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LAYERS OF POPULATION SPECIES COMMUNITY COMPLEXITY DYNAMICS AND INTERACTIONS COMPOSITION AND GROWTH MODELS RICHNESS POPULATION AND COMMUNITY ECOLOGY

A former New England farm is now a forest.

The old stone walls Population and Community Ecology are the only evidence ! that this forest was once farmland. When the Pilgrims arrived in Massachusetts in 1620, they found immense areas of undisturbed temperate seasonal forest containing a variety of tree species, including sugar maple (Acer saccharum), American beech (Fagus

1 THS A.P.E.S. CHAPTER 5 grandifolia), white pine (Pinus strobus), and eastern hemlock (Tsuga canadensis). Over the next 200 years, settlers cut down most of the trees to clear land for farming and to build houses. This deforestation peaked in the 1800s, at which point up to 80 percent of all New England forests had been cleared. Between 1850 and 1950, however, many people abandoned their New England farms to take jobs in the growing textile industry. Others moved to the Midwest, where farmland was considerably less expensive. Sugar Maple.

What happened to the former farmland is a testament to the resilience of the forest ecosystem. The transformation began shortly after the farmers left. Seeds of grasses and wildflowers were carried to the abandoned fields by birds or blown there by the wind. Within a year, the fields were carpeted with a large variety of plant species. Eventually, a single group of plants—the goldenrods—came to dominate the fields by growing taller and outcompeting other species of plants for Goldenrod. sunlight. The other species remained in the fields, but they were not very abundant. Nevertheless, the dominance of the goldenrods was short-lived.

Goldenrods and other wildflowers play an important part in old field communities by supporting a diverse group of plant- eating . Some of these herbivorous insects are generalists that feed on a wide range of plant species, while others specialize on only a small number of plant species. The Microrhopala leaf . number of individuals of each species varies from year to year, and occasionally some species experience very large population increases, or outbreaks. One such species is a (Microrhopala vittata) that specializes in eating goldenrods. Periodic outbreaks of leaf in the abandoned fields of New England dramatically reduced the populations of goldenrods. With fewer goldenrods, other plant species could compete and prosper.

The complex interactions among populations of goldenrods, Mixed Hemlock-broadleaf forest. insects, and other species created an ever-changing ecosystem. For example, as the leaf beetle population increased in the community, so did the populations of predators and parasites that fed on them. As predators and parasites reduced the leaf beetle population increased in the community, so did the populations of predators and parasites that fed on them. As predators and parasites reduced the leaf beetle population, the goldenrod population began to rebound. As goldenrod populations surged, they once again caused the other plant species to decline in numbers. !

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Over time, tree seeds arrived, and tree seedlings began to grow. Their presence changed the species composition of the old fields once again. One species in particular, the fast-growing white pine, eventually came to dominate. The pine trees cast so much shade that the goldenrods and other sunlight-loving plant species could not survive.

White pines dominated the old field communities until humans began harvesting them for lumber in the 1900s. Just as the reduction of goldenrod populations made room for other plant species, logging of the white pines made room for broadleaf tree species. Two of these broadleaf species, American beech and sugar maple, are dominant in New England forests today. Thus the abandoned New England fields were slowly trans-formed into communities that resemble the original forests of centuries ago, with ?a mix of pines, hemlocks, and broadleaf trees. The old stone walls are the only evidence that this forest was once farmland.

The story of the New England forests shows us that populations can increase or decrease dramatically over time. It also illustrates how species interactions within a community can alter species abundance. Finally, it demonstrates how human activity can alter the distribution and diversity of species within an ecosystem.

Sources: W. P. Carson and R. B. Root, Herbivory and plant species coexistence: Community regulation by an outbreaking phytophagous insect, Ecological Monographs 70 (2000): 73−99; T. Wessels, Reading the Forested Landscape (Countryman Press, 1997).

