Funders and governments are promoting climate-smart agriculture (CSA) as key to agricultural adaptation under climate change in Africa. However, with its progressions still at the policy level and framework description, there is a need to understand the current developments and activities conducted within the CSA research field. We conducted a scientific mapping and analyses of CSA research studies in Africa to understand the (i) thematic trends, (ii) developments, (iii) nature of collaboration networks, and (iv) general narratives supporting the adoption and application of CSA in Africa. Results show that several African countries had endorsed CSA as an approach to addressing agricultural productivity challenges, supporting adaptation strategies, and building resilience to climate change. However, a majority do not have national Climate-Smart Agriculture Investment Plans (CSAIPs). Additionally, CSA research in Africa is still developing, with only a few countries dominating the research outputs. For a successful implementation of CSA, a framework provided by the CSAIPs must be established to guide the processes. This will provide a framework to guide the integration of government programs, policies, and strategic plans by combining other inputs from stakeholders to support decision making and implementation of CSA.

Research on Land Use and Land Cover (LULC) dynamics, and an understanding of the drivers responsible for these changes, are very crucial for modelling future LULC changes and the formulation of sustainable and robust land-management strategies and policy decisions. This study adopted a mixed method consisting of remote sensing and Geographic Information System (GIS)-based analysis, focus-group discussions, key informant interviews, and semi-structured interviews covering 586 households to assess LULC dynamics and associated LULC change drivers across the Dedza district, a central region of Malawi. GIS-based analysis of remotely sensed data revealed that barren land and built-up areas extensively increased at the expense of agricultural and forest land between 1991 and 2015. Analysis of the household-survey results revealed that the perceptions of respondents tended to validate the observed patterns during the remotely sensed data-analysis phase of the research, with 57.3% (n = 586) of the respondents reporting a decline in agricultural land use, and 87.4% (n = 586) observing a decline in forest areas in the district. Furthermore, firewood collection, charcoal production, population growth, and poverty were identified as the key drivers of these observed LULC changes in the study area. Undoubtedly, education has emerged as a significant factor influencing respondents’ perceptions of these drivers of LULC changes. However, unsustainable LULC changes observed in this study have negative implications on rural livelihoods and natural-resource management. Owing to the critical role that LULC dynamics play to rural livelihoods and the ecosystem, this study recommends further research to establish the consequences of these changes. The present study and future research will support decision makers and planners in the design of tenable and coherent land-management strategies.

Drought is a creeping phenomenon whose effects evolve with time, yet the start and end is often only clear in the hindsight. The present study assessed drought conditions using two categories of drought indicators computed from precipitation data sets measured by weather stations across the Western Cape Province, South Africa for the period 1985 to 2016. The first category was the Standardized Precipitation Index (SPI) accumulated over 3-, 6- and 12-months (hereafter of SPI-3, SPI-6 and SPI-12 respectively). The second category consists of the four Drought Monitoring Indicators (DMI) i.e., Drought Duration (DD), Severity (DS), Intensity (DI) and Frequency (DF). Firstly, analysis of SPI-3, SPI-6 and SPI-12 illustrate that between 1985 and 2016, the Western Cape Province experienced recurrent mild drought conditions. This suggests that the drought conditions experienced during 2015/2016 hydrological year (hereafter current) in the Western Cape Province is a manifestation of past drought conditions. Secondly, analysis of trends in DMI series depict a noticeable spatial-temporal dependence wherein the southern and western regions experienced more severe droughts compared to the eastern and northern regions of the Western Cape Province. Results also show that the DMI trends exhibit up to ~8% variability over the past decade. Overall, the current drought conditions in the Western Cape Province continues to adversely affect agricultural production while the water reservoirs are at below 30% capacity implying that the socio-economic impacts of these droughts will continue to reverberate for many months to come. Though the on-going drought conditions in the Western Cape Province is a regular part of nature’s cycle, analysis of historical drought characteristics based on drought indicators is an important first step towards placing the current drought conditions into perspective, and contribute to triggering action and response thereof. All these lay the foundation for drought monitoring and contribute towards the development of drought early warning.

