Classification of Coastal Communities Reporting Commercial Fish Landings in the U.S. Northeast Region: Developing and Testing a Methodology

The National Marine Fisheries Service is required by law to conduct social impact assessments of communities impacted by fishery management plans. To facilitate this process, we developed a technique for grouping communities based on common sociocultural attributes. Multivariate data reduction techniques (e.g. principal component analyses, cluster analyses) were used to classify Northeast U.S. fishing communities based on census and fisheries data. The comparisons indicate that the clusters represent real groupings that can be verified with the profiles. We then selected communities representative of different values on these multivariate dimensions for in-depth analysis. The derived clusters are then compared based on more detailed data from fishing community profiles. Ground-truthing (e.g. visiting the communities and collecting primary information) a sample of communities from three clusters (two overlapping geographically) indicates that the more remote techniques are sufficient for typing the communities for further in-depth analyses. The in-depth analyses provide additional important information which we contend is representative of all communities within the cluster.

Lakes - Classification & Monitoring: a strategy for the classification of lakes

This is the report on Lakes – Classification and Monitoring, a strategy for the classification of lakes by the National Rivers Authority. This report describes a scheme for the assessment and monitoring of water and ecological quality in standing waters, greater than about 1ha in area, in England and Wales although it is generally relevant to Northwest Europe. Thirteen hydrological, chemical and biological variables are used to characterize the standing water body in any current sampling. Statistical testing on the chemical variables showed that at least six samples during a year would be needed to produce a representative sampling mean; but in this scheme the choice of variables minimizes logistic cost by not using boat sampling and time costs by not demanding extensive taxonomic work. Standing waters are classified in a state-changed system in which the contemporary values of the variables are compared with a reference baseline state and then placed in categories of percentage change from this baseline. The scheme is presently designed for use at about five year intervals on all lakes greater than 2ha area plus additional lakes of significant amenity or conservation interest.

Wetland resource evaluation and the NRA's role in its conservation. Classification of British wetlands

This is the Wetland resource evaluation and the NRA's role in its conservation: Classification of British wetlands report produced by the National Rivers Authority in 1995. This R&D document provides a clear classification for wetlands in England and Wales. The classification incorporates many of the existing ideas on the subject but avoids some of the problems associated with other classifications. A two-layered 'hydrotopographical' classification is proposed. The first layer identifies situation-types, i.e. the position the wetland occupies in the landscape, with special emphasis upon the principal sources of water. The second layer identifies hydrotopographical elements, i.e. units with distinctive water supply and, sometimes, distinctive topography in response to this. This system is seen as an independent, basic, classification upon which it is possible to superimpose additional, independent classifications based on other features (e.g. base-status, fertility, vegetation, management etc.). Some proposals for such additional classifications are provided.

An objective classification of climatic regions in the Pacific and Indian oceans

We have applied a number of objective statistical techniques to define homogeneous climatic regions for the Pacific Ocean, using COADS (Woodruff et al 1987) monthly sea surface temperature (SST) for 1950-1989 as the key variable. The basic data comprised all global 4°x4° latitude/longitude boxes with enough data available to yield reliable long-term means of monthly mean SST. An R-mode principal components analysis of these data, following a technique first used by Stidd (1967), yields information about harmonics of the annual cycles of SST. We used the spatial coefficients (one for each 4-degree box and eigenvector) as input to a K-means cluster analysis to classify the gridbox SST data into 34 global regions, in which 20 comprise the Pacific and Indian oceans. Seasonal time series were then produced for each of these regions. For comparison purposes, the variance spectrum of each regional anomaly time series was calculated. Most of the significant spectral peaks occur near the biennial (2.1-2.2 years) and ENSO (~3-6 years) time scales in the tropical regions. Decadal scale fluctuations are important in the mid-latitude ocean regions.

Bayesian classification of acoustical waveforms under environmental variability

We present in this paper a new multivariate probabilistic approach to Acoustic Pulse Recognition (APR) for tangible interface applications. This model uses Principle Component Analysis (PCA) in a probabilistic framework to classify tapping pulses with a high degree of variability. It was found that this model, achieves a higher robustness to pulse variability than simpler template matching methods, specifically when allowed to train on data containing high variability. © 2011 IEEE.

THE PHYLOGENETIC-RELATIONSHIPS AND CLASSIFICATION OF THE DOUCS AND SNUB-NOSED LANGURS OF CHINA AND VIETNAM

The taxonomy of the douc and snub-nosed langurs has changed several times during the 20th century. The controversy over the systematic position of these animals has been due in part to difficulties in studying them: both the doucs and the snub-nosed langurs are rare in the wild and are generally poorly represented in institutional collections. This review is based on a detailed examination of relatively large numbers of specimens of most of the species of langurs concerned. An attempt was made to draw upon as many types of information as were available in order to make an assessment of the phyletic relationships between the langur species under discussion. Toward this end, quantitative and qualitative features of the skeleton, specific features of visceral anatomy and characteristics of the pelage were utilized. The final data matrix comprised 178 characters. The matrix was analyzed using the program Hennig86. The results of the analysis support the following conclusions: (1) that the douc and snub-nosed langurs are generically distinct and should be referred to as species of Pygathrix and Rhinopithecus, respectively; (2) that the Tonkin snub-nosed langur be placed in its own subgenus as Rhinopithecus (Presbytiscus) avunculus and that the Chinese snub-nosed langur thus be placed in the subgenus Rhinopithecus (Rhinopithecus); (3) that four extant species of Rhinopithecus be recognized: R. (Rhinopithecus) roxellana Milne Edwards, 1870; R. (Rhinopithecus) bieti Milne Edwards, 1897; R. (Rhinopithecus) brelichi Thomas, 1903, and R. (Presbytiscus) avunculus Dollman, 1912; (4) that the Chinese snub-nosed langurs fall into northern and southern subgroups divided by the Yangtze river; (5) that R. lantianensis Hu and Qi, 1978, is a valid fossil species, and (6) the precise affinities and taxonomic status of the fossil species R. tingianus Matthew and Granger, 1923, are unclear because the type specimen is a subadult.

A classification of data quality assessment methods

Data quality (DQ) assessment can be significantly enhanced with the use of the right DQ assessment methods, which provide automated solutions to assess DQ. The range of DQ assessment methods is very broad: from data profiling and semantic profiling to data matching and data validation. This paper gives an overview of current methods for DQ assessment and classifies the DQ assessment methods into an existing taxonomy of DQ problems. Specific examples of the placement of each DQ method in the taxonomy are provided and illustrate why the method is relevant to the particular taxonomy position. The gaps in the taxonomy, where no current DQ methods exist, show where new methods are required and can guide future research and DQ tool development.