KEY IDEAS

There are clear patterns in the distribution and abundance of species across the globe. Understanding the factors that generate these patterns can help us find ways to preserve global biodiversity. These factors include the ways in which populations increase and decrease in size and the ways in which species interact with one another in their communities. ! After reading this chapter you should be able to:

‣! list the levels of complexity found in the natural world. ! ‣ contrast the ways in which density-dependent and density-independent factors affect population size. ! ‣ explain growth models, reproductive strategies, survivorship curves, and metapopulations. ! ‣ describe species interactions and the roles of keystone species. ! ‣ discuss the process of ecological succession. ! ‣ explain how latitude, time, area, and distance affect the species richness of a community. 3 THS A.P.E.S. CHAPTER 5

5.1 NATURE EXISTS AT SEVERAL LEVELS OF COMPLEXITY ! A New England forest is a wonderful reminder of the intricate complexity of the natural world. As FIGURE 5.1 shows, the environment around us exists at a series of increasingly complex levels: individuals, populations, communities, ecosystems, and the biosphere. The simplest level is the individual—a single organism. Natural selection operates at the level of the individual because it is the individual that must survive and reproduce.

! Figure 5.1 Levels of complexity Environmental scientists study nature at several different levels of complexity, ranging from the individual organism to the biosphere. At each level, scientists focus on different processes.

The second level of complexity is the population. A population is composed of all individuals that belong to the same species and live in a given area at a particular time. Evolution occurs at the level of the population. Scientists who study populations are also interested in the factors that cause the number of individuals to increase or decrease. !

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As we saw in Chapter 1, some populations, such as mosquito larvae living in a puddle of water, inhabit small areas, whereas others, such as the white-tailed deer (Odocoileus virginianus) that range across much of North America, inhabit large areas. The boundaries of a population are rarely clear and may be set arbitrarily by scientists. For example, depending on what we want to learn, we might study the entire population of white-tailed deer in North America, or we might focus on the deer that live within a single state, or even within a single forest.

The third level of complexity is the community. A community incorporates all of the populations of organisms within a given area. Like those of a population, the boundaries of a community may be defined by the state or federal agency responsible for managing it. Scientists who study communities are generally interested in how species interact with one another. Many communities are named for the species that are visually dominant. In the New England forest, for instance, we can talk about the maple-beech-hemlock community that made up the original forest or the goldenrod community that occupied the abandoned fields.

When terrestrial communities in different parts of the world experience similar patterns of temperature and precipitation, those communities can be grouped into biomes that contain plants with similar growth forms. Temperate seasonal forests around the world, for example, all contain deciduous trees. However, their actual tree species composition varies from community to community. Thus the temperate seasonal forests of the eastern United States and Europe may at first appear to be very similar, but they contain different tree species.

Communities exist within an ecosystem, which consists of all of the biotic and abiotic components in a particular location. Ecosystem ecologists study flows of energy and matter, such as the cycling of nutrients through the system.

The largest and most complex system environmental scientists study is the biosphere, which incorporates all of Earth’s ecosystems. Scientists who study the biosphere are interested in the movement of air, water, and heat around the globe.

CHECKPOINT

• What levels of complexity make up the biosphere? ! • What do scientists study at each level of complexity? ! • How do populations and communities differ?

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5.2 POPULATION ECOLOGISTS STUDY THE FACTORS THAT REGULATE POPULATION ABUNDANCE AND DISTRIBUTION

Populations are dynamic—that is, they are constantly changing. As FIGURE 5.2 shows, the exact size of a population is the difference between the number of inputs to the population (births and immigration) and outputs from the population (deaths and emigration) within a given time period. If births and immigration exceed deaths and emigration, the population will grow. If deaths and emigration exceed births and immigration, the population will decline and, over time, will eventually go extinct. The study of factors that cause populations to increase or decrease is the science of population ecology.

! ! Figure 5.2 Population inputs and outputs. Populations increase in size due to births and immigration and decrease in size due to deaths and emigration. ! There are many circumstances in which scientists find it useful to identify the factors that influence population size over time. For example, in the case of endangered species such as the California condor (Gymnogyps californianus), knowing the factors that affect a species’ population size has helped us implement measures to improve its survival and reproduction. Similarly, knowing the factors that influence the population size of a pest species can help us control it. For instance, population ecologists are currently studying the emerald ash borer (Agrilus planipennis), an invasive species in the American Midwest that is causing widespread deaths of ash trees. Once we understand the population ecology of this destructive insect, we can begin to discover and develop strategies to control or eradicate it. ! ! ! ! !

