World Population Growth

The theme of Dr. Kuhn's paper is that Darwin's theory of evolution to explain the origin of species is inadequate, and that the 2010 decision by the Texas State Board of Education to require textbooks to present the weaknesses, as well as the strengths, of Darwin's theory was appropriate. The three limitations of Darwin's theory concern the origin of DNA, the irreducible complexity of the cell, and the paucity of transitional species. Because of these limitations, the author predicts a paradigm shift away from evolution to an alternative explanation. The intellectual problem, in my opinion, is not that evolution has “fatal defects,” but rather that it remains a suspect theory for most Americans >150 years after the publication of The Origin of Species (1859). While the Texas State Board of Education may have debated the issue for 3 full days in 2010, its recommendation in the end will probably be ignored by scientists who write textbooks. I suppose the Texas decision represents progress. Tennessee's Butler Act made it unlawful to teach evolution, giving rise to the Scopes trial in 1925, in which John T. Scopes, a high school teacher, was accused of violating that law. After an 8-day trial, a guilty verdict was reached. To embrace the idea that all forms of life, great and small, plant and animal, primate and nonprimate, were derived from a common primordial cell or organism requires a scientific perspective. The various religions, current and extinct, typically elevate humans above other forms of life. Most Homo sapiens believe that the different species on planet earth were created independently by a God, in sequential batches, placed in certain locales, with the Homo sapiens inherently superior, made in the image of the creator—thus, the resistance to the concept of evolution. With respect to the origin of DNA as a weakness of Darwinism, our knowledge of DNA, from my reading, has added to, not subtracted from, the evidence of evolution. In the 2006 preface to the 30th anniversary edition of The Selfish Gene (first published by Oxford University Press in 1976), author Richard Dawkins wrote: The correct word of the title to stress is “gene” and let me explain why. A central debate within Darwinism concerns the unit that is actually selected: what kind of entity is it that survives, or does not survive, as a consequence of natural selection. That unit will become, more or less by definition, “selfish.” … Let me repeat and expand the rationale for the word “selfish” in the title. The critical question is which level in the hierarchy of life will turn out to be the inevitably “selfish” level, at which natural selection acts? The Selfish Species? The Selfish Group? The Selfish Organism? The Selfish Ecosystem? Most of these could be argued, and most have been uncritically assumed by one or another author, but all of them are wrong. Given that the Darwinian message is going to be pithily encapsulated as The Selfish Something, that something turns out to be the gene, for cogent reasons which this book argues. The notion of “irreducible complexity” in a cell, as an argument against evolution, is beyond my present understanding. Knowing that life has existed on planet earth for billions of years, however, I suspect that there has been time enough for evolution, no matter how complex, with reducibility. With respect to transitional species, a brief glance through recent issues of National Geographic shows no paucity of data from paleontologists. Human lineage can be traced back >6 million years, with fossils discovered in East Africa from all three major phases of hominid evolution—Ardipithecus, Australopithecus, and Homo—with a divergence from living ape species (chimpanzee and bonobos) roughly 8 to 6 million years ago. Transitional species have been identified in numerous other groups. The whale, for example, accomplished an enormous transformation, with fossil evidence. Fifty million years ago it was semi-terrestrial; now it is fully aquatic. Seven billion Homo sapiens now inhabit planet earth. World population in ad 1 (the time of Christ) was about 200 million. In the struggle for survival in the next century and beyond, the hand of natural selection will be at work, I believe, and evidence of evolution, to explain the origin, modification, and behavior of species, will continue to increase. Editor's note: Gregory Dimijian, MD, is also preparing a full-length article on Darwinism, which Proceedings will publish in an upcoming issue.

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

Eastern Africa has for several years been an important area for investigations into early hominid evolution. Depositional factors related to the subsiding Rift Valley system have provided favorable situations for fossils to be preserved, and subsequent erosion has caused fossiliferous sediments to become exposed for surface collection and excavation. Intercalations of potassium-rich volcanic ash layers or tuffs have allowed an unprecedented chronological documentation by potassium-argon dating techniques, and in recent years paleomagnetic dating has been a valuable adjunct to these results. Thus, not only have early hominid fossils been preserved and discovered in eastern Africa, but geological circumstances have facilitated their accurate dating. Eastern Africa has also seen the flowering of an empirical paleoanthropology, i.e. one which is supported by data collected in such a way that questions relating to early hominid evolution, paleobiology, and paleoecology can be answered. In addition to the elucidation of hominid phylogenesis, the documentation of early hominid behavior is a primary focus of research. Better dating techniques, paleoecological investigations, and multidisciplinary approaches have all contributed to this research. Some of the major recent advances in early hominid studies in eastern Africa are discussed here. The time period treated extends from approximately 4 to 1 million years before the present (my BP). The multidisciplinary research project has profoundly affected paleoanthropological research in eastern Africa, and has now spread to other areas

