High-momentum tails from low-momentum effective theories

In a recent work \cite{Anderson:2010aq}, Anderson \emph{et al.} used the renormalization group (RG) evolution of the momentum distribution to show that, under appropriate conditions, operator expectation values exhibit factorization in the two-nucleon system. Factorization is useful because it provides a clean separation of long- and short-distance physics, and suggests a possible interpretation of the universal high-momentum dependence and scaling behavior found in nuclear momentum distributions. In the present work, we use simple decoupling and scale-separation arguments to extend the results of Ref. \cite{Anderson:2010aq} to arbitrary low-energy $A$-body states. Using methods that are reminiscent of the operator product expansion (OPE) in quantum field theory, we find that the high-momentum tails of momentum distributions and static structure factors factorize into the product of a universal function of momentum that is fixed by two-body physics, and a state-dependent matrix element that is the same for both and is sensitive only to low-momentum structure of the many-body state. As a check, we apply our factorization relations to two well-studied systems, the unitary Fermi gas and the electron gas, and reproduce known expressions for the high-momentum tails of each.Comment: 22 pages, 0 figure

In-situ nitriding of Fe₂VAl during laser surface remelting to manipulate microstructure and crystalline defects

Tailoring the physical properties of complex materials for targeted applications requires optimizing the microstructure and crystalline defects that influence electrical and thermal transport and mechanical properties. Laser surface remelting can be used to modify the subsurface microstructure of bulk materials and hence manipulate their properties locally. Here, we introduce an approach to perform remelting in a reactive nitrogen atmosphere to form nitrides and induce segregation of nitrogen to structural defects. These defects arise from the fast solidification of the full-Heusler Fe2VAl compound that is a promising thermoelectric material. Advanced scanning electron microscopy, including electron channeling contrast imaging and three-dimensional electron backscatter diffraction, is complemented by atom probe tomography to study the distribution of crystalline defects and their local chemical composition. We reveal a high density of dislocations, which are stable due to their character as geometrically necessary dislocations. At these dislocations and low-angle grain boundaries, we observe segregation of nitrogen and vanadium, which can be enhanced by repeated remelting in nitrogen atmosphere. We propose that this approach can be generalized to other additive manufacturing processes to promote local segregation and precipitation states, thereby manipulating physical properties

Numerical modeling of microplastic interaction with fine sediment under estuarine conditions

Microplastic (MP) pollution is an important challenge for human life which has consequently affected the natural system of other organisms. Mismanagement and also careless handling of plastics in daily life has led to an accelerating contamination of air, water and soil compartments with MP. Under estuarine conditions, interactions with suspended particulate matter (SPM) like fine sediment in the water column play an important role on the fate of MP. Further studies to better understand the corresponding transport and accumulation mechanisms are required. This paper aims at providing a new modeling approach improving the MP settling velocity formulation based on higher suspended fine sediment concentrations, as i.e. existent in estuarine turbidity zones (ETZ). The capability of the suggested approach is examined through the modeling of released MP transport in water and their interactions with fine sediment (cohesive sediment/fluid mud). The model results suggest higher concentrations of MP in ETZ, both in the water column as well as the bed sediment, which is also supported by measurements. The key process in the modeling approach is the integration of small MP particles into estuarine fine sediment aggregates. This is realized by means of a threshold sediment concentration, above which the effective MP settling velocity increasingly approaches that of the sediment aggregates. The model results are in good agreement with measured MP mass concentrations. Moreover, the model results also show that lighter small MP particles can easier escape the ETZ towards the open sea

Effect of four plant species on soil 15N-access and herbage yield in temporary agricultural grasslands

