Understanding Competition

Understanding Competition

INTRODUCTION:

Competition occurs between any organisms living in a mutual habitat. Whether it is for food, water, shelter, or a mate, competition can be harmful or helpful to each organism. There are two basic types of competition; intraspecific and interspecific. These terms refer to competition within a specific species and the competition between different species, respectively. In this lab, we conducted 3 basic experiments. Our goal was to observe the effects of the competition in each instance. The first one was to observe the intraspecific competition between the wheat plants species, the second was for the intraspecific competition between the mustard plant species. The third was the interspecific competition of the wheat and mustard species together. The latter experiment’s data was divided into two sub groups of high density and low density, for purposes of graphing Dewitt diagrams. Dewitt diagrams are a way of expressing % yield and total productivity data so it can be evaluated and compared effectively. It has been noted that intraspecific competitions tend to be more intense than interspecific ones (Ciara, 1993). This is because members of the same species need the same types and amounts of nutrients. When these similar species are in the same habitat with fixed resources, then they consequently have to “fight” for their needs. This is was basis for our hypothesis. We hypothesized that the species that were involved with the interspecific competitions would have greater production (by ave. weight of grams) than their counterparts involved in the intraspecific competitions. Furthermore, we hypothesized that as the density of the intraspecific and interspecific competition species increased, then the production of the plants (by ave, weight in grams) would go down.

MATERIALS AND METHODS:

