An economical Custom-Built drone for assessing whale health

Drones or Unmanned Aerial Vehicles (UAVs) have huge potential to improve the safety and efficiency of sample collection from wild animals under logistically challenging circumstances. Here we present a method for surveying population health that uses UAVs to sample respiratory vapor, 'whale blow,' exhaled by free-swimming humpback whales (Megaptera novaeangliae), and coupled this with amplification and sequencing of respiratory tract microbiota. We developed a low-cost multirotor UAV incorporating a sterile petri dish with a remotely operated 'blow' to sample whale blow with minimal disturbance to the whales. This design addressed several sampling challenges: accessibility; safety; cost, and critically, minimized the collection of atmospheric and seawater microbiota and other potential sources of sample contamination. We collected 59 samples of blow from northward migrating humpback whales off Sydney, Australia and used high throughput sequencing of bacterial ribosomal gene markers to identify putative respiratory tract microbiota. Model-based comparisons with seawater and drone-captured air demonstrated that our system minimized external sources of contamination and successfully captured sufficient material to identify whale blow-specific microbial taxa. Whale-specific taxa included species and genera previously associated with the respiratory tracts or oral cavities of mammals (e.g., Pseudomonas, Clostridia, Cardiobacterium), as well as species previously isolated from dolphin or killer whale blowholes (Corynebacteria, others). Many examples of exogenous marine species were identified, including Tenacibaculum and Psychrobacter spp. that have been associated with the skin microbiota of marine mammals and fish and may include pathogens. This information provides a baseline of respiratory tract microbiota profiles of contemporary whale health. Customized UAVs are a promising new tool for marine megafauna research and may have broad application in cost-effective monit