Impact of Growing Season on Population Dynamics: Analytical Essay

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Population dynamics can be a challenging topic of study for a variety of reasons. In any given ecosystem, there is a variety of density-dependent and independent factors at play (Peterson 1977). It can be difficult to analyze the relationship between only two variables, because the confounding effects of other factors in the ecosystem may influence the relationship. For example, birth, death, immigration, and emigration are four of the most significant influences on population size (Peterson 1977). However, immigration and emigration are difficult to measure in a natural habitat. Isle Royale, an island located on Lake Superior, is an excellent field study site for population dynamics because its isolated territory effectively eliminates the influence of immigration and emigration on island populations.

Climate change is impacting the growing seasons of the Great Lakes area (Wuebbles et al. 2010). In the 1900s, the growing season length in the Great Lakes was around 150 days in a year; however, in recent years this has increased to around 170 days (Wilson and Baldocchi 2000). This increase in the growing season means that plants have more opportunity to reach maturity, which translates to an increase in food for herbivorous species living in the area.

In this study, we examine the effects of the growing season on the carrying capacity of moose (Alces alces) populations on the island. Isle Royale is a small island that is inhabited by only a few types of dominant species-- the moose, the grey wolf, and plants including grass, balsam fir, and maple (McLaren and Peterson 1994). In previous simulations of Isle Royale, it was observed that as the length of growing seasons increased, so did the maximum possible number of individuals. However, it is unknown whether this increase in population size is sustainable; therefore, the question is posed about how the carrying capacity, a measure of population sustainability, is affected by differences in growing season length. We hypothesize that as the growing season increases, the carrying capacity of moose populations will also increase, due to the increase in the availability of food and resources in the form of plants.


SimUText, an interactive textbook software, was used to stimulate the population ecology and ecosystem of Isle Royale. In the Isle Royale Playground module, factors such as the number of moose and wolves present, as well as the length of the growing season, were able to be manipulated in order to determine the relationships between specific biotic and abiotic factors on the island. There was also the option of running the stimulation for a desired number of years. The stimulation provided a comprehensive line graph that displayed the simultaneous changes in plant, moose, and grey wolf populations across time, and stopped until the indicated time interval had passed.

In this experiment, only the length of the growing season was manipulated. Five trials of carrying capacity were measured for each of the three growing seasons-- short, normal, and long. This was done to ensure the consistency of values for each trial, and so that there would be enough data for later ANOVA testing. The short growing season was characterized by a decrease in overall temperature on the island, while the long growing season was characterized by an increase in temperature, compared to normal conditions. For each trial, a population of 100 moose was placed on the island, and the simulation was run for 50 years. A population size of 100 was chosen because the relatively large size means that carrying capacity would be achieved faster. After 50 simulated years, the population of moose had been stabilized and the carrying capacity had been achieved. To determine the carrying capacity of the moose population, the number of moose at the beginning of the stabilization and at the end of the 50 years were recorded, then averaged. This process was repeated for each trial for each growing season, for a total of 15 trials.

To analyze the data, descriptive statistics of the carrying capacities, including the mean, standard deviation and mean confidence interval, were determined through the software Statistica. Using this data, graphs of carrying capacity against growing season length were constructed. Finally, a one-way ANOVA test was run. This test is used to determine if there is a statistically significant difference between the means of three or more independent categories. In the case of this experiment, the single, testable variable was growing season, which was then divided into three independent categories-- short, normal, and long. In the ANOVA test, the mean carrying capacity of each growing season was compared with each other. If the ANOVA test yielded a statistically significant difference, then the null hypothesis stating no relationship would be rejected, in favor of the alternate hypothesis, which states that at least two of the three growing seasons are statistically significantly different from each other.

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The mean carrying capacity of moose populations for the short, normal, and long growing seasons were 247, 583, and 868 individuals, respectively (Table 1). The confidence interval levels, based on 95% confidence of the mean, were 247 ± 2.37, 583 ± 3.58, and 868 ± 4.76 for the respective growing seasons (Table 1). The mean carrying capacity of moose populations showed a statistically significant increase from the short to normal growing seasons, as evidenced by the non-overlapping of their standard error bars and p-value (discussion

Analysis of the impact of growing season length on the mean carrying capacity of moose populations suggests a significant increase in the carrying capacity as the growing season turned from short to normal conditions. However, there was no statistically significant difference between the moose carrying capacities during normal and long growing season conditions. This conclusion is corroborated by the data because based on the ANOVA analysis, a p-value of less than 0.05 was achieved (overall, the results did not completely support the original hypothesis that carrying capacity will consistently increase as the length of the growing season increases. The non-relationship between normal and long growing seasons was unexpected because it was originally believed that an increase in temperature during the growing season should allow for more plant growth and therefore more nutrients and resources for moose populations (McLaren and Peterson 1994). Knowing this, there may be two possible explanations-- one being that there truly is no correlation between normal and long growing seasons, or that some experimental errors may have occurred while sampling or designing this study.

