Population Ecology and Life History: Study Notes for General Biology

Population Ecology and Life History

Natural Selection and Evolution

Natural selection is a fundamental mechanism of evolution, driving changes in populations over generations. For traits to evolve by natural selection, certain conditions must be met.

• Requirement 1: Variation: There must be heritable variation in traits among individuals in a population.

• Requirement 2: Differential Reproduction: These variations must lead to differences in reproductive success (some individuals leave more offspring than others because of their traits).

• Example: In a population of rats, some may be better camouflaged and thus survive predators more often, passing on their genes to the next generation.

Human Population Size and Growth

Understanding human population dynamics is essential in ecology and conservation biology.

• Current Human Population: As of the early 2020s, the global human population is approximately 8 billion.

• Historical Population: In 1928, the world population was about 2 billion.

• Application: Tracking population growth helps in planning for resources, healthcare, and environmental impact.

Life Span Differences in Mammals

In many mammalian species, females tend to live longer than males. This phenomenon is observed across various taxa and has several biological explanations.

• Key Point: Females often live longer due to lower risk behaviors, hormonal differences (such as protective effects of estrogen), and reduced exposure to predation or competition compared to males.

• Example: In humans and many other mammals, males may engage in more aggressive or risky behaviors, leading to higher mortality rates.

Aging (Senescence)

Aging is the process of becoming older, characterized by a gradual decline in physiological function and increased probability of death.

• Definition: Aging (or senescence) is the accumulation of changes in an organism over time, leading to decreased reproductive capacity and increased vulnerability to disease and death.

• Example: Cellular aging involves the shortening of telomeres and accumulation of cellular damage.

Survivorship Curves

Survivorship curves graphically represent the number of individuals surviving at each age for a given species or group.

• Type I Curve: High parental care, low numbers of offspring, high offspring survival (e.g., humans, elephants).

• Type II Curve: Constant mortality rate throughout life (e.g., some birds, lizards).

• Type III Curve: Very little parental care, high numbers of offspring, low offspring survival (e.g., many fish, insects, plants).

Type	Parental Care	Offspring Number	Offspring Survival	Example
I	High	Low	High	Humans, elephants
II	Moderate	Moderate	Moderate	Birds, lizards
III	Low	High	Low	Oysters, many fish

• Type III is likely to exhibit very little parental care and high numbers of offspring.

• Type I is likely to have high offspring survival and high parental care.

Population Growth Models

Population growth can be described mathematically using models that predict changes in population size over time.

Exponential Growth

Exponential growth occurs when resources are unlimited, and the population increases at a constant rate per time period.

• Equation:

$N_t = N_0 e^{rt}$

• Nt: Population size at time t

• N0: Initial population size

• r: Intrinsic rate of increase (per capita growth rate)

• t: Time

• Exponential growth occurs when resources are abundant and there are no limiting factors (e.g., food, space, disease).

• Example Calculation:

Given: At Generation 0, $N = 2$, $r_{max} = 2$

• Generation 1: $N_1 = N_0 imes r_{max} = 2 imes 2 = 4$

• Generation 2: $N_2 = N_1 imes r_{max} = 4 imes 2 = 8$

• Generation 3: $N_3 = N_2 imes r_{max} = 8 imes 2 = 16$

Generation	N
0	2
1	4
2	8
3	16

Logistic Growth

Logistic growth describes population expansion that decreases as resources become scarce, leveling off when the carrying capacity (K) is reached.

• Equation:

$\frac{dN}{dt} = r_{max} N \left(1 - \frac{N}{K}\right)$

• N: Population size

• rmax: Maximum per capita growth rate

• K: Carrying capacity (maximum population size the environment can support)

• Application: Logistic growth is more realistic for most populations, as resources are usually limited.

• Example Calculation (Given: $N_0 = 2$, $r_{max} = 2$, $K = 10$):

Generation 1: $N_1 = N_0 + r_{max} N_0 \left(1 - \frac{N_0}{K}\right)$ $N_1 = 2 + 2 \times 2 \left(1 - \frac{2}{10}\right) = 2 + 4 \times 0.8 = 2 + 3.2 = 5.2$

Generation 2: $N_2 = N_1 + r_{max} N_1 \left(1 - \frac{N_1}{K}\right)$ $N_2 = 5.2 + 2 \times 5.2 \left(1 - \frac{5.2}{10}\right) = 5.2 + 10.4 \times 0.48 = 5.2 + 4.992 = 10.192$

As $N$ approaches $K$, the growth rate slows and the population size levels off.

• Additional info: In practice, population size is often rounded to whole numbers, and environmental fluctuations can cause deviations from the model.