Soil Properties and Microbial Biodiversity of Straw-Covered Soil vs. Soil Without Straw Cover

Purpose: Through the use of a variety of experimental designs and techniques, data was collected that was analyzed to conclude the biodiversity of bacteria in the soil and how straw cover and no straw cover conditions affect soil microbiomes and properties. This data was collected with the goal of expanding on information already discovered on the benefits of straw return (Chen et al., 2022). Additionally, the experiment's findings were used to enhance plant health and production yield in a local community garden in Lafayette, IN.

Soil collection method:

Soil with straw cover, which will be notated as condition 1, was collected from three separate locations within the garden. We took 3 soil core samples that were around 6" deep, each, and collected them together in a Ziploc bag. Next, we repeated this process with condition two, which was the condition of soil without straw cover, using a separate Ziploc bag.

Figure 1: pH of Soil with Straw Cover versus Soil without Straw Cover

This bar graph illustrates the difference in pH between the two conditions. Each lab group in our class conducted this experiment, and the graph above depicts the average of each group’s sample measurements along with the standard deviation. The t-test was utilized through an Excel program to test if there was a statistical difference in the data, and since the p-value was 0.921, which is greater than 0.05, then there is no statistical difference between the data sets.

Figure 1 Method: 

The data was collected by weighing approximately three grams of each soil condition into its own conical tube. Then, 12 mL of water was added to each condition before using a vortex for one minute to thoroughly mix each sample. Tubes were allowed to sit for 30 minutes at room temperature with the tubes being gently swirled every five minutes. After this time, a pH probe was used to test the concentration of hydrogen ions in each sample, thus indicating an accurate measurement of each sample’s pH. 

Figure 1 Results:

The no-straw condition has a 1.28% higher average pH level than the straw condition. The standard deviation of the no-straw sample was slightly larger than the standard deviation of the straw sample. Additionally, the no-straw sample had a slightly higher pH reading, on average, than the straw sample. However, due to the pH probe data having a p-value of 0.921, there is no conclusive data to draw accurate measurements or data.

Using the data, it can be assumed that the general pH levels of the soil in this garden do not impact the soil or the plants that grow there, since there was no statistical difference in the data to support a difference between the two conditions based on pH. 

The pH levels were taken to confirm if there are differences in pH between the conditions, which could have an impact on the biodiversity of bacteria in the soil and how the plants grow. Too high and too low pH levels both negatively impact plant health and negatively impact the biodiversity of the bacteria in the soil. Differences in pH affect the plant’s ability to take up nutrients. Too high and too low pH acts as the primary determinant of the biodiversity levels of soil bacteria (Wu et al., 2017). Through our experimental design, we concluded that there is not a large enough difference in pH to affect the conditions. This would make sense since the soil was all generally in the same area, and the addition of straw would have little to no impact on soil pH. There have been no major events that would have caused just one of the conditions to have a large change in pH from the standard soil pH for the garden.

Figure 2 Moisture Content:

This bar graph illustrates the difference in percent moisture content between the two samples, with the straw condition having an average of 30.77% and the no-straw condition having an average of 22.42%. To get the final data for the bar graph, we took the average of the class for the average percent moisture content. An Excel program t-test was then used to find the p-value, which was less than 0.05, indicating a significant difference between both data sets.

Figure 2 Method:

These results were recorded by measuring one gram of each soil condition before placing the samples into a laboratory oven at 105-110 °C to dry for one week.  After one week, we took the soil, measured the new mass, and used this information to calculate the percent moisture of each sample.

Figure 2 Results:

We found that the average percent moisture control for condition 1, with straw, is 30.77% compared to the moisture control of condition 2, without straw, which averaged 22.42%. The straw sample has a percent moisture content that is 1.4x greater than the no-straw sample. When conducting the Excel t-test evaluation with the eight class samples, the p-value was 0.0277, indicating a significant difference in moisture content between the two sets of data.

Drawing on our knowledge of sunlight and heat working to evaporate water off of the ground, we are confident that the results are accurate. It would make sense that the moisture content of straw is higher than the moisture content for the no-straw sample since, “Using straw helps the soil to retain moisture easier through blocking some of the sun’s rays and keeping the ground cooler” (Chen et al, 2023).

Moisture content in the soil is vital to plant growth, as too much moisture or too little moisture can have lasting effects on plant health. Too much water can leach soil nutrients and create a waterlogged and anaerobic environment. On the other hand, little to no moisture can be too dry for plant growth. There is a variable amount of water that a plant can tolerate in the soil, and it was important to gather data on the differences in moisture content in the soil dependent on the usage of straw.

Figure 3.1 - 3.4 Method:

This data was collected by first diluting our soil samples, which were then inserted into an EcoPlate™ for culturing. The with-straw and without-straw samples were each diluted by a factor of 30, 14.5mL of sterile deionized water was added to 0.50g of the soil sample. In a 96-well EcoPlate™, columns 1-4 were filled with sterile deionized water, columns 5-8 were filled with the diluted condition 1 sample, and columns 9-12 were filled with the diluted condition 2 samples. The EcoPlateTM was used according to the manufacturer's directions.

