Physical Geography Paper

Soil Moisture and Soil Carbon Comparison

Danielle Gede Lab Semester Project 2105 – Physical Geography Lab

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Abstract Soil is the physical foundation of everything on earth and has many important roles such as supplying nutrients and water and being a habitat for plants and animals. A healthy soil can be measured by how much water and organic carbon is in the soil. Forest management practices like prescribed fires and thinning the trees can help with maintaining a healthy soil so that the whole forest can benefit. A semester-long experiment was conducted at Stockton University, Galloway, New Jersey. There were six sampling events were three samples were collected from the different sites which included: clearcut burned, thin burned, control burned, clearcut unburned, thin unburned, control unburned. The samples initial weight were recorded and then dried in an oven and weighed again to measure the soil moisture and soil carbon. The results of the experiment indicate no significant differences among the sites for soil moisture or soil carbon. This was probably due to several factors, which came from the timing of the experiment. Since the experiment was conducted in the winter, the temperature was too cold and the trees were not active nor had any leaves, which would have affected the soil moisture and carbon. What should be done differently if done again would be to conduct the experiment all year round and to have more consistent sampling events.

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Introduction Soils are the foundation of habitats, physically supporting all the organisms that live in the habitat. Forest management practices are not only used to sustain habitats, but also aid in the habitats’ well being. This experiment was done to see if forest management practices like prescribed fires and clear-cutting/thinning trees help increase soil moisture and carbon. It is important to know if these forest management practices benefit soils because the condition of the soil greatly impacts the composition of the ecosystem it’s in. A prescribed fire is a forest management practice that assists in supporting healthy soils. Clear-cutting and thinning trees is another practice that was used in this experiment that promotes healthy soil. Two essential components of soil, soil moisture and soil carbon, help maintain a normal climate, vegetation growth and composition of the forest/ecosystem. Prescribed fires are one of the forest management practices used that positively impacts soils in many ways. Prescribed fires or a prescribed burn is a forest management practice that sets a forest on fire on purpose, but is controlled. In a study of the region Fenno-Scandia, it was critical that prescribed fires were used to burn the humus layer so that water could reach the deep roots (Fire and Ecosystems, pg.15). For some ecosystems, prescribed fires are necessary to maintain a healthy level of soil moisture in order for the roots of plants to receive water. In a study about prescribed fires in upland oak forests, “Prescribed burning at 5 FPD reduced soil organic matter by 60% and soil organic carbon by 64% and increased bulk density by 20%”(Williams, Hallgren & Wilson, 2012). This study stated that more frequent fires had larger effects on soil properties, but some effects were not good for the soil (Williams et al., 2012). Prescribed fires can be very useful for forest management, but when using it as a practice, should be used with caution. Prescribed fires offer various benefits to many habitats, and can be vital to maintain some habitats. Clear-cutting and thinning forests were the other forest management practices that benefit many factors of soils. Clear-cutting is cutting all the trees into stumps and thinning is cutting the branches off the trees and cutting a few of the trees into stumps. In a study done in Finland, they noted that clear-cutting the forest studied, there was a higher density of tree species (Betula) most likely due to an increase of mineral soil

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(Hyvönen et al., 2016). This study indicates that clear-cutting forests increases the minerals in the soil, therefore benefiting the trees and other organisms in that habitat. In a study about thinning floodplain forests, “Thinning improved habitat value by producing 20 (±8) hollow-bearing trees per ha after 42 years, while the unthinned treatment produced none” (Horner et al., 2010). Based on this study, thinning forests improves forests, therefore has a positive impact on soils in those forests. Clear-cutting and thinning forests both decrease the density of forests, which in turn enhances the forests and their soil. Soil carbon and soil moisture are vital in an ecosystem because they impact climate, organisms and other aspects of soil. Soil moisture is how much water is in soil and is dependent on soil texture and the amount of precipitation the area receives. In a study done in Southeastern Europe, “We find a relationship between soil-moisture deficit, as expressed by the standardized precipitation index13, and summer hot extremes in southeastern Europe”(Hirschi et al., 2010). This study explains that when soil moisture is low, temperatures increase, most likely due to low evaporation rates. In a study about soil carbon affecting water retention, “At high organic carbon values, all soils showed an increase in water retention”(Rawls, Pachepsky, Ritchie, Sobecki, & Bloodworth, 2003). This study proves that increasing the amount of organic carbon in soil improves the soil’s ability to hold water, which is vital for plants and microorganisms in the soil. Overall, increasing soil moisture and soil organic carbon can increase the value and productivity of an ecosystem. The objectives of this experiment were to observe the effects of burning verses not burning on soil carbon and soil moisture and to observe the effects of clear-cutting and thinning a forest on soil carbon and soil moisture. The results of this experiment could tell us if these forest management practices benefit ecosystems. If so then Stockton can implement these practices in extended areas of campus and owned property.

