Chapter 19 Part 2: Population Ecology: Life Histories, Survivorship, Growth & Carrying Capacity

Introduction & Recap of Part 1

• Ecology = study of interactions between populations (or individuals) and their physical/biological environment.
• Population (formal definition)
  • Group of individuals of the same species within a defined area at a specific time.
• Prior concepts briefly referenced
  • Distribution patterns of individuals in a population.
  • Factors controlling where organisms are located in space.

Life-History Models (r- vs K-Selected Strategies)

• General idea: every species follows a characteristic “life–cycle strategy” that balances growth, reproduction, and survival.
• Only two broad archetypes (with many intermediates/exceptions):

r-Selected Species ("live fast, die young")

• Symbolic note: the r is lowercase (links later to the intrinsic growth rate symbol $r$).
• Traits
  • Short lifespan; rapid life-cycle turnover.
  • Early sexual maturity → quick generation times.
  • High fecundity: very large numbers of offspring per reproductive bout.
  • Minimal parental investment; offspring largely abandoned after birth/seeding.
  • High infant/juvenile mortality tolerated.
  • Opportunistic: exploit temporary resource pulses, disturbed sites, empty niches.
• Representative examples & anecdotes
  • Weeds in gardens/cracks of sidewalks: germinate, flower, seed, die in one season.
  • Small mammals (rats, mice): reproductive cycle ≈ $6\text{ weeks}$; litters every few weeks.

K-Selected Species ("slow and steady" or "equilibrium" species)

• Symbolic note: K is uppercase (matches carrying-capacity symbol $K$).
• Traits
  • Long lifespan; slow development.
  • Delayed sexual maturity.
  • Low fecundity: few offspring per bout & few total over lifetime.
  • Extensive parental investment & care to maximize survival of each young.
  • Strategy aims at maintaining population near environmental equilibrium (≈$K$).
• Representative examples & anecdotes
  • Humans: typically single offspring gestations; decades-long parental support.
  • Elephants: gestation ≈ $2\text{ years}$; multi-year juvenile protection.
  • Large wild cats show an intermediate tendency: several cubs, some years of care, moderate maturation time.

Survivorship Curves (Life-Table Visualization)

• Tracks the proportion of a birth cohort surviving to each age.
• X-axis: age (0 → maximum life expectancy, plotted as % of maximum).
• Y-axis: number/proportion of individuals surviving.

Type I Curve

• High survivorship through early & mid-life; steep decline only in old age.
• Characteristics: long-lived, few offspring, strong parental care.
• Aligns with K-selected strategy.
• Example: humans.

Type II Curve

• Constant mortality rate at every age; linear decline.
• "Every day is an equal chance of living or dying."
• Typical illustration: many songbirds.
  • Example scenario: clutch of $6$ eggs → $1$ lost pre-hatch, $5$ hatch → $3$ fledge → $2$ reach first year, etc.

Type III Curve

• Extremely high infant mortality; few survive early bottleneck but those that do tend to live full life spans.
• Characteristic of r-selected species.
• Showcase: sea turtles
  • Female lays ≈ $100$ eggs; studies show $1{-}3$ may reach adulthood.
  • Nest destruction by other nesting females; heavy predation (dogs, vultures, frigate birds) during hatchling run.
  • Conservation anecdote: Trinidad project—people collect hatchlings in buckets, release at night to reduce predation.

Population Growth Patterns

Exponential Growth (J-Shaped Curve)

• Doubling pattern: $2 \to 4 \to 8 \to 16 \to 32 \to 64 \to 128 \dots$
• Mathematically: $N<em>t = N</em>0 e^{rt}$ (not explicitly in transcript but implied by "2 to an exponent").
• Occurs when resources are effectively unlimited (short term); aligns with biotic potential concept.
• Eventually impossible to sustain → resource exhaustion or space limitation (e.g., bacteria filling a Petri dish).

