Variance Of Logarithm Research Articles

Heterogeneity of Treatment Effects in Internet- and Mobile-Based Interventions for Depression

While the effects of internet- and mobile-based interventions (IMIs) for depression have been extensively studied, no systematic evidence is available regarding the heterogeneity of treatment effects (HTEs), indicating to what extent patient-by-treatment interactions exist and personalized treatment models might be necessary. To investigate the HTEs in IMIs for depression as well as their efficacy and effectiveness. A systematic search in Embase, MEDLINE, Central, and PsycINFO for randomized clinical trials and supplementary reference searches was conducted on October 13, 2019, and updated March 25, 2022. The search string included various terms related to digital psychotherapy, depression, and randomized clinical trials. Titles, abstracts, and full texts were reviewed by 2 independent researchers. Studies of all populations with at least 1 intervention group receiving an IMI for depression and at least 1 control group were eligible, if they assessed depression severity as a primary outcome and followed a randomized clinical trial (RCT) design. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines. Risk of bias was evaluated using the Cochrane Risk of Bias Tool. HTE was investigated using logarithmic variance ratios (lnVR) and effect sizes using Hedges g. Three-level bayesian meta-regressions were conducted. Heterogeneity of treatment effects was the primary outcome of this study; magnitudes of treatment effect sizes were the secondary outcome. Depression severity was measured by different self-report and clinician-rated scales in the included RCTs. The systematic review of 102 trials included 19 758 participants (mean [SD] age, 39.9 [10.58] years) with moderate depression severity (mean [SD] in Patient Health Questionnaire-9 score, 12.81 [2.93]). No evidence for HTE in IMIs was found (lnVR = -0.02; 95% credible interval [CrI], -0.07 to 0.03). However, HTE was higher in more severe depression levels (β̂ = 0.04; 95% CrI, 0.01 to 0.07). The effect size of IMI was medium (g = -0.56; 95% CrI, -0.46 to -0.66). An interaction effect between guidance and baseline severity was found (β̂ = -0.24, 95% CrI, -0.03 to -0.46). In this systematic review and meta-analysis of RCTs, no evidence for increased patient-by-treatment interaction in IMIs among patients with subthreshold to mild depression was found. Guidance did not increase effect sizes in this subgroup. However, the association of baseline severity with HTE and its interaction with guidance indicates a more sensitive, guided, digital precision approach would benefit individuals with more severe symptoms. Future research in this population is needed to explore personalization strategies and fully exploit the potential of IMI.

Utilizing indicator functions with computational data to confirm nature of overlap in normal turbulent stresses: Logarithmic or quarter-power

Indicator functions of the streamwise normal-stress profiles (NSP), based on careful differentiation of some of the best direct numerical simulations (DNS) data from channel and pipe flows, over the range 550<Reτ<16 000, are examined to establish the existence and range in wall distances of either a logarithmic-trend segment or a 1/4-power region. For nine out of 15 cases of DNS data we examined where Reτ<2000, the NSP did not contain either of the proposed trends. As Reτ exceeds around 2000 a 1/4-power, reflecting the “bounded-dissipation” predictions of Chen and Sreenivasan [“Law of bounded dissipation and its consequences in turbulent wall flows,” J. Fluid Mech. 933, A20 (2022); “Reynolds number asymptotics of wall-turbulence fluctuations,” J. Fluid Mech. 976, A21 (2023)] and data analysis of Monkewitz [“Reynolds number scaling and inner-outer overlap of stream-wise Reynoldss stress in wall turbulence,” arXiv:2307.00612 (2023)], develops near y+=1000 and expands with Reynolds numbers extending to 1000<y+<10 000 for Reτ around 15 000. This range of 1/4-power NSP corresponds to a range of outer-scaled Y between around 0.3 and 0.7. The computational database examined did not include the zero-pressure-gradient boundary layer experiments at higher Reynolds numbers where the logarithmic trend in the NSP has been previously reported around y+ of 1000 by Marusic et al. [“Attached eddy model of wall turbulence,” Annu. Rev. Fluid Mech. 51, 49–74 (2019); “The logarithmic variance of streamwise velocity and conundrum in wall turbulence,” J. Fluid Mech. 933, A8 (2022)] according to a “wall-scaled eddy model.”