Positive plant diversity-productivity relationships have been reported for experimental semi-natural grasslands (Cardinale et al. 2006; Hector et al. 1999; Tilman et al. 1996) as well as temporary agricultural grasslands (Frankow-Lindberg et al. 2009; Kirwan et al. 2007; Nyfeler et al. 2009; Picasso et al. 2008). Generally, these relationships are explained, on the one hand, by niche differentiation and facilitation (Hector et al. 2002; Tilman et al. 2002) and, on the other hand, by greater probability of including a highly productive plant species in high diversity plots (Huston 1997). Both explanations accept that diversity is significant because species differ in characteristics, such as root architecture, nutrient acquisition and water use efficiency, to name a few, resulting in composition and diversity being important for improved productivity and resource use (Naeem et al. 1994; Tilman et al. 2002). Plant diversity is generally low in temporary agricultural grasslands grown for ruminant fodder production. Grass in pure stands is common, but requires high nitrogen (N) inputs. In terms of N input, two-species grass-legume mixtures are more sustainable than grass in pure stands and consequently dominate low N input grasslands (Crews and Peoples 2004; Nyfeler et al. 2009; Nyfeler et al. 2011). In temperate grasslands, N is often the limiting factor for productivity (Whitehead 1995). Plant available soil N is generally concentrated in the upper soil layers, but may leach to deeper layers, especially in grasslands that include legumes (Scherer-Lorenzen et al. 2003) and under conditions with surplus precipitation (Thorup-Kristensen 2006). To improve soil N use efficiency in temporary grasslands, we propose the addition of deep-rooting plant species to a mixture of perennial ryegrass and white clover, which are the most widespread forage plant species in temporary grasslands in a temperate climate (Moore 2003). Perennial ryegrass and white clover possess relatively shallow root systems (Kutschera and Lichtenegger 1982; Kutschera and Lichtenegger 1992) with effective rooting depths of <0.7 m on a silt loamy site (Pollock and Mead 2008). Grassland species, such as lucerne and chicory, grow their tap-roots into deep soil layers and exploit soil nutrients and water in soil layers that the commonly grown shallow-rooting grassland species cannot reach (Braun et al. 2010; Skinner 2008). Chicory grown as a catch crop after barley reduced the inorganic soil N down to 2.5 m depth during the growing season, while perennial ryegrass affected the inorganic soil N only down to 1 m depth (Thorup-Kristensen 2006). Further, on a Wakanui silt loam in New Zealand chicory extracted water down to 1.9 m and lucerne down to 2.3 m soil depth, which resulted in greater herbage yields compared with a perennial ryegrass-white clover mixture, especially for dryland plots (Brown et al. 2005). There is little information on both the ability of deep- and shallow-rooting grassland species to access soil N from different vertical soil layers and the relation of soil N-access and herbage yield in temporary agricultural grasslands. Therefore, the objective of the present work was to test the hypotheses 1) that a mixture comprising both shallow- and deep-rooting plant species has greater herbage yields than a shallow-rooting binary mixture and pure stands, 2) that deep-rooting plant species (chicory and lucerne) are superior in accessing soil N from 1.2 m soil depth compared with shallow-rooting plant species, 3) that shallow-rooting plant species (perennial ryegrass and white clover) are superior in accessing soil N from 0.4 m soil depth compared with deep-rooting plant species, 4) that a mixture of deep- and shallow-rooting plant species has greater access to soil N from three soil layers compared with a shallow-rooting two-species mixture and that 5) the leguminous grassland plants, lucerne and white clover, have a strong impact on grassland N acquisition, because of their ability to derive N from the soil and the atmosphere

Density-Independent Mortality and Increasing Plant Diversity Are Associated with Differentiation of Taraxacum officinale into r- and K-Strategists

