CK-12 Biology I - Honors
Page 76
Figure 17.11
Hummingbirds illustrate an reproductive strategy. Very little energy is spent to produce two tiny eggs, but they are enclosed in a secluded nest, usually hidden in a tree. Survival of the offspring is critical because there are only two, so parents invest tremendous amounts of energy finding food for themselves and their young for nearly three weeks. This energy investment allows the offspring to develop to nearly adult size before they fledge into the world of predators and competition.
Precocial and altricial birds play by the rules of costs and benefits, each group using a different strategy. Cowbirds, however, make up their own rules, earning them the title of “parasites” in the bird world. How can a bird be a parasite? Cowbirds are altricial, but they parasitize by laying their eggs in other birds’ nests, thereby escaping the high costs of parental care (Figure below). Cowbird eggs are usually slightly larger and hatch a little sooner than the host eggs affording cowbird parents a bit of extra energy. “Early bird” hatchlings do indeed “get the worm,” easily out-competing their smaller host siblings for parental food deliveries. Sometimes, they are strong enough to ungratefully oust their “sibs” from the nest. On the other hand, host parents occasionally recognize and eject the foreign egg before it hatches. Yellow warblers simply block off the offending egg (along with their own eggs) by building a new nest bottom. They then lay a new clutch of their own eggs (The eggs are not their primary energy investment). A five-“story” nest holds the record for yellow warbler (and cowbird?) determination!
Figure 17.12
A brown-headed cowbird egg in a phoebes nest illustrates yet another strategy for reproductive success: invest all of your energy in a single egg, just large enough to out-compete your altricial hosts eggs, and let the host parents feed your offspring! The right photo shows a male individual of this parasitic species.
Many species fall in between the extremes of precocial and altricial strategies, but all must make trade-offs between the costs of reproduction and those of surviving predation, competition, and disease, in order to ensure that at least one offspring per adult survives long enough to reproduce. It’s worth reprising the survivorship curves introduced in the previous lesson to illustrate these trade-offs (Figure below). Which curve illustrates the precocial strategy used by ducks, chickens, and grouse? Which curve demonstrates the altricial strategy of robins and hummingbirds? What shape do you think a cowbird’s survivorship curve might take?
Figure 17.13
Survivorship curves show the various strategies for achieving population growth by adjustments in birth rate and death rate. Recall that Hummingbirds have low birth rates (), but through time and energy spent on parental care and feeding, ensure high survival rates for their altricial offspring (low ). Geese, however, invest energy in many large eggs (high ) to offset high death rates from predation () among their precocial offspring.
One more strategy, introduced in the last lesson, involves variation of age at maturity. All other factors being equal (number and size of offspring, survival rates, and more), delayed reproduction lowers population growth rate. Bald eagles require five years of growth before they are able to reproduce. If they were to lay the same number of eggs during their first year, those first-year offspring and several generations of their offspring, as well as the parents, would be able to reproduce during that time, tremendously increasing the overall population. By delaying reproduction, bald eagles not only ensure good energy supplies for reproduction at maturity, but also limit population density to suit their large bodied, long-lived life history.
Migration and Other Movements Affect Population Densities
Populations change not only through births and deaths, but also via immigration, movement of individuals into a population from other areas, and emigration, movement of individuals out of a population. If we add per capita rates of immigration and emigration into our equation for population growth rate, it becomes:
r = (b + i) – (d + e)
growth rate = (birth rate + immigration rate) – (death rate + emigration rate)
Many kinds of movement adaptations regularly add to or subtract from population density.
Most species have some means of dispersal – movement of offspring away from the parents. This “behavior” reduces competition within the population, promotes colonization of suitable habitat, and improves reproductive success. Some dispersal mechanisms take advantage of natural energy in the environment. For example, dandelion seeds grow “parachutes” which allow wind to carry them far from their parents – and sometimes entirely out of a population (Figure below). For the same reason, immobile animals such as corals often produce motile larva. Mobile animals often evolve behaviors which ensure dispersal. A lone gray wolf which leaves its birth pack must find a mate and an unoccupied territory in order to reproduce; within the pack, usually only the alpha male and female have offspring. Dispersal behaviors are common in the living world; have you - as a teenage high school student, begun to feel stirrings of the wish to leave home?
Figure 17.14
Wind carries dandelion seeds away from their parent plants. The parachute adaptation allows for dispersal, reducing competition within the population and promoting colonization of suitable habitat.
Migration, the direct, often seasonal movement of a species, is a predictable change for some animal populations. Many northern hemisphere birds, such as Swainson's Hawks (Figure below), migrate thousands of miles southward in the fall and return north to nest in the spring in order to follow summer’s long days which provide extra hunting time and a greater abundance of food.
