The Role of AI in Combating Mistletoe Infestation in Mexican Forests: A Call for Interdisciplinary Action

Mistletoe is a hemiparasitic plant that attaches to host trees, extracting water and nutrients, which weakens the trees, reduces biodiversity, and disrupts critical ecosystem services. While often romanticized in cultural contexts, mistletoe poses a serious ecological threat, particularly in urban and forested ecosystems where infestations can spread unchecked. This article examines the role of artificial intelligence (AI) and remote sensing in addressing the detection and management challenges posed by mistletoe. Through a critical evaluation of methodologies ranging from texture-based machine learning to advanced deep learning models such as ResNet-34, this paper reflects on the successes, limitations, and implications of these approaches. Our interdisciplinary research highlights the transformative potential of combining AI with ecological expertise to develop scalable and efficient tools for conservation. However, we also identify key challenges, including the need for equitable access, ethical considerations, and scalability across diverse ecological contexts. Moreover, we emphasize the importance of engaging the broader community, as misconceptions about mistletoe hinder conservation efforts. By integrating public awareness with technological advancements, we advocate for a balanced and sustainable approach to ecological management. This paper aims to provoke critical dialogue and inspire actionable strategies for leveraging AI in addressing global conservation challenges.