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The study introduces an innovative approach utilizing Low-Altitude Unmanned Aerial Vehicle (UAV) imaging to track and forecast wasting disease affecting eelgrass, a crucial coastal ecosystem. Researchers conducted UAV surveys and sampling in intertidal eelgrass beds spanning various locations from Alaska to California. Their developed low-altitude UAV mapping technique aimed to identify disease prevalence, cross-validated against in situ findings.

Results showcased that the green leaf area index, derived from the UAV imagery, served as a robust and significant predictor, inversely correlating with the spatial spread and intensity of wasting disease on the ground, particularly in areas significantly impacted by the disease outbreak. This pioneering methodology demonstrates an efficient, adaptable, and portable means of investigating seagrass disease on a large scale, encompassing diverse geographical regions and environmental conditions.

By employing UAVs equipped with low-altitude autonomous imaging capabilities focusing on visible bands, this research contributes to understanding and predicting wasting disease in eelgrass ecosystems. The study’s significance lies in its ability to offer a comprehensive landscape-level analysis of seagrass disease across different geographic locations. This approach holds promise for monitoring and evaluating the health of eelgrass habitats across coastal regions more effectively. The innovation and efficiency of this methodology underscore its potential to aid in the management and conservation of these critical coastal ecosystems amidst the challenges posed by wasting disease outbreaks.

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