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This study was carried out to determine the relationships between physicochemical parameters and morphometric and reproduction features of the crayfishes (Astacus leptodactylus) in Yenice Central Irrigation Pond. Results of MDS analysis revealed that the relationships between physicochemical parameters and morphometric features and reproduction features in crayfishes could be explained at diff erent rates. Reproduction features such as fecundity and sperm production, were within a close relationship with temperature, magnesium, conductivity, dissolved oxygen, and the abdomen weight, carapace weight, abdominal width, carapace width, abdomen length, carapace length from morphometric features were within a close relationship especially with dissolved oxygen, magnesium, calcium, and temperature. These relationships could play an important role while considering the selection of maternal females for cultural environments and for the management of productive population, and for the selection of water sources that can be effective for populations that is generated by vaccination. [ABSTRACT FROM AUTHOR]

This study was carried out to investigate relationships between some morphological and reproductive traits of the Turkish crayfish, A. leptodactylus, collected from a controlled irrigation lake in the Yenice province (Canakkale, Turkey), between July 2007 and June 2008. For this objective, two multivariate analysis techniques, namely canonical correlation analysis and multivariate multiple linear regression analysis, were used. The results of the canonical correlation analysis have shown that the morphological traits may be used to predict the changes in the reproductive traits. For instance, canonical correlation analysis results suggested that the egg weight and the number of eggs are related to the total length, carapace length, and carapace width. The results of multivariate multiple linear regression analysis, on the other hand, show a slightly different picture. Therefore, it is possible to conclude that both canonical correlation and multivariate regression results can be taken into consideration together when investigating the relations between two variable sets. [ABSTRACT FROM AUTHOR]