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Inventory of Freshwater Snails in the Upper Delaware River
No full textThe Delaware River, spanning four states in the Northeast, supports diverse ecosystems essential for millions of people and a multitude of wildlife species. Despite their significant ecological roles as predators, prey, and nutrient cyclers, freshwater snails have been largely overlooked in research, often not identified to the species level. In order to understand the needs of the community (conservation, impact of invasive species, etc.), the dynamics of the community must first be identified. From July to August of 2022, a 70 mi stretch of the Upper Delaware River, within the boundaries of the Upper Delaware Scenic and Recreation River National Park, was sampled using a kick net and hand sampling techniques at 30 locations (100m reach for each location). In 2022, over 10,000 snails from eight families were found. During this field season, it became evident that there were major taxonomic issues related to identification of invasive species, namely the Chinese and Japanese mysterysnails, Cipangopaludina chinensis and Cipangopaludina japonica. Tissue barcoding is complete, but data analysis is still ongoing, especially in regards to the 2023 field season. This research underscores the critical role of freshwater snails in Delaware River ecosystems and emphasizes the urgency of addressing taxonomic challenges, especially concerning invasive species management
Galatea Erupted (2024)
Get PDFhttps://digitalcommons.oberlin.edu/productions_2023-2024/1000/thumbnail.jp
Measuring Social Dimensions of Sustainability at the Community Level: An Illustrative but Cautionary Tale
No full textMany communities are working to enhance the sustainability of their physical, economic, and social systems. While economic and physical systems are routinely measured (e.g., money and energy), psychological and behavioral elements of social systems (norms, attitudes, and individual behavior) are seldom tracked. The objective of this research was to evaluate a potentially scalable approach to measure the impact of sustainability initiatives on these variables in a community engaged in holistic sustainability programming. Online survey data were collected in 2012 (N = 155) and 2016 (N = 137), measuring pro-environmental thought and behavior in two towns in Ohio: Oberlin, a community engaged in holistic efforts to enhance environmental sustainability; and a similar community (Berea) used as a control. Survey links were distributed via recruitment letters mailed to randomly selected community residents from a purchased mailing list. We used two (town) by two (time) between subjects\u27 ANOVAs to evaluate whether Oberlin saw predicted increases in sustainable thought and behavior from 2012 to 2016, compared to the control community. Despite verifiable participation in and awareness of sustainability programs in Oberlin, our survey results did not provide strong evidence that programs resulted in the desired changes in attitudes, norms, and individual behaviors. Recycling attitudes and LED bulb installation were two exceptions. We conclude that assessing the psychological and behavioral dimensions of sustainability poses particular challenges. We encountered ceiling effects and inadequate statistical power. Possibly, norms and attitudes are not easily influenced even by a holistic community-wide effort
Using deep (machine) learning to forecast US inflation in the COVID-19 era
No full textThe 2021-2022 surge in US inflation was unanticipated by the Survey of Professional Forecasters (SPF) and other macroeconomists and institutions. This study assesses whether nascent deep learning frameworks and methods more accurately project recent core personal consumption expenditures inflation. We create a recurrent neural network (RNN) to forecast long-term inflation, and after training on 60 years of quarterly data, the model outperforms the SPF and projects a spike in inflation similar to that of recent years. We compare the model\u27s performance with and without COVID-19-specific data and discuss some implications of our findings for economic forecasting in global crises
Interpreting life-history traits, seasonal cycles, and coastal climate from an intertidal mussel species: Insights from 9000 years of synthesized stable isotope data
No full textUnderstanding past coastal variability is valuable for contextualizing modern changes in coastal settings, yet existing Holocene paleoceanographic records for the North American Pacific Coast commonly originate from offshore marine sediments and may not represent the dynamic coastal environment. A potential archive of eastern Pacific Coast environmental variability is the intertidal mussel species Mytilus californianus. Archaeologists have collected copious stable isotopic (delta O-18 and delta C-13) data from M. californianus shells to study human history at California\u27s Channel Islands. When analyzed together, these isotopic data provide windows into 9000 years of Holocene isotopic variability and M. californianus life history. Here we synthesize over 6000 delta O-18 and delta C-13 data points from 13 published studies to investigate M. californianus shell isotopic variability across ontogenetic, geographic, seasonal, and millennial scales. Our analyses show that M. californianus may grow and record environmental information more irregularly than expected due to the competing influences of calcification, ontogeny, metabolism, and habitat. Stable isotope profiles with five or more subsamples per shell recorded environmental information ranging from seasonal to millennial scales, depending on the number of shells analyzed and the resolution of isotopic subsampling. Individual shell profiles contained seasonal cycles and an accurate inferred annual temperature range of similar to 5 degrees C, although ontogenetic growth reduction obscured seasonal signals as organisms aged. Collectively, the mussel shell record reflected millennial-scale climate variability and an overall 0.52 parts per thousand depletion in delta O-18(shell) from 8800 BP to the present. The archive also revealed local-scale oceanographic variability in the form of a warmer coastal mainland delta O-18(shell) signal (-0.32 parts per thousand) compared to a cooler offshore islands delta O-18(shell) signal (0.33 parts per thousand). While M. californianus is a promising coastal archive, we emphasize the need for high-resolution subsampling from multiple individuals to disentangle impacts of calcification, metabolism, ontogeny, and habitat and more accurately infer environmental and biological patterns recorded by an intertidal species
Review: Duncan Terrace Piano Destruction Concert: The Landesmans’ Homage to “Spring can really hang you up the most” (art installation)
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How Cooking Emissions Impact Indoor Environments: a focus on triglycerides
No full textThe quality of the air we breathe has significant health implications, and an essential source of indoor air pollution comes from cooking activities. However, the long-term effects of exposure to the particulate matter produced by cooking oils still need to be fully understood. Recent studies have shown that indoor surfaces (e.g., walls, furniture, floors) act as reservoirs that can take up particulate matter from the air, which makes the chemical composition on indoor surfaces a valuable proxy for studying air quality. My research investigates how to derivatize and detect triglycerides commonly found in cooking oils in order to characterize the composition of oil residue on indoor surfaces. Fatty acids from triglycerides were extracted from samples and derivatized into fatty acid methyl esters (FAMEs) via an acid-catalyzed transesterification reaction. This method uses an acetyl chloride reaction at elevated temperatures, followed by a neutralization step. The extracted FAMEs were detected and quantified using gas chromatography-mass spectrometry (GC-MS). Preliminary results focused on successfully developing and optimizing a GC-MS method that allows us to separate and quantify 10 FAMEs, ranging from 15 to 23 carbon atoms in length, that come from triglycerides commonly found in cooking oils. Next, we selected three representative triglycerides, trimyristin, tripalmitin, and tristearin, to test and optimize the derivatization method. Future work includes utilizing cooking oil samples from home kitchens to separate and quantify their composition utilizing our developed GC-MS and derivatization method