The Efficacy of Indigenous Knowledge Systems in the War of Liberation Struggle in Southern Africa: A Zimbabwean Perspective

Application of African indigenous knowledge systems and practices for climate change and disaster risk management for policy formulation

The use of indigenous knowledge systems (IKS) in seasonal forecasting and adaptation to devastating vagaries of climate change has gained attention in academic discourses. The debates opened contrasting views with the first over-romanticizing IKS’ potentials, while the other arguing that it has many setbacks. In this study, we interrogated IKS’ roles in seasonal forecasting and chances of informing adaptation among poorly resourced smallholder farmers in ward 24, Bikita. Using focus group discussions, in-depth interviews, and key informant interviews, we identified diverse indigenous indicators and interrogated how they subsequently inform adaptation. We noted that IKS is important in providing seasonal forecasting information, which is critical in making decisions in planning, designing cropping calendars, offering early warnings, as well informing preparedness against disasters. However, we also noted that IKS is under threat from Western education, Christianity, scientific seasonal forecasting (SSF), and climate change. These factors are challenging and reducing IKS’ reliability and hence increasing its susceptibility to disappearance. We concluded that IKS can be resuscitated if included in science education and policy frameworks. We recommended governments to formulate policy frameworks, which allow it to work well with SSF in reducing poorly resourced smallholder farmers’ vulnerability to climate change disasters.

The peacebuilding space in Zimbabwe has been contested by a plethora of actors, which include Civil Society Organisations (CSOs). This thesis focuses on civil groups that engaged in peacebuilding in post-independent Zimbabwe. Despite their presence, the country remains in a negative peace mode with continued resurgence of structural-related conflicts. This points to the weaknesses of CSOs’ modus operandi of building peace. To address this, the study sought to develop, implement and evaluate a peacebuilding strategy that strengthens community-based CSOs in building positive peace in Zimbabwe through the use of indigenous knowledge systems (IKS) and political intelligence1. The research design of the study was two-tier, combining explanatory and action research approaches. The qualitative data methods collection used include documentary review, in-depth interviews and focus group discussions (FGD)s. A total of 43 participants were involved in the interviews and FGDs. Findings from the baseline data indicate that CSOs have failed to translate the prevailing negative peace into positive peace because they follow elitist or liberal peacebuilding models. To address this problem, I carried out inclusive knowledge gathering with an action research team. From the team’s responses, I designed a training manual to enhance CSOs’ peacebuilding activities through IKS and political intelligence. The concept of IKS is embedded in sustainable peacebuilding and a development approach. The training was conducted with members of a CSO2 based in Harare but engaged with grassroots in rural parts of Zimbabwe. The findings in the first evaluation showed that the training was successful, and participants learnt a great deal on how they can best build peace using IKS and political intelligence skills. The participants noted that working with local people generates context-specific solutions that are demand- driven and attractive to the beneficiaries. In the second evaluation participants in the training and local people interviewed highlighted that there was a great change in the manner in which CSO(A) was conducting its peacebuilding campaign. There was great involvement of the local people, use of proverbs and adoption of a stakeholder mapping. This approach led to the generation of legitimacy and local ownership of the peacebuilding programme. The ultimate result was that a culture of tolerance, respect and unity was created in the rural community. The study concludes that sustainable peace and development can be realised when CSOs build peace using IKS and political intelligence skills. I recommend that CSOs should continuously be trained and conduct peacebuilding using IKS and political intelligence in other parts of the country. The study is significant in that it combines theory and practice of building durable peace with CSO(A) through action research. The theory of sustainable peacebuilding was realised through training and implementation of building peace through the use of IKS and political intelligence skills.

IntroductionThe success of anticipatory action (AA) in climate change related disaster risk reduction depends largely on the ability to accurately predict adverse weather events and to subsequently take appropriate and timely action. The current seasonal climate forecasts obtained through national and global forecasting centers such as the Zimbabwe Meteorological Services Department (MSD) and the European Center for Medium-Range Weather Forecasts (ECMWF) have been found to have several limitations including limited skill in intra-seasonal variability which is vital in most processes, lack of accessibility, difficult interpretability and applicability to local communities. As a result, calls for the integration of Indigenous Knowledge Systems (IKS)-based climate services in seasonal climate forecasting to bolster the efficacy and accuracy of forecasts are increasing.MethodologyThe study employed a mixed methods approach combining a survey of 200 household heads, document reviews and key informant interviews with IKS specialists, AA community of practice members and disaster risk reduction specialists.ResultsThis article presents the findings of a study carried out in four semi-arid districts of Zimbabwe (Mbire, Matobo, Binga, and Mudzi) to assess the feasibility of integrating IKS into the drought AA mechanism at national, district, and ward level. We find that 82% of the surveyed households used indigenous knowledge systems for seasonal climate forecasting and extreme weather forecasting combined with scientific forecasts. Respondents demonstrated preference for triangulated forecasting to increase reliability. Both the meteorological approaches to seasonal climate forecasting and the IKS based forecasting had different strengths and weaknesses.DiscussionBased on the found gaps in current seasonal forecasting techniques, local applicability, and limited quantitative analysis in IKS, this study provides a guideline on how scientific and IKS forecasting can be triangulated for leveraging forecasting information in Zimbabwe. The use of IKS may be of utmost relevance to agencies and entities seeking the achievement of drought risk reduction through AA programmes.

