964 resultados para Multiple scales
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A number of methods are available for those researchers considering the addition of molecular analyses of ectomycorrhizal (EcM) fungi to their research projects and weighing the various approaches they might take. Analyzing natural EcM fungal communities has traditionally been a highly skilled, time-consuming process relying heavily on exacting morphological characterization of EcM root tips. Increasingly powerful molecular methods for analyzing EcM communities make this area of research available to a much wider range of researchers. Ecologists can gain from the body of work characterizing EcM while avoiding the requirement for exceptional expertise by carefully combining elements of traditional methods with the more recent molecular approaches. A cursory morphological analysis can yield a traditional quantification of EcM fungi based on tip numbers, a unit with functional and historical significance. Ectomycorrhizal root DNA extracts may then be analyzed with molecular methods widely used for characterizing microbiota. These range from methods applicable only to the simple mixes resulting from careful morphotyping, to community-oriented methods that identify many types in mixed samples as well as provide an estimate of their relative abundances. Extramatrical hyphae in bulk soil can also be more effectively studied, extending characterization of EcM fungal communities beyond the rhizoplane. The trend toward techniques permitting larger sample sets without prohibitive labor and time requirements will also permit us to more frequently address the issues of spatial and temporal variability and better characterize the roles of EcM fungi at multiple scales.
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在黄土丘陵区,地形因素和土壤水分是决定草地景观格局的主要因素,同时草地景观格局在不同尺度上影响着景观中的流。地形因素、土壤水分和草地结构在不同尺度上有着密切的联系,研究它们之间的关系对于了解生态系统的过程十分重要。针对黄土高原异质化的草地群落结构,选取黄土丘陵区经过20多年自然封育形成的天然草地,从坡面尺度对景观格局进行了调查研究,在地形因素、土壤水分和草地结构中选取了有代表性的指标14个,用多元统计分析对选取的指标进行了主成分分析和聚类分析。聚类分析将样方分成3种植被类型,不同植被类型的海拔、坡度、20~140cm土壤含水量以及物种丰富度和生物多样性存在显著性差异。相关分析表明:海拔对0~300cm土壤含水量影响显著;海拔对草地群落盖度,坡位、坡向对草地群落的物种丰富度和生物多样性有着重要影响;而草地群落的物种丰富度和生物多样性与0~100cm土层的含水量关系密切。
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In research field of oil geophysical prospecting, reservoir prediction is refers to forecasting physical properties of petroleum reservoir by using data of seismic and well logging, it is a research which can guide oil field development. Singularities of seismic and logging data are caused by the heterogeneity of reservoir physical property. It's one of important methods that using singularity characteristics of seismic and logging data to study the reservoir physical property in recently. Among them, realization of reservoir quantitative prediction by analyzing singularity of the data and enhancing transition description of data is difficulty in method research. Based on wavelet transform and the fractal theory, the paper studied the singularity judgment criterion for seismic and logging data, not only analyzed quantitative relation between singularity data and reservoir physical property, but also applied it in practical reservoir prediction. The main achievements are: 1. A new method which provides singular points and their strength information estimation at only one single scale is proposed by Herrmann (1999). Based on that, the dissertation proposed modified algorithm which realized singularity polarity detection. 2. The dissertation introduced onset function to generalize the traditional geologic boundaries variations model which used singularity characteristics to represent the abruptness of the lithologic velocity transition. We show that singularity analysis reveals generic singularity information conducted from velocity or acoustic impedance to seismogram based on the convolution seismic-model theory. Theory and applications indicated that singularity information calculated from seismic data was a natural attribute for delineating stratigraphy boundaries due to its excellent ability in detecting detailed geologic features. We demonstrated that singularity analysis was a powerful tool to delineate stratigraphy boundaries and inverse acoustic impedance and velocity. 3. The geologic significances of logging data singularity information were also presented. According to our analysis, the positions of singularities indicate the sequence stratigraphic boundary, and there is subtle relationship between the singularity strength and sedimentary environment, meanwhile the singularity polarity used to recognize stratigraphic base-level cycle. Based on all those above, a new method which provided sedimentary cycle analysis based on the singularity information of logging data in multiple scales was proposed in this dissertation. This method provided a quantitative tool for judging interface of stratum sequence and achieved good results in the actual application.
