1:30 PM Atmospheric and Environmental Science Breakout VIII: Panel A
Wednesday, August 2 1:30PM – 2:30PM
Location: Pinnacle
Kelly Graziadei
University of California Davis
Urban Tree Nutrition: A Database of Edible Trees for Feeding Cities
The urban forest offers a variety of services from mitigating climate change to offering people places for cultural recuperation. But urban forests are rarely incorporated into local urban food systems as a solution to combat food insecurity and to augment human nutrition. In this study, we examined Ginkgo biloba as an initial model species to compare different cultivars’ nutritional profiles, with future plans to repeat this analysis on other commonly planted urban tree species. We negated statistically significant differences between varieties in order to set the precedent for interspecies collection of the top 1123 urban tree species planted across the US. Nutritional profiles of Ginkgo biloba were collected through an extensive online search of published scientific materials, hard-copy plant encyclopedias, and website databases fact-checked against the literature. Data was collected in Excel and run through several analyses in R Studio. The curation of a database of urban tree nutritional profiles will allow for the creation of a new tool—based on urban tree traits and nutritional values—to aid urban farmers and communities in selecting and planting climate-appropriate and nutritionally-sound urban food trees across the US. This should help to further diversify and secure urban food systems, build resilience within and across communities, and add to the growing knowledge on ecologically-sound solutions for more sustainable cities.
Jaren Mojica
University of Texas at Austin
Waste Management at the University of Texas at Austin Sporting Events: An Analysis of Production and Disposal
Sporting events hosted by universities generate substantial waste, presenting significant environmental challenges that need to be addressed through effective waste management. This research aims to analyze waste production and disposal at the University of Texas at Austin's sporting events, with the objective of offering practical recommendations for sustainable waste management. The study involves examining the types and quantities of waste produced, evaluating the current waste management strategies, and exploring best practices from various sectors. The data will be collected through waste audits, surveys, interviews, and document analysis. Statistical and thematic analysis methods will be employed to analyze the collected data. Furthermore, the research will include case study comparisons with waste management practices at other universities or sporting events. The outcomes of this study will inform event organizers and university administrators about existing waste management practices, identify areas that require improvement, and provide actionable recommendations for waste reduction and recycling. By implementing sustainable waste management practices, the University of Texas at Austin can demonstrate its commitment to environmental stewardship and serve as an inspiration for other institutions to adopt similar approaches. This research project contributes to the existing knowledge on sustainable waste management in university sports and has the potential to create a positive impact on the environment while fostering a culture of sustainability.
Cristian Swift
University of Washington
Random Forest Regression Models for Predicting Phytoplankton Biomass Partitioning in the North Pacific
The partitioning of phytoplankton biomass is crucial for understanding how climate change impacts the carbon cycle as it sheds light on the distribution and dynamics of different phytoplankton groups. However, there is a significant knowledge gap regarding the environmental factors that drive the partitioning of phytoplankton biomass, particularly in warm, nutrient-poor regions expected to expand under future ocean conditions. This study focuses on the dominant phytoplankton groups in these regions: Prochlorococcus, Synechococcus, and eukaryotic picophytoplankton (less than 2 micrometers in diameter). Using random forest regression models, we assessed the predictability of phytoplankton biomass based on salinity, temperature, light intensity, and dissolved inorganic nutrient concentrations (nitrate, phosphorus, and iron). Model performance was evaluated using 1,200 observations obtained through high-frequency flow-cytometry in surface water of the North Subtropical and Subpolar gyres. In this presentation, I will share the insights gained from our initial results and emphasize the importance of various environmental factors as predictors of phytoplankton biomass. These regression models are specifically designed for the location and timing of this study. However, I will discuss how to set a path for further research to refine these predictive models by including more variables and cruise datasets. Preliminary results highlight the importance of nitrate, salinity, and to a lesser extent, iron, as predictors of Prochlorococcus biomass. Conversely, phosphate and nitrate emerge as the primary drivers of Synechococcus and picoeukaryote biomass, respectively.
Marian Walker
UC Santa Barbara
Restoring California’s Native Coastal Scrublands: Understanding Limitations to the Growth and Distribution of Artemisia californica
Restoration projects aim to reestablish native plant communities and support the growth of biodiverse ecosystems although, the variability of the natural environment presents challenges to those goals. At the University of California Santa Barbara’s North Campus Open Space (NCOS), the success of coastal sage scrub restoration relies on the strong establishment of keystone species, including California sagebrush (Artemisia californica). This study investigates the correlation between California sagebrush growth (plant size) and soil bulk density. We hypothesized that areas of NCOS with lower soil bulk density are more favorable for supporting California sagebrush communities than those with higher soil bulk density. This relationship was explored by gathering soil samples and measuring longest branch lengths across two distinct zones. Results from statistical analyses indicate a weak correlation between soil bulk density and longest branch length across both zones (R = 0.161, r2= -0.413) which provides a potential explanation for approximately 41.3% of the decrease in plant size as soil bulk density increases. While bulk density does not fully explain the differences in California sagebrush growth, our results indicate that it may be an important contributing factor to differential growth in restoration sites. Understanding this relationship may help land managers improve the success of California sagebrush establishment at NCOS and similar restoration sites across the state.