Question

How to assess the phenotypic variation in forest trees? ______________

• A. $\sigma^2_P = \sigma^2_G + \sigma^2_E$
• B. $\sigma^2_P = \sigma^2_A + \sigma^2_{NA} + \sigma^2_E$
• C. $\sigma^2_P = \sigma^2_A + \sigma^2_{NA}$
• D. Both 1 & 2

Hint:

Remember: $V_P = V_G + V_E$. Only the $V_A$ (additive) part is reliably passed from parent to offspring, which is why breeders focus on it.

Answer 1

The Correct Option is D

Step 1: Understanding the Question:
The question asks for the mathematical representation of the components that make up the total observable variation (phenotypic variation) in a population.

Step 2: Key Formula or Approach:
The fundamental equation of quantitative genetics is:
\[ \text{Phenotypic Variance } (\sigma^2_P) = \text{Genetic Variance } (\sigma^2_G) + \text{Environmental Variance } (\sigma^2_E) \]

Step 3: Detailed Explanation:

• Equation 1 (Broad Sense): The total phenotypic variation we see in trees (how tall they are, how fast they grow) is the sum of their internal genetic makeup ($\sigma^2_G$) and the influence of the site where they grow ($\sigma^2_E$). This is reflected in option (A).

• Equation 2 (Narrow Sense): The genetic component ($\sigma^2_G$) can be further broken down into "additive genetic variance" ($\sigma^2_A$) and "non-additive genetic variance" ($\sigma^2_{NA}$, which includes dominance and epistasis). Substituting this into the first equation gives:
\[ \sigma^2_P = \sigma^2_A + \sigma^2_{NA} + \sigma^2_E \]
This detailed breakdown is shown in option (B).

• Conclusion: Both formulas are standard and correct ways to partition phenotypic variance depending on the level of detail required by the breeder.

Step 4: Final Answer:
Both equations (1) and (2) correctly represent the components of phenotypic variation.