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Ch. 25 - Phylogenies and the History of Life

Chapter 24, Problem 14

The vast majority of animals that ever existed are now extinct, but Tereza Jezkova and John Wiens wondered which variables were most important in driving the diversification of species that exist today. Why are there so many species in some phyla, such as Cnidaria (see photo), but so few in others, such as Ctenophora? A sample of Jekova and Wiens' results is shown here. The R2 value represents the strength of the correlation (where 0.00 is lowest and 1.00 is highest). The P value represents the statistical significance. Which five traits look most important?

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Hi everyone. Let's look at our next problem. It says the strength of correlation R squared In which 0.00 is the lowest and 1.0 is the highest measures the proportion of variation in the dependent variable that can be attributed to the independent variable. Once the strength of the correlation are identified, for example, your size versus temperature. It must be subjected to analysis for statistical significance p value to identify that the correlation is not attributable by chance. Hence the importance of a specific trait for the organism's adaptation to existing environmental conditions. Suppose we determine the strength of correlation R. Squared and the traits corresponding significant significance. P. Value which of the following traits is considered the most important. So this is a lot of words and we have a chart of different characteristics along with an R. Squared value and a piece value. But kind of what we want to remember here is the higher the R squared value, the greater the correlation of the dependent value are variable. Excuse me. And then the lower the P value the greater the statistical significance. This is cool. That's because the P value represents the probability that your result is due to random chance. So you want that value to be low to show that you have a low probability that your result is just due to chance. And usually the cut off here is you want to see a p value That is less than 0.05 to prove statistical significance. So what we're looking for is a higher R squared and lower p value. So let's look at these different characteristics. We see presence of a skeleton have separate sexes, bilateral symmetry. Have mobile lifestyle and terrestrial life. Well, we'll go ahead and highlight the highest R squared value we see here Which is 0.78 on terrestrial life. And let's look at the high highest P value we see excuse me the lowest P value we see which is presence of a skeleton. Well they're not the same thing. So let's look first at terrestrial life which is the highest correlation. But it's P value is greater than 0.5. And when the P value is greater than 0.5 We would say it's not statistically significant. Therefore we can't say that that variation isn't due to random chance. So we're going to have to cross off terrestrial life just because we can't say that that's not just random chance showing that correlation. So let's look here and we'll find what's the next greatest R. Squared. Well that's 0.61 for presence of a skeleton. So now for presence of a skeleton we have um high R. Squared value. And when we look at our other values it's quite a bit higher. And our P value here is 0.3. So very low so that is definitely statistically significant. So we can say that choice the presence of a skeleton would be the most important trait for the organism's adaptation to the existing environmental conditions, since it shows the highest correlation and the lowest p value indicating statistical significance. See you in the next video.
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Textbook Question

The vast majority of animals that ever existed are now extinct, but Tereza Jezkova and John Wiens wondered which variables were most important in driving the diversification of species that exist today. Why are there so many species in some phyla, such as Cnidaria (see photo), but so few in others, such as Ctenophora? Draw a horizontal axis to represent the number of species within phyla using a logarithmic scale (1, 10, 100, 1000 species, etc.). Then use Table 30.1 to map seven representative phyla from small to large at intervals of about an order of magnitude on this scale.

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Textbook Question

The vast majority of animals that ever existed are now extinct, but Tereza Jezkova and John Wiens wondered which variables were most important in driving the diversification of species that exist today. Why are there so many species in some phyla, such as Cnidaria (see photo), but so few in others, such as Ctenophora? Based on your reading of this chapter, propose at least five traits that you think might have been most important in triggering diversification within phyla (examples: origin of hearing, origin of internal fertilization).

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Textbook Question

The vast majority of animals that ever existed are now extinct, but Tereza Jezkova and John Wiens wondered which variables were most important in driving the diversification of species that exist today. Why are there so many species in some phyla, such as Cnidaria (see photo), but so few in others, such as Ctenophora? Jezkova and Wiens used a type of graph called a linear regression to find correlations between variables such as the proportion of species per phylum with legs (on the y-axis) and the diversification rate per phylum (on the x-axis). Sketch a graph to show what a strong positive correlation between these two variables would look like and what the absence of a correlation would look like.

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Textbook Question

Which traits do not correlate strongly with diversification rate within phyla, but are likely to have been important in the original diversification of animal phyla during the Cambrian? Select True or False for each trait. T/F presence of a head T/F mobile lifestyle T/F terrestrial lifestyle T/F bilateral symmetry

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Textbook Question

The vast majority of animals that ever existed are now extinct, but Tereza Jezkova and John Wiens wondered which variables were most important in driving the diversification of species that exist today. Why are there so many species in some phyla, such as Cnidaria (see photo), but so few in others, such as Ctenophora? The researchers know that correlation does not equal causation. However, can the absence of a correlation enable you to reject a hypothesis of causation? How would the R2 values be different in a scenario where a single trait was important to diversification in many phyla versus a scenario where different traits were important to diversification in different phyla?

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