The agriculture sector is sensitive to climate change and the capacity of smallholder farmers in developing countries to adapt is limited. Similar to adoption of any development-oriented strategies, perception is prerequisite to successful adaptation of agricultural strategies against climate change effects. This study was conducted in the semi-arid Lower Gweru Communal area of Central Zimbabwe to sensitize smallholder farmers on climate change and to establish their perceptions of the projected climate of Zimbabwe by 2050. Data were collected during 2011 from a total of 60 farmers drawn from six villages in Mdubiwa and Nyama Wards. Farmers were selected using systematic random sampling from a households list and grouped into three wealth groups: resource rich; resource poor and intermediate. Focus Group Discussions were conducted with each group to investigate their perceptions of the projected climate by 2050 and their proposed adaptive strategies. Farmers perceived the projected climate to have negative effects on their livelihoods and there were no outstanding differences in the nature of responses across the three categories of farmers. Farmers' responses showed that they were concerned about crop and livestock productivity as well as availability of water resources, food and nutrition security and about their general well-being. The intermediate wealth group, which had more than half of its members above 70 years of age provided the least number of ideas for adaptations. Farmers also suggested how they could possibly counteract some of the predicted negative effects or maximize on positive effects. Strategies that were suggested by the farmers were largely concerned with cropping and tended to address water shortages. It was concluded that almost all strategies suggested by farmers were self-directed, rather than directed at authorities like government or donors to do something for them thus showing that farmers had the will power to deal with climate change themselves.

This study assessed the applicability of APSIM, a crop simulation model, to decisionmaking by small-scale resource-constrained farmers in Lower Gweru, Zimbabwe. Input data for APSIM were collected from 30 farmers through focus group discussions and resource allocation mapping. APSIM simulations were run to simulate the farmers' farming systems to establish model credibility and validate the model with the local data and to explore "what if" questions to discuss ways to improve maize yields in a below-normal season. After two years interacting with model outputs, semi-structured interviews were conducted with the farmers to assess their continued use of APSIM in decision-making, the form of information they value the most, and preferred sources of information. The study found a greater willingness to consider computerbased modeling because of the pressures of climate change and the waning adequacy of their indigenous systems. However, the study also found that farmers used APSIM when they saw for themselves its accuracy and relevance to their farming systems and found it useful for making decisions relative to climate variations. The study confirmed APSIM's limitations as the lack of accurate data, the need for expert support and access to computers, and found that indigenous indicators, although waning in reliability and accuracy, can be strengthened when revisited through a deliberate learning program designed to engage farmers in scientific enquiry. While preferring to obtain information from extension agents, farmers will not readily adopt significant changes unless they have hard facts that they themselves have participated in generating. Whether introducing a model like APSIM or other technologies, unless farmers are directly involved with its testing in the field they are unlikely to adopt what is offered.

It is well known that major changes in global food systems are needed when agriculture must meet the challenge of feeding a growing population and at the same time minimize global environmental impacts. Both these aims require optimal crop yields. This need applies crucially to staple foods, such as maize, and in developing parts of the world, such as much of Africa. Within-season rainfall will affect crop yields, and this paper, using simulations, investigates the effects of varying within-season daily rainfall distributions on potential maize yields. The results show that within-season distributions can affect maize yields in low-rainfall seasons, but yields are also dependent on the use of fertilizer. In average and aboveaverage rainfall seasons, within-season variance has little effect on maize yields. If within-season distributions affect crop yields in low-rainfall seasons, as shown here, then this finding could be important for understanding the impacts of possible changes in climate.

This study was conducted in Mapfungautsi forest to determine the extent of deforestation from the year 2000 (when no deforestation was detected by satellite imagery) up to 2020, as well as to gather perspectives from members of communities around the forest, on factors responsible for deforestation. A mixed method approach in the form of remote sensing techniques, questionnaires and key informant interviews was used to gather data. Findings indicated the extent of deforestation to be 4254ha (5%) and 10632ha (14%) after the first decade (2000 – 2010) and second decade (2000 – 2020) respectively. Of the cleared forest, the most affected vegetation cover type was the wooded grassland (84%) followed by bushland (31%) and wooded land (10%) after the 20-year period. Respondents identified political gain, expansion of jurisdictions of chiefs and population pressure as the social factors most responsible for accelerated deforestation in Mapfungautsi. Conversely, the identified economic factors mainly contributing to deforestation were agriculture, timber and firewood poaching. The study concluded that agriculture was the single most impactful factor responsible for deforestation as the main social factors (political gain and expansion of chieftaincy) worked in combination to invade and clear protected forests for settlement and agriculture (which is also the main livelihood source of local people). Consequently, any control measures to arrest deforestation in Mapfungautsi and any other protected forests for that matter, will require serious buy-in and will power from political and traditional leaders and other stakeholders like farmers and community members.

This study was conducted with agricultural extension agents of semi-arid Zimbabwe to gather their perceptions on innovation and technology adoption by small-scale resource-constrained farmers, as well as the effect of their working conditions on the quality of service delivery to small-scale farmers. Data was solicited through focus group discussions (FGDs) and semi-structured interviews (SSIs) with all the public agricultural extension agents operating in the study area. It was found that agents were mainly hampered by lack of in-service training, transport and poor remuneration. Of all disseminated technologies during the last 20 years, respondents assessed that 17% had very low adoption rate, 26% had low adoption, 17% had average adoption, 26% had high adoption and only 13% had very high adoption. Bulky, expensive and risky technologies like tractors, solar driers, metal silos and bee farming were among the least adopted whereas hybrid seeds and value addition were very highly adopted. Reasons for the very low adoption were noted to be lack of capital, markets and information support on how to use new technology. Despite these challenges respondents indicated that small-scale farmers had the capacity to innovate and to adopt technology in the form of indigenous knowledge, willingness and commitment to learn and improve productivity, and labor. Agents suggested the strengthening of farmer-extension-research linkages so that technologies could be developed from some successful indigenous innovations, where possible and also to ensure the development of technology tailor-made to the needs of small-scale farmers, resource-endowments and biophysical conditions of their farming communities.