Abstract

AbstractThe Grand Portage Band of Lake Superior Chippewa manages for sustainable subsistence harvests of moose (mooz; Alces alces) and white‐tailed deer (waawaashkeshi; Odocoileus virginianus). Moose populations in northern Minnesota, USA, are declining, which may necessitate alterations to Indigenous subsistence practices. Moose and deer exhibit seasonal behaviors such as altered space use and movement strategies, to which gray wolves (ma'iingan; Canis lupus) and humans may adapt, resulting in seasonal mortality patterns. Identifying periods of increased moose and deer vulnerability is important for achieving tribal conservation objectives. We assessed seasonal cause‐specific mortality of adult moose (2010–2021) and deer (2016–2022) fitted with global positioning system collars on and near the Grand Portage Indian Reservation (Gichi Onigaming; GPIR) in Minnesota and hypothesized mortality risk would be influenced by species‐specific space use patterns and weather. We estimated survival rates and mortality risk using time‐to‐event models. We recorded 42 moose mortalities (17 health issues, 8 predations, 4 subsistence harvests, 13 unknown causes) and 49 deer mortalities (26 predations, 13 harvests, 4 other causes, 6 unknown causes). Mean annual moose survival was 83.2%, and mortality risk peaked during late winter (~25 April) and fall (~8 October). Mean annual deer survival was 48.0%, and mortality risk peaked during late winter (~25 March) and during their fall migration period (~11 November). Mortality timing coincided with transitions between space use states (i.e., periods of spatial stability), suggesting ungulates are at greater risk during these transitional periods, though movement strategy (i.e., resident vs. migratory) did not influence mortality risk. Further, increased winter severity corresponded with increased deer mortality. We observed similar temporal peaks in mortality risk when harvest mortalities were censored, suggesting our observed seasonal mortality peaks occur naturally despite harvest comprising most fall deer mortality. Our results can inform population models and harvest regulations by identifying periods of mortality risk on GPIR under Anishinaabe principles of seventh‐generation conservation planning.

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