A geographical region, containing an unknown number of species, is partitioned into N quadrats. The range of a species is defined to be the number of quadrats in which the species is present. A random sample of n quadrats is drawn without replacement, and the species list is determined for each of the selected quadrats. Two estimators of S are proposed. The inclusion probabilities in the Horvitz-Thompson estimator involve the unknown species ranges but these ranges can be estimated to yield an "estimated" Horvitz-Thompson estimator. This estimator is biased because of the use of estimated inclusion probabilities. For the other estimator, it is shown that the expected number of species in the sample having a specified sample range r is a linear combination over R of the number S R of species in the population with population range R. Letting r vary yields a system of linear equations that can be solved to obtain estimates for the S R and for S. These estimators for S R and S are shown to be unbiased when the sample size n is sufficiently large. _
When working with raw data for multiple environmental indicators, it can be difficult to assess quality or 'health' because of the large number of indicators and inconsistencies among the indicators. By grouping the raw data into rankings, the data become more manageable and more comprehensible. We do not, however, want to lose information as a result of the groupings. It is possible to assess the quality of grouping options graphically by seeing if the resulting assessments of 'health' are concordant with the raw data. This can be done through the use of CDF-index values, cumulative distribution function plots, parallel coordinates plots, and scatterplots. A major purpose of this paper is to present approaches and the graphics for comparison and prioritization based on quintiles used, in this case, for ecological assessment of a large region.
With continuing proliferation of human influences on landscapes, there is mounting incentive to undertake quantification of relationships between spatial patterns of human populations and vegetation. In considering such quantification, it is apparent that investigations must be conducted at different scales and in a comparative manner across regions. At the broader scales it becomes necessary to utilize remote sensing of vegetation for comparative studies against map referenced census data. This paper explores such an approach for the urbanized area in the Tokyo vicinity. Vegetation is represented by the normalized difference vegetation index (NDVI) as determined from data acquired by the thematic mapper (TM) sensor of the Landsat satellite. Sparseness of vegetation is analyzed in relation to density of human residence, first by regression analysis involving stratified distance zones and then by the recent echelon approach for characterization of surfaces. Echelons reveal structural organization of surfaces in an objective and explicit manner. The virtual surface determined by census data collected on a grid is shown to have structural correspondence with the surface representing vegetation greenness as reflected in magnitude of NDVI values computed from red and infrared bands of image data.
Multi-band remotely sensed image data contain information on landscape pattern and temporal changes that are greatly underutilized in this technological era when monitoring of disturbance and ecological dynamics is increasingly important to address questions regarding sustainability of ecosystem health and climate change. Among the reasons for this loss of analytical opportunity are the inadequacy of methods for systematic extraction of pattern elements, incongruity between information paradigms for remote sensing and geographic information systems (GIS), and the sheer volume of remotely sensed image data when acquired regularly over time. Long-term cooperative landscape ecological investigations concerning habitat and change detection in conjunction with remote sensing and GIS have yielded a pattern-based approach to progressively segmenting images (PSI) that culminates in a doubly segmented image representation by sets of approximating signal vectors that serve as parsimonious proxies for pixel vectors. The coarser level of segmentation is entirely congruent with raster map structures for GIS, and yet mimics the appearance of an image display by colorization using information on typical spectral properties of segments contained in attribute tables. The components of the coarser representation as spatial segments constitute explicit elements of pattern at several levels. The explicit nature of these pattern elements enables spatial pattern matching for change detection that resolves difficulties with phenological variability and continuity of sensor configurations over time. Conversion to segmented representation can be applied to multi-temporal change indices so as to elicit longer-term patterns of change from temporal sequences of images. The finer level of segmentation for spectral detail enables restoration of image bands in the manner of a low-pass filter for analysis according to the usual paradigms of remote sensing. Mapping of the residuals for the finer detail of image approximation provides further information on exceptional features of landscape ecological pattern.
With contemporary emphasis on sustainability and ecosystem-oriented natural resources management, ecological mapping at landscape scales is becoming increasingly important as a framework for environmental planning, monitoring and assessment. This is especially so when the terrain has substantial variability in elevation and steep slopes. Recognizing the importance of hydrology in landscape dynamics, we base an ecological mapping approach on topological features of terrain from a hydrologic and habitat perspective. This approach emphasizes convexities and concavities of topography as caplands and confluent cuplands, respectively. A concept of coherent convex contours provides an operational basis for determining capland components, with cupland components being predominantly concave contributing areas for higher-order streams. Scaling sequences of subdivisions give progressive partitioning down to sizes of units that serve practical purposes of natural resource management. An innovation of dome domains and terrain tiers is introduced for more detailed topological treatment of land forms.