The important role indigenous knowledge systems (IKS) is described in redefining the biodiversity conservation agenda of the Chibememe and Tshovani communities in the Sangwe Communal Lands, Chiredzi, in the management of dryland ecosystems of the southeastern low veld of Zimbabwe. These communities constitute part of the Great Limpopo Transfrontier Conservation Area (GLTFCA). We explored ways in which the use of IKS by Chibememe and Tshovani communities have contributed to the conservation and sustainable utilisation of forest, water and wildlife resources in light of existing contemporary scientific value systems, policy and institutional frameworks. Participant observation, interviews with traditional leaders and elders, focus group discussions and literature review techniques were employed within a case study framework. Our results revealed that IKS approaches are used in the management of dryland forest, water and wildlife resources in the Chibememe and Tshovani communities and have contributed positively to the conservation and sustainable utilisation of dryland resources. We conclude that IKS play a critical role in the management of dryland forest, water and wildlife resources at the local community level and have potential to contribute to the conservation of transfrontier conservation area resources such as in the GLTFCA, provided they are recognised, respected, preserved, protected, as well as integrated into mainstream dryland ecosystem conservation. We recommend that, for communities and their biodiversity to survive, conventional science and IKS should complement and should not seek to undermine each other.

With its envisioned benefits of increased productivity, enhanced decision making with digital-based tools, qualitative and efficient processes, improved life expectancy rate, etc., the Fourth Industrial Revolution (4IR) is a desideratum for contemporary society. The need to prioritize skills and knowledge needed for the participation of Africa in the 4IR thus becomes imperative. This paper argues for indigenous knowledge systems (IKS) as a possible approach to enhance African participation in the 4IR. Consequently, the paper examines the methodical perspectives that would be appropriate for framing African Indigenous Knowledge Systems (AIKS) as a tool for advancing science and technology. It argues for the process form of ideating IKS against the content forms implicit in the various views on IKS. It is concluded that the process form of ideating IKS – which essentially focuses on the critical analysis of the systematic formations and development of IKS – unearths the epistemological basis for scientific postulations and technological advancement in Africa.

The colonial university has long existed as a site of traumatic incorporation of western knowledge systems into the lives of indigenous populations across the world. Western academic styles of teaching and learning in South Africa reenact indigenous traumas of violent loss of identity and the spiritual relationship to the wider world of self, family, community, ancestors and the environment on which the indigenous South African health model is based. As a result, academia in South Africa becomes a space in which the trauma of violent and unequal incorporation into the colonial social world is reproduced. Like other societies shaped by settler colonial domination, South African education systems have historically excluded indigenous knowledge systems and indigenous identities through both violent and subtle methods, including language and appearance policies aimed at disciplining and subduing the indigenous body. What has been termed ‘intellectual colonization’ sees the ongoing dismissal of African Indigenous Knowledge Systems (AIKS) as inferior, or as a resource to exploit. AIKS have been an object of study for anthropologists since the discipline’s inception, but the ontological possibilities it offers to transforming teaching practice from within have not been taken up. This has subsequently led to a situation in which academia exists as an unsafe space for indigenous people to engage with knowledge. There has been much discussion about the decolonization of education in South Africa, but very rarely are these decolonial discussion efforts met with actual change in pedagogical approaches. We reflect here on attempts to integrate indigenous knowledge systems (IKS) into the curriculum and pedagogical approach of an Anthropology Hons course in an English-Medium South African university in the Eastern Cape, Rhodes University. We argue that sharing understanding of content, and incorporating teaching practices, from an AIKS approach can enhance learning, and complement existing academic practices of text-based enquiry to produce a knowledge-transmission experience grounded in indigenous modes of learning which might mitigate the violence and trauma of the colonial university’s locking of students into one ontological frame presented as ‘normal’. Keywords: indigenous knowledge systems (IKS), decolonization, indigenous health models, university pedagogy.

South Africa's new and revised National Curriculum Statement implicitly suggests the integration of indigenous knowledge (IK) into the science curriculum so that learners can, inter alia, learn within the context of their cultural knowledge. Unfortunately, teachers do not necessarily know about the various indigenous knowledge systems (IKS) within South Africa. We therefore decided to identify the ideas of traditional health practitioners (THPs) concerning what children need to know, and then to obtain science teachers' responses to these ideas. In this pilot study in the Western Cape, we used a qualitative approach and conducted in-depth interviews with a small group of THPs, with a follow-up questionnaire and discussion with a larger group. We then shared the THPs' ideas with both experienced science educators and high school science teachers. Our results show that THPs think that South African learners need to know about and respect their heritages, especially African IKS. They emphasized the importance of learning about health and freedom from disease, particularly HIV/AIDS. The THPs believe that both science and IK are important in the education of learners, and that they could co-teach their IK in conjunction with science topics. They suggested how they could do this. They believe that science teachers need to learn about IK, and suggested that THPs could learn some science. Both groups of science teachers were interested in, and strongly supportive of the THP suggestions. They also emphasized that IK needs to be standardized and validated by an indigenous organization.

