Lecture_21_-_Population_Ecology_2024

Population Ecology

• Definition: Ecological study focused on a population.

  • Population: All individuals of one species inhabiting the same geographic area.

    • Example: Percentage of a sockeye salmon population that can be harvested by humans annually without causing long-term declines in numbers.

Long-term Human Population Change

• Research Questions:

  1. What is the long-term pattern in global human population change and associated ecological changes?

  2. How can we predict population change over time while considering environmental limits?

Human Population Growth Over Time

• Growth Timeline:

  • 1804: 1 billion

  • 1927: 2 billion

  • 1960: 3 billion

  • 1974: 4 billion

  • 1987: 5 billion

  • 1999: 6 billion

  • 2011: 7 billion

  • (Data displayed graphically over time)

Ecological Changes Associated with Human Growth

1. Declining Resource Availability:

   • Overconsumption and unsustainable use.

   • Ecosystem destruction.

2. Degradation of the Biosphere:

   • Resulting from pollution.

3. Climate Change:

   • Increased greenhouse gases raise temperatures and intensify droughts/storms.

4. Reduced Ecosystem Services:

   • Decline in biological production, species diversity, and ecosystem services like air and water purification.

Predicting Population Change

• Logistic Growth Model:

  • Presumes small initial populations with abundant resources.

  • Formula: ( Nt+1 = rmax Nt[(K - Nt)/K] + Nt )

    • Where:

      • ( Nt ): population size at the start of the interval.

      • ( rmax ): intrinsic growth rate based on reproductive potential.

      • ( K ): carrying capacity of the environment (maximum population the ecosystem can support).

      • ( Nt+1 ): population size at next time interval.

Population Growth Example (Logistic Model)

• Table displaying generation, population size (Nt), growth rate (rmax), carrying capacity (K), and subsequent population size (Nt+1).

  • Initial generation size: 10

  • Carrying capacity: 100

  • Population sizes increase incrementally leading to:

    • Generation 10 calculation using logistic model.

Density Dependence and Growth

• Growth Dynamics:

  • Density-dependent factors:

    • Growth rate slows at high population density.

    • Relates to carrying capacity limitations.

• Logistic Growth Graphs:

  • Illustrates population growth slowing as density increases.

Factors Regulating Population Change

1. Density-independent Factors:

   • Effects are unrelated to population density.

   • Examples include abiotic stressors (e.g., extreme temperatures) and physical disturbances (e.g., fires).

2. Density-dependent Factors:

   • Effect magnitude increases with population density.

   • Includes competition for resources, predation, and parasitism.

3. Life History Strategies:

   • r-selected Strategy:

     • High reproduction rate, low survival probability.

   • K-selected Strategy:

     • Low reproduction rate, high survival probability.

Life History Strategies and Population Dynamics

• r-selected:

  • Characterized by rapid population growth and fluctuations due to density-independent factors.

• K-selected:

  • Exhibits slow growth rates and stability near carrying capacity influenced by density-dependent factors.

Carrying Capacity Considerations

• Can populations exceed carrying capacity (K)?

  • If K is exceeded, potential long-term consequences for the population include resource depletion and increased mortality.

  • Example of St. Paul Island reindeer population illustrates food supply decline due to overconsumption.

Applications of Population Ecology

1. Sustainable Harvest Practices:

   • Optimal population management in fisheries and wildlife.

   • K = maximum population support by the environment; maximum sustainable yield (MSY) is K/2.

2. Metapopulation Theory:

   • Preserves populations in fragmented habitats and prevents extinction.

   • Enhances migration among smaller populations.

3. Maintaining Genetic Diversity:

   • By connecting isolated populations, managed landscapes enable gene flow and increase resilience against extinction.

   • Wildlife corridors facilitate movement and connectivity to sustain biodiversity.