1998 Results and Conclusion This experiment was a success in that all of our data supported our hypothesis. That is, red wiggler worms, Eisenia foetida, are able to exercise their own population control within an environment where there are limited resources, such as water, food, and space. We discovered that the "adjustment period," referred to in our hypothesis, was needed by worms in most of the bins before they could begin to reproduce. For example, at Check 1 six of the ten bins sustained the original number of worms put in. We believe these results were due to the time period the worms needed to adjust to their new surroundings in the smaller bins. The graph for Bin A reflects the general trend of there being little reproduction as the regression line is at a slight increase only. he population did not grow from its initial ten worms until Check 5 in which it increased to 12 worms, then 13 at Check 8. As they controlled their reproduction, the population began dropping down by one at every two checks. It rose back to a steady 11 for the last three checks. For Bin B, there was generally a slow decrease in population size. Starting at 10, it increased slightly to 11 worms at the second check and remained at this level until its increase to 12 at check 8. From then on, there is a decrease until Check 14, when it stays constant at 10 until rising to 11 worms for the last check. Bin C's data reflects the patten exactly for the line of regression is perfectly horizontal. From Checks 1 to 4 there is no change in the number of worms, but at Check 6 it increases sharply to 13 worms. Decreasing to 12, then down to 11, staying at 11 for 6 checks, and then steadily decreasing to 9 worms, insures the balance as the worms utilized their own population control. At Checks 17 to 18 and 19 to 20 there were increases of each one worm. Though there was no population growth in Bin D until halfway through the checks, the overall growth for the worms followed a slightly increasing trend. Quickly rising to 12 worms by Check 12, levelling off for three checks, then decreasing slowly and remaining at a constant 10 showed that the worms could control their reproduction rate closely. As with Bins A and D, Bin E has a basically level but slightly increasing regression line. As early as the first check, the number of worms were counted to be at 11, but it was at Check 6 when the population shot rapidly up to 14 in only four days. From there, the population decreased at an average of one worm every check until it settled back down at the original number of 10 worms. Increasing slowly from there on, and then dropping back down to 11 caused this slight increase in reproduction in this bin. Bin F's population growth was one of the two largest growths in all ten tested containers. Even though this was the case, the great, eventual increase was, in part, due to the quick, initial decline in population. At Checks 1 to 5 there were 9 worms, but from there in increased. At Check 6 there were 10, and at Checks 7 and 8 there were 11. Exercising population control, we found that from checks 9 through 15, there were 10 worms, the starting number. Checks 16 to 19 showed us eleven worms in the bin, and at the last check there were 12, the highest number in the bin during these twenty checks. Check 1 in Bin G turned out to be a quick and uncommon increase of 12 worms. From there, the numbers declined to be at a constant 10 from Checks 5 through 9. 11 worms were found in Checks 10 through 14, and the number remained virtually constant from then on, the only variation being at check 18, when there were 11 worms, again. This graph's line of regression is a downward slope, still above the 10 worm mark, however, demonstrating that when the numbers did exceed comfortable standards, the worms did control their population, not allowing it to drop below the original 10, though. Bin H was the only graph, beside that of F, which displays such a drastic population increase. The population, dipping down as low as 8 worms for Checks 4 , 5, 6, and 7, then grew at the approximate rate of one worm every two checks, finally reaching the twelve worm mark at Checks 16 to 18, then decreasing back down to 11 for the duration of the checks. Though there was a drastic reduction in the population(deaths), the worms reproduced again to build up the population, displaying that there is not only a maximum number of worms for the amount of space but also a minimum. Bin I's regression line shows us that there was a fairly slight increase in the number of worms in the bin, as they demonstrated the hypothesized population control. The beginning number of 10 worms did not increase at all until nearly halfway through at Check 8. Here, the number of 11 worms remained constant through Check 11. Then, the population dropped back down to 10 until Check 16. This is typical of the wave pattern found in the average trends of all the bins. From Checks 16 to 18 there were found to be 11 worms, and for the remaining two checks we counted 10 worms, again. The last bin, Bin J, came very close to demonstrating the consistency that worm population control would result in. The number of worms did not rise until over halfway through the checks, counting at Check 11 to be at 11 worms. From there, the numbers fluxuated, down to 10 at Check 12, up to 11 again for Check 13, and back down to 10 worms in Check 14. There were 9 worms counted in Checks 15 through 17, 10 found(consistent with the original) for Checks 18 and 19, and finally rising above again to 11 worms at Check 20. At Check 1, six of the ten bins had not changed from the original ten worms. Because of the disturbance in their environment during the process of moving these worms to their new environment, it is understandable that not much reproduction took place during the four days since the beginning of the experiment. This was referred to in the hypothesis as the "adjustment period." Three