This study uses old aerial photographs, current high resolution satellite images and ground truthing to analyze the patterns and dynamics of Mida Creek mangrove forest changes over 41 years from 1969-2010. A non-distractive method was used to collect data on 25 sample plots and 934 trees were measured to estimate the above ground biomass and carbon stock of the forest. General published allometric equations with variables of Diameter at Breast Height (DBH) and wood density (ρ) which were species specific were used to estimate above ground biomass. A decline in mangrove cover (16%) took place between 1969 and 1989 and between 1989 and 2010 an increment was observed in mangrove cover (1452.5 ha in 1989 to 1655.7 ha in 2010). Signs of degradation within the mangrove forest were observed in 2010 in which the degraded land covered 8.8 ha. The total above ground biomass and carbon estimated on the 25 plots was 296.14 ton•ha −1 and 148.07 ton•ha −1 respectively. Mida Creek mangrove forest is largely dominated by the presence of Rhizophora mucronata and Ceriop tagal and the regeneration of these two species is very high. If the present dominance of the two species continues it will affect the species composition of the current mangrove forest. This study recommends a better management plan for the mangrove forest through increasing involvement of the surrounding communities. Furthermore, there should be a way to control selective and illegal cutting of mangroves and promote other species of trees for domestic and commercial use to reduce the high dependency on the use of mangroves for construction purposes.
Eastern Kenya, a semi-arid region, is characterized by low and erratic rainfall, high temperatures, and low soil fertility. Climate change has further worsened the situation leading to frequent droughts and hence increased food insecurity. Traditional crops like finger millet are possible solutions to combating changing climate due to their drought resistance nature, ability to produce high yields with little inputs and high nutritional content. It is against this backdrop that a survey was carried out in Mwala and Katangi divisions of Machakos and Kitui counties, respectively, to assess farmer's perception on climate change, coping and adaptation mechanisms in finger millet production systems in smallholder farming systems of lower eastern Kenya. Data was collected, using semi-structured questionnaire, from 120 farmers i.e. 60 in each division. A stratified random sampling procedure, with location as a stratum was used to select respondent's households. A computer random number generator was used to select number of households in each stratum. Maize and beans were the most popular crops grown by over 98% of the farmers in both sub-counties. Farmers also grew drought tolerant legumes; cow peas, green grams pigeon peas and cereals; sorghum and finger millet. Temperature rise was ranked highest with 88% and 98%, followed by prolonged drought with 70% and 72%, irregular rainfall at 69% and 81% and increased wind intensity at 22% and 28% at Machakos and Kitui, respectively, as aspects of climate change perceived by farmers. Farmers had taken up early planting at 88.6% and 93.7%, use of organic inputs at 89% and 92%, introduced new tillage practices, by applying ridges and furrows and tied ridges at 45% and 54%, and by adopting irrigation at 13%, and 9%, as coping strategies to climate change in Machakos and Kitui, respectively.It can be concluded that farmers in Machakos and Kitui are aware of climate change and its negative effects on crop production. In a bid to minimize crop loss and food insecurity, they have taken up various soil moisture conservation and soil fertility enhancement technologies.
Variation in nutritional and anti-nutritional contents among six finger millet genotypes was determined. Improved finger millet
The current study, conducted in semi-arid Machakos and Kitui Counties of Kenya, simulated effect of climate change (CC) on finger millet yield under different soil fertilizer inputs (SFI), tillage practices (TP) and projected CC scenarios using the Agricultural Production Systems Simulator (APSIM) model. A randomized complete block design with split plot arrangement was employed. Main plots were TP; oxen plough-OP, ridges and furrows-RF with SFI; Farm yard manure-FYM, Triple super phosphate-TSP + Calcium Ammonium Nitrate-CAN (TSP+CAN) and no fertilizer input as splitplots. The CC scenarios considered were; Current Rainfall (R0) and Temperature (T0) provided the baseline, R1 (R0+10% increase in rainfall), R2 (R0-10% decrease in rainfall), T1 (T0 + 20C) and T2 (the combined effects of 10% decrease in rainfall and 20C increase in temperature (-10%+20C). Significantly (P≤0.001) higher finger millet yields were obtained in TSP+CAN treated plots compared to FYM and control in both Kitui (with higher yields) and Machakos. Comparatively, finger millet yields were well simulated with moderate RMSE (1.04, 0.94) values in OP and RF in Kitui and low values (0.18) in OP in Machakos). Simulated finger millet yields mirrored measured yields, and were higher in Kitui (RF) than Machakos (OP) with TSP+CAN recording highest simulated yields compared to FYM and control. R1 (R0+10% rainfall) registered significantly high finger millet yields under OP and RF with application of TSP+CAN in both sites. The lowest finger millet yields, across sites were noted in T2 (-10% rainfall+2 0 C), in decreasing order; TSP+CAN; FYM and control under OP and RF. Finger millet yields measured and simulated, insitu and across CC scenarios, indicated that application of TSP+CAN under conservation tillage practices (RF in Kitui and OP in Machakos) consistently gave superior yields compared to FYM and control. In the event of change of climate favouring increased rainfall (R1), finger millet grown under RF and OP with application of TSP+CAN may have the potential to adapt to climate change and enhance food and nutritional security. Further studies, mainly focusing on moisture conservation and breeding of drought tolerant crops, are nonetheless recommended to generate possible CC adaptation strategies under R2, T1 and T2 possible climate change scenarios in semi-arid regions of Kenya.
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