiently identify essential reactions missing in networks at high degradation rates, outperforming the stoichiometry-based tools in scalability. To demonstrate the utility of Meneco we applied it to two case studies. Its application to recent metabolic networks reconstructed for the brown algal model Ectocarpus siliculosus and an associated bacterium Candidatus Phaeomarinobacter ectocarpi revealed several candidate metabolic pathways for algal-bacterial interactions. Then Meneco was used to reconstruct, from transcriptomic and metabolomic data, the first metabolic network for the microalga Euglena mutabilis. These two case studies show that Meneco is a versatile tool to complete draft genome-scale metabolic networks produced from heterogeneous data, and to suggest relevant reactions that explain the metabolic capacity of a biological system
    corecore