The role of indigenous knowledge (IK) in adaptation to drought by agropastoral smallholder farmers in Uganda

44-52Majority of agro pastoral smallholder farmers in developing countries are characterised by low pay status, high illiteracy levels and are tied to cultural beliefs and spirits. These drawbacks have led them into using more indigenous knowledge as a way of adapting to droughts. This study explored the contribution of IK in enhancing farmer’s resilience to drought in crop and livestock production systems in semi-arid areas. The objectives were: (i) to examine the agro pastoral farmer’s perceptions of drought indicators and associated impacts and (ii) determinants for the adoption of indigenous knowledge drought adaptation responses. Socio-economic data was collected using oral interviews. The farmers (240) were selected using random sampling procedures and subjected to structured questionnaires and key informant guides. This study highlights that the droughts experienced were perceived to be more severe, recurrent and pervasive but also erratic. The IK drought signs were: flowering of wild plants, blowing of strong winds and appearance of flying and crawling insects. In crop-based systems, droughts reduced yields, caused plant stunted growth, increased incidences of diseases and invasive weed species. In livestock, droughts reduced surface water levels, lowered milk and beef yields, and increased diseases. The farmers reacted to droughts by practicing indigenous agro forestry, mulching, changing planting time, crop rotation and hoeing of trenches to control fires and pests/diseases. They also took their animals to wetlands for foraging and drew water for animals to drink. The uptake of IK drought adaptation practices was related to: household size, personal farming life experience, gender and age of the agro pastoral farmers. Therefore, employing IK drought adaptation responses is an important step towards increasing the resilience of agro pastoral smallholder farmers but also the conservation of IK for forthcoming generations

Stalk-eyed fly, Diopsis sp. population dynamics under varying temperature and Relative Humidity in rice ecosystems

This study was carried out to assess the stalk-eyed fly population dynamics under varying temperature and relative humidity in rice ecosystems of Uganda.Although the stalk-eyed fly (Diopsis sp.) has been observed in Ugandan rice fields, there is limited information on the fly’s population and its potential threat to rice production. This study assessed the stalk-eyed fly (Diopsis longicornis and Diopsis apicalis) population dynamics under varying temperature and relative humidity in rice ecosystems of Uganda. It was conducted in purposively selected small scale rice farming sub-counties in low land rain fed and irrigated rice agro-ecologies (Lake Victoria Crescent, Kasese transition zone and Northern moist farmlands). Diopsis sp. populations were monitored by sampling rice fields every 40 days for a period of 17 months. Weather parameters including air temperature and humidity were recorded by use of data loggers throughout the study period. R-statistical tool and MS Excel were used to assess the population dynamics and interactions of the diopsids. D. longicornis fly was dominantly abundant in rice fields of Lake Victoria Crescent and Northern Moist zones while D. apicalis was dominant in Kasese transition zone. There was significant mean count variations per survey for both species in all the agro-ecological zones with P-values of 0.000958 (D. longicornis) and 1.12e-12 (D. apicalis) in Lake Victoria crescent, 0.000473 (D. apicalis) and 0.0173 (D. longicornis) in Northern moist farmlands, 0.0188 (D. apicalis) and 0.0353 (D. longicornis) in Kasese transition zone. Temperature and relative humidity had a direct effect on the population of both species in Northern moist zone and only on D. apicalis in Kasese transition zone. The optimum/favorable temperatures for abundance were between 27oC and 29oC. Interpretation of the results? Integrated pest management strategies and introduction of improved Diopsis pest resistant rice varieties are some of the recommendations for managing the stalk-eyed fly populations in these rice ecosystems

Expansion of Commercial Sugarcane Cultivation among Smallholder Farmers in Uganda: Implications for Household Food Security

Understanding the impact of commercial agriculture in the face of global change is critical to support strategies that ensure food security and alleviate poverty among households. We assessed the contribution of commercial sugarcane cultivation to household-level food security among smallholder farmers in Busoga sub-region, eastern Uganda. Land use changes are motivated by quick commercial gains rather than sustained food production; a situation that influences food security. The majority of households cultivate few crop varieties, lack adequate and nutritious foods, and have inadequate income to purchase food to meet their needs. Inadequacy of food within some commercial sugarcane-cultivating households suggests that generating income does not necessarily increase food security. To cope with food insecurity, households offer labour in exchange for food, borrow food, ration food, and at times steal. This is exacerbated by increasing food crop failures, large family sizes, trade in food items, and declining availability of food and land for food production. Commercial sugarcane cultivation is the main driver of food insecurity but given its perceived economic benefits, future sugarcane plantations expansion in the region is probably inevitable. Therefore, future policy should be designed to provide triple-win strategies (i.e., food security, poverty alleviation, and climate change adaptation) that provide sustainable livelihoods

Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation

Climate models may be limited in their inferential use if they cannot be locally validated or do not account for spatial uncertainty. Much of the focus has gone into determining which interpolation method is best suited for creating gridded climate surfaces, which often a covariate such as elevation (Digital Elevation Model, DEM) is used to improve the interpolation accuracy. One key area where little research has addressed is in determining which covariate best improves the accuracy in the interpolation. In this study, a comprehensive evaluation was carried out in determining which covariates were most suitable for interpolating climatic variables (e.g. precipitation, mean temperature, minimum temperature, and maximum temperature). We compiled data for each climate variable from 1950 to 1999 from approximately 500 weather stations across the Western United States (32 degrees to 49 degrees latitude and -124.7 degrees to -112.9 degrees longitude). In addition, we examined the uncertainty of the interpolated climate surface. Specifically, Thin Plate Spline (TPS) was used as the interpolation method since it is one of the most popular interpolation techniques to generate climate surfaces. We considered several covariates, including DEM, slope, distance to coast (Euclidean distance), aspect, solar potential, radar, and two Normalized Difference Vegetation Index (NDVI) products derived from Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS). A tenfold cross-validation was applied to determine the uncertainty of the interpolation based on each covariate. In general, the leading covariate for precipitation was radar, while DEM was the leading covariate for maximum, mean, and minimum temperatures. A comparison to other products such as PRISM and WorldClim showed strong agreement across large geographic areas but climate surfaces generated in this study (ClimSurf) had greater variability at high elevation regions, such as in the Sierra Nevada Mountains

Regional Models of Diameter as a Function of Individual Tree Attributes, Climate and Site Characteristics for Six Major Tree Species in Alberta, Canada

We investigated the relationship of stem diameter to tree, site and stand characteristics for six major tree species (trembling aspen, white birch, balsam fir, lodgepole pine, black spruce, and white spruce) in Alberta (Canada) with data from Alberta Sustainable Resource Development Permanent Sample Plots. Using non-linear mixed effects modeling techniques, we developed models to estimate diameter at breast height using height, crown and stand attributes. Mixed effects models (with plot as subject) using height, crown area, and basal area of the larger trees explained on average 95% of the variation in diameter at breast height across the six species with a root mean square error of 2.0 cm (13.4% of mean diameter). Fixed effects models (without plot as subject) including the Natural Sub-Region (NSR) information explained on average 90% of the variation in diameter at breast height across the six species with a root mean square error equal to 2.8 cm (17.9% of mean diameter). Selected climate variables provided similar results to models with NSR information. The inclusion of nutrient regime and moisture regime did not significantly improve the predictive ability of these models