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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Comparing Economic and Physical Measures of Capacity Utilization in Fisheries
(The University of Chicago Press, 2025-10) Walden, John B.; Atwood, Joseph
Measurement of fishing vessel capacity and capacity utilization has garnered substantial interest among economists for many years. Most applied studies adopted an output-oriented capacity definition and used data envelopment analysis to estimate capacity. However, other types of capacity models have also been used to estimate fishing capacity. Examples include the non-convex free disposal hull model, the probabilistic order-M model, and the maximal revenue model. This study compares capacity utilization estimates for a group of 125 vessels using six different capacity models and compares differences in capacity utilization and days needed to fish at capacity. Findings show significant differences in both capacity utilization estimates and days needed to achieve maximum capacity. With multiple models available for generating capacity estimates, analysts should be careful to select appropriate models when estimating fishery-level capacity or determining the presence and/or conditions of over- or undercapacity.
The performance of drones and artificial intelligence for monitoring sage‐grouse at leks
(Wiley, 2025-06) McNew, Lance B.; Hanlon, J.; 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.
Comparative analysis of grape berry microbiota uncovers sour rot associates from a Maryland vineyard
(Public Library of Science, 2025-02) Jumbam, Blaise; Toro, Magaly; Hu, Mengjun
Grape sour rot (GSR) is a disease complex involving fungi and bacteria that can cause significant yield losses of susceptible varieties. It is widely spread in the eastern U.S. and other grape-growing regions globally. Previous studies suggest that damaged fruit skin and feeding insects like Drosophila spp. are required for the disease to occur. Current control strategies for the management of sour rot are not sustainable, and research on the implications of chemical management of the disease on microbiome diversity is scarce. Our aim was to: i) investigate the effect of insecticide application and netting treatment on the microbiota of GSR-susceptible and tolerant grape varieties; and ii) identify the core microbial assemblages potentially associated with grape sour rot development in Maryland. Using a combined analysis of culture-dependent and independent data, we found that microbiota diversity of healthy grape berries did not change with netting, insecticide application, and between varieties. There was a significant difference in bacterial diversity between healthy and sour rot-affected berries. Komagataeibacter was consistently associated with infected berries followed by Acetobacter and Gluconobacter. This is the first study to report the association of Komagataeibacter with GSR-infected berries. It is thus imperative to investigate its role alongside that of other identified core microbiomes in sour rot development. Candida and Pichia were also consistent genera in infected berries. Several unidentified Candida, Pichia, and other fungal species from infected berries formed the core mycobiomes and it would be worth investigating their involvement in GSR development in Mid-Atlantic vineyards.
The effect of soil water content and crop canopy on passive UHF-RFID wireless links
(Elsevier BV, 2025-05) Baumbauer, Carol; Baumbauer, David A.; Arias, Ana C.
High spatial density agricultural sensors that monitor soil fertility and moisture levels are quickly developing and could revolutionize precision agriculture once they are integrated with wireless communication systems. Passive Ultra High Frequency Radio Frequency Identification (UHF-RFID) is a wireless communication protocol for battery-free sensor nodes which could enable continuous soil monitoring. Soil texture, soil water content, and crop canopy impact the vertical read range between a passive RFID tag near the soil and a reader raised above the crop. Here, we evaluated these impacts and found that increases in soil water content decreased read range by 30–40 cm compared to dry soil. Adding 3.4 cm of distance between the wet soil and the tag increased the read range by 1–1.4 m. Crop canopy did not have a significant impact on read range once the soil water content had been accounted for.
Community living causes changes in metabolic behavior and is permitted by specific growth conditions in two bacterial co-culture systems
(American Society for Microbiology, 2025-05) Ellis, Elizabeth et al.; Pinkham, Nick
Although bacteria exist in complex microbial communities in the environment, their features and behavior are most often studied in monoculture. While environmental enrichments or complex co-cultures with tens or hundreds of members might more accurately represent the natural communities of bacteria, we sought to create simple pairs of organisms to learn what conditions create successful co-culture and how bacteria change transcriptionally when a partner species is present. We grew two pairs of organisms in co-culture, Pseudomonas aeruginosa and Escherichia coli and Lacticaseibacillus rhamnosus and Bacteroides thetaiotaomicron. At first, both co-cultures failed, with one organism outcompeting the other. However, through manipulating media and environmental conditions, we created co-cultures with stable member ratios over many generations for each community. We then show that changes in the expression of metabolic genes are present in all studied species, with key catabolic and anabolic pathways often upregulated in the presence of another organism. These changes in gene expression fail to occur in conditions that will not lead to successful co-culture, suggesting they are essential for adapting to and surviving in the presence of others.