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Cavitation at the solid surface normally begins with nucleation, in which defects or assembled molecules located at a liquid-solid interface act as nucleation centers and are actively involved in the evolution of cavitation bubbles. Here, we propose a simple approach to evaluate the behavior of cavitation bubbles formed under high intensity ultrasound (20 kHz, 51.3 W cm (2)) at solid surfaces, based on sonication of patterned substrates with a small roughness (less than 3 nm) and controllable surface energy. A mixture of octadecylphosphonic acid (ODTA) and octadecanethiol (ODT) was stamped on the Si wafer coated with different thicknesses of an aluminium layer (20-500 nm). We investigated the growth mechanism of cavitation bubble nuclei and the evolution of individual pits (defects) formed under sonication on the modified surface. A new activation behavior as a function of Al thickness, sonication time, ultrasonic power and temperature is reported. In this process cooperativity is introduced, as initially formed pits further reduce the energy to form bubbles. Furthermore, cavitation on the patterns is a controllable process, where up to 40-50 min of sonication time only the hydrophobic areas are active nucleation sites. This study provides a convincing proof of our theoretical approach on nucleation.
The circular dichroism (CD) induced by femtosecond laser pulse excitation of 3-methylcyclopentanone has been investigated by means of experiment and theory as a function of the laser pulse duration. In the experiment the CD in ion yields is measured by femtosecond laser ionization via a one-photon resonant excited state. In the theoretical part the CD is calculated by solving laser driven quantum electron dynamics for the same resonant excitation based on ab initio electronic structure calculations employing a complete description of the electric field-electric dipole and magnetic field-magnetic dipole interactions. Both the experimentally measured CD in ion yields and the calculated CD in excited state populations exhibit a marked increase of the CD for pulse duration increasing from 50 fs to about 200 fs. Beyond 200 fs pulse duration the CD levels off. The combination of experimental and theoretical evidences indicates that the CD decreases with increasing laser intensity connected to the increased coupling between the excited states.
Understanding changes in biodiversity in agricultural landscapes in relation to land-use type and intensity is a major issue in current ecological research. In this context nutrient enrichment has been identified as a key mechanism inducing species loss in Central European grassland ecosystems. At the same time, insights into the linkage between agricultural land use and plant nutrient status are largely missing. So far, studies on the relationship between chemical composition of plant community biomass and biodiversity have mainly been restricted to wetlands and all these studies neglected the effects of land use. Therefore, we analyzed aboveground biomass of 145 grassland plots covering a gradient of land-use intensities in three regions across Germany. In particular, we explored relationships between vascular plant species richness and nutrient concentrations as well as fibre contents (neutral and acid detergent fibre and lignin) in the aboveground community biomass.
We found the concentrations of several nutrients in the biomass to be closely linked to plant species richness and land use. Whereas phosphorus concentrations increased with land-use intensity and decreased with plant species richness, nitrogen and potassium concentrations showed less clear patterns. Fibre fractions were negatively related to nutrient concentrations in biomass, but hardly to land-use measures and species richness. Only high lignin contents were positively associated with species richness of grasslands. The N:P ratio was strongly positively related to species richness and even more so to the number of endangered plant species, indicating a higher persistence of endangered species under P (co-)limited conditions. Therefore, we stress the importance of low P supply for species-rich grasslands and suggest the N:P ratio in community biomass to be a useful proxy of the conservation value of agriculturally used grasslands.
Trait-based studies have become extremely common in plant ecology. Trait-based approaches often rely on the tacit assumption that intraspecific trait variability (ITV) is negligible compared to interspecific variability, so that species can be characterized by mean trait values. Yet, numerous recent studies have challenged this assumption by showing that ITV significantly affects various ecological processes. Accounting for ITV may thus strengthen trait-based approaches, but measuring trait values on a large number of individuals per species and site is not feasible. Therefore, it is important and timely to synthesize existing knowledge on ITV in order to (1) decide critically when ITV should be considered, and (2) establish methods for incorporating this variability. Here we propose a practical set of rules to identify circumstances under which ITV should be accounted for. We formulate a spatial trait variance partitioning hypothesis to highlight the spatial scales at which ITV cannot be ignored in ecological studies. We then refine a set of four consecutive questions on the research question, the spatial scale, the sampling design, and the type of studied traits, to determine case-by-case if a given study should quantify ITV and test its effects. We review methods for quantifying ITV and develop a step-by-step guideline to design and interpret simulation studies that test for the importance of ITV. Even in the absence of quantitative knowledge on ITV, its effects can be assessed by varying trait values within species within realistic bounds around the known mean values. We finish with a discussion of future requirements to further incorporate ITV within trait-based approaches. This paper thus delineates a general framework to account for ITV and suggests a direction towards a more quantitative trait-based ecology.
