尺度分析对景观格局指标的影响

采用优势规则和随机规则为基础的两种尺度分析方法,对分类的TM数据进行了尺度变换分析。结果表明,随着尺度(粒度)增加,优势规则处理法使景观中优势类型的面积增加,非优势类型的面积减少,随机规则处理法使各景观类型的面积基本上保持不变,随尺度变大,整个景观和多数类型的最大斑块面积指标增加;最小斑块面积等于尺度大小的平方;平均斑块面积都增加;斑块数迅速减少,在优势规则系列中,多样性指标减小,而在随机规则处理中,基本没有变化,聚集度随尺度的增大而减小,但测量尺度固定的情况下,随图分辨率的提高而增大,随尺度的增加,Moran’s Ⅰ指标减小,景观类型在空间上趋于随机分布,但是测量尺度固定的情况下,随图分辨率的提高而增大,景观类型在空间上趋于聚集分布。     

Sensitivity of landscape measurements to changing grain size for fine-scale design and management

Landscape pattern quantities are affected by issues of scale, namely extent and resolution. The grain size (resolution) of fine-resolution geographic information system (GIS) data for two highly fragmented landscapes in USA and Italy were altered to evaluate the effect of grain size changes on landscape pattern metrics and cost-surface model outputs. Beginning with 3 m resolution data and resampling the data to 300 m resolution, we applied pattern metrics and cost-surface models (available in GIS software) and evaluated the types of behaviors in resulting quantities. Results showed that some pattern metrics are robust to changes in grain size (such as area, cohesion, interspersion and juxtaposition metrics), while others exhibit staircase-like or erratic responses. Compared to previous studies, we identified behavioral responses that differ from grain-size changes at coarser resolutions. Cost-surface models demonstrated robust or consistent responses to grain size changes in most cases. For both types of pattern measurement, however, we found that behaviors could differ contextually; that is, there could be different types of behaviors for different landscapes, classifications, or grain sizes. Results indicate that comparing spatial data collected at different scales (such as historical data to more recent, high-resolution sensed data) is complicated by different types of responses to changes in grain size. This may limit the applicability of tools for the measurement of landscape change over time if landscapes are represented by differently scaled data.     

Morphological features of mucous secretory organ and mucous secretion of loach Misgurnus anguillicaudatus skin for friction drag reduction

We examined the functional morphology of loach Misgurnus anguillicaudatus skin by using synchrotron X-ray micro-computed tomography (SR-μCT) and high-contrast staining using osmium tetroxide or phosphotungstic acid (PTA), which enhances the image contrast of soft tissues. The captured high-spatial resolution images revealed that the surface ornamentations were stuck in the basement membrane of the loach scales. The ornamentations consisting of grooves (radii) and ridges (circuli) that can move freely and bend flexibly. The cross-sectional lateral microstructures of flat, concave and convex loach skins were observed from a live image of loach skin obtained through dark-field optical coherence tomography (OCT) imaging. The thickness of loach skin was changed with varying empty space between the mucous-cell layer and the scales by bending motion of loach. In addition, through direct measurement of drag reduction of loach skin, the mucous layer was found to have a strong influence on the reduction of skin friction. The present results enhance the understanding of the functional morphologies of mucous layer of loach to secrete mucus for skin friction reduction.     

Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy

Localization-based super resolution microscopy can be applied to obtain a spatial map (image) of the distribution of individual fluorescently labeled single molecules within a sample with a spatial resolution of tens of nanometers. Using either photoactivatable (PAFP) or photoswitchable (PSFP) fluorescent proteins fused to proteins of interest, or organic dyes conjugated to antibodies or other molecules of interest, fluorescence photoactivation localization microscopy (FPALM) can simultaneously image multiple species of molecules within single cells. By using the following approach, populations of large numbers (thousands to hundreds of thousands) of individual molecules are imaged in single cells and localized with a precision of ~10-30 nm. Data obtained can be applied to understanding the nanoscale spatial distributions of multiple protein types within a cell. One primary advantage of this technique is the dramatic increase in spatial resolution: while diffraction limits resolution to ~200-250 nm in conventional light microscopy, FPALM can image length scales more than an order of magnitude smaller. As many biological hypotheses concern the spatial relationships among different biomolecules, the improved resolution of FPALM can provide insight into questions of cellular organization which have previously been inaccessible to conventional fluorescence microscopy. In addition to detailing the methods for sample preparation and data acquisition, we here describe the optical setup for FPALM. One additional consideration for researchers wishing to do super-resolution microscopy is cost: in-house setups are significantly cheaper than most commercially available imaging machines. Limitations of this technique include the need for optimizing the labeling of molecules of interest within cell samples, and the need for post-processing software to visualize results. We here describe the use of PAFP and PSFP expression to image two protein species in fixed cells. Extension of the technique to living cells is also described.     

自适应指数加权互信息配准医学图像的测度及相应算法

为配准医学图像,本文提出了一种新的自适应指数加权的互信息(Adaptive Exponential Weighted Mutual Informa- tion,AEWMI)测度,分析表明:通过对互信息(Mutual Information,MI)测度进行指数加权可以提高测度曲线的峰值尖锐性和平滑性;而指数的权值则可以通过评估待配准图像的质量和分辨率大小来自适应确定。仿真实验结果在验证分析结果的同时也表明,基于本文AEWMI测度的配准方案,对图像噪声、分辨率差异等有较高的鲁棒性,且可有效地提高配准的成功率。     

基于不同空间尺度遥感影像估算森林叶面积指数的差异

地面测量点对遥感像元的代表性如何,怎样获取像元的相对真值,多大的空间分辨率可以真实地反映森林区域的叶面积指数(LAI),这些都是定量遥感中的重要问题.本研究计算LAI-2200和TRAC两种冠层分析仪测量的空间范围,并结合GF-2(4.1 m)、Sentinel-2(10 m)、Landsat-8(30 m)3种不同空间分辨率遥感影像,找到各尺度下像元的相对真值,在保持真值观测面积和遥感获取面积一致的条件下,基于一元指数和多元回归模型,对比分析不同空间分辨率影像对估算森林LAI的影响,并对3种影像模型进行30和100 m尺度下的检验以及各自数据集的空间代表性评价,比较得出最适合表达研究区域森林LAI的尺度.结果表明:对于森林来说,高分辨率并不一定能充分反映森林LAI.基于3种分辨率影像的统计模型都能很好地估测森林LAI,其中,基于Sentinel-2的反演精度最高,基于GF-2的反演精度最低.30和100 m尺度下的检验结果表明,基于GF-2反演模型高估了森林LAI,基于Landsat-8的反演模型低估了森林LAI,基于Sentinel-2分辨率的统计模型可以很好地估测研究区域森林LAI.     

Investigations of fine-scale phylogeography in Tigriopus californicus reveal historical patterns of population divergence

Background  

The intertidal copepod Tigriopus californicus is a model for studying the process of genetic divergence in allopatry and for probing the nature of genetic changes that lead to reproductive isolation. Although previous studies have revealed a pattern of remarkably high levels of genetic divergence between the populations of this species at several spatial scales, it is not clear what types of historical processes are responsible. Particularly lacking are data that can yield insights into population history from the finest scales of geographic resolution.     

Vegetation condition assessment and monitoring from sequences of satellite imagery

Summary   Vegetation changes over time are important indicators of condition, and are particularly important as targets or triggers for management. Satellite image data have unique capacities to provide information on changes in vegetation. In particular, Landsat imagery has the spatial resolution and a historical archive that make it relevant to providing information for understanding and management of native vegetation at a range of scales from small remnant to region. Regional and national vegetation monitoring programs based on time series Landsat imagery are now operational in Australia. These programs and their data have huge potential to provide information for conservation and natural resource management questions. They have already found multiple applications, including applications to biodiversity assessment and planning. This paper presents some examples of the delivery and application of satellite image monitoring information in the context of vegetation management.     