6 THS A.P.E.S. CHAPTER 5 ! 5.2.1 POPULATION CHARACTERISTICS ! To understand how populations change over time, we must first examine some basic population characteristics. These characteristics are population size, density, distribution, sex ratio, and age structure. ! POPULATION SIZE Population size(N) is the total number of individuals within a defined area at a given time. For example, the California condor once ranged throughout California and the southwestern United States. Over the past two centuries, however, a combination of poaching, poisoning, and accidents (such as flying into electric power lines) greatly reduced the population’s size. By 1987, there were only 22 birds remaining in the wild. Scientists who realized that the species was nearing extinction decided to capture all the wild birds and start a captive breeding program in zoos. As a result of captive breeding and other conservation efforts, the condor population size had increased to more than 300 by 2009. ! POPULATION DENSITY Population density is the number of individuals per unit area (or volume, in the case of aquatic organisms) at a given time. Knowing a population’s density, in addition to its size, can help scientists estimate whether a species is rare or abundant. For example, the density of coyotes (Canis latrans) in some parts of Texas might be only 1 per square kilometer, but in other parts of the state it might be as high as 12 per square kilometer. Scientists also study population density to determine whether a population in a particular location is so dense that it might outstrip its food supply.

Population density can be a particularly useful measure for wildlife managers who must set hunting or fishing limits on a species. For example, managers may divide the entire population of an species that is hunted or fished into management zones. These management zones may be human- defined areas, such as counties, or areas with natural boundaries, such as the major water bodies in a state. Wildlife managers might offer more hunting or fishing permits for high-density zones and fewer permits for low-density zones. ! POPULATION DISTRIBUTION In addition to knowing a population’s size and density, population ecologists are interested in knowing how a population occupies space. Population distribution is a description of how individuals are distributed with respect to one another. FIGURE 5.3 shows three types of population distributions. In some populations, such as a population of trees in a natural forest, the distribution of individuals is random (FIGURE 5.3a). In other words, there is no pattern to the locations where individual trees grow. ! !

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Figure 5.3 Population distributions. Populations in nature distribute themselves in three ways. (a) Many of the tree species in this New England forest are randomly distributed, with no apparent pattern in the locations of individuals. (b) Territorial nesting birds, such as these Australasian gannets (Morus serrator), exhibit a uniform distribution, in which all individuals maintain a similar distance from one another. (c) Many pairs of eyes are better than one at detecting approaching predators. The clumped distribution of these meerkats (Suricata suricatta) provides them with extra protection. ! ! In other populations, such as a population of trees in a plantation, the distribution of individuals is uniform. In other words, individuals are evenly spaced (FIGURE 5.3b). Uniform distributions are common among territorial , such as nesting birds that defend similarsized areas around their nests. Uniform distributions are also observed among plants that produce toxic chemicals to prevent other plants of the same species from growing close to them.

In still other populations, the distribution of individuals is clumped (FIGURE 5.3c). Clumped distributions, which are common among schooling fish, flocking birds, and herding mammals, are often observed when living in large groups enhances feeding opportunities or protection from predators. !

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POPULATION SEX RATIO The sex ratio of a population is the ratio of males to females. In most sexually reproducing species, the sex ratio is usually close to 50:50. Sex ratios can be far from equal in some species, however. In fig wasps, for example, there may be as many as 20 females for every male. Because the number of offspring produced is primarily a function of how many females there are in the population, knowing a population’s sex ratio helps scientists estimate the number of offspring a population will produce in the next generation. ! POPULATION AGE STRUCTURE Many populations are composed of individuals of varying ages. A population’s age structure is a description of how many individuals fit into particular age categories. Knowing a population’s age structure helps ecologists predict how rapidly a population can grow. For instance, a population with a large proportion of old individuals that are no longer capable of reproducing, or with a large proportion of individuals too young to reproduce, will produce far fewer offspring than a population that has a large proportion of individuals of reproductive age. !

! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

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6.2.2 FACTORS THAT INFLUENCE POPULATION SIZE ! Factors that influence population size can be classified as density dependent or density independent. We will look at each type in turn.

DENSITY-DEPENDENT FACTORS Density-dependent factors influence an individual’s probability of survival and reproduction in a manner that depends on the size of the population. The amount of available food, for example, is a density-dependent factor. Because a smaller population requires less total food, food scarcity will have a greater negative effect on the survival and reproduction of individuals in a large population than in a small population.

In 1932, Russian biologist Georgii Gause conducted a set of experiments that demonstrated how food supply controls population growth. Gause monitored population growth in two species of Paramecium (a type of single-celled aquatic organism) living under ideal conditions in test tubes. Each day he added a constant amount of food. As the graph in FIGURE 5.4a shows, both species of Paramecium initially experienced rapid population growth. Over time, however, the rate of growth began to slow. Eventually, the population sizes reached a plateau and remained there for the rest of the experiment. ! Figure 5.4 Gause’s experiments. (a) Over time, the population sizes of two species of Paramecium initially increased, but then leveled off as their food supply became limiting. (b) When Gause doubled their food supply, both species attained populations sizes that were nearly twice as large. [After Gause 1932.] ! Gause suspected that Paramecium population growth was limited by food supply. To test this hypothesis, he conducted a second experiment in which he doubled the amount of food he added to the test tubes. Again, both species of Paramecium experienced

10 THS A.P.E.S. CHAPTER 5 rapid population growth early in the experiment, and the rate of growth slowed over time. However, as FIGURE 5.4b shows, their maximum population sizes were approximately double those observed in the first experiment.

Gause’s results confirmed that food is a limiting resource for Paramecium. A limiting resource is a resource that a population cannot live without and which occurs in quantities lower than the population would require to increase in size. If a limiting resource decreases, so does the size of a population that depends on it. For terrestrial plant populations, water and nutrients such as nitrogen and phosphorus are common limiting resources. For animal populations, food, water, and nest sites are common limiting resources.

To better understand density dependence, let’s consider a situation in which there is a moderate amount of food available for animals to eat. At low population densities, only a few individuals share this limiting resource, and each individual has access to sufficient quantities. As a result, each individual in the population survives and reproduces well, and the population grows rapidly. At high population densities, however, many more individuals must share the food, so each individual receives a smaller share. With a smaller share, each individual has a lower probability of surviving, and those that do survive produce fewer offspring. As a result, the population grows slowly. In this example, the ability to survive and reproduce depends on the density of the population, so population growth is rapid at low population densities but slow at high population densities.

Similarly, in Gause’s Paramecium experiments, food was the limiting resource. Population growth slowed as population size increased because there was a limit to how many individuals the food supply could sustain. This limit is called the carrying capacity of the environment and denoted as K. Knowing the carrying capacity for a species, and what its limiting resource is, helps us predict how many individuals an environment can sustain. This is true whether those individuals are paramecia, cows, or humans. ! DENSITY-INDEPENDENT FACTORS Density-independent factors have the same effect on an individual’s probability of survival and amount of reproduction at any population size. A tornado, for example, can uproot and kill a large number of trees in an area. However, a given tree’s probability of being killed does not depend on whether it resides in a forest with a high or low density of other trees. Other density-independent factors include hurricanes, floods, fires, volcanic eruptions, and other climatic events. An individual’s likelihood of mortality increases during such an event regardless of whether the population happens to be at a low or high density.

Bird populations are often regulated by density independent factors. For example, in the United Kingdom, a particularly cold winter can freeze the surfaces of ponds, making amphibians and fish inaccessible to wading birds such as herons. With their food supply cut off, herons have an increased risk of starving to death, regardless of whether the heron population is at a low or a high density. ! !