Developing countries are vulnerable to negative impacts of climate change due to over reliance on climate-sensitive sectors, mainly agriculture. Limited adaptive capacity makes them vulnerable to climate-induced hazards. However, over the years, indigenous knowledge systems (IKS) have proven effective in promoting sustainable development particularly for those in subsistence agriculture. For example, in Lake Victoria basin, local communities have coped and adapted to climate-induced hazards using traditional systems and IKS. This chapter presents findings of a cross-sectional survey on the use of IKS in subsistence agriculture to enhance climate risk management and mitigation of community vulnerability in a changing climate. Data were collected by household questionnaires, key informants’ interviews, and focus group discussions. Results showed overall, significantly high community awareness levels prevail in study area, implicating climate change as the main challenge facing agricultural sector. Nevertheless, as climate change adaptation and mitigation measures, local communities use myriad of IKS to improve resilience and productivity. They use IKS in soil conservation, weather/climate forecasting, selection of planting seeds, and preservation of seeds/crops. This study, therefore, recommends incorporating IKS into scientific knowledge systems to promote climate change adaptation and mitigation among vulnerable communities dependent on climate-sensitive resources.

The semi-arid areas of Southern Africa receive low and erratic rainfall which varies in both seasons and from year to year resulting in food insecurity. Few of the smallholder farmers have access to seasonal climate forecasts from the meteorological department hence they depend mostly on their indigenous knowledge systems for forecasting seasons which they make use of to develop crop management adaptive strategies. The study shows that farmers have several indicators for weather forecasting and some of these are similar in both Zambia and Zimbabwe. Some of these indicators include; floods or excessive rains in the preceding season, strong winds around October, an extended cold season that goes up to August and sometimes September and abundance or scarcity of certain fruits. The indicators conflict in some seasons and in such cases the farmers resort to using those that they know to have stronger signals from their reliability factors. Positive relationship between indigenous knowledge systems and modern science were observed between the 2008/9 season and 2009/10 which confirms that indigenous knowledge systems, when fully developed could be very helpful in seasonal forecasting. The study recommends the importance of the restoration of the confidence of the indigenous people in their traditional knowledge and skills of weather forecasting.

This open access book analyzes the limitations of top-down intervention programs designed by the state to address the problem of unemployment among marginalized communities in Africa and foregrounds the centrality of IKS in fostering entrepreneurship. Samuel Ojo Oloruntoba, Inocent Moyo, and Lethiwe Zondo examine the solutions to these problems within the ongoing debate on decolonization of knowledge and epistemic justice. The contributors argue that when the voices of the marginalized communities are taken into consideration in the design of employment and entrepreneurship policies, such policies would be more effective, affirming the agency and rights within these communities. Using case studies and theoretical research, this book investigates how a better engagement with marginalized communities and indigenous knowledges in the design of entrepreneurship and employment policies could foster more positive outcomes in Africa. This book recenters the voices of Indigenous youth within entrepreneurship programs to highlight the interests, priorities, and challenges of these communities. This edited volume was produced in the context of the African Indigenous Knowledge Research Network (AIKRN) in partnership with the Mastercard Foundation. This was a two-year initiative that ran between 2023 and 2025 to uncover and promote sustainable and scalable opportunities for youth employment grounded in Indigenous African knowledge systems and values. The views expressed do not necessarily represent those of the Mastercard Foundation, its staff, or its Board of Directors. The ebook editions of this book are available open access under a CC BY-NC-ND 4.0 licence on bloomsburycollections.com. Open access provided in partnership with the Mastercard Foundation.

Indigenous African knowledge systems are concerned with local knowledge. But the question that this raises is how valid is such local knowledge? Can such local knowledge be generalized and claim universal validity? Or stated differently, what is the epistemic foundation of local knowledge? This article sets out to reflect critically on the epistemic status of local knowledge and concludes with a defence of local knowledge based on work done in the anthropology of science. Keywords: Indigenous knowledge systems, local knowledge, anthropology of science.Indilinga Vol. 5 (2) 2006: pp. 1-11

