The impact of credit accessibility and information communication technology on the income of small-scale sugarcane farmers in Ndwedwe Local Municipality, KwaZulu-Natal Province, South Africa.

Introduction: Access to credit and information and communication technology (ICT) plays a pivotal role in enhancing the practices of small-scale sugarcane farmers, impacting their financial, social, and economic wellbeing. However, many small-scale farmers need help accessing these resources, thereby affecting their ability to generate sustainable income. This study aimed to assess the factors influencing the adoption of ICT and access to credit and their subsequent impact on small-scale farmers' income. Methods: Employing a multistage sampling technique, 300 small-scale farmers were selected as participants in the study. The recursive bivariate probit regression model was used to assess the factors affecting adoption ICT and a selectivity-corrected ordinary least square regression model was utilized to estimate the synergistic effect of ICT adoption and access to credit on the income of small-scale sugarcane farmers. Results and discussion: The findings revealed that approximately 77% of small-scale farmers had access to credit, while more than 80% had adopted ICT. The results derived from the recursive bivariate probit (RBP) regression model indicated that access to credit, education, and extension support positively and significantly influenced the adoption of ICT. Conversely, marital status and non-farm income exhibited a negative and significant influence on the adoption of ICT. Gender and marital status were positively and significantly associated with access to credit, whereas age, education, and non-farm income showed a negative and significant relationship on access to credit. Subsequently, a selectivity-corrected ordinary least square regression model analysis revealed that factors such as gender, marital status, extension, government support, and transportation costs positively and significantly influenced farmer's income. In contrast, education, employment status, and non-farm income exhibited a negative and significant influence on income. Conclusion and recommendations: The study concludes that socio-demographic factors, such as gender, marital status, extension support, government support, and transportation costs, positively contribute to farmers' income. Small-scale sugarcane farmer involvement in other non-farm activities is associated with reduced farm income. This implies that farmers' livelihoods options are reduced as they can only focus on sugarcane development as a source of income. There is a pressing need to educate small-scale farmers on ICT and provide them with access to agricultural credit. Additionally, extension workers should offer advisory support to small-scale farmers requiring assistance in accessing agricultural credit. There is a need to train sugarcane farmers on different agricultural income generating activities to reduce their over-reliance on sugarcane development. By addressing the identified socio-demographic factors and implementing targeted policy interventions, stakeholders can foster an enabling environment for small-scale farmers to thrive, ultimately contributing to the sustainable development of the sugarcane sector and the broader agricultural landscape in South Africa.

Mapping Sub-surface Distribution of Soil Organic Carbon Stocks in South Africa's Arid and Semi-Arid Landscapes: Implications for Land Management and Climate Change Mitigation.

Soil organic carbon (SOC) stocks are critical for land management strategies and climate change mitigation. However, understanding SOC distribution in South Africa's arid and semi-arid regions remains a challenge due to data limitations, and the complex spatial and sub-surface variability in SOC stocks driven by desertification and land degradation. Thus, to support soil and land-use management practices as well as advance climate change mitigation efforts, there is an urgent need to provide more precise SOC stock estimates within South Africa's arid and semi-arid regions. Hence, this study adopted remote-sensing approaches to determine the spatial sub-surface distribution of SOC stocks and the influence of environmental co-variates at four soil depths (i.e., 0-30 cm, 30-60 cm, 60-100 cm, and 100-200 cm). Using two regression-based algorithms, i.e., Extreme Gradient Boosting (XGBoost) and Random Forest (RF), the study found the former (RMSE values ranging from 7.12 t/ha to 29.55 t/ha) to be a superior predictor of SOC in comparison to the latter (RMSE values ranging from 7.36 t/ha to 31.10 t/ha). Nonetheless, both models achieved satisfactory accuracy (R2 ≥ 0.52) for regional-scale SOC predictions at the studied soil depths. Thereafter, using a variable importance analysis, the study demonstrated the influence of climatic variables like rainfall and temperature on SOC stocks at different depths. Furthermore, the study revealed significant spatial variability in SOC stocks, and an increase in SOC stocks with soil depth. Overall, these findings enhance the understanding of SOC dynamics in South Africa's arid and semi-arid landscapes and emphasizes the importance of considering site specific topo-climatic characteristics for sustainable land management and climate change mitigation. Furthermore, the study offers valuable insights into sub-surface SOC distribution, crucial for informing carbon sequestration strategies, guiding land management practices, and informing environmental policies within arid and semi-arid environments.

Relationship between Village Chicken Availability and Dietary Diversity along a Rural-Urban Gradient.

