Unit 3 - Population Growth and Regulation

In this unit you will learn about the fundamental factors which influence how populations grow. You will also learn about the internal and external factors that regulate growth. Sometimes the factors that affect population growth are environmental, such as the presence of limited resources. Other times it is the trade off between factors such as survival and reproduction, or the number of young, and the size of each young produced. Species have evolved as a result of these environmental pressures, and this often gives rise to predictable patterns of survivorship and reproduction. For example, habitats that are complex and stable may favor organisms that produce fewer, larger offspring, whereas less crowded environments may favor organisms that produce smaller, but more numerous offspring.

It is possible to model the growth of populations over time. Simplistic models give explosive, exponential growth predictions. Complex models, which take resource availability into account, show that populations are limited in the total number of individuals that can successfully survive and reproduce.
Outcomes from these complex models indicate that there are important repercussions for humans as we begin to reach our carrying capacity here on earth. Because of the lack of clean water, food, or clean air, scientists predict that human population size will soon reach its limit. The consequences that will follow this event remain debatable.

Why should you care about population biology? Many of these theories and models apply to everyday life. If you like to vacation in the mountains or at the beach, you need a healthy ecosystem to keep the place looking vacation-like. If you get sick, you want antibiotics that effectively reduce the population size of germs inside you. And if you live in Austin, you may want the growth of bacterial in Barton Springs kept at a minimum, so you and your friends can go swimming.

Read  Concept 52.1 How biological processes affect population density… on pp. 1136-1139

Unit 3 outline:

3.1. Population characteristics
    l. definition
    ll. density
    lll. dispersion
3.2 Patterns of dispersion
    l. clumped
    ll. course grained versus fine-grained
    lll. uniform
    lV. random

3.3 Demography
    l. definition
    ll. demographic study factors of populations
3.4 Life tables
    l. definition of a life table
    ll. application to real populations
3.5 Survivorship curves
    l. type I
    ll. type II
    lll. type III
3.6 Life history traits (LHT)
    l. variation in LHT patterns
    ll. environmental factors
    lll. life history traits and extinction
    lV. life history tradeoffs
3.7 Reproductive episody
    l. semelparity
    ll. iteroparity
3.8 Population growth models
    l. birth rate
    ll. death rate
3.9 Methods for studying population growth
    l. simple mathematical models
    ll. comparing simple models to natural populations
3.9 Experimental population growth
    l. logistic population growth- theoretical
    ll. logistic growth and real populations
    lll. r and K-selected traits
3.10 Population limiting factors
     l. density dependent factors
     ll. density independent factors
3.12 Human population growth
    l. current growth rates as exponential
    ll. limits to human growth rates

3.1 Population Characteristics

l. definition

A population can be defined as a group of conspecifics (members of the same species) that use the same niche. Recall that a niche is an organism's "address"- everything the animal uses to survive and reproduce successfully. This can include food, shelter, water, nesting sited etc. Two important characteristics of any population are the density, or the number of individuals per unit area, and the dispersion, or patterns of spacing of individuals in a given area.

ll. density

Your book lists several different methods for measuring the density of a population. Some method are better suited for small organisms confined to an isolated habitat, such as a starfish or hermit crabs in a tide pool, while other methods are best for larger, migrating organisms such as caribou. It is important to realize that each method has its advantages and disadvantages. For example, counting all the individuals in the population is extremely important when studying rare and endangered species since habitat conservation plans are often based upon these estimates. The Peregrine Falcon is about to be removed from the United States endangered species list because scientists estimate that their numbers are over 1500. Obviously it is critical to know if this number is accurate or not. More commonly, population size is estimated by using a variety of sampling techniques. A density is first calculated for a small area, and population size for the entire area is then estimated from these data. Listed below are various techniques used to estimate populations:

- visual counts, such as raptor fly-overs or Christmas counts or songbirds
- traps ( live, snare, pheromone for insects, pitfall for crepuscular species)
- vocalization frequency (for nocturnal or arboreal species)
- fecal pellet (for mammals)
- nests or dens
- pelt records (especially good for historical work)
- percent ground cover (for plants)
- transect counts ( where the number of animals and plants are counted along a line. Good for sessile organisms)