The growth and development performance of the Middle East and North Africa (MENA) region presents one of the major anomalies that current economics literature seeks to resolve, which is how to reconcile the existence of massive natural resources with the high unemployment, low growth and the general underdevelopment of the region. In this debate, much attention is focused on the problems arising from: a) state oriented inward looking economic policies, b) lack of ‘integration’ with the world economy, c) underdeveloped financial sectors and chilling investment climate, and d) low levels of human capital development. In this paper, we attempt to present a summarized yet more balanced and hopefully more insightful analysis of the growth and development experience of the countries in the region with a special attention given to the existing bottlenecks hindering future development prospects. While discussing the MENA region as a whole we will divide the countries into five subgroups: 1) oil rich labor importing states (Bahrain, Kuwait, Oman, Libya, the United Arab Emirates, Qatar, and Saudi Arabia) 2) oil rich labor abundant states (Algeria, the Islamic Republic of Iran, Iraq, Syria), 3) oil poor labor abundant NICs (Egypt, Morocco, Turkey), 4) oilpoor limited natural resource states (Israel, Tunisia, West Bank and Gaza, Jordan, Lebanon), and 5) natural resource poor states (Sudan, Yemen). (Richards and Waterbury, 1996). Although the inclusion of Turkey, Israel, and Iran is controversial as the trajectory of the Arab and other Middle Eastern countries constitute a more appropriate whole, they share many commonalities as well. However, unless stated otherwise, the general statements will exclude Turkey and Israel. The economic history of MENA region is characterized by several cycles of growth and accumulation. In retrospect, the region formerly enjoyed higher levels of economic development and prosperity compared to its counterparts in Europe. While Istanbul with its 700,000 inhabitants in 16 century was the largest city in the world, North Africa overall was much more urbanized than Europe (Paris with 125,000 inhabitants vs. Cairo with 450,000 around 1500) (Bairoch, 1997:517-537). However, in the last of these cycles, the region experienced a decline in its growth and development indicators starting from early 18 century with the factors that precipitated this decline remaining a source of continuing debate. The current essay will focus

Highland bananas are an important staple food in East Africa, but there is little information on their physiology and growth patterns. This makes it difficult to identify opportunities for yield improvement. We studied allometric relationships by evaluating different phenological stages of highland banana growth for use in growth assessment, understanding banana crop physiology and yield prediction. Pared corms of uniform size (cv. Kisansa) were planted in a pest‐free field in Kawanda (central Uganda), supplied with fertilizers and irrigated during dry periods. In addition, tissue‐cultured plants (cv. Kisansa) were planted in an adjacent field and in Ntungamo (southwest Uganda), with various nutrient addition treatments (of N, P, K, Mg, S, Zn, B and Mo). Plant height, girth at base, number of functional leaves and phenological stages were monitored monthly. Destructive sampling allowed derivation of allometric relationships to describe leaf area and biomass distribution in plants throughout the growth cycle. Individual leaf area was estimated as LA (m2) = length (m) × maximum lamina width (m) × 0.68. Total plant leaf area (TLA) was estimated as the product of the measured middle leaf area (MLA) and the number of functional leaves. MLA was estimated as MLA (m2) = −0.404 + 0.381 height (m) + 0.411 girth (m). A light extinction coefficient (k = 0.7) was estimated from photosynthetically active radiation measurements in a 1.0 m grid over the entire day. The dominant dry matter (DM) sinks changed from leaves at 1118 °C days (47% of DM) and 1518 °C days (46% of DM), to the stem at 2125 °C days (43% of DM) and 3383 °C days (58% of DM), and finally to the bunch at harvest (4326 °C days) with 53% of DM. The allometric relationship between above‐ground biomass (AGB in kg DM) and girth (cm) during the vegetative phase followed a power function, AGB = 0.0001 (girth)2.35 (R2 = 0.99), but followed exponential functions at flowering, AGB = 0.325 e0.036(girth) (R2 = 0.79) and at harvest, AGB = 0.069 e0.068(girth) (R2 = 0.96). Girth at flowering was a good parameter for predicting yields with R2 = 0.7 (cv. Mbwazirume) and R2 = 0.57 (cv. Kisansa) obtained between actual and predicted bunch weights. This article shows that allometric relationship can be derived and used to assess biomass production and for developing banana growth models, which can help breeders and agronomists to further exploit the crop's potential.