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This thesis describes a new representation for two-dimensional round regions called Local Rotational Symmetries. Local Rotational Symmetries are intended as a companion to Brady's Smoothed Local Symmetry Representation for elongated shapes. An algorithm for computing Local Rotational Symmetry representations at multiple scales of resolution has been implemented and results of this implementation are presented. These results suggest that Local Rotational Symmetries provide a more robustly computable and perceptually accurate description of round regions than previous proposed representations. In the course of developing this representation, it has been necessary to modify the way both Smoothed Local Symmetries and Local Rotational Symmetries are computed. First, grey-scale image smoothing proves to be better than boundary smoothing for creating representations at multiple scales of resolution, because it is more robust and it allows qualitative changes in representations between scales. Secondly, it is proposed that shape representations at different scales of resolution be explicitly related, so that information can be passed between scales and computation at each scale can be kept local. Such a model for multi-scale computation is desirable both to allow efficient computation and to accurately model human perceptions.
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Joern Fischer, David B. Lindermayer, and Ioan Fazey (2004). Appreciating Ecological Complexity: Habitat Contours as a Conceptual Landscape Model. Conservation Biology, 18 (5)pp.1245-1253 RAE2008
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How do humans rapidly recognize a scene? How can neural models capture this biological competence to achieve state-of-the-art scene classification? The ARTSCENE neural system classifies natural scene photographs by using multiple spatial scales to efficiently accumulate evidence for gist and texture. ARTSCENE embodies a coarse-to-fine Texture Size Ranking Principle whereby spatial attention processes multiple scales of scenic information, ranging from global gist to local properties of textures. The model can incrementally learn and predict scene identity by gist information alone and can improve performance through selective attention to scenic textures of progressively smaller size. ARTSCENE discriminates 4 landscape scene categories (coast, forest, mountain and countryside) with up to 91.58% correct on a test set, outperforms alternative models in the literature which use biologically implausible computations, and outperforms component systems that use either gist or texture information alone. Model simulations also show that adjacent textures form higher-order features that are also informative for scene recognition.
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Grid cells in the dorsal segment of the medial entorhinal cortex (dMEC) show remarkable hexagonal activity patterns, at multiple spatial scales, during spatial navigation. How these hexagonal patterns arise has excited intense interest. It has previously been shown how a selforganizing map can convert firing patterns across entorhinal grid cells into hippocampal place cells that are capable of representing much larger spatial scales. Can grid cell firing fields also arise during navigation through learning within a self-organizing map? A neural model is proposed that converts path integration signals into hexagonal grid cell patterns of multiple scales. This GRID model creates only grid cell patterns with the observed hexagonal structure, predicts how these hexagonal patterns can be learned from experience, and can process biologically plausible neural input and output signals during navigation. These results support a unified computational framework for explaining how entorhinal-hippocampal interactions support spatial navigation.
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Claims of injustice in global forest governance are prolific: assertions of colonization, marginalization and disenfranchisement of forest-dependent people, and privatization of common resources are some of the most severe allegations of injustice resulting from globally-driven forest conservation initiatives. At its core, the debate over the future of the world's forests is fraught with ethical concerns. Policy makers are not only deciding how forests should be governed, but also who will be winners, losers, and who should have a voice in the decision-making processes. For 30 years, policy makers have sought to redress the concerns of the world's 1.6 billion forest-dependent poor by introducing rights-based and participatory approaches to conservation. Despite these efforts, however, claims of injustice persist. This research examines possible explanations for continued claims of injustice by asking: What are the barriers to delivering justice to forest-dependent communities? Using data collected through surveys, interviews, and collaborative event ethnography in Laos and at the Tenth Conference of Parties to the Convention on Biological Diversity, this dissertation examines the pursuit of justice in global forest governance across multiple scales of governance. The findings reveal that particular conceptualizations of justice have become a central part of the metanormative fabric of global environmental governance, inhibiting institutional evolution and therewith perpetuating the justice gap in global forest governance.
