IB ESS Topic 8.1 Notes: Human Populations and Urban Systems (HL)
IB ESS: Topic 8.1 Notes on Human Populations (HL)
Population Growth and the Planet
Guiding questions framing the unit:
How can the dynamics of human populations be measured and compared?
To what extent can the future growth of the human population be accurately predicted?
Task themes across pages: discuss course learnings and evidence; consider factors that could alter population projections.
Drivers of population change (Page 5):
Fertility (births)
Mortality (deaths)
Migration (movement)
Projections and competing forecasts:
UN projection: world population levels out at about 10 imes 10^9 (10 billion) by the end of the 21st century (2100) and begins to decline thereafter.
Other organizations (e.g., Lancet) project a peak of about 9.7 imes 10^9 (9.7 billion) around 2060, followed by a decline.
Key question: what factors discussed in SL could shift these trajectories (e.g., education, gender equality, health care, policy, economic development, climate impacts)?
Regional patterns and drivers (Page 6):
Most population growth expected to come from Africa due to:
Lower gender equality and education for women (reproductive health, access to education).
Limited access to quality health care.
Europe: expected to decline due to higher female education and workforce participation, and higher living costs.
Conceptual framework: the Doughnut Economics model (Page 7–9):
Biocapacity disparity and crossing social foundations/planetary boundaries are visualized as a doughnut.
The doughnut hole (center) represents the proportion of people lacking essentials (food, housing, healthcare, political freedom).
SDGs aim to lift everyone out of the hole (meet basic needs).
Going outside the ecological ceiling (above) stresses Earth’s life-support systems.
Implication: greater population or higher consumption increases resource demand and waste; sustainable outcomes depend on aligning population/resource use with Earth’s limits.
Essentials and sustainability (Page 8–9):
Meeting basic needs (food, housing, healthcare, political freedom of expression) is a baseline.
If population growth and resource demand are controlled, sustainability (within the doughnut’s ecological ceiling) becomes more feasible.
Wealth, consumption, and biocapacity (Page 10):
Middle-class growth leads to higher consumption of water, meat, dairy, and fossil fuels, increasing waste.
Combined with population growth, this reduces the planet’s biocapacity and can push beyond sustainable limits if not managed.
Connections to policy, ethics, and real-world relevance:
Ethical implications of reproductive rights and gender equality.
Policy relevance of providing education, healthcare, and access to resources.
Practical implications for urban planning, infrastructure, and environmental stewardship.
Age–Sex Pyramids and Dependency Ratios
Age–sex pyramids are used to determine:
Dependency ratio
Population momentum
Dependency ratio definition (Pages 11–12):
Dependent groups: under 15 years and over 64 years.
Economically productive group: 15–64 years.
Dependency ratio (DR) measures the balance of dependents to workers.
High DR occurs with very high or very low fertility.
Dependency ratio formula (Page 12):
DR = rac{Y + O}{W} imes 100
Where:
Y = number of young dependents (under 15)
O = number of old dependents (over 64)
W = number of workers (ages 15–64)
Example calculation: DR = rac{11.105 + 9.341}{38.342} imes 100 = 53.33
Interpretation: for every 100 workers, there are about 53 dependents.
Follow-up task (Pages 13–14):
Calculate dependency ratios for five countries following the website task instructions.
Key features of dependency ratios (Pages 14–15):
A DR of 100 means one dependent per worker (a neutral burden).
Higher DR implies greater fiscal pressure on government services funded by taxes.
As the share of dependents increases, there are fewer workers to fund services, potentially raising taxes to support government needs.
Aging population effects: more people requiring pensions/health benefits and social support.
Government policy can influence DR (examples: China’s one-child policy; policies to attract foreign workers to offset aging populations).
Sub-components of dependency (Page 16):
Child dependency vs Old-age dependency
Notable country examples (Page 17):
Niger:
Overall DR: 108.92
Youthful dependency: 103.50
Old-age dependency: 5.42
Qatar:
Overall DR: 18.38
Youthful dependency: 16.17
Old-age dependency: 2.22
Limitations and problems (Page 18):
Age group delineations do not fit all contexts (LICs). Child labor, education completion ages vary by country.
Retirement ages are fluid and vary by country (e.g., Turkey: 52 (men), 49 (women); Norway/Iceland: 67).
Population Momentum (Pages 19–21)
Concept: population momentum explains continued population growth even after fertility declines.
It depends on the size of the cohort of women of reproductive age and their age distribution.
A larger proportion of young people leads to more births when they reach reproductive age, sustaining growth despite lower fertility rates.
Data example (Page 19): LIC vs HIC demonstration
LIC: Age 15–49 = 90; Age 50+ = 10; Total = 100; TFR = 2;
Births = 90 imes 2 = 180; Final population = 90 + 10 + 180 = 280
HIC: Age 15–49 = 50; Age 50+ = 50; Total = 100; TFR = 2;
Births = 50 imes 2 = 100; Final population = 50 + 50 + 100 = 200
Key takeaway: even with replacement-level fertility (TFR ≈ 2), population can rise temporarily due to momentum.
Watch resources (Pages 20–21):
Dependency Ratio (video): reinforces understanding of the concept.
Population Momentum (video): visual demonstration of the concept.
Trends in Population (Indonesia and Japan) and the Demographic Transition Model (DTM)
Indonesia (Pages 23–26):
DTM stage: currently Stage 3 (declining birth rates, lower death rates, stabilized growth).
Past (1970s–1980s): high birth rates declined due to family planning programs (e.g., "Two Children Enough").
