Please enable JavaScript.
Coggle requires JavaScript to display documents.
Changing Population - Coggle Diagram
Changing Population
Population and economic development patterns
Factors affecting population distribution at a global scale
Human
Places with good communications and potential for trade
Political factors: government planning; decentralization
Physical
Fertile valleys/coast/floodplains such as the Nile Valley
75% live within 1000km of the sea
Places with a regular supply of water
Moderate, temperate climates
85% of global population live between latitudes 68N and 20N
Flat, gentle, low lands
85% live in areas less than 500m high
Global patterns and classification of economic development
High Income Countries (HIC) - developed or more developed economies
While some LICs have seen their GNI per capita rise very slowly between 1994 and 2014, from $180 to $250 in Malawi, income in HICs like Norway has increased massively, from $26010 to $103050 during the same period.
Low Income Countries (LIC)
% of people living in LICs fell by 80% from 1994 to 2014; Countries like Bangladesh, India and Kenya have moved from out of the LIC phase into the low MIC category
Middle Income Countries (MIC)
Some 5 billion people live in MICs, generating 1/3 of the global GDP
China and Mexico are classified as upper middle income countries
Newly Industrializing Countries (NICs)
Countries that have experienced rapid industrial, social and economic growth since the 1960s
BRICS: Brazil, Russia, India, China and South Africa
MINT: Mexico, Indonesia, Nigeria, Turkey
CIVETS, New Eleven and centrally planned economies like Cuba and North Korea
Oil-rich countries - OPEC
Rich in terms of GNI per capita, although not evenly distributed
Least Developed Countries
Sub-Saharan Africa and Afghanistan; very low standards of living
Population distribution and economic development at the national level
China
Concentrated in the eastern part, especially in the coastal zones and lower reaches of the river valley
90% live on 30% of the land
less than 4% live on 50% of the land
Tibet and Inner Mongolia
Physical factors
Limited amount of land that is able to provide for rain-fed agriculture - much of the land is either too dry or too steep
Favored coastal and river locations are also the more favored sites for trade and commerce
The western provinces remain less developed than the eastern ones
China's economic growth has reinforced core-periphery inequalities in population distribution of the east (core) and west (periphery)
More than 50 cities with over a million inhabitants each
Mega-regions/megalopolises
Capital economic zone: Beijing and Tianjin
Pearl River Delta: Hong Kong, Guangzhou, Shenzhen
Yangtze River Delta: Shanghai
Internal migration
since 1978, China experienced the world's largest internal migration when 160+ million migrants have left rural areas to seek work in urban areas
Wages in urban areas were 40% higher than in countrysides
Shenzhen was a settlement of a few thousands in 1978 and now 12 million people live in Shenzhen by 2020
During the 1990s, rural-urban wealth inequalities widened
Land and labor costs are rising
Gov has attempted to direct recent industrial development and the destination of internal migrants to interior regions (Chongqing)
South Africa
Highly uneven - core economic zones like Gauteng have pop densities of over 1000 people/km2 while large areas of the Northern Cape province have densities of less than 5 people/km2
In general, pop decreases from the south east to the north west
Physical factors
access to mineral resources such as diamonds and gold
Good potential for farming and trade such as Durban and Cape Town
Rainfall - lowest pop densities are found in the most arid areas
Internal migration
economic migration due to industrial development until 1950
Many blacks moved from the countryside to the urban areas to work as migrant laborors in the gold and diamond mines between the two world wars
forced migration due to the apartheid movement
The National Party set up the apartheid system in 1948 which forced 4 million blacks to move out of 'white' areas; there are also restrictions preventing blacks from entering white towns ('influx control')
Voluntary migration due to the collapse of the apartheid system
Many blacks moved back to cities in search of work; up to 2.4 million blacks moved from white-owned commercial farms to nearby towns between 1994 and 2004
Urban pop grew from 55% in 1995 to 65% in 2015
High natural increase - 70% in Gauteng between 1996 and 2001
Circular migration
Moves repeatedly between home and host areas
Farms are seemed as preferred place for retirement
In order to supplement income, a family member (increasingly more women) will seek work in an urban area, leaving children to be cared by grandparents
Circular migrants usually take poorly paid insecure jobs in informal sectors
high cost of living in cities and the need for grandparents to take care of children make this form of migration common
Changing population and places
Population Change and Demographic Transition
Demographic Transition Model (DTM)
- based on data from England, Wales and Sweden
