Limitations Of Population Growth
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Introduction
There are a number of factors that can contribute to the growth of a population and these trends can be seen in a number of species. It is generally believed, from an ecological perspective, that populations will display either an exponential of logistic growth rate. If optimal environments are consistently maintained with no biotic or abiotic limiting factors (excess food, excess space availability, optimum climactic environment, no predation, etc) then a population will grow in an exponential direction. Species with high maximal relative growth rates do not occupy infertile habitats because their physiologies are more sensitive to suboptimal habitats and so their relative growth rates decrease more rapidly as fertility of the environment decreases (Shipley, 1988). A logistic curve will occur in population growth if the population is exposed to at least one limiting factor. The logistics model is and empirical description of how a population tends to grow when environmental conditions are not optimal. Although these two models can be seen in some species of organisms such as bacteria, they are rarely exhibited in natural occurring populations in the wild. In nature population growth in organisms is seen as more or less regular oscillations with high and low points, termed, the time lag model. In the time lag model there is a lag between a change in the environment and a corresponding change in the rate of population growth. These cyclic oscillations are influenced by the environment which the organism inhabits. Changes in the environment can affect numerous functions of an organism including natality (amount of births in a population) and mortality (number of deaths in a population). Laboratory populations of Daphnia are a good example of the effect of time lags on population growth (BOOK)!!!!!!. In this experiment Daphnia magna were utilized to observe the direct relationship of one limiting factor (food in this case) on the dynamics of growth in a population.
Daphnia are found in many kinds of water bodies, including rock pools on the island in the Gulf of Finland (Hanski, 1983). Daphnia exhibit some interesting adaptations to various limiting factors such as low food abundance. If energy and nutrients are limited, the number and size of offspring produced by an organism will depend on how these resources are allocated between reproduction and other life functions (Glazier, 1992). In this experiment there are two different populations of Daphnia, one which received food weekly (food is not a limiting factor) and one that did not receive food. Effects of food availability and toxic stress on maturation in female Daphnia magna are presented (Enserink, 1995). As food levels increase, the developmental rate approaches a maximum (Eneserink, 1995). It is also interesting to note that when food is scarce, some Daphnia eggs develop into males (weeeeeb). Because males are not the components that are responsible for population growth (females are) the addition of males should reduce the amount of offspring adding to the population. Overpopulation can lead to intraspecific competition for resources that are now limited like food availability. This adaptation of adding more males to the population seems to have evolved to curtail overpopulation that can occur in an optimal environment. The descriptive null hypothesis is there will be no difference in population growth between the supplemented treatments versus the unsupplemented treatments. Because of the evident sensitivity of Daphnia to limitation of food, the supplemented group should exhibit a greater population growth then that of the unsupplemented. It is expected that there will be significantly more Daphnia in the supplemented group over the 8 week time span of the experiment then in the unsupplemented group.
Materials and Methods
This experiment was conducted at the Texas State University Biology Department and lasted a full 8 weeks. Ten groups obtained two 1 liter bottles of clear plastic. One bottle was labeled “supplemented” and the other was labeled “unsupplemented”. Each bottle was filled 3/4 full with spring water from the San Marcos River. The water levels in the bottles were marked for future reference. Ten large Daphnia magna were carefully placed n each bottle along with a pinch of Spirulina (powdered algae). For the duration of the experiment, only the supplemented group of Daphnia magna received food weekly, the unsupplemented did not. Spring water was added periodically to the bottles when the water levels were below the line marked previously. Each week the numbers of Daphnia were counted utilizing a light source in order to illuminate the Daphnia and allowed them to be visible. The daphnia were placed in the designated lab area that maintained at room temperature. The data for a total span of 8 weeks was pooled and recorded. The data was then used for various types of statistical analysis including weekly means, per capita growth rates, t-tests, etc.
Results
According to the data collected, the Daphnia magna population in neither the supplemented treatment nor the unsupplemented treatment portrayed either the exponential or logistic growth model. The supplemented group showed a steady decline in the population while the unsupplemented group at first began with a significant drop off at first but then also became a steady decline. The week with the highest maximum growth rate for the supplemented group was week 7 and for the unsupplemented group was also in week 7. The supplemented group had an average maximum growth rate of 1.2 during week 7 and the unsupplemented group had a maximum growth rate of .3 during week 7. It is evident that the supplemented group showed a much higher max growth rate then the unsupplemented group. The t-test utilizing the maximum growth rates revealed a t-critical value less the t-calculated value and the decision to reject the null hypothesis. There is a difference between the growth rates between the supplemented group and the unsupplemented group. When analyzing the per capita values, the control group (unsupplemented group) had its highest value of .429 in week 7 and the treatment group (supplemented group) had its highest value of .39 in week 7. When comparing the two values against each other, the unsupplemented group had a higher per capita value.
Table A- Shows the statistical analysis conducted on the Supplemented data. The statistical calculations above include the mean of each week, the standard deviation of each week, the growth rate means for each week and the per capita growth rate for each week
Supplemented
Week 1
Week