Carbon Sequestration in Agroforestry Technologies as a Strategy for Climate Change Mitigation

Worldwide agroforestry has been recognized as a potential greenhouse gases mitigation strategy under Kyoto protocol. And this is due to its potential in carbon sequestration. There are several agroforestry technologies with different rate in carbon sequestration. In that respect carbon sequestration can depend on type of technology, climate, time since land use change and previous land use. Our knowledge in this topic from the tropical countries such as Tanzania is how ever very limited. To address this challenge this study was undertaken in Kilombero District where the local community are practicing various agroforestry technologies. The objective of this study was to understand the carbon sequestration in different trees species in agroforestry technologies and also to understand which agroforestry technology provide the greatest benefit in term of carbon sequestration. Ecological survey was conducted and a total of 90 plot engaged in different agroforestry technologies were randomly selected from three villages of different altitudinal range. Pivot table was used in analysis and allometric equation was used for computing biomass and carbon. The result shows that Mangifera indica contributed highest carbon over all the tree species encountered during ecological survey with 189.88 Mg C ha−1. Home garden, Mixed intercropping, Parkland and Boundary with 19 514.19 MgCha−1, 648.44MgCha−1,144.79 MgCha−1 and 139.29 Mg C ha−1 respectively were the agroforestry technology practiced in Kilombero. From the results Home garden contributed more to carbon sequestration and this study results can be used to inform practitioners and policy makers on the most effective agroforestry technologies for carbon sequestration since agroforestry technologies are expected to play important role as climate change mitigation strategy.

Determinants of farmers’ adoption of agroforestry technology in Ibarapa Area of Oyo State, Nigeria

This study examined the various forms of agroforestry technologies adopted by the farmers as well as assessed the factors influencing the adoption of agroforestry technologies among farmers in the study area. A multi-stage sampling technique was used to select the respondents from the study area. Both descriptive statistics such as frequencies and percentages as well as inferential statistics such as Logistic Regression model were used in the study. From the study, it was discovered that adopters of agroforestry technology accounts for 42.47%, while non-adopters accounted for 57.53% of the sampled respondents. The result further shows the different forms of agroforestry practices adopted by the farmers in the study area which includes boundary planting, multipurpose trees/shrubs, wind breaks and live fencing. The result of the analysis of the factors that influence the adoption of agroforestry technologies among farmers from the logistic regression analysis revealed that access to extension services, age, education, farming experience, farm size and gender were positive and significant factors in determining the adoption of agroforestry technologies among the farmers.

Adoption of Coffee Shade Agroforestry Technology and Shade Tree Management in Gobu Seyo District, East Wollega, Oromia

Coffee production in the form of agroforestry practices is the most important management approach to improve the livelihoods of the farming community. This study was conducted to assess factors affecting the adoption of the technology, its socioeconomic and environmental benefits, and the management practices related to the technology. Out of eight kebeles in the district, two kebeles were selected purposively based on the existing and extensive agroforestry practices. Four villages were selected randomly. Based on the preidentified criteria as coffee growers and nongrowers, coffee growers were selected purposively. Then a total of 120 households were selected by Simple Random Sampling Method. Data were collected by using structured interview and field observation. The data were analyzed by using descriptive statistics analysis. The logit model was used to identify the factors affecting the adoption of coffee shade agroforestry technology. The results of this study showed that adoption of coffee shade agroforestry technology had a positive relationship and was statistically significant at 1% level with age and area covered by coffee production, while household composition and training were at 5% level. Education level, land holding, and extension services also had positive relationship, but it was not statistically significant. The farmers in the study area mentioned other benefits of these technologies such as for animal feed, firewood and construction materials, medicinal purpose, erosion control, honey bee production, and soil fertility enhancement. Different management activities were also identified in the area (such as composting, pruning, watering, and weeding). Coffee shade agroforestry technology was important to diversify the agricultural products, to solve the problem of livelihood, and adds economic and environmental benefits.