Label-free visualization and quantification of the drug-type-dependent response of tumor spheroids by dynamic optical coherence tomography

We demonstrate label-free dynamic optical coherence tomography (D-OCT)-based visualization and quantitative assessment of patterns of tumor spheroid response to three anti-cancer drugs. The study involved treating human breast adenocarcinoma (MCF-7 cell-line) with paclitaxel (PTX), tamoxifen citrate (TAM), and doxorubicin (DOX) at concentrations of 0 (control), 0.1, 1, and 10 µM for 1, 3, and 6 days. In addition, fluorescence microscopy imaging was performed for reference. The D-OCT imaging was performed using a custom-built OCT device. Two algorithms, namely logarithmic intensity variance (LIV) and late OCT correlation decay speed (OCDSl\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_l$$\\end{document}) were used to visualize the tissue dynamics. The spheroids treated with 0.1 and 1 µM TAM appeared similar to the control spheroid, whereas those treated with 10 µM TAM had significant structural corruption and decreasing LIV and OCDSl\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_l$$\\end{document} over treatment time. The spheroids treated with PTX had decreasing volumes and decrease of LIV and OCDSl\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_l$$\\end{document} signals over time at most PTX concentrations. The spheroids treated with DOX had decreasing and increasing volumes over time at DOX concentrations of 1 and 10 µM, respectively. Meanwhile, the LIV and OCDSl\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_l$$\\end{document} signals decreased over treatment time at all DOX concentrations. The D-OCT, particularly OCDSl\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_l$$\\end{document}, patterns were consistent with the fluorescence microscopic patterns. The diversity in the structural and D-OCT results among the drug types and among the concentrations are explained by the mechanisms of the drugs. The presented results suggest that D-OCT is useful for evaluating the difference in the tumor spheroid response to different drugs and it can be a useful tool for anti-cancer drug testing.

Label-free drug response evaluation of human derived tumor spheroids using three-dimensional dynamic optical coherence tomography

This study aims at demonstrating label-free drug-response-patterns assessment of different tumor spheroids and drug types by dynamic optical coherence tomography (D-OCT). The study involved human breast cancer (MCF-7) and colon cancer (HT-29) spheroids. The MCF-7 and HT-29 spheroids were treated with paclitaxel (Taxol; PTX) and the active metabolite of irinotecan SN-38, respectively. The drugs were applied with 0 (control), 0.1, 1, and 10 μM concentrations and the treatment durations were 1, 3, and 6 days. A swept-source OCT microscope equipped with a repeated raster scanning protocol was used to scan the spheroids. Logarithmic intensity variance (LIV) and late OCT correlation decay speed (OCDS_l) algorithms were used to visualize the tumor spheroid dynamics. LIV and OCDS_l images visualized different response patterns of the two types of spheroids. In addition, spheroid morphology, LIV, and OCDS_l quantification showed different time-courses among the spheroid and drug types. These results may indicate different action mechanisms of the drugs. The results showed the feasibility of D-OCT for the evaluation of drug response patterns of different cell spheroids and drug types and suggest that D-OCT can perform anti-cancer drug testing.

Renal tubular function and morphology revealed in kidney without labeling using three-dimensional dynamic optical coherence tomography

Renal tubule has distinct metabolic features and functional activity that may be altered during kidney disease. In this paper, we present label-free functional activity imaging of renal tubule in normal and obstructed mouse kidney models using three-dimensional (3D) dynamic optical coherence tomography (OCT) ex vivo. To create an obstructed kidney model, we ligated the ureter of the left kidney for either 7 or 14 days. Two different dynamic OCT (DOCT) methods were implemented to access the slow and fast activity of the renal tubules: a logarithmic intensity variance (LIV) method and a complex-correlation-based method. Three-dimensional DOCT data were acquired with a 1.3 upmum swept-source OCT system and repeating raster scan protocols. In the normal kidney, the renal tubule appeared as a convoluted pipe-like structure in the DOCT projection image. Such pipe-like structures were not observed in the kidneys subjected to obstruction of the ureter for several days. Instead of any anatomical structures, a superficial high dynamics appearance was observed in the perirenal cortex region of the obstructed kidneys. These findings suggest that volumetric LIV can be used as a tool to investigate kidney function during kidney diseases.

