Fall 2026 Friday Faculty Seminar

Hitaishi Vatsal Desai · Declining Seedling Recruitment in the Boreal-Temperate Ecotone

Transitional zones between distinct ecosystems, such as the Boreal-Temperate ecotone (BTE), can be leveraged as natural testing grounds to study the potential effects of global change on ecosystem dynamics. Within these regions, demographic processes such as seedling recruitment (germination, establishment, and early-stage survival) are particularly vulnerable to altered growing conditions. However, seedlings establishing in the understory of intact forests are shielded from external climatic fluctuations due to the tightly regulated microclimates provided by closed forest canopies. As a result, climate-driven shifts in recruitment patterns will likely first be reflected in disturbed forest stands. To study this shift and the role of disturbances in the BTE, my project used the Forest Inventory and Analysis (FIA) data to analyze spatial and temporal trends of seedling recruitment of key boreal and temperate species found in the North American BTE region from 2005 to 2024. Contrary to our initial hypothesis, we show that instead of showing the differential patterns indicative of a disturbance-accelerated climate-induced ecotonal shift, both boreal and temperate species show similar and significant declines in seedling recruitment primarily driven by declines in intact-canopy recruitment, while the effect of damage remains largely stable over time.

Anna Yu · Perceiving bear risks: Incorporating community dynamics into conservation planning

Human risk perception of living alongside large carnivores strongly influences attitudes toward these animals, yet most studies fail to link these perceptions to conservation decision-making. What is sorely missing is the integration of social and community contexts into risk perception assessments, which could enhance predictions of local support for various conservation actions. For Tibetan herders in the Sanjiangyuan region of the Tibetan Plateau, where cultural ties to the land and its wildlife are deeply rooted and community life supports survival, developing a nuanced understanding of human dimensions and community contexts can be the key to addressing the novel challenges of intensified human-bear conflicts posed by recovering and rewilding of Tibetan brown bears (Ursus arctos pruinosus). To investigate how social and community attributes shape herders’ risk perception and collective responses to conflicts, we applied the ICONS model of risk perception and socio-ecological vulnerability theory. Using a quasi-experimental design, we conducted 400 questionnaire surveys across two Sanjiangyuan counties with similar social-ecological contexts but distinct conflict histories. We employed mixed regression models and spatial analysis to examine how norms, shared information effects, and spatial connectedness influence herders’ risk perceptions and vulnerability to bear-related risks, and consequently shape preferences for four types of mitigation strategies. By applying well-established theories to a novel conservation challenge, this study will advance the mechanistic understanding of various human dimensions in a critical socio-ecological system. Findings will provide evidence and context-based insights for decision-makers in Sanjiangyuan and beyond to help develop co-beneficial solutions for both people and wildlife, ultimately creating enabling conditions for sustainable coexistence.

Megan Jones · Dynamic Line Ratings Counteract Transmission Investment Needs Driven by Climate Change

Rising temperatures due to climate change will reduce power system transmission capacity. This reduction will interact with an ongoing shift from static to time-varying transmission rating standards. Previous research has yet to disentangle the effects of changing rating standards and climates on investment decisions. We quantify transmission investment needs for the Western U.S. power system (WECC) through mid-century under climate change and three rating standards: static ratings (SLR), ambient-adjusted ratings (AAR), and dynamic line ratings (DLR). By embedding alternative rating standards and high-resolution future weather data into a generation and transmission expansion model, PyPSA-USA, we find WECC will lose 1-3% of its transmission capacity across potential future climates under static ratings by midcentury, necessitating a 1-5% increase in transmission investment. Adoption of AAR or DLR eliminates most (81-99%) of the adaptation-driven transmission capacity needs, and further reduces aggregate transmission investments (by up to 31%). Additionally, we demonstrate that planning with time-varying ratings does not increase investment variability for individual lines under climate uncertainty relative to planning with static ratings. Our results emphasize the value and practicality of considering alternative rating standards in climate adaptation planning.

Martha Vierra · How Combined Residential Technology Adoption Reshapes Bulk Grid Peak Demand Under Climate Uncertainty

Bulk power grid reliability faces compounding stress from increasingly severe weather events and shifting residential demand profiles driven by the adoption of household electrification and efficiency technologies. The intersection of these changes, in extreme events because of climate change and residential demand because of technology adoptions, presents a dual uncertainty challenge for bulk grid planning. However, existing literature fails to capture the heterogeneous responses of residential technologies and the bulk grid under climate stress as common modeling approaches rely on additive assumptions of technology behavior, only consider technology adoptions individually and in pairs, or do not capture climate uncertainty. We examine how increasing levels of residential heating electrification, building envelope efficiencies, and behind the meter photovoltaic plus energy storage system adoption interact with climate change to drive peak demand. We develop an integrated residential-to-bulk-grid modeling framework coupling a machine learning-based building simulation model with a bulk demand prediction model. Modeling the California Independent System Operator system across five dynamically downscaled climate models spanning 2030–2050, we find that triplet adoption of these technologies produces a peak demand profile (top 100 hours over 20 years of weather data) distinct from any coupled pairing that cannot be recovered by superimposing individual technology effects. County-level synergy analysis confirms that triplet adoption outperforms the additive prediction in 40 of 55 California counties, with stronger effects in hot dry summer climates accounting for up to 19% of peak demand. A variance decomposition reveals that technology adoption pathway dominates peak demand variance overall with an effect size of η² = 0.89, but within the most effective coupled photovoltaic plus energy storage system pathways, climate uncertainty becomes the primary source of variation with 23% climate variation vs. 11% technology variation. These results demonstrate that climate-robust planning is critical for identifying which technology combinations are most effective at reducing peak demand.