Factors Affecting Adaptation to Climate Change through Agroforestry in Kenya

The environmental effects of climate change have significantly decreased agricultural productivity. Agroforestry technologies have been applied as a solution to promote sustainable agricultural systems. This study evaluates the factors influencing the adoption of agroforestry technology in Kenya. A multistage sampling technique was employed to collect data from 239 households in West Pokot County, Kenya. A Probit model and K-means algorithm were used to analyze the factors affecting farmers’ agroforestry technology adoption decisions based on the sampled households’ socio-economic, demographic, and farm characteristics. The study found that the total yield for maize crop, farm size, extension frequency, off-farm income, access to training, access to credit, access to transport facilities, group membership, access to market, gender, distance to nearest trading center, and household education level had significant effects on the adoption of agroforestry technologies. The findings of this study are important in informing policy formulation and implementation that promotes agroforestry technologies adoption.

Gliricidia Agroforestry Technology Adoption Potential in Selected Dryland Areas of Dodoma Region, Tanzania

Declining soil fertility is one of the major problems facing producers of field crops in most dryland areas of Sub-Saharan Africa. In response to the declining soil fertility, extensive participatory research has been undertaken by the World Agroforestry (ICRAF) and smallholder farmers in Dodoma region, Tanzania. The research has, amongst others, led to the development of Gliricidia agroforestry technology. The positive impact of Gliricidia intercropping on crop yields has been established. However, information on farmers’ willingness and ability to adopt the Gliricidia agroforestry technology on their farms is limited. This study predicts the adoption of Gliricidia agroforestry and conventional mineral fertilizer use technology. Focus Group Discussions (FGDs) were conducted with groups of farmers, purposively selected based on five sets of criteria: (i) at least 2 years of experience in either trying or using Gliricidia agroforestry technology, (ii) at least 1 year of experience in either trying or using the mineral fertilizer technology (iii) at least 10 years of living in the study villages, (iv) the age of 18 years and above, and (v) sex. The Adoption and Diffusion Outcome Prediction Tool (ADOPT) was used to predict the peak adoption levels and the respective time in years. A sensitivity analysis was conducted to assess the effect of change in adoption variables on predicted peak adoption levels and time to peak adoption. The results revealed variations in peak adoption levels with Gliricidia agroforestry technology exhibiting the highest peak of 67.6% in 12 years, and that the most influential variable to the peak adoption is the upfront cost of investing in Gliricidia agroforestry and fertilizer technologies. However, in Gliricidia agroforestry technology most production costs are incurred in the first year of project establishment but impact the long term biophysical and economic benefits. Moreover, farmers practicing agroforestry technology accrue environmental benefits, such as soil erosion control. Based on the results, it is plausible to argue that Gliricidia agroforestry technology has a high adoption potential and its adoption is influenced by investment costs. We recommend two actions to attract smallholder farmers investing in agroforestry technologies. First, enhancing farmers’ access to inputs at affordable prices. Second, raising farmers’ awareness of the long-term environmental benefits of Gliricidia agroforestry technology.

Making the case for institutional support on designing agroforestry technology models for rehabilitating critical lands

Land and forest management practices in developing countries have resulted in millions of hectares of degraded lands. This is caused by policy implementation unable to synergize between conservation-ecological goals, and the economic needs of farmer households. This study aims to showcase a model for bringing together economic and ecological interests more closely in line with one another. Furthermore, the study also presents an institutional structure of a program that could help to establish agroforestry-based land rehabilitation policies. The research employed includes a combination of Farming Income Analysis and Interpretative Structural Modeling Analysis. The results show that farming income, when employing agroforestry technology is higher than non-agroforestry approaches. Furthermore, agroforestry technology supports critical land rehabilitation and provides conditions for longer term sustainability. Therefore, a programmatic institutional approach is needed to support these dual goals. We identify that a programmatic approach would include: (1) applying conditions of an agroforestry system as a holistic structured unit, (2) improvement of farmer knowledge and skills, (3) increasing the role and capacity of relevant institutions, (4) improving coordination between sectors, (5) developing conservation agriculture systems, (6) improving bureaucratic support systems, and (7) strengthening control and supervision functions. These elements imply that implementation of agroforestry technology requires institutional support in designing policy for critical land rehabilitation, of which would have significant economic and ecological outcomes on critical lands.