Migration tracking assists harvest management of overabundant Canada geese in Manitoba, Canada

Similar to other jurisdictions across North America, populations of temperate-nesting giant Canada geese (Branta canadensis maxima) have increased to unprecedented levels in Manitoba, Canada, causing extensive damage to crops and property, posing risks to human safety, and mostly avoiding mortality risk from fall hunting seasons. As a result, this population in southern Manitoba was declared overabundant in 2019, through an amendment to the Canada Migratory Birds Regulations. Management authorities sought to increase harvest rates by introducing an additional hunting period in spring, or conservation season, wherein harvest could be concentrated on this population. An important consideration was the need to avoid additional harvest on non-target populations that do not meet the criteria to be classified as overabundant, specifically, sub-arctic nesting Canada geese (Branta canadensis interior) and mid-continent cackling geese (Branta hutchinsii hutchinsii). To investigate differences in migration timing of populations, and ultimately determine start and closure dates for the spring conservation season, we deployed light-level geolocators on adult females of each population between 2016 and 2018. We used Bayesian approaches to derive locations from light-level data and generalized linear mixed models to investigate potential differences in timing of international border crossing among goose populations. Migration data confirmed that movement of these populations overlapped extensively in fall, but in spring, a narrow period existed where mainly the target population was present. Our findings provide the basis for decisions about timing of spring conservation seasons for overabundant temperate-nesting Canada geese in Manitoba, the first season of its kind for this population in North America. Additionally, our work represents the first large-scale use of light-level geolocator technology for assisting with waterfowl harvest management decisions.