Figure 3.1 - 3.4 Results:
The soil samples with and without straw had significant differences in their average Shannon Diversity Index (H) values and richness (P < 0.05). The soil with straw had a 5.37% higher richness, meaning on average the soil microbes in the samples with straw used 1.4 times more carbon sources. These soil samples also had a 2% higher H value, so they were overall more biodiverse.  However, there was no statistically significant difference in evenness between these two conditions. In addition, our group's carbon utilization data observed a slight decrease in carboxylic acid use and a slight increase in carbohydrate use in the sample with straw cover.

The group is confident in the conclusion drawn from the EcoPlate™ data through the use of an unpaired t-test assuming unequal variance which concluded a significant difference in the Shannon Diversity Index and richness data. Additionally, using the averages of the class data (including eight different sample groups) provides a more complete and accurate analysis of the data from Figures 3.1-3.3.

There are many reasons that straw cover can increase the microbial biodiversity of soil. Straw cover reduces water erosion, which can wash away important nutrients that microbes need (Shi et al, 2021). Mulching prevents raindrop impact, causing higher organic matter content build up in the soil (Hati et al, 2006). Another important piece of information is that using straw cover leads to an increase in soil carbon (Liu et al, 2023). Together, these factors explain why the samples with straw cover had a greater overall microbial biodiversity (Shannon Diversity Index) and greater species richness.

Figure 4.1 and 4.2 Method:

The soil samples were homogenized through blending before a detergent buffer was added and then used to disrupt the cell membranes and break down the proteins. Then DNA was extracted through the addition of reagents and then purified by spinning the DNA. Next, the DNA was washed with ethanol and resuspended for sequencing. The sequence of 16S rRNA was amplified through PCR amplification, where primers targeted regions of the gene. After purification, Rush Univeristy facility used the MiniSeq system to perform sequencing of the 16S rRNA gene. 

Using Nephele, we accessed QIIME 2.0 and used it to run our data sequences and create our Phyla Taxonomic bar plot. We were then able to compare and contrast the different phyla from each condition.

Figure 4.1 and 4.2 Results:

There are nine dominant phyla groups that make up an average of 92% of soil libraries. The majority of our top 10 phyla groups match these dominant phyla groups, with the exception of two outliers: Crenarchaeota (archaea) and Myxococcota. When looking at the separate phyla comparing straw with no straw, we saw no significant difference between our conditions.  

According to the QIIME data, we did not find a statistical difference in the data between our conditions, so we can conclude that neither condition provides a unique soil microbiome genetic diversity. However, a point of interest is that our soil supported different dominant phyla groups for our general area when compared to other soil libraries. Based on our EcoPlate, we thought we would see a higher difference between the two samples in microbial diversity. This was not the case, leading to conflicting data results between the two methods (Rush and QIIME data versus the EcoPlate methods). 

Two of our phyla were different from the 9 main phyla: Crenarchaeota (archaea) and Myxococcota. Myxococcota is important because they, “Are predominantly aerobic soil-dwelling microorganisms that are capable of predation and fruiting body formation” (Genomes of Novel...). Crenarchaeota (archaea) is important in soil because, “Crenarchaeota are postulated to be the most abundant ammonia-oxidizing organisms in soils” (Niederberger 2023). Ammonia is a vital component of plant health due to its ability to increase nitrogen, an important nutrient for plant health, within the soil. While these two bacteria species were an unexpected find, their presence is beneficial for the plants in the garden. It was important for the experiment to determine whether the addition of straw to the top of the soil would alter the Phyla groups found in the soil. The addition of straw appears to have no significant effect, and therefore we can rule that it does not affect the microbial communities within the soil.

Figure 4.3 Shannon Diversity Index for Alpha Bacteria Biodiversity

This bar graph was created through running the class data through Nephele’s QIIME program and taking the average of the class data for alpha biodiversity in the soil samples. Standard deviation is shown on this graph and we can draw that there was no statistical difference of alpha biodiversity in the soil.

Figure 4.4 Richness for Alpha Bacteria Biodiversity

This bar graph depicts the average of the class data for bacteria species richness in the two soil sample conditions. Data was collected through running our soil samples through Nephele’s QIIME program to determine the richness values for each sample, and then taking the average. The standard deviation shown on the graph portrays that there is no statistical difference in the data to indicate that the difference in straw versus no straw affects alpha bacteria richness in soil.

 Figure 4.5  Evenness for Alpha Bacteria Biodiversity

Evenness values were calculated through an Excel program that used the QIIME richness and Shannon Diversity Index numbers from the Nephele program to calculate the average evenness value. Standard deviation lines indicate a statistical difference in the data between the straw and no straw conditions for this data.

