Abstract
Agriculture is the most important sector in Uganda’s economy, but it continues to experience challenges of erratic rainfall variability and environmental degradation. This paper is situated within post-structuralist geographical thought to (i) classify CSA practices and (ii) empirically quantify the relative importance of household socio-economic factors that structure the adoption of CSA practices in drylands in Uganda. The study was carried out in Nakasongola District in Central Uganda, and 143 geo-referenced questionnaires were used to collect relevant farming household and CSA data. Results indicated that timely planting, crop rotation, intercropping, and proper spacing were the most prevalent CSA practices, while rotational grazing, mulching, fertilizer use, and use of pesticides and herbicides were the least prevalent practices. Principal component analysis (PCA) generated a factor solution, and the components were clustered into three CSA practices: crop management, conservation agriculture, and land management practices. There are important differences in the propensity of households living in village settings to adapt. Parameter estimates indicated that the size of household, household income diversity index, access to pesticide uses, fertilizers, extension services, domestic water sources, improved seeds, credit, main decision-maker in the household, and education levels of the head of the household significantly influence (p < 0.05) the adoption of CSA practices.
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Notes
- 1.
It has been realized for some time that rural people no longer remain confined to crop production, fishing, forest management, or livestock rearing but combine a range of occupations (Khatun and Roy 2012). This kind of practice, sometimes referred to as livelihood diversification, is one of the most remarkable characteristics of rural livelihoods (Gautam and Andersen 2016). Given as a process by which rural families construct a diverse portfolio of activities and social support capabilities in their struggle for survival and improvement in their standards of living (Ellis 1998), it was important to measure the level of diversification of farming households or the overall degree of income diversity/diversification using a single index.
There are several income diversification and household labor allocation indices, and some of these are given by Gebreyesus (2016), McNamara and Weiss (2001), and Zhao and Barry (2013). They include the Herfindahl index, ogive index, inverse Simpson index, Shannon index (H), Shannon equitability index, entropy index, modified entropy index, composite entropy index (Gebreyesus 2016), USA Today Diversity Index (Meyer and McIntosh 1992), Berger-Parker index, Shannon-Weaver index, and Margalef index (FAO 2015), among others. These indices or approaches can be divided into two groups. One group contains one-dimensional indices, which include indicators that count the number of activities or evaluate changes in the volumes of different divisions. The other group measures diversification based on two dimensions considering both the number of areas of activities and their relative volumes of turnover (Zhao and Barry 2013). Most of these indices require data on the proportion of income from one activity relative to all other activities. Given that, during the data collection exercise, we found difficulties in estimating incomes from individual activities that the farming households engaged in, except for reports of the number and types of activities, we constructed the income diversity index for this study using the Margalef index (MI) given as:
$$ \mathrm{D}i=\frac{\left[{S}_i-1\right]}{In\left[{N}_i\right]} $$(3)where:
Ni = total count of income sources that support household livelihoods
Si = number of income sources for each individual household i (namely, a count)
The index has a lower limit of zero if only one unit of diversity is observed.
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Acknowledgments
This research forms part of the Climate and Water Resources Centre, Department of Geography, Geo-informatics and Climatic Sciences (http://www.mak.ac.ug/geography), research agenda. We would like to thank the Regional Capacity Building for Sustainable Natural Resource Management and Agricultural Productivity under Climate Change (CAPSNAC) for funding this study. Any errors herewith are the responsibility only of the authors, and this paper reflects the opinions of the authors and not the institutions which they represent or with which they are affiliated.
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Nakabugo, R., Mukwaya, I.P., Geoffrey, S. (2019). Adoption of Climate Smart Agricultural Technologies and Practices in Drylands in Uganda: Evidence from a Microlevel Study in Nakasongola District. In: Bamutaze, Y., Kyamanywa, S., Singh, B., Nabanoga, G., Lal, R. (eds) Agriculture and Ecosystem Resilience in Sub Saharan Africa. Climate Change Management. Springer, Cham. https://doi.org/10.1007/978-3-030-12974-3_24
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