Final answer:
Population values might not match predictions due to sampling errors, measurement errors, and environmental changes. These factors can lead to actual population sizes being higher or lower than predicted, and predictions should be tested and refined accordingly.
Step-by-step explanation:
There are several possible circumstances that would explain why a population value might not be 100% accurate compared to predictions. Firstly, there could be sampling errors, where the sample taken does not represent the entire population. For example, a chance error may occur if the sample size is too small, or there is bias if the sample isn't randomly selected.
Measurement errors are another factor; this can stem from inaccurate ways of measuring or counting individuals within a population, or uncertainty in numbers taken from graphs. Other influential circumstances include environmental changes that affect population dynamics in unpredictable ways, such as availability of food, predators, disease, or weather events that were not considered in the initial predictions.
If actual future data for rabbit populations is inaccurate and based on predictions that do not account for these errors or changes, the number of rabbits in 2021 could be higher or lower than estimated. An underestimate of population size may occur, for instance, if animals learn to avoid traps or counters. Therefore, it is essential to regularly test and refine prediction models to account for the various factors that can cause outcomes to deviate from predicted values.