Figures 4.3-4.5 Method:

Using the Nephele DADA2 program, we ran tests that collected Shannon Diversity Index and Richness data. These numbers were then placed into an Excel program that calculated averages, standard deviation data, and evenness values. We then used this data to create the above visual representations.

Figures 4.3-4.5 Results:

The soil samples with and without straw had significant differences in their average evenness values. A standard deviation “t-test” was performed with P < 0.05 to determine this information. There was approximately 7.33% greater evenness in the straw conditions. Additionally, there was no significant difference in the mean Shannon Diversity Index (H-value) nor the mean richness value between these two conditions, which was determined using the “t-test” method.

  There is a statistical difference in the evenness data between the class mean for each condition, which shows that straw versus no straw does have an effect on the evenness of bacterial biodiversity in the soil. There was no statistical difference between the class average data for richness nor the Shannon-Diversity Index value, which allows us to conclude that straw versus no straw has no effect on bacterial richness or variety in the soil.

  While the class average data for alpha biodiversity produced contrary data as compared to the data recorded based on the EcoPlate data method, we can assume that the class average data tested by Rush University is a more accurate representation due to the increased volume of samples to draw data from and the reduced risk for human error. The class data being more accurate would make sense for this experiment since it has been recorded that the upcycling straw does not affect bacterial richness, abundance, or diversity (Chen et al., 2022). The decomposition of straw as it degrades appears to have no impact on bacterial biodiversity factors like richness and diversity, however, according to the class data it appears to have an impact on evenness. This would make sense, as an additional straw layer could hinder the movement and spread of bacteria in the soil.

Discussion:  

Based on the class efforts and data, alongside data acquired by our smaller lab group, we determined the following statistical differences between the straw versus no straw cover soil samples. Differences in moisture content proved to have statistical differences and showed an increased moisture content in the soil with straw cover. There was no difference in pH between the soil samples that was significantly difference. Using our own class laboratory, we determined significant differences between the Shannon Diversity Index and richness value whereas the evenness values were not. The sample with straw cover had an increased richness and H value over the sample without straw cover. However, when this data was sent and ran by Rush University, they found the opposite data to be significantly different. Evenness values were significantly different whereas the Shannon Diversity Index and richness values were not found to have meaningful differences in the data. It is uncertain which set of data results should be taken into greater consideration, but our group discussed that Rush University and the use of Nephele programs most likely provides a more accurate data analysis due to less chance for human error and better methods and technology. Overall, it would require more advanced experimentation to pinpoint the exact quality differences in biodiversity levels. It can be concluded from this experiment's data that straw cover seems to have an impact on microbial diversity in the soil alongside moisture content, with the use of straw increasing moisture content in the soil.

Collaboration Statement: 

Alongside various other lab groups, and under the teachings and guidance of Dr. Jacob Adler and Mr. Renjin Xiao; Emma Creviston, Mara Welty, and Emory Walker collaborated to create the final product that is presented before the audience. Emory Walker focused on the Figure 1 data analysis and presentation, along with the Alpha Biodiversity data analysis and overall discussion. Emma Creviston primarily worked on the Figure 2 data analysis and the taxonomic bar plot data analysis. Mara Welty analyzed the Figure 3 data and worked on the Beta Biodiversity data analysis.

Thank you Dr. Jacob Adler and Mr. Renjin Xiao for your continuous guidance and support throughout the creation and execution of this project. In addition, thank you to Purdue University for funding. 

References:

Chen, Limei, et al. “Effects of straw return and straw biochar on soil properties and crop growth: A review.” NCBI, 27 September 2022, www.ncbi.nlm.nih.gov/pmc/articles/PMC9552067/. Accessed 23 September 2023.

Fan, Dengxing, et al. “The effectiveness of mulching practices on water erosion control: A global meta-analysis.” ScienceDirect, Elsevier B.V., October 2023, www.sciencedirect.com/science/article/pii/S0016706123003208. Accessed 16 November 2023.

Murphy, Chelsea, et al. “Genomes of Novel Myxococcota Reveal Severely Curtailed Machineries for Predation and Cellular Differentiation.” AMS Journals, American Society for Microbiology, 10 November 2021, www.journals.asm.org/doi/10.1128/aem.01706-21. Accessed 16 November 2023.

Niederberger, Thomas. “Crenarchaeota | archaea phylum.” Britannica, 20 October 2023, www.britannica.com/science/Crenarchaeota. Accessed 16 November 2023.

Shi, Yulong, et al. “Straw cover improved the community structure of nitrogen cycle function microorganism driven by water erosion.” NCBI, 26 January 2021, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9453445/ Accessed 16 November 2023

Wu, Yucheng, et al. “pH is the primary determinant of the bacterial community structure in agricultural soils impacted by polycyclic aromatic hydrocarbon pollution.” NCBI, PubMed, 4 January 2017, www.ncbi.nlm.nih.gov/pmc/articles/PMC5209717/. Accessed 16 November 2023.