Applications Of An Unmanned Aircraft Vehicle And Remote Cameras For Studying A Sub-Arctic Ecosystem

The midcontinent population of lesser snow geese (Anser caerulescens caerulescens) has increased dramatically since the 1960’s due to changing agricultural practices in their southern wintering areas. The destructive foraging and continued population growth of lesser snow geese has resulted in cascading negative impacts on northern ecosystems. Studying remote sub-Arctic ecosystems is logistically challenging, but the advent of remote sensing technologies (such as drones and remote cameras) may assist ecologists in understanding snow goose ecology. Before these tools can be integrated into snow goose research programs, precursor “proof-of-concept” studies are required to validate tool use. The objectives of this study were to investigate the use of unmanned aircraft systems (hereafter “drones”) and remote cameras for studying various aspects of lesser snow goose ecology within the sub-Arctic ecosystem of the Cape Churchill Peninsula, Manitoba, Canada. We first evaluated impacts of drone surveys on wildlife by measuring drone-induced behavioural responses of nesting lesser snow geese using mini-surveillance cameras. We monitored 25 nests with cameras from 2015-2016, comparing behaviours of birds on days with drone surveys, and on days without surveys. Days with drone surveys resulted in decreased low-vigilance behaviours, and increased high-vigilance behaviours. Similarly, overhead vigilance behaviours increased from a baseline 0.03% of observation time to 0.56% when the drone was overhead, indicating birds were likely observing the drone as it flew overhead. Polar bears (Ursus maritimus) were also monitored via video recording during drone flights in 2016, and they responded in a similar fashion to previously published tourism activity impact estimates (mean vigilance bout lengths during drone surveys = 18.7 ± 2.6 seconds). We estimated goose habitat degradation using photointerpretation of drone imagery and compared estimates to those made with ground-based linear transects. We compared estimates between ground-based transects and those made from unsupervised classification of drone imagery collected at altitudes of 75, 100, and 120 m above ground level (ground sampling distances of 2.4, 3.2, and 3.8 cm respectively). We found large time savings during the data collection step of drone surveys, but these savings were ultimately lost during imagery processing. Based on photointerpretation, overall accuracy of drone imagery was generally high (88.8% to 92.0%) and Kappa coefficients were similar to previously published habitat assessments from drone imagery. Mixed model estimates indicated 75m drone imagery overestimated barren (F2,182 = 100.03, P < 0.0001) and shrub classes (F2,182 = 160.16, P < 0.0001) compared to ground estimates. Inconspicuous graminoid and forb species (non-shrubs) were difficult to detect from drone imagery and were underestimated compared to ground-based transects (F2,182 = 843.77, P < 0.0001). Remote cameras were also used as a remote sensing tool to estimate impacts of Ursid predators on nesting lesser snow geese. From 2013-2018 we deployed 233 remote cameras on goose nests and reviewed images for occurrences of bears and associated avian predators. We recorded the amount of time that female geese spent on and of their nest on days with bears (bear-days), and the day before (control-days). Contrary to predictions, geese spent less total time off-nest on bear-days than control-days (β = -0.32 ± 0.13, P < 0.05). Avian predators were observed more frequently on bear-days (13/18 days) than their paired control-days (2/18 days), and bear presence has a positive effect on avian predator occurrence (β = 3.035 ± 0.916, P < 0.001). We suspect that geese spend more time on-nest in response to bears to defend nests from increased activity of avian predators, and we examined these behaviours using agent-based models. In mixed predator scenarios (bears and avian predators), birds that left their nest early would reduce the probability of nest loss by bears, but had increased risk by avian predators. This work demonstrates that the relationship between nesting geese and bear predators is more complex than commonly depicted, and provides a foundation for future examination of the continued impact of bears on nesting birds. This work demonstrates the value of remote sensing tools for understanding sub-Artic ecosystems and other regions where ecological research is logistically challenging.

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