Give an example of sampling bias.

• A. Collecting fish from a shallow water area for ease of trapping, without considering other habitats.
• B. Collecting fish randomly from all habitats.
• C. Using traps that catch all individuals equally.
• D. Sampling the entire population.

Answer: (A)

Sampling bias shows up when the way we collect data favors some individuals over others, so the sample doesn’t reflect the whole population. Collecting fish only from a shallow water area because it’s easier to trap narrows the view to those that use shallow zones and misses fish from deeper habitats or other microhabitats. This makes any conclusions about the whole fish community unreliable, since the sample is skewed toward one part of the environment. To avoid this, sampling should try to include all relevant habitats or use methods that give each habitat (and each fish) a known chance of being sampled. In contrast, randomly sampling from all habitats, using traps that catch all individuals, or attempting a census would reduce bias because they better capture the true variety and abundance across the population.