Unit 3 Beta

Populations: the one-page sheet

3.1 Generalist and Specialist Species

Specialist species have narrow niches: a few foods, one habitat or a narrow range of conditions. They thrive where their resource is stable but decline when the environment changes. Generalist species have broad niches and can switch foods and habitats, so they cope better with change and often spread into new and disturbed places.

Specialist species have a narrow niche: they eat a few foods, live in one kind of habitat, or tolerate a narrow range of conditions. Examples: the giant panda (bamboo) and the koala (eucalyptus leaves).
Generalist species have a broad niche: they eat many foods, live in many habitats and tolerate a wide range of conditions. Examples: raccoons, coyotes, rats and cockroaches.
Specialists do well in stable environments where their resource is reliable. They are more likely to decline or die out when the environment changes.
Generalists cope better with change, and they often spread into new places, including towns and farms.

it can be very efficient where those resources are plentiful the specialist has nothing to switch to, so its population falls when one resource declines it switches to others, so it copes better with change

generalist species: A species with a broad niche: it eats many kinds of food, lives in many habitats and tolerates a wide range of conditions, such as raccoons and coyotes. Generalists cope well with environmental change.
specialist species: A species with a narrow niche: it depends on a few foods, one kind of habitat or a narrow range of conditions, such as the giant panda and bamboo. Specialists are more likely to decline when their environment changes.

3.2 K-Selected r-Selected Species

r-selected species have many small offspring, little parental care, early reproduction and short lives; they have a high biotic potential, their populations swing up and down, and they rebound quickly after a disruption. K-selected species have few large offspring, much parental care, late reproduction and long lives; their populations are steadier but recover slowly from losses. Most species fall between the two ends.

Biotic potential is the fastest rate at which a population could grow if it had unlimited resources. r-selected species have a high biotic potential; K-selected species have a low one.
r-selected species: many small offspring, little or no parental care, early first reproduction, short lives. Insects, mice, many fish and weeds.
K-selected species: few large offspring, much parental care, late first reproduction, long lives. Elephants, whales, great apes, many large trees.
K-selected populations tend to stay near the largest size their environment can support; r-selected populations swing up and down. After a disruption, r-selected species rebound quickly; K-selected species recover slowly and are more at risk of dying out.

most offspring die young, but the population can grow very quickly when conditions are good an r-selected species rebounds fast, because each survivor can soon produce many offspring more of each offspring survive, but the population grows slowly and recovers slowly after losses

biotic potential: The fastest rate at which a population could grow if it had unlimited resources and no limits. It depends on how many offspring each individual produces, how early it starts and how often it reproduces.
r-selected: Describes species with a high biotic potential: many small offspring, little or no parental care, early first reproduction and short lives, such as insects, mice and weeds. Their populations swing up and down and rebound quickly after disruptions.
K-selected: Describes species with a low biotic potential: few large offspring, much parental care, late first reproduction and long lives, such as elephants and whales. Their populations are fairly steady but recover slowly after losses.
reproductive strategy: The way a species balances the number of offspring it produces against the care and resources given to each one. r-selected and K-selected are the two ends of the range of reproductive strategies.

3.3 Survivorship Curves

A survivorship curve plots the number of survivors from a group born at the same time against age. Type I curves stay high and drop in old age, Type II curves fall steadily (a straight line on a log scale), and Type III curves drop steeply early in life. Survivorship describes when deaths happen; it is related to, but not the same as, r- and K-selection, which describe how a species reproduces.

A survivorship curve shows how many individuals of a group born at the same time are still alive at each age. Survivors are usually plotted on a log scale, starting from 1,000.
Type I: high survival through most of life, with deaths concentrated in old age. Humans in wealthy countries, elephants, many large mammals.
Type II: a steady chance of dying at every age, so the curve is a straight line on a log scale. Many songbirds, lizards, some rodents.
Type III: very many deaths among the young, then high survival for the few that make it. Oysters, most fish, many insects and plants.

they get a survivorship curve: survivors (often on a log scale) plotted against age the curve stays high and then drops steeply at old age: Type I the curve falls as a straight line on a log scale: Type II the curve drops steeply at first, then levels off for the few survivors: Type III

survivorship curve: A graph of the number of individuals still alive at each age, out of a group born at the same time (often 1,000), usually with survivors on a log scale. Type I: most die old. Type II: a steady chance of dying at every age. Type III: most die young.

3.4 Carrying Capacity

Carrying capacity is the largest population an environment can support over time. A population that grows past it is in overshoot and uses resources faster than they are replaced; resource shortages then cause dieback, a sharp population crash. Because overshoot can damage the resources, carrying capacity may be lower afterward than before.

