8 resultados para Stepwise Discriminant Analysis
em Aquatic Commons
Resumo:
Discriminant analysis takes into consideration the natural correlation existing between different characteristics of fish when studying mesh selectivity. Some specimen data are presented for two different sets of fish and it is shown that the discriminant analysis shows a significant difference between the two sets where F test failed.
Resumo:
Discriminant functions were worked out for adoption or non-adoption of five improved practices in fish curing. Four variables measured quantitatively formed the basis for discrimination. In four out of five equations, the selected variables were found to discriminate significantly between the adopters and non-adopters.
Resumo:
Endoparasitic helminths were inventoried in 483 American plaice (Hippoglossoides platessoides) collected from the southern Gulf of St. Lawrence, NAFO (North Atlantic Fisheries Organization) division 4T, and Cape Breton Shelf (NAFO subdivision 4Vn) in September 2004 and May 2003, respectively. Forward stepwise discriminant function analysis (DFA) of the 4T samples indicated that abundances of the acanthocephalans Echinorhynchus gadi and Corynosoma strumosum were significant in the classification of plaice to western or eastern 4T. Cross validation yielded a correct classification rate of 79% overall, thereby supporting the findings of earlier mark-recapture studies which have indicated that 4T plaice comprise two discrete stocks: a western and an eastern stock. Further analyses including 4Vn samples, however, indicated that endoparasitic helminths may have little value as tags in the classification of plaice overwintering in Laurentian Channel waters of the Cabot Strait and Cape Breton Shelf, where mixing of 4T and 4Vn fish may occur.
Resumo:
Five species of submerged vegetation Lagarosiphon ilicifolius, Najas pectinata, Vallisneria aethiopica, Ceratophyllum demersum and Potamogeton octandrus; 7 species of gastropods Melanoides tuberculata, Bellamya capillata, Biomphalaria pfeifferi, Bullinus tropicus, Cleopatra sp, and Lymnaea natalensis and 4 species of bivalves Corbicula africana, Caelatura mossambicensis, Mutela dubia and Aspatharia wahlbergii are correlated with environmental variables particularly slope and transparency, in Lake Kariba. A stepwise regression analysis further revealed interdependence between (Cleopatra sp., B. pfeifferi, L. natalensis, B. capillata, and V. aethiopica as well as between as between C. mossambicensis and L. ilicifolius and N. pectinata. The dependence of B. pfeifferi, L. natalensis, B. capillata, Cleopatra sp. on V. aethiopica and C. mossambicensis on L. ilicifolius and N. pectinata implies that a change in the biomass of the vegetation species may affect distribution and biomass of the faunal species.
Resumo:
Nuclear RNA and DNA in muscle cell nuclei of laboratory-reared larvae of Walleye Pollock (Gadus chalcogrammus) were simultaneously measured through the use of flow cytometry for cell-cycle analysis during 2009–11. The addition of nuclear RNA as a covariate increased by 4% the classification accuracy of a discriminant analysis model that used cell-cycle, temperature, and standard length to measure larval condition, compared with a model without it. The greatest improvement, a 7% increase in accuracy, was observed for small larvae (<6.00 mm). Nuclear RNA content varied with rearing temperature, increasing as temperature decreased. There was a loss of DNA when larvae were frozen and thawed because the percentage of cells in the DNA synthesis cell-cycle phase decreased, but DNA content was stable during storage of frozen tissue.
