BIOL 4254 - CM LAB REPORT

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Louisiana State University *

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4254

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Biology

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Feb 20, 2024

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Name : Casey Noyes Section Number : 1 Overall research question: Do different abiotic environments affect the plant communities on campus? COMMUNITY METRICS: Research Hypothesis 1 : Species richness will vary across the different areas of campus. Reasoning: Communities on campus are exposed to different levels of abiotic variables including humidity, temperature, sunlight, and soil moisture. Based on these conditions, one would hypothesize that areas with ideal levels of these factors would have significantly better species representation than other communities. Null Hypothesis 1 : There will not be a significant difference in species richness in the various communities. • Analytical Approach and Appropriate Graph type: ANOVA, bar graph • Independent Variable: Campus location. • Dependent Variable: Number of species (S). Research Hypothesis 2 : Species evenness will vary across the different areas of campus. Reasoning: Based on a communities’ abiotic range, certain species may dominate entire areas of campus. Whereas other areas, specifically those with ideal conditions, would likely give rise to a more even population. Null Hypothesis 2 : There will not be a significant difference in species evenness in the various communities. • Analytical Approach and Appropriate Graph type: ANOVA, bar graph • Independent Variable: Campus location. • Dependent Variable: Relative abundance of species (J’). ABIOTIC VARIABLES: Research Hypothesis 3 : Average air temperature will vary across the different areas of campus. Reasoning: The amount of sunlight an area is exposed to is dependent on the surrounding architecture, trees, or any other shading objects. Increased presence of these shading objects will decrease the sunlight availability and, therefore, drop the air temperature. Null Hypothesis 3 : There will not be a significant difference in average air temperature in the various communities. • Analytical Approach and Appropriate Graph type: ANOVA, bar graph • Independent Variable: Campus location. • Dependent Variable: Air temperature. Research Hypothesis 4 : The relative humidity will vary across the different areas of campus. Reasoning: Because different areas of campus are exposed to different amounts of sunlight, the soil humidity will vary accordingly due to different rates of evaporation.

Name : Casey Noyes Section Number : 1 Null Hypothesis 4 : There will not be a significant different in relative humidity in the various communities. • Analytical Approach and Appropriate Graph type: ANOVA, bar graph • Independent Variable: Campus location. • Dependent Variable: Relative humidity. JACCARD’S SIMILARITY INDEX: Research Hypothesis 5 : Species composition will differ between two communities on campus. Reasoning: Because the communities are exposed to different abiotic variables, we expect different species to be present based on their tolerances to humidity, temperature, sunlight, and soil moisture. Null Hypothesis 5 : There will be no difference in species composition in different areas on campus. • Analytical Approach: Jaccard’s similarity index. • Independent Variable: Campus location. • Dependent Variable: Species present. LAB REPORT 1 FEEDBACK: - “Try to keep tense in 3 rd person throughout.” - “Try to aim for 5 paragraphs for the introduction.” - “Put the equations in their own line (Methods).” - “Overall good work! The discussion has some great points but could use a few more connections to the literature or a detailed explanation of future directions.” - “Good citation style but try to ensure that you have at least 5 sources that are primary or peer reviewed like journal articles as opposed to websites.” Majority of my errors in the first lab report were from technical things such as (1) not using 3 rd person, (3) not setting up my methods section correctly, and (5) not using primary sources in my report. In this report, I will attempt to resolve this easy-to-fix issues by double-checking my writing now that I am aware of what to look out for. My other, non-technical, errors were simply from not making my report long enough. This time, I will be sure to include all of the necessary information to extend my writing. Academic integrity statement By signing, I acknowledge that I have completed this coversheet and the attached report according to the Code of Student Conduct and the syllabus for this course (i.e., I certify that I wrote this report independently and that the material within is my intellectual property and not anyone else’s): __Casey Noyes _______________________ Date _30 October 2023 __________________

