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Climate is changing rapidly in the Arctic. This has important implications for parasites of Arctic ungulates, and hence for the welfare of Arctic peoples who depend on caribou, reindeer, and muskoxen for food, income, and a focus for cultural activities. In this Opinion article we briefly review recent work on the development of predictive models for the impacts of climate change on helminth parasites and other pathogens of Arctic wildlife, in the hope that such models may eventually allow proactive mitigation and conservation strategies. We describe models that have been developed using the metabolic theory of ecology. The main strength of these models is that they can be easily parameterized using basic information about the physical size of the parasite. Initial results suggest they provide important new insights that are likely to generalize to a range of host–parasite systems. [ABSTRACT FROM AUTHOR]

Arctic ecosystems are changing rapidly in response to climate warming. While Arctic mammals are highly evolved to these extreme environments, particularly with respect to their stress axis, some species may have limited capacity to adapt to this change. We examined changes in key components of the stress axis (cortisol and its carrier protein-corticosteroid binding globulin [CBG]) in polar bears (Ursus maritimus) from western Hudson Bay (N = 300) over a 33 year period (1983-2015) during which time the ice-free period was increasing. Changing sea ice phenology limits spring hunting opportunities and extends the period of onshore fasting. We assessed the response of polar bears to a standardized stressor (helicopter pursuit, darting, and immobilization) during their onshore fasting period (late summer-autumn) and quantified the serum levels of the maximum corticosteroid binding capacity (MCBC) of CBG, the serum protein that binds cortisol strongly, and free cortisol (FC). We quantified bear condition (age, sex, female with cubs or not, fat condition), sea ice (breakup in spring-summer, 1 year lagged freeze-up in autumn), and duration of fasting until sample collection as well as cumulative impacts of the latter environmental traits from the previous year. Data were separated into "good" years (1983-1990) when conditions were thought to be optimal and "poor" years (1991-2015) when sea ice conditions deteriorated and fasting on land was extended. MCBC explained 39.4% of the variation in the good years, but only 28.1% in the poor ones, using both biological and environmental variables. MCBC levels decreased with age. Changes in FC were complex, but more poorly explained. Counterintuitively, MCBC levels increased with increased time onshore, 1 year lag effects, and in poor ice years. We conclude that MCBC is a biomarker of stress in polar bears and that the changes we document are a consequence of climate warming., (© 2020 John Wiley & Sons Ltd.)

Allee effects may render exploited animal populations extinction prone, but empirical data are often lacking to describe the circumstances leading to an Allee effect. Arbitrary assumptions regarding Allee effects could lead to erroneous management decisions so that predictive modelling approaches are needed that identify the circumstances leading to an Allee effect before such a scenario occurs. We present a predictive approach of Allee effects for polar bears where low population densities, an unpredictable habitat and harvest-depleted male populations result in infrequent mating encounters. We develop a mechanistic model for the polar bear mating system that predicts the proportion of fertilized females at the end of the mating season given population density and operational sex ratio. The model is parametrized using pairing data from Lancaster Sound, Canada, and describes the observed pairing dynamics well. Female mating success is shown to be a nonlinear function of the operational sex ratio, so that a sudden and rapid reproductive collapse could occur if males are severely depleted. The operational sex ratio where an Allee effect is expected is dependent on population density. We focus on the prediction of Allee effects in polar bears but our approach is also applicable to other species.