Rapid expansion of commercial horticulture production and related activities contribute to declining surface water quality. The study sought to understand the impacts on select rivers in Laikipia and Meru, production hotspots. The specific aims were (1) to identify prevailing surface water quality by examining variations of 14 physico-chemical parameters, and (2) to categorize measured surface water quality parameters into land use types highlighting potential pollutant source processes. Water samples were collected in July and August 2013 along 14 rivers in the study area. The data were analyzed using principal component analysis (PCA) and discriminant analysis (DA). Principal components (PCs) explained 70% of the observed total variability of water quality, indicating a prevalence of heavy metal traces (cadmium, phosphate, and zinc). These were linked to the rigorous use of phosphate fertilizers and copper-based agrochemicals in intensive farming. DA provided four significant (p < 0.05) discriminant functions, with 89.5% correct assignment enabling the association of land use with observed water quality. Concentrations of dissolved solids, electro-conductivity, and salinity spiked at locations with intensive small-scale and large-scale horticulture. Understanding the impacts of intensive commercial horticulture and land use practices on water quality is critical to formulating ecologically sound watershed management and pollution abatement plans.
This study analysed socio-economic determinants for inputs use in major bean corridors in Kenya. It comprised 417 respondents sampled from four major bean corridors. A structured questionnaire was used in data collection. Probit model was used to assess determinants of input use among the bean-farming households. From the results, 74% of respondents were male with a mean age of 48.6 years. The probability of using agricultural inputs increased with education level and income from crop sales. Fertilizer was mainly used in Bomet (73%) and Narok (74%) counties. Eighty-five percent planted recycled seeds. Education level and Income from crops positively influenced inputs use. It was concluded that education level, incomes from sale of crops, livestock and livestock products, and farm income influenced use of inputs. As a recommendation, Capacity building on merits of input use and promotion of public-private partnerships to strengthen input supply system would enhance increased input use by smallholder farmers.
Expansion and heterogeneous clustering of commercial horticulture within the central highlands of Kenya after the mid-1990s impact watersheds and the sustainable resource management. This is distressing since climate conditions for world horticultural regions are projected to change, making such farming extremely difficult and costly to the environment. To understand the scope of impact on vegetation, the study evaluated (1) interannual variability in averaged normalized difference vegetation index (NDVI); (2) trends in average annual NDVI before and after 1990 -the presumed onset of rapid horticulture; and (3) relationship between the average annual NDVI and large-scale commercial farms, population density, and mean annual rainfall in subwatersheds. Time-series analysis of long-term Global Inventory Modeling and Mapping Studies NDVI data were analyzed as indicator of vegetation condition. NDVI trends before 1990s (1982-1989) and after 1990s (1990-2006) were evaluated to determine the slope (sign), and the Spearman's correlation coefficient (strength). Overall, results show considerable variations in vegetation condition due largely to mixed factors including intensive farming activities, drought, and rainfall variation. Statistical analysis shows significant differences in slopes before 1990 and after 1990 (p < 0.05 and p < 0.1 respectively). Negative (decline) trends were common after 1990, linked to increased commercial horticulture and related anthropogenic disturbances on land cover. There was decline in vegetation over densely populated subwatersheds, though low NDVI values in 1984 and 2000 were the effect of severe droughts. Understanding the linkage between vegetation responses to the effects of humaninduced pressure at the subwatershed scale can help natural resource managers approach conservation measures more effectively.
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