Riti Bhandarkar · Beyond the historical record: improving the representation of low-probability extreme weather in power system modeling using climate ensembles

Recent large scale resource adequacy failures, as occurred in California in 2020 from extreme heat and Texas in 2021 from extreme cold, highlight the need for new approaches to resource adequacy (RA) that better capture weather uncertainty. Studies of grid reliability frequently lean on the historical record, which has limited observations of extremes and does not reflect the changing climate, to model weather dependent risks. Consequently, resource adequacy assessments, which focus on rare, 1-in-10 year extremes, are grounded in an incomplete and often inaccurate picture of the weather conditions the system could experience.

Using a high resolution climate ensemble, CESM-HR, we evaluate 2030 resource adequacy for the MISO grid region over 589 distinct weather years, modeling dependencies for load, thermal derates, solar and wind generation, and forced outages. By integrating climate ensembles, which generate many realizations of typical weather conditions for a future year, into power system modeling, we construct a statistically robust and physically realistic representation of weather conditions a system could experience. In our study, we quantify the number of weather years required to obtain an accurate understanding of grid reliability for common reliability metrics like LOLE and EUE and calculate the magnitude of error in limited-sample approaches to RA assessment. Additionally, we assess MISO’s vulnerability to the 1-in-10 year events grid operators currently focus on, as well as lower probability (e.g., 1-in-100 year) extremes that are unprecedented in the historical record.

Olivia David · Intractability in Environmental Justice Policy Conflicts: The Epistemic Politics of Water Shutoffs in Detroit

Drinking water affordability is a policy challenge for many U.S. cities, as utilities must balance social equity with financial solvency. This study examines one instantiation of this challenge—conflict around water shutoffs for non-payment in Detroit—as an intractable environmental justice (EJ) policy issue, positing that its intractability stems from epistemic politics: disagreement over what the problem is and whose knowledge counts. Through qualitative analysis of interviews and policy documents, I identify the epistemic frameworks underlying actors’ arguments and strategies. I find that political actor groups hold different conceptions of the problem itself and imagined solutions to their version of the problem: non-payment as irresponsibility, requiring enforcement through shutoffs, versus as a product of historic and systemic inequality. Epistemic politics unfold through actors’ uses of not only technical expertise, but also moral claims. I argue that moral authority is an epistemic resource itself, and that racial and epistemic justice are co-constituted. My analysis suggests that EJ policy conflicts require local governments to reconfigure policymaking systems to incorporate deliberative processes beyond standard participation procedures, and mechanisms for processing moral claims as legitimate policy decision inputs. Findings offer insights for urban environmental governance and utility sectors more broadly, and how epistemic dynamics intersect with and reinforce racial inequalities.

Berk Duruturk · Sink or Source? What’s Happening Beneath Lake Superior?

Lake Superior is the most pristine and oligotrophic of the Laurentian Great Lakes, yet algal blooms have begun appearing along its coast. It’s well-known with its phosphorus-limited ecosystem, however its sediment may regulate whether nitrogen (N) is removed or recycled to the water column. To determine whether these sediments act as a net N sink or source, we measured N₂, O₂, and nutrient fluxes using continuous-flow core incubations with ¹⁵N-nitrate tracers during ice-free seasons (2021–2023). We compared a deep, oxygenated offshore site (Western Mooring) with a bloom-affected coastal bay (Siskiwit Bay). Denitrification dominated N loss, although sediments periodically exhibited net nitrification. Denitrification appeared carbon-limited rather than P-limited, potentially uncoupling it from nitrification and driving the elevated water-column N:P ratio.

Spencer Checkoway · 45V and Beyond: Mechanisms for Incentivizing Green Hydrogen

Hydrogen has the potential to decarbonize hard-to-electrify sectors of the economy when produced via renewable electrolysis. Within the Inflation Reduction Act, the United States included an emissions-tiered subsidy provision (§45V) for clean hydrogen in an attempt to drive cost parity between electrolysis and the higher emissions incumbent, steam methane reforming. To achieve this goal, the §45V production tax credit (valued up to $3/kg H2) could be seen as having three objectives: 1) be an efficient mechanism for subsidizing a new technology in the market, 2) drive planned electrolysis projects toward using clean electricity, 3) value CO2 high enough to outcompete other H2 production modes on price. This project uses three case studies to evaluate how effectively and efficiently the §45V tax credit would have performed across the United States had it been rolled out in its legislated form in 2024. Early results show that the §45V production tax credit (PTC) would have been 13-22% as efficient per dollar spent as an equally valued investment tax credit (ITC) and 32-41% as efficient as an electricity tax credit (ETC). At the market value of an electrolyzer, renewable electrolysis would have only outcompeted grid-connected projects in 5-14% of U.S. counties. While the credit itself values carbon between 4-21 times the global average carbon price (depending on the production source), §45V would have to value carbon at over $1,000/tCO2 for renewable electrolysis to remain competitive in a majority of US counties.