If the data are accurate one can also estimate the frequency of juveniles, adults, larvae and other types of immature organisms. The data are then used to construct life tables (see section 3.5 below). Whatever sampling method is used, the method itself must avoid all biases such as the tendency to over, or undercount certain individuals. If every time you hear a golden cheek warbler sing you count one male in your sample, then you may be estimating the density of golden cheek warblers if the male moves frequently within his territory. Sampling from a population is an advantageous method when there are limited people or funds to do the work, and if the species in question appears to have a uniform distribution throughout its habitat. This sampling technique is less useful when habitats begin to vary, and the distribution of individuals is lumped.
Marking and recapturing individuals is another way to estimate population size. This would be most applicable to migrating species, such as butterflies and birds that follow highly predicable patterns of migration. Initial marking and recapturing of individuals must be based on random sampling techniques however, and must include a sufficient number of individuals to avoid any biases. Mallet et. al. (1987) found that mark-recapture techniques influenced the behavior of Helconius butterflies, and thus population estimates, since the butterflies avoided areas where they had been previously captured.

lll. dispersion

Populations can vary their dispersion patterns. Often the distribution of resources, and the type of resource can influence how a population distributes itself in its environment. Local distributions often are limited by physical or abiotic factors of the environment. These may include: temperature, moisture, light, pH, soil quality, salinity or water currents. For example, trees in the Northeastern United States can show different tolerances for light and nitrogen availability: Species that are tolerant for abiotic factors may have a wider range of distribution that those that are less tolerant, or intolerant for a specific factor. A tree species such as hickory that can tolerate low light (shade) can grow in more places that a tree species that cannot tolerate low light levels, such as tulip poplars. Hickories can grow in any area while tulip poplars are restricted to those areas of the forest with sufficient light. Thus hickories should have a wider distribution that tulip poplars. In general, young organisms tend to be more sensitive to variation in resources and less able to tolerate suboptimal conditions. This may be due to the fact that growing organisms need to used more energy and resources than mature organisms.

 SEPARATION OF TREE SPECIES IN THE UNITED STATED BY SHADE AND NITROGEN TOLERANCE

 TREE SPECIES

 SHADE TOLERANCE

 NITROGEN TOLERANCE

 HICKORY

 Tolerant

 Tolerant

 WHITE OAK

 Tolerant

 Intermediate

 BIG TOOTH ASPEN

 Tolerant

 Intolerant

 BEECH

 Intermediate

 Tolerant

 BASS WOOD

 Intermediate

 Intermediate

 TREMBLING ASPEN

 Intermediate

 Intolerant

 SUGAR MAPLE

 Intolerant

 Tolerant

 WHITE ASH

 Intolerant

 Intermediate

 TULIP POPULAR

 Intolerant

 Intolerant

3.2 Patterns of dispersion

l. clumped

A clumped distribution of organisms may occur when the resources themselves are patchy. For example, salvia plants may group together in places where the soil is alkaline and free of salt. Organisms often clump around the most limited of resources or factors: temperature, moisture, light, nutrients (nitrogen and phosphorous) and oxygen content. It may be that one factor such as temperature, is most important. Saguaro cactuses can withstand a frost if the plant can thaw out during the day. Plants will die however, if temperatures remain below freezing for more than 36 hours. The distribution of saguaro cactuses in Arizona is very distinct: they do not grow in places that do not thaw during the daytime hours. In turn there may be several factors that interact to determine organismal distribution. Recall that the availability of light and nutrients such as nitrogen, calcium, and potassium may all contribute to the distribution of trees within a forest.

Individuals may also group together for mating and social purposes, or because there are safety in numbers. Individual fish swimming in a school in the open ocean are less likely to be eaten than fish that swim by themselves. It is harder for a predator to pick off individuals in a group since it is more difficult to focus on a single individual. Imagine trying to catch a tennis ball when someone is throwing five of them at you at once. You will notice how difficult it is to keep your eyes on the ball. Indeed it is much harder than trying to catch a single ball.

ll. course grained versus fine-grained

Resources may vary in the size and number of clumps that are formed. This will dramatically affect the distribution of the animals using the resources. A coarse-grained environment may have large patches, such stands of acacia trees in the African grasslands. The trees may be lumped together around a limiting resource such as water and the clumps of trees may be very spread out across the savanna. A large numbers of individuals, such as monkeys can use the trees simultaneously for sleeping, and shelter from predators. Thus the distribution of monkeys and acacias in this case will be into a few, large patches. In contrast, a fine-grained environment will have smaller patch size and thus can accommodate fewer individuals per patch.

