Which Of The Following Could Describe A Population That Is Decreasing In Size?
Affiliate 19: Population and Customs Ecology
Population Growth and Regulation
Learning Objectives
By the end of this section, y'all will exist able to:
- Explain the characteristics of and differences between exponential and logistic growth patterns
- Give examples of exponential and logistic growth in natural populations
- Give examples of how the carrying capacity of a habitat may change
- Compare and dissimilarity density-dependent growth regulation and density-independent growth regulation giving examples
Population ecologists brand use of a multifariousness of methods to model population dynamics. An accurate model should be able to describe the changes occurring in a population and predict time to come changes.
Population Growth
The 2 simplest models of population growth use deterministic equations (equations that practice not account for random events) to describe the charge per unit of change in the size of a population over time. The first of these models, exponential growth, describes theoretical populations that increase in numbers without whatsoever limits to their growth. The second model, logistic growth, introduces limits to reproductive growth that become more than intense as the population size increases. Neither model adequately describes natural populations, but they provide points of comparing.
Exponential Growth
Charles Darwin, in developing his theory of natural selection, was influenced past the English clergyman Thomas Malthus. Malthus published his book in 1798 stating that populations with abundant natural resources abound very rapidly; however, they limit further growth past depleting their resources. The early pattern of accelerating population size is chosen exponential growth.
The best example of exponential growth in organisms is seen in leaner. Bacteria are prokaryotes that reproduce largely by binary fission. This partition takes well-nigh an hr for many bacterial species. If 1000 leaner are placed in a large flask with an abundant supply of nutrients (and so the nutrients volition non become quickly depleted), the number of bacteria volition accept doubled from 1000 to 2000 after just an 60 minutes. In another hour, each of the 2000 bacteria will divide, producing 4000 bacteria. After the third hour, in that location should be 8000 bacteria in the flask. The important concept of exponential growth is that the growth rate—the number of organisms added in each reproductive generation—is itself increasing; that is, the population size is increasing at a greater and greater rate. Later 24 of these cycles, the population would have increased from 1000 to more sixteen billion leaner. When the population size, Due north, is plotted over time, a J-shaped growth bend is produced ([Figure 1]a).
The leaner-in-a-flask example is not truly representative of the real world where resources are ordinarily limited. Notwithstanding, when a species is introduced into a new habitat that it finds suitable, it may show exponential growth for a while. In the case of the bacteria in the flask, some bacteria will die during the experiment and thus not reproduce; therefore, the growth charge per unit is lowered from a maximal rate in which there is no mortality. The growth rate of a population is largely adamant by subtracting the decease rate, D, (number organisms that die during an interval) from the nativity rate, B, (number organisms that are born during an interval). The growth rate tin can be expressed in a simple equation that combines the birth and death rates into a single factor: r. This is shown in the following formula:
[latex]\text{Population growth }=\text{ }rN[/latex]
The value of r can be positive, significant the population is increasing in size (the rate of alter is positive); or negative, meaning the population is decreasing in size; or cypher, in which instance the population size is unchanging, a status known as naught population growth.
Logistic Growth
Extended exponential growth is possible merely when infinite natural resource are available; this is not the case in the real world. Charles Darwin recognized this fact in his description of the "struggle for existence," which states that individuals volition compete (with members of their own or other species) for limited resources. The successful ones are more likely to survive and pass on the traits that made them successful to the next generation at a greater rate (natural selection). To model the reality of limited resource, population ecologists developed the logistic growth model.
Carrying Chapters and the Logistic Model
In the existent world, with its limited resource, exponential growth cannot continue indefinitely. Exponential growth may occur in environments where there are few individuals and plentiful resources, but when the number of individuals gets big enough, resources will be depleted and the growth rate will slow down. Eventually, the growth rate will plateau or level off ([Figure 1]b). This population size, which is determined past the maximum population size that a particular environment can sustain, is called the carrying capacity, or K. In real populations, a growing population oftentimes overshoots its carrying capacity, and the death rate increases beyond the birth rate causing the population size to pass up dorsum to the carrying capacity or below it. Virtually populations usually fluctuate around the carrying capacity in an undulating fashion rather than existing right at it.