The Free State (FS) and North West (NW) Provinces are often hard hit by droughts with impacts on water availability, farm production and livestock holdings. The South African government declared the two Provinces drought disaster areas in the 2015/2016 hydrological year. This is a major drawback, since both the Provinces play an important role to South African economy as they are a haven to agricultural production and have major water reservoirs in South Africa. This study was undertaken to investigate the historical evolution of drought within the FS and NW Provinces over the past 30 years. The Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) calculated based on monthly meteorological data from 14 weather/climate stations within the FS and NW Provinces were used to explore and characterize variation in drought intensity, duration, frequency and severity in FS and NW Provinces during 1985–2015. Results indicate that there exist localized positive and negative trends with spatial dependence across the selected stations. In particular, about 60% of the weather stations exhibiting a decreasing trend are located in FS Province, suggesting that FS has being experiencing increasing drought during the analyzed period compared to NW Province. Results from the analysis of drought evaluation indicators (DEIs) calculated from SPEI suggest that drought severity and frequency was more pronounced in FS while the intensity of the drought was more in NW Province during 1985–2015. In addition, based on SPEI calculations, moderate drought occurrences increased during 1985–1994 and 1995–2004 periods and decreased thereafter (2005–2015) in both Provinces. Drought classification based on parameters derived from SPEI produced similar results for mild drought occurrences during the same time scales.

The use of crop modeling as a decision tool by farmers and other decision-makers in the agricultural sector to improve production efficiency has been on the increase. In this study, artificial neural network (ANN) models were used for predicting maize in the major maize producing provinces of South Africa. The maize production prediction and projection analysis were carried out using the following climate variables: precipitation (PRE), maximum temperature (TMX), minimum temperature (TMN), potential evapotranspiration (PET), soil moisture (SM) and land cultivated (Land) for maize. The analyzed datasets spanned from 1990 to 2017 and were divided into two segments with 80% used for model training and the remaining 20% for testing. The results indicated that PET, PRE, TMN, TMX, Land, and SM with two hidden neurons of vector (5,8) were the best combination to predict maize production in the Free State province, whereas the TMN, TMX, PET, PRE, SM and Land with vector (7,8) were the best combination for predicting maize in KwaZulu-Natal province. In addition, the TMN, SM and Land and TMN, TMX, SM and Land with vector (3,4) were the best combination for maize predicting in the North West and Mpumalanga provinces, respectively. The comparison between the actual and predicted maize production using the testing data indicated performance accuracy adjusted R² of 0.75 for Free State, 0.67 for North West, 0.86 for Mpumalanga and 0.82 for KwaZulu-Natal. Furthermore, a decline in the projected maize production was observed across all the selected provinces (except the Free State province) from 2018 to 2019. Thus, the developed model can help to enhance the decision making process of the farmers and policymakers.

Notwithstanding the dispersed nature of the water, energy and food (WEF) nexus scholarship in the African continent, its strategic importance to the African agenda has gained widespread attention in research and planning circles. In this regard, the bibliometric science mapping and content analysis of the WEF nexus scientific publication trends, the conceptual, intellectual and social structures, as well as the inherent paradigmatic shifts in the WEF nexus body of knowledge in the African continent have been undertaken, using the nexus body of literature accessed from the Web of Science and Scopus core collection databases. The review results confirmed that, whilst the WEF nexus scholarship has expanded since 2013, there is also evidence of growth in the conceptual, intellectual and social structures of the WEF nexus in the African continent. These shifts have resulted in the emergence of hot topics (subfields) including modelling and optimization, climate variability and change, environmental ecosystem services sustainability, and sustainable development and livelihoods. The review further determined that these structures have evolved along two main perspectives of WEF nexus research development, i.e., the interdisciplinary and transdisciplinary domains. In support of the interpretation of the visual analytics of the intellectual structure and changing patterns of the WEF nexus research, the shifts in positivist, interpretivist and pragmatic paradigmatic perspectives (these are underpinned by the ontology, epistemology, and methodology and methods) are considered when explaining WEF nexus research shifts: (a) From the unconnected silo paradigms that focus on water, energy and food (security concerns) to interconnected (and sometimes interdependent or nested) linkages or systems incorporating environmental, social-economic and political drivers (also viewed as subfields) in a bid to holistically support the Sustainable Development Goals (SDGs) across the African continent; and (b) in the evaluation of the WEF nexus scholarship based on novel analytical approaches. We contend that whilst the theories of science change underpin this apparent expansion, the macro-economic theory will find use in explaining how the WEF nexus research agenda is negotiated and the Integrative Environmental Governance (IEG) is the duly suited governance theory to bridge the inherent disconnect between WEF nexus output and governance processes uncovered in the literature. Overall, operational challenges and opportunities of the WEF nexus abound, transitioning the WEF nexus research to practice in Africa, motivating the need to take advantage of the scholar–practitioner research underpinnings, as contemplated in the transdisciplinary research approach, which is characterised by the dual quest for new knowledge and considerations of use. Yet, there is need for more coordinated and collaborative research to achieve impact and transition from WEF nexus thinking to WEF nexus practice.