Included in the April 24, 2025, biweekly update 

This week’s articles by MSU faculty, specialists and students making a difference feature juvenile sea lamprey, aquaculture, and an Internet of Things-based disease forecaster.
 

Field and laboratory evaluations of visible light as a cue for guiding downstream-migrating juvenile Sea Lamprey

The corresponding author on this article is Scott Miehls, smiehls@usgs.gov.

Haro et al. (2025) examine whether white light could guide juvenile sea lamprey during downstream migration, both in a natural stream and a controlled flume. This study uses non-physical cues to manipulate lamprey behavior—a smart approach for managing invasive species in sensitive ecosystems.

In the field, the researchers observed that lamprey primarily moved downstream during precipitation-driven flow events when water temperatures ranged from 4°C to 8°C. This suggests that flow spikes may serve as natural triggers of migration. Interestingly, while the juveniles did show some attraction to bank-mounted light arrays, this effect was inconsistent, making light an imperfect yet promising tool.

In the lab, the results were clearer: at moderate water velocities (0.25 and 0.75 m/s), lamprey were nearly three times more likely to approach areas near a linear light source. But at high flow (1.0 m/s), the effect dropped off, suggesting that effective field use of light to guide lamprey may require longer or strategically placed light arrays, especially in faster-flowing or turbulent waters.

Overall, light is not a silver bullet, but it’s a promising, non-lethal addition to integrated sea lamprey control strategies, especially in slower waters.

Haro, A. J., Miehls, S. M., Johnson, N. S., & Wagner, C. M. (2025). “Field and laboratory evaluations of visible light as a cue for guiding downstream-migrating juvenile Sea Lamprey.”Transactions of the American Fisheries Society. https://doi.org/10.1093/tafafs/vnaf008

Opportunities for veterinary engagement to improve aquaculture production and the health of farmed fish in the North Central Region of the United States

The corresponding author on this article is Myron Kebus, kebusmyr@msu.edu.

Kebus et al. (2025) explore fish health challenges and veterinary engagement across aquaculture operations in the U.S. North Central Region (NCR). Through interviews with 24 fish farmers, the researchers find that most veterinary interactions are driven by regulatory fish health inspections, not proactive or preventive care. 

Despite known benefits of veterinary support in terrestrial animal agriculture, only 46% of respondents reported working with fish health professionals. Voluntary health practices—like vaccination, written biosecurity plans, or the use of veterinary feed directives—were rare. Producers commonly cited disease, water quality and limited access to trusted information as top challenges to successfully managing their fish farming operations.

The researchers identify an opportunity for veterinarians and fish health experts to support fish farms by improving diagnostic capacity, providing education, and making better use of existing health resources. Strengthening this connection could enhance fish welfare, reduce losses, and build a more resilient aquaculture industry in the NCR.

Kebus, M., Loch, T. P., Smith, M., & Phelps, N. B. D. (2025). “Opportunities for veterinary engagement to improve aquaculture production and the health of farmed fish in the North Central Region of the United States.” Journal of the American Veterinary Medical Association. Advance online publication. https://doi.org/10.2460/javma.25.01.0037

Development of an Internet of Things (IoT)-based disease forecaster to manage purple spot on asparagus fern

The corresponding author on this article is Younsuk Dong, dongyoun@msu.edu.

Spafford et al. (2025) focus on managing purple spot disease (Stemphylium vesicarium) in asparagus, a pathogen that makes spears unmarketable and causes premature defoliation of the asparagus fern, impacting future yields. To control this foliar disease, fungicides are applied based on disease severity values (DSV), which are influenced by environmental conditions like leaf wetness. These values are generated using disease forecasting systems like TOMCAST (TOMato disease foreCASTing) and weather data.

The researchers compared two systems for determining when to apply fungicides: SpecConnect, a commercially available system, and LOCO-DM, which uses Internet of Things (IoT) sensors. They then assessed the effectiveness of fungicide application at two different DSV thresholds (15 or 20 DSV) or every 10 days.

Results showed that the LOCO-DM system provided more accurate DSV data compared to SpecConnect. All treatments, including those using SpecConnect and LOCO-DM, were more effective in limiting disease progression compared to the non-treated control, indicated by the Area Under Disease Progress Curve (AUDPC) data.

Spafford et al. concluded that IoT-based systems like LOCO-DM can enhance disease forecasting, allowing fungicides to be applied only when the risk of infection is high. This approach not only improves disease control but also reduces fungicide use, lowering costs and environmental impact.

Spafford, J. R., Hausbeck, M. K., Werling, B. P., Tucker, S. F., & Dong, Y. (2025). “Development of an Internet of Things (IoT)-based disease forecaster to manage purple spot on asparagus fern.” Smart Agricultural Technology, 11, 100941. https://doi.org/10.1016/j.atech.2025.100941