The formula used to calculate logistic growth adds the carrying chapters as a moderating strength in the growth rate. The expression "K – N" is equal to the number of individuals that may exist added to a population at a given time, and "Grand – N" divided by "K" is the fraction of the carrying capacity available for further growth. Thus, the exponential growth model is restricted by this cistron to generate the logistic growth equation:
[latex]\text{Population growth }=\text{ }rN\text{ }\left[\frac{Thou-N}{K}\right][/latex]
Find that when N is well-nigh cypher the quantity in brackets is well-nigh equal to 1 (or K/K) and growth is close to exponential. When the population size is equal to the conveying chapters, or Due north = K, the quantity in brackets is equal to zero and growth is equal to zero. A graph of this equation (logistic growth) yields the Southward-shaped bend ([Figure 1]b). It is a more realistic model of population growth than exponential growth. There are three unlike sections to an S-shaped curve. Initially, growth is exponential considering there are few individuals and ample resources available. Then, as resource begin to go limited, the growth rate decreases. Finally, the growth rate levels off at the carrying capacity of the environment, with picayune change in population number over time.
Role of Intraspecific Competition
The logistic model assumes that every individual within a population will have equal access to resource and, thus, an equal gamble for survival. For plants, the amount of h2o, sunlight, nutrients, and space to grow are the important resources, whereas in animals, important resources include food, water, shelter, nesting infinite, and mates.
In the real globe, phenotypic variation amid individuals within a population means that some individuals volition be ameliorate adapted to their surround than others. The resulting contest for resources among population members of the aforementioned species is termed intraspecific competition. Intraspecific competition may not affect populations that are well below their carrying capacity, as resource are plentiful and all individuals tin obtain what they need. However, as population size increases, this competition intensifies. In addition, the aggregating of waste matter products can reduce carrying capacity in an environment.
Examples of Logistic Growth
Yeast, a microscopic mucus used to make bread and alcoholic beverages, exhibits the classical S-shaped curve when grown in a test tube ([Figure two]a). Its growth levels off as the population depletes the nutrients that are necessary for its growth. In the existent world, however, there are variations to this idealized curve. Examples in wild populations include sheep and harbor seals ([Figure two]b). In both examples, the population size exceeds the carrying chapters for brusque periods of fourth dimension and so falls below the carrying capacity afterwards. This fluctuation in population size continues to occur as the population oscillates around its conveying capacity. Still, even with this oscillation, the logistic model is confirmed.
Art Connectedness
If the major food source of seals declines due to pollution or overfishing, which of the post-obit would probable occur?
- The carrying capacity of seals would decrease, as would the seal population.
- The carrying capacity of seals would decrease, but the seal population would remain the aforementioned.
- The number of seal deaths would increase, but the number of births would also increase, so the population size would remain the same.
- The carrying capacity of seals would remain the aforementioned, but the population of seals would decrease.
[reveal-answer q="640864″]Bear witness Respond[/reveal-answer]
[hidden-respond a="640864″]A: The conveying capacity of seals would decrease, as would the seal population.[/hidden-answer]
Population Dynamics and Regulation
The logistic model of population growth, while valid in many natural populations and a useful model, is a simplification of real-globe population dynamics. Implicit in the model is that the conveying capacity of the environment does not change, which is non the instance. The carrying chapters varies annually. For instance, some summers are hot and dry whereas others are cold and wet; in many areas, the conveying chapters during the winter is much lower than it is during the summer. Besides, natural events such as earthquakes, volcanoes, and fires can change an surroundings and hence its carrying chapters. Additionally, populations do non usually be in isolation. They share the surroundings with other species, competing with them for the same resource (interspecific contest). These factors are as well important to agreement how a specific population volition grow.
Population growth is regulated in a diverseness of ways. These are grouped into density-dependent factors, in which the density of the population affects growth rate and mortality, and density-independent factors, which cause mortality in a population regardless of population density. Wildlife biologists, in detail, want to empathize both types because this helps them manage populations and prevent extinction or overpopulation.