Background: Differential selection between clones of apomictic species may result in ecological differentiation without mutation and recombination, thus offering a simple system to study adaptation and life-history evolution in plants. Methodology/Principal Findings: We caused density-independent mortality by weeding to colonizer populations of the largely apomictic Taraxacum officinale (Asteraceae) over a 5-year period in a grassland biodiversity experiment (Jena Experiment). We compared the offspring of colonizer populations with resident populations deliberately sown into similar communities. Plants raised from cuttings and seeds of colonizer and resident populations were grown under uniform conditions. Offspring from colonizer populations had higher reproductive output, which was in general agreement with predictions of r-selection theory. Offspring from resident populations had higher root and leaf biomass, fewer flower heads and higher individual seed mass as predicted under K-selection. Plants grown from cuttings and seeds differed to some degree in the strength, but not in the direction, of their response to the r- vs. K-selection regime. More diverse communities appeared to exert stronger K-selection on resident populations in plants grown from cuttings, while we did not find significant effects of increasing species richness on plants grown from seeds. Conclusions/Significance: Differentiation into r- and K-strategists suggests that clones with characteristics of r-strategists were selected in regularly weeded plots through rapid colonization, while increasing plant diversity favoured the selection of clones with characteristics of K-strategists in resident populations. Our results show that different selection pressures may result in a rapid genetic differentiation within a largely apomictic species. Even under the assumption that colonizer and resident populations, respectively, happened to be r- vs. K-selected already at the start of the experiment, our results still indicate that the association of these strategies with the corresponding selection regimes was maintained during the 5-year experimental period

Diversity Promotes Temporal Stability across Levels of Ecosystem Organization in Experimental Grasslands

The diversity–stability hypothesis states that current losses of biodiversity can impair the ability of an ecosystem to dampen the effect of environmental perturbations on its functioning. Using data from a long-term and comprehensive biodiversity experiment, we quantified the temporal stability of 42 variables characterizing twelve ecological functions in managed grassland plots varying in plant species richness. We demonstrate that diversity increases stability i) across trophic levels (producer, consumer), ii) at both the system (community, ecosystem) and the component levels (population, functional group, phylogenetic clade), and iii) primarily for aboveground rather than belowground processes. Temporal synchronization across studied variables was mostly unaffected with increasing species richness. This study provides the strongest empirical support so far that diversity promotes stability across different ecological functions and levels of ecosystem organization in grasslands

Plant Species Loss Affects Life-History Traits of Aphids and Their Parasitoids

The consequences of plant species loss are rarely assessed in a multi-trophic context and especially effects on life-history traits of organisms at higher trophic levels have remained largely unstudied. We used a grassland biodiversity experiment and measured the effects of two components of plant diversity, plant species richness and the presence of nitrogen-fixing legumes, on several life-history traits of naturally colonizing aphids and their primary and secondary parasitoids in the field. We found that, irrespective of aphid species identity, the proportion of winged aphid morphs decreased with increasing plant species richness, which was correlated with decreasing host plant biomass. Similarly, emergence proportions of parasitoids decreased with increasing plant species richness. Both, emergence proportions and proportions of female parasitoids were lower in plots with legumes, where host plants had increased nitrogen concentrations. This effect of legume presence could indicate that aphids were better defended against parasitoids in high-nitrogen environments. Body mass of emerged individuals of the two most abundant primary parasitoid species was, however, higher in plots with legumes, suggesting that once parasitoids could overcome aphid defenses, they could profit from larger or more nutritious hosts. Our study demonstrates that cascading effects of plant species loss on higher trophic levels such as aphids, parasitoids and secondary parasitoids begin with changed life-history traits of these insects. Thus, life-history traits of organisms at higher trophic levels may be useful indicators of bottom-up effects of plant diversity on the biodiversity of consumers