Previous studies suggest different but not necessarily mutually exclusive conclusions about growing season and moose population dynamics in an ecosystem. In a study investigating the effects of growing seasons on sexual dimorphism, Garel et al. (2006) found that during shorter growing seasons, there was a greater difference in male and female body sizes. This suggested that under harsh conditions with fewer nutrients, the body size of male and female moose was more variable. In addition, the sex ratio was more skewed during this time, with the number of males in the population decreasing while females stayed relatively the same. Both of these imbalances may lead to challenges during mating and reproduction, which translates to fewer offspring being born in the generation and a lower carrying capacity for the season. The results of this study indirectly support our original hypothesis and some of our results. As previously mentioned, there was indeed an increase in carrying capacity when comparing short to normal growing conditions. This could be explained by a significant increase in food availability per individual moose. However, because the study on sexual size dimorphism did not specifically examine the effects of atypically long growing seasons on moose physiology, it is unknown whether it affects moose populations in a significant manner.

In a separate study on the relationship between climate and moose reproductive synchrony, Bowyer et al. (1998) found that the temperature levels during the growing season affected moose foraging availability, but not the synchrony of female reproduction. The study concluded that for some shrub species consumed by moose, a decrease in temperature and an increase in the shade was actually ideal for growth. If this were the case, it would go against our previous belief that an increase in temperature during longer growing seasons will facilitate plant growth. However, it is important to note that the researchers only carried out this study for five years, which is likely not sufficient enough for a time interval for truly significant trends to be established. Furthermore, moose primarily feed off of the leaves, twigs, and bark of trees, not shrubs (Wilson and Baldocchi 2000). In fact, the most favored plant species include balsam fir, willows, and maples (Peterson, 1977). To put this in the context of our own experiment, although this study may have found that some shrubs grow better in conditions similar to short growing seasons, it’s entirely possible that moose do not preferentially feed off of these shrubs in the first place. For this reason, although the conclusions of this study do not support our original hypothesis, it does not contradict it either.

Based on the conclusions of our study as well as references to previous studies (Bowyer et al. 1998, Garel et al. 2006), we maintain our original hypothesis that an increase in growing season corresponds to an increase in moose carrying capacity. The inconclusive relationship between normal and long growing seasons was surpseasonrising, but may be due to flaws in the experimental design, which may have skewed the results of the study. However, we propose ways to improve upon the design. First, running the stimulation for only five trials for each growing season may have not been sufficient to ensure that the data is reliable; if this study were to be revised, we propose to carry out more trials and sample more carrying capacities for each season. In addition, there were no conclusive statements in the SimUText stimulation about the exact range of growing seasons, in terms of days or variances in temperature. This means that while our original hypothesis may be correct, the difference in time between the normal and long growing seasons may not have been statistically significantly different, leading to null results when comparing the two categories. For this reason, a possible future extension of this study is to determine the approximate length of the growing season as well as the temperature range in which carrying capacity is significantly impacted. Then, referencing the current and projected growing season lengths as established in the research of Wuebbles et al., we can estimate the number of years it may take for temperatures to reach this level of carrying capacity in the Great Lakes area. This has practical applications, as it is known that instability in density-independent factors can eventually lead to instability in populations living in an ecosystem (McLaren and Peter 1994). By developing an accurate model of rising temperatures and moose carrying capacities, predictions can be made about when a species may face destabilization and possible extinction due to highly variable environmental factors. Subsequently, appropriate measures can then be taken to maintain at-risk populations.

Our experiment found that the moose population carrying capacity on Isle Royale significantly increased from short to normal growing seasons, whereas carrying capacity did not change significantly from normal to long growing seasons. The results from this study shed light on how moose populations are impacted by changes in the climate. While some may take the conclusions of this study as support that increasing global temperatures is beneficial for certain species, the fact remains that ecosystems are complex networks that are dependent upon the interactions of many types of organisms, not only herbivores such as moose. Future applications of this study can help model the influence of climate on many different populations, and facilitate the prediction of populations at risk of destabilization in an ecosystem.

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