During the 1970s, when severe droughts affected West African farmers, cereal banks became popular in the region. However, things quickly became very quiet again about this type of food security scheme, probably also because many of the cereal banks failed. Scientific surveys addressing the topic are scarce. A study in The Gambia in 2014 investigated how such cereal banks function and what the important variables for their success are.

The Gambia National Agricultural Investment Plan (GNAIP) is the medium-term (2011-2015) strategic plan of the Government of The Gambia (GOTG) towards achieving the vision for the agricultural and natural resources (ANR) sector and food security in the country within the framework of the New Partnership for Africa (NEPAD) Comprehensive Africa Agriculture Development Programme (CAADP). It is aligned fully with the national goals of Vision 2020, and supports the realization of main national strategic programmes, including the Poverty Reduction Strategy Paper II (PRSP II 2007-2011) and the ANR Sector Policy (2010). The proposed interventions are expected to achieve at least eight percent growth in the agricultural sector in The Gambia and this combined with accelerated non-agricultural growth could stimulate the level of growth needed in the sector to transform the country’s rural areas and to significantly reduce poverty levels. The GNAIP formulation process was highly consultative and participatory from the grassroots at village level to the highest level policy making body at national level through district, regional and national consultative meetings. There were also consultations with ECOWAS and its specialized institutions to ensure that the document is consistent with the CAADP pillars.

The questionnaire is about current and future direct and indirect drivers of land use/cover change (LUCC), positive or negative impact of drivers of LUCC on food security and water security and trends of land cover and crop types under "business as usual"in the Upper East Region (UER). The questionnaire has been send by e-mail to researchers (experts) in Ghana who are doing or have done research on land use changes in the Upper East Region. The questionnaire is based on interviews with researchers in Ghana on driving forces of land use change in the Upper East Region, conducted in November 2013.

Innovation is essential for agricultural and economic development, especially in today’s rapidly changing global environment. While farmers have been recognised as one of the key sources of innovation, many studies on agricultural innovations continue to consider farmers as adopters of externally-driven technologies only. This thesis, in contrast, analyses the innovation-generating behaviour among rural farmers. Specifically, the study looks at the determinants, impacts and identification of farmer innovation. The study is based on primary data obtained from a survey of 409 smallholder farm households in the Upper East region of northern Ghana. Additional data were collected through an innovation contest and a stakeholder workshop conducted in the region. Employing recursive bivariate probit and endogenous treatment-regression models which control for selection bias, it was found that participation in Farmer Field Fora − a participatory extension approach with elements of the innovation systems perspective − is a key determinant of innovation behaviour in farm households. Other important determinants are education, climate shocks and risk preferences. These results are robust to alternative specifications and estimation techniques. The study also found no spillover effect of FFF on farmers’ innovation capacity and discussed its implications. Using endogenous switching regression and propensity score matching techniques, the effect of farmer innovation on household welfare was analysed. The results show that farmer innovation significantly improves both household income and consumption expenditure for innovators. It also contributes significantly to the reduction of food insecurity among innovative households by increasing household food consumption expenditure, reducing the length of food shortages, and decreasing the severity of hunger. However, the findings show that the positive income effects of farmer innovation do not significantly translate into nutritious diet, measured by household dietary diversity. The results also indicate that though households innovate mainly to increase production, their innovations indirectly contribute to building their resilience to climate shocks. Overall, the results show positive and significant welfare effects of farmer innovation. Through an innovation contest that rewards farmers’ creativity and a household survey, 48 outstanding innovations developed by smallholder farmers were identified in the study region. The innovations are largely extensive modification of existing practices or combination of different known practices in unique ways to save costs or address crop and livestock production constraints. While some of the identified innovations can be recommended or disseminated to other farmers, most of them may require further validation or research. The multi-criteria decision making analysis − based on expert judgement ¬− is proposed as a simple and useful method that can be applied in prioritising high-potential innovations. Using this method, it was found that among the most promising innovations involve the control of weeds, pest and diseases using plant residues and extracts, and the treatment of livestock diseases using ethnoveterinary medicines. In conclusion, this study provides empirical evidence that smallholder farmers develop diverse and spectacular innovations to address the myriad challenges they face. These innovations also contribute significantly to household well-being, hence, need to be recognised and promoted. An institutional arrangement that permits interactions and learning among stakeholders may be a potential option for strengthening farmers’ innovation capacity.

The dataset consists of socio-economic data obtained from the survey of 409 farm households in the Bongo, Kassena Nankana East and Kassena Nankana West Districts in Upper East Ghana. It also includes constructed data from the main dataset for the analysis of the drivers and impacts of farmer innovation. A description of all the variables in the data is also included.