Nicholas E. Bader

Since the last glacial period, North America has experienced dramatic changes in regional climate, including the collapse of ice sheets and changes in precipitation. We use clumped isotope (∆₄₇) thermometry and carbonate δ¹⁸O measurements of glacial and deglacial pedogenic carbonates from the Palouse Loess to provide constraints on hydroclimate changes in the Pacific Northwest. We also employ analysis of climate model simulations to help us further provide constraints on the hydroclimate changes in the Pacific Northwest. The coldest clumped isotope soil temperatures T(₄₇) (13.5 ± 1.9°C to 17.1 ± 1.7°C) occurred ∼34,000–23,000 years ago. Using a soil‐to‐air temperature transfer function, we estimate Last Glacial Maximum (LGM) mean annual air temperatures of ∼−5.5°C and warmest average monthly temperatures (i.e., mean summer air temperatures) of ∼4.4°C. These data indicate a regional warming of 16.4 ± 2.6°C from the LGM to the modern temperatures of 10.9°C, which was about 2.5–3 times the global average. Proxy data provide locality constraints on the boundary of the cooler anticyclone induced by LGM ice sheets, and the warmer cyclone in the Eastern Pacific Ocean. Climate model analysis suggests regional amplification of temperature anomalies is due to the proximal location of the study area to the Laurentide Ice Sheet margin and the impact of the glacial anticyclone on the region, as well as local albedo. Isotope‐enabled model experiments indicate variations in water δ¹⁸O largely reflect atmospheric circulation changes and enhanced rainout upstream that brings more depleted vapor to the region during the LGM.

Environmental Data-Driven Inquiry and Exploration (EDDIE) modules engage students in analysis of data collected by networks of environmental sensors, which are used to study various natural phenomena, such as nutrient loading, climate change, and stream discharge. We compared two approaches to EDDIE module implementation in an undergraduate time-series analysis course. Course goals were to use high-frequency and long-term environmental datasets to improve quantitative literacy, develop data manipulation and analysis skills, construct scientific knowledge about natural phenomena, highlight the inherent variability in real data, and develop informed views about the nature of science (NOS). In both instructional treatments, students explored data and developed skills through a scaffolded in-class analysis and then solved more complex problems in homework assignments. In Treatment 1, engage and explore lesson phases involved discussion of instructor-prepared plots using the think–pair–share method. Conversely, in Treatment 2's engage and explore lesson phases, students prepared graphs and completed activities in a computer lab, which required more guidance in data manipulation and thus contained less structured discussion of data analysis and interpretation. We administered a pre/postquestionnaire to compare learning gains between the two treatments in quantitative literacy, statistical reasoning, nature-of-science (NOS) understanding, and understanding of seismological concepts. Results indicate that EDDIE modules are sufficiently flexible to be effective in both learning environments. Our results indicate that students reacted similarly to both instructional treatments, suggesting that EDDIE modules are flexible enough platforms to achieve measurable learning gains in a variety of pedagogical environments.