Name : Casey Noyes Section Number : 1 Abstract: When studying how abiotic factors influence a plant community, it is important to understand the community’s ecological basis. Community ecology is the study of species within a defined area and how they interact with one another. Ecologists use community metrics such as species richness and species evenness to understand and compare ecological patterns in many different communities. These metrics are the basis of a community and can be influenced by many abiotic factors such as air temperature, humidity, soil moisture, and wind speeds. This study examines these different abiotic factors and the coordinating community metrics between eight subsections of LSU’s campus. Both abiotic factors and community metrics were used to distinguish the significant differences in plant communities across campus. As a result, two hypotheses were made regarding the varying community metrics across campus, two hypotheses were made regarding the varying abiotic factors across campus, and a last hypothesis was made regarding the differences in species composition between areas (Jaccard’s Similarity Index). Statistical Analysis of the pooled data was conducted using Microsoft Excel and generated into graphs using JMP and ANOVA. The results showed various significance levels for each factor studied, but general trends indicated that there are likely correlations between the composition of campus plant communities and the disturbances in the area. Introduction: The species interactions and compositions that define a plant community can be explained using community ecology. Community ecology focuses on all species within a defined area as well as the interactions that bind them. Ecologists use community metrics such as species richness, species evenness, the Shannon Weiner index, and Jaccard’s index in order to quantify this broad field in terms of an individual community’s structure. The alterations of these natural communities, both positively and negatively, can come from human or natural interference. Most notably, an article in The Journal of Tropical Forest Science notes that human disturbances to natural plant systems were one of the leading explanations for changes in species composition and density (Hoang VS et al., 2011). The effects of interferences on plant communities can be seen when comparing areas with minimal changes to the natural landscape to high-traffic areas that are highly susceptible to human interference. This study largely focuses on areas that are susceptible to human interference with the addition of architecture and landscape choices. These changes to the natural community can be seen in the differences in relative humidity, air temperature, wind speed, and soil moisture. Additionally, factors such as sunlight susceptibility and soil pH would also work to quantify this measurement. In this report, statistical tests were run on air temperature and humidity, which can be related to human disturbances, to study the plant community’s reaction. These results, and similar ones of this affect, are crucial when it comes to ecologists further expanding their understanding of how disturbances affect communities (Nichols, 1989). This further understanding is also important in regard to plant survival in future architectural and landscape advances (De Blois et al., 2002). Abiotic factors in the environment are one of the most crucial aspects when it comes to the survivorship of a plant community. Plants are dependent upon their environment to survive, and understanding how to strengthen their survival is an important ecological concept. An article published in Vol. 8 of Ecology and Evolution , relates plant survival rate due to abiotic factors to a worldwide issue, global warming (Cowles et al. 2018). This article notes that the rising temperatures seen across the globe are detrimental to plant communities. Although this study

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Name : Casey Noyes Section Number : 1 does not directly deal with global warming, it does show the effects of warmer climates on plant communities. Plant community ecology is a rapidly evolving field of study with constant advances in technology and knowledge occurring each day. Therefore, since several similar field studies have been performed over the years, this report serves as a continuation and attempted replicate of these efforts. The overall hypothesis of this report is that different areas of LSU’s campus will have significant differences in community metrics and abiotic factors. The community metrics analyzed here are species richness and species evenness and the abiotic factors are average air temperature and relative humidity. Additionally, Jaccard’s similarity index is used to quantify the similarities in species composition between three sets of two communities. In this study, it was determined that community metrics (richness, evenness) and abiotic factors (air temperature, humidity) are significantly different in the different areas of LSU’s campus. However, these two categories do not show a direct correlation, indicating that these specific abiotic factors are not the cause for the community metrics observed. Additionally, Jaccard’s index showed very little similarity among different groups across campus, indicating that the communities are not subject to the exact same niches. Methods: In order to determine the differences between two plant communities, data was gathered for both community metrics and abiotic factors for eight areas around LSU’s campus. This experiment involved eight sections of 10-15 students collecting data in their designated area and pooling the data to be further analyzed. In order to study community metrics, species were named using the iNaturalist app, counted for abundance, and tallied into a shared Google Sheet. This gave access to quantify the species richness and evenness for each community. Abiotic variables of air temperature, wind speed, relative humidity, and soil moisture were also collected during the species identification using a weather gauge and recorded into the same Google Sheet. Once the data was collected, statistical analysis was performed with Microsoft Excel. The values were then transferred to JMP version 16 to run an ANOVA test and generate according bar graphs. The statistics from JMP were then used to determine if the data was significant. Jaccard’s similarity index was also calculated using the data from the pooled Microsoft Excel file. The first calculation made was species richness (S), which involved counting the number of different species within an individual community. Next, total abundance was determined by summing the total number of individuals tallied for that community. In order to account for both richness and relative abundance when discussing species diversity of a community, we used Shannon’s diversity index (H’) as below. 𝐻 ′= −∑ 𝑝 i (ln( 𝑝 i ) ) - H’ represents the value of the Shannon Weiner diversity index. - p i is the proportion of the community represented by the i th species. - ln is the natural logarithm of p i .

Name : Casey Noyes Section Number : 1 Once the final sum of H’ was obtained, species evenness (J’) was calculated using the equation below. 𝐽 ′= ( 𝐻 ′) / ( 𝐻 max ) - 𝐻 max = 𝑙𝑛 ( 𝑆 ) Lastly, Jaccard’s similarity index was calculated as below in order to compare species composition between two communities. Jaccard values range from 0 to 1 with larger numbers representing a larger percentage of species in common. Of note, Jaccard values do not serve as a quantitative value of a single community. This calculation was repeated four times in order to have each species compared to another (1-2, 3-4, 5-6, 7-8). Jaccard’s Index = (number of shared species) / (total number of species) Results: Figure 1. Species richness in different plant communities across LSU’s campus. Each bar represents the total number of species counted per area. Each of the eight communities studied had various values for species richness, with the lowest being community 2 with 16 species and the highest being community 5 with 64 species.