Resumo:
Using water quality management programs is a necessary and inevitable way for preservation and sustainable use of water resources. One of the important issues in determining the quality of water in rivers is designing effective quality control networks, so that the measured quality variables in these stations are, as far as possible, indicative of overall changes in water quality. One of the methods to achieve this goal is increasing the number of quality monitoring stations and sampling instances. Since this will dramatically increase the annual cost of monitoring, deciding on which stations and parameters are the most important ones, along with increasing the instances of sampling, in a way that shows maximum change in the system under study can affect the future decision-making processes for optimizing the efficacy of extant monitoring network, removing or adding new stations or parameters and decreasing or increasing sampling instances. This end, the efficiency of multivariate statistical procedures was studied in this thesis. Multivariate statistical procedure, with regard to its features, can be used as a practical and useful method in recognizing and analyzing rivers’ pollution and consequently in understanding, reasoning, controlling, and correct decision-making in water quality management. This research was carried out using multivariate statistical techniques for analyzing the quality of water and monitoring the variables affecting its quality in Gharasou river, in Ardabil province in northwest of Iran. During a year, 28 physical and chemical parameters were sampled in 11 stations. The results of these measurements were analyzed by multivariate procedures such as: Cluster Analysis (CA), Principal Component Analysis (PCA), Factor Analysis (FA), and Discriminant Analysis (DA). Based on the findings from cluster analysis, principal component analysis, and factor analysis the stations were divided into three groups of highly polluted (HP), moderately polluted (MP), and less polluted (LP) stations Thus, this study illustrates the usefulness of multivariate statistical techniques for analysis and interpretation of complex data sets, and in water quality assessment, identification of pollution sources/factors and understanding spatial variations in water quality for effective river water quality management. This study also shows the effectiveness of these techniques for getting better information about the water quality and design of monitoring network for effective management of water resources. Therefore, based on the results, Gharasou river water quality monitoring program was developed and presented.
Resumo:
ENGLISH: Morphometric data from yellowfin tuna, Thunnus albacares, were collected from various locations in the eastern Pacific Ocean during 1974 to 1976, to assess geographic and temporal variation of morphometric characters. The data were statistically adjusted, using allometric formulae to partition size. Discriminant analyses were applied to the adjusted morphometric characters. Yellowfin sampled from north of 15°N-20oN were different from those sampled from south of 15°N-20oN. The absence of any clinal relationships between morphometric characters and latitude or longitude suggests a pattern of somewhat distinct regional groups. These results clearly demonstrate geographic variation in morphometric characters of yellowfin in the eastern Pacific Ocean, which suggests differences between the life histories of the northern and southern groups. SPANISH: Entre 1974 Y1976 se tomaron datos morfométricos de atunes aleta amarilla, Thunmus albacares, de varios lugares en el Océano Pacífico oriental, a fin de evaluar la variación geográfica y temporal de los caracteres morfométricos. Se ajustaron los datos estadísticamente, usando fórmulas alométricas para eliminar los efectos del tamaño. Se aplicaron análisis discriminantes a los caracteres morfométricos ajustados. Aletas amarillas muestreados provenientes del norte de 15°N-20°N eran diferentes a aquellos muestreados del sur de 15°N -20°N. La falta de una relación clinal entre los caracteres morfométricos y latitud o longitud sugiere la existencia de grupos regionales algo distintos. Estos resultados demuestran claramente una variación geográfica en los caracteres morfométricos del aleta amarilla en el Océano Pacífico oriental, la cual sugiere diferencias en los ciclos vitales de los grupos del norte y del sur. (PDF contains 41 pages.)
Resumo:
King mackerel (Scomberomorus cavalla) are ecologically and economically important scombrids that inhabit U.S. waters of the Gulf of Mexico (GOM) and Atlantic Ocean (Atlantic). Separate migratory groups, or stocks, migrate from eastern GOM and southeastern U.S. Atlantic to south Florida waters where the stocks mix during winter. Currently, all winter landings from a management-defined south Florida mixing zone are attributed to the GOM stock. In this study, the stock composition of winter landings across three south Florida sampling zones was estimated by using stock-specific otolith morphological variables and Fourier harmonics. The mean accuracies of the jackknifed classifications from stepwise linear discriminant function analysis of otolith shape variables ranged from 66−76% for sex-specific models. Estimates of the contribution of the Atlantic stock to winter landings, derived from maximum likelihood stock mixing models, indicated the contribution was highest off southeastern Florida (as high as 82.8% for females in winter 2001−02) and lowest off southwestern Florida (as low as 14.5% for females in winter 2002−03). Overall, results provided evidence that the Atlantic stock contributes a certain, and perhaps a significant (i.e., ≥50%), percentage of landings taken in the management-defined winter mixing zone off south Florida, and the practice of assigning all winter mixing zone landings to the GOM stock should