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In pea plants, purple flower color, C, is dominant to white flower color, c. The table shows the frequencies of the dominant and recessive alleles in three generations of peas in a garden.



\begin{table}

\captionsetup{labelformat=empty}

\caption{Allele Frequency for Flower Color in Peas}


Generation		$p$$q$

1		0.60.4

2		0.70.3

3		0.80.2




\end{table}



Which scientific question might these results cause a scientist to ask?


AWhich population most likely experienced a genetic mutation?
BWhy do some pea plants have purple flowers and others have white flowers?
CWould the frequency of alleles change if the pollinators in the area all died?
DIs there another way to calculate the frequencies of the alleles in this population?

Verified Answer :

  • The data tracks the allele frequency trend of a pea plant population over three generations, showing a steady increase in the dominant allele \(p\) and a decrease in the recessive allele \(q\).
  • Scientific inquiry aims to uncover the causes behind such observed evolutionary trends.
  • The question 'Would the frequency of alleles change if the pollinators in the area all died?' is the only option that directly relates the observed shift in frequencies to a testable mechanism of change.
  • The most appropriate scientific question is: \(\boxed{\text{Would the frequency of alleles change if the pollinators in the area all died?}}\)

Explanation

  1. Data and trend analysis

The data provided displays the frequencies of dominant (\(p\)) and recessive (\(q\)) alleles for a single population of pea plants over three consecutive generations. Observing the table, we see:

  • Generation 1: \(p=0.6\), \(q=0.4\)
  • Generation 2: \(p=0.7\), \(q=0.3\)
  • Generation 3: \(p=0.8\), \(q=0.2\)

The data shows a clear, consistent trend: the frequency of the dominant allele \(p\) is increasing by \(0.1\) in each generation, while the frequency of the recessive allele \(q\) is decreasing by \(0.1\). In evolutionary biology, such a shift in allele frequencies over time indicates that the population is evolving, meaning it is not in Hardy-Weinberg equilibrium.

  1. Evaluating scientific questions based on observed data

To determine the most appropriate scientific question, we evaluate the provided options:

  1. 'Which population most likely experienced a genetic mutation?': This data tracks a single population over time, not multiple populations, so comparing them is not the focus.
  2. 'Why do some pea plants have purple flowers and others have white flowers?': This is a fundamental question about trait inheritance but does not address the specific observation that the frequencies are changing over time.
  3. 'Would the frequency of alleles change if the pollinators in the area all died?': This question investigates the mechanisms behind the observed evolution. Changes in allele frequency are often driven by selective pressures, such as pollination patterns or environmental factors. This question sets up a testable hypothesis regarding the cause of the evolutionary trend.
  4. 'Is there another way to calculate the frequencies of the alleles in this population?': This is a question about mathematical methods rather than a biological investigation into the causes of the observed phenomena.
  1. Conclusion on the most appropriate scientific question

Given that the data shows a clear evolutionary trend, the most productive scientific inquiry is one that seeks to explain why these changes are occurring. By asking how external factors—such as pollinators—might influence these frequencies, a scientist can design experiments to test for natural selection or other evolutionary mechanisms. Therefore, the question regarding the effect of pollinators on allele frequencies is the most relevant.

Examples

This type of analysis is used in population genetics to study how traits change over time in a population. For example, if a researcher observes that a particular bird species' beak size is shifting across generations, they would ask questions about environmental pressures like food availability, much like the pea plant study asks about pollinator impact. By identifying these mechanisms, we can better understand how species adapt to their environments.

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