Nutritive value of fishes of Lake Tanganyika: II. Mineral composition

The composition of the minerals in three economically important fish species of Lake Tanganyika was determined. From the analyses there does not appear to be significant difference in the composition for the three species. Beside the major elements: Ca, P, K, Na, Mg, Cl, Fe, Al and Zn, eighteen trace elements were determined. The presence of the bones in the fish is especially nutritionally important for the following elements: Ca, P, Br, Sr, Mn and Mg.

Nutritional and anti-nutritional analyses of Azolla africana Desv. and Spirodela polyrrhiza L. Schleiden as feedstuffs for fish production

The chemical composition of Azolla africana and Spirodela polyrrhiza cultivated in earthen ponds were determined. Crude protein contents of the samples were 28.9~c0.6 and 25.6~c0.2% dry matter for A. africana and S. polyrrhiza respectively. Dry matter, crude fibre and lipid contents of A. africana were higher (P<0.05) than values obtained for S. polyrrhiza. Mineral analyses showed that S. polyrrhiza contained higher levels of Na, S, Ca, Mg and Fe than A. africana. Except for Ca content in S. polyrrhiza, heavy metals (Ni and Zn) accumulation in Azolla were very high. There were no wide differences in the individual amino acid indexes except for methionine. Some anti-nutritional factors were determined. Cyanide, tannin and phytin contents of fresh weed samples were higher than sun-dried samples. A. africana contained more cyanide and tannin than S. polyrrhiza both in fresh and sun-dried forms

Effects of fishing on growth traits: a simulation analysis

Abstract—Fisheries often target individuals based on size. Size-selective fishing can create selection differentials on life-history traits and, when those traits have a genetic basis, may cause evolution. The evolution of life history traits affects potential yield and sustainability of fishing, and it is therefore an issue for fishery management. Yet fishery managers usually disregard the possibility of evolution, because little guidance is available to predict evolutionary consequences of management strategies. We attempt to provide some generic guidance. We develop an individual-based model of a population with overlapping generations and continuous reproduction. We simulate model populations under size-selective fishing to generate and quantify selection differentials on growth. The analysis comprises a variety of common life-history and fishery characteristics: variability in growth, correlation between von Bertalanffy growth parameters (K and L∞), maturity rate, natural mortality rate (M), M/K ratio, duration of spawning season, fishing mortality rate (F), maximum size limit, slope of selectivity curve, age at 50% selectivity, and duration of fishing season. We found that each characteristic affected the magnitude of selection differentials. The most vulnerable stocks were those with a short spawning or fishing season. Under almost all life-history and fishery characteristics examined, selection differentials created by realistic fishing mortality rates are considerable.