Materials and Methods Site Description: The experiment is taking place at Stockton University, Galloway, New Jersey, USA. The climate of this site is very seasonal and includes four seasons. The temperature is cold in the winter months (December through March) and is warm in the

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summer months (June through September). The lowest average temperature was 33 degrees F in January and the highest average temperature was 76.2 degrees F in July. The precipitation is uniformly moderate throughout the year. Vegetation type includes forests. The soils that are present in the area include downer loamy sand, Atsion sand, and Manahawkin muck. The treatments include: burned control, burned clearcut, burned thin, unburned control, unburned clearcut, and unburned thin. The sampling methods were random sampling of each treatment at various times on campus during the spring semester.

Figure 1: A map of the location of the experiment in Southern New Jersey on the Stockton University campus.

Soil Moisture and Soil Carbon Comparison

Figure 2: The average precipitation in inches of each month in the region near the Atlantic City Airport.

Figure 3: Average temperature in degrees Fahrenheit of each month in the region near the Atlantic City Airport.

Field and Lab Methods: The forest was last burned on March 18, 2018. Treatment areas include clearcut burned, thin burned, control burned, clearcut unburned, thin unburned, control unburned. For each treatment area, three samples were taken from the A horizon soil layer (grey) at random locations in each treatment. Treatment Descriptions: There were 3 sites clearcut, thin, and control. There were also 2 treatments burned and unburned. There were six sampling events between January and

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March of 2018. We measured the gravimetric water content because we used the dry and wet weight to determine how much water was lost instead of using the volume differences. For soil moisture, the temperature at which it was dried was 105 degreed Celsius and the amount of time the samples were in the oven was over night. For the soil carbon, the temperature of the muffle furnace was 500 degrees Celsius and the amount of time the samples were in there was 4 hours. The formula used to calculate % soil moisture: (initial sample weight – final sample weight)/final sample weight x 100 The formula used to calculate % soil carbon: (initial sample weight – final sample weight)/initial sample weight x 100 Statistical Analysis: An ANOVA (single factor) was used to understand the relationship among the different treatments (control burned, thinned burned, and clearcut burned) for soil moisture and soil carbon. Also (two way) two sample t-tests were conducted to examine if there were any differences between the treatments for soil moisture and soil carbon. For both soil moisture and soil carbon, we tested if all the treatments were similar or different. The software used to compute ANOVA was Microsoft Excel 2011. The pvalue for the soil moisture burned sites of ANOVA was 0.4. The p-value for the soil moisture unburned sites of ANOVA was 0.3. The p-value for the soil carbon burned for ANOVA was 0.3. The p-value for the soil carbon unburned for ANOVA was 0.2.

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Soil Moisture and Soil Carbon Comparison Results

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Figure 4: Mean soil moisture percentage from treatments burned clear cut, control, and thin. Error bars represent 1 standard deviation from the mean. Letters denote differences at the p=0.05 level. Comparisons were made using a Protected Least Squared Differences test (one-way ANOVA followed by two sample t-tests).

Significant differences in soil moisture percentage were not measured among the three treatments (p=0.4). There is no significant difference in soil moisture percentage among the clear-cut treatment (mean  standard deviation = 19%  12%), the control treatment (mean  standard deviation = 32%  37%), and the thin treatment (mean  standard deviation = 31%  31%).

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Soil Moisture and Soil Carbon Comparison

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Figure 5: Mean soil organic carbon percentage from treatments burned clear cut, control, and thin. Error bars represent 1 standard deviation from the mean. Letters denote differences at the p=0.05 level. Comparisons were made using a Protected Least Squared Differences test (one-way ANOVA followed by two sample t-tests).

Significant differences in soil organic carbon percentage were not measured among the three treatments (p=0.3). There is no significant difference in soil organic carbon percentage among the clear-cut treatment (mean  standard deviation = 5%  5%), the control treatment (mean  standard deviation = 11%  16%), and the thin treatment (mean  standard deviation = 12%  16%).

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Figure 6: Mean soil moisture percentage from treatments unburned clear cut, control, and thin. Error bars represent 1 standard deviation from the mean. Letters denote differences at the p=0.05 level. Comparisons were made using a Protected Least Squared Differences test (one-way ANOVA followed by two sample t-tests).

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Soil Moisture and Soil Carbon Comparison Significant differences in soil organic carbon percentage were not measured among the three treatments (p=0.3). There is no significant difference in soil organic carbon

percentage among the clear-cut treatment (mean  standard deviation = 15%  6%), the control treatment (mean  standard deviation = 19%  19%), and the thin treatment (mean  standard deviation = 25%  25%).

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Figure 7: Mean soil organic carbon percentage from treatments unburned clear cut, control, and thin. Error bars represent 1 standard deviation from the mean. Letters denote differences at the p=0.05 level. Comparisons were made using a Protected Least Squared Differences test (one-way ANOVA followed by two sample t-tests).

Significant differences in soil organic carbon percentage were not measured among the three treatments (p=0.2). There is no significant difference in soil organic carbon percentage among the clear-cut treatment (mean  standard deviation = 3%  2%), the control treatment (mean  standard deviation = 6%  7%), and the thin treatment (mean  standard deviation = 9%  13%).