The photo-dehydro-Diels-Alder (PDDA) reaction is a valuable extension of the classical Diels-Alder (DA) reaction. The PDDA reaction differs from the DA reaction by the replacement of one of the C-C-double bonds of the diene moiety by a C-C triple bond and by the photochemical triggering of the reaction. This entails that, in contrast to the DA reaction, the PDDA reaction proceeds according to a multistage mechanism with biradicals and cycloallenes as intermediates. The PDDA reaction provides access to a considerable variety of compound classes. For example, 1-phenylnaphthlenes, 1,1'-binaphthyls, N-heterocyclic biaryls, and naphthalenophanes could be obtained by this reaction.
The inversion of the flexible five-membered ring in tetrahydrodicyclopentadiene (TH-DCPD) derivatives remains fast on the NMR timescale even at 103 K. Since the intramolecular exchange process could not be sufficiently slowed for spectroscopic evaluation, the conformational equilibrium is thus inaccessible by dynamic NMR. Fortunately, the spatial magnetic properties of the aryl and carbonyl groups attached to the DCPD skeleton can be employed in order to evaluate the conformational state of the system. In this context, the anisotropic effects of the functional groups in the H-1 NMR spectra prove to be the molecular response property of spatial nucleus independent chemical shifts (NICS).
Understanding and predicting the composition and spatial structure of communities is a central challenge in ecology. An important structural property of animal communities is the distribution of individual home ranges. Home range formation is controlled by resource heterogeneity, the physiology and behaviour of individual animals, and their intra- and interspecific interactions. However, a quantitative mechanistic understanding of how home range formation influences community composition is still lacking. To explore the link between home range formation and community composition in heterogeneous landscapes we combine allometric relationships for physiological properties with an algorithm that selects optimal home ranges given locomotion costs, resource depletion and competition in a spatially-explicit individual-based modelling framework. From a spatial distribution of resources and an input distribution of animal body mass, our model predicts the size and location of individual home ranges as well as the individual size distribution (ISD) in an animal community. For a broad range of body mass input distributions, including empirical body mass distributions of North American and Australian mammals, our model predictions agree with independent data on the body mass scaling of home range size and individual abundance in terrestrial mammals. Model predictions are also robust against variation in habitat productivity and landscape heterogeneity. The combination of allometric relationships for locomotion costs and resource needs with resource competition in an optimal foraging framework enables us to scale from individual properties to the structure of animal communities in heterogeneous landscapes. The proposed spatially-explicit modelling concept not only allows for detailed investigation of landscape effects on animal communities, but also provides novel insights into the mechanisms by which resource competition in space shapes animal communities.
Standing stocks are typically easier to measure than process rates such as production. Hence, stocks are often used as indicators of ecosystem functions although the latter are generally more strongly related to rates than to stocks. The regulation of stocks and rates and thus their variability over time may differ, as stocks constitute the net result of production and losses. Based on long-term high frequency measurements in a large, deep lake we explore the variability patterns in primary and bacterial production and relate them to those of the corresponding standing stocks, i.e. chlorophyll concentration, phytoplankton and bacterial biomass. We employ different methods (coefficient of variation, spline fitting and spectral analysis) which complement each other for assessing the variability present in the plankton data, at different temporal scales. In phytoplankton, we found that the overall variability of primary production is dominated by fluctuations at low frequencies, such as the annual, whereas in stocks and chlorophyll in particular, higher frequencies contribute substantially to the overall variance. This suggests that using standing stocks instead of rate measures leads to an under- or overestimation of food shortage for consumers during distinct periods of the year. The range of annual variation in bacterial production is 8 times greater than biomass, showing that the variability of bacterial activity (e.g. oxygen consumption, remineralisation) would be underestimated if biomass is used. The P/B ratios were variable and although clear trends are present in both bacteria and phytoplankton, no systematic relationship between stock and rate measures were found for the two groups. Hence, standing stock and process rate measures exhibit different variability patterns and care is needed when interpreting the mechanisms and implications of the variability encountered.
The analysis of palaeoclimate time series is usually affected by severe methodological problems, resulting primarily from non-equidistant sampling and uncertain age models. As an alternative to existing methods of time series analysis, in this paper we argue that the statistical properties of recurrence networks - a recently developed approach - are promising candidates for characterising the system's nonlinear dynamics and quantifying structural changes in its reconstructed phase space as time evolves. In a first order approximation, the results of recurrence network analysis are invariant to changes in the age model and are not directly affected by non-equidistant sampling of the data. Specifically, we investigate the behaviour of recurrence network measures for both paradigmatic model systems with non-stationary parameters and four marine records of long-term palaeoclimate variations. We show that the obtained results are qualitatively robust under changes of the relevant parameters of our method, including detrending, size of the running window used for analysis, and embedding delay. We demonstrate that recurrence network analysis is able to detect relevant regime shifts in synthetic data as well as in problematic geoscientific time series. This suggests its application as a general exploratory tool of time series analysis complementing existing methods.