Aerial Branch Sampling to Detect Forest Pathogens

Diagnostic testing to detect forest pathogens requires the collection of physical samples from affected trees, which can be challenging in remote or rugged environments. As an alternative to traditional ground-based sampling at breast height by field crews, we examined the feasibility of aerially sampling and testing material collected from upper canopy branches using a small unoccupied aerial system (sUAS). The pathogen of interest in this study is Ceratocystis lukuohia, the fungal pathogen responsible for Ceratocystis wilt of ‘ōhi‘a, a vascular wilt disease which has caused widespread mortality to ‘ōhi‘a in native forests across the state of Hawai‘i. To characterize the minimum branch diameter needed to successfully detect the pathogen of interest in infected trees, we tested 63 branch samples (0.8–9.6 cm in diameter) collected from felled trees inoculated with C.lukuohia on Hawai‘i Island. Subsequently, we aerially sampled branches from ten symptomatic ‘ōhi‘a (Metrosideros polymorpha) trees using two different branch sampling systems, the Flying Tree Top Sampler from ETH Zurich and the new Kūkūau branch sampler system introduced in this work, producing 29 branch samples with a maximum diameter of 4.2 cm and length of >2 m. We successfully detected the target fungal pathogen from the collected branches and found that branch diameter, leaf presence and condition, as well as wood moisture content are important factors in pathogen detection in sampled branches. None of the smallest branch samples (those C.lukuohia, while 77% of the largest diameter branch samples (5–10 cm) produced positive results. The Kūkūau branch sampler system is capable of retrieving branches up to 7 cm diameter, providing important capacity for pathogenic research requiring larger diameter samples for successful diagnostic testing. Inconclusive and/or non-detection laboratory results were obtained from sample materials that were either too desiccated or from a branch with asymptomatic leaves, suggesting there is an optimal temporal window for sampling.