Microbial interactions with plant biomass contribute significantly to the cycling of nutrients and contaminants in the environment. Primarily among these interactions is the role of fungal-induced degradation of organic matter, its regulatory effects on the carbon cycle, and pollutant transport. This study uses fungal colonization of spent coffee grounds as a model for understanding fungi-plant biomass interactions and their relationship to carbon stability and pollutant removal capacity. Results indicate that fungal-induced alterations of the plant material result in an increase in aromatic and a concomitant decrease in methyl components of the organic matter. This molecular alteration was accompanied by an increase in the carbon content of the remaining material, an increase in the carbon stability as determined by the materials R , and an increase in sorption capacity for cationic species as determined from gentian violet sorption to the materials. The results from this study could contribute additional knowledge to solving grand challenges in climate and pollution.

Excessive greenhouse gas emissions that result from unregulated energy exploitation contribute to climate change and air pollution. One way to restore the carbon balance within the earth’s systems is to increase carbon inputs by capturing atmospheric carbon and storing it in stable reservoirs, also known as Carbon Sequestration. Using the process of photosynthesis, plants absorb carbon dioxide from the atmosphere and convert it to organic carbon that is relatively more stable than gaseous carbon. The ability to sequester carbon varies across different vegetation species and the environments in which they grow. Using ArcGIS tools and free-access remote sensing data, this study will survey the spatial distribution of plant biomass and their effective carbon storage capacity in a case study located in Africa. The results from this study will i) identify facilities with the most effective carbon sequestration potential ii) help conservation programs in making landscaping decisions for future urban developments.

Bats provide many ecosystem services, including pest control, pollination, and seed dissemination, which are economically beneficial to humans. Yet as human populations continue to grow, leading to the increasing loss, degradation, and fragmentation of natural habitats to urban sprawl, wildlife species including bats are having to adapt to this unnatural environment. One important resource that bats must access in such environments is water. In natural landscapes, bats drink from ponds, lakes, streams, rivers, and even puddles, but in human-modified areas, studies have shown that bats can drink from drainage ditches, cattle troughs, and residential swimming pools. However, it is generally assumed that these resources are not preferred and, if present, more semi-natural water sources, such as retention and ornamental ponds, would be preferentially used. But what if we are incorrectly assuming that all semi-natural water sources are readily accessible and available to bats. To explore this uncertainty, we conducted behavioral observation surveys using thermal cameras and acoustic detectors to determine whether semi-natural water sources within Fort Worth, including the retention pond on the Texas Christian University (TCU) campus, were suitable for bats. Specifically, we compared bat drinking activity at these ponds and identified pond characteristics that might deter or encourage bats to drink at them. Our study revealed that the presence of artificial lights represented a major characteristic that deterred bats. In particular, we found that only when flood lights from the TCU soccer field were turned off, bat activity was recorded at the TCU retention pond. This result confirmed that not all water sources are readily accessible and available to bats, but turning lights off when they are not needed could effectively improve water availability for bats. It is findings such as these that can inform the enrichment of urban environments for bats and, therefore, aid their conservation.

The United States Environmental Protection Agency (US EPA) classifies nearly 28% of assessed rivers and streams in Texas as impaired due to pathogenic bacteria in the water. One such stream is the Village Creek, a tributary of the Trinity River in north-central Texas. Therefore, this study in the Water and Society Lab at TCU aims to monitor Escherichia coli (E. coli) concentration in the Village Creek.

In this ongoing study, we collect water quality samples weekly, incubate them for 24 hours at 35 °C, and then determine the presence or absence and total E. coli count as CFU (colony forming units) using the US EPA-approved Colilert system. E. coli over 126 CFU per 100 mL water sample indicates unsafe levels per the Texas Commission on Environmental Quality and the US EPA. Based on the analysis of 16 samples, the average, minimum, and maximum E. coli counts are 324.4 CFU, 15.5 CFU, and 1620 CFU, respectively. The next important step in this study is to build the statistical relationship of E. coli with different hydro-climatological variables, including streamflow, rainfall, ambient temperature, water temperature, pH, conductivity, and turbidity. The findings of this study will help make water quality and water resources management decisions in the north-central Texas region.

Fort Worth, Texas has become one of the most populated areas in the United States. With a growing influx of commuters on a daily basis, there is no doubt that there will be a large amount of car crashes in the city. According to the Texas Department of Transportation, in 2020 there were over 15,000 car crashes while in 2021 there were over 17,000 car accidents. In 2022 alone there have been over 3000 car crashes already. Many of these car crashes are likely avoidable and finding the areas that are most susceptible to these accidents will be valuable knowledge for drivers and the city. Applying ESRI ArcGIS Pro’s spatial analysis extension to the Texas Department of Transportation's car accident the roads of Fort Worth with high crash and fatality rates will be found and mapped accordingly.