11 resultados para Principal components analysis

em Aquatic Commons


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Aquaculture in the Philippines is a long-standing activity but has witnessed relatively recent, rapid, technical change with the introduction of hatchery technology and commercial feed-mills changing the production possibilities for a fishpond operator. We are confronted with a diversity of aquaculture practices in the coastal areas of the Philippines, with new technologies being incorporated into more traditional systems. As a first step to understanding the sector, we therefore present a typology of farming systems with the motivation of generating domains (farm “types”) over which we can compare performance on a number of indicators. Our typology, restricted to brackish-water pond systems, is constructed using multivariate methods (principal components analysis, cluster analysis). Eight variables are used relating to the management of the farm across all the major factors of production. A stratified net sample of 136 observations provides the data for the analysis, from a farm-level survey carried out between January and June 2003 in the two main brackish-water production regions in the Philippines. We define five farm types from this analysis. In later work we will show how the use of this typology can be used for comparative study of economic, social and ecological performance at the farm-level. [PDF contains 42 pages]

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The broad distribution of Pacific sardine (Sardinops sagax) along the Pacif ic coast of North America makes it difficult for fisheries managers to identify regional stocks of this dominant small pelagic species. An investigation of morphometric characteristics of otoliths of Pacific sardine across most of their range revealed regional differences in populations. In a survey of over 2000 otoliths, all ages (with an emphasis on age-1 recruits) were compared. Principal components analysis, multivariate analysis of variance, and a novel method derived from regression and residuals calculations, termed perimeter-weight profiles (PWPs), revealed otolith similarities and differences. The results of the different approaches to statistical comparisons did not always agree. Sardine otoliths from Mexican waters were generally lighter and more lobate than those from U.S. and Canadian populations. Age-1 otoliths from northern California in 2006–07 tended to be heavier and smoother than those from other areas, including year-class cohorts from southern California. Comparisons of age-groups and year-classes of northern California otoliths with the use of the PWP models indicated signif icant trends in year-to-year patterns. In conjunction with other established indices of population structure, otolith PWPs are a useful tool for identifying local and regional stocks of Pacific sardine and may help distinguish populations of other fish species as well.

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The coastal Pacific Ocean off northern and central California encompasses the strongest seasonal upwelling zone in the California Current ecosystem. Headlands and bays here generate complex circulation features and confer unusual oceanographic complexity. We sampled the coastal epipelagic fish community of this region with a surface trawl in the summer and fall of 2000–05 to assess patterns of spatial and temporal community structure. Fifty-three species of fish were captured in 218 hauls at 34 fixed stations, with clupeiform species dominating. To examine spatial patterns, samples were grouped by location relative to a prominent headland at Point Reyes and the resulting two regions, north coast and Gulf of the Farallones, were plotted by using nonmetric multidimensional scaling. Seasonal and interannual patterns were also examined, and representative species were identified for each distinct community. Seven oceanographic variables measured concurrently with trawling were plotted by principal components analysis and tested for correlation with biotic patterns. We found significant differences in community structure by region, year, and season, but no interaction among main effects. Significant differences in oceanographic conditions mirrored the biotic patterns, and a match between biotic and hydrographic structure was detected. Dissimilarity between assemblages was mostly the result of differences in abundance and frequency of occurrence of about twelve common species. Community patterns were best described by a subset of hydrographic variables, including water depth, distance from shore, and any one of several correlated variables associated with upwelling intensity. Rather than discrete communities with clear borders and distinct member species, we found gradients in community structure and identified stations with similar fish communities by region and by proximity to features such as the San Francisco Bay.

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Defining types of seafloor substrate and relating them to the distribution of fish and invertebrates is an important but difficult goal. An examination of the processing steps of a commercial acoustics analyzing software program, as well as the data values produced by the proprietary first echo measurements, revealed potential benef its and drawbacks for distinguishing acoustically distinct seafloor substrates. The positive aspects were convenient processing steps such as gain adjustment, accurate bottom picking, ease of bad data exclusion, and the ability to average across successive pings in order to increase the signal-to-noise ratio. A noteworthy drawback with the processing was the potential for accidental inclusion of a second echo as if it were part of the first echo. Detailed examination of the echogram measurements quantified the amount of collinearity, revealed the lack of standardization (subtraction of mean, division by standard deviation) before principal components analysis (PCA), and showed correlations of individual echogram measurements with depth and seafloor slope. Despite the facility of the software, these previously unknown processing pitfalls and echogram measurement characteristics may have created data artifacts that generated user-derived substrate classifications, rather than actual seafloor substrate types.

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Based upon a global comparison of over 400 fisheries, the Principal Components Analysis (PCA) methodology was used to identify factors affecting the choice of growth estimation methods. Of the six factors examined, the growth rate (K) and asymptotic length (L8) explained most of the variations. Financial resources, i.e., Gross National Product (GNP), and latitude were also important factors.

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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.