lll. uniform
Uniform environments are ones in which the individuals are evenly spaced throughout the habitat. Plants may be evenly spaced to avoid competition for resources such as sun and water. Other organisms, such as penguins may space themselves out to avoid aggression in a limited area.

lV. random

A random distribution occurs when there is no distinct pattern or predictability to the spacing. This is most likely to occur when conspecifics do not have an influence on each other (either for resources or social interactions). Trees in a forest often fall into this category.

Clumped or uniform patterns appear to be most common in nature, while random distribution appears to be more rare. Whatever the distribution of individuals is, however, it is important to study these patterns. By examining the distribution of individuals we can analyze how populations change over time. For example, we can determine whether populations of an endangered species are growing in size, or declining towards the edge of extinction.

3.3 Demography

l. definition

Demography is the study of factors that affect the growth and decline of a population. Additions to a population can occur through birth or immigration, while declines in a population occur through death or emigration. The birth and death rates of a population depend upon the age of the individuals in the population. For example, the death rate will be lower in a population of young organisms than in a population of older organisms.

ll. demographic study factors of populations

An age structure in a population is created when you have an overlap in generations. It is defined as the age of all the individuals in the population. Each age group will have its own birth rate, (for example 5 year olds versus 20 year olds), and death rates (20 year olds versus 60 year olds). Since certain age groups are more likely to reproduce young and other age groups are more likely to die, the total number of individuals in each age group will have direct effects on the growth and decline of a population. For example, a population of young rats will have a faster growth rate than a population of old rats whose birth rate has declined, and whose mortality rate has increased. While it sounds easy to create age structures for populations of organisms, it can be quite difficult to accurately age wild organisms. There are a number of ways to age wild-caught organisms and the most accurate method may be to mark and recapture individuals. For example, nesting and fledgling golden cheek warblers are captured in Central Texas each spring, and each is given an individual colored band combination and identification number. In succeeding years, biologists attempt to recapture every individual in the population (as well as band any new fledglings). In this way long-term (10-year) age profiles and can be collected to create age structures for a localized endangered species. While it takes a tremendous effort to mark and recapture the majority of individuals, the results can be impressive. In the case of golden cheek warblers, Dean Keddy-Hector's study recaptured 90 percent of all individuals in the population. Other, less accurate methods of estimating age include observing the wear and replacement of teeth in deer, or the annual growth rings in sheep horns and trees.

 

 

 

3.4 Life Tables

l. definition

Once you have collected information on the age of individuals in your population, you can begin to estimate the likelihood of an individual surviving from one year to another. For example if you mark one hundred nestling birds in year one and only recapture 80 individuals the next spring, you can estimate the chance of surviving as a yearling. Thus Life Tables are created from age data to estimate how long an individual of a given age is likely to live. Data for the life tables can be collected by following a specific group of individuals from birth to death, or through a census of living and dead individuals. Information on human age is used constantly by insurance companies that to figure out how long you are likely to live. Doctors use it when trying to predict how long someone can live once they have been diagnosed with cancer or heart disease. Life tables are important to have when estimating how well and threatened or endangered species is doing. They can help determine whether a population is able to maintain itself or whether individuals are dying and the species is going extinct.

ll. application to real populations

Life tables have been created for thousands of different species. If you look on page 1139 in Campbell you will find a life table for Belding Ground Squirrels. The table starts with 337 individual females (or 349 males) and records the number of individuals who survive from year to year. Note that while there are a few individuals who live to 6 or 7 years of age, the majority of squirrels, do not make it through their first year. Indeed 1/3 of the population is dead by the end of the second year. By counting the number of individuals who die each year, a death rate and average life expectancy can be calculated. The average life expectance of a newborn ground squirrel is 1.33 (or 1.07) years. You will note that this number coincides with the fact that almost 80% of individuals are dead by that point.