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CHECKPOINT

• What factors regulate the size of a population? ! • What did Gause discover in his experiments? ! • What is the difference between density-dependent and density-independent factors that influence population size? ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

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5.3 GROWTH MODELS HELP ECOLOGISTS UNDERSTAND POPULATION CHANGES

Scientists often use models to help them explain how things work and to predict how things might change in the future. Population ecologists use population growth models that incorporate density- dependent and density-independent factors to explain and predict changes in population size. Population growth models are important tools for population ecologists, whether they are protecting an endangered condor population, managing a commercially harvested fish species, or controlling an insect pest. In this section we will look at several growth models and other tools for understanding changes in population size. ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

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5.3.1 THE EXPONENTIAL GROWTH MODEL ! Population growth models are mathematical equations that can be used to predict population size at any moment in time. The growth rate of a population is the number of offspring an individual can produce in a given time period, minus the deaths of the individual or its offspring during the same period. Under ideal conditions, with unlimited resources available, every population has a particular maximum potential for growth, which is called the intrinsic growth rate and denoted as r. When there is plenty of food available, for example, white-tailed deer can give birth to twin fawns, domesticated hogs (Sus domestica) can have litters of 10 piglets, and American bullfrogs (Rana catesbeiana) can lay up to 20,000 eggs. Under these ideal conditions, the number of deaths also decreases. Together, a high number of births and a low number of deaths produce a high population growth rate. Under less than ideal conditions, when resources are limited, the population’s growth rate will be lower than its intrinsic growth rate because individuals will produce fewer offspring (or forego breeding entirely) and the number of deaths will increase. ! If we know the intrinsic growth rate of a population (r) and the number of reproducing individuals that are currently in the population (N0), we can estimate the population’s future size (Nt) after some period of time (t) has passed. To do this, we can use the exponential growth model,

where e is the base of the natural logarithms (the ex key on your calculator, or 2.72) and t is time. This equation tells us that, under ideal conditions, the future size of the population (Nt) depends on the current size of the population (N0), the intrinsic growth rate of the population (r), and the amount of time (t) over which the population grows. ! ! Figure 5.5 The exponential growth model. When populations are not limited by resources, their growth can be very rapid. More births occur with each step in time, creating a J-shaped growth curve. !

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When populations are not limited by resources, their growth can be very rapid, as more births occur with each step in time. When graphed, the exponential growth model produces a J-shaped curve, as shown in FIGURE 5.5.

One way to think about exponential growth in a population is to compare it to annual interest payments in a bank account. Let’s say you put $1,000 in a bank account at an annual interest rate of 5 percent. After a year, assuming you did not withdraw any of your money, you would earn 5 percent of $1,000, which is $50. The account would then show a balance of $1,050. In the second year, again assuming no withdrawals, the 5 percent interest rate would be applied to the new amount of $1,050, and would generate $52.50 in interest. In the tenth year, the account would generate $77.57 in interest. Moving forward to the twentieth year, the same 5 percent interest rate would produce a much larger increase of $126.35.

Applying an annual rate of growth to an increasing amount, whether money in a bank account or a population of organisms, produces rapid growth over time. Exponential growth is density independent because no matter how much money you have in the account, the value will grow by the same percentage every year. Do the Math “Calculating Exponential Growth” gives a step-by-step example to show how this principle works.

The exponential growth model is an excellent starting point for understanding population growth. Indeed, there is solid evidence that real populations—even small ones—can grow exponentially, at least initially. However, no population can experience exponential growth indefinitely. In Gause’s experiments with Paramecium, the two populations initially grew exponentially until they approached the carrying capacity of their test-tube environment, at which point their growth slowed and eventually leveled off to reflect the amount of food that was added daily. We turn next to another model that gives a more complete view of population growth. !

! ! ! ! ! ! ! ! ! !