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The Deepwater Horizon (DWH) accident in the northern Gulf of Mexico occurred on April 20, 2010 at a water depth of 1525 meters, and a deep-sea plume was detected within one month. Oil contacted and persisted in parts of the bottom of the deep-sea in the Gulf of Mexico. As part of the response to the accident, monitoring cruises were deployed in fall 2010 to measure potential impacts on the two main soft-bottom benthic invertebrate groups: macrofauna and meiofauna. Sediment was collected using a multicorer so that samples for chemical, physical and biological analyses could be taken simultaneously and analyzed using multivariate methods. The footprint of the oil spill was identified by creating a new variable with principal components analysis where the first factor was indicative of the oil spill impacts and this new variable mapped in a geographic information system to identify the area of the oil spill footprint. The most severe relative reduction of faunal abundance and diversity extended to 3 km from the wellhead in all directions covering an area about 24 km2. Moderate impacts were observed up to 17 km towards the southwest and 8.5 km towards the northeast of the wellhead, covering an area 148 km2. Benthic effects were correlated to total petroleum hydrocarbon, polycyclic aromatic hydrocarbons and barium concentrations, and distance to the wellhead; but not distance to hydrocarbon seeps. Thus, benthic effects are more likely due to the oil spill, and not natural hydrocarbon seepage. Recovery rates in the deep sea are likely to be slow, on the order of decades or longer.

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In this study, in order to assess the ecological health status and zoning of soft bottom of Gorgan Bay, the spatial and temporal distribution of macrofauna and their relationship with environmental stress were investigated. Sediment samples were collected using a Van Veen grab at 22 sampling points, seasonally during 2012-2013. The averages (±SD) of the percentages of sand, silt, clay and TOM (Total Organic Matter) in the sediment samples were determined (44.4± 15, 53.4 ± 14, and 2.2 ±2.2 and 7.2% ± 1.6, respectively). Our results showed that mean (range) of Al, As, Cu, Fe, Ni, Pb and Zn in the sediment samples were 1.2 % (0.4-2.1), 4.8 (2.5- 10.3) ppm, 10.5 (4.4-16.9) ppm, 1 (0.4 – 1.6) % , 13.6 (6.2-21.5) ppm, 9.1 (4.7-12.9) ppm and 23.9 (3.1-39.4) ppm, respectively. In spring, both Al and Ni were higher than the guideline level. In the event that arsenic was exceeds the guidelines in summer. In this study, 14 species of macrofauna from 12 families were identified. Polychaeta with 3 species was the most dominant group in terms of abundance. The four most abundant taxa making up 85% of all specimens (Streblospio gynobranchiata, Tubificidae, Hediste versicolor and Abra segmentum). The western area were characterized by the higher species diversity (H', 1.94). So Gorgan Bay presents transitional macrobenthic assemblages that are spatially distributed along substrate gradients .The mean of Shannon index, BENTIX, BO2A, AMBI and M-AMBI in the bay was 1.3, 2.2, 0.4, 3.2 and 0.65 respectively. According to the results of these indices, ecological status of the western part of the bay assessed better than the other parts. According to the results of the nmMDS (non-metric Multidimensional Scaling), PCA (Principal Components Analysis), the map of distribution of heavy metals and the map of the ecological status , it seems Gorgan Bay is divided into two separate zones (the eastern and the western parts).M-AMBI finaly introduced reliable index for assessing the ecological status of the Bay.

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A study was conducted in 54 wetlands of 13 districts of Assam, India to evaluate the causes of fish depletion. Twenty-two variables were considered for the study. Seven factors were extracted through factor analysis (Principal Component Analysis) based on Eigen Value Criteria of more than one. These seven factors together accounted for 69.3% of the total variance. Based on the characteristics of the variables, all the factors were given descriptive names. These variables can be used to measure the extent of management deficiency of the causes of fish depletion in the wetlands. The factors are management deficiency, organic load interference, catchment condition, extrinsic influence, fishermen’s ignorance, external environment and aquaculture program. Management deficiency accounted for a substantial portion of the total variance.

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EXTRACT (SEE PDF FOR FULL ABSTRACT): Four broad regions of the western United States within which annual streamflows exhibit strong spatial coherence are identified using principal component analysis with a varimax rotation. Geographically, the four regions encompass the Pacific Northwest, Far West-Great Basin, Central Rockies-High Plains, and Northern Great Plains. These regions are really consistent with previously documented, descriptively derived streamflow regimes as well as with general atmospheric circulation and precipitation modes of variation. Collectively, the four regional components account for nearly 63 percent of the total annual variation in western U.S. streamflow. The time history of most principal component patterns exhibit little or no persistence.

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EXTRACT (SEE PDF FOR FULL ABSTRACT): An analysis of the principal components of surface temperature and precipitation in the western U.S. is presented. Data consist of monthly mean temperature and total precipitation for 66 climate divisions west of the Continental Divide, for the years 1931-1984. The analysis is repeated for three separate combinations of months - the water year (Oct - Sept), the cool season (Oct - Mar) and the warm season (Apr - Sept). Inspection of monthly precipitation climatology indicates that selection of these combinations of months results in very few awkward splittings of the natural precipitation seasons found in the West.