A Two‐Dimensional Closed‐Form Analytical Solution for Heat Transport With Nonvertical Flow in Riparian Zones

AbstractHeat as a tracer has received increasing attention in recent decades and has become a popular and widely used tool for quantifying streambed fluxes, among many other applications. Nonvertical flow component is an important parameter for heat transport in riparian zones. However, previous investigations using heat as a tracer in the quantification of streambed fluxes frequently overlooked or simplified nonvertical flow component with erroneous presumptions. In this study, a novelty two‐dimensional closed‐form analytical solution for heat transport with vertical and nonvertical flow components and arbitrary initial and boundary conditions under losing conditions is presented for the first time using Green's function method. The new model is tested by finite‐element solution and stochastic modeling. The capabilities of the new analytical solution are demonstrated using field data. Results show that the nonvertical flow component has a significant impact on heat transport in streambed. The temperature difference between the streambed and the surface water increases as the nonvertical flow component increases, and the amplitude of the temperature curves decreases with increasing horizontal distance from the center of stream at the same depth due to the influences of nonvertical flow. Stochastic modeling shows that an increasing nonuniform flow can result in overestimation of vertical and nonvertical flow components near the bank of stream, and the new analytical model works well in a heterogeneous streambed when the variance of natural logarithm of the streambed hydraulic conductivity is less than 0.10 (). The vertical and nonvertical flow components are more sensitive to temperature‐time data than the other parameters. The new analytical model is a significant advancement of the previous one‐dimensional analytical models which only considered vertical flow.

Autism Detection in Children using Common Spatial Patterns of MEG Signals.

Autism exhibits a wide range of developmental disabilities and is associated with aberrant anatomical and functional neural patterns. To detect autism in young children (4-7 years) in an automatic and non-invasive fashion, we have recorded magnetoencephalogram (MEG) signals from 30 autistic and 30 age-matched typically developing (TD) children. We have used a machine learning classification framework with common spatial pattern (CSP)-based logarithmic band power (LBP) features. When comparing the LBP feature to the conventional logarithmic variance (LV) spatial pattern, CSP + LBP (92.77%) has performed better than CSP + LV (90.66%) in the 1-100 Hz frequency range for distinguishing autistic children from TD children. In frequency band-wise analysis using our proposed method, the high gamma frequency band (50-100 Hz) has shown the highest classification accuracy (97.14%). Our findings reveal that the occipital lobe exhibits the most distinct spatial pattern in autistic children over the whole frequency range. This study shows that spatial brain activation patterns can be utilized as potential biomarkers of autism in young children. The improved performance signifies the clinical relevance of the work for autism detection using MEG signals.

Predicting ecosystem productivity based on plant community traits.

With the rapid accumulation of plant trait data, major opportunities have arisen for the integration of these data into predicting ecosystem primary productivity across a range of spatial extents. Traditionally, traits have been used to explain physiological productivity at cell, organ, or plant scales, but scaling up to the ecosystem scale has remained challenging. Here, we show the need to combine measures of community-level traits and environmental factors to predict ecosystem productivity at landscape or biogeographic scales. We show how theory can extend the production ecology equation to enormous potential for integrating traits into ecological models that estimate productivity-related ecosystem functions across ecological scales and to anticipate the response of terrestrial ecosystems to global change.

New method for scaling nonpoint source pollution by integrating the SWAT model and IHA-based indicators

Nonpoint source (NPS) pollution shows spatial scaling effects because it is affected by topography, river networks, and many other factors. Currently, the lack of an integrated methodology for quantifying the scaling effect has become a crucial barrier in evaluating NPS pollution. In this study, a new method was proposed for scaling NPS pollution by integrating hydrological model and hydrological alteration indicators. Nested catchments were delineated by eight-direction algorithm, and a semidistributed hydrological model was used to simulate the interannual process within the drainage area and to obtain data series of runoff, sediment, and total phosphorus (TP) at different spatial scales. In addition, the average, the extrema, the change rate and feature variables of each type of indicators were proposed to quantitatively describe the pattern of NPS pollution at different spatial scales. The results show the coefficients of variation (CVs) of most runoff and TP indicators are 0.6–0.8, while those of sediment vary greatly from 0.4 to 1.6 with the threshold of those indicators being 0.33. With the increase in drainage area, the NPS load-related indicators show an increasing trend, while load intensity indicators show a decreasing trend and their changing patterns are affected by the heterogeneity of topographic or hydrological information included. Based on logarithmic variance of the change rate, 825 km2 was identified as the turning point for scaling transformation where the slope changes dramatically. The proposed methodology comprehensively describes features of the NPS scaling effect that could be utilized for targeted monitoring and control of NPS pollution in other watersheds.