Density-dependent Regulation
Nearly density-dependent factors are biological in nature and include predation, inter- and intraspecific competition, and parasites. Usually, the denser a population is, the greater its mortality rate. For instance, during intra- and interspecific contest, the reproductive rates of the species volition commonly be lower, reducing their populations' rate of growth. In add-on, depression prey density increases the mortality of its predator because it has more difficulty locating its nutrient source. Also, when the population is denser, diseases spread more than speedily among the members of the population, which impact the mortality rate.
Density dependent regulation was studied in a natural experiment with wild donkey populations on two sites in Australia. i On 1 site the population was reduced by a population command program; the population on the other site received no interference. The high-density plot was twice as dumbo equally the low-density plot. From 1986 to 1987 the high-density plot saw no change in donkey density, while the low-density plot saw an increase in donkey density. The difference in the growth rates of the 2 populations was caused past bloodshed, not by a difference in birth rates. The researchers found that numbers of offspring birthed by each mother was unaffected by density. Growth rates in the ii populations were different generally because of juvenile mortality caused by the female parent'southward malnutrition due to scarce high-quality food in the dumbo population. [Effigy 3] shows the difference in age-specific mortalities in the two populations.
Density-independent Regulation and Interaction with Density-dependent Factors
Many factors that are typically concrete in nature cause bloodshed of a population regardless of its density. These factors include conditions, natural disasters, and pollution. An private deer will be killed in a forest burn regardless of how many deer happen to be in that area. Its chances of survival are the same whether the population density is high or low. The same holds true for cold winter conditions.
In real-life situations, population regulation is very complicated and density-dependent and independent factors can interact. A dense population that suffers mortality from a density-contained cause volition exist able to recover differently than a sparse population. For instance, a population of deer affected by a harsh winter will recover faster if in that location are more deer remaining to reproduce.
Evolution in Action
Why Did the Woolly Mammoth Go Extinct?
Woolly mammoths began to become extinct near 10,000 years agone, soon after paleontologists believe humans able to chase them began to colonize North America and northern Eurasia ([Figure 4]). A mammoth population survived on Wrangel Island, in the East Siberian Sea, and was isolated from human contact until as recently as 1700 BC. We know a lot about these animals from carcasses constitute frozen in the ice of Siberia and other northern regions.
It is usually thought that climate change and human hunting led to their extinction. A 2008 study estimated that climate change reduced the mammoth's range from 3,000,000 foursquare miles 42,000 years ago to 310,000 foursquare miles six,000 years ago. two Through archaeological prove of kill sites, it is also well documented that humans hunted these animals. A 2012 study concluded that no single factor was exclusively responsible for the extinction of these magnificent creatures. 3 In addition to climate change and reduction of habitat, scientists demonstrated another important factor in the mammoth'southward extinction was the migration of human hunters across the Bering Strait to Due north America during the last ice age 20,000 years ago.
The maintenance of stable populations was and is very complex, with many interacting factors determining the consequence. Information technology is important to remember that humans are too part of nature. In one case we contributed to a species' decline using primitive hunting technology only.
Demographic-Based Population Models
Population ecologists have hypothesized that suites of characteristics may evolve in species that atomic number 82 to particular adaptations to their environments. These adaptations bear on the kind of population growth their species experience. Life history characteristics such every bit nascence rates, age at first reproduction, the numbers of offspring, and even expiry rates evolve but like anatomy or beliefs, leading to adaptations that affect population growth. Population ecologists have described a continuum of life-history "strategies" with Thou-selected species on one terminate and r-selected species on the other. K-selected species are adapted to stable, predictable environments. Populations of K-selected species tend to be close to their carrying capacity. These species tend to have larger, but fewer, offspring and contribute big amounts of resources to each offspring. Elephants would be an instance of a K-selected species. r-selected species are adapted to unstable and unpredictable environments. They have big numbers of pocket-size offspring. Animals that are r-selected do not provide a lot of resources or parental care to offspring, and the offspring are relatively self-sufficient at birth. Examples of r-selected species are marine invertebrates such as jellyfish and plants such equally the dandelion. The two extreme strategies are at two ends of a continuum on which real species life histories volition exist. In add-on, life history strategies do not need to evolve as suites, but can evolve independently of each other, so each species may have some characteristics that trend toward one extreme or the other.
Section Summary
Populations with unlimited resources grow exponentially—with an accelerating growth rate. When resources become limiting, populations follow a logistic growth bend in which population size will level off at the carrying capacity.