Name : Casey Noyes Section Number : 1 Figure 2. Species evenness in different plant communities across LSU’s campus. Each bar represents the calculated quantity of evenness (J’) for each community. The eight communities studied all had various levels of species evenness, but each of them had a J’ > 0.5, indicating that no one species was overbearingly dominant. Air Temperature 0 20 40 60 80 100 D BC C AB D A AB E 1 2 3 4 5 6 7 8 Community

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Name : Casey Noyes Section Number : 1 Figure 3. The average air temperature for each community. Each bar represents the mean (± SE) of air temperature taken via weather gauge over the data collection period for various areas of LSU’s campus. Post hoc Tukey categories are also indicated above each error bar. An analysis of variance (ANOVA) performed on the pooled air temperature data indicated that there was a significant difference in air temperature for the different areas on campus (F (7,413) = 56.9426, p = <.0001, Figure 3). A post hoc Tukey test revealed that areas 6 and 8 were the most statistically different campus areas in regard to temperature. This test also revealed that all of the areas, except area 8, experienced some level of overlap in their data. Figure 4. The average relative humidity for each community. Each bar represents the mean (± SE) of relative humidity taken via weather gauge over the data collection period for various areas of LSU’s campus. An analysis of variance (ANOVA) performed on the pooled relative humidity data indicated that there was a significant difference in air temperature for the different areas on campus (F (5,393) = 73.0559, p = <.0001, Figure 4). As seen in Figure 4, the area with the lowest humidity on LSU’s campus is community 7, whereas the highest humidity is community 8, closely followed by communities 3 and 5.

Name : Casey Noyes Section Number : 1 Figure 5. Jaccard’s Similarity Index between four sets of two campus areas. Calculation of Jaccard’s similarity index shows that none of our plant communities are very similar. All of our communities have a value for J which is equal to <0.12. This low number indicates that our communities share less than 12% of the same species. Discussion: Based on the data collected and analyzed in the study, it has been determined that abiotic environments do vary among the plant communities on LSU’s campus. First, community metrics for the eight areas show that each community is different, albeit some slightly, in both their richness and evenness quantities (Figure 1,2). It has also been determined that the different areas have different averages for both air temperature and humidity (Figure 3,4). Thus, the data is able to reject null hypotheses 1-4 because significant difference was noted for each of the four factors (richness, evenness, air temperature, humidity). This variety can be explained by the architecture surrounding the area, landscaping upkeep, and many other external factors. However, there is no significant data here which proves that the variety in the chosen abiotic factors is correlated to the variety in community metrics. If this were the case, there would be evidence proving that higher/lower air temperature/humidity is directly related to higher/lower species richness/evenness. However, this is not cause enough to reject the overarching question: “Do different abiotic environments affect the plant communities on campus?” since all possible abiotic factors were not accounted for. Further studies on how abiotic factors affect plant communities should expand on the concepts discussed in this report. One way this could be achieved is by including more technologically advanced equipment in data collection. For example, an article in Ecological Informatics, Vol. 61 notes that soil nitrogen content is one of the leading abiotic variables which explains plant diversity (Zhang et al., 2021). Due to limited equipment availability, this study did not take chemical content of the areas studied into consideration when discussing species diversity and makeup. Lastly, calculation of Jaccard’s similarity index shows that all of the communities studied across LSU’s campus are extremely different and share less than 12% of the same species (Figure 5). This rejects null hypothesis 5 . Once again, this lack of similarity in community makeup is not explained by the abiotic factors in this report but could be further explained with additional research. Additional development on this index should be performed to determine if

Name : Casey Noyes Section Number : 1 the niches of the species in each area is an explanation as to why they can survive better on certain parts of campus. Some potential errors of this study include lack of advanced equipment and inconsistent data collection among researchers. As discussed, further research on this topic should be done with more up-to-date and reliable equipment but should also involve more structure between each community’s data collection procedures. In this study, some of the areas (1-8) did not complete the same abiotic measurements as others, leaving the report with several missing variables. Additionally, LSU has seen out-of-character weather this year, leaving the researchers unable to determine if current trends are truly as they appear. References: Cowles, J., Boldgiv, B., Liancourt, P., Petraitis, P. S., & Casper, B. B. (2018). Effects of increased temperature on plant communities depend on landscape location and precipitation. Ecology and Evolution , 8 (11), 5267–5278. https://doi.org/10.1002/ece3.3995 De Blois, S., Domon, G., & Bouchard, A. (2002). Landscape issues in plant ecology. Ecography , 25 (2), 244–256. https://doi.org/10.1034/j.1600-0587.2002.250212.x Hoang, V., Baas, P., Keßler, P., Slik, J., Steege, H. T., & Raes, N. (2011). HUMAN AND ENVIRONMENTAL INFLUENCES ON PLANT DIVERSITY AND COMPOSITION IN BEN EN NATIONAL PARK, VIETNAM. Journal of Tropical Forest Science , 23 (3), 328–337. http://www.jstor.org/stable/23616978 Nichols, Alan B. 1989. “Tropical Deforestation Triggers Ecological Chain Reaction.” Water Environment & Technology 1, no. 2: 320–27. Zhang, Q., Wang, J., & Wang, Q. (2021). Effects of abiotic factors on plant diversity and species distribution of alpine meadow plants. Ecological Informatics , 61 , 101210. https://doi.org/10.1016/j.ecoinf.2021.101210

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