Plant life tables are more complex. Age is more difficult to determine and it is difficult to identify separate individuals. While the "parent" plant may die, it also lives on through the sprouts and suckers that come off of the roots of the plant. Thus demographers have to deal with mortality on two levels-one for the individual (or parent) plant, and one for the clones.

Plant mortality life tables can be useful when asking specific types of questions. For example, data on seed mortality and survival, life expectancies of perennial plants marked as seedlings, and life cycles of annual plants can be fairly easy to collect and fairly accurate.

 

3.5 Survivorship Curves

Data on another species, the cactus ground finches, would show that individuals do not necessarily survive at a constant rate. Life tables can be used to create mortality curves and survivorship curves. A mortality curve plots the rate of death against age. Often it may have several phases. For example in the finches we would see three phases: a juvenile phase where mortality rates were high, an adult phase where overall mortality were lower, and finally a "post adult" phase when mortality rates increased once more for older individuals. In this case, the change in mortality rate over age results in a "J" shaped curve. This pattern of survivorship is common for some birds and many mammals.

l. type 1

Survivorship curves can be plotted in a number of ways. Typically, the logarithmic number of survivors is plotted against time, or the age of the survivors. The accuracy of the table will depend upon the accuracy of the original data, and whether or not environmental conditions have changed. It turns out that species have different patterns of living and dying (see figure 52.5 on page 1140 in Campbell)) Type I survivorship curves depict a species with high survival rate through most of its lifetime, and a high mortality rate at the end. Animals (typically vertebrates) that have few offspring and invest heavily in their young fall in this category. Humans who have access to medical care and preventative medicine also follow these patterns of survivorship.

ll. type II

Type II organisms have a steady rate of mortality throughout their life span. Small animals such as squirrels, hydra, and migrating songbirds often follow this trend.

lll. type III

Type III organisms suffer tremendously high rates of mortality at an early age. Once individuals get through the bottleneck, however, they can live for a long time. Barnacles, for example, produce millions of young and release them into the sea. Most of the young drift along ocean currents and are eaten by predators. A few manage to settle in the rocky intertidal zone where they can find food and shelter. Those few individuals that make it there have an excellent chance of survival. Trees, insects, weeds and many aquatic species like clams would also be examples of type lll organisms. They make hundreds, even thousands of offspring but invest little energy in each. As a result many offspring do not find a favorable environment and die at an early age.

Note that while these 3 survivorship curves fit a great number of species, there are still exceptions to the rule. For example, some species exhibit a stepwise survivorship progression. There would include invertebrates that experience high survivorship during most of the year followed by high mortality during periods of molt. During a molt an animal's exoskeleton, such as a lobster's shell, is soft. This makes the organism very vulnerable to predation. Indeed, organisms like the lobster often hide during this period. Another exception to the typical survivorship patterns is exhibited Atlantic mackerel (Scomber scombrus). Mackerel tend to exhibit a type III curve with a high juvenile mortality rate.

Read Concept 52.2 "Life History Traits" on pp. 1141-1143

3. 6 Life History Traits (LHT)

l. variation in LHT patterns

In addition to births and deaths there are other factors that shape the population dynamics of a given species. These traits often affect the timing of reproduction and death.

ll. environmental factors

Often the life history patterns that arise coincide with specific types of environments. For example, David Lack's studies of songbirds in the 1940's indicated that temperate species often produce more offspring than tropical species. This pattern appears to hold true for mammals and lizards as well. Certain life history traits tend vary with one another. For example and increase in fecundity coincides with an increase in adult mortality.

lll. life history traits and extinction

Many biologists believe there are certain life history traits that increase a species' susceptibility to extinction. If this is so, it would be critical to know whether a endangered species, such as the whooping crane, posses these traits. Some of traits that have been identified include:
a) dispersal ability. Species that are capable of migrating between fragmented habitats stand a better chance of finding mates and maintaining genetic diversity. Thus if one fragmented population goes "extinct' it can be replaced by migrating individuals (see unit 4).
b) Degree of specialization. Organisms who specialize on only one type of resource, like panda bears that will only eat a specific species of bamboo, or wasps that will only eggs on one species of fig, are more likely to go extinct. Animals with more generalized diets can switch between food items if there is a loss of habitat.
c) Rates of reproduction. Species, like rats, that can produce a lot of offspring at an early age are more likely to bounce back after a population decline. An endangered species which can produce 100 offspring per year can replace itself more quickly that a species which only produced 1 offspring per year.
d) Longevity. A species that lives a long time, such as an elephant or a parrot (both which can live 70 or 80 years) may be able to withstand poor environmental conditions for several years and forgo reproduction during that time. In contrast, a species, which reproduces early, but dies quickly (such as opossums that typically live less than 3 years) may be unable to "wait it out" and die without replacing themselves.