Fertility decline in most countries of sub-Saharan Africa has thus far started later and proceeded more slowly than in countries in Asia and Latin America and the Caribbean undergoing the transition in fertility since the 1950s from high levels to near-replacement or even below-replacement levels (Bongaarts and Casterline 2013). Yet there is considerable variation among countries in sub-Saharan Africa: in the duration and magnitude of fertility decline, whether stalls in fertility decline have occurred, shifts in the timing of births, and even the economic and population subgroups that have led declines in family size (Caldwell, Orubuloye, and Caldwell 1992; Bongaarts and Casterline 2013; Cleland, Onuoha, and Timæus 1994; Cohen 1998; Ezeh, Mberu, and Emina 2009; Garenne 2008; Kirk and Pillet 1998; Rossier, Corker, and Schoumaker 2015; Timæus and Moultrie 2008). With current fertility estimated at 5.1 births per woman in the region and 19 countries in sub-Saharan Africa at or above that level and another 21 countries with at least four births per woman on average (United Nations 2015a), the pathways that future fertility takes will significantly determine population growth and age structure shifts not only in the region, but increasingly for the world. Sub-Saharan Africa is projected to grow from 840 million people in 2010 to nearly 1.4 billion in 2030 (United Nations 2015a). Above-replacement fertility is projected to account for 61 percent of this population increase from 2010 to 2030 compared to 4 percent from mortality reduction, 37 percent from a young age structure in 2010 (population momentum), and a small negative contribution from migration (United Nations 2015b). These projections draw on the United Nations medium variant and do not take into account the uncertainty around current and future fertility levels, uncertainty that only increases the farther the projection period extends. For high-fertility countries in sub-Saharan Africa, the wide uncertainty around where fertility is headed can result in substantial differences in population projections (Ezeh, Mberu, and Emina 2009; Fuchs and Goujon 2014; Gerland et al. 2014). Beyond population numbers alone, the uncertainty about fertility decline also bears on policy-relevant questions such as the degree to which the region may realize a demographic dividend (e.g., how fast the shift will occur toward a higher ratio of working-age population to non-working-age population and the consequent effects on economic growth) (Bloom et al. 2013) or the extent to which greenhouse gas emissions might be reduced by slowing population growth (O'Neill et al. 2010). Earlier reviews of the fertility transitions in sub-Saharan Africa through the 1980s and 1990s showed fertility declines underway in most countries and particularly rapid declines in several countries in Eastern Africa (Kenya, Rwanda, and Zimbabwe) and Southern Africa (Botswana and South Africa) (Cleland, Onuoha, and Timæus 1994; Cohen 1998; Kirk and Pillet 1998). Subsequent survey data suggested an apparent slowdown in the pace of fertility decline in more than ten sub-Saharan African countries (Bongaarts 2008). Further analyses of the data indicated far fewer stalls in fertility decline had in fact occurred in the region, with evidence strongly supportive of stalls in Kenya and Rwanda, and the stalls that do occur have been of relatively short duration (Garenne 2011; Machiyama 2010; Schoumaker 2009, 2014). Most countries in sub-Saharan Africa still lack complete and accurate vital registration data on births, so these and other analyses of fertility trends will continue to rely heavily on survey data and require reconciling estimates from different sources (Alkema et al. 2012; United Nations 2015c). Our aim in this chapter is to provide an updated and concise description of the diversity of fertility decline patterns among countries1 in sub-Saharan Africa, drawing on the latest series of fertility estimates that take into account many different data sources and that are harmonized with other demographic components (United Nations 2015d). We focus on the level of fertility prior to the start of fertility decline, the time period of the fertility transition, and the estimated pace of decline. We also explore the implications of different fertility decline patterns for future fertility and population projections in the region. We draw on the distinct patterns of fertility decline among countries worldwide that are advanced in (or have completed) their first fertility transition to construct probabilistic fertility and population projections for sub-Saharan African countries. The illustrative comparisons of projections highlight the demographic impact if future fertility decline in sub-Saharan countries were to accelerate and follow the rapid pace of decline already experienced by a diverse group of countries. The UN Population Division publishes estimates and projections of period total fertility rates in World Population Prospects (WPP) every two years. The estimates of total fertility presented in this chapter are from the 2015 Revision and are for five-year time periods for countries or areas with 90,000 persons or more in 2015 (United Nations 2015a). The most recent data underlying the total fertility estimates from the 2015 Revision for 50 sub-Saharan African countries2 (United Nations 2015c) are from the period 2013–2014 for 14 countries, 2010–2012 for 30 countries, and 2005–2009 for six countries. A common challenge in estimating total fertility over time, especially for countries without accurate or complete vital registration data,3 is that estimates vary across data sources and by the methodology used to derive those estimates. Schoumaker (2014) showed that the underlying data from standardized, high-quality surveys such as the Demographic and Health Surveys vary considerably within and across countries, yielding total fertility estimates from recent fertility data of good quality (e.g., Gabon, Lesotho, Namibia, and Zimbabwe) and of poor quality (e.g., Benin, Burkina Faso, Cameroon, Chad, Ethiopia, Guinea, Madagascar, Mali, Mozambique, Niger, Nigeria, and Uganda). Total fertility estimates based on births in the last three years tend to be under-estimated by 10 percent or more in most of the surveys with poor quality fertility data from retrospective birth histories. Figure 1 illustrates the variation in total fertility estimates based on survey data and estimation methods (direct methods (D) and cohort-completed (C) fertility) for Nigeria for the period 1985 to 2015. The thick lines show the total fertility estimates from the 2010, 2012, and 2015 Revisions of WPP. Given new data from the 2008 DHS and other surveys, total fertility in the 2012 Revision was re-estimated at a higher level than the 2010 Revision beginning in the mid-1980s, resulting in