Logistic Growth (S-Shaped Curve)

• Begins like exponential growth but slows as it approaches environmental limits.
• Plateaus near carrying capacity $K$.
• Visual mnemonic: stretched "S" shape.

Carrying Capacity ($K$) — Definition & Dynamics

• Formal: "Number of individuals of a population that can be supported indefinitely in a given area." (Instructor stresses inclusion of the word indefinitely—textbook omission = conceptual error.)
• Determined by at least one limiting factor (could be food, water, space, mates, shelter, etc.).
• Graph behavior near $K$
  • Overshoot → resource shortage → increased death rate.
  • Die-back below $K$ → surplus resources → higher birth rate.
  • Repeated oscillations tend to dampen over time toward stable equilibrium.

Oscillatory Templates

Boom-and-Bust Cycle

• Large overshoot above $K$; abrupt crash (high mortality).
• Re-growth when resources recover; cycle repeats (common in some rodents, insects).

Stabilizing (Damped) Oscillation

• Each overshoot/undershoot magnitude decreases.
• Eventually births ≈ deaths; population hovers narrowly around $K$ (ideal long-term outcome).
• Complication: $K$ is not fixed—seasonal shifts, disturbances, or resource changes continually reset the target.

Limiting Resources & Examples

• Food availability.
• Water supply.
• Space / territory / nesting or den sites.
• Access to mates (for sexually reproducing species).
• Shelter/protection from elements & predators.
• Any single resource can become the defining limit; identity of that resource may change seasonally or after disturbances.

Density-Dependent vs Density-Independent Regulation

Density-Dependent Factors (effect size ∝ population density)

• Limited food supply.
• Increased competition (energetically costly → lowers survival & fecundity).
• Elevated disease/parasite transmission (illustrated by historical Black Plague in Europe—crowded urban vs sparsely populated countryside).
• Consequences
  • ↑ Mortality rates.
  • ↓ Birth rates.
  • Frequently both simultaneously.

Density-Independent Factors (effect size unrelated to population density)

• Natural disasters: volcanic eruptions, earthquakes, hurricanes.
• Weather extremes (heat waves, cold snaps).
• Pollution (instructor notes borderline status; independent for non-human species, although pollution levels often linked to human density).

Interaction Between Categories

• Density-independent events can alter density-dependent pressures.
  • Example: volcanic eruption destroys crops → sudden reduction in food → food becomes a much stronger density-dependent limitation.
• Asymmetry: dependent variables don’t change the occurrence of independent events but independent events change the severity of dependent controls.

Symbol & Term Quick-Reference

• $r$ (lowercase) = intrinsic rate of increase; defines "r-selected" label.
• $K$ (uppercase) = carrying capacity; also inspires "K-selected" label.
• Exponential growth: "J-curve".
• Logistic growth: "S-curve"; mathematical form $\frac{dN}{dt}=rN\Bigl(1-\frac{N}{K}\Bigr)$ (formula not in audio but standard for context).
• Survivorship Curves: Type I, II, III.

Ethical & Practical Implications / Real-World Connections

• Sea-turtle conservation illustrates how understanding Type III curves can guide interventions (e.g., timed releases, predator management).
• Public-health parallels: crowding (density dependence) magnifies epidemics; informs urban planning & disease-control policy.
• Human population analysis (promised for next lecture) will apply concepts of $r$, $K$, logistic vs exponential growth to sustainability debates.

Conceptual Flow Map (How the Pieces Connect)

1. Life-history strategy (r vs K) → influences…
2. Survivorship pattern (Type III vs Type I) → feeds into…
3. Population growth curve (rapid exponential vs near-equilibrium logistic) → constrained by…
4. Carrying capacity $K$ → modulated by…
5. Limiting resources & density factors → interacting with…
6. Environmental stochasticity (independent factors) → shaping long-term stability, conservation tactics, and ecosystem management.

Instructor finishes by hinting the next segment will apply all of the above to human population ecology.