Artificial Intelligence in Forest Pathology: Opportunities and Challenges

Forest diseases threaten tree health, biodiversity, and ecosystem services, with impacts amplified by climate change and global trade. Understanding and managing these threats is difficult due to the longevity of trees, the size and inaccessibility of forests, and the often cryptic or delayed expression of symptoms. This review first introduces the field of forest pathology and the key challenges it faces, including multifactorial declines, root and vascular diseases, and emerging invasive pathogens. We then examine how artificial intelligence (AI) can be applied to biotic, abiotic, and decline-related diseases, integrating remote sensing, imaging, genomics, and ecological data across spatial and temporal scales. Lessons from agricultural systems are discussed, highlighting potential tools and pitfalls for forestry. Finally, we outline future directions, emphasizing the need for interpretable models, incorporation of ecological context, cross-species validation, and coordinated data infrastructures to ensure AI delivers actionable, scalable solutions for complex forest ecosystems.