Small-scale fish farmers in developing countries are faced with challenges owing to their limited information on aquaculture management. Nile tilapia farmers in Teso North Sub-County recorded lower yields than expected in 2009 despite having been provided with required inputs. Water quality was suspected to be the key factor responsible for the low yields. This study sought to assess the effects of earthen pond water physico-chemical parameters on the growth of Nile tilapia in six earthen fish ponds under semi-intensive culture system in Teso North Sub-County. The study was longitudinal in nature with pond water and fish being the units of analysis. Systematic sampling was used to select five ponds while a control pond was purposively selected based on its previously high harvest. Four ponds were fed by surface flow and two by underground water. Each pond was fertilized and stocked with 900 fry of averagely 1.4 g and 4.4 cm. Physico-chemical parameters were measured in-situ using a multi-parameter probe. Sixty fish samples were randomly obtained from each pond fortnightly for four months using a 10 mm mesh size and measured, weighed and returned into the pond. Mean range of physico-chemical parameters were: dissolved oxygen (DO) 4.86-10.53 mg/l, temperature 24-26°C, pH 6.1-8.3, conductivity 35-87 μS/cm and ammonia 0.01-0. 3 mg/l. Temperature (p = 0.012) and conductivity (p = 0.0001) levels varied significantly between ponds. Overall Specific Growth Rate ranged between 1.8% (0.1692 g/day) and 3.8% (1.9 g/day). Ammonia, DO and pH in the ponds were within the optimal levels for growth of tilapia, while temperature and conductivity were below optimal levels. As temperature and DO increased, growth rate of tilapia increased. However, increase in conductivity, pH and ammonia decreased fish growth rate. Temperature and DO ranging between 27 and 30°C and 5-23 mg/l, respectively, and SGR of 3.8%/day and above are recommended for higher productivity.

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The Sondu-Miriu Hydroelectric Power Project (SMHPP) is a run-of-the-river hydro-power project on the Sondu-Miriu River, Kenya. The part of the river studied: between the Sondu Bridge upstream, and Osodo Bay on L. Victoria, was divided into three zones; 1. Upstream of the dam, artificial lake approximately 5 km long; 15 -2 km wide, 2. Depleted section and, 3. Lower section. SMHPP caused part of river below the dam (depleted section) to reduce in volume during power generation. Since inception, construction and implementation of the project, concerns were raised that the project would result in loss of Labeo and Synodontis fishes which were singled out as most vulnerable. This investigation set to determine the effects of SMHPP on river's fishes; and focused on species diversity, abundance and distribution. An electrofisher was used in sampling. The data obtained was compared with those reported earlier, particularly a single previous report based on electrofishing. Fish biomasses were: Upper zone 4,583 g, depleted zone, 10,666 g and lower zone, 22,004 g respectively, with a total biomass of 37,253 g from fishing activity lasting for 429 min. Catch-effort data for each zone; types, numbers and weights are given, compared and discussed. Diversity was highest, Simpson's Diversity Index was 12.945 in the upper zone.

Anthropogenic activities are increasingly catalyzing natural climatic factors that drive land cover change at different spatial scales. Available land cover data of the Mara River basin however give a broader picture of the entire basin regardless of the heterogeneity that exists at the sub-catchment level. This study sought to establish sub-catchment specific information on land cover changes through examination of satellite images of four Mara River sub-catchments (Amala, Nyangores, Talek and Sand River) for the period 1987-2017. The relationship between temperature, rainfall and land cover was also computed. In addition, a household survey and focus group discussions were conducted in each sub-catchments to establish the socioeconomic impacts of land cover change on the community's wellbeing. Forest cover was dominant in Amala (39.8%) and Nyangores (43.7%) sub-catchments in 1987 but by 2017 crop lands had surpassed forest cover in the two sub-catchments, accounting for 53.2% and 45.7%, respectively. However, in Talek (52.8%) and Sand River (47.4%) sub-catchments, grassland was the dominant land cover type in 1987 and after the 30 year period, grasslands remained dominant in Sand River, while shrub land became dominant in Talek sub-catchment. A weak positive correlation was observed between rainfall and forest cover, shrub land and cropland, while a negative correlation was observed between rainfall and bare land. Average temperature showed a positive moderate correlation with bare land and built up areas. Analysis of survey data revealed that livestock keeping, temperature increase, type of trees, education level of household head and weak environmental laws were the main drivers of land cover change (P < 0.05), while decline in forest cover, crop failure and shift in planting seasons were attributed to climate change. Pearson correlation of annual precipitation against crop yield for the period 1987-2017 revealed How to cite this paper: Mngube, F.M.,

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