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DO THE MATH Calculating Exponential Growth ! Consider a population of rabbits that has an initial population size of 10 individuals (N0 = 10). Let’s assume that the intrinsic rate of growth for a rabbit is r = 0.5 (or 50 percent), which means that each rabbit produces a net increase of 0.5 rabbits each year. With this information, we can predict the size of the rabbit population 1 year from now: ! We can then ask how large the rabbit population will be after 5 years: ! We can also project the size of the rabbit population 10 years from now: ! These data are graphed in FIGURE 5.6. ! Figure 5.6 Rabbit population growth. Graphing the data from Do the Math “Calculating Exponential Growth” gives us a clearer sense of how rapid exponential growth can be. When the rabbit population is small, small numbers of rabbits are added in a single year. The larger the population grows, however, the more rabbits are added each year. ! Your Turn: Now assume that the intrinsic rate of growth is 1.0 for rabbits. Calculate the predicted size of the rabbit population after 1, 5, and 10 years.

! ! ! ! !

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5.3.2 THE LOGISTIC GROWTH MODEL ! The exponential growth model describes a continuously increasing population that grows at a fixed rate. But populations do not experience exponential growth indefinitely. For this reason, ecologists have modified the exponential growth model to incorporate environmental limits on population growth, including limiting resources. The logistic growth model describes a population whose growth is initially exponential, but slows as the population approaches the carrying capacity of the environment (K?). As we can see in FIGURE 5.7, if a population starts out small, its growth can be very rapid. ! ! Figure 5.7 The logistic growth model. A small population initially experiences exponential growth. As the population becomes larger, however, resources become scarcer, and the growth rate slows. When the population size reaches the carrying capacity of the environment, growth stops. As a result, the pattern of population growth follows an S- shaped curve. ! ! ! ! ! As the population size nears about one-half of the carrying capacity, however, the population’s growth begins to slow. As the population size approaches the carrying capacity, the population stops growing. When graphed, the logistic growth model produces an S-shaped curve. We observed this pattern in Gause’s Paramecium experiments: at the carrying capacity, the populations stopped growing and remained at a constant size.

The logistic growth model is used to predict the growth of populations that are subject to density- dependent constraints, such as increased competition for food, water, or nest sites, as the population grows. Because density-independent factors such as hurricanes and floods are inherently unpredictable, the logistic growth model does not account for them.

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5.3.3 VARIATIONS ON THE LOGISTIC GROWTH MODEL ! One of the assumptions of the logistic growth model is that the number of offspring individuals produce depends on the current population size and the carrying capacity of the environment. However, many species of mammals mate during the fall or winter, and the number of offspring that develop depends on the food supply at the time of mating. Because these off-spring are not actually born until the following spring, there is a risk that food availability will not match the new population size. If there is less food available in the spring than needed to feed the offspring, the population will experience an overshoot by becoming larger than the spring carrying capacity. As a result, there will not be enough food for all the individuals in the population, and the population will experience a die- off, or population crash.

The reindeer (Rangifer tarandus) population on St. Paul Island in Alaska is a good example of this pattern. After a small population of 25 reindeer was introduced to the island in 1910, it grew exponentially until it reached more than 2,000 reindeer in 1938. After 1938, the population crashed to only 8 animals, most likely because the reindeer ran out of food. FIGURE 5.8 shows these changes graphically.

! Figure 5.8 Growth and decline of a reindeer population. Humans introduced 25 reindeer to St. Paul Island, Alaska, in 1910. The population initially experienced rapid growth (blue line) that approximated a J-shaped exponential growth curve (orange line). In 1938, the population crashed, probably because the animals exhausted the food supply. [Data from V. B. Scheffer, The rise and fall of a reindeer herd, Scientific Monthly (1951): 356−362.]

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Figure 5.9 Population oscillations. Some populations experience recurring cycles of overshoots and die-offs that lead to a pattern of oscillations around the carrying capacity of their environment. ! Such die-offs can take a population well below the carrying capacity of the environment. In subsequent cycles of reproduction, the population may grow large again. FIGURE 5.9 illustrates the recurring cycle of overshoots and die-offs that causes populations to oscillate around the carrying capacity. In many cases, these oscillations decline over time and approach the carrying capacity.