Using Plant Functional Traits to Explain Diversity–Productivity Relationships

Background: The different hypotheses proposed to explain positive species richness–productivity relationships, i.e. selection effect and complementarity effect, imply that plant functional characteristics are at the core of a mechanistic understanding of biodiversity effects. Methodology/Principal Findings: We used two community-wide measures of plant functional composition, (1) community- weighted means of trait values (CWM) and (2) functional trait diversity based on Rao’s quadratic diversity (FDQ) to predict biomass production and measures of biodiversity effects in experimental grasslands (Jena Experiment) with different species richness (2, 4, 8, 16 and 60) and different functional group number and composition (1 to 4; legumes, grasses, small herbs, tall herbs) four years after establishment. Functional trait composition had a larger predictive power for community biomass and measures of biodiversitity effects (40–82% of explained variation) than species richness per se (,1–13% of explained variation). CWM explained a larger amount of variation in community biomass (80%) and net biodiversity effects (70%) than FDQ (36 and 38% of explained variation respectively). FDQ explained similar proportions of variation in complementarity effects (24%, positive relationship) and selection effects (28%, negative relationship) as CWM (27% of explained variation for both complementarity and selection effects), but for all response variables the combination of CWM and FDQ led to significant model improvement compared to a separate consideration of different components of functional trait composition. Effects of FDQ were mainly attributable to diversity in nutrient acquisition and life-history strategies. The large spectrum of traits contributing to positive effects of CWM on biomass production and net biodiversity effects indicated that effects of dominant species were associated with different trait combinations. Conclusions/Significance: Our results suggest that the identification of relevant traits and the relative impacts of functional identity of dominant species and functional diversity are essential for a mechanistic understanding of the role of plant diversity for ecosystem processes such as aboveground biomass production

How useful is Active Learning for Image-based Plant Phenotyping?

Deep learning models have been successfully deployed for a diverse array of image-based plant phenotyping applications including disease detection and classification. However, successful deployment of supervised deep learning models requires large amount of labeled data, which is a significant challenge in plant science (and most biological) domains due to the inherent complexity. Specifically, data annotation is costly, laborious, time consuming and needs domain expertise for phenotyping tasks, especially for diseases. To overcome this challenge, active learning algorithms have been proposed that reduce the amount of labeling needed by deep learning models to achieve good predictive performance. Active learning methods adaptively select samples to annotate using an acquisition function to achieve maximum (classification) performance under a fixed labeling budget. We report the performance of four different active learning methods, (1) Deep Bayesian Active Learning (DBAL), (2) Entropy, (3) Least Confidence, and (4) Coreset, with conventional random sampling-based annotation for two different image-based classification datasets. The first image dataset consists of soybean [Glycine max L. (Merr.)] leaves belonging to eight different soybean stresses and a healthy class, and the second consists of nine different weed species from the field. For a fixed labeling budget, we observed that the classification performance of deep learning models with active learning-based acquisition strategies is better than random sampling-based acquisition for both datasets. The integration of active learning strategies for data annotation can help mitigate labelling challenges in the plant sciences applications particularly where deep domain knowledge is required

Nitrogen but not phosphorus addition affects symbiotic N-2 fixation by legumes in natural and semi-natural grasslands located on four continents

Background and aims: The amount of nitrogen (N) derived from symbiotic N-2 fixation by legumes in grasslands might be affected by anthropogenic N and phosphorus (P) inputs, but the underlying mechanisms are not known.Methods: We evaluated symbiotic N-2 fixation in 17 natural and semi-natural grasslands on four continents that are subjected to the same full-factorial N and P addition experiment, using the N-15 natural abundance method.Results: N as well as combined N and P (NP) addition reduced aboveground legume biomass by 65% and 45%, respectively, compared to the control, whereas P addition had no significant impact. Addition of N and/or P had no significant effect on the symbiotic N-2 fixation per unit legume biomass. In consequence, the amount of N fixed annually per grassland area was less than half in the N addition treatments compared to control and P addition, irrespective of whether the dominant legumes were annuals or perennials.Conclusion: Our results reveal that N addition mainly impacts symbiotic N-2 fixation via reduced biomass of legumes rather than changes in N-2 fixation per unit legume biomass. The results show that soil N enrichment by anthropogenic activities significantly reduces N-2 fixation in grasslands, and these effects cannot be reversed by additional P amendment