A simple, specific, and precise RP-HPLC method with photodiode-array detection has been developed for simultaneous analysis of the quinazoline alkaloids vasicine and vasicinone, pharmacologically important constituents of Adhatoda vasica. The compounds were separated by use of 0.1% trifluoroacetic acid in water:acetonitrile 90:10 as isocratic mobile phase at a flow rate of 1.0 mL min−1. Under these conditions, plots of integrated peak area against concentration were linear over the ranges 0.05–10.0 μg mL−1 and 0.5–100.0 μg mL−1 (r2 = 0.999 and 0.998) for vasicine and vasicinone, respectively. Mean recovery was 99.06% for vasicine and 98.69% for vasicinone. The method is therefore suitable for routine analysis of vasicine and vasicinone in Adhatoda vasica plants of different varieties and in herbal medicinal products prepared from the plants.
Spatially synoptic multivariate image data implicitly embody information on landscape pattern, for which analytical techniques of explicit pattern extraction are evolving. In parallel, a multiplicity of 'environmental indicators' is being generated in the arena of geographic information systems. Landscape ecological analysis offers substantial opportunity for configuring these indicators synoptically as cells over spatial extents and for stacking them into complementary sets of image-structured multiple environmental indicators whereby the values of the indicators become intensity analogs of brightness for spectral bands. As environmental signal analogs of multiband images, these data become available to image portrayal in both graytone and quasi-color renditions to reveal joint properties of pattern for visual interpretation. Likewise, many of the conventional image analysis operations can be conceived more broadly to allow their application in the indicator context. This includes combinatorial approaches such as calculation of an NDVI equivalent from indicator intensities. Similarly, supervised and unsupervised analyses can have meaningful application in the context of multiple environmental indicators. Furthermore, newer techniques of pattern-based image segmentation can also be applied. Application to habitat modeling for vertebrates from Gap Analysis shows the effectiveness of the approach.
Simvastatin is a selective HMG-CoA reductase inhibitor and ezetimibe has lipid-lowering activity. Both are potential anti-lipidemic agents used in combination to reduce the amount of cholesterol and triglycerides in systemic circulation. This paper describes a simple, precise, and accurate HPTLC method for simultaneous estimation of the compounds as the bulk drugs and in the tablet dosage form. Chromatographic separation was performed on aluminium-backed silica gel 60 F254 plates with 8:2 (v/v) toluene-2-propanol as mobile phase. The separated spots were densitometrically evaluated at 240 nm. The drugs were satisfactorily resolved with RF values 0.48 ± 0.01 and 0.53 ± 0.01 for simvastatin and ezetimibe, respectively. The accuracy and reliability of the method were assessed by determination of validation data for linearity (0.4–2.0 μg per spot for both simvastatin and ezetimibe), precision (intra-day RSD 0.51–1.04%, inter-day RSD 0.34–1.11% for simvastatin; intra-day RSD 0.47–0.61%, inter-day RSD 0.31–0.61% for ezetimibe), accuracy (98.50 ± 0.23 for simvastatin and 98.99 ± 0.38 for ezetimibe), and specificity, in accordance with ICH guidelines. The proposed method can be used for analysis of ten or more formulations on a single plate and is a rapid and cost-effective quality-control tool for routine simultaneous analysis of simvastatin and ezetimibe as the bulk drugs and in tablet formulations.
A simple, sensitive, and accurate liquid chromatographic method with photodiode array detector was developed for the determination of andrographolide, phyllanthin, and hypophyllanthin. The separation was carried out on a reverse-phase 250 mm × 4.6 mm, 5μ symmetry C8 column (Waters). The gradient was prepared from 0.1% orthophosphoric acid (solvent A) and (1:1) acetonitrile:methanol (solvent B) as mobile phase delivered at a flow rate of 1 mL min−1. A linear behavior was observed between observed peak area response, and concentration of analytes was investigated, with good correlation coefficient. The method established was successfully applied to quantify andrographolide, phyllanthin, and hypophyllanthin from the herbal hepatoprotective formulation.
A simple, specific, accurate, and precise high-performance thin-layer chromatographic method for analysis of cefuroxime axetil and potassium clavulanate in a combined tablet dosage form is reported. The compounds were separated on aluminium foil plates precoated with silica gel 60 F254, with chloroform-methanol-toluene 4:3:3 (v/v) as mobile phase. Densitometric evaluation of the separated bands was performed at 225 nm. The two drugs were satisfactorily separated with RF 0.77 ± 0.0114 and 0.29 ± 0.0114 for cefuroxime axetil and potassium clavulanate, respectively. Response was a linear function of amount over the calibration ranges 500–2500 and 2000–10 000 ng per band, respectively. The method was successfully validated and used for analysis of the drugs in a pharmaceutical formulation. Recovery was 100.05 ± 0.98% for cefuroxime axetil and 99.94 ± 0.538% for potassium clavulanate (mean ± RSD).