Population Growth and Life History Strategies

Population growth is a fundamental concept that examines how and why populations change over time.

Definition: The schedule of an organism’s growth, development, reproduction, and survival.
Represents an allocation of limited time and resources to achieve maximum reproductive success.

Fecundity: The number of offspring produced by an organism per reproductive episode.
Parity: The number of reproductive episodes an organism experiences.
Parental Investment: The time and energy given to an offspring by its parents.
Longevity (Life Expectancy): The life span of an organism.

Variation in one life history trait often correlates with variations in other life history traits.
- Example: The number of offspring is negatively correlated with the size of offspring.
Species can be categorized along a slow to fast continuum based on life history traits:
- Slow Life History:
- Long time to sexual maturity.
- Long life span.
- High parental investment
- Examples: Humans, sharks, elephants.
- Fast Life History:
- Short time to sexual maturity.
- Short life span.
- Low parental investment.
- Examples: Small mammals, insects (e.g., mice).

Considerations: Think about the three assumptions for natural selection:
- Variation.
- Differential survival/reproduction.
- Heritability.

Population growth is significantly influenced by life histories which include age-specific survivorship and age-specific fecundity.

Compare two populations:
- Older population (>50 years).
- Younger population (<50 years).
- Expectation: The population with a larger proportion of young individuals will have higher birth rates and faster growth.
- The population with older individuals may see lower birth rates and possible decline.

Age Structure: The distribution of individuals among age classes within a population.

Broad base indicates a growing population.
Narrow base and wide middle suggests a declining population due to inadequate young individuals to replace older generations.
Straight sides indicate a stable population.

Historical impacts (e.g., World War II) can be observed through drastic changes in birth rates evident in age structure.

Various models exist to compute population growth: geometric, logistic, and exponential.
Importance of age structure should be noted in more complex models to predict population trends accurately.

Focus on:
1. Type of growth.
2. Information given.
3. What the question is asking for.
Use problem-solving approaches rather than memorization.

Geometric Growth:
- Formula: N(t + 1) = N_t imes ext{λ} or N_t = N_0 imes ext{λ}^t.
- ext{λ} = per-capita growth rate, defining the rate at which the population increases.
Exponential Growth: Differs from geometric as resources are unlimited leading to continuous reproduction.
- Formula: N(t) = N(0)e^{rt} with ext{λ} = e^r and r = ext{intrinsic growth rate}.
Logistic Growth: Characterized by limited resources and has a carrying capacity (K).

Density-Dependent Factors:
- Limits population size based on its density (e.g., disease, food, space).
Density-Independent Factors:
- Limit population size regardless of density (e.g., natural disasters, climate change).

Choose the appropriate model based on:
1. Resource availability.
2. Mode of reproduction.
Discrete Reproduction: Choose geometric model.
Continuous Reproduction with Limited Resources: Choose logistic model.

Initial population during naturalization phase of cheatgrass follows geometric growth. Problem solved via:
- 150 = N_0 imes 1.6^6 leading to initial invasion approximation.

Population growth shown from 21 bison in 1902, illustrating discrete reproduction and utilizing geometric, exponential, or logistic models effectively.
Performance of population projections against historical data gives insight into future conservation strategies and the sustainability of wildlife populations.