Six weeks previous to the conductance of this lab, Biology 108 section, planted wheat and mustard plants according to table#1 on page 3 of the Principles of Biology 108 Lab Manual. This table depicts all of the total pots and number and type of seeds planted in the pots. It accounts for the experiments of the intraspecific competition and interspecific competition. Replicates of each pot were planted to add precision and more acceptable statistics. Therefore, there were 40 pots, that is, 20 treatments conducted twice (Ciara, 1993). Each Biology 108 section planted these pots and the data from every section was to be combined for an overall data sheet. Our group in section 6 had the role of planting 5 of the experimental pots with the assigned number of wheat seeds or mustard seeds or both. We filled each 4″ pot with artificial soil mix and packet it down below the rim, and then placed the required number of seeds onto the surface and sprinkled a little more soil on top. We were ordered by the TAs to plant a few extra seeds into each pot, depending on the original number of seeds originally assigned to each pot. This was meant to account for the statistical expected non-germination of some of the seeds. In a week or two following the initial planting, the extra plants were weeded out, so that each pot contained the originally assigned number of plants. The pots were then placed in the University greenhouse and watered routinely, and given supplemental light (Ciara, 1993). Six weeks later the data was collected. There were several calculations included in the expression of the data, primarily the interspecific data and the Dewitt diagrams. The Dewitt diagrams were graphs that enabled comparison of; the percent yield of the mustard ( mustard ave. pot weight in mixture / mustard ave, pot weight when alone x 100) and percent yield of wheat ( wheat ave. pot weight in mixture / wheat ave, pot weight when alone x 100). The Dewitt diagrams also enabled us to graph the Total Pot Productivity, which is the percent yield of mustard added to the percent yield of wheat, all on the same graph. The data for the Dewitt diagrams were divided into 2 groups, that of high density and low density relating to the number of plants in a pot. RESULTS: INTERSPECIFIC DATA The interspecific data is displayed on figures #1 and #2, the Dewitt Diagrams. The low density data is on figure #1 and it shows the percent yield of the mustard plant treatments in relation to the treatments of 0, 2, 4, 6 and 8 number of mustard plants compared to the percent yield of the wheat plant treatments with the same number of plants per treatment, respectively. Also shown (by the dotted line) is the optimum percent yield of each species had there been no interaction or competition between species. In comparison to the optimum percent yield, the species in this low density competition, the graph shows us that the mustard exhibited a slightly higher percent yield than the wheat, as it had more plotted points above its optimum percent yield. Another set of data that it recorded on this graph is Total Pot Productivity. This curve showed that the biomass of both species was slightly higher than the optimum of 100%. In figure #2, the high density Dewitt Diagrams, the percent yield of the mustard plant treatments in relation to the treatments of 0, 8, 16, 24 and 32 number of mustard plants compared to the percent yield of the wheat plant treatments with the same number of plants per treatment, respectively. Again, as in the low density results, the mustard had a higher percent yield. There was one extravagantly high percent yield for the mustard at the 24 mustard / 8 wheat plant treatment. There was also a higher percent yield at the same treatment for the wheat. INTRASPECIFIC DATA In figure #3 (Density Data) there is a visualization of the data collected for the intraspecific experiments. This graph shows the average plant weight compared to the number of plants in its respective pot. There is a line graphed for the wheat plants and one for the mustard plants. We see that, overall, the average plant weight of each species decreases as the density of the plants in each pot increases. Figure #4 displays the comparison between the average weights per treatment of the mustard plants in intraspecific competition and interspecific competition. It also compares the weights per treatment of the wheat plants in intraspecific competition and interspecific competition. In the interspecific competition, the number of plants (of the particular species being documented) does have an additional number of the other species in its pot which is indicated in the figure. Both the mustard and the wheat plants had, overall, higher average weights per plant as the number of plants per pot decreased. Discussion: The intraspecific data in figure #3 of a line graph was designed to visualize the density data for the mustard plant average weights compared to that of the wheat, per treatment. We can clearly see that the mustard plants had greater average weights at every treatment. This may be due to faster growth by the mustard plants or the fact that that they have more above-ground biomass than the wheat. Since we haven’t taken into consideration the below ground biomass, we will ignore the latter, for now. Also, as our hypothesis projected, the average weights of the plants per treatment decrease as the density, or number of plants per pot, increases. This is due to the competition of the plants for nutrients in an environment in which the nutrient levels and life necessities are fixed. As the number of plants increases, the amount of nutrients per plant decreases and thus, each plant has less nutrients than the pot treatment before it with less plants. The interspecific data for low density data in figure #1 showed us that predation was occurring. The Mustard exhibited a higher than optimum overall percent yield and the wheat, overall seemed to be below normal. Although the wheat did have one percent yield plot point that was higher than its optimum, the trend for the line graph was below the optimum. This information lead us to believe that the mustard was the “predator” because it seemed to take away nutrients from the growth of the wheat, which is the reason the percent yield of the wheat was lower than optimum. The reason the mustard species dominated over the wheat could be for two reasons: 1) the mustard is a faster growing species and its plants mature early and are able to dominate in that fashion over the immature wheat. This conclusion was reached after examining the intraspecific data, where the mustard had higher averages of plant weight per treatment; or 2) the mustard is simply a more aggressive species that has adaptive features which enable it to overtake plants such as the wheat. For figure #2, The Dewitt Diagram of high density data, there did not seem to be predation as in the low density interspecific treatments because there was not as great of a distinction between one species benefiting and the other costing. Overall, both species seemed to benefit and have higher percent yields than their optimum. This is considered mutualism because they both benefited. However, the mustard did still have a distinctively higher percent yield. Concerning the very high data point at 131%, there could have been a data collection error or a calculation error involved. This is not to be considered valid because it is impossible to have over 100% yield. However, it is taken into consideration as a high value (over its optimum percent yield) because the data trend is such. As for the Total Pot Productivity Curve, it simply represents the biomass of the two species combined and therefore allows us to see the overall productivity compared to the optimum. In the case of the low density data in figure #1, the Total Pot Productivity was higher than optimum in some points and lower in others, reflecting the higher % yield of the mustard and the predation of the mustard upon the wheat. In the high density data in figure #2, the Total Pot Productivity Curve was entirely above the optimum level. This is because of the combination of wheat not overall below its optimum percent yield and the mustard having some very high percent yield figures. Referring to our hypothesis, the average weights of the mustard plants interspecific experiments were higher than those in the intraspecific experiments, per treatment ( plant #). This is observed in figure #4 . These results are because in the interspecific experiments the plants did not have to compete with their own species that needed similar nutrients at the same growth stages. Also, as we predicted, the plants produced less as the density grew. This was observed in the intraspecific data when the average weight of the plants per treatment decreased as the number of plants per treatment increased. And in the interspecific data, in both high and low density, the percent yield of the plants went down as there were more plants added, in each treatment. This was exhibited in both the mustard and the wheat plants for all experiments. One aspect which we paid respect to in our consideration of our experiment was that in our data we only measured the above-ground biomass and not the plant structure below ground. This could be a factor that could introduce error in our results. This is because a plant species such as wheat or mustard could have an extensive root structure which could add a significant increase to its measurement of weight. Some plants, as we know, produce most of their biomass underground, such as a potato or carrot. Our data proposed a question as to what might happen if this experiment was extended over a longer period of time, or each pot was replanted to sow new generations. We concluded that, first of all, there would be much more accurate results given the longer time span which would more closely represent the length of time and generations that a plant species would go through in an existence. Secondly, that the mustard would probably exterminate (only after a long battle) the wheat from the pots. This hypothesis is taken from our determination from our results of our experiments where we decided that the mustard was the more aggressive plant and that it was also the faster growing. But the final results on that hypothesis would be another experiment.

0 replies

Leave a Reply

Want to join the discussion?
Feel free to contribute!

Leave a Reply