almost half a birth per woman difference in the 2005–2010 period. The 2015 Revision used new data from the 2013 Demographic and Health Survey. The 2013 survey estimates highlight a recurring pattern in which fertility estimates based on a recent reference period are consistently lower than fertility estimates from reconstructed birth histories for the same time point. Looking only at fertility estimates from a three-year reference period, the 2013 DHS shows a decline in total fertility to 5.5 births per woman from a stalling pattern of 5.7 births per woman in the 2003 and 2008 DHS. Yet the absolute differences are large between these three-year reference period estimates and those for the same time point from the reconstructed birth histories: about half a birth difference in the mid-2000s (comparing the 2008 and 2013 survey estimates) and about one birth difference in the early 2000s (comparing the 2003 survey estimate to those from the 2008 and 2013 surveys). Estimates of the total fertility rate for Nigeria 1985–2015 based on various data sources and estimation methods, and WPP estimates from the 2010, 2012, and 2015 Revisions NOTES: DHS = Demographic and Health Survey; MICS = Multiple Indicator Cluster Survey; MIS = Malaria Indicator Survey. (C) refers to cohort completed fertility (i.e., average number of children ever born) for women aged 40–44 and 45–49 at the date of the survey and backdated using their mean age of childbearing. (D) refers to direct fertility estimates based on maternity histories or recent births in the 12 or 24 months preceding the survey. SOURCES: Federal Office of Statistics of Nigeria (1992); National Bureau of Statistics (2008, 2012); National Population Commission (2000, 2002, 2004, 2009, 2012, 2014). WPP fertility estimates consider as many types and sources of empirical estimates as possible, including retrospective birth histories and direct and indirect fertility estimates (Gerland 2014). The 2015 Revision updated all total fertility estimates taking into account new data and the inconsistencies among estimates. Moreover, total fertility estimates are derived to ensure as much internal consistency as possible with all other demographic components and intercensal cohorts enumerated in successive censuses (United Nations 2015d). The advantages of this approach are that the estimates are internally consistent within a country over time and with respect to other related demographic information. A disadvantage is that the estimates can depart from a country's official estimates of fertility. Figure 2 shows the estimated trends in period total fertility for sub-regions of sub-Saharan Africa from 1950 to 2015. It was high (above six births per woman) in all sub-regions in 1950–1955. Fertility remained high in Eastern and Western Africa until the 1980s, after which it began a slow decline to 4.9 births per woman in Eastern Africa and 5.5 in Western Africa in 2010–2015. Fertility in Middle Africa began to decline a decade later and more slowly, reaching 5.8 births per woman in 2010–2015. Southern Africa departed from the overall trends with a decline beginning in the 1950s and dropping below three births per woman in the 2000s. The 2010–2015 estimate of 2.5 births per woman in Southern Africa is about half the total fertility level in Eastern, Middle, and Western Africa. Sub-regional trends in total fertility, sub-Saharan Africa, 1950–2015 SOURCE: United Nations 2015a The sub-regional fertility levels mask diverse levels among countries. Figure 3 shows country-specific total fertility levels in 2010–2015. Among the 16 countries in Western Africa, total fertility ranged from 2.4 in Cabo Verde to 7.6 in Niger. One additional country had a fertility level of more than six births per woman (Mali), six countries had fertility between five and six births per woman (Burkina Faso, Côte d'Ivoire, Gambia, Guinea, Nigeria, and Senegal), and seven had fertility between four and five births per woman. Total fertility levels in countries in Africa, 2010–2015 SOURCE: United Nations 2015a. Total fertility levels ranged even more widely among the 20 countries in Eastern Africa, from 1.5 in Mauritius to 6.6 in Somalia. One additional country in Eastern Africa still had a fertility level above six in 2010–2015 (Burundi) and six countries had fertility between five and six births per woman (Malawi, Mozambique, South Sudan, Uganda, Tanzania, and Zambia). Eight countries had fertility levels between four and five births per woman. The lowest levels of fertility were in Djibouti (3.3 births per woman) and in the small island countries of Mauritius, Réunion, and Seychelles (less than three births per woman). The nine countries of Middle Africa all had fertility levels at or above four children per woman. In Angola, Chad, and DR Congo, fertility levels were six or more births per woman, and in the remaining six countries fertility levels were between four and five births per woman. While fertility in Southern Africa is largely dominated by South Africa's pattern, the range in fertility among the five countries in the sub-region is narrow, from 2.4 births per woman in South Africa to 3.6 in Namibia. Both Botswana and South Africa now have fertility levels below three births per woman. The start of the fertility transition also varies widely across sub-Saharan Africa. We analyze when and at what level of fertility a country experienced a maximum total fertility level before the onset of fertility decline. This maximum is defined as the most recent five-year time period where total fertility is within half a child of the overall maximum fertility in the country over the 1950–2015 estimation period, thus excluding random fluctuations in pre-transition fertility (Alkema et al. 2011). Figure 4 shows the diversity across countries and within sub-regions in the level and time period of the maximum fertility level before the onset of fertility decline, as assessed in the 2015 Revision. By the late 1970s, 29 sub-Saharan countries were on the verge of a fertility decline, increasing to 40 countries by the early 1980s. While the maximum fertility before the onset of fertility decline was reached in all countries in Southern Africa by the late 1970s, the range of experiences was much wider among countries in Eastern Africa (from the early 1950s in Réunion to the late 1990s in Somalia), Middle Africa (from the late 1960s in Angola to the late 1990s in Chad and DR Congo), and Western Africa (from the early 1960s in Cabo Verde to the late 1990s in Niger). Maximum total fertility in the time period before the onset of fertility transition, sub-Saharan African countries by sub-region SOURCE: United Nations 2015a. The maximum fertility before the onset of fertility transition ranged from less than six births per woman in five countries (Central African Republic, Equatorial