Figure 17.15
Entire populations of Swainsons Hawks migrate annually from North America to South America and back. Migration can affect all four factors of the growth rate equation: rates of birth, death, immigration, and emigration.
Apparently, energy benefits outweigh costs for this annual long-distance commute. Elk migrate vertically – up the mountains in spring as snow recedes and down the mountains in fall as winter advances. Monarch butterflies migrate in “shifts”; somewhat like a relay team, successive generations divide the task of moving from Mexican wintering grounds to northern summer habitats. Such migrations do not add to or subtract from populations as much as they move entire populations from one set of boundaries and environmental conditions to another. Some species, such as Peregrine Falcons, have both migratory and non-migratory forms, so their populations may grow or decline with migration. Gray Whales migrate 12,500 miles from Alaska to Mexico for calving, but at least one population limits its northward journey to the Oregon coast (Figure below). Seasonal densities of migratory species vary considerably, but resources and environmental benefits vary as well. Migration can affect all four factors of the growth rate equation.
Figure 17.16
Gray Whales migrate up to 12,500 miles further than any other mammal. At least one population stops its northward journey in Oregon; this behavior probably results in immigration and/or emigration, changing intraspecific interactions as populations merge and separate.
Other types of movement are less predictable, but still may affect population growth.
Nomadism, regular, wide-ranging wandering behavior, allows some species to compensate for fluctuating food sources. Normally arctic species, Snowy Owls occasionally venture as far south as Texas, southern Russia, and northern China (Figure below). Bohemian waxwings are notoriously nomadic, feeding on highly variable berry supplies.
Figure 17.17
Normally arctic species, Snowy Owls occasionally wander as far south as Texas, southern Russia, and northern China. This nomadic behavior allows them to feed on prey which have unpredictable fluctuations in population density.
Irruptions or invasions are irregular movements, often caused by food source failures. Owls such as Great Grays and Boreals occasionally invade northern US states from their Canadian homes when rodent populations decline. Some may remain to nest following such an irruption.
> Range expansion involves the gradual extension of a population beyond its original boundaries. Recent examples in the US include Cardinals, now common in northern areas where they were originally absent. The Swainson’s Thrush follows an indirect and unnecessarily long migration path - retracing, scientists believe, a range expansion from 10,000 years ago. Intentional introductions of non-native species such as the House Sparrow and reintroductions of extirpated species such as Peregrine Falcons throughout the Eastern US are human-initiated colonizations, which are often followed by range expansions.
Closely related to range expansion is colonization, but the latter often involves newly created, or at least newly found, habitats. Illustrating both range expansion and colonization, the small red-eyed dragonfly spread throughout Europe in the late 20th century and colonized Britain in 1999 (Figure below).
Figure 17.18
Small red-eyed dragonflies expanded their range throughout northwest Europe in the late 20 century and colonized Britain in 1999.
How Do Populations Grow in Nature?
You learned above that populations can grow exponentially if conditions are ideal. While exponential growth occurs when populations move into new or unfilled environments or rebound after catastrophes, most organisms do not live in ideal conditions very long, if at all. Let’s look at some data for populations growing under more realistic conditions.
Biologist Georgyi Gause studied the population growth of two species of Paramecium in laboratory cultures. Both species grew exponentially at first, as Malthus predicted. However, as each population increased, rates of growth slowed and eventually leveled off. Each species reached a different maximum, due to differences in size of individuals and space and nutrient needs, but both showed the same, S-shaped growth pattern. Figures Paramecium Graph, Sheep in Tasmania Graph, and Population Growth Graph according to Malthus' and Verhulst's models show this growth pattern graphically as an S-shaped curve.
Figure 17.19
Two species of Paramecium illustrate logistic growth, with different plateaus due to differences in size and space and nutrient requirements. The growth pattern resembles and is often called an S-curve. Slow but exponential growth at low densities is followed by faster growth and then leveling.
Perhaps even more realistic is the growth of a sheep population, observed after the introduction of fourteen sheep to the island of Tasmania in 1800. Like the lab Paramecia, the sheep population at first grew exponentially. However, over the next 20 years, the population sharply declined by 1/3. Finally, the number of sheep increased slowly to a plateau. The general shape of the growth curve matched the S-shape of Paramecium growth, except that the sheep “overshot” their plateau at first.
Figure 17.20
Sheep introduced to Tasmania show logistic growth, except that they overshoot their carrying capacity before stabilizing.
As Malthus realized, no population can maintain exponential growth indefinitely. Inevitably, limiting factors such as reduced food supply or space lower birth rates, increase death rates, or lead to emigration, and lower the population growth rate. After reading Malthus’ work in 1938, Pierre Verhulst derived a mathematical model of population growth which closely matches the S-curves observed under realistic conditions. In this logistic (S-curve) model, growth rate is proportional to the size of the population but also to the amount of available resources. At higher population densities, limited resources lead to competition and lower growth rates. Eventually, the growth rate declines to zero and the population becomes stable.