bins showed an increase in population, and one showed a decrease; however, these changes were two at the maximum. The range of population in the ten bins were 9 through 12. The mode, of course, was 10, and the average number of worms was 10.3. The variations in the population can be accounted for by considering the different levels of maturity each of the worms had when they were placed in their respective bins. Although we tried to select similar size worms, some might have been more mature than others. The range of population for Check 5 was 8 through 11. Exactly like in Check 1, six of the bins had the original number of worms, 10. Two bins showed an increase in number and two showed a decrease. The average population was 9.9. A general decrease in population of worms occurred during this time period. A general increase of worm population took place at Check 10. In Bin A, for example, an increase of three worms (from 10 worms at Check 5 to 13 at Check 10) occurred. The range of worm population was 10-13. Three of the bins contained 10 worms, while seven bins contained 11 or more. The calculated average was 11.1 worms. We started to see a peculiar pattern developing. Check 1 produced a slight increase of population, while Check 5 produced a slight decrease. Check 10, meanwhile showed an increase. The increase, decrease, then increase pattern, or the "wave pattern," may exist in the worms' natural population control mechanism. The range of population at Check 15 was 9 through 11. Keeping up with the "wave pattern," this represented a slight decrease in population from check 10 data. For example, Bin A's count went down from 13 to 11. Four bins contained 11 worms, while five contained 10, and one contained 9 worms. The average population was 10.3. The range at Check 20 was 10-12, a slight increase from Check 15. The average increased from 10.3 to 10.8. Three bins contained 10 worms, while six bins contained 11, and one bin 12. Bins A, B, C, and I went back to the original count, 10. This was the ideal result we hoped to display during this experiment. A surprising trend evident in our data was the "wave effect," a tendency for the fluctuations in the worm populations to oscillate back and forth in respect to their relative gains/losses. In other words, we were able to confirm that Eisenia foetida are able to limit population growth based upon available resources. This is evident in comparing the average worm population at certain time intervals. At Check 1, the average number of worms was 10.3 worms, while at Check 5 the average decreased slightly to 9.9 worms. At Check 10, however, the number increased to 11.1 worms; it then decreased again to 10.3 at Check 15. By Check 20, the number had risen slightly to 10.8 worms. This up and down pattern of population resembles a "wave," and can also be seen in data for individual bins throughout the testing time period. Bin J, for example(with a nearly horizontal regression line) shows how worms not only control their population in terms of the maximum number of worms but also a minimum. Throughout, its population followed this "wave" pattern, rising and falling from 10 worms to 11, then back down to 10, up to 11, and so forth, reaching only as high as one over the original number of worms and reaching as low as one under the original. The maximum number of worms counted in this experiment was 14, for Bin E at Check 6. The minimum number was 8, occurring several times for worm populations in different bins. This resulting range of 8 to 14 worms was smaller than our hypothesized range of 7 to 15 worms. Thus, the worms exercised stricter population control than what we had predicted. There were several minute problems we faced when conducting this experiment. First, the transition the worms experienced from their environments in the large bins used for previous years' experiments to the smaller bins used in this year's, must have caused them a considerable amount of stress. As discussed above with the period of adjustment, we would eliminate this problem in future tests by allowing the worms a week to adjust to the surroundings before we begin the experiment. Second, the counting accuracy may have been off a little due to human error during the counting of the worms(due to the fact that baby worms are approximately 2mm in length and almost transparent). Third, every four days a counting resulted in a small amount of stress for the worms, as their environments were disturbed and they were extracted from the bins to be isolated and counted. There are many practical and theoretical applications for this experiment. The purpose of this experiment was to find out if red wiggler worms were capable of exercising population control in small, contained environments. The environments simulated in this experiment are representational of those found in household and large-scale vermicomposting projects. Both people with household bins and those with community or commercial vermicomposting units will thus be able to use red wiggler worms without worrying that an increasing, uncontrolled population will mean increasingly more and more resources. Since the process of vermicomposting is a growing solution to some of the leading environmental problems, the results of this experiment are going to be sent to over twenty worm farms across the United States and in Canada. Copies of this report are also going to be sent to several vermiculturists in California, Florida, and other states, who have specifically asked for the results of this research in an attempt to use and relay this new data to other researchers. The results are to be sent, as well, to the Worm Digest, a magazine specifically published for vermicomposters. Hopes are that the results of this year's experiment and our three year study will help to cut down on at least a small amount of household wastes that would have otherwise accumulated in landfills, maybe never to be decomposed.