ALBERT

Description: Abstract Inverse methods involving compressive sensing are tested in the application of two‐dimensional aperture‐synthesis imaging of radar backscatter from field‐aligned plasma density irregularities in the ionosphere. We consider basis pursuit denoising, implemented with the fast iterative shrinkage thresholding algorithm, and orthogonal matching pursuit (OMP) with a wavelet basis in the evaluation. These methods are compared with two more conventional optimization methods rooted in entropy maximization (MaxENT) and adaptive beamforming (linearly constrained minimum variance or often “Capon's Method.”) Synthetic data corresponding to an extended ionospheric radar target are considered. We find that MaxENT outperforms the other methods in terms of its ability to recover imagery of an extended target with broad dynamic range. Fast iterative shrinkage thresholding algorithm performs reasonably well but does not reproduce the full dynamic range of the target. It is also the most computationally expensive of the methods tested. OMP is very fast computationally but prone to a high degree of clutter in this application. We also point out that the formulation of MaxENT used here is very similar to OMP in some respects, the difference being that the former reconstructs the logarithm of the image rather than the image itself from basis vectors extracted from the observation matrix. MaxENT could in that regard be considered a form of compressive sensing.

Description: Individual tree growth and yield models precisely describe tree growth irrespective of stand complexity and are capable of simulating various silvicultural alternatives in the stands with diverse structure, species composition, and management history. We developed both age dependent and age independent diameter increment models using long-term research sample plot data collected from both monospecific and mixed stands of European beech (Fagus sylvatica L.) in the Slovak Republic. We used diameter at breast height (DBH) as a main predictor and other characteristics describing site quality (site index), stand development stage (dominant height and stand age), stand density or competition (ratio of individual tree DBH to quadratic mean diameter), species mixture (basal area proportion of a species of interest), and dummy variable describing stand management regimes as covariate predictors to develop the models. We evaluated eight versatile growth functions in the first stage using DBH as a single predictor and selected the most suitable one, i.e., Chapman-Richards function for further analysis through the inclusion of covariate predictors. We introduced the random components describing sample plot-level random effects and stochastic variations on the diameter increment, into the models through the mixed-effects modelling. The autocorrelation caused by hierarchical data-structure, which is assumed to be partially reduced by mixed-effects modelling, was removed through the inclusion of the parameter accounting for the autoregressive error-structures. The models described about two-third parts of a total variation in the diameter increment without significant trends in the residuals. Compared to the age independent mixed-effects model (conditional coefficient of determination, R c 2 = 0.6566; root mean square error, RMSE = 0.1196), the age dependent model described a significantly larger proportion of the variations in diameter increment ( R c 2 = 0.6796, RMSE = 0.1141). Diameter increment was significantly influenced differently by covariate predictors included into the models. Diameter increment decreased with the advancement of stand development stage (increased dominant height and stand age), increasing intraspecific competition (increased basal area proportion of European beech per sample plot), and diameter increment increased with increasing site quality (increased site index) and decreased competition (increased ratio of DBH to quadratic mean diameter). Our mixed-effects models, which can be easily localized with the random effects estimated from prior measurement of diameter increments of four randomly selected trees per sample plot, will provide high prediction accuracies. Our models may be used for simulating growth of European beech irrespective of its stand structural complexity, as these models have included various covariate variables describing both tree-and stand-level characteristics, thinning regimes, except the climate characteristics. Together with other forest models, our models will be used as inputs to the growth simulator to be developed in the future, which is important for decision-making in forestry.

Description: The objective of this study was to develop the models that predict both timber and branch volumes of Norway spruce (Picea abies/L./Karst.), the most abundant tree species in Europe, and determine the relationships among timber and branch volumes and various site and stand characteristics. The data used in this study come from 76 sample plots in the different stands and site conditions across Norway spruce forests in the Czech Republic. Timber volume was determined by Huber’s formula and branch volume (logging residue) was determined by drying and weighing of 10 samples from the 10-chipped trees on each sample plot, meaning that a total of 760 samples were analyzed. The results showed that timber volume was significantly positively correlated with branch volume, mean diameter at breast height (mean DBH) per sample plot, mean height per sample plot, slope of sample plot, and stand age, but negatively correlated with stand stocking. The branch volume was more significantly affected by stand stocking than timber volume. The timber-to-branch volume ratio (TBR) reached the mean value of 3.7 (±0.14 SE) and significantly increased with increasing elevation. The trees on the nutrient-rich sites were characterized by higher branch volume, while TBR reached higher values on the acid sites. Site quality class had a significant effect only on the branch volume production. Compared to the timber volume (root mean square error, RMSE = 3.6176; adjusted coefficient of determination, R2adj = 0.7310), the branch volume was relatively poorly described by the model (RMSE = 1.928; R2adj = 0.2517). The volume prediction models show that timber volumes increase with increasing slope and branch volume increases with decreasing site quality class. For effective forest management practice, the highest branch volume in favor of timber production is characterized for lowland forests with stand stocking ≤60% (TBR 1.5), while the highest share of timber volume (TBR 9.5) can be reached in the mountains with a full stand stocking.