Figure 17.21
Growth of populations according to Malthus exponential model (A) and Verhulsts logistic model (B). Both models assume that population growth is proportional to population size, but the logistic model also assumes that growth depends on available resources. A models growth under ideal conditions and shows that all populations have a capacity to grow infinitely large. B limits exponential growth to low densities; at higher densities, competition for resources or other limiting factors inevitably cause growth rate to slow to zero. At that point, the population reaches a stable plateau, the carrying capacity (K).
The logistic model describes population growth for many populations in nature. Some, like the sheep in Tasmania, “overshoot” the plateau before stabilizing, and some fluctuate wildly above and below a plateau average. A few may crash and disappear. However, the plateau itself has become a foundational concept in population biology known as carrying capacity (K). Carrying capacity is the maximum population size that a particular environment can support without habitat degradation. Limiting factors determine carrying capacity, and often these interact. In the next section, we will explore in more detail the kinds of factors which restrict populations to specific carrying capacities and some adaptations that limit growth.
Limits to Population Growth
A limiting factor is a property of a population’s environment – living or nonliving – which controls the process of population growth. Biologists have identified two major types of limiting factors: Density-dependent factors and Density-independent factors.
Density-dependent factors promote intraspecific competition – competition between members of the same population for the same resource – as the population grows and becomes more crowded. Density-dependent limiting factors have the potential to control population size. Consider food supply as an example. When population density is low, amount of food per individual is high, and birth rates are high. As density increases, food supply per individual decline and birth rates drop, causing growth rate to decline. Eventually, food shortages may lead to increased death rates and a negative growth rate, lowering population size. Lower population size means more food per individual, and the population begins to grow again, reaching or temporarily overshooting the carrying capacity. Food supply in this instance is a regulatory limiting factor, because it keeps the population at equilibrium. Density-dependent limiting factors may include:
Light
Water, nutrients/minerals, or oxygen
Waste, or the ability of an ecosystem to recycle nutrients and/or waste
Predation by predators which feed preferentially on more abundant prey
Disease and/or parasites
Space, with or without territorial behaviors, or nesting sites
Temperature
Aggressive behaviors, often combined with stress and effects on immune systems
Let’s look at two examples in detail, to emphasize the importance of density-dependent regulation of growth. First, waste products build up with increasing population density. Most environments have some capacity for recycling of wastes, but sometimes rapid population growth means that natural environmental systems can’t keep up. An interesting - if not completely natural - example is the growth of yeast populations through fermentation in the making of wine. Alcohol is a waste product for the yeast, even though it is the point of the process as far as we’re concerned. As the yeast population grows, alcohol builds up; but alcohol is toxic – to yeast as well as to humans – and after the concentration reaches 13%, increased death rates doom the yeast population. Therefore, no naturally fermented wine contains more than 13% alcohol.
A second density-dependent limiting factor is predation. Predators kill and eat their prey, of course, so predation increases prey death rate and can cause negative growth rates – population decline. If predators have multiple types of prey, and switch their feeding to specific prey only when they are abundant, predators may regulate prey population size. However, especially in northern climates, predators often specialize on a single prey species. Goshawks, for example, feed primarily on ruffed grouse, and Canada Lynx depend on snowshoe hares (Figure below). If predation causes a significant decline in the prey population, starving predators may experience their own (delayed) decrease in population as a result of lower birth rates or increased death rates. The result is a predator-prey cycle; both populations rise and fall, with predator populations trailing prey (Figure below).
Populations of snowshoe hare (left) and their Canada Lynx predator (right) show repeating cycles, with predator population changes trailing those of their prey.
Figure 17.23
Repeating cycles of growth and decline characterize population dynamic interactions between some pairs of predator and prey species.
Goshawks play the game with a little twist; when ruffed grouse populations in their Canadian conifer forest homes decline, they migrate southward. Grouse populations show ten-year cycles; note that the goshawk counts from Hawk Ridge in Duluth, Minnesota show ten-year “invasions” which correspond to prey population lows in Canada (Figure below).
Figure 17.24
The pattern of migration of goshawks observed at Hawk Ridge in Duluth, Minnesota, shows irruptions which correspond to low points in cycles of their Canadian prey populations (ruffed grouse). Such cycles are the result of density-dependent interactions between predator and prey. Predators cause increased death rates in prey populations, especially at high prey densities. When prey populations crash as a result of predation, predators are stressed and some (such as lynx) decline. Others, such as the goshawk, irrupt southward in search of higher-density populations.
All of these factors have the potential to lower birth rates or increase death/emigration rates via increased intraspecific competition at higher population densities. Many natural populations are kept at or below carrying capacity by one or a complex interaction among several of the above limiting factors.