Present: fertility ~ 2.3 children per woman; rapid urbanization; rising education levels; growing middle class; growth slowing, especially in urban areas.
Future (next 30 years): expected to move toward Stage 4 by 2050 with a stabilized population around 335 imes 10^6 (335 million); potential for a demographic dividend from a young population, with aging coming later.
Japan (Pages 27–31):
DTM stage: Stage 5 (very low birth and death rates; shrinking, aging population).
Past (1950s–1980s): post-WWII economic growth, healthcare improvements, urbanization; birth rate declined as women entered workforce; rising costs influenced family size.
Present: fertility ~ 1.3 children per woman; aging population; shrinking labor force; high living costs and work culture deter family growth.
Future (next 30 years): population projected to decline further, potentially below 100 imes 10^6 by 2050; by mid-century, around 40 ext{%} of the population may be over 65.
Influences on both populations (Page 31): comparative factors
Historical: post-WWII growth, urbanization, aging, etc.
Economic: living costs, urbanization, middle-class growth; work culture influencing family size.
Social: aging vs youthful population dynamics.
Political: effectiveness of policies (family planning, incentives) in shaping birth rates.
Demographic Transition Model (DTM) refresher (implicit):
Stage 2: high birth rates begin to fall with improving healthcare.
Stage 3: birth rates fall further; population growth slows.
Stage 4: low birth and low death rates; stable or slowly growing population.
Stage 5: very low birth rates plus aging population; potential population decline.
Environmental Issues and Migration
Environmental drivers of migration (Pages 32–35):
Climate change, drought, land degradation promoting environmental migration.
Migration can be driven by sudden onset events (floods, droughts, fires, storms) and slow onset events (desertification, sea-level rise, saltwater intrusion).
Climate migration discourse (Page 33):
The Economist: "Climate migrants: what to do?" (watch note, context for policy discussions).
Impacts of extreme weather and sea-level rise (Page 34):
Extreme weather events threaten homes, infrastructure, livelihoods; frequent/severe events can force displacement.
Sea level rise/enduring coastal inundation disrupts freshwater supplies and housing.
Desertification, land degradation, and resource scarcity (Page 35):
Desertification reduces arable land, increasing food insecurity and migration.
Water scarcity and disrupted climate patterns threaten agriculture and livelihoods.
Case study: Tuvalu to New Zealand (Pages 36–37):
Tuvalu features: nine low-lying islands; morphology dependent on coral; shallow freshwater lakes; high population density; livelihoods heavily reliant on fisheries.
Climate impacts: sea-level rise, saltwater intrusion, drought forcing displacement.
In the last 10 years: roughly 74 ext{%} of households affected by climate change; 8% of migrants named climate change as the reason for migrating.
Case study context: Mozambique (Page 38):
Task: follow instructions to analyze trends in population and emigration due to repeated cyclones
Note: involves understanding how repeated tropical cyclones influence emigration patterns and the wider social-ecological system.
Connections to SL/Foundational Principles
Population dynamics are a function of interlinked factors: fertility, mortality, migration, education, health care, economy, policy, and culture.
The Doughnut Economics framework connects social foundations (essentials for life) with ecological ceilings (planetary boundaries) to assess sustainability in relation to population and consumption.
Demographic indicators (dependency ratio, age structure, momentum) inform policy needs in economics, healthcare, education, pensions, and social protection.
The Demographic Transition Model explains broad population patterns as societies develop; variations exist by country due to policy choices, economic structure, culture, and technology.
Formulas and Key Numbers (LaTeX)
Dependency ratio:
DR = rac{Y + O}{W} imes 100
Example: DR = rac{11.105 + 9.341}{38.342} imes 100 = 53.33
Example demographic momentum calculation (LIC vs. HIC):
LIC: births = 90 imes 2 = 180; Final population = 90 + 10 + 180 = 280
HIC: births = 50 imes 2 = 100; Final population = 50 + 50 + 100 = 200
Population projections (illustrative):
UN projection: 10 imes 10^9 by 2100
Lancet projection: 9.7 imes 10^9 around 2060
Fertility rates (examples):
Indonesia: ext{TFR} \, ext{~} 2.3
Japan: ext{TFR} \, ext{~} 1.3
Population totals and stages:
Indonesia projected final population: 335 imes 10^6 by ~2050
Japan aging share: notional projection that by mid-century, around 40 ext{%} over 65 years old
Summary of Practical Implications
Population growth interacts with resource use and environmental limits; policies supporting education, healthcare, and gender equality can influence fertility and thus shape future population trajectories.
Dependency ratios inform fiscal planning (tax revenue vs. pension/health demands) and influence retirement age policies and social protection schemes.
Population momentum means even rapid declines in fertility may not immediately halt population growth; planning must account for continued growth and aging.
Climate change and environmental degradation contribute to migration, with cases like Tuvalu illustrating climate-driven displacement and adaptation needs.
Understanding trends in different countries (Indonesia, Japan) helps anticipate economic opportunities and challenges associated with the Demographic Transition Model.
Study Prompts and Connections to Exam Prep
Compare UN vs Lancet projections and discuss factors that could shift trajectories.
Explain how the Doughnut Economics model frames sustainability concerns related to population and consumption.
Compute a dependency ratio from given age-structure data and interpret the result for policy implications.
Describe population momentum using the LIC vs HIC example; explain why momentum can drive growth even if TFR is at replacement level.
Outline how demographic transitions in Indonesia (Stage 3 moving toward Stage 4) differ from Japan (Stage 5) and what regional factors drive these differences.
Discuss how climate-related events (extreme weather, sea-level rise, desertification) influence migration patterns, using Tuvalu as a case study.