Unit 2: Ecology of Populations

Population Concepts

Population and Meta-population

Population (Definition): A population is a group of individuals of the same species that live in the same geographic area at the same time, and have the capability of interbreeding.

Ecology at the population level studies how population size, density, and composition change over time and in different locations.

Meta-population (Definition): A meta-population is a "population of populations." It is a group of spatially separated populations of the same species that interact at some level (i.e., individuals move between them).

This concept was developed by Richard Levins. Imagine a group of islands, each with its own small population of butterflies. These populations are separate, but occasionally a butterfly from one island flies to another. This entire network of island populations is a meta-population.

• Patches: The individual habitat areas occupied by a population.
• Migration/Dispersal: The movement of individuals between patches. This is key for "rescuing" small populations from extinction (the rescue effect).
• Dynamics: The meta-population is stable if the rate of colonization of empty patches is greater than or equal to the rate of extinction of existing populations.

r- and K-selection

This is a theory about life history strategies, describing two "extremes" of how organisms allocate resources to reproduction and survival. This concept relates directly to the logistic growth model (see Logistic Growth).

Characteristic	r-selected species ("opportunists")	K-selected species ("competitors")
Mnemonic	r for rapid growth rate	K for Karrying Kapacity (capacity)
Environment	Unstable, unpredictable	Stable, predictable
Population Size	Variable, often below K, boom-and-bust cycles	Fairly constant, close to K
Reproduction	Many offspring, small size, early maturity, "big bang" (semelparity)	Few offspring, large size, late maturity, repeated (iteroparity)
Parental Care	Little or none	High
Survivorship	Type III (high early mortality)	Type I (high late mortality)
Examples	Insects, bacteria, algae, weeds, mice	Elephants, whales, humans, redwood trees

Characteristics of Population

Populations have unique characteristics that individuals do not, such as density, age structure, and growth rate.

Population Density

Definition: Population density is the number of individuals of a species per unit area or volume.

• Crude Density: Number of individuals per total unit of area. (e.g., 100 deer per 10 square km).
• Ecological Density: Number of individuals per unit of habitat space (the area actually usable by the species). (e.g., 100 deer per 5 square km of forest, if the other 5 km is a lake they don't use).

Measurement Techniques:

1. Direct Count (Census): Counting every individual. Only feasible for large, easily seen organisms in a small area (e.g., counting elephants from a plane).
2. Sampling (Quadrat Method): Used for plants and slow-moving animals. A frame of a known size (e.g., 1m x 1m) called a quadrat is placed randomly. Individuals inside are counted, and the number is extrapolated to the whole area.
3. Mark-Recapture Method: Used for mobile animals (fish, birds, butterflies).
   • Step 1: Capture a sample (M) individuals, mark them, and release.
   • Step 2: After some time, capture a second sample (n).
   • Step 3: Count how many in the second sample are marked (m).
   • Step 4: Estimate total population (N) using the Lincoln-Petersen Index:
   N = (M * n) / m
   (Total Population = (Marked in sample 1 * Total in sample 2) / Recaptured in sample 2)

Natality and Mortality

• Natality (Birth Rate): The production of new individuals in a population over a period of time.
  • Crude Natality: Number of births per unit time (e.g., 500 births per year).
  • Specific Natality: Number of births per unit time per individual (e.g., 0.5 births per female per year).
• Mortality (Death Rate): The number of individuals dying in a population over a period of time.
  • Crude Mortality: Number of deaths per unit time.
  • Specific Mortality: Number of deaths per unit time per individual.

Survivorship Curves: A graph showing the number of surviving individuals over time, from a cohort (group of individuals born at the same time).

• Type I (Convex): High survival through early and middle life, followed by a rapid decline in old age. (e.g., Humans, elephants - K-selected).
• Type II (Diagonal): Constant mortality rate regardless of age. (e.g., Many birds, lizards, hydra).
• Type III (Concave): Very high mortality for the young, but high survival for those who make it to adulthood. (e.g., Oysters, fish, insects, trees - r-selected).