So far we have considered only how populations are limited by resources such as food, water, and the availability of nest sites. Predation may play an important additional role in limiting population growth. A classic example is the relationship between snowshoe hares (Lepus americanus) and the lynx (Lynx canadensis) that prey on them in North America. Trapping records from the Hudson’s Bay Company, which purchased hare and lynx pelts for nearly 90 years in Canada, indicate that the populations of both species cycle over time. FIGURE 5.10 shows how this interaction works. The lynx population peaks 1 or 2 years after the hare population peaks. As the hare population increases, it provides more prey for the lynx, and thus the lynx population begins to grow. As the hare population reaches a peak, food for hares becomes scarce, and the hare population dies off. The decline in hares leads to a subsequent decline in the lynx population. The low lynx numbers reduce predation, and the hare population increases again. ! !

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Figure 5.10 Population oscillations in lynx and hares. Population sizes of predatory lynx and their hare prey have been estimated from records of the number of hare and lynx pelts purchased by the Hudson’s Bay Company. Both species exhibit repeated oscillations of abundance, with the lynx population peaking 1 to 2 years after the hare population. [Data from Hudson’s Bay Company.] ! A similar case of predator control of prey populations has been observed on Isle Royale, Michigan, an island in Lake Superior. Wolves (Canis lupus) and moose (Alces alces) have coexisted on Isle Royale for several decades. Starting in 1981, the wolf population declined sharply, probably as a result of a deadly canine virus. As wolf predation on moose declined, the moose population grew rapidly until it ran out of food. It then experienced a large die-off beginning in 1995. FIGURE 5.11 shows the changes in both populations over a 50-year period. !

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Figure 5.11 Predator control of prey populations. As the population of wolves on Isle Royale succumbed to a canine virus, their moose prey experienced a dramatic population increase. [Data from J. A. Vucetich and R. O. Peterson, Ecological Studies of Wolves on Isle Royale: Annual Report 2007−2008, School of Forest Resources and Environmental Science, Michigan Technological University.] !

! ! ! ! !

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5.3.4 REPRODUCTIVE STRATEGIES AND SURVIVORSHIP CURVES ! Population size most commonly increases through reproduction. Population ecologists have identified a range of reproductive strategies in nature.

K-SELECTED SPECIES Some species have a low intrinsic growth rate, which causes their populations to increase slowly until they reach the carrying capacity of the environment. As a result, the abundance of such species is determined by the carrying capacity, and their population fluctuations are small. Because carrying capacity is denoted as K in population models, such species are referred to as K-selected species.

K-selected species have certain traits in common. For instance, K-selected animals are typically large organisms that reach reproductive maturity relatively late, produce a few, large offspring, and provide substantial parental care. Elephants, for example, do not become reproductively mature until they are 13 years old, breed only once every 2 to 4 years, and produce only one calf at a time. Large mammals and most birds are K-selected species. For environmental scientists interested in biodiversity management or protection, K-selected species pose a challenge because their populations grow slowly. In practical terms, this means that an endangered K-selected species cannot respond quickly to efforts to save it from extinction. ! r-SELECTED SPECIES At the opposite end of the spectrum are those species that have a high intrinsic growth rate because they reproduce often and produce large numbers of offspring. Because intrinsic growth rate is denoted as r in population models, such species are referred to as r-selected species. In contrast to K-selected species, populations of r-selected species do not typically remain near their carrying capacity, but instead exhibit rapid population growth that is often followed by overshoots and die-offs. Among animals, r-selected species tend to be small organisms that reach reproductive maturity relatively early, reproduce frequently, produce many small offspring, and provide little or no parental care. House mice (Mus musculus), for example, become reproductively mature at 6 weeks of age, can breed every 5 weeks, and produce up to a dozen offspring at a time. Other r-selected organisms include small fishes, many insect species, and weedy plant species. Many organisms that humans consider to be pests, including cockroaches, dandelions, and rats, are r- selected species. ! ! ! ! ! !

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TABLE 5.1 summarizes the traits of K-selected and r-selected species. These two concepts represent opposite ends of a wide spectrum of reproductive strategies. Most species fall somewhere in between these two extremes, and many exhibit combinations of traits from the two extremes. For example, tuna and redwood trees are both long-lived species that take a long time to reach reproductive maturity. Once they do, however, they produce millions of small offspring that receive no parental care.

