366 research outputs found

    Global leaf-trait mapping based on optimality theory

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    Aim Leaf traits are central to plant function, and key variables in ecosystem models. However recently published global trait maps, made by applying statistical or machine-learning techniques to large compilations of trait and environmental data, differ substantially from one another. This paper aims to demonstrate the potential of an alternative approach, based on eco-evolutionary optimality theory, to yield predictions of spatio-temporal patterns in leaf traits that can be independently evaluated. Innovation Global patterns of community-mean specific leaf area (SLA) and photosynthetic capacity (Vcmax) are predicted from climate via existing optimality models. Then leaf nitrogen per unit area (Narea) and mass (Nmass) are inferred using their (previously derived) empirical relationships to SLA and Vcmax. Trait data are thus reserved for testing model predictions across sites. Temporal trends can also be predicted, as consequences of environmental change, and compared to those inferred from leaf-level measurements and/or remote-sensing methods, which are an increasingly important source of information on spatio-temporal variation in plant traits. Main conclusions Model predictions evaluated against site-mean trait data from > 2,000 sites in the Plant Trait database yielded R2 = 73% for SLA, 38% for Nmass and 28% for Narea. Declining species-level Nmass, and increasing community-level SLA, have both been recently reported and were both correctly predicted. Leaf-trait mapping via optimality theory holds promise for macroecological applications, including an improved understanding of community leaf-trait responses to environmental change

    Experimental Impacts into Strength-Layered Targets: Crater Morphology and Morphometry

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    Impact cratering is a fundamental physical process that has dominated the evolution and modification of nearly every planetary surface in the Solar System. Impact craters serve as a means to probe the subsurface structure of a planetary body and provide hints about target surface properties. By examining small craters on the lunar maria and comparing these to experimental impacts in the laboratory, Oberbeck and Quaide first suggested that crater morphology can be used to estimate the thickness of a regolith layer on top of a more competent unit. Lunar craters show a morphological progression from a simple bowl shape to flat-floored and concentric craters as crater diameter increases for a given regolith thickness. This quantitative relationship is commonly used to estimate regolith thicknesses on the lunar surface and has also been explored via numerical and experimental studies. Here we report on a series of experimental impact craters formed in targets com-posed of a thin layer of loose sand on top of a stronger substrate at the Experimental Impact Laboratory at NASA Johnson Space Center

    Experimental Impacts into Strength-Layered Targets: Ejecta Kinematics

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    AImpact cratering has dominated the evolution and modification of planetary surfaces through-out the history of the solar system. Impact craters can serve as probes to understanding the details of a planetary subsurface; for example, Oberbeck and Quaide, suggested that crater morphology can be used to estimate the thickness of a regolith layer on top of a more competent unit. Lunar craters show a morphological progression from a simple bowl shape to flat-floored and concentric craters as crater diameter in-creases for a given regolith thickness. The final shape of the impact crater is a result of the subsurface flow-field initiated as the projectile transfers its energy and momentum to the target surface at the moment of impact. Therefore, when a regolith layer is present over a stronger substrate, such as is the case on the lunar surface, the substrate modifies the flow-field and thereby the excavation flow of the crater, which is reflected in the morphology of the final crater. Here we report on a series of experimental impacts into targets composed of a thin layer of loose sand on top of a stronger substrate. We use the Ejection-Velocity Measurement System developed to examine the ejecta kinematics during the formation of these craters

    Easing into Reality: Experimental Impacts into Slopes and Layers

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    Impact cratering is the dominant geo-logic process affecting the surfaces of solid bodies throughout our solar system. Because large impacts are (luckily) rare on Earth, the process is studied through experiments, observations of existing structures, numerical modeling, and theory, most of which make the simplifying assumptions that the target is homogeneous, with no substantial topography. Craters do not always form on level targets com-posed of homogeneous loose material. Rather (Fig. 1), they often form on sloped surfaces and in layered tar-gets, both of which significantly influence the excavation and ejecta deposition processes. Such craters are common on the Moon and asteroids. We are investigating crater formation in two separate suites of experiments using sloped and layered targets (Fig. 2) at the Experimental Impact Laboratory at NASA Johnson Space Center. An experiment was also performed in a flat, homogenous target to serve as a reference

    A Dual-Stack Coaxial Magnetic Gear for a Wave Energy Conversion Generator

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    This paper presents the electromagnetic and mechanical design and analyses of a 7.67:1 gear ratio magnetic gear for a wave energy converter demonstrator. A 2-D and 3-D magnetostatic finite element analysis (FEA) was conducted to maximize the mass torque density. To increase torque without increasing the diameter a unique dual-stack rotor topology was used along with a twelve-segment per pole-pair inner rotor Halbach array and a four-segment per pole-pair outer rotor Halbach topology. The eddy current loss within the magnetic gear was mitigated by using laminated magnets and a low-loss electrical steel. The experimentally tested magnetic gear had a peak torque of 1796.8 N∙m which corresponds to an active region volumetric and mass torque density of 221.1 N∙m/L and 105.74 N∙m/kg, respectively. The efficiency at rated speed and maximum torque was measured to be 95%. A new in-plane eddy current loss mechanism was identified as being a primary reason for the measured electrical losses being higher than initially calculated

    The p75 receptor mediates axon growth inhibition through an association with PIR-B

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    The Nogo receptor and paired immunoglobulin-like receptor B (PIR-B) are receptors for three myelin-derived axon-growth inhibitors, including myelin-associated glycoprotein (MAG). In this study, we report that the p75 receptor is required for the signal transduction of PIR-B, which interacted with p75 upon ligand binding. In addition, p75 was required for activation of Src homology 2-containing protein tyrosine phosphatase (SHP), which is induced by MAG binding to PIR-B. Mice carrying a mutation in the p75 gene showed promotion of axonal regeneration after optic nerve injury. Thus, our results indicate that p75 has a critical role in axon growth inhibition in specific neuronal tracts

    TRY plant trait database - enhanced coverage and open access

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    Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

    On the continuing relevance of Mandelbrot’s non-ergodic fractional renewal models of 1963 to 1967

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    The problem of “1∕ƒ” noise has been with us for about a century. Because it is so often framed in Fourier spectral language, the most famous solutions have tended to be the stationary long range dependent (LRD) models such as Mandelbrot’s fractional Gaussian noise. In view of the increasing importance to physics of non-ergodic fractional renewal models, and their links to the CTRW, I present preliminary results of my research into the history of Mandelbrot’s very little known work in that area from 1963 to 1967. I speculate about how the lack of awareness of this work in the physics and statistics communities may have affected the development of complexity science, and I discuss the differences between the Hurst effect, “1∕ƒ” noise and LRD, concepts which are often treated as equivalent
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