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New representations of tree-structured data objects, using ideas from topological data analysis, enable improved statistical analyses of a population of brain artery trees. A number of representations of each data tree arise from persistence diagrams that quantify branching and looping of vessels at multiple scales. Novel approaches to the statistical analysis, through various summaries of the persistence diagrams, lead to heightened correlations with covariates such as age and sex, relative to earlier analyses of this data set. The correlation with age continues to be significant even after controlling for correlations from earlier significant summaries.
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Movements of wide-ranging top predators can now be studied effectively using satellite and archival telemetry. However, the motivations underlying movements remain difficult to determine because trajectories are seldom related to key biological gradients, such as changing prey distributions. Here, we use a dynamic prey landscape of zooplankton biomass in the north-east Atlantic Ocean to examine active habitat selection in the plankton-feeding basking shark Cetorhinus maximus. The relative success of shark searches across this landscape was examined by comparing prey biomass encountered by sharks with encounters by random-walk simulations of ‘model’ sharks. Movements of transmitter-tagged sharks monitored for 964 days (16754km estimated minimum distance) were concentrated on the European continental shelf in areas characterized by high seasonal productivity and complex prey distributions. We show movements by adult and sub-adult sharks yielded consistently higher prey encounter rates than 90% of random-walk simulations. Behavioural patterns were consistent with basking sharks using search tactics structured across multiple scales to exploit the richest prey areas available in preferred habitats. Simple behavioural rules based on learned responses to previously encountered prey distributions may explain the high performances. This study highlights how dynamic prey landscapes enable active habitat selection in large predators to be investigated from a trophic perspective, an approach that may inform conservation by identifying critical habitat of vulnerable species.
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Largely used as a natural biological tag in studies of dispersal/connectivity of fish, otolith elemental fingerprinting is usually analyzed by laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS). LA-ICP-MS produces an elemental fingerprint at a discrete time-point in the life of a fish and can generate data on within-otolith variability of that fingerprint. The presence of within-otolith variability has been previously acknowledged but not incorporated into experimental designs on the presumed, but untested, grounds of both its negligibility compared to among-otolith variability and of spatial autocorrelation among multiple ablations within an otolith. Here, using a hierarchical sampling design of spatial variation at multiple scales in otolith chemical fingerprints for two Mediterranean coastal fishes, we explore: 1) whether multiple ablations within an otolith can be used as independent replicates for significance tests among otoliths, and 2) the implications of incorporating within-otolith variability when assessing spatial variability in otolith chemistry at a hierarchy of spatial scales (different fish, from different sites, at different locations on the Apulian Adriatic coast). We find that multiple ablations along the same daily rings do not necessarily exhibit spatial dependency within the otolith and can be used to estimate residual variability in a hierarchical sampling design. Inclusion of within-otolith measurements reveals that individuals at the same site can show significant variability in elemental uptake. Within-otolith variability examined across the spatial hierarchy identifies differences between the two fish species investigated, and this finding leads to discussion of the potential for within-otolith variability to be used as a marker for fish exposure to stressful conditions. We also demonstrate that a 'cost'-optimal allocation of sampling effort should typically include some level of within-otolith replication in the experimental design. Our findings provide novel evidence to aid the design of future sampling programs and improve our general understanding of the mechanisms regulating elemental fingerprints.