Dietary diversity is one of the fundamental factors of nutritional security and a proxy used to measure diet quality. The objective of this study was to investigate the relationship between village chicken availability and the dietary diversity of households along a rural-urban gradient. Face-to-face interviews were conducted using a structured questionnaire in rural (n = 100), peri-urban (n = 100), and urban (n = 100) areas of Pietermaritzburg uMgungundlovu District, KwaZulu-Natal, in South Africa. A positive relationship between distance from the city center and village chicken flock sizes (p < 0.001) was observed. Consumption of vegetables increased with an increase in distance from the city center (p < 0.01). A quadratic relationship was observed between distance from the city center and consumption of livestock-derived foods (LDFs) (p < 0.05). Consumption of LDFs increased with an increase in village chicken flock sizes (p < 0.05). Consumption of vegetables increased with an increase in village chicken flock sizes (p < 0.01). Food variety score (FVS) increased with an increase in distance from the city center (p < 0.05). Assessing the availability of village chickens across rural-urban gradients is a worthy opportunity to utilize to improve households' dietary diversity and alleviate poverty. It can be concluded that expanding village flock sizes could enhance the dietary diversity of households.

Impact of pre-existing depression and food insecurity on the trajectory of depressive symptomatology during the COVID-19 pandemic outbreak in South Africa: A panel analysis of nationally representative South African data.

We investigated the trajectory of depressive symptoms ("depression") from the start of the COVID-19 pandemic in South Africa (March 2020) until 2021, between individuals with and without pre-pandemic depression, specifically regarding the role of food security. Our investigation used publicly available panel data (N = 6,930) from the South African National Income Dynamics Study Coronavirus Rapid Mobile Survey (SA-NIDS-CRAM from 2020-2021) on those who had also participated in the pre-pandemic South African National Income Dynamics Study (SA-NIDS, 2017) depression interview. We investigated trends in depressive symptomatology (based on a 2-item Patient Health Questionnaire) at SA-NIDS-CRAM Wave 2 (July 2020), Wave 3 (February 2021) and Wave 5 (May 2021). Generalized estimating equations (GEE) with post-estimation linear combinations of estimators were fitted to investigate the roles of pre-pandemic depression (based on 2017 SA-NIDS data) and food insecurity during the pandemic on depressive symptomatology. During the pandemic, the highest levels of depression were observed consistently among those with pre-pandemic depression and food insecurity; and were lowest among those without pre-pandemic depression and food security. Depressive symptomatology rose in nearly equal magnitude during the early phases of the pandemic in two groups: those without pre-pandemic depression but food insecure during the pandemic; as well as those with pre-pandemic depression but food secure during the pandemic. However, this dynamic changed later in the pandemic, when higher depressive symptomatology was observed in the group with both pre-pandemic depression and food insecurity, widening the gap between them from Wave 3 (adj ß = 0.63, p < 0.01) to Wave 5 (adj ß = 0.79, p < 0.01). Our results highlight the importance of addressing both population mental health and food insecurity, particularly at the early stages of a crisis/disaster. As we showed that mental health impact is linked to food insecurity during a pandemic, strengthening social protection measures, especially around food and nutrition, would help build resilience to crises in the long term.

Remote Sensing of Depth-Induced Variations in Soil Organic Carbon Stocks Distribution Within Different Vegetated Landscapes.

The preservation and augmentation of soil organic carbon (SOC) stocks is critical to designing climate change mitigation strategies and alleviating global warming. However, due to the susceptibility of SOC stocks to environmental and topo-climatic variability and changes, it is essential to obtain a comprehensive understanding of the state of current SOC stocks both spatially and vertically. Consequently, to effectively assess SOC storage and sequestration capacity, precise evaluations at multiple soil depths are required. Hence, this study implemented an advanced Deep Neural Network (DNN) model incorporating Sentinel-1 Synthetic Aperture Radar (SAR) data, topo-climatic features, and soil physical properties to predict SOC stocks at multiple depths (0-30cm, 30-60cm, 60-100cm, and 100-200cm) across diverse land-use categories in the KwaZulu-Natal province, South Africa. There was a general decline in the accuracy of the DNN model's prediction with increasing soil depth, with the root mean square error (RMSE) ranging from 8.34 t/h to 11.97 t/h for the four depths. These findings imply that the link between environmental covariates and SOC stocks weakens with soil depth. Additionally, distinct factors driving SOC stocks were discovered in both topsoil and deep-soil, with vegetation having the strongest effect in topsoil, and topo-climate factors and soil physical properties becoming more important as depth increases. This underscores the importance of incorporating depth-related soil properties in SOC modelling. Grasslands had the largest SOC stocks, while commercial forests have the highest SOC sequestration rates per unit area. This study offers valuable insights to policymakers and provides a basis for devising regional management strategies that can be used to effectively mitigate climate change.

Ecosystem Resilience of a South African Mesic Grassland with Change from Rotational to Continuous Grazing.

