scholarly journals Determination of the Level and Trend of Fertility in Four Provinces in South Africa

2021 ◽  
pp. 41-52
Author(s):  
K. A. KYEI ◽  
R. S. RAMUYA

Relevance of the research: Th e study of fertility and mortality is of great importance because it shows the dynamics of the population and the need for eff ective planning measures required to be put in place to avert catastrophe. It is therefore important for South Africa also to check whether its fertility is heading toward the same trajectory seen in these developed countries. Purpose of the article: This study seeks to determine the level and trend of the fertility in South Africa using four provinces, Mpumalanga, Kwazulu-Natal, North West and Limpopo, for the years 2011, 2012, 2013 and 2014, as case studies. Th us, the study aims to determine: (a) Whether the fertility rate was changing in the provinces during the years 2011, 2012, 2013 and 2014. (b) What is the trend? And; (c) Whether the fertility is falling below replacement level or not. Scientifi c novelty of the article: Th e study shows that fertility in South Africa has indeed declined with some provinces having the level of fertility below replacement level. Th e decline seen in this study is mainly due to the fertility of the black majority population. Th e high population growth rate was mainly due to the fertility of the blacks, therefore, when recent fertility levels in the country are low, the implication is that the fertility of the blacks has gone down, and in fact this is what this study is showing, and advises that unless measures are put in place, the fertility of the blacks or fertility in South Africa will go down below replacement level. Fertility levels have declined worldwide, including South Africa. But the extent to which South Africa’s fertility has declined is not very clear because data from two previous censuses on fertility and mortality were very poor. South Africa (SA) had reliable data on the White popula-tion of the country, but with the new dispensation since 1994, data collection, especially from the black population that forms majority, has not been easy. Th e quality of data from the black population that accounts for over 80 percent of the population has not been good and reliable, probably because of the low level of education of this segment. Fertility and mortality data from the two previous censuses, 2001 and 2011, were not reliable when compared with data from vital statistics and national population register. Th us, estimates made from these censuses’ data on these events are questionable. South Africa, however, has data from the General Household Surveys (GHS), and this study uses data from these surveys to attempt to fi nd the level and trend of fertility. Th e GHS is an annual household survey which measures the living circumstances of South African households. Demographic and statistical methods are used to calculate measures, like the UN age ratio scores, to assess the quality of the data from four provinces, namely, North West, Kwazulu-Natal, Mpumalanga and Limpopo provinces, for the period 2011 to 2014. Th e four provinces are selected as a case study to compare rural and urban fertility characters. Th e results show that the quality of the survey data is fairly good and reliable with KwazuluNatal province having the most reliable data. Th e fertility levels were lowest in the more urbanized and educated provinces of Kwazulu-Natal and North West, and highest in the less educated and rural provinces of Limpopo and Mpumalanga. Th e study further shows that fertility in all the provinces has been declining since 2012, with the gross reproduction rate falling below replacement level; with implication that the fertility of the black population is declining fast. Th e decline in the fertility level could be attributed to quite a number of factors including education, urbanization, and improvement in primary health care. Because of the sharp decline in the fertility level in the recent years, the study calls for proper policy intervention to avoid population “extinction”.

2014 ◽  
Vol 54 (3) ◽  
pp. 279-285 ◽  
Author(s):  
Ncoza C. Dlova ◽  
Avumile Mankahla ◽  
Nomandla Madala ◽  
Anneke Grobler ◽  
Joyce Tsoka-Gwegweni ◽  
...  