Carrying capacity (K) is the largest population of a species that an environment can support over time, given its food, water, space and other resources.
When a population grows past its carrying capacity, it is in overshoot: it uses resources faster than they are replaced.
Overshoot leads to dieback: a sharp drop in population as individuals starve, sicken or fail to reproduce.
Overshoot can damage the resources themselves (plants eaten down to bare ground, soil washed away), so carrying capacity can be lower after a dieback than before.

births outnumber deaths and the population grows individuals use resources faster than they are replaced, for example eating plants faster than they regrow starvation, disease and fewer births make the population crash (dieback) the carrying capacity can stay lower than before for many years

carrying capacity: The largest population of a species that an environment can support over time with its food, water, space and other resources. Written K. It can change when the environment changes.
overshoot: The state of a population that has grown larger than the carrying capacity of its environment, so it uses resources faster than they are replaced.
dieback: A sharp drop in a population after overshoot, as individuals starve, sicken or fail to reproduce because resources have run short. Also called a population crash.

3.5 Population Growth and Resource Availability

With unlimited resources, a population grows exponentially (a J-curve), by a constant percent each period. In real environments, limiting factors slow growth as the population nears carrying capacity, giving logistic growth (an S-curve). Density-dependent factors such as food shortage, disease and competition strengthen as a population grows; density-independent factors such as floods and frosts act whatever its size.

Exponential growth: with unlimited resources, a population grows by a constant percent each period, so it adds more individuals each time. The graph is a J-curve.
Logistic growth: growth is fast at first, slows as resources run short, and levels off at the carrying capacity. The graph is an S-curve; growth is fastest at about half of K.
A limiting factor is any resource or condition that keeps a population from growing: food, water, space, light, nutrients, predators, disease.
Density-dependent factors grow stronger as a population gets denser (food shortage, disease, competition, predation). Density-independent factors hit a population whatever its size (a flood, a frost, a fire).

it grows by a constant percent each year, so it adds more individuals each year: exponential growth, a J-curve limiting factors such as food, space and disease become stronger growth slows and the population levels off at K: logistic growth, an S-curve

exponential growth: Growth by a constant percent each period, so the number added gets larger each time. It happens when resources are unlimited and gives a J-shaped curve (J-curve).
logistic growth: Growth that is fast at first, slows as resources run short, and levels off at the carrying capacity. It gives an S-shaped curve (S-curve), with the fastest growth at about half the carrying capacity.
limiting factor: A resource or condition that limits the growth of a population, such as food, water, space, nutrients, light, predators or disease.
density-dependent factor: A limiting factor whose effect grows stronger as a population becomes denser, such as food shortage, competition, disease or predation.
density-independent factor: A limiting factor that affects a population whatever its size or density, such as a flood, a frost, a fire or a drought.
population density: The number of individuals of a population per unit of area or volume, such as 25 deer per square kilometer. Population density = number of individuals / area.

3.6 Age Structure Diagrams

An age structure diagram shows a population’s size by age group and sex, each bar a cohort. A wide base (pyramid) predicts rapid growth, a column predicts slow or no growth, and a narrow base predicts decline. Because young cohorts become parents, a population with a wide base keeps growing for decades even after families shrink: population momentum. Developing countries tend to have wide bases; developed countries columns or narrow bases.

An age structure diagram (population pyramid) shows how many people are in each age group, males on one side and females on the other, youngest at the bottom.
Each bar is a cohort: a group of people born in the same span of years. The cohorts at the base are the children who will be the parents of the next generation.
Shape predicts growth: a wide base (pyramid) means rapid growth; bars of about equal width (column) mean slow or no growth; a narrow base (more middle-aged than young) means decline.
Population momentum: a population with a wide base keeps growing for decades even after families get smaller, because so many young people are reaching parenting age. Wide bases are typical of developing countries; columns and narrow bases of developed countries.

many people are about to reach the ages when people have children births stay high even if each family has fewer children than their parents did this delay is population momentum; a narrow base gives the opposite, a shrinking population

age structure diagram: A graph of how many people (or what percent of a population) are in each age group, usually with males on the left and females on the right and the youngest at the bottom. Also called a population pyramid. Its shape predicts whether a population will grow, stay stable or shrink.
cohort: A group of people born during the same span of years, shown as one bar of an age structure diagram, such as everyone aged 0 to 9.
population momentum: The tendency of a population with many young people to keep growing for decades even after families have fewer children, because the large young cohorts are still reaching the ages when people have children.
developed country: A developed country has a high average income, widespread schooling and health care, and usually slow population growth; a developing country has a lower average income and usually a younger, faster-growing population.

3.7 Total Fertility Rate

The total fertility rate is the average number of children a woman would have in her lifetime. Replacement level is about 2.1, a little above 2 because some children die young. Education and paid work for women, family planning, lower infant mortality and urban living lower TFR; where children work on farms and support parents in old age, TFR tends to stay high. A TFR below replacement means, in the long run, a shrinking population.