Guinea, Gabon, Lesotho, and Seychelles) to more than eight births per woman in two countries (Kenya and Rwanda). There was a positive but weak relationship between the maximum fertility level and the timing of when fertility transition commenced (R2 = .04). The transition from the maximum fertility to the current estimated fertility level in 2010–2015 has been slow for most countries in sub-Saharan Africa. We examine both the maximum decline in fertility in a five-year period and the duration of time between the maximum fertility level and when a country achieved a 10 percent decline in total fertility. A 10 percent decline in total fertility is one of several empirical rules that researchers have used to identify when fertility has begun to decline in a sustained manner from a pre-transitional maximum (Bongaarts and Casterline 2013; Coale and Treadway 1986; United Nations 2014), including differences in the time period selected to identify the onset of fertility decline (Casterline 2001) and the magnitude of decline (e.g., 5 percent decline with further conditions for subsequent changes applied, see Bryant 2007). While the different rules all strive to distinguish sustained decline from random fluctuations in fertility levels, each rule will have different repercussions for interpretations about the timing of onset of fertility decline, duration and pace of decline, and correlations with levels of development and other indicators. In seven countries the first steps of fertility decline took place over a long time period. In Angola, Gambia, and Uganda, a 10 percent decline from the maximum fertility level took 40 years; and in Lesotho, Mozambique, Niger, and Tanzania, it took 30 to 35 years (Appendix Table 1).4 In other countries the fertility decline never gained speed. Overall declines from the country-specific maximum fertility level to the level in 2010–2015 were very slow in nine countries (Angola, Congo, Gambia, Mali, Mozambique, Niger, Nigeria, Uganda, and Tanzania), where average fertility declines were 0.2 children per woman or less, a pace at which it would take at least 25 years to realize a decline of one birth per woman (Appendix Table 1). During the fertility transition, some countries experience an acceleration of fertility decline that, based on historical experience of past transitions in Latin America and the Caribbean and Asia, might reach a decline of more than one birth per woman in a five-year period (United Nations 2015a). In most countries in sub-Saharan Africa, however, the maximum fertility decline is much smaller. The largest declines of more than one birth per five-year period were registered in the early-transition countries in Eastern Africa before 2000 (Djibouti, Mauritius, Mayotte, Réunion, Rwanda, Seychelles, and Zimbabwe). For some countries the maximum fertility decline is projected to be reached in the future: one country in Eastern Africa (Mozambique), four in Middle Africa (Angola, DR Congo, Equatorial Guinea, and Sao Tome and Principe), and five in Western Africa (Gambia, Guinea, Mali, Niger, and Nigeria). Figure 5 shows that countries reaching the maximum fertility decline later tend to reach it at lower levels (the correlation across the 50 countries is R2 = .45). Maximum five-year decline in total fertility since the onset of fertility transition, actual and projected, sub-Saharan African countries by sub-region SOURCE: United Nations 2015a. The pace of fertility decline is illustrated in Figure 6 for Ethiopia and Nigeria, the two most populous countries in sub-Saharan Africa. Estimated levels of total fertility from 1950–1955 to 2010–2015 are shown with a fitted model of the fertility transition. Both countries reached maximum fertility levels before the onset of fertility decline between the late 1970s and early 1980s, and both reached a 10 percent decline from this maximum in the early 2000s. While Ethiopia reached the peak pace of fertility decline in 2005–2010 (a decline of nearly one birth in the five-year period), Nigeria's fertility decline has been consistently slow, with a low peak pace of decline. The maximum fertility decline per five-year period in Nigeria is projected to be reached in the future (a decline of 0.3 births in 2020–2025). The difference in the pace results in current total fertility of 4.6 births per woman in Ethiopia and 5.7 in Nigeria. The 80 percent prediction intervals (dashed lines in Figure 6) around the probabilistic projections of total fertility indicate the magnitude of the different fertility changes that could reasonably happen. For example, by 2045–2050 there is a one in ten chance that total fertility in Nigeria could be as low as 2.6 or as high as 4.4 (Figure 6 and Appendix Table 2). Observed decline in total fertility from 1950–1955 to 2010–2015, predicted decline, and time period of maximum TFR and maximum decline, Ethiopia and Nigeria SOURCES: United Nations 2015a and computations by authors. Given the slow pace of fertility decline in most sub-Saharan African countries thus far and the uncertainty around the pace of future declines, what might be the impact on future fertility levels and the growth in total population if fertility declines in the region followed an accelerated pace that has already been experienced by countries that have completed or are nearing completion of the fertility transition? To answer this question, we generated probabilistic fertility scenarios for 2015–2100 using a modeling approach described in Alkema et al. (2011) and implemented in a publicly accessible software package BayesTFR (Ševčíková, Alkema, and Raftery 2011). The standard United Nations 2015 probabilistic results pool the experience of all countries having similar fertility levels and trends (the baseline scenario). An alternative probabilistic scenario was created using only the fertility transition experiences of 21 countries5 that shared a similar pattern of accelerated decline in fertility (the accelerated scenario): specifically, a slow pace at the start of the transition that sharply rises to a peak pace of decline before steadily tapering off after total fertility has reached about four births per woman. These 21 countries, which include—among countries with more than 10 million inhabitants in 2015—Bangladesh, China, El Salvador, Morocco, Peru, South Africa, Sri Lanka, Thailand, Turkey and Uzbekistan, represent disparate institutional, social, economic, and cultural contexts and yet experienced a similar pattern of a relatively abrupt acceleration of fertility decline. The objective of this exercise is to examine the impact on population size of fertility decline that is more rapid than currently projected, and to illustrate the implications of such a hypothetical scenario. While we do not theorize or analyze the factors that produced these rapid fertility declines, the fact that a