Oryx ◽  
2000 ◽  
Vol 34 (1) ◽  
pp. 46-55 ◽  
Author(s):  
Anna. M. Whitehouse ◽  
Anthony. J. Hall-Martin

AbstractThe history of the Addo elephant population in South Africa, from the creation of the Addo Elephant National Park (AENP) in 1931 to the present (every elephant currently living within the park is known), was reconstructed. Photographic records were used as a primary source of historical evidence, in conjunction with all documentation on the population. Elephants can be identified in photographs taken throughout their life by study of the facial wrinkle patterns and blood vessel patterns in their ears. These characteristics are unique for each elephant and do not change during the individual's life. The life histories of individual elephants were traced: dates of birth and death were estimated and, wherever possible, the identity of the individual's mother was ascertained. An annual register of elephants living within the population, from 1931 to the present, was compiled, and maternal family trees constructed. Preliminary demographic analyses for the period 1976–98 are presented. The quantity and quality of photographs taken during these years enabled thorough investigation of the life histories of all elephants. Prior to 1976, insufficient photographs were available to provide reliable data on the exact birth dates and mothers' identities for every calf born. However, data on annual recruitment and mortality are considered sufficiently reliable for use in analyses of the population's growth and recovery.


Zootaxa ◽  
2011 ◽  
Vol 3093 (1) ◽  
pp. 1 ◽  
Author(s):  
PHILIP D. PERKINS

The southern African species of the water beetle genus Ochthebius Leach, 1815, are reviewed. Eight new species are described, and new collection records are given for eight previously described species, based on the examination and databasing of 8,919 specimens from 253 localities/events. Male genitalia of the new species are illustrated, and high resolution habitus images of the holotypes of new species are provided. Distribution maps are given for the 18 species of Ochthebius now known from southern Africa, including Namibia, South Africa, Lesotho, Zimbabwe, the extreme southern part of Angola, and the southern part of Mozambique. New species of Ochthebius are: O. anchorus (South Africa, KwaZulu-Natal Province, Oribi Gorge); O. bicomicus (South Africa, Western Cape Province, 22 mi. N. Nelspoort); O. bupunctus (Namibia, Kaokoveld, Kunene River, Swartbooisdrift); O. endroedyi (South Africa, North West Province, Barberspan); O. granulinus (South Africa, Western Cape Province, Elandsdrift); O. involatus (South Africa, Western Cape Province, near Kommetje); O. sitiensis (Namibia, Okau Fountain, 12.5 km inland); and O. zulu (South Africa, KwaZulu-Natal Province, Nqutu).


2019 ◽  
Vol 11 (4) ◽  
pp. 1145 ◽  
Author(s):  
Omolola Adisa ◽  
Joel Botai ◽  
Abiodun Adeola ◽  
Abubeker Hassen ◽  
Christina Botai ◽  
...  

The use of crop modeling as a decision tool by farmers and other decision-makers in the agricultural sector to improve production efficiency has been on the increase. In this study, artificial neural network (ANN) models were used for predicting maize in the major maize producing provinces of South Africa. The maize production prediction and projection analysis were carried out using the following climate variables: precipitation (PRE), maximum temperature (TMX), minimum temperature (TMN), potential evapotranspiration (PET), soil moisture (SM) and land cultivated (Land) for maize. The analyzed datasets spanned from 1990 to 2017 and were divided into two segments with 80% used for model training and the remaining 20% for testing. The results indicated that PET, PRE, TMN, TMX, Land, and SM with two hidden neurons of vector (5,8) were the best combination to predict maize production in the Free State province, whereas the TMN, TMX, PET, PRE, SM and Land with vector (7,8) were the best combination for predicting maize in KwaZulu-Natal province. In addition, the TMN, SM and Land and TMN, TMX, SM and Land with vector (3,4) were the best combination for maize predicting in the North West and Mpumalanga provinces, respectively. The comparison between the actual and predicted maize production using the testing data indicated performance accuracy adjusted R2 of 0.75 for Free State, 0.67 for North West, 0.86 for Mpumalanga and 0.82 for KwaZulu-Natal. Furthermore, a decline in the projected maize production was observed across all the selected provinces (except the Free State province) from 2018 to 2019. Thus, the developed model can help to enhance the decision making process of the farmers and policymakers.


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