Table 5.1

! ! ! ! ! ! ! ! ! ! ! !

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Figure 5.12 Survivorship curves. Different species have distinct patterns of survivorship over the life span. Species range from exhibiting excellent survivorship until old age (type I curve) to exhibiting a relatively constant decline in survivorship over time (type II curve) to having very low rates of survivorship early in life (type III curve). K-selected species tend to exhibit type I curves, whereas r-selected species tend to exhibit type III curves.

! In addition to different reproductive strategies, species have distinct patterns of survival over time. These patterns can be plotted on a graph as survivorship curves, as shown in FIGURE 5.12. There are three basic types of survivorship curves. K-selected species such as elephants, whales, and humans have high survival rates throughout most of their life span. As they approach old age, however, they start to die in large numbers. This pattern is called a type I survivorship curve. In contrast, r-selected species such as mosquitoes and dandelions experience low survivorship early in life, and few individuals reach adulthood. This pattern is called a type III survivorship curve. Many other species, such as corals and squirrels, experience a relatively constant decline in survivorship throughout their life span. This pattern is called a type II survivorship curve. ! !

! !

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5.3.5 METAPOPULATIONS ! Cougars (Puma concolor)—also called mountain lions or pumas—once lived throughout North America, but because of habitat destruction and overhunting, they are now found primarily in the remote mountain ranges of the western United States. In New Mexico, cougar populations are distributed in patches of mountainous habitat scattered across the desert landscape. These mountain habitats allow the cats to avoid human activities and provide them with reliable sources of water and prey such as mule deer (Odocoileus hemionus).

Because areas of desert separate the cougar’s mountain habitats, we can consider the cougars of each mountain range to be a distinct population. Each population has its own dynamics based on local abiotic conditions and prey availability: large mountain ranges support large cougar populations and smaller mountain ranges support smaller cougar populations. However, cougars sometimes move between mountain ranges, often using strips of natural habitat that connect the separated populations. Such strips of habitat—called corridors—provide some connectedness among the populations, as FIGURE 5.13 shows. A group of spatially distinct populations that are connected by occasional movements of individuals between them is called a metapopulation. ! Figure 5.13 A cougar metapopulation. Populations of cougars live in separate mountain ranges in New Mexico. Occasionally, however, individuals move between mountain ranges. These movements can recolonize mountain ranges with extinct populations and add individuals and genetic diversity to existing populations. ! ! ! ! !

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The connectedness among the populations within a metapopulation is an important part of each population’s overall persistence. Small populations are more likely than large ones to go extinct. First, as we have seen, small populations contain relatively little genetic variation and therefore may not be able to adapt to changing environmental conditions. Second, they are more vulnerable than large populations to density-independent catastrophes such as particularly harsh winters. In a metapopulation, occasional immigrants from larger nearby populations can add to the size of a small population and introduce new genetic diversity. Both of these factors help to reduce the risk of extinction.

Metapopulations can also provide a species with some protection against threats such as diseases. A disease could cause a population living in a single large habitat patch to go extinct. But if a population living in an isolated habitat patch is part of a much larger metapopulation, then a disease could wipe out that isolated population, but immigrants from other populations could later recolonize the patch and help the species to persist.

Because many habitats are naturally patchy across the landscape, many species are part of metapopulations. For instance, numerous species of butterflies specialize on plants with patchy distributions. Some amphibians live in isolated wetlands, but occasionally disperse to other wetlands. The number of species that exist as metapopulations is growing because human activities have fragmented habitats, dividing single large populations into several smaller populations. Identifying and managing metapopulations is thus an increasingly important part of protecting biodiversity.

CHECKPOINT ! • What happens if you alter the r or K terms in the logistic growth model? ! • What did scientists learn from the records of the Hudson’s Bay Company? ! • What is a metapopulation? How do metapopulations contribute to the preservation of biodiversity? ! !

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