Figure 3

Figure 3: Functional Biodiversity

Figure 3 compares the traits of biodiversity found in the two “new” and “old” soil conditions of the raingardens. To find the Shannon Diversity Index in figure 3A, we used the formula  −1 X Σ [pi × ln(pi)] where “pi” is the ratio of color development in one well to color development in all the wells for that condition. To find Average Richness, we added together the wells that provided values above the change in absorbance threshold once corrections were made. To calculate the Average evenness, we need to remove the average richness value from the Shannon diversity index. The formula to accomplish this is H/ln(S) where H represents the Shannon diversity index and S is the richness value. Lastly, to calculate the relative utilization efficiency percentage, we divided the relative utilization sum by the total amount of carbon then multiplied by 100 to get a percentage. In the above figures, the average values for the Shannon Diversity Index (H), Richness (S), and Evenness (E) are shown for the two soil types along with their standard deviations. An unpaired t-test was conducted for each set of data. The p-values generated are roughly 0.0 97 for the Shannon Diversity Index, 0.074 for Richness, and 0.576 for Evenness. 

Method 

The collected soil samples from the old and new rain gardens were inserted into the Ecoplate which scanned the soils at certain wavelengths and collected their average colors through monitored absorptions. The Ecoplate measured carbon source utilization by analyzing the soil microbes in each sample. We used a micropipette and placed the DNA of the old, new, and control samples into the Ecoplate. The carbon sources in the Ecoplate well were used by by the microbes, and caused the wells to become different shades of purple, where dark purple indicates high utilization of carbon source. We analyzed these wells by measuring the change in absorbance at 595 nm by using a spectrophotometer. After this, we put the data into an excel sheet, where we used values to find our Richness, Eveness, and Shannon Diversity. We calculated Richness by adding up the number of positive response wells (wells that met the threshold of 0.25) and compare the values for our old and new samples. To calculate Evenness, we used the formula in the excel sheet H/ln(s), which compared the color development in the wells. For Shannon Diversity, we used the formula −1 X Σ [pi × ln(pi)]. In this formula, pi is the ratio of color development in one well compared to the sum of development in all the wells. We then used these values to compare the functional biodiversity of each sample. 

Evidence 

As we can see from our graphs above, we are looking at the Shannon diversity index, the richness, and evenness of our soil. We look at these conditions because they are all good indicators of biodiversity in our soil. From our data for our old condition, we got a Shannon diversity index of 3.20, richness of 26, and evenness of 0.99. Then for our new condition we got a Shannon diversity index of 3.29, a richness of 28, and an evenness of 0.99. We can see from these averages that all our results were not far off from each other. The Shannon diversity index for our new condition is 2.7% greater than for our old condition. The richness for our new condition is 7.14% greater, and the evenness is the same. The p-value for our Shannon diversity index was 0.097, for Richness it was 0.07, and for Evenness it was 0.56. Our p-values showed that none of our results were significantly different, which ultimately means we accept the null hypothesis for our data. Accepting the Null hypothesis means we do not have sufficient evidence to say that they are different between the old and new rain garden. For the carbon sources in our experiment, we can see some differences by eye. We can see the differences in the carbohydrates and polymers the most by eye from our chart. Overall, they are all close, but the carbohydrates being the most different leads the entire graph to shift to look more different. 

Conclusion

From the data in figure 3A, 3B, 3C, and 3D, we see the Shannon diversity index, average richness, average evenness, and relative utilization efficiency for our new and old soil types. The new and old have different values in each graph, however the values are close. For the Shannon diversity index of the samples, the p-value is 0.097. Since this value is above 0.05, this means that the Shannon diversity index of the samples is not significantly different. Therefore, we can confidently conclude that they are not unique, based on this p-value. For the average richness of the samples, our p-value was 0.07. So, we can also conclude that they are not significantly different. Our p-value for average evenness is 0.56, which is greater than 0.05, proving that the samples are not significantly different in evenness. We can conclude they are not unique because these p-values are greater than 0.05. Lastly, the relative utilization efficiency graph shows very little differences between the old and new soil samples. The only noticeable two differences seen in the graph are the values of carbohydrates and polymers for each sample. However, when looking at the actual percentages of these, they are very close, proving that they are not significantly different. The values of the new soil samples’ carbohydrate percentage are 28.57%, while the old sample is 33.33%. These values are close and not significantly different. For the polymers in each sample, there is only a 3.17% difference in the values seen in the old and new. Based on all these values, where there are only small value differences between the data, we are confident in our data values and are certain that the Shannon diversity index, average richness, average evenness, and relative utilization efficiency of the old and new soil samples do not have unique values and are not significantly different.

Explanation 

The conclusion confirms that the two conditions we tested, young and old rain gardens, are not significantly different. In other words, the rain gardens are very similar in terms of biodiversity. A leading cause for this similarity is the “spatial and temporal patterning” of the environment in which the rain gardens exist (Bardgett). Living less than a mile apart, the gardens endured very similar weather conditions and the differences in soil properties between the two conditions is not substantial enough to hinder or improve the biodiversity of one condition over the other. A relationship can be made between the “spatial scaling of biodiversity and the area–diversity”, thus the spatial-temporal patterning theory holds true (Decaëns). Decaëns also mentions factors such as fires, grazing, and cultivation which will have a greater probability of impacting the biodiversity values than resource availability in this case. For example, if the building next to the old garden caught fire and spread to the greenery, or if the young garden was easily accessible for animals to graze, the damage to the plants would impact the diversity. The results from the tests, however, do not suggest such possibilities.  Therefore, we can establish the cause for the lack of statistical significance is due to the similarities in the environment in which both gardens grew.