lV. life history tradeoffs

No matter what the fundamental life history pattern a species follows, there appear to be several fundamental tradeoffs in nature. Since most organisms compete for limited resources, there is a finite amount of energy available to an organism over its lifetime. Decisions must be made about how to invest this energy. One of the most important tradeoffs is the investment of energy in survival versus an investment of energy in reproduction. Should one put all of one's energy into reproducing now, or put energy into surviving until the next breeding season when the conditions may be more favorable. Investment in the offspring includes not only the weight of offspring (ex. energy stored in eggs or seeds) but energy for nursing, or brooding, or caring for the young. Herbaceous perennial plants, for example, invest 15-20% of annual energy in reproduction whereas as wild annuals expend 15- 30%. Domesticated grain crops such as corn invest 30-40% of their energy in reproduction. Lizards like Lacerta vivipara invest 7-9% of their annual energy in reproduction where as
Mountain salamanders (Desmognathus ochophaeus) spend 48% of their energy on eggs and brooding.

3.7 Reproductive Episody

l. semelparity

Reproductive episody is the frequency of offspring production over one's lifetime. Semelparity (semel = once, parity = to beget) describes species such as salmon that have one large brood of offspring and then die. Annual plants and century plants also follow this pattern, as well as most insects, and some species of fish like the salmon. An extreme example would be some species of bamboo live for 100 to 120 years before the produce seeds and die.

ll. Iteroparity

Iteroparity (itero= to repeat), in contrast, describes species who have fewer offspring over many seasons. Thus perennial plants and most vertebrates would fall into this pattern. It is important to recognize that the total number of surviving offspring produced by a semelparous or iteroparous species may be the same. It is the timing of reproduction that varies. Conditions favor semelparity when the cost of surviving between broods is very high and there is a large tradeoff between fecundity and survivorship. Conditions favor iteroparity when infant morality is high, when parents are not present to raise their young, and established individuals have higher rates of surviving. This coincides with many of the Type III survivorship conditions.

Iteroparous species face another trade-off. An organism can produce several small offspring or a few large ones. Thus organisms can vary the number, and size of the offspring they have within a given breeding cycle. In general, the number of offspring an organism has will increase, as the cost of survivorship from one year to the next decreases. For example, organisms that experience high predation rates or overwintering moralities often fall into a Type III patterns of survivorship. As the size of offspring increase, the number of offspring decreases. Codfish lay millions of eggs that float in the ocean with no parental care. Bass, in contrast, lay 100's of eggs and provide some parental care. Most amphibians and reptiles provide little or nor care for their offspring and lay many more eggs than birds which actively care for their young. The exception to this rule is crocodiles that actively defend the nest and care for young. Crocodiles tend to lay fewer eggs than other species of reptiles.

Read Concept 52.3- 52.4"Population Growth Models" on pp. 1143-1167

3.8 Population Growth Models

l. simple mathematical models

Recall that the two factors that affect the growth of any population are the overall birth rate and death rate. A population's growth can be examined through observation, experimentation, or through mathematical modeling.
It is extremely difficult (if not impossible) to model an experimental population, that contains all the factors and variables that are found in a natural population. Yet models should not be ignored. They can be quite useful in identifying the important principles that affect the growth of most populations. Thus a useful starting point when modeling is to start with simple assumptions and add assumptions one at a time. We will start off in our model of population growth by assuming that the population size is small, and that resources are unlimited. Under these simplistic conditions:

a change in populations size = BR (birth rate) -DR (death rate)
(during a given time interval )

or N/ t= B-D

where N= the population and t= time

It is not very useful to look at the birth rate for an entire species when what we are studying is a sample population. Thus it is more useful to study a per capita birth rate (b) and death rate (d) than an absolute birth and death rates. A per capita birth looks at the birth rate per a certain number of individuals. For example, if the population size is 1000 and 20 offspring are born into that population, then the birth rate b= 20/1000 or .020. (If you are unsure with these calculations you may wish to look at Unit 2 and go over frequencies and percents again).