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The nonlinear propagation of finite amplitude ion acoustic solitary waves in a plasma consisting of adiabatic warm ions, nonisothermal electrons, and a weakly relativistic electron beam is studied via a two-fluid model. A multiple scales technique is employed to investigate the nonlinear regime. The existence of the electron beam gives rise to four linear ion acoustic modes, which propagate at different phase speeds. The numerical analysis shows that the propagation speed of two of these modes may become complex-valued (i.e., waves cannot occur) under conditions which depend on values of the beam-to-background-electron density ratio , the ion-to-free-electron temperature ratio , and the electron beam velocity v0; the remaining two modes remain real in all cases. The basic set of fluid equations are reduced to a Schamel-type equation and a linear inhomogeneous equation for the first and second-order potential perturbations, respectively. Stationary solutions of the coupled equations are derived using a renormalization method. Higher-order nonlinearity is thus shown to modify the solitary wave amplitude and may also deform its shape, even possibly transforming a simple pulse into a W-type curve for one of the modes. The dependence of the excitation amplitude and of the higher-order nonlinearity potential correction on the parameters , , and v0 is numerically investigated.
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The nonlinear propagation of amplitude-modulated electrostatic wavepackets in an electron-positron-ion (e-p-i) plasma is considered, by employing a two-fluid plasma model. Considering propagation parallel to the external magnetic field, two distinct electrostatic modes are obtained, namely a quasi-thermal acoustic-like lower mode and a Langmuir-like optic-type upper one. These results equally apply in warm pair ion ( e. g. fullerene) plasmas contaminated by a small fraction of stationary ions ( or dust), in agreement with experimental observations and theoretical predictions in pair plasmas. Considering small yet weakly nonlinear deviations from equilibrium, and adopting a multiple-scales perturbation technique, the basic set of model equations is reduced to a nonlinear Schrodinger (NLS) equation for the slowly varying electric field perturbation amplitude. The analysis reveals that the lower ( acoustic) mode is mostly stable for large wavelengths, and may propagate in the form of a dark-type envelope soliton ( a void) modulating a carrier wavepacket, while the upper linear mode is intrinsically unstable, and thus favours the formation of bright-type envelope soliton ( pulse) modulated wavepackets. The stability ( instability) range for the acoustic ( Langmuir-like optic) mode shifts to larger wavenumbers as the positive-to-negative ion temperature ( density) ratio increases. These results may be of relevance in astrophysical contexts, where e-p-i plasmas are encountered, and may also serve as prediction of the behaviour of doped ( or dust-contaminated) fullerene plasmas, in the laboratory.
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The nonlinear amplitude modulation of electromagnetic waves propagating in pair plasmas, e.g., electron-positron or fullerene pair-ion plasmas, as well as three-component pair plasmas, e.g., electron-positron-ion plasmas or doped (dusty) fullerene pair-ion plasmas, assuming wave propagation in a direction perpendicular to the ambient magnetic field, obeying the ordinary (O-) mode dispersion characteristics. Adopting a multiple scales (reductive perturbation) technique, a nonlinear Schrodinger-type equation is shown to govern the modulated amplitude of the magnetic field (perturbation). The conditions for modulation instability are investigated, in terms of relevant parameters. It is shown that localized envelope modes (envelope solitons) occur, of the bright- (dark-) type envelope solitons, i.e., envelope pulses (holes, respectively), for frequencies below (above) an explicit threshold. Long wavelength waves with frequency near the effective pair plasma frequency are therefore unstable, and may evolve into bright solitons, while higher frequency (shorter wavelength) waves are stable, and may propagate as envelope holes.(c) 2007 American Institute of Physics.
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The reductive perturbation technique is employed to investigate the modulational instability of dust-acoustic (DA) waves propagating in a four-component dusty plasma. The dusty plasma consists of both positive- and negative-charge dust grains, characterized by a different mass, temperature and density, in addition to a background of Maxwellian electrons and ions. Relying on a multi-fluid plasma model and employing a multiple scales technique, a nonlinear Schrodinger type equation (NLSE) is obtained for the electric potential amplitude perturbation. The occurrence of localized electrostatic wavepackets is shown, in the form of oscillating structures whose modulated envelope is modelled as a soliton (or multi-soliton) solution of the NLSE. The DA wave characteristics, as well as the associated stability thresholds, are studied analytically and numerically. The relevance of these theoretical results with dusty plasmas observed in cosmic and laboratory environments is analysed in detail, by considering realistic multi-component plasma configurations observed in the polar mesosphere, as well as in laboratory experiments.