Logarithmic Variance for the Height Function of Square-Ice

In this article, we prove that the height function associated with the square-ice model (i.e. the six-vertex model with $$a=b=c=1$$ on the square lattice), or, equivalently, of the uniform random homomorphisms from $$\mathbb {Z}^2$$ to $$\mathbb {Z}$$ , has logarithmic variance. This establishes a strong form of roughness of this height function.

Label-free metabolic imaging of non-alcoholic-fatty-liver-disease (NAFLD) liver by volumetric dynamic optical coherence tomography.

Label-free metabolic imaging of non-alcoholic fatty liver disease (NAFLD) mouse liver is demonstrated ex vivo by dynamic optical coherence tomography (OCT). The NAFLD mouse is a methionine choline-deficient (MCD)-diet model, and two mice fed the MCD diet for 1 and 2 weeks are involved in addition to a normal-diet mouse. The dynamic OCT is based on repeating raster scan and logarithmic intensity variance (LIV) analysis that enables volumetric metabolic imaging with a standard-speed (50,000 A-lines/s) OCT system. Metabolic domains associated with lipid droplet accumulation and inflammation are clearly visualized three-dimensionally. Particularly, the normal-diet liver exhibits highly metabolic vessel-like structures of peri-vascular hepatic zones. The 1-week MCD-diet liver shows ring-shaped highly metabolic structures formed with lipid droplets. The 2-week MCD-diet liver exhibits fragmented vessel-like structures associated with inflammation. These results imply that volumetric LIV imaging is useful for visualizing and assessing NAFLD abnormalities.

The logarithmic variance of streamwise velocity and conundrum in wall turbulence

The logarithmic dependence of streamwise turbulence intensity has been observed repeatedly in recent experimental and direct numerical simulation data. However, its spectral counterpart, a well-developed $k^{-1}$ spectrum ( $k$ is the spatial wavenumber in a wall-parallel direction), has not been convincingly observed from the same data. In the present study, we revisit the spectrum-based attached eddy model of Perry and co-workers, who proposed the emergence of a $k^{-1}$ spectrum in the inviscid limit, for small but finite $z/\delta$ and for finite Reynolds numbers ( $z$ is the wall-normal coordinate, and $\delta$ is the outer length scale). In the upper logarithmic layer (or inertial sublayer), a reexamination reveals that the intensity of the spectrum must vary with the wall-normal location at order of $z/\delta$ , consistent with the early observation argued with ‘incomplete similarity’. The streamwise turbulence intensity is subsequently calculated, demonstrating that the existence of a well-developed $k^{-1}$ spectrum is not a necessary condition for the approximate logarithmic wall-normal dependence of turbulence intensity – a more general condition is the existence of a premultiplied power-spectral intensity of $O(1)$ for $O(1/\delta ) < k < O(1/z)$ . Furthermore, it is shown that the Townsend–Perry constant must be weakly dependent on the Reynolds number. Finally, the analysis is semi-empirically extended to the lower logarithmic layer (or mesolayer), and a near-wall correction for the turbulence intensity is subsequently proposed. All the predictions of the proposed model and the related analyses/assumptions are validated with high-fidelity experimental data (Samie et al., J. Fluid Mech., vol. 851, 2018, pp. 391–415).

On Smooth Mesoscopic Linear Statistics of the Eigenvalues of Random Permutation Matrices

AbstractWe study the limiting behavior of smooth linear statistics of the spectrum of random permutation matrices in the mesoscopic regime, when the permutation follows one of the Ewens measures on the symmetric group. If we apply a smooth enough test function f to all the determinations of the eigenangles of the permutations, we get a convergence in distribution when the order of the permutation tends to infinity. Two distinct kinds of limit appear: if $$f(0)\ne 0$$ f ( 0 ) ≠ 0 , we have a central limit theorem with a logarithmic variance; and if $$f(0) = 0$$ f ( 0 ) = 0 , the convergence holds without normalization and the limit involves a scale-invariant Poisson point process.