Thus we can now restate our original equation using per capita birth and death rates as

N/ t= bN - dN

We can also symbolize the rate of population growth (r) as the per capita birth rate minus the per capita death rate, or r = b-d. A positive r indicates that the population is growing while a negative r indicates that the population is declining.

Thus N/ t= rN

Finally, we may wish to look at a particular segment of time during which the population is growing or declining. We call this segment of time the instantaneous rate of growth or decline (rmax). Using the instantaneous rate of growth or decline will allow us to create an equation that is essentially the same as the preceding one, but with smaller time intervals, Thus we arrive at our final equation:

dN/dt= rN

Under the experimental growth conditions which were outlined above (a small population size and unlimited resources), rmax is the intrinsic rate of population increase and dN/dt = rmaxN . This is the called the Exponential Population Growth Equation and gives us a J shaped curve. You can see an example of a two different J-shaped curves on page 1160 in Campbell (figure 52.8).

ll. Comparing simple models to natural populations

The exponential growth curve gives us a good starting point, and may be useful in describing populations that have move into new or empty environments. Recall that a natural disaster such as flooding may "empty" a habitat. Populations will expand quickly as they capitalize on the unlimited resources. It is under this period of time that we will see rmax (the intrinsic rate of increase) at its maximum. However, the exponential growth model is unrealistic under most natural conditions because of its starting assumptions. Most populations are limited by resources such as food, shelter, water etc. The carrying capacity of any population is defined as the maximum number of individuals that can be supported over time in a given habitat. We symbolize the carrying capacity as K. The carrying capacity (K) for each population is determined by its most limited resource. What limits a natural population will vary from species to species, and between environments. Light availability may be the limiting resource for a plant in a cold climate, while water may be the limiting resource for that same species in a warmer, dryer climate. Thus K is environmentally determined. An increase in the number of individuals, or a decrease in the birth rate will both lead to a decrease in the intrinsic rate of growth, and a decrease in the populations growth.

3. 9 Experimental Population Growth

l. logistic population growth- theoretical

To make a more useful model, we will now change one of our starting assumptions. We have seen that unlimited resources are rare in nature and that population growth is affected by the amount of available resources. In logistic growth equations we need to allow for a change in r, the intrinsic rate of growth as we get changes in N, the populations size. This will allow us to incorporate the idea that as the population size grows, (and reaches its carrying capacity (K)) resources will be limited and the rate of increase (how fast the population can grow) will also be limited. Thus as our population size approaches the K, we will get a decrease in the intrinsic rate of growth:

dN/dt = rmax N (K-N/K)

This will now give us a more realistic model of change in population size over time. Instead of giving us a J-shaped curve as we saw in the exponential model, our new logistic growth equation gives rise to a sigmoidal shaped curve (see page 1162, figure 54.11 in Campbell). We can see that the rate of intrinsic increase is fastest when there are few individuals competing for lots of resources (at the start of the population growth). This resembles the beginning of the exponential growth model where resources were unlimited.

ll. logistic growth and real populations

We have now included more realistic assumptions into the population growth models. How well do the modified models mimic population growth among species in the real world? Data from a variety of species suggests that the annual plants and small animals, such as beetles, crustaceans and microorganisms fit as S- shaped growth curve fairly. Exceptions occur when the starting population is too small. A small starting population may not have enough genetic variation to keep the population viable, or enough individuals to meet the demands of social breeding and cohabitation. Growth along the S- shaped curve may not occur smoothly if there are lag times in the appearance of resources and the start of the breeding cycle.

lll. r and K selected traits

The different life history "strategies" used by species are sometimes referred to as "r-selected" and K-selected" strategies. Table 52.3 illustrates how groups of behaviors often cluster together, depending upon whether the species is opportunistic and lives in an uncrowded environment. Species living in a simple, spacious environment can grow rapidly with little competition. Thus traits which favor early reproduction with lots of young are more likely to arise. A perfect example would be an annual plant. In contrast, species living in complex, crowded environments face severe competition. Young must receive large amounts of parental investment to be successful in this crowded market. Thus traits which favor delayed reproduction and heavy investment in a few offspring are strongly favored.