Populations are regulated by a variety of density-dependent and density-independent factors. Life-history characteristics, such as age at first reproduction or numbers of offspring, are characteristics that evolve in populations just as anatomy or behavior can evolve over time. The model of r– and K-selection suggests that characters, and possibly suites of characters, may evolve adaptations to population stability near the carrying chapters (K-option) or rapid population growth and collapse (r-selection). Species will exhibit adaptations somewhere on a continuum betwixt these two extremes.
Multiple Choice
Species with limited resources usually exhibit a(n) ________ growth curve.
- logistic
- logical
- experimental
- exponential
[reveal-respond q="432132″]Show Reply[/reveal-answer]
[hidden-answer a="432132″]1[/hidden-answer]
The maximum growth charge per unit feature of a species is called its ________.
- limit
- conveying capacity
- biotic potential
- exponential growth pattern
[reveal-answer q="827518″]Show Answer[/reveal-answer]
[subconscious-respond a="827518″]3[/hidden-respond]
The population size of a species capable of being supported past the environment is called its ________.
- limit
- carrying chapters
- biotic potential
- logistic growth blueprint
[reveal-answer q="671162″]Prove Respond[/reveal-answer]
[subconscious-answer a="671162″]ii[/subconscious-reply]
Species that have many offspring at 1 time are unremarkably:
- r-selected
- K-selected
- both r- and Thou-selected
- not selected
[reveal-answer q="300275″]Show Answer[/reveal-answer]
[hidden-respond a="300275″]ane[/subconscious-answer]
A forest fire is an example of ________ regulation.
- density-dependent
- density-independent
- r-selected
- M-selected
[reveal-answer q="966755″]Prove Answer[/reveal-answer]
[hidden-answer a="966755″]2[/subconscious-answer]
Free Response
Draw the growth at diverse parts of the S-shaped curve of logistic growth.
In the first part of the curve, when few individuals of the species are present and resources are plentiful, growth is exponential, similar to a J-shaped curve. Later, growth slows due to the species using up resources. Finally, the population levels off at the carrying capacity of the surround, and it is relatively stable over time.
Give an case of how density-dependent and density-independent factors might interact.
If a natural disaster such equally a burn down happened in the wintertime, when populations are depression, it would have a greater issue on the overall population and its recovery than if the same disaster occurred during the summer, when population levels are high.
Footnotes
- 1 David Choquenot, "Density-Dependent Growth, Body Condition, and Demography in Feral Donkeys: Testing the Food Hypothesis," Ecology 72, no. 3 (June 1991):805–813.
- ii David Nogués-Bravo et al., "Climate Change, Humans, and the Extinction of the Woolly Mammoth." PLoS Biol six (April 2008): e79, doi:10.1371/periodical.pbio.0060079.
- 3 Chiliad.M. MacDonald et al., "Blueprint of Extinction of the Woolly Mammoth in Beringia." Nature Communications 3, no. 893 (June 2012), doi:10.1038/ncomms1881.
Glossary
- birth rate
- the number of births inside a population at a specific indicate in time
- carrying chapters
- the maximum number of individuals of a population that tin be supported by the limited resources of a habitat
- death rate
- the number of deaths within a population at a specific point in time
- density-dependent regulation
- the regulation of population in which birth and death rates are dependent on population size
- density-independent regulation
- the regulation of population in which the death charge per unit is independent of the population size
- exponential growth
- an accelerating growth design seen in populations where resources are not limiting
- intraspecific competition
- the competition among members of the same species
- J-shaped growth curve
- the shape of an exponential growth curve
- Thousand-selected species
- a species suited to stable environments that produce a few, relatively large offspring and provide parental care
- logistic growth
- the leveling off of exponential growth due to limiting resources
- r-selected species
- a species suited to irresolute environments that produce many offspring and provide lilliputian or no parental intendance
- South-shaped growth curve
- the shape of a logistic growth bend
- nothing population growth
- the steady population size where nascence rates and death rates are equal
Which Of The Following Could Describe A Population That Is Decreasing In Size?,
Source: https://opentextbc.ca/conceptsofbiologyopenstax/chapter/population-growth-and-regulation/
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