Age Structure

The distribution of individuals among different age classes in a population. This is often visualized using an Age Pyramid, which plots the percentage of the population in pre-reproductive, reproductive, and post-reproductive age groups.

1. Expanding/Growing Population: A pyramid with a wide base and narrow top. Many young individuals, high birth rate. (e.g., India, Nigeria).
2. Stable/Stationary Population: A "beehive" or bell shape. Pre-reproductive and reproductive groups are roughly equal. (e.g., Sweden, France).
3. Declining/Diminishing Population: An "urn" shape with a narrow base. Fewer young individuals than reproductive individuals. (e.g., Japan, Germany).

Age structure is a crucial predictor of future population growth.

Population Growth

Population size changes based on four factors: Births (B), Deaths (D), Immigration (I), and Emigration (E).
Change in N = (B + I) - (D + E)

For simplified models, we often ignore I and E and focus on births and deaths. The intrinsic rate of natural increase (r) is defined as r = b - d (per-capita birth rate minus per-capita death rate).

• If r > 0, the population is growing.
• If r < 0, the population is shrinking.
• If r = 0, the population is stable (Zero Population Growth).

Geometric Growth

This model applies to populations with discrete breeding seasons (e.g., deer that mate once a year, annual plants). Growth is measured in "steps."

• N(t) = Population size at time t
• N(0) = Initial population size at time 0
• λ (lambda) = Geometric rate of increase (ratio of population size in one year to the previous year).
• t = Number of discrete time intervals (e.g., years)

Exponential Growth (J-shaped curve)

This model applies to populations with continuous breeding (e.g., bacteria, humans) living in an unlimited environment (infinite resources, no predators).

The rate of change in the population (dN/dt) is proportional to the population size (N) and the intrinsic rate of increase (r).

The resulting growth curve is J-shaped. Population growth starts slow but accelerates rapidly as the population base gets larger. This type of growth is unsustainable in the real world.

Logistic Growth (S-shaped curve)

This is a more realistic model that incorporates environmental limits. As the population grows, resources become scarce, and growth slows down. The maximum population size an environment can sustainably support is called the Carrying Capacity (K).

The logistic model modifies the exponential model by adding a "braking" term: (K-N)/K.

• When N is very small (much less than K), the term (K-N)/K is close to 1, and growth is almost exponential (dN/dt ≈ rN).
• When N approaches K, the term (K-N)/K approaches 0, and growth stops (dN/dt ≈ 0).
• If N > K, the term is negative, and the population shrinks.

The resulting growth curve is S-shaped (sigmoid). Growth is fastest when the population is at K/2 (half the carrying capacity). This point is called the maximum sustainable yield.

Limits to Population Growth

These are the environmental factors that stop a population from growing exponentially forever. The syllabus only lists "density-dependent" factors, but it's crucial to know both types.

Density-dependent Factors

Factors whose limiting effect becomes stronger as population density increases. These are usually biotic factors.

• Competition (Intraspecific): Individuals of the same species compete for limited resources (food, water, mates, territory). More individuals = more intense competition.
• Predation: Predators may be attracted to areas of high prey density, increasing the mortality rate of the prey.
• Disease and Parasitism: Diseases spread more easily in dense populations.
• Toxic Waste Accumulation: (e.g., yeast in a wine vat die from their own alcohol waste as their population density increases).

Density-dependent factors are what "push" a population towards its carrying capacity (K) in the logistic model.

Density-independent Factors (Implied)

Though not explicitly listed, understanding these is key. These factors limit a population's size regardless of its density. These are usually abiotic factors.

• Weather: A hurricane, drought, flood, or cold snap can kill individuals without regard for how crowded the population is.
• Natural Disasters: Volcanic eruptions, fires, earthquakes.
• Human Activities: Pollution, habitat destruction (e.g., building a dam).

These factors often cause sudden "crashes" in population, rather than a gradual leveling off.