ScholarWorks

ScholarWorks is an open access repository for the capture of the intellectual work of Montana State University (MSU) in support of its teaching, research and service missions. MSU ScholarWorks is a central point of discovery for accessing, collecting, sharing, preserving, and distributing knowledge to the Montana State University community and the world.

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Scholarship & Research

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The Sound in the NIght
(Montana State University, 2026)
Johnson, K.E.
A poem that reflects an unfortunate childhood memory.
Review of Platform Power and Libraries. Edited by Christine F. Smith. Library Juice Press, 2025. 151 pp.
(Duke University Press, 2026)
Mannheimer, Sara
Think back to your first music collection. Did you have a shelf of vinyl? Mixtapes shared by friends? CDs borrowed from your library? At the end of each year, when Spotify Wrapped presents each user with an analysis of their listening behavior, I encounter a flurry of social media posts sharing the year's statistics. In 2025, Spotify informed us of our “listening age.” Maybe it was fifty-nine (“You were into music from the early ’80s. You're an old soul”), or maybe it was eighteen (“You were into music from the early 2020s. Your taste is trending”). Of course, I love sharing music with friends. But what lies beneath the glossy veneer of the Wrapped feature? Spotify dominates the streaming market, controls access to our entire music library, tracks the minutiae of our behaviors, and algorithmically recommends music, creating an echo chamber that further entrenches our “listening age”—all while charging us a monthly fee.
Sharing (or Not Sharing) Sensitive Data
(Association of College and Research Libraries, 2026-10)
Mannheimer, Sara
;
Bayrd, Venice
Recent years have seen the rise of initiatives to share research data openly to facilitate research transparency and reproducibility and to advance and accelerate scientific discovery. However, not all research data should be made openly available. In this chapter, we examine sensitive data from the perspective of data curators. We provide an overview of sensitive data and discuss strategies that can enable sensitive data sharing or facilitate transparency when data cannot be shared. To illustrate the complexities of sensitive data, we provide an example of a form of data that may be less commonly recognized as sensitive—research data on water quality from private wells in Montana. We conclude the chapter with lessons learned and advocacy for an ethically centered, highly collaborative, interdisciplinary future for open data initiatives.
Drought tolerance assessment of Bambara groundnut (Vigna subterranea L. Verdc) accessions based on morphological and physiological traits
(Elsevier BV, 2025-09)
Kunene, Sithembile
;
Shegro Gerrano, Abe
;
Oduor Odindo, Alfred
Understanding the adaptive responses of Bambara groundnut (Vigna subterranea L. Verdc) under water-limited conditions is vital for improving resilience of this crop in semi-arid agriculture. This study evaluated the growth, yield, physiological, and photochemical responses of 24 Bambara groundnut accessions under drought stress and non-stress conditions. Significant variation (p < 0.05) was observed among accessions for key morphological traits such as leaf length, plant height, and petiole number. Drought stress markedly reduced biomass and seed yield, with Acc 97 and Acc 100 demonstrating superior yield under stress. Physiological responses showed significant declines in photosynthetic rate, stomatal conductance, and chlorophyll fluorescence parameters under drought. However, accessions such as Acc 25, Acc 61, and Acc 87 maintained relatively higher water-use efficiency and photochemical stability, indicating better drought adaptation. Drought indices highlighted Acc 200, Acc 190, and Acc 175 as promising genotypes, combining high yield potential and stress tolerance. Principal component analysis revealed that photosynthetic efficiency and biomass traits predominantly contributed to phenotypic variation under stress. Overall, this study identified genetically diverse and drought-resilient Bambara groundnut accessions with potential for targeted breeding programs aimed at enhancing drought tolerance and securing food production in marginal environments.
The performance of drones and artificial intelligence for monitoring sage‐grouse at leks
(Wiley, 2025-06)
McNew, Lance B.
;
Hanlon, Jason
;
Buzytsky, Ilya
Accurately monitoring sage‐grouse populations is critical for conservation, yet traditional ground‐based visual surveys face challenges in scalability and consistency, prompting the exploration of innovative drone‐based methodologies enhanced by artificial intelligence. We evaluated the effectiveness of drone‐based survey protocols combined with an AI count model relative to traditional ground‐based visual surveys for counting sage‐grouse at leks. Drone‐induced flushing of sage‐grouse from leks occurred in 16% of flight attempts. Point‐of‐interest (POI) flight profiles outperformed linear flight profiles in counting accuracy for both AI and manual methods. POI flights provided more images and a larger field of view, resulting in counts similar to traditional ground‐based visual (GBV) lek surveys, while linear flights consistently produced undercounts. Our custom AI counter (INDECS) yielded counts of sage‐grouse similar to manual counts in POI surveys, but not in linear surveys. When integrated into modified N‐mixture models, drone surveys with POI profiles yielded precise estimates of detection probabilities and abundance for all survey methods that resulted in similar inference to GBV surveys. Our results suggest that AI‐enhanced drone surveys, particularly with POI flight profiles, offer a promising alternative to traditional surveys with reduced bias and improved consistency in sage‐grouse population monitoring.