East Africa's coastal mountains, island massifs jutting up out of the surrounding savannas, have a thirty-million-year natural history as biological refuges. Their slopes have been watered for millennia by the Indian Ocean monsoons and have fostered the evolution of a broad diversity of flora and fauna.1 African farmers have long sought out these climatic and botanical havens and developed around their water sources a sophisticated agricultural production system designed to mitigate the severe droughts which periodically plague eastern Africa. Although long-term settlement in the mountains caused environmental change, its character and scope has yet to be adequately explained. Nonetheless, over the past seventy years, colonial and postcolonial governments have moved to ameliorate what they have perceived as human-induced ecological stress. This article examines the early phase of the colonial debates over environmental degradation and its remedies in the Mlalo basin, an upland region in the West Usambara mountains of Tanzania. The policy discussions regarding Mlalo occurred in the context of a general crisis in colonial society between 1929 and 1940, during which colonial perceptions of agroecological decline and the economic pressures of depression challenged European colonial governments in Africa and Asia. In terms of ecological issues, worldwide concern over erosion in the American Dust Bowl resonated across East Africa, resulting in an official preoccupation with soil conservation. Tanganyika Territory's Mlalo basin came to be cited in the 1930S as one of several particularly striking manifestations of soil degradation and agroecological decline.2 When a food shortage known as njaa ya Chankola (Chankola's famine) struck between 1941 and 1946, the specter of human and environmental catastrophe justified colonial degradation scenarios, which in turn guided the colonial government's attempt between 1946 and 1949 to modernize husbandry via the Mlalo Basin Rehabilitation Scheme.3 Recent scholarship in the social sciences has raised a number of questions regarding the course and interpretation of environmental degradation in Africa and Latin America. Many of these studies cite the historical tendency of Western (or

The environmental unsustainability becomes constantly aggressive Globally and that causes threats to human life and nature in general. Climate change consists of multivariant like storms, heatwaves, floods, and earthquakes and all these are caused by human pollution to the environment. Recently, the Eastern Africa in 2024 April was severely attack by the floods where humanitarian were the casualties. In Kenya over 300 people were reported dead while in Tanzania, Malawi, Mozambique, and Sudan was also very high number of fatalities. People lost their homes and belongings, while agricultural damages were also very severe and that resulted in food shortages. South Africa and Brazil were also affected by the floods which killed and caused damages. The KwaZulu-Natal floods were so strong where 139 Schools were destroyed and both industrial and residential were demolished. The purpose of this article is to identify the causes of climate change and how to ensure environmental sustainability to eradicate this threat. The most affected population in African countries are the rural villages as they don’t have quality household structures and infrastructures. Commonly, no household in rural villages is registered with the Deeds office in South Africa and again, they are not insured against natural disasters of this nature. There no such a thing of stormwater facilities and engineers in the rural villages. The methodology followed in this article is a pure reliable literature review analysis. The research employed non empirical research by deeply focusing on theoretical systematic and thematic analysis of literature. The findings of this research will contribute significantly to addressing the cause of aggressive climate change and to provide solution to sustainable rural villages living environment.

East Africa's agricultural sector faces profound challenges due to shifting climate patterns, impacting livelihoods and food security across the region. This review examines the evolving climate dynamics in East Africa and their implications for agricultural sustainability. Temperature trends reveal a warming trend, altering agricultural zones and affecting crop growth cycles. Changes in precipitation patterns, including variability in intensity and duration, have a significant impact on water availability, which is critical for irrigation and livestock management. Climate extremes such as droughts, floods, and cyclones are increasing in frequency, disrupting farming communities and exacerbating crop losses and livestock mortality. Seasonal variability further complicates agricultural planning, influencing planting schedules and harvest times. This review synthesises current research, case studies, and data-driven analyses to provide insights into how ecological changes are reshaping agricultural landscapes in East Africa. It highlights the interconnectedness between climate dynamics and agricultural sustainability, stressing the urgency of adopting climate-smart practices and policies to mitigate risks and build resilience. Key strategies include promoting drought-resistant crop varieties, implementing efficient water management techniques, and integrating precision agriculture with climate information services. Policy and institutional frameworks play a crucial role in supporting these efforts by incentivizing climate-resilient practices and investing in agricultural research. By understanding and addressing these regional climate trends, policymakers, farmers, and stakeholders can enhance agricultural resilience, ensure food security, and sustain livelihoods in East Africa amidst ongoing climate challenges. Keywords: Regional Climate, Trends, Agricultural Sustainability, East Africa

