The ongoing exponential growth of human population poses a risk to sustainable development goals (SDGs). Unless we understand the drivers of this growth and inform policy development accordingly, SDGs would remain a dream. One of the old theories of population growth known as the Malthusian theory predicts that resource availability drives population growth to a certain time when population growth outrun resource availability, leading to all sort of crises known as Malthusian crisis. Although the link between economic growth and population has been widely investigated while testing the theory, little is known about environmental and social factors po-tentially driving population growth. Here, because of various crises of our time recalling the Malthusian crisis, we revisited the theory by fitting structural equation models to environmental, social and economic data collected over 30-year period in South Africa. None of the social varia-bles tested predicts population growth. Instead, we found that biodiversity (species protection index) correlates positively with population growth. Biodiversity provides various resources through ecosystem goods and services to human, thus supporting population growth as pre-dicted in the Malthusian theory. However, we also found that this population growth may lead to conservation conflict as we found that biodiversity habitat (wetland area) correlates negatively with population growth, thus raising the compromising effect of population growth on life on earth. What’s more, we found a significant link between economic growth measured as GDP and population growth, further supporting the Malthusian prediction. Overall, our study re-affirms the value of biodiversity to human and suggests that the Malthusian theory should continuously be tested with predictors other than economic.

Globally, there are 1.35 million road fatalities every year, which are estimated to cost governments approximately US$ 518 billion, making road fatalities the 8th leading cause of death across all age groups and the leading cause of death of children and young adults. In South Africa, despite tremendous governmental efforts to curb the soaring trajectory of road accidents, the annual number of road fatalities has increased by 26% in recent years. By fitting a structural equation model (SEM) and a GARCH Model (Generalized Auto-Regressive Conditional Heteroskedastic-ity) to analyze and predict future trend of road accidents (number of road accidents, number of casualties, number of fatal crashes and number of persons killed) in South Africa, we propose and test a complex metamodel that integrates multiple causality relationships. We show an increasing trend of road accidents over time, a trend that is predictable by number of vehicles in the country, the population of the country and the total distance travelled by vehicles. We further show that death rate linked to road accidents is on average 23.14 deaths per 100,000 persons and is pre-dictable following the equation: y = -0.0114x2+1.2378x-2.2627 (R2=0.76) with y = death rate and x = year. Finally, in the next decade, the number of road accidents is predicted to be roughly constant at 617,253 accidents but can reach 1 896 667 accidents in the worst-case scenario. The number of casualties was also predicted to be roughly constant at 93 531 over time, although this number may reach 661 531 in the worst-case scenario. However, although the number of fatal crashes may decrease in the next decade, it is forecasted to reach 11 241 within the next 10 years with the worse scenario estimated at 19 034 within the same period. At the same time, the number of persons killed in fatal crashes is also predicted to be roughly constant at 14 739 but may also reach 172 784 in the worse scenario. Overall, the present study reveals perhaps the positive effects of government initiatives to curb road accidents and their consequences; we call for more stronger actions for a drastic reduction in road accident events in South Africa.