Foam Evolution Inspired Modeling for Staged Construction of Ultra-Dense Small Cell Networks

Small cells (SCs) are expected to be ultra-densely deployed in or close to the traffic hot-spots in the fifth generation (5G) mobile networks to provide wireless capacity cost-effectively. Traffic hot-spots change over time, which means SCs cannot be deployed in a one-off manner as macrocells normally do, rather they should be constructed in a staged process. Hence, mathematical models that capture the time-varying staged-construction process, are urgently needed for operators to effectively predict the construction period, but are currently lacking. In this paper, inspired by the foam bursting process-a natural phenomenon that can be observed in daily life such as hand-washing, we first propose a novel model that can predict the time-varying expectation and logarithmic variance of SC coverage areas. Then, we verify the model by real network deployment cases. Additionally, in order to extract parameters from historical base station deployment data, a parameter estimation algorithm is designed and verified. The findings of the paper reveal that mobile operators should construct ultra-dense SC networks in a staged manner like how larger foams split into smaller ones.

Optical coherence tomography-based tissue dynamics imaging for longitudinal and drug response evaluation of tumor spheroids

We present optical coherence tomography (OCT)-based tissue dynamics imaging method to visualize and quantify tissue dynamics such as subcellular motion based on statistical analysis of rapid-time-sequence OCT signals at the same location. The analyses include logarithmic intensity variance (LIV) method and two types of OCT correlation decay speed analysis (OCDS). LIV is sensitive to the magnitude of the signal fluctuations, while OCDSs including early- and late-OCDS (OCDS e and OCDS l , respectively) are sensitive to the fast and slow tissue dynamics, respectively. These methods were able to visualize and quantify the longitudinal necrotic process of a human breast adenocarcinoma spheroid and its anti-cancer drug response. Additionally, the effects of the number of OCT signals and the total acquisition time on dynamics imaging are examined. Small number of OCT signals, e.g., five or nine suffice for dynamics imaging when the total acquisition time is suitably long.

New method for determining the permeability function parameters of soft soils considering synchronous sedimentation and consolidation

The measurement or estimation of the permeability of soft sediments remains a difficult albeit necessary task for several geotechnical applications, such as land reclamation and tailings management. This note presents a new method for determining the two parameters (the multiplier and power) of the power permeability function for high water content sediments, using settlement data from a column experiment, where sedimentation and consolidation occur synchronously. The proposed method stems from the distinct effects of the multiplier and power on the geometric features of numerically predicted settlement curves in the height versus log-time plane. The predicted settlement curves shape is multiplier-independent but controlled by the power; whilst, for a prescribed power, the position of settlement curve depends on the multiplier and can be shifted according to a change in the multiplier without using additional simulation. These effects were recently observed to apply to consolidation analysis only (i.e. without sedimentation), but here are shown to be more general. Further, it is newly shown that the mathematical variance of logarithms of times at a set of random points on the predicted settlement curve correlates very well with the power value. Together, these correlations lead to the development of a new method for calibrating the power and then multiplier that is both accurate and inexpensive (computationally and experimentally), as demonstrated using a well-known case study.

EEG Signal Analysis for Diagnosing Neurological Disorders Using Discrete Wavelet Transform and Intelligent Techniques.

Analysis of electroencephalogram (EEG) signals is essential because it is an efficient method to diagnose neurological brain disorders. In this work, a single system is developed to diagnose one or two neurological diseases at the same time (two-class mode and three-class mode). For this purpose, different EEG feature-extraction and classification techniques are investigated to aid in the accurate diagnosis of neurological brain disorders: epilepsy and autism spectrum disorder (ASD). Two different modes, single-channel and multi-channel, of EEG signals are analyzed for epilepsy and ASD. The independent components analysis (ICA) technique is used to remove the artifacts from EEG dataset. Then, the EEG dataset is segmented and filtered to remove noise and interference using an elliptic band-pass filter. Next, the EEG signal features are extracted from the filtered signal using a discrete wavelet transform (DWT) to decompose the filtered signal to its sub-bands delta, theta, alpha, beta and gamma. Subsequently, five statistical methods are used to extract features from the EEG sub-bands: the logarithmic band power (LBP), standard deviation, variance, kurtosis, and Shannon entropy (SE). Further, the features are fed into four different classifiers, linear discriminant analysis (LDA), support vector machine (SVM), k-nearest neighbor (KNN), and artificial neural networks (ANNs), to classify the features corresponding to their classes. The combination of DWT with SE and LBP produces the highest accuracy among all the classifiers. The overall classification accuracy approaches 99.9% using SVM and 97% using ANN for the three-class single-channel and multi-channel modes, respectively.

