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Answer :
1. The overshoot of the carrying capacity observed in the initial moose population can be explained by the phenomenon known as lag effect.
The population response to changes in resource availability is not instantaneous, and there is a time delay in the population's ability to adjust to the carrying capacity. Initially, when the moose population had abundant resources, such as food and habitat, their reproduction rate increased, leading to rapid population growth. However, as the population approached or exceeded the carrying capacity, the available resources became limited, resulting in competition for resources, increased mortality, and reduced birth rates. This eventually led to a decline in the population size until it reached a stable equilibrium.
2. Real-world populations rarely follow smooth curves of logistic growth equation due to several factors. Ecological systems are complex, and populations are influenced by a range of biotic and abiotic factors, including competition, predation, disease, availability of resources, environmental variability, and human activities. These factors introduce fluctuations and disturbances that can cause population size to deviate from the predicted trajectory. Additionally, external events such as natural disasters or climate fluctuations can have significant impacts on population dynamics, leading to non-linear growth patterns.
3. The weather conditions on Isle Royale had a significant impact on the populations, particularly the moose and wolf populations. Changes in weather patterns, such as severe winters or warm summers, can directly affect food availability and habitat suitability. For example, harsh winters with deep snow can limit the accessibility of food sources for moose, leading to decreased survival and reproduction rates. This, in turn, affects the predation pressure on moose by wolves, as their main prey becomes less abundant. Therefore, weather fluctuations play a crucial role in shaping the population dynamics on Isle Royale.
4. A t-test is a useful statistical tool for ecologists because it allows them to compare the means of two groups or populations and determine whether the observed differences are statistically significant. In this lab, the t-test was likely used to analyze and compare specific variables or measurements between different treatments or experimental groups. By applying the t-test, the researchers could assess whether the differences observed in the data were due to chance or if they were statistically significant. The significance of the results would provide insights into the effects of the experimental factors on the variables being studied. The specific results and their significance would depend on the context and the data analyzed in the lab, so further information would be needed to provide a definitive answer.
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