Introduction
The methodology of the present experiment is built on the use of quantitative methods of analysis to study an artificial ecosystem. A brief overview of the entire experiment is that critical changes were consistently measured as a function of time for an aquarium prepared at week 9 with a biological diversity of functional ecosystem roles (producers, phytophages, predators). Nearly three weeks of sealed aquarium storage was expected to cause significant ecosystem transformations. Evidence of these changes could then be found in quantitative analyses of the biological and chemical composition of the liquid. This presentation reveals details of the methodology of the entire experiment and evaluates ways to process the data obtained for the following parts of the project.
Sample Preparation
In the preparation step, a critical step was the need to prepare all reagents and solutions used. As shown in the Figure, six labeled transparent beakers with different contents were prepared according to the reference chart. The jars were hermetically sealed for storage prior to use during laboratory analysis. Airtight storage was a critical step as it directly depended on the results of all testing (USC, 2017). The ecosystem was created as a sealed environment, so any foreign intrusion into the environment was considered an experimental error.
Quantitative Analysis
After the beakers with the samples were left to stand for several days, their biological composition was expected to change: in particular, the number of algae as first-order producers. Three solutions (A, B, and C) were prepared, which had different dilution factors. Sedgewick Rafter was used to determining algal bulk density in three observations (Led Jepara, 2019). In addition, natural cycles in the ecosystem may include excess ammonia as a component of shrimp fecal product. Ammonia content was measured with a household detector for aquariums: assessment was done by comparing ammonia content in clean water with three measurements. Histograms of distributions of dependent variables from observed values were created for the data obtained, allowing quantification of trends.
Changes: Biological Composition
At the end of the two weeks of analysis, the biological composition of the ecosystem was expected to change. The last section of the lab work used Sedgewick Rafter to examine the numerical change in species representation in the artificial ecosystem (Led Jepara, 2019). The formula depicted on the slide was used to calculate the percentage change, and the data was then recorded in a summary table relevant to the Results section.
Changes: Chemical Composition
In addition, it was expected that the chemical composition of the ecosystem had also changed upon completion of the laboratory project. Three measurement procedures were used to test this hypothesis. First, the concentration of ammonia in the liquid was analyzed similarly to what was done at week 10, with the difference that only one measurement was used. Second, the medium’s acidity was measured using a pH meter: a change in pH value could indicate a change in dissolved carbon dioxide concentration (Cattano et al., 2019). Finally, an aquarium water salinity meter was used, which was also an indication of dynamic biochemical changes in the ecosystem. All data were recorded in the Table. Upon completion of the last use of the laboratory instruments, all reagents and samples were adequately disposed of.
Data Processing
The data collected from each week were numbers recorded in summary tables. Processing them statistically using MS Excel was a necessary step to attractively visualize the data and draw conclusions and critical trends of the lab project (Miller, 2021). The total number of graphs created was five, and the slide lists them.
References
Cattano, C., Fine, M., Quattrocchi, F., Holzman, R., & Milazzo, M. (2019). Behavioural responses of fish groups exposed to a predatory threat under elevated CO2. Marine Environmental Research, 147, 179-184. Web.
Led Jepara. (2019). Sedgewick Rafter counting cell import alat penghitung micro organisme. YouTube. Web.
Miller, K. (2021). What to keep in mind when creating data visualizations in Excel. HBS. Web.
USC. (2017). Transporting biological materials. EHS. Web.