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This paper contributes to the literature on Indigenous health, human dimensions of climate change, and place-based dimensions of health by examining the role of environment for Inuit health in the context of a changing climate. We investigated the relationship between one key element of the environment – sea ice – and diverse aspects of health in an Inuit community in northern Canada, drawing on population health and health geography approaches. We used a case study design and participatory and collaborative approach with the community of Nain in northern Labrador, Canada. Focus groups (n = 2), interviews (n = 22), and participant observation were conducted in 2010–11. We found that an appreciation of place was critical for understanding the full range of health influences of sea ice use for Inuit. Negative physical health impacts were reported on less frequently than positive health benefits of sea ice use, which were predominantly related to mental/emotional, spiritual, social, and cultural health. We found that sea ice means freedom for sea ice users, which we suggest influences individual and collective health through relationships between sea ice use, culture, knowledge, and autonomy. While sea ice users reported increases in negative physical health impacts such as injuries and stress related to changing environmental conditions, we suggest that less tangible climate change impacts related to losses of health benefits and disruptions to place meanings and place attachment may be even more significant. Our findings indicate that climate change is resulting in and compounding existing environmental dispossession for Inuit. They also demonstrate the necessity of considering place meanings, culture, and socio-historical context to assess the complexity of climate change impacts on Indigenous environmental health. [ABSTRACT FROM AUTHOR]

Soil quality models developed for ecodistrict polygons (EDP) and the polygons of the soil landscapes of Canada (SLC) to monitor the concentration of soil organic matter require daily climate data as an important input. The objectives of this paper are (i) to provide a method that interpolates the daily station data onto the 894 SLC polygons and 150 EDP in the province of Alberta, Canada, so that the interpolated data fit not only climate mean but also climate variability, especially for the precipitation field, and hence can be used as realistic climate input to soil quality models and (ii) to understand the variability of the Alberta daily climate, such as precipitation frequency. The procedure interpolates the station data onto a dense network of grid points and then averages the gridpoint values inside polygons. The procedure and results for maximum temperature, minimum temperature, and precipitation are reported in detail. The interpolation uses the observed daily data for the period 1 January 1961-31 December 1997 (13 514 days) within the latitude-longitude box (45°-64°N, 116°-124°W). Because the precipitation field can have a short spatial correlation length scale and large variability, a hybrid of the methods of inverse-distance weight and nearest-station assignment is developed for interpolating the precipitation data. This method can reliably calculate not only the number of precipitation days per month, but also the precipitation amount for a day. The temperature field has a long spatial correlation scale, and its data are interpolated by the inverse-distance-weight method. Cross-validation shows that the interpolated results on polygons are accurate and appropriate for soil quality models. The computing algorithm uses all the daily observed climate data; despite that, some stations have a very short time record or only summer records. [ABSTRACT FROM AUTHOR]