Description: Abstract Kinetic Alfvén wave (KAW) and whistler wave play a key role in the framework of turbulence and reconnection. There are lot of observations of these wave in the magnetopause region. The present paper deals with the nonlinear evolution of KAW and a weak whistler wave through the pre‐existing magnetic reconnection site. For this study the dynamical evolution equations are derived by taking into account the ponderomotive force driven density modification and magnetic field fluctuations due to shear field modelled by the Harris sheet. Furthermore, these equations have been solved numerically as well as semi‐analytically. For numerical integrations we have used the pseudospectral method and finite difference method and for semi‐analytically Runge Kutta method. Simulated results have shown the evolution of coherent structures or current sheets, which are capable to energy transfer efficiently. These structures have scale size around ion gyroradius as well as electron inertial length as calculated analytically. At a later time the chaotic structures arise in this reconnection site. This gives the signature of turbulence generation. Therefore, the magnetic power spectrum with scaling is also presented in this manuscript and their relevance with the observed spectrum (calculated from the cluster data (Chaston 2008)) is also pointed out.

Description: Height-to-diameter at breast height (DBH) ratio (HDR) is an important tree and stand stability measure. Several factors such as stand dynamics, natural and anthropogenic disturbances, and silvicultural tending significantly affect HDR, and, therefore, in-depth investigation of HDR is essential for better understanding of ecological processes in a forest. A nonlinear mixed-effects HDR model applicable to several tree species was developed using the Czech national forest inventory data comprising 13,875 sample plots and 348,980 trees. The predictive performance of this model was evaluated using the independent dataset which was originated from 25,146 trees on 220 research sample plots. Among various tree- and stand-level variables describing tree size, site quality, stand development stage, stand density, inter-tree spacing, and competition evaluated, dominant height (HDOM), dominant diameter (DDOM), relative spacing index (RS), and DBH-to-quadratic mean DBH ratio (dq) were identified as the most important predictors of HDR variations. A random component describing sample plot-specific HDR variations was included through mixed-effects modelling, and dummy variables describing species-specific HDR variations and canopy layer-specific HDR variations were also included into the HDR model through dummy variable modelling. The mixed-effects HDR model explained 79% of HDR variations without any significant trends in the residuals. Simulation results showed that HDR for each canopy layer increased with increasing site quality and stand development stage (increased HDOM) and increasing competition (increased RS, decreased DDOM and dq). Testing the HDR model on the independent data revealed that more than 85% of HDR variations were described for each individual species (Norway spruce, Scots pine, European larch, and European beech) and group of species (fir species, oak species, birch and alder species) without significant trends in the prediction errors. The HDR can be predicted with a higher accuracy using the calibrated mixed-effects HDR model from measurements of its predictors that can be obtained from routine forest inventories. To improve the prediction accuracy, a model needs to be calibrated with the random effects estimated using one to four randomly selected trees of a particular species or group of species depending on the availability of their numbers per sample plot. The HDR model can be applied for stand stability assessment and stand density regulation. The HDR information is also useful for designing a stand density management diagram. Brief implications of the HDR model for designing silviculture strategies and forest management planning are presented in the article.

Description: 〈p〉Coexistence of reversible polar distortions and metallicity leading to a ferroelectric metal, first suggested by Anderson and Blount in 1965, has so far remained elusive. Electrically switchable intrinsic electric polarization, together with the direct observation of ferroelectric domains, has not yet been realized in a bulk crystalline metal, although incomplete screening by mobile conduction charges should, in principle, be possible. Here, we provide evidence that native metallicity and ferroelectricity coexist in bulk crystalline van der Waals WTe〈sub〉2〈/sub〉 by means of electrical transport, nanoscale piezoresponse measurements, and first-principles calculations. We show that, despite being a Weyl semimetal, WTe〈sub〉2〈/sub〉 has switchable spontaneous polarization and a natural ferroelectric domain structure at room temperature. This new class of materials has tantalizing potential for functional nanoelectronics applications.〈/p〉