Read Concept 52.5"Population Limiting Factors" on pp. 1148-1152 

3.10 Population Limiting Factors

l. density dependent factors

It is clear that the environment can have a potent affect upon a species ability to survive and successfully reproduce. Let's examine these factors in more detail. There are two basic categories of population limiting factors. Density dependent factors are those that intensify as the size of the population increases. This is due to the fact that individuals are competing for limited resources. This limiting resource, whether it is food, water, shelter, etc. sets "K" the carrying capacity. Density can also increase the mortality rate when overcrowding leads to toxic buildup, and physiological stress. A good example would be what happens in your garden when you have planted your plants too close. At first the small plants have plenty of sunlight, room and nutrients to grow. As the nutrients are used up and the plants begin to crowd one another, their roots compete for water and the leaves may compete for sunlight. Predation rates can also change with density. When a prey species becomes common, predators often switch and focus on the most common species. Thus a grasshopper that had been eating other things now switches over to your prized snapdragons. No matter what the cause, density dependent factors are ones that have an increased percentage of mortality as the population size increases.

ll. Density independent factors

Density independent factors are different. Here, natural disasters such as storms and droughts affect the population equally. A bad storm may kill 80% of a bird species whether or not there are 50 or 1000 individuals. Most organisms experience both types of mortality over the long term.

Finally, while both exponential and logistic models predict a smooth change in the intrinsic rate of increase, populations in nature often fluctuate. Some population fluctuations are so regular that they are now perceived as cyclical population cycles. The life cycle of the cicada, which complete a life cycle every 13 or 17 years, is the best known example. For predatory species that heavily depend on one prey item, the size of the prey population has dramatic effects on the size of the predator population. Data collected over the past 100 years indicates that snowshoe hares and lynx have regulate boom and bust population cycles that take place every 10 years.

Read Concept 52.6"Human Population Growth" on pp. 1152-1156

3.12 Human Population Growth

l. current growth rate as exponential

It is important that to consider human growth patterns when studying the population growth and decline of other species. While the human population remained relatively stable and small for most of the history, explosive growth in the last few hundred years has had an affect on every other species on the planet. Humans out compete most species for almost every resource- food, water, land, etc. And this means there are fewer resources available for other organisms. Thus their carrying capacity is dramatically affected our presence. In addition, as human populations increase, the amount of toxic build up, whether through pesticide run off, cargo ship oil spills, or acid rain, not only poisons humans, but other animals as well. Ironically, there are some species that benefit by the growth of the human population. Edificarians, species such as house sparrows and cockroaches use human shelters for homes are one example. Some species such as bacteria and amoebae's can use humans as an intermediate host in their life cycle and others, such as lice, thrive in humans. Thus no matter what the species, humans have an impact of their ability to survive and reproduce.

Ironically, the exponential growth model ideally fits the explosive growth of humans. This is a unique case among larger animals and is most likely due to our capacity to simply out compete other organisms. As Fig. 52.20 indicates, population growth remained low (500 million) until the mid 17th century and they began to double at a phenomenal rate. The world population is now estimated at 6 billion and will rise to 8 billion in another 17 years.

The two most important factors that have lead to this explosive growth are a decrease in the mortality rate- primarily among infants and children and a relatively stable birth rate in developing countries. Age structure also plays an important role in determining which countries are growing the fastest. While industrialized countries such as Sweden have a stable age structure and a stable, modest birth rate, Mexico has a predominately young population with a very high birth rate. Thus populations of humans in Mexico are growing at a rate that far exceeds the population in Sweden.

ll. limits to human growth rates

An essential question remains. What is the carrying capacity for the human race? Some population estimates that the human population will double to 12 billion by the year 2050. Others suggest that the human population will peak at about 10.6 billion and then begin a slight decline as it stabilizes. What ever the number is, humans will reach a carrying capacity, and it is still unclear what the most limiting factor will be. Many people have predicted that food resources will limit population growth. Already we see that a disturbance to food production due to floods in India or Columbia in the past few years have devastating consequences. In the last 50 years we have seen the world change into a global economy as food resources are shipped to areas plagued with disaster. But as we run out of food will we continue to share our resources? It is also unclear whether changes in dietary habitat, such as consuming less meat so that more food can be produced, or genetically altering plants to increase food production can raise the overall amounts of food available.