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Discussion Figures 4, 5, 6 and 7 show no differences in average soil moisture percentage and soil carbon percentage. This would mean that the varying treatments had an effect on neither the soil moisture or soil carbon. The burned treatment with the largest mean soil moisture percentage was control and the smallest was clearcut. The burned treatment with the largest mean soil carbon percentage was thin and the smallest was clearcut. The unburned treatment with the largest mean soil moisture percentage was thin and the smallest was clearcut. The unburned treatment with the largest mean soil carbon percentage was thin and the smallest was clearcut. The reason why was there no significant differences could be because of the timing of the sampling events. Since the samples were taken in January through March, the temperature could have been too cold to have any differences because soil moisture and soil carbon depend on temperature. Also because it was winter the trees and plants were dead and did not have leaves. Another reason could be that the areas of the different treatments could be too close to each other. The factors that could have affected the results could have been the time/season the samples were taken. Factors like sunlight, rain, leaf coverage, air temperature are much different in the winter than in the summer when the results would have been better. One important factor that affected the results of the experiment was fire. Right before the last sample was taken, Stockton conducted a prescribed fire in the campus forest. A different experiment that measured the effects of prescribed fires on the longterm health of a forest was compared to this paper (Brockway & Lewis, 1997). In contrast with the results of this experiment, they had found significant differences among the different treatments, which were based on differing frequencies of burning. Another paper that measured the effects of prescribed fires on the properties of the soil was compared to this paper (Williams, Hallgren & Wilson, 2012). In contrast, the soil carbon percentage and bulk density did have differences among the varying treatments. What I would do differently is conduct the experiment all year round to achieve the most accurate average soil moisture and soil carbon. Since the location of the experiment was in New Jersey, the temperatures vary and the climate includes all four seasons, there are too many differences to only collect samples in one season, especially

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just in the winter. In the winter the trees and plants are not active, therefore would have a higher soil moisture in the winter because the trees are no taking any of the water and the sun is not evaporating it as much as it would in the summer. Another procedure I would do differently is taking more samples than we had done for this experiment. Over the three months, we only had six sampling events. Therefore I would at least have twelve sampling events for the three months or if we sampled all year round I would do a sampling event once a week for all twelve months. One shortcoming was the duration of sampling events. We were supposed to sample twice every week but in the end were not able to do as many as we liked.

Conclusion The soil moisture and soil carbon of all the sites and treatments turned out to have no differences. But, because the samples were taken in the winter, several factors such as temperature and litter coverage, could have affected the overall results. It is important to know the soil moisture and soil carbon in order to know how the soil works and how healthy it is.

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Works Cited Brockway, D. G., & Lewis, C. E. (1997). Long-term effects of dormant-season prescribed fire on plant community diversity, structure and productivity in a longleaf pine wiregrass ecosystem. Forest Ecology and Management, 96(1-2), 167-183. doi:10.1016/s0378-1127(96)03939-4 Fire and Ecosystems. (n.d.). Retrieved from https://books.google.com/books?hl=en&lr=&id=Nrg-EP1oVcC&oi=fnd&pg=PA7&dq=soil benefits of prescribed fire&ots=QWsi8UmmSW&sig=FHDBpjRRuZg2wCxE8Xu7nJDaj5Q#v=onepag e&q=soil benefits of prescribed fire&f=false Hirschi, M., Seneviratne, S. I., Alexandrov, V., Boberg, F., Boroneant, C., Christensen, O. B., . . . Stepanek, P. (2010). Observational evidence for soil-moisture impact on hot extremes in southeastern Europe. Nature Geoscience, 4(1), 17-21. doi:10.1038/ngeo1032 Horner, G. J., Baker, P. J., Nally, R. M., Cunningham, S. C., Thomson, J. R., & Hamilton, F. (2010). Forest structure, habitat and carbon benefits from thinning floodplain forests: Managing early stand density makes a difference. Forest Ecology and Management, 259(3), 286-293. doi:10.1016/j.foreco.2009.10.015 Hyvönen, R., Kaarakka, L., Leppälammi-Kujansuu, J., Olsson, B. A., Palviainen, M., Vegerfors-Persson, B., & Helmisaari, H. (2016). Effects of stump harvesting on soil C and N stocks and vegetation 8–13years after clear-cutting. Forest Ecology and Management, 371, 23-32. doi:10.1016/j.foreco.2016.02.002 Rawls, W., Pachepsky, Y., Ritchie, J., Sobecki, T., & Bloodworth, H. (2003). Effect of soil organic carbon on soil water retention. Geoderma, 116(1-2), 61-76. doi:10.1016/s0016-7061(03)00094-6 Williams, R. J., Hallgren, S. W., & Wilson, G. W. (2012). Frequency of prescribed burning in an upland oak forest determines soil and litter properties and alters the soil microbial community. Forest Ecology and Management, 265, 241-247. doi:10.1016/j.foreco.2011.10.032