Nanoscale Imaging of Caveolin-1 Membrane Domains In Vivo

Light microscopy enables noninvasive imaging of fluorescent species in biological specimens, but resolution is generally limited by diffraction to ~200–250 nm. Many biological processes occur on smaller length scales, highlighting the importance of techniques that can image below the diffraction limit and provide valuable single-molecule information. In recent years, imaging techniques have been developed which can achieve resolution below the diffraction limit. Utilizing one such technique, fluorescence photoactivation localization microscopy (FPALM), we demonstrated its ability to construct super-resolution images from single molecules in a living zebrafish embryo, expanding the realm of previous super-resolution imaging to a living vertebrate organism. We imaged caveolin-1 in vivo, in living zebrafish embryos. Our results demonstrate the successful image acquisition of super-resolution images in a living vertebrate organism, opening several opportunities to answer more dynamic biological questions in vivo at the previously inaccessible nanoscale.     

VSDI: a new era in functional imaging of cortical dynamics

During the last few decades, neuroscientists have benefited from the emergence of many powerful functional imaging techniques that cover broad spatial and temporal scales. We can now image single molecules controlling cell differentiation, growth and death; single cells and their neurites processing electrical inputs and sending outputs; neuronal circuits performing neural computations in vitro; and the intact brain. At present, imaging based on voltage-sensitive dyes (VSDI) offers the highest spatial and temporal resolution for imaging neocortical functions in the living brain, and has paved the way for a new era in the functional imaging of cortical dynamics. It has facilitated the exploration of fundamental mechanisms that underlie neocortical development, function and plasticity at the fundamental level of the cortical column.     

In vivo micro particle image velocimetry measurements of blood-plasma in the embryonic avian heart

The measurement of blood-plasma velocity distributions with spatial and temporal resolution in vivo is inevitable for the determination of shear stress distributions in complex geometries at unsteady flow conditions like in the beating heart. A non-intrusive, whole-field velocity measurement technique is required that is capable of measuring instantaneous flow fields at sub-millimeter scales in highly unsteady flows. Micro particle image velocimetry (muPIV) meets these demands, but requires special consideration and methodologies in order to be utilized for in vivo studies in medical and biological research. We adapt muPIV to measure the blood-plasma velocity in the beating heart of a chicken embryo. In the current work, bio-inert, fluorescent liposomes with a nominal diameter of 400 nm are added to the flow as a tracer. Because of their small dimension and neutral buoyancy the liposomes closely follow the movement of the blood-plasma and allow the determination of the velocity gradient close to the wall. The measurements quantitatively resolve the velocity distribution in the developing ventricle and atrium of the embryo at nine different stages within the cardiac cycle. Up to 400 velocity vectors per measurement give detailed insight into the fluid dynamics of the primitive beating heart. A rapid peristaltic contraction accelerates the flow to peak velocities of 26 mm/s, with the velocity distribution showing a distinct asymmetrical profile in the highly curved section of the outflow tract. In relation to earlier published gene-expression experiments, the results underline the significance of fluid forces for embryonic cardiogenesis. In general, the measurements demonstrate that muPIV has the potential to develop into a general tool for instationary flow conditions in complex flow geometries encountered in cardiovascular research.     

Classification of Pinus massoniana and secondary deciduous tree species in northern subtropical region based on high resolution and hyperspectral remotely sensed data