In ethnobotany, the availability hypothesis predicts that plants that are abundant and easily accessible to people are more likely to be medicinal than not. By protecting species diversity away from people, protected areas (PAs) may act as a limiting factor to a sustainable development of traditional knowledge concerning medicinal uses, and in so doing, PAs provide opportunity to prioritize ex-situ conservation for species that are PAs restricted. In this scenario, ex-situ conservation becomes the only chance for people to develop traditional knowledge on plants which otherwise wouldn’t be documented as traditionally useful to people. To test these expectations, we used data collected for almost 20 years of fieldworks on plant medicinal uses and their abundance inside and outside the Kruger National Park (KNP), South Africa. We fitted four different scenarios of structural equation models (SEMs) to the data collected. We found that total plant abundance (abundance outside + inside KNP) is a significant positive predictor of medicinal status, and so is abundance outside KNP, thus supporting the availability hypothesis. However, not only abundance inside KNP is not a direct significant correlate of medicinal status, but also the relationship between both is negative. The lack of predictive power of inside-abundance is most likely because some species are exclusively found inside KNP, and local communities do not have access to them. It also shows that the positive and direct correlation of total abundance with medicinal status is driven by outside-abundance. In addition, the negative relationships between inside abundance and medicinal status implies that abundant plants inside KNP tend to be not-medicinal, further providing evidence that PAs hinder the development of medicinal knowledge. Furthermore, when inside and outside abundance were included simultaneously in a model as two distinct variables, inside abundance was never a direct significant predictor of medicinal status, but it was so, via an indirect path mediated by outside abundance. This suggests that outside abundance is the key variable driving the development of medicinal plant knowledge. Cumulatively, our findings suggest that anything that promotes the growth of PA-restricted plants beyond the natural realized niches of these plants (ex-situ conservation) such as in botanical gardens, private gardens, in agroforestry systems, etc., is to be promoted so that people-plant interactions may continue for the benefits of ethnobotanical knowledge development.

Although South Africa is well known for its incredible biodiversity, targeted efforts are still re-quired to accelerate the discovery and description of the still-unknown species in this floristically mega-diverse country. In addition, new species discovery is a new opportunity for the devel-opment of ethnobotanical knowledge. In the present study, we collected data on current knowledge of plant richness in the country and expert taxonomists’ opinions and used statistical modelling technique to predict what might still be missing in South Africa’s flora. According to experts’ opinions and our modelling, we might be missing 1400-1575 plant species in the country. We predicted that we might take 40-45 years to identify and describe these species and that be-tween 64 and 315 taxonomists will be required. The pool of taxonomists who took part in this study have spent a total of R 680 670 000 (US $40 039 411) to describe 419 species. This implies that, in theory, R 1 624 510.74 (US $95 559) was spent, on average, to describe 1 species. At this rate, R 2 558 604 415.00 (US $150 506 142) would be required to describe the 1575 (modelling) or R 2 274 315 036.00 (US $133 783 237) for the 1400 remaining species (expert opinion) in the current context where both full- and part-time taxonomists are committed to biodiversity assessment in the country. It is important to highlight that this estimate does not correspond to what is required specifically for only species description but does integrate all connected activities, e.g., running cost, bursary, salaries, grants, etc. Furthermore, we must bear in mind that these estimates do not account for the possibility of taxonomic revision which, on its own, needs to be funded, nor do they account for molecular laboratory requirement. However, if we consider that 15% of the predicted funds are spent solely on taxonomic activities, this means that we would need ~R243 673 (US$ 14 334) on 1 species. Overall, our study provides an important figure that can inform policy development including funding and recruitment strategies of taxonomists to fuel efforts towards a comprehensive assessment of the unique South Africa’s biodiversity. The implication of new species discovery is that it opens windows for traditional knowledge development.

Ethnobotany has been, for too long, a descriptive discipline. However, ethnobotanists are increasingly calling for a paradigm shift towards the formulation of unifying theories and hypothesis-driven research in ethnobotany. Here, we formulated a theory, termed time-since-introduction theory, to explain the integration of alien plants into local pharmacopoeias in their recipient environment. This theory suggests that the factor time is paramount in determining which alien plants are more likely to be included in the medicinal flora of the areas they are introduced in. The theory relies on three hypotheses, the availability and versatility hypotheses alongside the residence time hypothesis newly proposed in the present study. We tested this theory by fitting a structural equation model to ethnobotanical data collected on South Africa’s alien woody flora. Although residence time is a direct predictor of medicinal status of alien plants, it is a better predictor when mediated through plant versatility. These findings are in support of the theory, and we consequently proposed a framework with which to understand different paths linking all three hypotheses. Collectively, our study shows the value of time in the development of ethnobotanical knowledge and fully responds to the pressing call for paradigm shift in ethnobotany.