Fine-Particle Charging-Rate-Limit Modification to Grain Dynamics in Abrupt and Gradual Inhomogeneities

Gyro-phase drift is a guiding center drift that is directly dependent on the charging rate limit of dust grains. The effect of introducing a gyro-phase-dependence on the grain charge leads to two orthogonal components of guiding-center drift. One component, referred to here as grad-q drift results from the time-varying, gyro-phase angle dependent, in-situ-equilibrium grain charge, assuming that the grain charging is instantaneous. For this component, the grain is assumed to be always in its in-situ-equilibrium charge state and this state gyro-synchronously varies with respect to the grain\u27s average charge state. The other component, referred to here as the gyro-phase drift, arises from any non-instantaneous-charging-induced modification of the grad-q drift and points in the direction associated with increasing magnitude of in-situ-equilibrium charge state. Gyro-synchronous grain charge modulation may arise from either abrupt or gradual inhomogeneity in plasma conditions. In the abrupt inhomogeneity, q1 is the in-situ-equilibrium charge on one side of the inhomogeneity, q2 is the in-situ equilibrium charge on the other side, q1 Gyro-synchronous grain charge modulation may arise from either abrupt or gradual inhomogeneity in plasma conditions. In the abrupt inhomogeneity, q1 is the in-situ-equilibrium charge on one side of the inhomogeneity, q2 is the in-situ equilibrium charge on the other side, q1

Competition from Bromus tectorum removes differences between perennial grasses in N capture and conservation strategies

Background and aims Competition from the annual grass Bromus tectorum threatens aridland perennial bunchgrass communities. Unlike annuals, perennials must allocate part of their first year nitrogen (N) budget to storage rather than growth, potentially placing them at a competitive disadvantage. Methods We evaluated N acquisition and conservation for two perennial bunchgrasses, Agropyron desertorum and Pseudoroegneria spicata, at the seedling stage to investigate potential trade-offs between storage and growth when grown with and without B. tectorum under two levels of soil N. Results Agropyron desertorum had higher growth rates, N uptake, and N productivity than P. spicata when grown without B. tectorum, but trait values were similarly low for both species under competition. Without competition, N resorption was poor under high soil N, but it was equally proficient among species under competition. Conclusions A. desertorum had higher growth rates and N productivity than P. spicata without competition, suggesting these traits may in part promote its greater success in restoration programs. However, B. tectorum neighbors reduced its trait advantage. As plant traits become more integral to restoration ecology, understanding how N capture and conservation traits vary across candidate species and under competition may improve our ability to select species with the highest likelihood of establishing in arid, nutrient-limited systems

Body fineness ratio as a predictor of maximum prolonged-swimming speed in coral reef fishes

The ability to sustain high swimming speeds is believed to be an important factor affecting resource acquisition in fishes. While we have gained insights into how fin morphology and motion influences swimming performance in coral reef fishes, the role of other traits, such as body shape, remains poorly understood. We explore the ability of two mechanistic models of the causal relationship between body fineness ratio and endurance swimming-performance to predict maximum prolonged-swimming speed (Umax ) among 84 fish species from the Great Barrier Reef, Australia. A drag model, based on semi-empirical data on the drag of rigid, submerged bodies of revolution, was applied to species that employ pectoral-fin propulsion with a rigid body at U max. An alternative model, based on the results of computer simulations of optimal shape in self-propelled undulating bodies, was applied to the species that swim by body-caudal-fin propulsion at Umax . For pectoral-fin swimmers, Umax increased with fineness, and the rate of increase decreased with fineness, as predicted by the drag model. While the mechanistic and statistical models of the relationship between fineness and Umax were very similar, the mechanistic (and statistical) model explained only a small fraction of the variance in Umax . For body-caudal-fin swimmers, we found a non-linear relationship between fineness and Umax , which was largely negative over most of the range of fineness. This pattern fails to support either predictions from the computational models or standard functional interpretations of body shape variation in fishes. Our results suggest that the widespread hypothesis that a more optimal fineness increases endurance-swimming performance via reduced drag should be limited to fishes that swim with rigid bodies.MEA was partially supported by National Science Foundation Division of Environmental Biology (NSF DEB) grant 0842397 (http://www.nsf.gov/div/ index.jsp?div = DEB). CJF was partially supported by the Australian Research Council (http://www.arc.gov.au/)

Sphagnum physiology in the context of changing climate: emergent influences of genomics, modelling and host-microbiome interactions on understanding ecosystem function.

