Discriminant analysis for mesh selectivity studies

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.

Discriminant analysis of selected variables in the adoption of fish curing

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.

Using measurements of muscle cell nuclear RNA with flow cytometry to improve assessment of larval condition of Walleye Pollock (Gadus chalcogrammus)

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.

Preparation of environmental monitoring plan pattern for surface water quality in Iran (Case study: Gharehsou River)

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.

Morphometric analysis of yellowfin tuna, Thunnus albacares, from the Eastern Pacific Ocean

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.)

An ecological analysis of rockfish (Sebastes spp.) assemblages in the North Pacific Ocean along broad-scale environmental gradients

Environmental variability affects the distributions of most marine fish species. In this analysis, assemblages of rockfish (Sebastes spp.) species were defined on the basis of similarities in their distributions along environmental gradients. Data from 14 bottom trawl surveys of the Gulf of Alaska and Aleutian Islands (n=6767) were used. Five distinct assemblages of rockfish were defined by geographical position, depth, and temperature. The 180-m and 275-m depth contours were major divisions between assemblages inhabiting the shelf, shelf break, and lower continental slope. Another noticeable division was between species centered in southeastern Alaska and those found in the northern Gulf of Alaska and Aleutian Islands. The use of environmental variables to define the species composition of assemblages is different from the use of traditional methods based on clustering and nonparametric statistics and as such, environmentally based analyses should result in predictable assemblages of species that are useful for ecosystem-based management.