Aims Using remote sensing data for tree species classification plays a key role in forestry resource monitoring, sustainable forest management and biodiversity research.Methods This study used integrated sensor LiCHy (LiDAR, CCD and Hyperspectral) to obtain both the high resolution imagery and the hyperspectral data at the same time for the natural secondary forest in south Jiangsu hilly region. The data were used to identify the crown and to classify tree species at multiple levels. Firstly, tree crowns were selected by segmenting high-resolution imagery at multiple scales based on edge detection; secondly, characteristic variables of hyperspectral images were extracted, then optimization variables were selected based on the theory of information entropy. Tree species and forest types were classified using either all characteristic variables or optimization variables only. Finally, tree species and forest types were reclassified along with the tree crowns information, and the accuracy of classification was discussed. Important findings Based on all available characteristic variables, the overall accuracy for four typical tree species classification was 64.6%, and the Kappa coefficient was 0.493. The overall accuracy for forest types classification was 81.1%, and the Kappa coefficient was 0.584. Based on optimization variables only, the overall accuracy for four typical tree species classification dropped to 62.9%, and the Kappa coefficient was 0.459. The overall accuracy for forest types classification was 77.7%, and the Kappa coefficient was 0.525. Obtaining both high resolution image and hyperspectral data at the same time by integrated sensor can increase overall accuracy in classifying forest types and tree species in northern subtropical forest.     

基于高分辨率与高光谱遥感影像的北亚热带马尾松及次生落叶树种的分类

利用遥感数据开展森林资源树种的分类对森林资源的监测、森林可持续经营及生物多样性研究都有重要意义。该文以江苏南部丘陵地区的北亚热带天然次生林为研究对象, 利用LiCHy (LiDAR、CCD、Hyperspectral)集成传感器同期获取的高分辨率和高光谱数据, 进行冠幅识别和多个层次的树种分类: 首先, 对高分辨率影像进行基于边缘检测的多尺度分割, 提取出单木冠幅; 其次, 对高光谱影像进行特征变量提取, 并对提取出的特征变量利用信息熵原理选取优化特征变量; 然后, 分别利用全部特征变量和经优化的重要特征变量对森林树种及森林类型进行预分类; 最后, 在预分类结果中加入单木冠幅信息对森林树种及森林类型进行重分类, 并分析分类结果的精度。研究表明: 1)利用全部特征变量进行4个典型树种分类时, 总体精度为64.6%, Kappa系数为0.493; 而针对森林类型的分类精度为81.1%, Kappa系数为0.584。2)利用选取的优化特征变量分类精度略低于利用全部特征变量的分类精度, 其中对4个典型树种分类时, 总体精度为62.9%, Kappa系数为0.459; 而针对森林类型的分类精度为77.7%, Kappa系数为0.525。通过集成传感器同期获取的高分辨率和高光谱数据可以有效地进行北亚热带森林的树种分类及森林类型的划分。     

Diffusion, Transport, and Cell Membrane Organization Investigated by Imaging Fluorescence Cross-Correlation Spectroscopy

Cell membrane organization is dynamic and is assumed to have different characteristic length scales. These length scales, which are influenced by lipid and protein composition as well as by the cytoskeleton, can range from below the optical resolution limit (as with rafts or microdomains) to far above the resolution limit (as with capping phenomena or the formation of lipid “platforms”). The measurement of these membrane features poses a significant problem because membrane dynamics are on the millisecond timescale and are thus beyond the time resolution of conventional imaging approaches. Fluorescence correlation spectroscopy (FCS), a widely used spectroscopic technique to measure membrane dynamics, has the required time resolution but lacks imaging capabilities. A promising solution is the recently introduced method known as imaging total internal reflection (ITIR)-FCS, which can probe diffusion phenomena in lipid membranes with good temporal and spatial resolution. In this work, we extend ITIR-FCS to perform ITIR fluorescence cross-correlation spectroscopy (ITIR-FCCS) between pixel areas of arbitrary shape and derive a generalized expression that is applicable to active transport and diffusion. ITIR-FCCS is applied to model systems exhibiting diffusion, active transport, or a combination of the two. To demonstrate its applicability to live cells, we observe the diffusion of a marker, the sphingolipid-binding domain (SBD) derived from the amyloid peptide Aβ, on live neuroblastoma cells. We investigate the organization and dynamics of SBD-bound lipid microdomains under the conditions of cholesterol removal and cytoskeleton disruption.     