similar pattern of fertility decline took place within such a diverse group of countries raises the possibility that a similar decline could occur within a region that also reflects quite distinctive and diverse contexts. Each fertility scenario is used to simulate 10,000 probabilistic population projections for 2015–2100 under identical conditions (i.e., using the same mortality and migration assumptions) that show the population growth trajectories if sub-Saharan African countries were to follow a specific fertility decline pattern.6 The implications of this specific fertility decline pattern for future fertility trends are shown in Figure 7 for Ethiopia and Nigeria. The accelerated fertility decline scenario leads to much more rapid declines for these countries. By 2045–2050, median projected total fertility in Ethiopia would decline from 2.3 (baseline) to 2.0 (accelerated decline) and in Nigeria from 3.6 (baseline) to 2.6 (accelerated decline) (see Appendix Table 2). Probabilistic fertility projections (median and 80 percent prediction intervals) for two scenarios: baseline and accelerated fertility decline, Ethiopia and Nigeria SOURCES: United Nations 2015a and computations by authors. The accelerated fertility scenario has greater implications for projected fertility in Nigeria, where the recent pace of fertility decline has been much slower than in Ethiopia. The projected medians of the accelerated scenario are similar to the lower bound of the baseline scenario for parts of the projections, suggesting that Ethiopia and Nigeria would need to experience a rapid fertility decline, similar to the rapid declines experienced by the group of 21 countries, in order to realize the lower-bound fertility level of the baseline scenario. The assumption that Ethiopia and Nigeria would follow the fast fertility decline experiences of these 21 countries leads to substantially lower population projections compared with the baseline scenario (Figure 8 and Appendix Table 3). If Ethiopia experienced an accelerated fertility decline, the projected population grows from 99 million in 2015 to 182 million by 2100 (80 percent prediction interval of 93 million to 324 million) compared with the higher median projection of 234 million under the baseline scenario. If Nigeria adopted the accelerated fertility decline pattern, the projected population grows from 182 million in 2015 to a median of 466 million by 2100 (80 percent prediction interval of 282 million to 777 million) rather than the faster projected growth to 737 million under the baseline scenario. Probabilistic population projections (median and 80 percent prediction intervals) for two scenarios: baseline and accelerated fertility decline, Ethiopia, Nigeria, and sub-Saharan Africa SOURCES: United Nations 2015a and computations by authors. The counterfactual of sub-Saharan African countries following an accelerated fertility decline, as experienced by the group of 21 countries, results in a projected increase in total population in the region from 962 million in 2015 to 3.2 billion by the end of the century (with 80 percent probability of being between 2.8 and 3.7 billion). The total population projection for the baseline UN 2015 scenario would lead to a median projection of about 4 billion, or a difference of 770 million people with an 80 percent prediction interval mostly above the upper bound of the accelerated fertility decline scenario. We presented here an updated description of fertility decline in sub-Saharan Africa and have explored the implications for fertility and population projections if sub-Saharan African countries follow a pattern of accelerated fertility decline. Because estimates of fertility in the region rely almost entirely on survey and census data, there is still uncertainty about fertility change over time. Our analyses of trends over time were based on a new historical time series of total fertility estimates for the period 1950 to 2015 from the 2015 Revision of World Population Prospects. Fertility has remained persistently high in Eastern, Middle, and Western Africa (4.9 births per woman or higher as of 2010–2015) and declined rapidly in Southern Africa, which currently has about half the total fertility level of other sub-regions births per woman). Southern Africa is dominated by South Africa, TFR of 2.4 is the lowest in the Yet there is wide variation in total fertility across countries, even within from below fertility births per woman) in Mauritius to 7.6 births per woman in Niger. The fertility level before the onset of decline was high in all countries in sub-Saharan Africa, from less than six births per woman in five countries to more than eight births per woman in two countries. By the late 1970s, 29 countries were on the verge of fertility decline, increasing to 40 countries by the early 1980s. The transition from these maximum levels of fertility prior to the onset of fertility decline to current levels has been slow for most countries, including seven in which it took 30 years or more to a 10 percent decline in total fertility. While countries in Asia and in Latin America and the Caribbean experienced an acceleration in fertility decline of more than one birth per five-year time period, this level of acceleration has been experienced thus far by only seven countries in Eastern Africa before the The pace of fertility decline in sub-Saharan Africa will a large in the magnitude of future growth in We showed through an illustrative scenario that an acceleration in the pace of fertility decline to that already experienced by 21 countries South Africa) would the growth in future population in the region from a projected billion by to billion and total population size from a projected 4 billion people by the end of the century to 3.2 While these 21 countries represent a wide range of institutional, social, economic, and cultural a similar fast decline from fertility levels of six or more children per woman in the past to less than two or three in recent years. this accelerated pace of fertility decline to countries at of transition illustrates the substantial impact on future population growth of other possible patterns of fertility decline in sub-Saharan Africa. of this are assumption that the fertility estimates from the World Population Prospects are and the fact that uncertainty around the estimates of period total fertility in recent is not into By scenarios on the distinct fertility decline patterns that have been experienced thus far by countries that have completed or are advanced in their fertility we new patterns of fertility decline in the Because most countries in Middle Africa and Western Africa are still in the early of fertility transition, an sub-Saharan African pattern of fertility decline may still and Timæus The is not for the or of by the authors. than be to the for the