Stochastic matrix metapopulation models with fast migration: Re-scaling survival to the fast scale

In this work we address the analysis of discrete-time models of structured metapopulations subject to environmental stochasticity. Previous works on these models made use of the fact that migrations between the patches can be considered fast with respect to demography (maturation, survival, reproduction) in the population. It was assumed that, within each time step of the model, there are many fast migration steps followed by one slow demographic event. This assumption allowed one to apply approximate reduction techniques that eased the model analysis. It is however a questionable issue in some cases since, in particular, individuals can die at any moment of the time step. We propose new non-equivalent models in which we re-scale survival to consider its effect on the fast scale. We propose a more general formulation of the approximate reduction techniques so that they also apply to the proposed new models. We prove that the main asymptotic elements in this kind of stochastic models, the Stochastic Growth Rate (SGR)11Stochastic Growth Rate (SGR). Scaled Logarithmic Variance (SLV). and the Scaled Logarithmic Variance (SLV), can be related between the original and the reduced systems, so that the analysis of the latter allows us to ascertain the population fate in the first. Then we go on to considering some cases where we illustrate the reduction technique and show the differences between both modelling options. In some cases using one option represents exponential growth, whereas the other yields extinction.

Defect Inspection Based on Segmentation and Defective Tracking in Radiographic Image

In this paper, automatic weld defect segmentation into the radiographic image non-destructive evaluation and testing, with orthogonal polynomials transformation-enhancement (OPT-E) is presented. This proposed system defect identification the given defect Radiographic image. In digital radiographic images, the unknown masses appear very light with weak edges, and hence image enhancement technique needs to be applied with transform domain and radiographic images of some illustrative weld deserts invent. The proposed scheme has three phases. In first phase, a radiographic image enhancement technique, which is performed by logarithmic common variance and enhancement factor, computed from the absolute value of the orthogonal polynomials transformation coefficient as principal parameters for increasing the energy of the masses in the digital radiographic image enhancement. In case of successful enhanced of image in addition to gradient estimation scheme is working to point the edges current, in the next phase. The consequential edge image is again applied with orthogonal polynomials. In the final phase, edge tracking are the salient features with angle based defect identification. Experimental is improved quality of images and high relative segmentation by OPT-E.