It may be that food is not the limiting resource at all. Instead clean, drinkable water may be most in peril. Already most streams in the United States are considered unsafe to drink out of due to contamination from animal waste, sewage and fertilizers. The same holds true in other parts of the world. As clean water becomes unavailable, mortality due to dysentery and other water born diseases may put human growth in check.

No matter what the ultimate cause, humans in some parts of the world are already reaching their carrying capacity and we as a global species will reach this point in the next two generations. Not only does it affect humans but the other species who share this planet. Humans will have to make conscious decisions about the state of population growth through social change and individual reproductive decisions, or endure the inevitable consequences.

UNIT 3: Study Terms:

 populations, density, dispersion, clumped dispersion, uniform dispersion, random dispersion, census, density estimates, mark-recapture, line-transect method, spot-mapping, grain, course grain, fine grain, demography, age structure, sex ratio, fecundity, death rate, generation time, life table, cohort, survivorship curve, Type I curve, Type II curve, Type III curve, life histories, semelparity, iteroparity, age of first reproduction. exponential growth, dN/dt, B (per capita birth rate), D (per capita death rate), r (per capita growth rate), rmax(Intrinsic Rate of Natural Increase), Logistic population growth, K (carrying capacity), r-selected species (opportunistic populations), K-selected species (equilibrium populations), density dependent factors, density independent factors, cyclic population growth, lag effect, age pyramids and population age structure, age of first breeding.

Tables: 52.1, 52.3, 52.3

Figures 52.3,52.5, 52.7, 52.9 52.10, 52.11, 52.12, 52.13 52.14, 52.15 and 52.18-52.27

Short Answer and Study Questions

1. List and explain the various types of dispersion patterns found in populations of organisms. Explain what factors might cause these types of distribution patterns.
2. Compare censuses and density estimates in terms of accuracy and difficult of accomplishing.
3. Explain how the mark-recapture system of estimating population size works. Show the formula used to calculate potential population size.
4. Explain the concept of ecological grain. Give examples of what kinds of environmental factors would be fine or course grain factors for a large animal like a Bison.
5. Draw a graph, which shows the three types of Survivorship curves. Label each axis and give one example of an animal that shows each type of survivorship.
6. Create a simple life table in which no individual lives beyond the age of 4 years and only half of each cohort survives into the next year.
7. Describe how resource limitation, survival ability and fecundity all interact to influence how many young an animal will have in one year, versus in its entire lifespan.
8. Contrast semelparity and iteroparity. Under what conditions would you expect organisms to use each reproductive pattern?
9. Graph the relationship between population size and number of generations for a species like a bacterium that grows exponentially but with none overlapping generations. In your plot (graph) be sure to label each axis, and show clearly how many cells exist at the end of each generation over 4 generations of growth.
10. Explain the meaning of all of the components of the equation of exponential population growth. As a special case, explain the circumstances under which growth will be most rapid.
11. Graph the relationship between population size and number of generations for a species with overlapping generations in which r=1.0. Label each axis, and draw the relationship so that it is clear how many individuals exist at the end of each generation. Under what circumstances would you expect to find this kind of populations growth?
12. Graph the relationship between generation time and rmax for bacteria, protists, insects and vertebrates.
13. Graph the relationship between population size and number of generations for a population that shows logistic growth. In your graph, show where 'r' will be maximal, and where 'r' will be minimal. Also, show the location of the carrying capacity, and show accurately how growth rate changes as population size approaches the carrying capacity.
14. Explain the meaning of each term in the equation for logistic population growth. Show what happens to this equation when (a) population size approaches the carrying capacity, and (b) population size is close to zero.
15. Explain two ways in which real populations deviate from logistic growth curves.
16. Give four characteristics of r-selected and four characteristics of K-selected populations. Under what conditions should each kind of population do best.
17. Describe the two categories of population limiting factors. Give at least two examples of each kind.
18. Give two possible explanations for cyclic population growth such as that documented in the 10-year snowshoe hare Canadian lynx cycles.
19. Describe the characteristics of rapidly growing and slowly growing human populations.



this page last updated: November 2006
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