Ecology

Geology/Geography/Oceanography/Atmospheric Sciences

Quiz 10 :

Population Dynamics

Quiz 10 :

Population Dynamics

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Population ecologists have assumed that populations of species with very high reproductive rates, those with offspring sometimes numbering in the millions per female, must have a type III survivorship curve even though very few survivorship data exist for such species. Why is this a reasonable assumption? In general, what is the expected relationship between reproductive rate and patterns of survival?
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The pattern of the survival can be understood from the survivorship curve. The survivorship curves are of three types namely type I survivorship curve, type II survivorship curve and type III survivorship curve.
The type III survivorship curve shows high mortality rate of the offspring. The mortality rate decreases later in life. The species producing offspring in numbers of millions per female have been assumed to have type III survivorship curve even though the data on survivorship curve of such species are few.
The assumption is reasonable because of following reasons:-
• The species have been confirmed to produce a huge number of offspring by noting millions of seeds produced by some plant species and millions of eggs produced by the species of fish.
• If all or most of the offspring would have survived that would have led to tremendous number or huge populations of these species.
• In nature, the populations of such species are found to be comparatively small.This confirms the assumption that irrespective of production of huge number of offspring, majority die in the juvenile state and only few mature to the adult age.
The reproductive rate and mortality rate together affect the pattern of survival. For example, high reproductive rate along with high mortality of the offspring is typical of the pattern of survival shown by the type III survivorship curve.
A low reproductive rate with low mortality rate of offspring is typical of type I survivorship curve. A constant mortality rate may lead to type II survivorship curve.
Thus, the pattern of survival as shown by the survivorship curves varies with the reproductive rate.

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Compare cohort and static life tables. What are the main assumptions of each? In what situations or for what organisms would it be practical to use either?
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Cohort and static life tables are used to estimate patterns of survival within a population. A group born at the same time is called cohort. The life table made is from the data collected from a large number of people born at the same time and maintains a record of them from birth to death is known as cohort life table.
Another way to estimate patterns of survival in wild population is to record the age at death of a large number of individuals. This method produces a static life table, which needs to estimate the age at which individual dies. The static life table involves a snapshot of survival within a population during a short interval of time.
The cohort is used to study a group of plant seedlings that germinated at the same time or all the lambs born into a population of mountain sheep in a particular year. While, the static life table differs from cohort approach as the sample born at different times is considered. For instance, mountain sheep can be aged by counting the growth rings of their horns.

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Of the three survivorship curves, type III has been the least documented by empirical data. Why is that? What makes this pattern of survivorship difficult to study?
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The type III survivorship indicates a pattern of survival in which there is high rate of mortality of the offspring in the juvenile stage followed by low mortality rate in the later stages.
The type III survivorship is shown by some species of the marine fish and the plants. The offspring produced by these species may range in millions. However, due to less parental care the offspring show high rate of mortality. Hence, less than hundred juveniles survive till the adult stage.
Type III survivorship curve has been least supported by empirical data due to following reasons:
• The species showing type III survivorship curve produce offspring in millions. Keeping a record of such a huge number of offspring is difficult.
• In case of plants, the number of seeds produced that may range in millions may be difficult to determine.
• The juveniles are usually small in size. Hence, the recognition and further observations may be difficult.

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Concept 10.5 in chapter 10 says that we can use the information in life tables and fecundity schedules to estimate some characteristics of populations ( R 0, T , r ). Why does Concept 10.5 use the word "estimate" rather than "calculate"? In putting together your answer, think about the population of P. drummondii studied by Leverich and Levin (1979).We calculated R 0 for this population by summing the lx mx column. When we did, the number we got was R 0 = 2.4177. Assuming that Leverich and Levin accurately counted seeds and surviving plants, is 2.4177 an estimate of the average reproductive rate of the 996 individual P. drummondii in their study? Right, 2.4177 is not an estimate; it's the actual average number of seeds produced by these 996 individuals. So, what's this estimate business about? If Leverich and Levin had studied a second (or third, fourth, etc.) group of 996 individuals in their P. drummondii population, do you think it's likely that they would have gotten an R 0 exactly equal to 2.4177?
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Draw hypothetical age structures for growing, declining, and stable populations. Explain how the age structure of a population with highly episodic reproduction might be misinterpreted as indicating population decline. How might population ecologists avoid such misinterpretations?
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What values of R 0 indicate that a population is growing, stable, or declining? What values of r indicate a growing, stable, or declining population?
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From a life table and a fecundity schedule, you can estimate the geometric rate of increase, ? , the average reproductive rate, R 0 , the generation time, T , and the per capita rate of increase, r. That is a lot of information about a population. What minimum information do you need to construct a life table and fecundity schedule?
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Outline Müller's (1954, 1974) colonization cycle. If you were studying the colonization cycle of the freshwater snail N. latissima, how would you follow colonization waves upstream? How would you verify that these colonization waves gain individuals from local populations and also contribute individuals to those same local populations?
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In our discussions of the research of Baird, Soares, and their colleagues (Baird, Barber, Calow 1990, Soares, Baird, Calow 1992), we focused on the effects of a residue of an organic pesticide, dichloroaniline (DCA), on the per capita rate of increase, r , of D. magna. These researchers also found that the r of D. magna responds significantly to a variety of inorganic pollutants. What do these results indicate about the usefulness of r as an indicator of the ecological impact of potential pollutants?
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S. Holling (1959) observed predator numerical responses to changes in prey density. He attributed the numerical responses to changes in the reproductive rates of the predators. Discuss a hypothetical example of reproductive-rate numerical response by a population of predators in terms of changes in fecundity schedules and life tables. Include the terms R 0 , T , and r in your discussion.
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When using a significance level of 0.05, how often will we reject hypotheses that are actually correct? For instance, how often will we reject the hypothesis that the individuals in a study population are randomly distributed when, in fact, they really are randomly distributed?
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