refer to textbook diagram p397
Natural increase
birth rate - death rate, expressed in percentage
Does not take into account migration, while overall population change does
Doubling time - number of years needed for a pop to double in size
DT=70/rate of natural increase (%)
Population momentum
Tendency for a population to grow despite a fall in the birth rate or fertility levels
Occurs because of a relatively high concentration of people in the pre-childbearing and childbearing years
as these people grow older and move through their reproductive years, the greater number of births will exceed the number of deaths in the older population
Total Fertiltiy Rate
The average number of live births per thousand women of childbearing age per year
Changes in TFR are a combination of both socio-cultural and economic factors; as LICs develop and move towards HICs, their TFR generally decline
The status of women
Inequality between the sexes in life expectancy, education and standards of living
Singapore: between 1960 and 2000, there are great social and economic changes resulting in full employment including for women. TFR fell from 3 to 1.51 in 2000 and 0.81 in 2015
Level of education and maternal ambition
the more educated parents are, the fewer children they will have
Middle income families have the smallest families since they have high aspirations but limited means to improve their living standards compared to the affluent who can afford to have large families
Maternal health
Women who are not healthy tend to get pregnant more frequently because of high infant mortality rate and more unsuccessful pregnancies
Religion
Most religions including Catholicism are pro-natalist, opposed to birth control and contraception
Economic prosperity
Economic prosperity favors increased birth rate but increased costs of living lead to declines in birth rate
The more equitable the distribution of wealth, the lower the TFR
The need for children
High infant mortality leads to high compensatory or replacement briths
To provide labor for farms and as security for parents in old age
Location of residence
Rural areas more children than cities
rigid social pressure on women
less state control (China's one child policy less stringent in rural areas)
Fewer economic and educational opps for women
High birth rates in large urban areas due to young pop structure
Life expectancy
The average number of years a person can be expected to live from birth
LE rise over time for most countries due to better food supply, cleaner water and adequate housing
Babies born in 2007 in Japan are expected live at an average of aorund 107 years
In the 40 countries with the lowest LE, only 2 are not in the sub-Saharan region
A combination of poverty, conflict and the AIDS virus
Often higher for women than men due to lifestyles and other socioeconomic factors
Longer LE doesn't mean a good living standard/condition in old age
Population pyramid
Refer to p401 and p402
Dependency ratio
[Population aged <16 + pop aged>64 (the dependents)]/pop aged 16 to 64 (the economically active)
Megacity growth
Case study: Mumbai
India's largest city, with a pop of around 18 million
Financial, commercial and entertainment center of India
Many TNCs such as the Tata group
Home to financial instituions such as the Reserve Bank of India and the National Stock Exchange of India
Scientific industries such as the Department of Atomic Energy (nuclear)
25% of India's industrial output, 6% of total GDP and 40% of foreign trade; per capita income is 3 times the national average; gender ratios lower than the national average (greater incidence of male migration)
Mumbai has diversified its economy since the 1970s to include industries such as computers, engineering and electronic equipment
Challenges
nearly 10 millions live in slums
Limited security of tenures
Dharavi
, 2 km2, is home to 1 million people
There is great pressure to clear parts of Dharavi for modern development due to its proximity to Mumbai's financial and commercial district
Informal sectors
Up to 85% of adults in Dharavi work locally, and there are major recycling industries and pottery industries
Dangerous working conditions
up to 4000 cases of diphtheria and typhoid a day due to a lack of proper sewerage system
Access to water is limited and many pumps are available for only 2 hours a day
For the migrants
Migration to megacities provide many with higher standards of living and quality of life due to better jobs, education, infrastruscture, etc.
Migration to megcities can also lead to underemployment, poor quality housing (in slums/ghettos) and the risk fo environmental hazards for some
For megacities/societies
Compact cities - large numbers of people living in proximity make it easier to provide public transport, housing and healthcare (more efficient)
If exceeds carrying capacity, the provision of such services would be inadequate - traffic congestion, air pollution, declining water quality
Forced migration
Conflict-induced:
Development-induced
Disaster-induced
Case Study: Syria
Types of migrants
Challenges and Opportunities
Aging population
Demographic Dividend
Youthful population
Human trafficking