APES Video Notes 3.5 - Population Growth & Resource Availability

Scientific concepts & discoveries / nature phenomena presented

Population growth & carrying capacity

• Carrying capacity (K): The maximum population size an environment can sustain given limiting resources.
• Limiting factors: Food availability, predation, and other constraints determine carrying capacity.

Essential knowledge: resource availability limits populations

• Resources are always limited in ecosystems (e.g., food and space).
• Limited resources limit population growth.
• If limiting resources increase, population growth capacity increases and the population can rise toward a higher carrying capacity.
• If limiting resources decrease, survival and reproduction worsen, causing populations to drop back below carrying capacity.

Basic population characteristics

• Population size (N): Number of individuals.
  • Larger populations can be safer (e.g., greater genetic diversity and reduced risk of decline).
  • Some species may benefit from predator protection via large group/herd effects.
• Density: Individuals per unit area.
  • Higher density increases competition and can increase disease transmission.
• Distribution patterns:
  • Random distribution: Common for plants with seeds dispersed by wind/animals.
  • Uniform distribution: Seen when organisms inhibit neighbors (e.g., plants releasing defensive chemicals/toxins) or with territorial/nesting behaviors.
  • Clumped distribution: Common in animals living in groups/herds (e.g., meerkats).
• Sex ratio: Male-to-female ratio.
  • Populations closer to a 50/50 ratio are generally more optimal for reproduction.
  • Bottlenecks/natural disasters can skew sex ratios (e.g., too few females), limiting recovery and growth.

Density-dependent vs. density-independent limiting factors

• Density-dependent factors: Effects that increase in strength with population density.
  • Examples: competition for food/water/habitat/nesting sites, and disease spread in dense populations.
  • For example, given different population sizes (e.g., 500 vs. 5,000 deer), the same drought affects larger populations more in absolute impact.
• Density-independent factors: Effects that occur regardless of density.
  • Examples: natural disasters such as floods, hurricanes, tornadoes, and fires.
  • Impact is relatively similar whether the population is small or large.

Key model: exponential vs. logistic growth

• Biotic potential / maximum growth rate: Early growth when resources are not yet limiting.
  • Described as exponential growth (rapid increase).
• Logistic growth: Growth slows as competition increases for limiting resources until reaching carrying capacity.
  • This is presented as the expected pattern in natural ecosystems due to limited resources.

Famous experiment (Paramecium) demonstrating carrying capacity changes

• Researcher: Gregory (G.) Gause
• System: Two Paramecium species grown in petri dishes with limited food.
• Observation / results:
  • With limited food:
    • Rapid growth initially (early exponential phase)
    • Then growth slows and levels off at a carrying capacity
  • With doubled food supply:
    • The exponential phase looks similar initially
    • The population reaches a carrying capacity that is roughly doubled
• Conclusion: Increasing a limiting resource (food) increases carrying capacity.

Population change calculation methodology (birth/death/immigration/emigration)

A mathematical relationship for how population size changes:

• Population increases with births and immigration
• Population decreases with deaths and emigration

Formula concept stated:

• New population size = (births + immigration) − (deaths + emigration), applied to the starting population

Practice problems included:

• An “elf population” starting at 52 with 19 births, 6 deaths, and 5 immigrations
• A “wolf pack” starting at 14 with 5 deaths, 3 births, and 4 new wolves released/immigrating

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Researchers / sources featured

• Gregory Gause (Russian biologist; Paramecium experiment)
• (Also referenced: Mr. Smith as the presenter, but not as a scientific researcher.)