Experimental study on the fluid mechanics of blood sucking in the proboscis of a female mosquito

Female mosquitoes are known to have a magnificent micro-scale pumping system that can transport small quantities of blood very effectively. To understand the dynamic characteristics of blood flow inside female mosquitoes, the measurement technique that is capable of measuring instantaneous flow fields of a biological sample at micrometer scales is required. In this study, the blood-sucking flow inside a female mosquito's food canal was measured in vivo using a micro particle image velocimetry (micro-PIV) velocity field measurement technique with high-temporal resolution. The volumetric flow rate (Q) and the time-averaged feeding speed (V) based on the diameter of the food canal (D) was found to be 5.751×10^?3 mm³/s and 0.416 cm/s, respectively. Spectral analysis on the velocity waveform shows a clear peak at 6.1 Hz, indicating distinct pulsatile blood-sucking characteristics. The Womersley number (α) was about 0.117 and the velocity profile of the blood flow inside the proboscis has a parabolic Hagen–Poiseuille flow pattern when α is much smaller than 1.     

Old and new challenges in using species diversity for assessing biodiversity

Although the maintenance of diversity of living systems is critical for ecosystem functioning, the accelerating pace of global change is threatening its preservation. Standardized methods for biodiversity assessment and monitoring are needed. Species diversity is one of the most widely adopted metrics for assessing patterns and processes of biodiversity, at both ecological and biogeographic scales. However, those perspectives differ because of the types of data that can be feasibly collected, resulting in differences in the questions that can be addressed. Despite a theoretical consensus on diversity metrics, standardized methods for its measurement are lacking, especially at the scales needed to monitor biodiversity for conservation and management purposes. We review the conceptual framework for species diversity, examine common metrics, and explore their use for biodiversity conservation and management. Key differences in diversity measures at ecological and biogeographic scales are the completeness of species lists and the ability to include information on species abundances. We analyse the major pitfalls and problems with quantitative measurement of species diversity, look at the use of weighting measures by phylogenetic distance, discuss potential solutions and propose a research agenda to solve the major existing problems.     

Kinematic study of root elongation in Arabidopsis thaliana with a novel image-analysis program

The measurement of the spatial profile of root elongation needs to determine matching points between time-lapse images and calculate their displacement. These data have been obtained by laborious manual methods in the past. Some computer-based programs have been developed to improve the measurement, but they require many time-series digital images or sprinkling graphite particles on the root prior to image capture. Here, we have developed GrowthTracer, a new image-analysis program for the kinematic study of root elongation. GrowthTracer employs a multiresolution image matching method with a nonlinear filter called the critical point filter (CPF), which extracts critical points from images at each resolution and can determine precise matching points by analysis of only two intact images, without pre-marking by graphite particles. This program calculates the displacement of each matching point and determines the displacement velocity profile along the medial axis of the root. In addition, a manual input of distinct matching points increases the matching accuracy. We show a successful application of this novel program for the kinematic analysis of root growth in Arabidopsis thaliana.     

Land surface phenology as an indicator of biodiversity patterns

With the rapid decline in biodiversity worldwide it is imperative to develop procedures for assessing changes in biodiversity across space. The synoptic view provided by imaging remote sensors constitutes a suitable approach for analyzing biodiversity from local to regional scales. A procedure based on the close relationship between floristic similarity and the similarity in land surface phenology was recently developed and successfully applied to assess diversity patterns using time series imagery acquired by the Moderate Resolution Imaging Spectro-radiometer (MODIS). However, as it depends on high temporal resolution remotely sensed data (e.g., MODIS), the procedure is constrained by the coarse spatial resolution characterizing these high temporal resolution data. Using an optimized technique for image fusion, we combined high temporal resolution data acquired by the MODIS sensor system with moderate spatial resolution data acquired by the Landsat TM/ETM+ sensor systems. Our results show that the MODIS/Landsat data fusion allows the characterization of land surface phenology at higher spatial resolutions, which better corresponded with information acquired within vegetation survey plots established in temperate montane forests located in Wolong Nature Reserve, Sichuan Province, China. As such, the procedure is useful for capturing changes in biodiversity induced by disturbances operating at large spatial scales and constitutes a suitable tool for monitoring and managing biodiversity.