The production of plasminogen activator (PA) by two cloned cell lines, one from an ethylnitrosourea-induced glioma (A15A5) and the other from normal adult rat brain (ARBO C9), has been investigated. Three assays were used to detect and measure PA in harvest fluids, cells and cell lysates. Similar levels were detected in harvest fluids from both cell lines. However, the cell and lysate assays indicated much higher levels in the tumor line. When actively growing cells were compared A15A5 cells had approximately 16X more fibrinolytic activity than the control cells with a limit of detection in the order of 10(3) cells or 1 microgram protein (cell lysate). In contrast for the control cells PA could only be detected when upwards of 10(4) cells or 5-10 micrograms protein were assayed. Plaminogen activator in as few as 10(3) tumor cells could be detected in the presence of 10(4) non-tumor cells. Plasminogen activator in 26 micrograms protein of A15A5 cell lysate could also be detected in the presence of 44 micrograms protein from ARBO C9 lysates indicating no inhibitory activity in the control cell lysates. Levels of PA in both harvest fluids and cell lysates were determined as cultures progressed through the growth cycle. For cell lysates this showed a build-up of PA in the normal cell line as the cells approached and attained confluence. A much higher level was measured in the tumor cells soon after seeding and maintained to confluence. No differences in growth cycle-associated changes in secreted PA could be determined in harvest fluids: both cell lines showing similar levels at confluence.

Creating a framework towards integrated health syndromic surveillance and response in Africa

Transfer of a cyanobacterial neurotoxin, β-methylamino-l-alanine from soil to crop and its bioaccumulation in Chinese cabbage

Synchronous mitoses occur in Physarum polycephalum in the absence of cell division. Nucleoside and nucleotide profiles were prepared from synchronously growing P. polycephalum at intervals throughout the growth cycle. Comparison of these profiles demonstrates that the pool of adenosine triphosphate decreases from a high level at prophase to a minimum through mitosis and increases again in the postmitotic period. These events appear to coincide with changes in the pools of adenosine diphosphate and adenosine but not with that of adenosine monophosphate. This observed decrease in the pool of adenosine triphosphate during mitosis was confirmed by direct enzymatic assay. These results presumably reflect the energy demands of the cell during mitosis.

Through reverse transcription-polymerase chain reaction and Northern blot analysis, we identified TBK5, a novel plant-specific kinesin-like protein (KLP) that is highly expressed in interphase tobacco BY-2 cells. TBK5 mRNA was present at a high level throughout the growth cycle, even in cells that had entered the stationary phase, where cell proliferation had ceased. However, transcripts for five other tobacco KLPs that we have identified were preferentially expressed in mitotic cells, and either not or only slightly accumulated in cells that had entered the stationary phase. Thus, TBK5 appears to be a KLP whose cellular function most closely relates to the cortical array of microtubules that plays a key role in plant cell morphogenesis. The predicted structure of TBK5 is characterized by a central motor domain that is phylogenetically distant from those of other reported KLPs, coiled-coil domains located on both sides of the motor domain, and a basic C-terminal domain. In addition, TBK5 has a putative neck domain which is closely related to the neck domain of KLPs with C-terminal motor domains, previously shown to control the direction of KLP movement towards the minus ends. Antibodies against truncated TBK5 recognized a polypeptide with a molecular mass of 74 kDa in cytoplasmic extracts of interphase cells, and this polypeptide cosedimented with microtubules assembled in the cytoplasmic extracts. The 74 kDa polypeptide corresponding to TBK5 dissociated from microtubules with high concentrations of NaCl but was not dissociated by MgATP. We hypothesize that TBK5 functions in the regulation of the arrangement of cortical microtubules.

Eastern Africa maintains a key position in debates surrounding the emergence of Homo sapiens across Africa. Extensive research in the region has revealed a rich fossil record in association with a ‘generic’ but variable Middle Stone Age (MSA) material culture, providing an important laboratory for testing hypotheses about the behavioural evolution of our species. For example, multiple archaeological studies of the eastern African MSA note a link between the distribution and density of sites, archaeological diversity and environmental conditions, with ecology and demography often cited as key drivers of cultural evolution. This article formulates new hypotheses using theoretical models of complex fitness landscapes of evolution and reviews the archaeological and climatic records of Middle-late Pleistocene eastern Africa in the light of these ideas. It proposes that evidence from eastern Africa implicates much of the region as a refugial zone within Pleistocene Africa, providing consistently suitable conditions for survival that were characterised by high and changing biodiversity, facilitating population growth and interconnectivity as well as material culture diversification. Interactions between different evolutionary processes likely resulted in the complex cultural mosaic observed across Africa, including the appearance of ‘specific’ innovations against a backdrop of more ‘generic’ MSA elements.

On the epidemiology, biology and food-dependent reproduction of the feral pigeon (Columba livia)