This paper uses existing studies to explore how Artificial Intelligence (AI) advancements enhance recruitment, retention, and the effective management of a diverse workforce in South Africa. The extensive literature review revealed key themes used to contextualize the study. This study uses a meta-narrative approach to literature to review, critique and express what the literature says about the role of AI in talent recruitment, retention and diversity mapping within South Africa. An unobtrusive research technique, documentary analysis, is used to analyze literature. The findings reveal that South Africa’s Human Resource Management (HRM) landscape, marked by a combination of approaches, provides an opportunity to cultivate alternative methods attuned to contextual conditions in the global South. Consequently, adopting AI in recruiting, retaining, and managing a diverse workforce demands a critical examination of the colonial/apartheid past, integrating contemporary realities to explore the potential infusion of contextually relevant AI innovations in managing South Africa’s workforce.

The characteristics of agricultural products are influenced by the ecosystem, from the perspective of biotic and abiotic factors, which produce in the plant physiological responses and in turn in the fruit unique physicochemical properties, which are the basis for designations of origin and strategies to add value to the product in the current market. In the present work, ten cocoa materials (Theobroma cacao L.) were selected for their outstanding productivity (FSV41, FLE3, FEAR5, FSA12, FEC2, SCC23, SCC80, SCC55, ICS95 and CCN51), which were established in the departments of Santander (931 m a.s.l.), Huila (931 m a.s.l.), Huila (931 m a.s.l.), Huila (931 m a.s.l.), Huila (931 m a.s.l.), Huila (931 m a.s.l.) and Huila (931 m a.s.l.). These were established in the departments of Santander (931 m a.s.l.), Huila (885 m a.s.l.) and Arauca (204 m a.s.l.), the main cocoa-producing areas in Colombia. For the evaluation of the physical characteristics of the collected materials, 21 quantitative descriptors were used to determine the physical variability of the fruit according to clone and place of collection. The data collected were analyzed by means of Pearson’s correlation matrix and principal component analysis, it was possible to identify those descriptors that contribute most to the variability among materials (ear index, diameter length ratio, seed weight and diameter, and fruit weight and length). In addition, it was possible to verify the effect of the place of harvest on the physical characteristics of the materials, high-lighting the importance of the adaptation study prior to the planting of the cocoa material, with the objective of guaranteeing a premium, productive and quality cocoa crop for the industry, which is competitive in the market.

Tropical dry forests are complex and fragile ecosystems with high anthropogenic intervention and restricted reproductive cycles. They harbor unique richness, structural, physiological and phenological diversity. This research was carried out in the upper Magdalena valley, in four forest fragments with different successional stages. In each fragment, four permanent plots of 0.25 ha were established and the light habitat associated with species richness, relative abundance and rarity was evaluated, as well as the forest dynamics that included mortality, recruitment and diameter growth for a period of 5.25 years. In mature riparian forest, species richness was found to be higher than that reported in other studies for similar areas in the Cauca Valley and the Atlantic coast. Values of species richness, heterogeneity and rarity are higher than those found in drier areas of Tolima. Forest structure, diversity and dynamics were correlated with light habitat, showing differences in canopy architecture and its role in the capture and absorption of radiation. The utilization rate of photosynthetic effective radiation in the forest underlayer with high canopy density is low, which is related to the low species richness, while the underlayer under light is more abundant and heterogeneous.

The structure and diversity of tree species in a temperate forest in northwestern Mexico was characterized. Nine sampling sites of 50 × 50 m (2,500 m²) were established, and a census of all tree species was carried out. Each individual was measured for total height and diameter at breast height. The importance value index (IVI) was obtained, calculated from the variable abundance, dominance and frequency. The diversity and richness indices were also calculated. A total of 12 species, four genera and four families were recorded. The forest has a density of 575.11 individuals and a basal area of 23.54/m². The species of Pinus cooperi had the highest IVI (79.05%), and the Shannon index of 1.74.

Knowledge of the state of fragmentation and transformation of a forested landscape is crucial for proper planning and biodiversity conservation. Chile is one of the world’s biodiversity hotspots; within it is the Nahuelbuta mountain range, which is considered an area of high biodiversity value and intense anthropic pressure. Despite this, there is no precise information on the degree of transformation of its landscape and its conservation status. The objective of this work was to evaluate the state of the landscape and the spatio-temporal changes of the native forests in this mountain range. Using Landsat images from 1986 and 2011, thematic maps of land use were generated. A 33% loss of native forest in 25 years was observed, mainly associated to the substitution by forest plantations. Changes in the spatial patterns of land cover and land use reveal a profound transformation of the landscape and advanced fragmentation of forests. We discuss how these patterns of change threaten the persistence of several endemic species at high risk of extinction. If these anthropogenic processes continue, these species could face an increased risk of extinction.

In light of swift urbanization and the lack of precise land use maps in urban regions, comprehending land use patterns becomes vital for efficient planning and promoting sustainable development. The objective of this study is to assess the land use pattern in order to catalyze sustainable township development in the study area. The procedure adopted involved acquiring the cadastral layout plan of the study area, scanning, and digitizing it. Additionally, satellite imagery of the area was obtained, and both the cadastral plan and satellite imagery were geo-referenced and digitized using ArcGIS 9.2 software. These processes resulted in reasonable accuracy, with a root mean square (RMS) error of 0.002 inches, surpassing the standard of 0.004 inches. The digitized cadastral plan and satellite imagery were overlaid to produce a layered digital map of the area. A social survey of the area was conducted to identify the specific use of individual plots. Furthermore, a relational database system was created in ArcCatalog to facilitate data management and querying. The research findings demonstrated the approach's effectiveness in enabling queries for the use of any particular plot, making it adaptable to a wide range of inquiries. Notably, the study revealed the diverse purposes for which different plots were utilized, including residential, commercial, educational, and lodging. An essential aspect of land use mapping is identifying areas prone to risks and hazards, such as rising sea levels, flooding, drought, and fire. The research contributes to sustainable township development by pinpointing these vulnerable zones and providing valuable insights for urban planning and risk mitigation strategies. This is a valuable resource for urban planners, policymakers, and stakeholders, enabling them to make informed decisions to optimize land use and promote sustainable development in the study area.