Browsing by Author "Ntawuruhunga, Donatien"

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Farmers’ knowledge, attitude, and motivation for adoption of climate-smart agroforestry in two contrasting agroecosystems of Rwanda
(Elservier, 2025) Ntawuruhunga, Donatien; Ngowi, Edwin Estomii; Mangi, Halima Omari; Salanga, Raymond John; Leonard, Kenneth Lynch
Globally, the experiences show that climate-smart agroforestry (CSAF) can contribute to sustainable agricultural growth and rural transformation while tackling climate change. This study evaluated the interplay between farmers’ knowledge, attitude, and motivation to adopt CSAF. The study used data from 381 farmers surveyed in Bugesera and Rulindo regions, Rwanda. Bugesera, in the semi-arid savannah lowlands, and Rulindo, in the temperate central highlands, were purposively selected for their distinct physiographic features. A questionnaire was used to collect the data and descriptive statistics, Pearson correlation, and binomial logistic regression were performed for data analysis. The results from the correlation analysis showed that various revealed factors, including gender, civil status, education, household size, household poverty level (ubudehe), farm size, farmers’ experience in CSAF, ownership of radio and mobile phone, livestock herd size, farm-river distance, training, and extension visits, influenced farmers’ knowledge in adopting CSAF. The most significant positive correlation was found between owning a mobile phone and farmers’ knowledge, while the weakest positive correlation existed between farmers’ gender and their knowledge of CSAF. These factors equally affected farmers’ attitudes, except for statistically insignificant gender. The most significant positive correlation was between owning a mobile phone and farmers’ attitudes, while the weakest was between extension visits and farmers’ attitudes towards CSAF. Further, results revealed a positively significant relationship between the farmers’ ages and their motivation to adopt CSAF. Additionally, the binomial logit regression analysis showed that farmers knowledgeable with CSAF were 2.5 times more likely to practice CSAF than farmers without such knowledge. Moreover, being motivated by CSAF benefits increased the likelihood of adopting CSAF by 0.6 times compared to unmotivated farmers. By filling the gap in understanding farmers’ knowledge, attitudes, and motivations toward CSAF adoption, this study contributes to advancing sustainable agricultural practices in Rwanda. It provides a blueprint for similar initiatives elsewhere.
Geospatial characterization of climate-smart agroforestry in two contrasting physiographic zones of Rwanda
(Research square, 2023-05-10) Ntawuruhunga, Donatien; Ngowi, Edwin Estomii; Mangi, Halima Omari; Salanga, Raymond John; Shikuku, Kelvin Mashisia
The unmatched world population growth with production has increased human demand causing starvation consequent to food shortage. Climate-smart agroforestry (CSAF) among other options can enhance productivity, improve income and food security, and stabilize the environment. This study investigates the land suitability for CSAF in the Bugesera and Rulindo regions of Rwanda. After searching the literature and the local expert knowledge and opinions, nine variables were considered for investigation in the study viz. elevation, slope, soil type, rainfall, temperature, LU/LC, distance from roads and trade centers, and landslide risks. The analysis used two commonly known techniques (AHP and GIS) integrated to classify and sort out the suitable land for CSAF practices and development. Results identified three CSAF suitability zones, ranging from 1,662.82ha (1.60%) as most suitable and 90,123.78ha (86.62%) suitable to 12,262.50ha (11.78%) unsuitable zones in Bugesera. In Rulindo, suitability zones range from 709.92ha (9.69%) as most suitable and 6,514.56ha (88.92%) suitable to 102.24ha (1.39%) unsuitable land for CSAF. Results further showed that the available means suitable land for CSAF are 34,683.03ha in Bugesera (34,683.03 ± 48,304.71) and 2,442.24ha in Rulindo (2,442.24 ± 3,539.79). Land suitability scores for CSAF largely varied across sites (F = 1.33, p = 0.31). Cross-validation using ground-truthing information (field visit and collection of GPS-based ground coordinates of random locations of actual CSAF) and evidence from literature about existing CSAF mostly supported the generated CSAF suitability maps (nearly 91% of ground-based locations supported the model output). These results reveal the extent of implementation of CSAF practices in the targeted areas. In areas such as Bugesera and Rulindo where investigations on CSAF are scanty, suitability maps in this study would allow identifying sites with high potential for CSAF. The cross-site suitability mapping and analysis for CSAF would provide an opportunity to policy-makers for location-specific land use planning for expanding and implementing CSAF-based models. Those would assist in addressing ecosystem restoration, optimum farm production, increased income, and enhanced food security. This study will pave the way for further studies on the potential CSAF and possibly required interventions for the assessed areas.