Peatlands harbour more than one-third of terrestrial carbon leading to the argument that the bryophytes, as major components of peatland ecosystems, store more organic carbon in soils than any other collective plant taxa. Plants of the genus Sphagnum are important components of peatland ecosystems and are potentially vulnerable to changing climatic conditions. However, the response of Sphagnum to rising temperatures, elevated CO2 and shifts in local hydrology have yet to be fully characterized. In this review, we examine Sphagnum biology and ecology and explore the role of this group of keystone species and its associated microbiome in carbon and nitrogen cycling using literature review and model simulations. Several issues are highlighted including the consequences of a variable environment on plant-microbiome interactions, uncertainty associated with CO2 diffusion resistances and the relationship between fixed N and that partitioned to the photosynthetic apparatus. We note that the Sphagnum fallax genome is currently being sequenced and outline potential applications of population-level genomics and corresponding plant photosynthesis and microbial metabolic modelling techniques. We highlight Sphagnum as a model organism to explore ecosystem response to a changing climate and to define the role that Sphagnum can play at the intersection of physiology, genetics and functional genomics

Analysis of full-waveform LiDAR data for classification of an orange orchard scene

Full-waveform laser scanning data acquired with a Riegl LMS-Q560 instrument were used to classify an orange orchard into orange trees, grass and ground using waveform parameters alone. Gaussian decomposition was performed on this data capture from the National Airborne Field Experiment in November 2006 using a custom peak-detection procedure and a trust-region-reflective algorithm for fitting Gauss functions. Calibration was carried out using waveforms returned from a road surface, and the backscattering coefficient c was derived for every waveform peak. The processed data were then analysed according to the number of returns detected within each waveform and classified into three classes based on pulse width and c. For single-peak waveforms the scatterplot of c versus pulse width was used to distinguish between ground, grass and orange trees. In the case of multiple returns, the relationship between first (or first plus middle) and last return c values was used to separate ground from other targets. Refinement of this classification, and further sub-classification into grass and orange trees was performed using the c versus pulse width scatterplots of last returns. In all cases the separation was carried out using a decision tree with empirical relationships between the waveform parameters. Ground points were successfully separated from orange tree points. The most difficult class to separate and verify was grass, but those points in general corresponded well with the grass areas identified in the aerial photography. The overall accuracy reached 91%, using photography and relative elevation as ground truth. The overall accuracy for two classes, orange tree and combined class of grass and ground, yielded 95%. Finally, the backscattering coefficient c of single-peak waveforms was also used to derive reflectance values of the three classes. The reflectance of the orange tree class (0.31) and ground class (0.60) are consistent with published values at the wavelength of the Riegl scanner (1550 nm). The grass class reflectance (0.46) falls in between the other two classes as might be expected, as this class has a mixture of the contributions of both vegetation and ground reflectance properties

A Contribution of the Trivial Connection to Jones Polynomial and Witten's Invariant of 3d Manifolds I

We use the Chern-Simons quantum field theory in order to prove a recently conjectured limitation on the 1/K expansion of the Jones polynomial of a knot and its relation to the Alexander polynomial. This limitation allows us to derive a surgery formula for the loop corrections to the contribution of the trivial connection to Witten's invariant. The 2-loop part of this formula coincides with Walker's surgery formula for Casson-Walker invariant. This proves a conjecture that Casson-Walker invariant is a 2-loop correction to the trivial connection contribution to Witten's invariant of a rational homology sphere. A contribution of the trivial connection to Witten's invariant of a manifold with nontrivial rational homology is calculated for the case of Seifert manifolds.Comment: 28 page

CHP toolkit: case study of LAIe sensitivity to discontinuity of canopy cover in fruit plantations

This paper presents an open-source canopy height profile (CHP) toolkit designed for processing small-footprint full-waveform LiDAR data to obtain the estimates of effective leaf area index (LAIe) and CHPs. The use of the toolkit is presented with a case study of LAIe estimation in discontinuous-canopy fruit plantations. The experiments are carried out in two study areas, namely, orange and almond plantations, with different percentages of canopy cover (48% and 40%, respectively). For comparison, two commonly used discrete-point LAIe estimation methods are also tested. The LiDAR LAIe values are first computed for each of the sites and each method as a whole, providing “apparent” site-level LAIe, which disregards the discontinuity of the plantations’ canopies. Since the toolkit allows for the calculation of the study area LAIe at different spatial scales, between-tree-level clumpingcan be easily accounted for and is then used to illustrate the impact of the discontinuity of canopy cover on LAIe retrieval. The LiDAR LAIe estimates are therefore computed at smaller scales as a mean of LAIe in various grid-cell sizes, providing estimates of “actual” site-level LAIe. Subsequently, the LiDAR LAIe results are compared with theoretical models of “apparent” LAIe versus “actual” LAIe, based on known percent canopy cover in each site. The comparison of those models to LiDAR LAIe derived from the smallest grid-cell sizes against the estimates of LAIe for the whole site has shown that the LAIe estimates obtained from the CHP toolkit provided values that are closest to those of theoretical models