荒漠植物功能性状及其多样性对土壤水盐变化的响应

PDF HTML阅读 XML下载 导出引用 引用提醒 荒漠植物功能性状及其多样性对土壤水盐变化的响应 DOI: 10.5846/stxb201801300253 作者: 作者单位: 绿洲生态教育部重点实验室,绿洲生态教育部重点实验室,绿洲生态教育部重点实验室,新疆大学资源与环境科学学院,绿洲生态教育部重点实验室 作者简介: 通讯作者: 中图分类号: 基金项目: 新疆维吾尔自治区高校科研计划青年教师科研启动基金（XJEDU2016S026）；国家自然科学基金项目（31700354，31560131） Responses of plant functional trait and diversity to soil water and salinity changes in desert ecosystem Author: Affiliation: Xinjiang University,,,,Key Laboratory of Oasis Ecology, Education Ministry Fund Project: The Scientific Research Startup Foundation for young teachers program in Xinjiang Uygur Autonomous Region University(XJEDU2016S026),The National Natural Science Foundation of China(grant no.31700354, 31500343) 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:植物功能性状及其多样性对环境变化的响应研究有助于揭示极端环境下植物适应策略和群落构建机制。通过实地调查和实验分析，研究艾比湖荒漠植物形态、生理和化学等8个功能性状的特征，并从多维性状和一维性状角度揭示功能多样性对土壤水分和盐分变化的响应规律。结果表明：高水盐环境下（SW1），（1）群落加权株高、叶绿素含量（SPAD）及叶片碳（C）和钙（Ca）含量显著高于低水盐环境，叶片氮（N）、磷（P）、硫（S）含量在不同水盐环境间无显著差异。（2）SW1环境下，沿乔木-小乔木-灌木-草本层次，上层生活型植物性状值普遍高于下层植物，其中灌木叶片仅N、钾（K）含量显著高于草本；沿该生活型层次植物性状呈趋同变化。（3）低水盐环境下（SW2），乔木叶片性状差异特征与SW1相似；小乔木叶片C、N含量分别显著高于和低于灌木及草本；相比于草本，灌木SPAD、S含量显著高，K含量显著低，株高、C、N、P含量差异不显著；SW2环境下各生活型植物性状呈趋同变化。（4）SW1环境下多维功能丰富度、功能离散度显著高于SW2环境，但均匀度无显著差异。（5）一维功能均匀度在不同水盐环境间均无显著差异，但化学性状的均匀度总体高于植物株高；高水盐环境下叶片N、S和Ca的功能分异指数显著高于低水盐环境。研究为掌握胁迫环境下的植物适应策略和荒漠植被恢复提供参考。 Abstract:Exploring the response of plant functional trait to environmental variations is essential to elucidate the adaptation mechanism and community assembly of desert plants under extreme environmental conditions, and more importantly to formulate strategies to protect and restore desert ecosystem. However, previous studies are mostly large scale, and only a few studies have focused on the effects of soil water and salinity on desert plant functional trait and diversity at fine scale. It is known that, even at fine scales, environmental variables (e.g., soil variables) can actually be heterogeneous and affect plant. Therefore, in the present study, we aimed to analyze (1) how morphological, physiological, and chemical functional traits of desert plant, and functional richness, evenness, and dispersion indexes respond to varied soil water and salinity and (2) what community assembly process did functional diversity revealed in different soil water and salinity environment? Three transects were set at 5-km intervals perpendicular to the northern bank of the Aqikesu River in the Ebinur Lake Wetland Nature Reserve (ELWNR). At each transect, the soil gradually changed from saline to sandy soil with the increase in distance from the river. Ten to twelve plots (10×10 m2) were set at an interval of 500 m in each transect. A total of 32 plots were set across the three transects. The geographic data (longitude, latitude, and altitude), number of species, plant abundance (number of individuals of each species), and height of each individual sampled in each plot were recorded. The chlorophyll content (SPAD) was measured by SPAD502, and soil volumetric water content (SVWC) at a depth of 12 cm was measured by time domain reflectometry before sampling. The leaf and soil samples were then collected for further investigation. Based on the investigation and analysis, responses of one morphological (height), one physiological (SPAD) and six chemical functional traits (leaf carbon (C), nitrogen (N), phosphorus (P), sulfur (S), potassium (K), and calcium (Ca) content), and response of multidimensional and single dimensional functional diversities to soil water and salinity were explored. The results showed the following. (1) The community weighted mean height, SPAD, and leaf C and Ca content in high soil water and salinity sites (SW1) were significantly higher than those in low soil water and salinity sites (SW2). The leaf N, P, and S content had no significant differences across the two sites. (2) In SW1 sites, the plant functional trait differences generally decreased along the tree-small tree-shrub-herb life form level, with only leaf N and K content exhibiting significant difference between shrub and herb. Furthermore, plant functional trait showed convergence along the life form level. (3) In SW2 sites, functional trait differences in trees were similar to those in the SW1; the leaf C and N content were significantly higher than those in shrubs and herbs. Furthermore, the SPAD and leaf S content of shrubs were significantly higher than those in herbs, whilst, the leaf K content of shrubs was lower than that in herbs. The height, and leaf C, N, and P content exhibited no significant differences between shrubs and herbs. The plant functional traits among life forms in SW2 site presented a trend of convergence. (4) The multidimensional functional richness (FAD2) and functional divergence (Rao) in SW1 sites were higher than those in SW2 sites, whilst, the functional evenness showed no difference. (5) All single dimensional functional evenness showed no difference between high and low soil water content and salinity; however, functional evenness of chemical trait was generally higher than that of plant height. Furthermore, functional logarithmic variance (FDvar) of leaf N, S, and Ca in SW1 was significantly higher than that of SW2. The study provides references to understand the adaption mechanism of plants subjected to extreme environments and to recover desert plants. 参考文献 相似文献 引证文献