Grazing practices affect the soil and vegetation of grasslands, which further influence the provision of ecosystem services and the productivity of grasslands. We determined the ecosystem resilience of a mesic grassland under three grazing management systems in the Pakkies area, (30°33'08''S, 29°25'22'' E), South Africa: cooperative (continuously grazed since 2017), commercial (rotationally grazed for >20 years), and communal (continuously grazed for >20 years) farms. This was carried out by measuring the penetration resistance and infiltration, soil nutrients, forage quality contents for livestock, veld condition, plant species composition and richness, and functional diversity. The soils had a higher penetration resistance in the continuously grazed communal farm, while water infiltration was highest in the continuously grazed cooperative farm. The plant species and functional diversity were greater in the rotationally grazed commercial farm than in the continuously grazed communal and cooperative farms. The continuously grazed cooperative farm had the highest veld condition score (97%), while the rotationally grazed commercial and the continuously grazed communal farms had 82% and 56% veld condition scores, respectively. The forage quality and soil nutrients were generally similar among all farms. The lower plant diversity observed with continuous grazing may indicate that the ecological system was not as resilient concerning this type of grazing. However, for forage quality, soil nutrients and veld condition, continuous grazing was resilient, which indicates that rotational grazing may not be better than continuous grazing for livestock production in this specific region. As long as a minimum level of ecological resilience can be retained, continuous grazing can sustain effective animal production, particularly for small-holder farmers.

'Is there value for us in agriculture?' A case study of youth participation in agricultural value chains in KwaZulu-Natal, South Africa.

Developing countries in Africa face an unemployment crisis, with many unemployed youth. Agriculture has been identified as a strategic sector for employment creation targeted at youth, including those who may not have agriculture-related qualifications. However, various challenges limit the effectiveness of youth participation in the agriculture value chain. The study aimed to (i) determine youth awareness of agricultural value-chain opportunities, (ii) determine their perception of their role in the value chain, (iii) determine their perception of agricultural programs targeting youth and their opinions on who is responsible for attracting youth into agriculture and, (iv) to characterise the dynamics of youth empowerment in agriculture. Data was collected using focus group discussions and an online survey and analysed using SPSS and NVivo. Poor knowledge, low levels of awareness of agricultural value-chain activities and careers, and not meeting the minimum requirements for employment in processing and retail businesses were identified as key challenges. Most youth were interested in non-primary activities such as agro-processing, which are less labour-intensive and have a quicker return on investment than agricultural production. However, support services and programs for promoting youth participation in agriculture mainly focus on primary activities, signifying a mismatch between youth aspirations and current support. Understanding youth aspirations, perceptions and dynamics underpinning youth empowerment and participation in value chains is critical for promoting participation and formulating relevant and responsive policies. Additionally, improving access to information and building awareness of agricultural value chains is crucial in reducing barriers to entry. Policymakers should integrate agriculture and food systems knowledge into the primary education curriculum to promote youth awareness and evoke interest in agri-food system careers at an early age.

Remote Sensing-Based Outdoor Thermal Comfort Assessment in Local Climate Zones in the Rural-Urban Continuum of eThekwini Municipality, South Africa.

Due to the need to continuously monitor and understand the thermal environment and its socioeconomic implications, this study used remotely sensed data to analyze thermal comfort variation in LCZs, including along the rural to urban gradient of the eThekwini Municipality in KwaZulu-Natal province of South Africa. LCZs were mapped using multi-temporal and multi-spectral Landsat 8 and Landsat 9 data using the approach by World Urban Database and Access Portal Tools (WUDAPT), while thermal data were used to retrieve land surface temperatures (LSTs). Data for training classification of LCZs and accuracy assessment were digitized from GoogleEarth guided by knowledge gained and data collected during a field survey in March 2022 as well as pre-existing maps. LCZs were mapped using the random forest classifier in SAGA GIS software while a single channel algorithm based on band 10 was used to compute LST for different scenes. The LSTs were adjusted and further used to derive thermal comfort based on the Universal Thermal Comfort Index (UTCI) categories as an indicator for outdoor thermal comfort on the extremely low- and extremely high-temperature periods in the cool and hot seasons, respectively. LCZs were mapped with high accuracy (overall accuracy of 90.1% and kappa of 0.88) while inter-class separability was high (>1.5) for all LCZ pairs. Built-up LCZs dominate the eastern parts of the municipality, signifying the influence of the sea on development within the area. Average LST was coolest in the dense forest, open low-rise and water LCZs in the cool and hot seasons, respectively. The compact high-rise LCZ was the warmest in both the hot (36 °C) and the cool (23 °C) seasons. The sea sands were among coolest regions in both seasons due to their high water content, attributed to their high water table and close proximity to the ocean. There was no thermal stress during the cool season, while most areas recorded moderate to strong heat stress in the hot season. Some areas in the densely built-up LCZs recorded very strong heat stress in the hot season. The findings suggest that policies and strategies should enhance heat mitigation capacities in strong-heat-stress areas during the hot season. Municipal authorities and citizens must work together to build strategies to minimize temperature extremes and associated socioeconomic pressures. Urban development policies, plans and strategies should consider implications on the thermal environment as well as the value of conservation of LCZs with high-heat mitigation value such as dense forests and expansion of built-up LCZs with low-heat absorption levels such as open low-rise. The study was based mainly on remotely sensed temperatures with some ground data used to validate results, which may limit the assessment. Overall, the study provides insights towards achievement of global sustainable and climate-smart development targets.