The objective of this review was to provide an overview of the major biotic and abiotic factors that determine the composition of stream fish communities. Fish communities often consist of discrete and nonrandom species assemblages. Stream fish communities are all structured none randomly in space. In a meta-community framework, local fish communities may be structured by both spatial and environmental factors. Most fish in small, stable streams are most probably habitat specialists that have evolved various morphological and behavioral adaptations to exploit specific habitat types. Over large geographical and habitat scales, environmental filtering and anthropogenic effects are generally the most important determinants of assemblage variability. Streams are important habitats, providing shelter and feeding opportunities for a wide range of organisms like fish, insects, plants, mollusks, birds and mammals. Fish community structure depends on biotic interactions and abiotic variables. Predation is a major determinant of ecological patterns in fresh water fish communities. Resource partitioning among fishes suggest that competition may play an important role in the local organization of communities. Most studies are based on field observations, and many suggest that niche segregation rather than competitive exclusion is the predominant outcome resulting from competitive interactions. Finally, we saw that, fish community composition was negatively affected by human impact, Climate change, introduction of exotic spices and tourism or sports on streams.

Fish are perishable and hence susceptible to high post-harvest losses. Post-harvest losses in fisheries include material losses of fish due to spoilage, breakage, size, discarding of by-catches and operational losses. This research was conducted to propose a management strategy to reduce post-harvest losses suffered by Tekeze dam and Lake Hashenge fishery associations. This research was conducted in Tekeze dam and Lake Hashenge fishery associations. The data were collected from primary and secondary quantifiable information on post-harvest losses. A total of eight official associations were surveyed during the study period. Each of these associations was found to own at least a refrigerator and a boat with (7.67 ± 3.82) nets. The mean (±SD) number of refrigerators owned at present is (11.13 ± 10.09), and 94.9% of the respondents involved in the study were males. Fish loss and yield per year of the associations showed a positive strong significant correlation (r = 0.948, df = 6, p < 0.01). Physical loss was the most common loss observed causing high economic loss. Improvement of facilities from the point of production until it reaches the consumer is vital, and fish must be stored and distributed under chilled temperature conditions.

Habitat selectivity and ecology of freshwater fishes were studied in two selected streams and their junction point which consist a total of 39 microhabitats. The aims of this study were to describe the habitat preference and its availability to fish assemblage, as well as ecology, habitat use, and habitat characteristics. We collected fish with backpack electrofishing three times during August 2013, December 2013, and March 2014. Using a variation partitioning approach of R software, we studied the relationship of fish abundances with stream type, habitat type, and abundance of key macroinvertebrate taxa. A total of 6554 fishes representing four species belonging to the family Cyprinidae were caught. A higher total fish abundance was recorded from Gereb Tsedo (4870; 74.3%) than from Elala stream (1684; 25.7%). Taking both streams together, the overall total relative fish abundance was significantly higher in pools (53%) than in runs (35%) and in riffles (12%) at P < 0.05. Species-wise comparisons showed that 71%, 15%, 13%, and 1% of the pool fish community were occupied by Garra blanfordii, Garra ignestii, Garra dembecha, and Garra aethiopica, respectively. Stream type, habitat type, and key macroinvertebrate taxa each explained a significant proportion of the variation in fish abundance. Based on the variation partitioning approach, fish abundance was higher in Gereb Tsedo stream (P < 0.01). Moreover, fish abundance increased with pool habitat type (P < 0.01) and with availability of key macroinvertebrate taxa (P < 0.01). Fish abundance differed between stream types, among habitats and among key macroinvertebrate taxa availability. Among the factors, habitat type was the most important driving factor behind variation among fish abundances, and pool supports the highest fish abundance.

Fisheries and Aquatic Sciences