Aim: Developing and promoting a culturally relevant school curriculum in the teaching and learning environment is one step to overcoming systemic inequalities and closing the education achievement gap of learners of African descent. This paper proposes methodological approaches for integrating African Indigenous Knowledge Systems (AIKS) into Cameroon's formal education system to promote cultural relevance and educational equity. Methods: This paper is conceptual in nature with contextual narrative analysis of empirical literature. This paper was anchored on the Integrated Theoretical Framework by Dasen, 2003 and the Developmental Niche Theory by Super & Harkness, 1986. Results: The issue of education in Africa and Cameroon in particular, has been central to the curriculum development process since independence and reunification to the present. Post-colonial school curricula in Cameroon are mostly dominated by western values, knowledge and pedagogies at the expense of indigenous knowledge and epistemologies. Integrating African indigenous knowledge systems (AIKS) into Cameroon's educational system could improve its relevance. This is due to the holistic, community-based nature and approach of AIKS to education and knowledge production. However, this requires an African indigenous theoretical framework of knowledge to guide the integration process. The framework should also clarify the relevance of African Indigenous languages in knowledge production and share in the era of globalisation. Conclusion: Researchers have highlighted the need for inclusion of indigenous knowledge systems in formal schooling but there is little literature as to how exactly these systems can be included. Recommendation: The methodology to include indigenous knowledge systems in schools include but are not limited to: Inclusion as Independent Subjects and inclusion as Instructional and Learning Methods in Mainstream Subjects (e.g., curriculum reform processes, teacher training needs, community involvement). The Role of Elders in Teaching Indigenous Knowledge Systems.

Natural resources play a critical role to societies. Many people in developing countries conform their livelihoods and life style to nature. However, natural resources in resettlement areas of Zimbabwe are increasingly becoming degraded despite their importance. The study sought to assess how the adoption of indigenous knowledge systems for natural resources management in A1 resettlement areas can reduce resource depletion. The study employed a quasiexperimental design in which communal areas of Zaka District and A1 resettlement areas of Chiredzi District were used as experimental groups. Focus Group Discussions (FGDs) and interviews were used to gather data from traditional leaders and the elderly. In addition, observations were made to complement data from FGDs and interviews. The study found that a variety of indigenous knowledge systems still exist in communal areas and natural resources protected by indigenous knowledge systems were well preserved. However, in A1 resettlement areas where indigenous knowledge systems have been eroded due to the dynamic social, economic and physical environment there is excessive environmental degradation. There is therefore need to adopt and strengthen the use of indigenous knowledge systems in A1 resettlement areas to curb environmental degradation.