Looking Without Landing—Using Remote Piloted Aircraft to Monitor Fur Seal Populations Without Disturbance - McIntosh, Rebecca R.; Holmberg, Ross; Dann, Peter (Frontiers in Marine Science, 2018)
Technical advances in monitoring devices, specifically drones, are allowing managers and scientists to obtain quality information on ecosystem health with minimal disturbance to ecosystems and the wildlife they support. Temporal and spatial indicators of ecosystem health, such as population size and/or abundance estimates of marine mammals are the basis for our understanding and prediction of ecosystem change. This is critical for the achievement of conservation goals and sustainable natural resources use. Performing surveys to obtain abundance estimates can be logistically demanding and expensive particularly in offshore marine environments, and can cause significant disturbance to wildlife. These constraints may lead to sub-optimal monitoring programs that reduce the frequency and/or precision of surveys at the cost of data quality and confidence in the resulting analyses. Using Remote Piloted Aircraft (RPA) can be a solution to this challenge. With appropriate testing and ethical consideration; for many situations, RPAs can perform surveys with increased frequency, higher data resolution and less disturbance than typical methods that involve people being present on the ground, thereby enabling more robust programs for monitoring. We demonstrate the process of testing images from RPAs for estimating the abundance of Australian fur seals (Arctocephalus pusillus doriferus) at one of their largest colonies on Seal Rocks, Australia. Two sizes of multirotor (1,400 and 350 mm) with different imaging equipment were tested at 40, 60, and 80 m altitude above sea level. We assessed wildlife disturbance levels and optimized a methodology for effective and economical monitoring of this site. We employed commercially available and open-source software for programming survey flights (Drone Deploy), image processing (Agisoft Photoscan and Autopano Giga), data collation and analyses (R and Python). An online portal “SealSpotter” was developed to facilitate data collection, with the ultimate goal being the engagement of the public as citizen scientists in fur seal counts from RPA images. Preliminary comparisons show that a small RPA at 40 m altitude can produce pup counts 20–32% higher than corresponding ground counts without observable disturbance. The benefits and disadvantages of the RPA trials are discussed, as well as important considerations for those looking to incorporate similar methodologies in their research.