শিক্ষামূলক নোট: এই পৃষ্ঠা একাডেমিক জীববিজ্ঞান শেখা ও পরীক্ষার প্রস্তুতির সহায়ক।
Survivorship Curve, Life Table and Growth Models
Concept Overview
Population ecology studies how a population changes through birth, death, survival and migration. Survivorship curve shows the pattern of survival across age. Life table records age-specific survival and mortality. Growth models explain whether a population grows rapidly, slowly, or stabilizes near environmental limits.
In simple words, this lesson answers three questions:
- How many individuals survive at each age?
- At which age does mortality become high?
- How does population size change over time?
Why This Matters
A population is not just a number. It has age structure, birth rate, death rate, resource demand and environmental pressure. Fisheries, wildlife conservation, pest control, disease ecology, human population planning and endangered species management all require survivorship and growth-model thinking.
LBFL Educational Framework
Use the central framework pages below for the full method. This page keeps only the topic-specific learning path so learners do not meet the same boilerplate repeatedly.
Population-Ecology Learning Focus
এই lecture central LBFL framework-কে population ecology-তে প্রয়োগ করে। Learner-এর focus হবে survivorship pattern, age-specific mortality, life-table interpretation, exponential growth, logistic growth, carrying capacity and real-life population management.
Key Terms
Population
Same species living in the same area at a given time.
Survivorship
Proportion of individuals surviving to a given age.
Mortality
Death rate or age-specific death pattern in a population.
Life table
A table showing survival and mortality data by age class.
Exponential growth
Rapid J-shaped growth under unlimited resource conditions.
Logistic growth
S-shaped growth that slows near carrying capacity.
Survivorship Curves
Survivorship curves are usually grouped into three major types.
Type I
High survival in early and middle life; mortality rises in old age.
Example: humans and many large mammals.
Type II
Constant mortality rate throughout life.
Example: many birds and small mammals.
Type III
Very high early mortality; survivors may live relatively longer.
Example: many fishes, oysters and plants.
Survivorship Curve Logic
Birth cohort starts
↓
Individuals face age-specific mortality
↓
Survivors at each age are counted
↓
Survival pattern is plotted
↓
Curve type reveals life-history strategy
Life Table: What It Shows
A life table organizes survival and mortality data by age class.
| Column | Meaning | Learning use |
|---|---|---|
| Age class | time interval or age group | identifies life stage |
| Number alive | survivors at that age | tracks cohort decline |
| Deaths | number dying in interval | identifies mortality pressure |
| Survivorship | proportion surviving | builds survivorship curve |
| Mortality rate | death risk in interval | compares vulnerable stages |
Example Interpretation
High death in early age
↓
Type III tendency
↓
Many offspring strategy may be selected
Low death until old age
↓
Type I tendency
↓
Parental care and low offspring number may be common
Population Growth Equation
Population change is controlled by births, deaths, immigration and emigration.
Population change = Births + Immigration − Deaths − Emigration
For a closed population where migration is ignored:
Population change ≈ Births − Deaths
Exponential Growth
Exponential growth occurs when resources are abundant and limiting factors are low.
Small population
↓
High birth rate and low competition
↓
Rapid increase
↓
J-shaped curve
Mathematically, the idea is often expressed as:
dN/dt = rN
Where:
- N = population size
- r = intrinsic rate of increase
- dN/dt = rate of population change over time
Logistic Growth
Logistic growth includes environmental resistance and carrying capacity.
Population grows rapidly
↓
Resource limitation increases
↓
Competition rises
↓
Growth slows
↓
Population approaches carrying capacity K
↓
S-shaped curve
A common model is:
dN/dt = rN (K − N) / K
Where:
- K = carrying capacity
- N = population size
- r = intrinsic rate of increase
Exponential vs Logistic Growth
| Feature | Exponential growth | Logistic growth |
|---|---|---|
| Curve shape | J-shaped | S-shaped |
| Resource assumption | unlimited | limited |
| Carrying capacity | not included | included |
| Competition | low or ignored | increases with population size |
| Realism | short-term ideal condition | more realistic for natural systems |
Carrying Capacity
Carrying capacity (K) is the maximum population size that an environment can support for a long period with available resources.
Factors affecting K:
- food availability;
- water supply;
- space;
- nesting/breeding sites;
- disease pressure;
- predators;
- climate;
- human disturbance.
Application Examples
Conservation
Life-table data helps identify vulnerable age groups in endangered species.
Fisheries
Growth models help estimate sustainable harvesting limits.
Pest control
High reproductive rate and Type III pattern help explain sudden outbreaks.
Public health ecology
Vector population growth can affect disease transmission risk.
Common Mistakes to Avoid
Mistake 1
Thinking every population grows exponentially forever. Real environments have limits.
Mistake 2
Confusing survivorship curve with population growth curve. They answer different questions.
Mistake 3
Calling carrying capacity fixed forever. K can change when environment changes.
Mistake 4
Memorizing formulas without interpreting biological meaning.
Synaptic Bridge
Population ecology teaches that growth without limits is not sustainable. A population, a city, a classroom or even personal ambition must face resource limits. Ecology therefore teaches disciplined growth: expand when conditions allow, stabilize when limits appear, and adjust behaviour before collapse.
Critical Thinking Questions
- Why do Type III species often produce many offspring?
- How does a life table help identify vulnerable age classes?
- Why is exponential growth usually temporary in nature?
- Explain carrying capacity using a pond, forest or classroom example.
- Why is logistic growth more realistic for long-term population prediction?
Related Learning Paths
References
- Standard HSC Zoology Ecology notes.
- Integrated Zoology references on population ecology, life table and survivorship curves.
- General ecology references on exponential growth, logistic growth and carrying capacity.