The total fertility rate (TFR) is the average number of children a woman would have in her lifetime at a population’s current birth patterns.
Replacement-level fertility is the TFR at which each generation just replaces itself: about 2.1 in countries where few children die young. It is a little above 2 because some children die before adulthood and slightly more boys than girls are born.
Infant mortality is the number of babies who die before their first birthday, per 1,000 live births. Where it is high, families tend to have more children; as it falls, TFR tends to fall too.
Factors that lower TFR: more education and paid work for women, access to family planning, lower infant mortality, people moving to cities, pensions for old age. Factors that raise it: early marriage, children working on family farms, religious and cultural values that favor large families.

they tend to marry and have children later, and choose to have fewer parents no longer need many births to be sure some children survive, and they can choose how many to have population growth slows, and in time the population can stop growing or start to shrink

total fertility rate: The average number of children a woman would have in her lifetime if birth patterns at each age stayed as they are now. Written TFR.
replacement-level fertility: The total fertility rate at which a population exactly replaces itself from one generation to the next, about 2.1 children per woman where few children die young. It is above 2 because some children die before adulthood and slightly more boys than girls are born.
infant mortality: The number of babies who die before their first birthday, for every 1,000 babies born alive in a year. It is a key measure of a population’s health and is linked to fertility: where infant mortality is high, families tend to have more children.

3.8 Human Population Dynamics

Crude birth and death rates count births and deaths per 1,000 people per year. Their difference divided by 10 is the rate of natural increase in percent, and 70 divided by that rate is the doubling time in years; add it to the start year to find the year a population doubles. Immigration and emigration also change population size. Malthus argued that population would outrun food; so far, food production has kept pace, but his question about limits remains.

Crude birth rate (CBR): births per 1,000 people per year. Crude death rate (CDR): deaths per 1,000 people per year.
Rate of natural increase (in %) $= \frac{\text{CBR} - \text{CDR}}{10}$ . The 10 turns a rate per 1,000 into a percent (per 100).
Doubling time (years) $= \frac{70}{\text{growth rate in }\%}$ . For "in what year", add the doubling time to the start year.
Total growth also counts immigration (people moving in) and emigration (people moving out). Malthusian theory holds that population grows faster than food, so famine, disease or war will check it.

their difference is the natural increase per 1,000 people per year the result is the rate of natural increase in percent gives the doubling time in years; adding it to the start year gives the year the population doubles a country’s total growth can differ from its natural increase

crude birth rate: The number of live births in a year for every 1,000 people in a population. Written CBR.
crude death rate: The number of deaths in a year for every 1,000 people in a population. Written CDR.
rate of natural increase: The growth of a population from births minus deaths, ignoring migration, as a percent per year: (crude birth rate minus crude death rate) divided by 10. It is negative when deaths outnumber births.
immigration: The movement of people into a country (immigration) or out of it (emigration). Net migration is immigrants minus emigrants; it adds to or subtracts from the growth that births and deaths give.
Malthusian theory: The idea, from the economist Thomas Malthus in 1798, that population tends to grow faster than the food supply, so it will be held back by famine, disease or war unless births fall.

3.9 Demographic Transition

The demographic transition model follows a country’s crude birth and death rates as it develops. In the preindustrial stage both are high and growth is slow; in the transitional stage the death rate falls first, so growth is fastest; in the industrial stage the birth rate falls and growth slows; in the postindustrial stage both are low and the population levels off or declines. Each stage has a typical age structure diagram.

The demographic transition model describes how a country’s crude birth and death rates change as it develops economically, in four stages.
Preindustrial stage (1): high birth and death rates, slow growth. Transitional stage (2): death rate falls, birth rate stays high, fastest growth.
Industrial stage (3): birth rate falls toward the death rate, growth slows. Postindustrial stage (4): both low, little or no growth, sometimes decline.
Each stage has a typical age structure: a wide base in stages 1 and 2, a narrowing base in stage 3, and a column or a narrow base in stage 4.

birth and death rates are both high, so the population grows slowly the death rate falls fast while the birth rate stays high, so the population grows rapidly the birth rate falls, the gap narrows and growth slows the population grows slowly, holds steady, or may start to shrink if births fall below deaths

demographic transition: A model of how a country’s crude birth and death rates change as it develops economically: both start high, the death rate falls first, then the birth rate falls, and both end low. It has four stages.
preindustrial stage: The four stages of the demographic transition. Preindustrial (1): high birth and death rates, slow growth. Transitional (2): falling death rate, high birth rate, fast growth. Industrial (3): falling birth rate, slowing growth. Postindustrial (4): low birth and death rates, little or no growth.