To determine the distribution pattern of the oyster larvae, we need to carefully examine the table provided, which shows the density of larvae at four different sites across three days:
[tex]\[
\begin{array}{|c|c|c|c|c|}
\hline
& \text{Site W} & \text{Site X} & \text{Site Y} & \text{Site Z} \\
\hline
\text{Day 1} & 40 & 22 & 0 & 7 \\
\hline
\text{Day 2} & 3 & 1 & 14 & 26 \\
\hline
\text{Day 3} & 2 & 6 & 3 & 1 \\
\hline
\end{array}
\][/tex]
Let's consider each distribution pattern one-by-one:
1. Random Distribution: If the distribution were random, we would expect the densities to vary without any clear pattern or grouping. However, the data show varying densities that might not strictly indicate randomness when closely inspected.
2. Clumped Distribution: In a clumped distribution pattern, individuals in a population are found in groups or clusters. Observing the table, we see significant variations in densities across different sites and days. For example:
- On Day 1: Site W has a density of 40 while Site Y has 0.
- On Day 2: Densities range from 1 (Site X) to 26 (Site Z).
- On Day 3: Densities are generally low but still exhibit variation.
The densities at various sites on different days show abrupt changes, suggesting the larvae might gather in specific areas or patches rather than being evenly or randomly distributed.
3. Stationary Distribution: This pattern implies no or little change in population density over time. The significant day-to-day variations in densities among the sites indicate this is not a stationary distribution.
4. Uniform Distribution: In a uniform distribution, individuals are evenly spaced across the environment. The variations seen in the table, such as high density at one site and low at another, do not support a uniform pattern.
Given the significant and abrupt differences in densities at various sites over different days, the most appropriate description of the larvae's distribution is:
B. clumped
The data suggests that oyster larvae exhibit a clumped distribution pattern across the different sites and days.
